diff --git a/.github/workflows/codetools.yml b/.github/workflows/codetools.yml new file mode 100644 index 00000000..7027fec2 --- /dev/null +++ b/.github/workflows/codetools.yml @@ -0,0 +1,46 @@ +name: ci + +on: [push, pull_request] + +env: + PACKAGE: virtual_ship + TESTS: tests + +jobs: + codetools: + runs-on: ubuntu-20.04 + strategy: + matrix: + python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"] + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5.1.0 + with: + python-version: ${{ matrix.python-version }} + - name: install + run: pip install ".[dev]" + - name: flake8 + run: flake8 ./$PACKAGE ./$TESTS + - name: pydocstyle + run: pydocstyle ./$PACKAGE + - name: sort-all + run: | + find ./$PACKAGE -type f -name '__init__.py' -print0 | xargs -0 sort-all + [[ -z $(git status -s) ]] + git checkout -- . + - name: black + run: black --diff --check ./$PACKAGE ./$TESTS + - name: isort + run: isort --check-only --diff ./$PACKAGE ./$TESTS + + tests: + runs-on: ubuntu-20.04 + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5.1.0 + with: + python-version: 3.12 + - name: install + run: pip install ".[dev]" + - name: run_tests + run: pytest --cov=virtual_ship tests diff --git a/.gitignore b/.gitignore index 353469da..924a28fe 100644 --- a/.gitignore +++ b/.gitignore @@ -169,3 +169,8 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ + +# Auto generated by setuptools scm +virtual_ship/_version_setup.py + +.vscode/ diff --git a/Sail_the_ship.ipynb b/Sail_the_ship.ipynb deleted file mode 100644 index a06f638d..00000000 --- a/Sail_the_ship.ipynb +++ /dev/null @@ -1,143 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "https://www.youtube.com/watch?v=G82kIgc1imk\n", - "\n", - "\n", - "\n", - "### Time has come to start your expedition!\n", - "Make sure your datafiles, the JSON file and this file are all in the same folder.\n", - "\n", - "It might take up to an hour to gather the data depending on your choices, make sure your computer doesn't fall asleep while running the cells/script below.\n", - "\n", - "Meanwhile read up on some of the onboard safety procedures and browse through blogs and cruise reports if you want. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Download the latest version of the virtual ship and the bathymetry file\n", - "import requests \n", - "\n", - "files = {\n", - " \"GLO-MFC_001_024_mask_bathy.nc\":\"https://surfdrive.surf.nl/files/index.php/s/AdbtlgP3LJv6tOn/download\",\n", - " \"virtualship.py\":\"https://raw.githubusercontent.com/OceanParcels/Virtual_ship_classroom/main/virtualship.py\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - "\n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)\n", - "print('Download ready')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Sail the virtual ship!\n", - "%run virtualship.py" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Welcome aboard\n", - "\n", - "Welcome aboard, oceanography students, to our scientific research vessel! We're thrilled to have you join us for this exciting 3-week journey into the depths of the ocean. As we embark on this voyage of exploration and discovery, there are a few things I'd like to share with you to ensure a smooth and enriching experience:\n", - "\n", - "**Introduction to the Vessel:** Take some time to familiarize yourselves with the layout of the ship. Get to know key areas such as the laboratories, living quarters, dining area, and deck spaces. \n", - "\n", - "**Daily Routine:** Life on a research vessel follows a structured daily routine. We'll have designated times for meals, research activities, data analysis, and downtime. It's important to maintain this routine to ensure that our work is conducted efficiently and that everyone onboard has the opportunity to rest and recharge.\n", - "\n", - "**Safety Orientation:** Safety is our top priority. As we set sail, we'll conduct a comprehensive safety orientation. This will cover important topics such as emergency procedures, the location of safety equipment, and proper use of personal protective gear. Please pay close attention during this orientation to ensure your safety and the safety of others on board.\n", - "\n", - "**Respect for the Environment:** As we explore the ocean, it's essential to maintain a deep respect for the marine environment. We'll adhere to strict environmental protocols to minimize our impact on marine ecosystems and wildlife. Remember to dispose of waste properly and avoid disturbing marine life whenever possible.\n", - "\n", - "**Teamwork and Collaboration:** Oceanographic research is a collaborative effort that requires teamwork and cooperation. You'll be working closely with your fellow students. Embrace the opportunity to learn from each other and support one another throughout the journey.\n", - "\n", - "![Ship layout](https://ceoas.oregonstate.edu/sites/ceoas.oregonstate.edu/files/ship_design_bw_1400x500.jpg)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "\n", - "### Emergency procedures\n", - "\n", - "Before going on any research expedition you need follow a one day Safety at Sea course and get a medical check-up.\n", - "\n", - "Of course this is not needed for your virtual fieldwork, but I like to draw for your attention to the following on-board emergency procedures.\n", - "\n", - "**Safety Drills:** We conduct regular safety drills to ensure that everyone on board is well-prepared in case of an emergency. Specifically, fire and boat drills are held once a week. These drills are not just routine; they are essential survival training and should be taken seriously. To minimize disruption to the research program, science party members are usually notified in advance of the scheduled drills. In the event that you must continue working during a drill, prior arrangements can be made through the Chief Scientist.\n", - "\n", - "**Emergency Signal:** In the event of an emergency signal, your immediate action is crucial. Don life jackets, put on long-sleeved garments, and wear a hat or head covering if available. Then, proceed to the designated station indicated on the station card located next to your bunk.\n", - "\n", - "**On-Call Readiness:** Please keep in mind that while on board the ship, you may be called upon without warning to assist during your off-watch periods. Emergencies can happen at any time, and your readiness to respond promptly and efficiently is essential to the safety of all aboard.\n", - "\n", - "**Boat Drill (Abandon Ship):** The signal for abandon ship is seven or more short blasts followed by one long blast of the ship’s whistle and general alarm. When this signal is heard, report to your designated life raft station. There the Mate in charge will explain the procedures for launching and embarking into the life rafts. The rafts will not be launched during a drill.\n", - "\n", - "**Fire and Emergency Drills:** The signal is one long blast on the ship’s whistle and general alarm bell, lasting for ten seconds or more. During this drill, members of the science party muster in the designated area. Attendance will be taken and reported to the bridge.\n", - "\n", - "**Man Overboard:** If someone falls overboard, throw a life-ring into the water towards the person. Keep your eye on the person at all times and point towards the person. Shout “MAN OVERBOARD, STARBOARD (or PORT),” and call the bridge on the sound powered phone or squawk box to inform them without losing sight of the person if possible. If you hear someone hail \"Man Overboard,\" pass the word to the bridge." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Reporting\n", - "Reporting your journey is an essential aspect of our oceanographic research expedition. It allows us to share our experiences, communicate our findings, and contribute to the broader scientific community. After each scientific expedition a cruise reports needs to be written. \n", - "You can find many cruise reports online, e.g. https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/pe358.pdf and blogs from many different cruises, e.g. https://www.nioz.nl/en/blog/topic/1027. \n", - "\n", - "Reporting our journey allows us to validate the data collected during our research activities. It provides context for our findings and helps ensure that our results are accurately interpreted and understood. Detailed reports enable us to cross-reference our observations with environmental conditions, sampling locations, and other relevant factors, enhancing the reliability and credibility of our data. Our reports also serve as valuable educational resources for students, educators, and the general public. They provide insights into the process of scientific inquiry, the challenges of conducting research at sea, and the significance of oceanographic discoveries. \n", - "\n", - "I look forward to seeing the impact of your collective efforts during the presentations on March 22nd!\n", - "\n", - "Please don't worry if your results are insufficient to answer your research question. Share your failure and things you would do different a next time instead!\n", - "\n", - "E.g. Normalizing failure: when things go wrong in participatory marine social science fieldwork. https://academic.oup.com/icesjms/article/79/8/2184/6705562 \n", - "\n", - "E.g. Emotions and failure in academic life: Normalising the experience and building resilience. https://www.cambridge.org/core/journals/journal-of-management-and-organization/article/emotions-and-failure-in-academic-life-normalising-the-experience-and-building-resilience/91FD71A50A32404D8EDFFB7886FF3521\n", - "\n", - "![Our ocean provides](https://seewhatgrows.org/wp-content/uploads/2019/06/our-ocean.jpg)\n", - "![10 ways to help our ocean](https://oceanservice.noaa.gov/ocean/help-ocean.jpg)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/codetools.sh b/codetools.sh new file mode 100755 index 00000000..8e0a4acc --- /dev/null +++ b/codetools.sh @@ -0,0 +1,39 @@ +#!/bin/sh + +# Runs all codetools and attempts to apply fixes wherever possible. +# Not suitable for the CI as that should not make any changes. + +set -e + +# Set working directory to the directory of this script. +cd "$(dirname "$0")" + +PACKAGE=virtual_ship +TESTS=tests + +echo "--------------" +echo "flake8" +echo "--------------" +flake8 ./$PACKAGE ./$TESTS +# darglint is ran as a plugin for flake8. + +echo "--------------" +echo "pydocstyle" +echo "--------------" +pydocstyle ./$PACKAGE ./$TESTS + +echo "--------------" +echo "sort-all" +echo "--------------" +find ./$PACKAGE -type f -name '__init__.py' -print0 | xargs -0 sort-all + +echo "--------------" +echo "black" +echo "--------------" +black ./$PACKAGE ./$TESTS + +echo "--------------" +echo "isort" +echo "--------------" +isort ./$PACKAGE ./$TESTS + diff --git a/cruise_plan_info.ipynb b/cruise_plan_info.ipynb deleted file mode 100644 index 9811773d..00000000 --- a/cruise_plan_info.ipynb +++ /dev/null @@ -1,322 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Additional information for creating a cruiseplan \n", - "Run the cell below to download required data and scripts" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import json \n", - "import os \n", - "import requests \n", - "\n", - "files = {\n", - " \"GLO-MFC_001_024_mask_bathy.nc\":\"https://surfdrive.surf.nl/files/index.php/s/AdbtlgP3LJv6tOn/download\",\n", - " \"virtualship.py\":\"https://raw.githubusercontent.com/OceanParcels/Virtual_ship_classroom/main/virtualship.py\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - "\n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)\n", - "print('Download ready')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Check your JSON file:\n", - "After you filled in your cruise proposal template and your JSON file, please run the following cell to check the input and correct your JSON file if necessary: " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "from virtualship import VirtualShipConfiguration\n", - "config = VirtualShipConfiguration('student_input.json') \n", - "plt.scatter(*zip(*config.route_coordinates), c=list(range(len(config.route_coordinates))), cmap='copper')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Ship cruising speed\n", - "\n", - "The cruising speed of the research vessel (i.e. the max speed between two locations without performing operations) is 10 knots. A knot is a unit of speed, equal to one nautical mile per hour. Something traveling at one knot is going about 1.151 land miles per hour. 10 knots = 18.52 kilometers per hour. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Cruise map\n", - "\n", - "A possible way to create a list of coordinates and/or map of your cruise is to use an interactive leafmap. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import leafmap \n", - "from ipyleaflet import Rectangle \n", - " \n", - "m = leafmap.leafmap.Map(center=(0, -100), zoom=5) \n", - "# Draw a rectange to indicate region where data will be collected \n", - "North = 64\n", - "East = -23\n", - "South = 59\n", - "West = -43\n", - "m.add_layer(Rectangle(bounds=((North, West), (South, East)))) \n", - "# Add a point at port of departure: Puntarenas, Costa Rica \n", - "m.add_marker([9.97625, -84.83836]) \n", - "m " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can use the feature “Draw a polyline” (5th symbol from the top) to assemble a list of coordinates. Each point you click will show up as a white square and can be given as output. The blue lines can be used as transects. Double click the last point to finish the line (or click Finish). Create your output with: " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "line = m.user_rois \n", - "coords = line.get('features')[0].get('geometry').get('coordinates') \n", - "print(coords) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Total cruise time \n", - "\n", - "To estimate the cruise time, you’ll need to divide the travelled distance by the cruise speed. To calculate the distance between 2 geographic coordinates you can use the haversine function (https://community.esri.com/t5/coordinate-reference-systems-blog/distance-on-a-sphere-the-haversine-formula/ba-p/902128) or an existing python package, for example geopy (https://geopy.readthedocs.io/en/stable/#module-geopy.distance) or haversine (https://pypi.org/project/haversine/) " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from geopy import distance\n", - "newport_ri = (41.49008, -71.312796)\n", - "cleveland_oh = (41.499498, -81.695391)\n", - "print(distance.great_circle(newport_ri, cleveland_oh).nautical)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Depth sampling \n", - "\n", - "A possible way to investigate the depth where you’ll be sampling is to use the bathymetry data that the virtual ship will also use.\n", - "\n", - "An example for plotting and querying is given below." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt \n", - "import cartopy.crs as ccrs \n", - "import xarray as xr \n", - " \n", - "# Load the bathymetry data using xarray \n", - "data = xr.open_dataset('GLO-MFC_001_024_mask_bathy.nc') \n", - "# Create a bathymetry figure and axis with Cartopy projection \n", - "fig, ax = plt.subplots(figsize=(15, 5), subplot_kw={'projection': ccrs.PlateCarree()}) \n", - "data.deptho.plot(ax=ax, cmap='viridis') \n", - "# Specify extent, add gridlines and coastlines, show plot \n", - "ax.set_extent((130,160,-70,-40), crs=ccrs.PlateCarree()) \n", - "ax.gridlines(draw_labels=True) \n", - "ax.coastlines() \n", - "plt.show() \n", - "# Query and print the bathymetry data at the specified location \n", - "station_depth = data.deptho.sel(latitude=-50, longitude=150, method='nearest') \n", - "print(station_depth.values) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Measurement options \n", - "\n", - "### Underway data \n", - "\n", - "Underway data collection, also known as underway sampling, refers to the process of collecting oceanographic and environmental data while a research vessel is in motion. This method allows scientists to continuously gather data on various parameters such as sea surface temperature and salinity. The water inlet is located onthe hull of the ship at approximately 2 meters under the surface. \n", - "\n", - "You can collect underway data during your entire cruise and may assume it doesn’t take any time to start or stop taking measurements. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### CTD \n", - "\n", - "A Conductivity, Temperature, and Depth (CTD) sensor is an instrument used to measure the physical properties of seawater in oceanographic and environmental research. It typically consists of sensors for conductivity, temperature, and pressure (which is used to derive depth). \n", - "\n", - "Throughout a CTD deployment, the research vessels needs to stay in the same location. To calculate the time needed for a CTD deployment, take the following information into account: \n", - "\n", - "Add time to lower the vessels speed to zero and set the vessel to the appropriate direction against swell, current, wind, etc = 10 minutes \n", - "Add time to deploy the CTD, and to recover = 10 minutes (2*5 min) \n", - "Add time for the way down and up, usually at 1 m/s (winch capacity) = twice your water depth (in seconds) \n", - "\n", - "https://youtu.be/7N2UsPDczTw?feature=shared \n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ADCP \n", - "\n", - "An Acoustic Doppler Current Profiler (ADCP) is an instrument used to measure the speed and direction of ocean currents at various depths. It operates based on the principle of Doppler shift, where sound waves emitted by the instrument are reflected off moving particles in the water, such as plankton or sediment, and the frequency shift of the returning waves is used to calculate the velocity of the water. \n", - "\n", - "You can deploy the ADCP on transects and choose between a shallow profiler capable of providing information to a depth of 150 m every 4 meters (the 300kHz seaSeven), or a long-range profiler capable of providing about 1000m of range every 24 meters (the 38kHz Ocean Observer). You may assume it doesn’t take any time to start or end ADCP measurements. \n", - "\n", - "https://youtu.be/mDyoZagght8?feature=shared&t=38 \n", - "\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Drifters \n", - "\n", - "A surface drifter is an oceanographic instrument used to study surface currents and ocean circulation patterns. These devices are designed to drift passively with the surface currents while transmitting data on their position and temperature. \n", - "\n", - "You may assume it doesn’t take any time to deploy drifters. \n", - "\n", - "https://youtu.be/3m_CxEE8Bhs?feature=shared&t=15 \n", - "\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Argo floats \n", - "\n", - "Argo floats are self-contained, battery-powered instruments equipped with sensors to measure temperature and salinity profiles from the surface down to depths of up to 2000 meters or more. These sensors provide high-resolution vertical profiles of ocean properties, allowing researchers to study ocean variability and climate change. \n", - "\n", - "The floats periodically descend to a predetermined depth, typically around 1000 meters, and then ascend to the surface, measuring temperature and salinity profiles along the way. In tutorial 2, you learn how to control the dive depth and duration. \n", - "\n", - "You may assume it doesn’t take any time to deploy Argo floats. \n", - "\n", - "https://youtu.be/IgcYQML5se4?feature=shared \n", - "\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Additional information \n", - "\n", - " \n", - "\n", - "Things not to worry about on your virtual cruise, but which are important when planning an actual cruise: \n", - "\n", - " \n", - "\n", - "### Planning \n", - "\n", - "Preparing for a seagoing expedition involves many months (often years) of planning. There are many forms and documents to prepare; there are many criteria to be met and logistical issues to sort out; there are even issues of personal preparation. The most successful research cruises are typically the ones that are planned early, with an awareness of both the big picture and the fine details. Research ships are often fully booked over a year in advance. Collaborative planning ensures that cruises in neighboring regions are scheduled together to minimize transit time. To gain insights into the schedules of various European research ships, you can e.g. refer to https://www.marinefacilitiesplanning.com/programme. \n", - "\n", - " \n", - "\n", - "### Diplomatic clearance \n", - "\n", - "If the cruise includes data collection and/or sampling in other countries exclusive economic zones (EEZ) the cruise leader must seek permission through diplomatic channels ref UNCLOS (United Nations Convention of the Laws Of the Seas) Part XIII Marine Scientific Research. Normal processing time is at least 3 to 6 months. This is especially important when sampling on or below the seafloor, trawling, and collecting high resolution bathymetric data. \n", - "\n", - " \n", - "\n", - "### Polar code \n", - "\n", - "Research vessels have different polar capabilities and it therefore varies in which areas they can operate at different times of the year, depending on ice conditions and minimum allowed air temperature. \n", - "\n", - " \n", - "\n", - "### Crew shifts \n", - "\n", - "Many research vessels operate on a watch system, where crew members are divided into teams (watches) that take turns being responsible for the vessel's operations. This ensures that the vessel is staffed 24 hours a day, allowing for continuous data collection and monitoring. Traditional watch schedules include the “12-on, 12-off\", “4-on, 8-off\" or \"6-on, 6-off\" rotation, where crew members work for a set number of hours (e.g., 4 or 6 hours) and then have a set amount of time off duty. This rotation continues throughout the day and night. Depending on the requirements of the research mission, modified watch schedules may be implemented. \n", - "\n", - " \n", - "\n", - "### Logistics (transportation, customs, intermediate storage) \n", - "\n", - "All equipment required at sea needs to be transferred to the port of departure before leaving. Consider these issues on how to prepare and pack your equipment in the office: \n", - "\n", - "Create a comprehensive checklist of all the equipment you'll need for your research. This includes scientific instruments, sampling tools, safety gear, and any other materials essential to your work. \n", - "Clean and calibrate your instruments as needed. Ensure that sensors are functioning properly, batteries are charged, and any necessary software is updated. Make note of any items that may require special handling or storage. \n", - "Organize your equipment in a systematic manner. Group items together based on their function or use. Clearly label each item with its name, purpose, and any specific instructions for handling or setup. \n", - "Fit your equipment in the 20-foot container. The container will be sent to your port of departure ahead of time with a cargo boat, so make sure you are packed in time for this transfer. Remember there are no shops at sea, so think carefully and plan ahead. \n", - "You are responsible for ensuring the equipment is loaded or unloaded from the vessel. You should plan to have a responsible person at the port stop for loading or unloading your equipment. Please do not assume the crew will take care of this for you. \n", - "\n", - "![Equipment preparation NIOZ](https://www.nioz.nl/application/files/9116/7500/3457/2023-01-16-packing.jpg) \n", - "\n", - "![Equipment loading](https://www.nioz.nl/application/files/7416/7810/2265/2023-03-06-container-shifting.jpg) " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/datadownload.txt b/datadownload.txt deleted file mode 100644 index c9c095d6..00000000 --- a/datadownload.txt +++ /dev/null @@ -1,48 +0,0 @@ -# # Script/notes to download data from CMEMS - -# https://data.marine.copernicus.eu/product/GLOBAL_ANALYSISFORECAST_PHY_001_024/download?dataset=cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i_202211 - -# 5 to -10 N/S -# -170 to -80 W/E - -# All possible depths - -# Period? - -# files: -# cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i -# cmems_mod_glo_phy-so_anfc_0.083deg_PT6H-i -# cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i -# cmems_mod_glo_phy_anfc_0.083deg_static - -# Copy MOTU command from CMEMS website, e.g. -# python -m motuclient --motu https://nrt.cmems-du.eu/motu-web/Motu --service-id GLOBAL_ANALYSISFORECAST_PHY_001_024-TDS --product-id cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i --longitude-min -160 --longitude-max -80 --latitude-min -10 --latitude-max 5 --date-min '2023-09-25 00:00:00' --date-max '2023-09-27 00:00:00' --depth-min 0.49402499198913574 --depth-max 5727.9169921875 --variable uo --variable vo --out-dir --out-name --user --pwd - -# conda activate cmems # environment with motuclient==1.8.4 installed - -# replace and with your desired output directory and filename -# replace and with your CMEMS credentials (mine are stored in /Users/0448257/Data/copernicus_credentials.txt) -# replace " with ' in the date arguments (doesn't seem to be needed) - -# python -m motuclient --motu https://nrt.cmems-du.eu/motu-web/Motu --service-id GLOBAL_ANALYSISFORECAST_PHY_001_024-TDS --product-id cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i --longitude-min -170 --longitude-max -75 --latitude-min -10 --latitude-max 5 --date-min '2023-11-19 00:00:00' --date-max '2023-11-22 00:00:00' --depth-min 0.49402499198913574 --depth-max 5727.9169921875 --variable uo --variable vo --out-name studentdata_UV_4.nc --user edaniels --pwd Pepertj3$ -# python -m motuclient --motu https://nrt.cmems-du.eu/motu-web/Motu --service-id GLOBAL_ANALYSISFORECAST_PHY_001_024-TDS --product-id cmems_mod_glo_phy-so_anfc_0.083deg_PT6H-i --longitude-min -170 --longitude-max -75 --latitude-min -10 --latitude-max 5 --date-min '2023-11-01 00:00:00' --date-max '2023-11-11 00:00:00' --depth-min 0.49402499198913574 --depth-max 5727.9169921875 --variable so --out-name studentdata_S.nc --user edaniels --pwd Pepertj3$ -# python -m motuclient --motu https://nrt.cmems-du.eu/motu-web/Motu --service-id GLOBAL_ANALYSISFORECAST_PHY_001_024-TDS --product-id cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i --longitude-min -170 --longitude-max -75 --latitude-min -10 --latitude-max 5 --date-min '2023-11-01 00:00:00' --date-max '2023-11-11 00:00:00' --depth-min 0.49402499198913574 --depth-max 5727.9169921875 --variable thetao --out-name studentdata_T.nc --user edaniels --pwd Pepertj3$ - -# New files are available! uo, vo, so, thetao all in one file, hourly resolution? -# cmems_mod_glo_phy_anfc_0.083deg_PT1H-m -# test download: -# python -m motuclient --motu https://nrt.cmems-du.eu/motu-web/Motu --service-id GLOBAL_ANALYSISFORECAST_PHY_001_024-TDS --product-id cmems_mod_glo_phy_anfc_0.083deg_PT1H-m --longitude-min -170 --longitude-max -75 --latitude-min -10 --latitude-max 5 --date-min "2023-10-11 23:30:00" --date-max "2023-10-12 23:30:00" --depth-min 0.49402499198913574 --depth-max 5727.9169921875 --variable so --variable thetao --variable uo --variable vo --out-name studentdata11-21.nc --user edaniels --pwd Pepertj3$ -# unfortunately only available at the surface, no depth yet... - -# Files can be downloaded in sizes up to 2048.0Mb so had to do several downloads -# Op lorenz staat cdo geinstalleerd, dus kan je de files aan elkaar plakken met -# also installed cdo to local cmems environment -# cdo mergetime studentdata_UV_1.nc studentdata_UV_2.nc studentdata_UV_3.nc studentdata_UV.nc - -# TMP, motuclient will be deprecated by Feb 2024 -# python -m motuclient --motu https://nrt.cmems-du.eu/motu-web/Motu --service-id GLOBAL_ANALYSISFORECAST_PHY_001_024-TDS --product-id cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i --longitude-min 152 --longitude-max 157 --latitude-min 36.5 --latitude-max 37 --date-min 2024-01-31T00:00:00 --date-max 2024-02-02T00:00:00 --depth-min 0.49402499198913574 --depth-max 155.85069274902344 --variable uo --variable vo --out-name JapanWindCurrents.nc --user edaniels --pwd Pepertj3$ - -# NEW way to download https://help.marine.copernicus.eu/en/articles/7970514-copernicus-marine-toolbox-installation -conda activate activate cmt_1.0 - -https://help.marine.copernicus.eu/en/articles/7972861-copernicus-marine-toolbox-cli-subset \ No newline at end of file diff --git a/download_data.py b/download_data.py deleted file mode 100644 index af2ee611..00000000 --- a/download_data.py +++ /dev/null @@ -1,90 +0,0 @@ -# Install as in https://help.marine.copernicus.eu/en/articles/7970514-copernicus-marine-toolbox-installation -# test student_input with VirtualshipConfiguration from virtualship.py (different conda env) -# conda activate cmt_1.0 -# run file from commandline with echo -e "\n\n\n\n\n\n\n\n" | python download_data.py - -import os -import json -import copernicusmarine -import datetime -# from virtualship import VirtualShipConfiguration - -class VirtualShipConfiguration: - def __init__(self, json_file): - with open(os.path.join(os.path.dirname(__file__), json_file), 'r') as file: - json_input = json.loads(file.read()) - for key in json_input: - setattr(self, key, json_input[key]) - -if __name__ == '__main__': - config = VirtualShipConfiguration('student_input_groupF.json') - datadir = 'data_groupF' - - download_dict = { - 'UVdata': {'dataset_id': 'cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i', 'variables': ['uo', 'vo'], 'output_filename': "studentdata_UV.nc"}, - 'Sdata': {'dataset_id': 'cmems_mod_glo_phy-so_anfc_0.083deg_PT6H-i', 'variables': ['so'], 'output_filename': "studentdata_S.nc"}, - 'Tdata': {'dataset_id': 'cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i', 'variables': ['thetao'], 'output_filename': "studentdata_T.nc"} - } - - for dataset in download_dict: - copernicusmarine.subset( - dataset_id=download_dict[dataset]['dataset_id'], - variables=download_dict[dataset]['variables'], - minimum_longitude=config.region_of_interest["West"], - maximum_longitude=config.region_of_interest["East"], - minimum_latitude=config.region_of_interest["South"], - maximum_latitude=config.region_of_interest["North"], - start_datetime=config.requested_ship_time["start"], - end_datetime=config.requested_ship_time["end"], - minimum_depth=0.49402499198913574, - maximum_depth=5727.9169921875, - output_filename=download_dict[dataset]['output_filename'], - output_directory=datadir - ) - - - if len(config.drifter_deploylocations) > 0: - - download_dict = { - 'UVdata': {'dataset_id': 'cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i', 'variables': ['uo', 'vo'], 'output_filename': "drifterdata_UV.nc"}, - 'Tdata': {'dataset_id': 'cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i', 'variables': ['thetao'], 'output_filename': "drifterdata_T.nc"} - } - - for dataset in download_dict: - copernicusmarine.subset( - dataset_id=download_dict[dataset]['dataset_id'], - variables=download_dict[dataset]['variables'], - minimum_longitude=config.region_of_interest["West"]-5, - maximum_longitude=config.region_of_interest["East"]+5, - minimum_latitude=config.region_of_interest["South"]-5, - maximum_latitude=config.region_of_interest["North"]+5, - start_datetime=config.requested_ship_time["start"], - end_datetime=f'{datetime.datetime.strptime(config.requested_ship_time["end"],"%Y-%m-%dT%H:%M:%S")+datetime.timedelta(days=21):%Y-%m-%dT%H:%M:%S}', - minimum_depth=0.49402499198913574, - maximum_depth=0.49402499198913574, - output_filename=download_dict[dataset]['output_filename'], - output_directory=datadir - ) - - if len(config.argo_deploylocations) > 0: - download_dict = { - 'UVdata': {'dataset_id': 'cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i', 'variables': ['uo', 'vo'], 'output_filename': "argodata_UV.nc"}, - 'Sdata' : {'dataset_id': 'cmems_mod_glo_phy-so_anfc_0.083deg_PT6H-i', 'variables': ['so'], 'output_filename': "argodata_S.nc"}, - 'Tdata': {'dataset_id': 'cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i', 'variables': ['thetao'], 'output_filename': "argodata_T.nc"} - } - - for dataset in download_dict: - copernicusmarine.subset( - dataset_id=download_dict[dataset]['dataset_id'], - variables=download_dict[dataset]['variables'], - minimum_longitude=config.region_of_interest["West"]-5, - maximum_longitude=config.region_of_interest["East"]+5, - minimum_latitude=config.region_of_interest["South"]-5, - maximum_latitude=config.region_of_interest["North"]+5, - start_datetime=config.requested_ship_time["start"], - end_datetime=f'{datetime.datetime.strptime(config.requested_ship_time["end"],"%Y-%m-%dT%H:%M:%S")+datetime.timedelta(days=21):%Y-%m-%dT%H:%M:%S}', - minimum_depth=0.49402499198913574, - maximum_depth=5727.9169921875, - output_filename=download_dict[dataset]['output_filename'], - output_directory=datadir - ) diff --git a/environment.yml b/environment.yml deleted file mode 100644 index 1c1693a0..00000000 --- a/environment.yml +++ /dev/null @@ -1,361 +0,0 @@ -name: Parcels -channels: - - conda-forge - - defaults -dependencies: - - _libgcc_mutex=0.1=conda_forge - - _openmp_mutex=4.5=2_gnu - - argon2-cffi-bindings=21.2.0=py311hd4cff14_3 - - asttokens=2.2.1=pyhd8ed1ab_0 - - aws-c-auth=0.7.0=hbbaa140_3 - - aws-c-cal=0.6.0=h93469e0_0 - - aws-c-common=0.8.23=hd590300_0 - - aws-c-compression=0.2.17=h862ab75_1 - - aws-c-event-stream=0.3.1=h9599702_1 - - aws-c-http=0.7.11=hbe98c3e_0 - - aws-c-io=0.13.28=h3870b5a_0 - - aws-c-mqtt=0.9.0=h2e270ba_0 - - aws-c-s3=0.3.13=heb0bb06_2 - - aws-c-sdkutils=0.1.12=h862ab75_0 - - aws-checksums=0.1.16=h862ab75_1 - - aws-crt-cpp=0.21.0=h87b6960_2 - - aws-sdk-cpp=1.10.57=h7062fed_18 - - backcall=0.2.0=pyh9f0ad1d_0 - - backports=1.0=pyhd8ed1ab_3 - - backports.functools_lru_cache=1.6.5=pyhd8ed1ab_0 - - binutils_impl_linux-64=2.40=hf600244_0 - - binutils_linux-64=2.40=hbdbef99_1 - - blosc=1.21.4=h0f2a231_0 - - boost-cpp=1.78.0=h6582d0a_3 - - brotli=1.0.9=h166bdaf_9 - - brotli-bin=1.0.9=h166bdaf_9 - - brotli-python=1.0.9=py311ha362b79_9 - - bzip2=1.0.8=h7f98852_4 - - c-ares=1.19.1=hd590300_0 - - ca-certificates=2023.7.22=hbcca054_0 - - cairo=1.16.0=hbbf8b49_1016 - - cartopy=0.21.1=py311hd88b842_1 - - cffi=1.15.1=py311h409f033_3 - - cfitsio=4.2.0=hd9d235c_0 - - cftime=1.6.2=py311h4c7f6c3_1 - - comm=0.1.4=pyhd8ed1ab_0 - - contourpy=1.1.0=py311h9547e67_0 - - curl=8.2.1=hca28451_0 - - cytoolz=0.12.2=py311h459d7ec_0 - - dask-core=2023.8.0=pyhd8ed1ab_0 - - debugpy=1.6.8=py311hb755f60_0 - - decorator=5.1.1=pyhd8ed1ab_0 - - executing=1.2.0=pyhd8ed1ab_0 - - expat=2.5.0=hcb278e6_1 - - fiona=1.9.1=py311hba01205_0 - - font-ttf-dejavu-sans-mono=2.37=hab24e00_0 - - font-ttf-inconsolata=3.000=h77eed37_0 - - font-ttf-source-code-pro=2.038=h77eed37_0 - - font-ttf-ubuntu=0.83=hab24e00_0 - - fontconfig=2.14.2=h14ed4e7_0 - - fonts-conda-ecosystem=1=0 - - fonts-conda-forge=1=0 - - fonttools=4.42.0=py311h459d7ec_0 - - freetype=2.12.1=hca18f0e_1 - - freexl=1.0.6=h166bdaf_1 - - gcc_impl_linux-64=13.1.0=hc4be1a9_0 - - gcc_linux-64=13.1.0=hd2d1137_1 - - gdal=3.6.4=py311h1caf18b_5 - - geopandas-base=0.13.2=pyha770c72_1 - - geos=3.11.2=hcb278e6_0 - - geotiff=1.7.1=h22adcc9_11 - - gettext=0.21.1=h27087fc_0 - - gflags=2.2.2=he1b5a44_1004 - - giflib=5.2.1=h0b41bf4_3 - - glog=0.6.0=h6f12383_0 - - gmp=6.2.1=h58526e2_0 - - hdf4=4.2.15=h501b40f_6 - - hdf5=1.14.1=nompi_h4f84152_100 - - icu=72.1=hcb278e6_0 - - importlib_metadata=6.8.0=hd8ed1ab_0 - - importlib_resources=6.0.1=pyhd8ed1ab_0 - - ipykernel=6.25.1=pyh71e2992_0 - - ipython=8.14.0=pyh41d4057_0 - - ipython_genutils=0.2.0=py_1 - - jedi=0.19.0=pyhd8ed1ab_0 - - json-c=0.16=hc379101_0 - - jupyter_client=8.3.0=pyhd8ed1ab_0 - - jupyter_core=5.3.1=py311h38be061_0 - - jupyter_server=1.23.6=pyhd8ed1ab_0 - - jupyterlab_pygments=0.2.2=pyhd8ed1ab_0 - - jupyterlab_server=2.24.0=pyhd8ed1ab_0 - - jupyterlab_widgets=3.0.8=pyhd8ed1ab_0 - - kealib=1.5.1=h3e6883b_4 - - kernel-headers_linux-64=2.6.32=he073ed8_16 - - keyutils=1.6.1=h166bdaf_0 - - kiwisolver=1.4.4=py311h4dd048b_1 - - krb5=1.21.1=h659d440_0 - - lcms2=2.15=haa2dc70_1 - - ld_impl_linux-64=2.40=h41732ed_0 - - lerc=4.0.0=h27087fc_0 - - libabseil=20230125.3=cxx17_h59595ed_0 - - libaec=1.0.6=hcb278e6_1 - - libarrow=12.0.1=h10ac928_8_cpu - - libblas=3.9.0=17_linux64_openblas - - libbrotlicommon=1.0.9=h166bdaf_9 - - libbrotlidec=1.0.9=h166bdaf_9 - - libbrotlienc=1.0.9=h166bdaf_9 - - libcblas=3.9.0=17_linux64_openblas - - libcrc32c=1.1.2=h9c3ff4c_0 - - libcurl=8.2.1=hca28451_0 - - libdeflate=1.18=h0b41bf4_0 - - libedit=3.1.20191231=he28a2e2_2 - - libev=4.33=h516909a_1 - - libevent=2.1.12=hf998b51_1 - - libexpat=2.5.0=hcb278e6_1 - - libffi=3.4.2=h7f98852_5 - - libgcc-devel_linux-64=13.1.0=he3cc6c4_0 - - libgcc-ng=13.1.0=he5830b7_0 - - libgdal=3.6.4=hd54c316_5 - - libgfortran-ng=13.1.0=h69a702a_0 - - libgfortran5=13.1.0=h15d22d2_0 - - libglib=2.76.4=hebfc3b9_0 - - libgomp=13.1.0=he5830b7_0 - - libgoogle-cloud=2.12.0=h840a212_1 - - libgrpc=1.56.2=h3905398_0 - - libiconv=1.17=h166bdaf_0 - - libjpeg-turbo=2.1.5.1=h0b41bf4_0 - - libkml=1.3.0=h37653c0_1015 - - liblapack=3.9.0=17_linux64_openblas - - libnetcdf=4.9.2=nompi_h7e745eb_109 - - libnghttp2=1.52.0=h61bc06f_0 - - libnsl=2.0.0=h7f98852_0 - - libnuma=2.0.16=h0b41bf4_1 - - libopenblas=0.3.23=pthreads_h80387f5_0 - - libpng=1.6.39=h753d276_0 - - libpq=15.4=hfc447b1_0 - - libprotobuf=4.23.3=hd1fb520_0 - - librttopo=1.1.0=h0d5128d_13 - - libsanitizer=13.1.0=hfd8a6a1_0 - - libsodium=1.0.18=h36c2ea0_1 - - libspatialindex=1.9.3=h9c3ff4c_4 - - libspatialite=5.0.1=hca56755_27 - - libsqlite=3.42.0=h2797004_0 - - libssh2=1.11.0=h0841786_0 - - libstdcxx-ng=13.1.0=hfd8a6a1_0 - - libthrift=0.18.1=h8fd135c_2 - - libtiff=4.5.1=h8b53f26_0 - - libutf8proc=2.8.0=h166bdaf_0 - - libuuid=2.38.1=h0b41bf4_0 - - libuv=1.44.2=hd590300_1 - - libwebp-base=1.3.1=hd590300_0 - - libxcb=1.15=h0b41bf4_0 - - libxml2=2.11.5=h0d562d8_0 - - libzip=1.9.2=hc929e4a_1 - - libzlib=1.2.13=hd590300_5 - - lz4=4.3.2=py311h9f220a4_0 - - lz4-c=1.9.4=hcb278e6_0 - - markupsafe=2.1.3=py311h459d7ec_0 - - matplotlib-base=3.7.2=py311h54ef318_0 - - matplotlib-inline=0.1.6=pyhd8ed1ab_0 - - msgpack-python=1.0.5=py311ha3edf6b_0 - - nbconvert-core=7.7.4=pyhd8ed1ab_0 - - nbconvert-pandoc=7.7.4=pyhd8ed1ab_0 - - ncurses=6.4=hcb278e6_0 - - nest-asyncio=1.5.6=pyhd8ed1ab_0 - - netcdf4=1.6.4=nompi_py311h9a7c333_101 - - nodejs=20.5.1=hf52ce11_0 - - nspr=4.35=h27087fc_0 - - nss=3.92=h1d7d5a4_0 - - numcodecs=0.11.0=py311hcafe171_1 - - numpy=1.25.2=py311h64a7726_0 - - openjpeg=2.5.0=hfec8fc6_2 - - openssl=3.1.2=hd590300_0 - - orc=1.9.0=h385abfd_1 - - pandas=2.0.3=py311h320fe9a_1 - - pandoc=3.1.3=h32600fe_0 - - parcels=2.4.2=py311h38be061_1 - - parso=0.8.3=pyhd8ed1ab_0 - - pcre2=10.40=hc3806b6_0 - - pexpect=4.8.0=pyh1a96a4e_2 - - pickleshare=0.7.5=py_1003 - - pillow=10.0.0=py311h0b84326_0 - - pixman=0.40.0=h36c2ea0_0 - - poppler=23.05.0=hd18248d_1 - - poppler-data=0.4.12=hd8ed1ab_0 - - postgresql=15.4=h8972f4a_0 - - proj=9.2.1=ha643af7_0 - - prometheus_client=0.17.1=pyhd8ed1ab_0 - - prompt-toolkit=3.0.39=pyha770c72_0 - - prompt_toolkit=3.0.39=hd8ed1ab_0 - - psutil=5.9.5=py311h2582759_0 - - pthread-stubs=0.4=h36c2ea0_1001 - - ptyprocess=0.7.0=pyhd3deb0d_0 - - pure_eval=0.2.2=pyhd8ed1ab_0 - - pyarrow=12.0.1=py311h39c9aba_8_cpu - - pygments=2.16.1=pyhd8ed1ab_0 - - pyproj=3.6.0=py311ha169711_1 - - python=3.11.4=hab00c5b_0_cpython - - python-box=7.0.1=py311h2582759_0 - - python-fastjsonschema=2.18.0=pyhd8ed1ab_0 - - python-tzdata=2023.3=pyhd8ed1ab_0 - - python_abi=3.11=3_cp311 - - pyyaml=6.0=py311hd4cff14_5 - - pyzmq=25.1.0=py311h75c88c4_0 - - re2=2023.03.02=h8c504da_0 - - readline=8.2=h8228510_1 - - rpds-py=0.9.2=py311h46250e7_0 - - rtree=1.0.1=py311h3bb2b0f_2 - - ruamel.yaml=0.17.32=py311h459d7ec_0 - - ruamel.yaml.clib=0.2.7=py311h2582759_1 - - s2n=1.3.46=h06160fa_0 - - scikit-learn=1.3.0=py311hc009520_0 - - scipy=1.11.1=py311h64a7726_0 - - shapely=2.0.1=py311h54d622a_1 - - snappy=1.1.10=h9fff704_0 - - sqlite=3.42.0=h2c6b66d_0 - - stack_data=0.6.2=pyhd8ed1ab_0 - - sysroot_linux-64=2.12=he073ed8_16 - - tiledb=2.13.2=hd532e3d_0 - - tk=8.6.12=h27826a3_0 - - tornado=6.3.2=py311h459d7ec_0 - - traitlets=5.9.0=pyhd8ed1ab_0 - - typing_extensions=4.7.1=pyha770c72_0 - - tzcode=2023c=h0b41bf4_0 - - ucx=1.14.1=h0aa22dc_2 - - wcwidth=0.2.6=pyhd8ed1ab_0 - - xerces-c=3.2.4=h8d71039_2 - - xorg-kbproto=1.0.7=h7f98852_1002 - - xorg-libice=1.1.1=hd590300_0 - - xorg-libsm=1.2.4=h7391055_0 - - xorg-libx11=1.8.6=h8ee46fc_0 - - xorg-libxau=1.0.11=hd590300_0 - - xorg-libxdmcp=1.1.3=h7f98852_0 - - xorg-libxext=1.3.4=h0b41bf4_2 - - xorg-libxrender=0.9.11=hd590300_0 - - xorg-renderproto=0.11.1=h7f98852_1002 - - xorg-xextproto=7.3.0=h0b41bf4_1003 - - xorg-xproto=7.0.31=h7f98852_1007 - - xz=5.2.6=h166bdaf_0 - - yaml=0.2.5=h7f98852_2 - - zeromq=4.3.4=h9c3ff4c_1 - - zlib=1.2.13=hd590300_5 - - zstd=1.5.2=hfc55251_7 - - pip: - - anyio==3.7.1 - - appdirs==1.4.4 - - argon2-cffi==23.1.0 - - asciitree==0.3.3 - - attrs==23.1.0 - - babel==2.12.1 - - beautifulsoup4==4.12.2 - - bleach==6.0.0 - - bokeh==3.2.1 - - bqplot==0.12.40 - - branca==0.6.0 - - certifi==2023.7.22 - - cgen==2020.1 - - charset-normalizer==3.2.0 - - click==8.1.6 - - click-plugins==1.1.1 - - cligj==0.7.2 - - cloudpickle==2.2.1 - - colorama==0.4.6 - - colour==0.1.5 - - cycler==0.11.0 - - dask==2023.8.0 - - defusedxml==0.7.1 - - distributed==2023.8.0 - - entrypoints==0.4 - - exceptiongroup==1.1.2 - - fasteners==0.17.3 - - fastjsonschema==2.18.0 - - filelock==3.12.2 - - folium==0.14.0 - - fsspec==2023.6.0 - - gdown==4.7.1 - - geojson==3.0.1 - - geopandas==0.13.2 - - idna==3.4 - - importlib-metadata==6.8.0 - - importlib-resources==6.0.1 - - iniconfig==2.0.0 - - ipyevents==2.0.2 - - ipyfilechooser==0.6.0 - - ipyleaflet==0.17.3 - - ipysheet==0.7.0 - - ipython-genutils==0.2.0 - - ipytree==0.2.2 - - ipywidgets==8.1.0 - - jinja2==3.1.2 - - joblib==1.3.2 - - json5==0.9.14 - - jsonschema==4.19.0 - - jsonschema-specifications==2023.7.1 - - jupyter-server==1.23.6 - - jupyterlab==3.3.2 - - jupyterlab-pygments==0.2.2 - - jupyterlab-server==2.24.0 - - jupyterlab-widgets==3.0.8 - - leafmap==0.23.3 - - locket==1.0.0 - - mapclassify==2.5.0 - - mistune==3.0.1 - - munch==4.0.0 - - munkres==1.1.4 - - nbclassic==0.5.6 - - nbclient==0.8.0 - - nbconvert==7.7.4 - - nbformat==5.9.2 - - networkx==3.1 - - notebook-shim==0.2.3 - - packaging==23.1 - - pandocfilters==1.5.0 - - partd==1.4.0 - - pip==23.2.1 - - pkgutil-resolve-name==1.3.10 - - platformdirs==3.10.0 - - pluggy==1.2.0 - - pooch==1.7.0 - - prometheus-client==0.17.1 - - pscript==0.7.7 - - pycparser==2.21 - - pycrs==1.0.2 - - pymbolic==2022.2 - - pyparsing==3.0.9 - - pyshp==2.3.1 - - pysocks==1.7.1 - - pystac==1.8.3 - - pystac-client==0.7.3 - - pytest==7.4.0 - - python-dateutil==2.8.2 - - pytools==2023.1.1 - - pytz==2023.3 - - referencing==0.30.2 - - requests==2.31.0 - - scooby==0.7.2 - - send2trash==1.8.2 - - setuptools==68.0.0 - - six==1.16.0 - - sniffio==1.3.0 - - sortedcontainers==2.4.0 - - soupsieve==2.3.2.post1 - - tblib==1.7.0 - - terminado==0.17.1 - - threadpoolctl==3.2.0 - - tinycss2==1.2.1 - - toml==0.10.2 - - tomli==2.0.1 - - toolz==0.12.0 - - tqdm==4.65.1 - - traittypes==0.2.1 - - typing-extensions==4.7.1 - - tzdata==2023.3 - - urllib3==2.0.4 - - webencodings==0.5.1 - - websocket-client==1.6.2 - - wheel==0.41.1 - - whitebox==2.3.1 - - whiteboxgui==2.3.0 - - widgetsnbextension==4.0.8 - - xarray==2023.7.0 - - xyzservices==2023.7.0 - - zarr==2.16.0 - - zict==3.0.0 - - zipp==3.16.2 -prefix: /nethome/0448257/.conda/envs/Parcels diff --git a/meta.yaml b/meta.yaml new file mode 100644 index 00000000..6073e7c7 --- /dev/null +++ b/meta.yaml @@ -0,0 +1,30 @@ +package: + name: virtual_ship + version: 0.0.2 + +source: + path: virtual_ship + +build: + entry_points: + - do_expedition = virtual_ship.cli.do_expedition:main + +requirements: + run: + - python >=3.8 + - parcels >=3,<4 + - pyproj >=3,<4 + - sortedcontainers ==2.4.0 + - opensimplex ==0.4.5 + - numpy >=1,<2 + +about: + home: https://oceanparcels.org/ + license: MIT + license_file: LICENSE + summary: > + Code for the Virtual Ship Classroom, where Marine Scientists can combine + Copernicus Marine Data with an OceanParcels ship to go on a virtual expedition. + description: > + Code for the Virtual Ship Classroom, where Marine Scientists can combine + Copernicus Marine Data with an OceanParcels ship to go on a virtual expedition. diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 00000000..f585c3f7 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,74 @@ +[build-system] +requires = ["setuptools >= 61.0", "setuptools_scm[toml]>=6.2"] +build-backend = "setuptools.build_meta" + +[project] +name = "virtual_ship" +description = "Code for the Virtual Ship Classroom, where Marine Scientists can combine Copernicus Marine Data with an OceanParcels ship to go on a virtual expedition." +readme = "README.md" +dynamic = ["version"] +authors = [{ name = "oceanparcels.org team" }] +requires-python = ">=3.8" +license = { file = "LICENSE" } +classifiers = [ + "Development Status :: 3 - Alpha", + "License :: OSI Approved :: MIT License", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Operating System :: OS Independent", + "Topic :: Scientific/Engineering", + "Topic :: Education", + "Intended Audience :: Education", +] +dependencies = [ + "parcels >= 3, < 4", + "pyproj >= 3, < 4", + "sortedcontainers == 2.4.0", + "opensimplex == 0.4.5", + "numpy >=1, < 2", + "pydantic >=2, <3", +] + +[project.urls] +homepage = "https://oceanparcels.org/" +repository = "https://github.com/OceanParcels/Virtual_ship_classroom" +tracker = "https://github.com/OceanParcels/Virtual_ship_classroom/issues" + +[tool.setuptools] +packages = ["virtual_ship"] + +[tool.setuptools_scm] +write_to = "virtual_ship/_version_setup.py" +local_scheme = "no-local-version" + +[project.optional-dependencies] +dev = [ + "black == 24.4.0", + "darglint == 1.8.1", + "flake8 == 7.0.0", + "Flake8-pyproject == 1.2.3", + "isort == 5.13.2", + "pydocstyle == 6.3.0", + "sort-all == 1.2.0", + "pytest == 8.2.0", + "pytest-cov == 5.0.0", + "codecov == 2.1.13", + "seabird == 0.12.0", + "setuptools == 70.0.0", + "sortedcontainers-stubs == 2.4.2", +] + +[project.scripts] +do_expedition = "virtual_ship.cli.do_expedition:main" + +[tool.isort] +profile = "black" +skip_gitignore = true + +[tool.flake8] +extend-ignore = "E501" # Don't check line length. +docstring_style = "sphinx" # Use sphinx docstring style for darglint plugin. diff --git a/scripts/download_data.py b/scripts/download_data.py new file mode 100644 index 00000000..d89edba8 --- /dev/null +++ b/scripts/download_data.py @@ -0,0 +1,136 @@ +""" +Download data required to run expeditions. + +This is a very crude script, here just as long as we do not properly incorporate it into the library. +""" + +import copernicusmarine +import datetime + +if __name__ == "__main__": + datadir = "input_data" + username = input("username: ") + password = input("password: ") + + copernicusmarine.subset( + dataset_id="cmems_mod_glo_phy_my_0.083deg_static", + force_dataset_part="bathy", + variables=["deptho"], + minimum_longitude=-0.01, + maximum_longitude=0.01, + minimum_latitude=-0.01, + maximum_latitude=0.01, + minimum_depth=0.49402499198913574, + maximum_depth=5727.9169921875, + output_filename="bathymetry.nc", + output_directory=datadir, + username=username, + password=password, + force_download=True, + ) + + download_dict = { + "UVdata": { + "dataset_id": "cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i", + "variables": ["uo", "vo"], + "output_filename": "default_uv.nc", + }, + "Sdata": { + "dataset_id": "cmems_mod_glo_phy-so_anfc_0.083deg_PT6H-i", + "variables": ["so"], + "output_filename": "default_s.nc", + }, + "Tdata": { + "dataset_id": "cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i", + "variables": ["thetao"], + "output_filename": "default_t.nc", + }, + } + + for dataset in download_dict: + copernicusmarine.subset( + dataset_id=download_dict[dataset]["dataset_id"], + variables=download_dict[dataset]["variables"], + minimum_longitude=-0.01, + maximum_longitude=0.01, + minimum_latitude=-0.01, + maximum_latitude=0.01, + start_datetime=datetime.datetime.strptime("2023-01-01", "%Y-%m-%d"), + end_datetime=datetime.datetime.strptime("2023-01-02", "%Y-%m-%d"), + minimum_depth=0.49402499198913574, + maximum_depth=5727.9169921875, + output_filename=download_dict[dataset]["output_filename"], + output_directory=datadir, + username=username, + password=password, + force_download=True, + ) + + download_dict = { + "UVdata": { + "dataset_id": "cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i", + "variables": ["uo", "vo"], + "output_filename": "drifter_uv.nc", + }, + "Tdata": { + "dataset_id": "cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i", + "variables": ["thetao"], + "output_filename": "drifter_t.nc", + }, + } + + for dataset in download_dict: + copernicusmarine.subset( + dataset_id=download_dict[dataset]["dataset_id"], + variables=download_dict[dataset]["variables"], + minimum_longitude=-0.01, + maximum_longitude=0.01, + minimum_latitude=-0.01, + maximum_latitude=0.01, + start_datetime=datetime.datetime.strptime("2023-01-01", "%Y-%m-%d"), + end_datetime=datetime.datetime.strptime("2023-01-02", "%Y-%m-%d"), + minimum_depth=0.49402499198913574, + maximum_depth=0.49402499198913574, + output_filename=download_dict[dataset]["output_filename"], + output_directory=datadir, + username=username, + password=password, + force_download=True, + ) + + download_dict = { + "UVdata": { + "dataset_id": "cmems_mod_glo_phy-cur_anfc_0.083deg_PT6H-i", + "variables": ["uo", "vo"], + "output_filename": "argo_float_uv.nc", + }, + "Sdata": { + "dataset_id": "cmems_mod_glo_phy-so_anfc_0.083deg_PT6H-i", + "variables": ["so"], + "output_filename": "argo_float_s.nc", + }, + "Tdata": { + "dataset_id": "cmems_mod_glo_phy-thetao_anfc_0.083deg_PT6H-i", + "variables": ["thetao"], + "output_filename": "argo_float_t.nc", + }, + } + + for dataset in download_dict: + copernicusmarine.subset( + dataset_id=download_dict[dataset]["dataset_id"], + variables=download_dict[dataset]["variables"], + minimum_longitude=-0.01, + maximum_longitude=0.01, + minimum_latitude=-0.01, + maximum_latitude=0.01, + start_datetime=datetime.datetime.strptime("2023-01-01", "%Y-%m-%d"), + end_datetime=datetime.datetime.strptime("2023-01-02", "%Y-%m-%d"), + minimum_depth=0.49402499198913574, + maximum_depth=5727.9169921875, + output_filename=download_dict[dataset]["output_filename"], + output_directory=datadir, + username=username, + password=password, + force_download=True, + ) diff --git a/src/IPO/cruise_simulation.py b/src/IPO/cruise_simulation.py deleted file mode 100755 index 30579024..00000000 --- a/src/IPO/cruise_simulation.py +++ /dev/null @@ -1,218 +0,0 @@ -#!/usr/bin/env python3 -# Script to simulate a cruise with CTD casts and ADCP data - -import numpy as np -import pyproj -from datetime import timedelta -from shapely.geometry import Point, Polygon -from parcels import Field, FieldSet, JITParticle, Variable, ParticleSet - -# set initial location -coords_input = [[-85, -2.5], [-95, -2.5], [-105, -2.5], [-115, -2.5], [-125, -2.5], [-120, -2], [-110, -2], [-100, -2], [-90, -2], [-80, -2]] -#coords_input = [[-80, 2], [-90, 2], [-100, 2], [-110, 2], [-120, 2], [-125, 2.5], [-115, 2.5], [-105, 2.5], [-95, 2.5], [-85, 2.5]] - -# Load the CMEMS data (3 weeks for IPO) -dataset_folder = "/nethome/0448257/Data" -filenames = { - "U": f"{dataset_folder}/studentdata_UV.nc", - "V": f"{dataset_folder}/studentdata_UV.nc", - "S": f"{dataset_folder}/studentdata_S.nc", - "T": f"{dataset_folder}/studentdata_T.nc"} -variables = {'U': 'uo', 'V': 'vo', 'S':'so', 'T':'thetao'} -dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth':'depth'} - -# create the fieldset and set interpolation methods -fieldset = FieldSet.from_netcdf(filenames, variables, dimensions) -fieldset.T.interp_method = "linear_invdist_land_tracer" -fieldset.S.interp_method = "linear_invdist_land_tracer" - -# add bathymetry data to the fieldset for CTD cast -bathymetry_file = f"{dataset_folder}/GLO-MFC_001_024_mask_bathy.nc" -bathymetry_variables = ('bathymetry', 'deptho') -bathymetry_dimensions = {'lon': 'longitude', 'lat': 'latitude'} -bathymetry_field = Field.from_netcdf(bathymetry_file, bathymetry_variables, bathymetry_dimensions) -fieldset.add_field(bathymetry_field) -# read in data already -fieldset.computeTimeChunk(0,1) - -### Determine ship course as intermediate points between CTD stations - -# Initialize lists to store intermediate points -lons = [] -lats = [] - -# Loop over station coordinates and calculate intermediate points along great circle path -i = 0 -for i in (range(len(coords_input)-1)): - startlong = coords_input[i][0] - startlat = coords_input[i][1] - endlong = coords_input[i+1][0] - endlat = coords_input[i+1][1] - - # calculate line string along path with segments every 5 min = 3.6*60*5 = 1080 m (or switch comment for 2 midpoints) - g = pyproj.Geod(ellps='WGS84') - r = g.inv_intermediate(startlong, startlat, endlong, endlat, del_s = 1080) - # r = g.inv_intermediate(startlong, startlat, endlong, endlat, initial_idx=0, return_back_azimuth=False, npts=3) - lons.append(r.lons) # stored as a list of arrays - lats.append(r.lats) - -# initial_idx will add begin point to each list (but not end point to avoid dubbling) so add final endpoint manually -lons = np.append(np.hstack(lons), endlong) -lats = np.append(np.hstack(lats), endlat) - -# check if input sample locations are within data availability area, only save if so -poly = Polygon([(-170, 5), (-170, -10), (-75, -10), (-75, 5)]) -coords = [] -sample_lons = [] -sample_lats = [] -for coord in coords_input: - if poly.contains(Point(coord)): - coords.append(coord) -for i in range(len(lons)): - if poly.contains(Point(lons[i], lats[i])): - sample_lons.append(lons[i]) - sample_lats.append(lats[i]) - -### Define particles and sampling functions - -# Create ADCP like particles to sample the ocean -class ADCPParticle(JITParticle): - """Define a new particle class that does ADCP like measurements""" - U = Variable('U', dtype=np.float32, initial=0.0) - V = Variable('V', dtype=np.float32, initial=0.0) - -# define ADCP sampling function without conversion (because of A grid) -def SampleVel(particle, fieldset, time): - particle.U, particle.V = fieldset.UV.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False) - # particle.V = fieldset.V.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False) - -# Create CTD like particles to sample the ocean -class CTDParticle(JITParticle): - """Define a new particle class that does CTD like measurements""" - salinity = Variable("salinity", initial=np.nan) - temperature = Variable("temperature", initial=np.nan) - pressure = Variable("pressure", initial=np.nan) - raising = Variable("raising", dtype=np.int32, initial=0.0) - -# define function lowering and raising CTD -def CTDcast(particle, fieldset, time): - seafloor = fieldset.bathymetry[time, particle.depth, particle.lat, particle.lon] - vertical_speed = 1.0 # sink and rise speed in m/s - - if particle.raising == 0: - # Sinking with vertical_speed until near seafloor - particle_ddepth = vertical_speed * particle.dt - if particle.depth >= (seafloor - 20): - particle.raising = 1 - - if particle.raising == 1: - # Rising with vertical_speed until depth is 2 m - if particle.depth > 2: - particle_ddepth = -vertical_speed * particle.dt - if particle.depth + particle_ddepth <= 2: - # to break the loop ... - particle.state = 41 - print("CTD cast finished") - -# define function sampling Salinity -def SampleS(particle, fieldset, time): - particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon] - -# define function sampling Temperature -def SampleT(particle, fieldset, time): - particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] - -# define function sampling Pressure -def SampleP(particle, fieldset, time): - particle.pressure = fieldset.P[time, particle.depth, particle.lat, particle.lon] - -### Run simulation - -# Create ADCP like particle with accurate depths, 1000 m every 20 m = 50 particles -depthnum = 50 -# Initiate ADCP like particle set -pset = ParticleSet.from_list( - fieldset=fieldset, pclass=ADCPParticle, lon=np.full(depthnum,sample_lons[0]), lat=np.full(depthnum,sample_lats[0]), depth=np.linspace(5, 1005, num=depthnum), time=0 -) -# create a ParticleFile to store the ADCP output -adcp_output_file = pset.ParticleFile(name="./results/sailship_adcp.zarr") -adcp_dt = timedelta(minutes=5).total_seconds() # timestep of ADCP output, every 5 min == 1080 m (3.6*60*5 =m/s*s/min*min) - -# initialize CTD station number and time -total_time = timedelta(hours=0).total_seconds() -ctd = 0 -ctd_dt = timedelta(seconds=10) # timestep of CTD output reflecting post-proces binning into 10m bins - -# run the model for the length of the sample_lons list -for i in range(len(sample_lons)-1): - - #vexecute the kernels to sample U and V - pset.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) - adcp_output_file.write(pset, time=pset[0].time) - - # check if we are at a CTD station - if (sample_lons[i] - coords[ctd][0]) < 0.01 and (sample_lats[i] - coords[ctd][1]) < 0.01: - ctd += 1 - - # release CTD particle - pset_CTD = ParticleSet(fieldset=fieldset, pclass=CTDParticle, lon=sample_lons[i], lat=sample_lats[i], depth=2, time=total_time) - - # create a ParticleFile to store the CTD output - ctd_output_file = pset_CTD.ParticleFile(name=f"./results/CTD_test_{ctd}.zarr", outputdt=ctd_dt) - - # record the temperature and salinity of the particle - pset_CTD.execute([SampleS, SampleT, CTDcast], runtime=timedelta(hours=4), dt=ctd_dt, output_file=ctd_output_file) - total_time = pset_CTD.time[0] #+ timedelta(hours=1).total_seconds() # add CTD time and 1 hour for deployment - - # update the particle time and location - pset.lon_nextloop[:] = sample_lons[i+1] - pset.lat_nextloop[:] = sample_lats[i+1] - - total_time += adcp_dt - pset.time_nextloop[:] = total_time -# write the final locations of the ADCP particles -pset.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) -adcp_output_file.write_latest_locations(pset, time=total_time) - -### Post-processing -import xarray as xr -from scipy.ndimage import uniform_filter1d - -# rewrite CTD data to cvs -for i in range(1, ctd+1): - - # Open output and read to x, y, z - ds = xr.open_zarr(f"./results/CTD_test_{i}.zarr") - x = ds["lon"][:].squeeze() - y = ds["lat"][:].squeeze() - z = ds["z"][:].squeeze() - time = ds["time"][:].squeeze() - T = ds["temperature"][:].squeeze() - S = ds["salinity"][:].squeeze() - ds.close() - - # add some noise - random_walk = np.random.random()/10 - z_norm = (z-np.min(z))/(np.max(z)-np.min(z)) - t_norm = np.linspace(0, 1, num=len(time)) - # dS = abs(np.append(0, np.diff(S))) # scale noise with gradient - # for j in range(5, 0, -1): - # dS[dS<1*10**-j] = 0.5-j/10 - # add smoothed random noise scaled with depth (and OPTIONAL with gradient for S) - # and random (reversed) diversion from initial through time scaled with depth - S = S + uniform_filter1d( - np.random.random(S.shape)/5*(1-z_norm) + - random_walk*(np.max(S).values - np.min(S).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/40), 1)) - T = T + uniform_filter1d( - np.random.random(T.shape)*5*(1-z_norm) - - random_walk/2*(np.max(T).values - np.min(T).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/20), 1)) - - # reshaping data to export to csv - header = f"'pressure [hPa]','temperature [degC]', 'salinity [g kg-1]'" - data = np.column_stack([(z/10), T, S]) - new_line = '\n' - np.savetxt(f"./results/CTD_station_{i}.csv", data, fmt="%.4f", header=header, delimiter=',', - comments=f'{x.attrs}{new_line}{x[0].values}{new_line}{y.attrs}{new_line}{y[0].values}{new_line}start time: {time[0].values}{new_line}end time: {time[-1].values}{new_line}') - diff --git a/src/IPO/post_process.py b/src/IPO/post_process.py deleted file mode 100644 index a47ab123..00000000 --- a/src/IPO/post_process.py +++ /dev/null @@ -1,47 +0,0 @@ -#!/usr/bin/env python3 -# Post proces .results folder created by cruise_simulation.py - -### Post-processing -import xarray as xr -import numpy as np -from scipy.ndimage import uniform_filter1d - -# rewrite CTD data to cvs -ctd = 9 -for i in range(1, ctd+1): - - # Open output and read to x, y, z - ds = xr.open_zarr(f"./results/CTD_test_{i}.zarr") - x = ds["lon"][:].squeeze() - y = ds["lat"][:].squeeze() - z = ds["z"][:].squeeze() - time = ds["time"][:].squeeze() - T = ds["temperature"][:].squeeze() - S = ds["salinity"][:].squeeze() - ds.close() - - # add some noise - random_walk = np.random.random()/10 - z_norm = (z-np.min(z))/(np.max(z)-np.min(z)) - t_norm = np.linspace(0, 1, num=len(time)) - # dS = abs(np.append(0, np.diff(S))) # scale noise with gradient - # for j in range(5, 0, -1): - # dS[dS<1*10**-j] = 0.5-j/10 - # add smoothed random noise scaled with depth (and OPTIONAL with gradient for S) - # and random (reversed) diversion from initial through time scaled with depth - S = S + uniform_filter1d( - np.random.random(S.shape)/5*(1-z_norm) + - random_walk*(np.max(S).values - np.min(S).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/40), 1)) - T = T + uniform_filter1d( - np.random.random(T.shape)*5*(1-z_norm) - - random_walk/2*(np.max(T).values - np.min(T).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/20), 1)) - - # reshaping data to export to csv - header = f"'pressure [hPa]','temperature [degC]', 'salinity [g kg-1]'" - data = np.column_stack([(z/10), T, S]) - new_line = '\n' - np.savetxt(f"./results/CTD_station_{i}.csv", data, fmt="%.4f", header=header, delimiter=',', - comments=f'{x.attrs}{new_line}{x[0].values}{new_line}{y.attrs}{new_line}{y[0].values}{new_line}start time: {time[0].values}{new_line}end time: {time[-1].values}{new_line}') - diff --git a/src/IPO/submit.sh b/src/IPO/submit.sh deleted file mode 100644 index 5626f4a7..00000000 --- a/src/IPO/submit.sh +++ /dev/null @@ -1,11 +0,0 @@ -#!/bin/bash -l -# -#SBATCH -J VSC # the name of your job -#SBATCH -p normal # request the short partition, job takes less than 3 hours -#SBATCH -t 5:00:00 # time in hh:mm:ss you want to reserve for the job -#SBATCH -n 1 # the number of cores you want to use for the job, SLURM automatically determines how many nodes are needed -#SBATCH -o log%j.o # the name of the file where the standard output will be written to. %j will be the jobid determined by SLURM -#SBATCH -e log%j.e # the name of the file where potential errors will be written to. %j will be the jobid determined by SLURM - -conda activate parcels -srun ./cruise_simulation.py diff --git a/src/OLD/adcpCMEMS.ipynb b/src/OLD/adcpCMEMS.ipynb deleted file mode 100644 index b6d3f0ec..00000000 --- a/src/OLD/adcpCMEMS.ipynb +++ /dev/null @@ -1,359 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Local ADCP Particle test with CMEMS data" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from datetime import timedelta\n", - "import numpy as np\n", - "import math\n", - "\n", - "from parcels import (\n", - " ErrorCode,\n", - " FieldSet,\n", - " JITParticle,\n", - " ParticleSet,\n", - " Variable,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# # Example for function from https://github.com/OceanParcels/parcels/blob/0f396703be2804f8eaf12b10d1ec1c978af812b3/performance/example_performanceProfiling.py#L76\n", - "# import os\n", - "# from glob import glob\n", - "\n", - "# def set_cmems_fieldset(cs, deferLoadFlag=True, periodicFlag=False):\n", - "# ddir_head = \"/Users/0448257/Data\"\n", - "# ddir = os.path.join(ddir_head, \"CMEMS/\")\n", - "# files = sorted(glob(ddir+\"glo12_rg_1d-m_2021010*.nc\"))\n", - "# variables = {'U': 'uo', 'V': 'vo'}\n", - "# dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time'}\n", - "\n", - "# if cs not in ['auto', False]:\n", - "# # cs = (1, cs, cs) # == OLD initialization as tuple. Advised to rather use a dictionary. ==#\n", - "# cs = {dimensions['time']: 1, dimensions['lon']: cs, dimensions['lat']: cs}\n", - "# if periodicFlag:\n", - "# return FieldSet.from_netcdf(files, variables, dimensions, time_periodic=timedelta(days=30), deferred_load=deferLoadFlag, field_chunksize=cs)\n", - "# else:\n", - "# return FieldSet.from_netcdf(files, variables, dimensions, allow_time_extrapolation=True, deferred_load=deferLoadFlag, field_chunksize=cs)\n", - "\n", - "# fieldset = set_cmems_fieldset(False)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read sample input data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.494025\n" - ] - } - ], - "source": [ - "# Load the CMEMS data (3 days manually downloaded)\n", - "example_dataset_folder = \"../Data\"\n", - "filenames = {\n", - " \"U\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"V\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"S\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-so_hcst_R20210113.nc\",\n", - " \"T\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-thetao_hcst_R20210113.nc\",\n", - "}\n", - "variables = {'U': 'uo', 'V': 'vo', 'S':'so', 'T':'thetao'}\n", - "dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth':'depth'}\n", - "fieldset = FieldSet.from_netcdf(filenames, variables, dimensions, time_periodic=timedelta(days=3))\n", - "\n", - "# uppermost layer in the hydrodynamic data\n", - "fieldset.mindepth = fieldset.U.depth[0]\n", - "print(fieldset.mindepth)\n", - "\n", - "# set initial location\n", - "ini_lat = -31\n", - "ini_lon = 32" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create particles and initalize" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO: Compiled ArraySampleParticleInitZeroSampleS ==> /tmp/parcels-382783/lib45ac30e829f5354904253e0c9bfec45f_0.so\n", - "WARNING: dt or runtime are zero, or endtime is equal to Particle.time. The kernels will be executed once, without incrementing time\n", - "INFO: Compiled ArraySampleParticleInitZeroSampleT ==> /tmp/parcels-382783/lib274d8ae72420a16131edca44f12f7cf2_0.so\n" - ] - }, - { - "ename": "TypeError", - "evalue": "ParticleSetSOA.Kernel() got an unexpected keyword argument 'dt'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[4], line 35\u001b[0m\n\u001b[1;32m 33\u001b[0m pset\u001b[39m.\u001b[39mexecute(Sample_S_kernel, dt\u001b[39m=\u001b[39m\u001b[39m0\u001b[39m)\n\u001b[1;32m 34\u001b[0m pset\u001b[39m.\u001b[39mexecute(Sample_T_kernel, dt\u001b[39m=\u001b[39m\u001b[39m0\u001b[39m)\n\u001b[0;32m---> 35\u001b[0m pset\u001b[39m.\u001b[39;49mKernel(SampleVel_kernel, dt\u001b[39m=\u001b[39;49m\u001b[39m0\u001b[39;49m)\n", - "\u001b[0;31mTypeError\u001b[0m: ParticleSetSOA.Kernel() got an unexpected keyword argument 'dt'" - ] - } - ], - "source": [ - "# Create and initialize Variable particles to sample the ocean\n", - "class SampleParticleInitZero(JITParticle):\n", - " \"\"\"Define a new particle class with Variables init 0\"\"\"\n", - " salinity = Variable(\"salinity\", initial=0)\n", - " temperature = Variable(\"temperature\", initial=0)\n", - " U = Variable('U', dtype=np.float32, initial=np.nan)\n", - " V = Variable('V', dtype=np.float32, initial=np.nan)\n", - "\n", - "# define function sampling Salinity \n", - "def SampleS(particle, fieldset, time):\n", - " particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# define function sampling Temperature \n", - "def SampleT(particle, fieldset, time):\n", - " particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# define function sampling u and v as in https://docs.oceanparcels.org/en/latest/examples/tutorial_sampling.html\n", - "def SampleVel_correct(particle, fieldset, time):\n", - " particle.U, particle.V = fieldset.UV[time, particle.depth, particle.lat, particle.lon, particle]\n", - "\n", - "# Attempt for ADCP like particle TODO accurate depths \n", - "depthnum = 30\n", - "# Initiate ADCP like particle set \n", - "pset = ParticleSet.from_list(\n", - " fieldset=fieldset, pclass=SampleParticleInitZero, lon=np.full(depthnum,ini_lon), lat=np.full(depthnum,ini_lat), depth=np.linspace(5, 1000, num=depthnum)\n", - ")\n", - "\n", - "Sample_S_kernel = pset.Kernel(SampleS) # Casting the SampleS function to a kernel.\n", - "Sample_T_kernel = pset.Kernel(SampleT) # similar for temperature\n", - "SampleVel_kernel = pset.Kernel(SampleVel_correct) # Casting the function to a kernel.\n", - "\n", - "# only execute the sampling kernels to record the init temp of the particles\n", - "pset.execute(Sample_S_kernel, dt=0)\n", - "pset.execute(Sample_T_kernel, dt=0)\n", - "pset.execute(SampleVel_kernel, dt=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Determine ship course and add as kernel " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# change advection to ship movement\n", - "# Cruising speed Pelagia (and Anna Weber) is 9 knp https://www.nioz.nl/application/files/3614/9744/8746/Pelagia_Technical_specifications-2016.pdf\n", - "# survey speed nog iets lager? Zoals bij https://schmidtocean.org/rv-falkor/ship-specifications/\n", - "# 7 knp = 13 km/h = 3.6 m/s\n", - "\n", - "def ShipVel(particle, fieldset, time):\n", - " speed = 3.6\n", - " target_lat = -50\n", - " target_lon = 20\n", - " # determine ship direction\n", - " heading = math.sqrt((target_lat - particle.lat)**2 + (target_lon - particle.lon)**2)\n", - " # calculate e/w and n/s speed (m/s)\n", - " lat_add = (target_lat - particle.lat)/(heading/speed)\n", - " lon_add = (target_lon - particle.lon)/(heading/speed)\n", - " # convert to lat/lon\n", - " lat_add_deg = lat_add / 1.11e5\n", - " lon_add_deg = lon_add / (1.11e5 * math.cos(particle.lat * math.pi / 180))\n", - " # add to particle position\n", - " particle.lat += lat_add_deg * particle.dt\n", - " particle.lon += lon_add_deg * particle.dt\n", - "\n", - "# cast the ships velocity function to a kernel object\n", - "ShipVel_kernel = pset.Kernel(ShipVel)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run simulation" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO: Compiled ArraySampleParticleInitZeroShipVelSampleSSampleTSampleVel_correct ==> /tmp/parcels-382783/lib057c17877b184be2fe6a44f0844c423d_0.so\n", - "INFO: Output files are stored in ADCPtest.zarr.\n", - "100%|██████████| 86400.0/86400.0 [02:32<00:00, 566.27it/s] \n" - ] - } - ], - "source": [ - "# set output file name and dt\n", - "output_file = pset.ParticleFile(\n", - " name=\"ADCPtest.zarr\", # the file name\n", - " outputdt=timedelta(hours=1), # the time step of the outputs\n", - ")\n", - "\n", - "# Choose which kernels to use\n", - "kernels = ShipVel_kernel + Sample_S_kernel + Sample_T_kernel + SampleVel_kernel\n", - "\n", - "# Execute code and save to file \n", - "pset.execute(\n", - " kernels, \n", - " runtime=timedelta(days=1), # the total length of the run\n", - " dt=timedelta(minutes=60), # the timestep of the kernel\n", - " output_file=output_file,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Do some plotting to check output" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import xarray as xr\n", - "\n", - "# Open output and read to x, y, z\n", - "ds = xr.open_zarr(\"ADCPtest.zarr\")\n", - "x = ds[\"lon\"][:].squeeze()\n", - "y = ds[\"lat\"][:].squeeze()\n", - "z = ds[\"z\"][:].squeeze()\n", - "U = ds[\"U\"][:].squeeze()\n", - "V = ds[\"V\"][:].squeeze()\n", - "S = ds[\"salinity\"][:].squeeze()\n", - "T = ds[\"temperature\"][:].squeeze()\n", - "ds.close()\n", - "\n", - "# Plot Particle depth\n", - "fig = plt.figure(figsize=(13, 10))\n", - "ax = plt.axes(projection=\"3d\")\n", - "cb = ax.scatter(x, y, z, c=U, s=20, marker=\"o\")\n", - "ax.set_title('Zonal velocity along ship trajectory', size=15)\n", - "ax.set_xlabel(\"Longitude\")\n", - "ax.set_ylabel(\"Latitude\")\n", - "ax.set_zlabel(\"Depth (m)\")\n", - "ax.set_zlim(np.max(z), 0)\n", - "plt.colorbar(cb, shrink = 0.7)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Dimensions: (trajectory: 10, obs: 73)\n", - "Coordinates:\n", - " * obs (obs) int32 0 1 2 3 4 5 6 7 8 9 ... 64 65 66 67 68 69 70 71 72\n", - " * trajectory (trajectory) int64 80 81 82 83 84 85 86 87 88 89\n", - "Data variables:\n", - " U (trajectory, obs) float32 dask.array\n", - " V (trajectory, obs) float32 dask.array\n", - " lat (trajectory, obs) float32 dask.array\n", - " lon (trajectory, obs) float32 dask.array\n", - " salinity (trajectory, obs) float32 dask.array\n", - " temperature (trajectory, obs) float32 dask.array\n", - " time (trajectory, obs) datetime64[ns] dask.array\n", - " z (trajectory, obs) float32 dask.array\n", - "Attributes:\n", - " Conventions: CF-1.6/CF-1.7\n", - " feature_type: trajectory\n", - " ncei_template_version: NCEI_NetCDF_Trajectory_Template_v2.0\n", - " parcels_mesh: spherical\n", - " parcels_version: 2.4.2\n" - ] - } - ], - "source": [ - "print(ds)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "py3_parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/OLD/adcp_ctdCMEMS.ipynb b/src/OLD/adcp_ctdCMEMS.ipynb deleted file mode 100644 index a7e60e35..00000000 --- a/src/OLD/adcp_ctdCMEMS.ipynb +++ /dev/null @@ -1,558 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Combined ADCP and CTD particle test with CMEMS data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read sample input data" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from datetime import timedelta\n", - "import numpy as np\n", - "import math\n", - "\n", - "from parcels import (\n", - " AdvectionRK4,\n", - " ErrorCode,\n", - " Field,\n", - " FieldSet,\n", - " JITParticle,\n", - " ScipyParticle,\n", - " ParticleSet,\n", - " Variable,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "# Load the CMEMS data (3 days manually downloaded)\n", - "example_dataset_folder = \"../Data\"\n", - "filenames = {\n", - " \"U\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"Usample\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"V\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"Vsample\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"S\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-so_hcst_R20210113.nc\",\n", - " \"T\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-thetao_hcst_R20210113.nc\"}\n", - "variables = {'U': 'uo', 'Usample': 'uo', 'V': 'vo', 'Vsample': 'vo', 'S':'so', 'T':'thetao'}\n", - "dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth':'depth'}\n", - "\n", - "# create the fieldset and set interpolation methods\n", - "fieldset = FieldSet.from_netcdf(filenames, variables, dimensions, time_periodic=timedelta(days=3))\n", - "fieldset.T.interp_method = \"linear_invdist_land_tracer\"\n", - "fieldset.S.interp_method = \"linear_invdist_land_tracer\"\n", - "\n", - "# # determine top and bottom layer in the hydrodynamic data\n", - "# fieldset.mindepth = math.ceil(fieldset.U.depth[0])\n", - "# fieldset.maxdepth = math.floor(fieldset.U.depth[-1])\n", - "\n", - "# add bathymetry data to the fieldset for CTD cast\n", - "bathymetry_file = f\"{example_dataset_folder}/GLO-MFC_001_024_mask_bathy.nc\"\n", - "bathymetry_variables = ('bathymetry', 'deptho')\n", - "bathymetry_dimensions = {'lon': 'longitude', 'lat': 'latitude'}\n", - "bathymetry_field = Field.from_netcdf(bathymetry_file, bathymetry_variables, bathymetry_dimensions)\n", - "fieldset.add_field(bathymetry_field) \n", - "fieldset.add_constant('z_start',0.5)\n", - "\n", - "# set initial location\n", - "coords = [[-94.394531, -4.390229], [-106.523437, -0.175781], [-124.541016, -6.053161], [-140.537109, -0.527336]]\n", - "loc = 1\n", - "ini_lat = coords[loc][1]\n", - "ini_lon = coords[loc][0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "### Determine ship course and add as kernel " - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# change advection to ship movement\n", - "# Cruising speed Pelagia (and Anna Weber) is 9 knp https://www.nioz.nl/application/files/3614/9744/8746/Pelagia_Technical_specifications-2016.pdf\n", - "# survey speed nog iets lager? Zoals bij https://schmidtocean.org/rv-falkor/ship-specifications/\n", - "# 7 knp = 13 km/h = 3.6 m/s\n", - "\n", - "# TODO add coords to function\n", - "def ShipVel(particle, fieldset, time):\n", - " # loc = 1\n", - " speed = 3.6\n", - " target_lat = -32 #coords[loc][0]\n", - " target_lon = 49 #coords[loc][1]\n", - " # # slow down when close to target\n", - " # if target_lat - particle.lat < 3.6*3600/1.11e5 or target_lon - particle.lon < 3.6*3600/(1.11e5 * math.cos(particle.lat * math.pi / 180)):\n", - " # speed = speed/4\n", - " # determine ship direction\n", - " heading = math.sqrt((target_lat - particle.lat)**2 + (target_lon - particle.lon)**2)\n", - " # calculate e/w and n/s speed (m/s)\n", - " lat_add = (target_lat - particle.lat)/(heading/speed)\n", - " lon_add = (target_lon - particle.lon)/(heading/speed)\n", - " # convert to lat/lon\n", - " lat_add_deg = lat_add / 1.11e5\n", - " lon_add_deg = lon_add / (1.11e5 * math.cos(particle.lat * math.pi / 180))\n", - " # add to particle position\n", - " particle.lat += lat_add_deg * particle.dt\n", - " particle.lon += lon_add_deg * particle.dt\n", - " # update loc if close to target TODO target reached\n", - " # if target_lat - particle.lat < 3.6*3600/1.11e5 or target_lon - particle.lon < 3.6*3600/(1.11e5 * math.cos(particle.lat * math.pi / 180)):\n", - " # loc += 1\n", - " # speed = 3.6" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define particles and sampling functions " - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "# Create and initialize Variable particles to sample the ocean\n", - "class ADCPParticle(JITParticle):\n", - " \"\"\"Define a new particle class that does ADCP like measurements\"\"\"\n", - " U = Variable('U', dtype=np.float32, initial=0.0)\n", - " V = Variable('V', dtype=np.float32, initial=0.0)\n", - "\n", - "# # define function sampling u and v as in https://docs.oceanparcels.org/en/latest/examples/tutorial_sampling.html\n", - "# def SampleVel_correct(particle, fieldset, time):\n", - "# # Attention: samples particle velocity in units of the mesh (deg/s or m/s)\n", - "# particle.U, particle.V = fieldset.UV[time, particle.depth, particle.lat, particle.lon, particle]\n", - "\n", - "# define sampling function from Usample and Vsample (because of A grid)\n", - "def SampleVel(particle, fieldset, time):\n", - " particle.U = fieldset.Usample[time, particle.depth, particle.lat, particle.lon]\n", - " particle.V = fieldset.Vsample[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# Create and initialize Variable particles to sample the ocean\n", - "class CTDParticle(JITParticle):\n", - " \"\"\"Define a new particle class that does CTD like measurements\"\"\" \n", - " salinity = Variable(\"salinity\", initial=np.nan)\n", - " temperature = Variable(\"temperature\", initial=np.nan)\n", - " raising = Variable(\"raising\", dtype=np.int32, initial=0.0)\n", - "\n", - "# define function lowering and raising CTD\n", - "def CTDcast(particle, fieldset, time):\n", - " seafloor = fieldset.bathymetry[time, particle.depth, particle.lat,particle.lon]\n", - " vertical_speed = 1.0 # sink and rise speed in m/s\n", - "\n", - " if particle.raising == 0:\n", - " # Sinking with vertical_speed until depth is smaller than seafloor\n", - " particle.depth += vertical_speed * particle.dt\n", - " if particle.depth >= seafloor:\n", - " particle.raising = 1\n", - "\n", - " elif particle.raising == 1:\n", - " # Rising with vertical_speed until depth is 0.5 m\n", - " while particle.depth > 1.5:\n", - " particle.depth -= vertical_speed * particle.dt\n", - " if particle.depth <= 1.5:\n", - " print(\"CTD cast finished\")\n", - " break\n", - "\n", - "# define function sampling Salinity \n", - "def SampleS(particle, fieldset, time):\n", - " particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# define function sampling Temperature \n", - "def SampleT(particle, fieldset, time):\n", - " particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create a particle set and choose kernels" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "# ADCP like particle TODO accurate depths \n", - "depthnum = 5\n", - "# Initiate ADCP like particle set \n", - "pset = ParticleSet.from_list(\n", - " fieldset=fieldset, pclass=ADCPParticle, lon=np.full(depthnum,ini_lon), lat=np.full(depthnum,ini_lat), depth=np.linspace(5, 1000, num=depthnum)\n", - ")\n", - "\n", - "# Casting the ADCP sample function to a kernel\n", - "# SampleVel_kernel = pset.Kernel(SampleVel_correct) \n", - "SampleVel_kernel = pset.Kernel(SampleVel) \n", - "\n", - "# Cast the ships velocity function to a kernel object\n", - "ShipVel_kernel = pset.Kernel(ShipVel)\n", - "\n", - "# Choose which kernels to use\n", - "kernels = SampleVel_kernel + ShipVel_kernel " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run simulation" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO: Compiled ArrayCTDParticleSampleSSampleTCTDcast ==> /tmp/parcels-382783/lib04c095da969e206ae079d9f759b9dab8_0.so\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CTD time!\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO: Compiled ArrayCTDParticleSampleSSampleTCTDcast ==> /tmp/parcels-382783/lib7d7b341c638368966a66052fef88a67a_0.so\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CTD time!\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO: Compiled ArrayCTDParticleSampleSSampleTCTDcast ==> /tmp/parcels-382783/lib805b3b4194b363c3477f9afc8b5c61e2_0.so\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CTD cast finished\n", - "CTD cast finished\n" - ] - }, - { - "ename": "ThroughSurfaceError", - "evalue": "0\nParticle P[35](lon=-102.290871, lat=-1.041822, depth=-9.500000, salinity=34.711002, temperature=22.843367, raising=1.000000, time=46630.000000)\nTime: 2021-01-02T00:57:10.000000000\ntimestep dt: 10.0\nThrough-surface sampling by particle at (-102.2908706665039, -1.041822075843811, -9.5)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mThroughSurfaceError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m/nethome/0448257/Virtual_ship_classroom/adcp_ctdCMEMS.ipynb Cell 14\u001b[0m line \u001b[0;36m5\n\u001b[1;32m 50\u001b[0m CTD_kernels \u001b[39m=\u001b[39m Sample_S_kernel \u001b[39m+\u001b[39m Sample_T_kernel \u001b[39m+\u001b[39m Cast_CTD_kernel\n\u001b[1;32m 52\u001b[0m \u001b[39m# record the temperature and salinity of the particles\u001b[39;00m\n\u001b[0;32m---> 53\u001b[0m pset_CTD\u001b[39m.\u001b[39;49mexecute(CTD_kernels, runtime\u001b[39m=\u001b[39;49moutputdt, dt\u001b[39m=\u001b[39;49mtimedelta(seconds\u001b[39m=\u001b[39;49m\u001b[39m10\u001b[39;49m))\n\u001b[1;32m 55\u001b[0m \u001b[39m# write the CTD particles to the output file\u001b[39;00m\n\u001b[1;32m 56\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mCTD time!\u001b[39m\u001b[39m\"\u001b[39m)\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/particleset/baseparticleset.py:548\u001b[0m, in \u001b[0;36mBaseParticleSet.execute\u001b[0;34m(self, pyfunc, pyfunc_inter, endtime, runtime, dt, moviedt, recovery, output_file, movie_background_field, verbose_progress, postIterationCallbacks, callbackdt)\u001b[0m\n\u001b[1;32m 546\u001b[0m \u001b[39m# If we don't perform interaction, only execute the normal kernel efficiently.\u001b[39;00m\n\u001b[1;32m 547\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39minteraction_kernel \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m--> 548\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mkernel\u001b[39m.\u001b[39;49mexecute(\u001b[39mself\u001b[39;49m, endtime\u001b[39m=\u001b[39;49mnext_time, dt\u001b[39m=\u001b[39;49mdt, recovery\u001b[39m=\u001b[39;49mrecovery, output_file\u001b[39m=\u001b[39;49moutput_file,\n\u001b[1;32m 549\u001b[0m execute_once\u001b[39m=\u001b[39;49mexecute_once)\n\u001b[1;32m 550\u001b[0m \u001b[39m# Interaction: interleave the interaction and non-interaction kernel for each time step.\u001b[39;00m\n\u001b[1;32m 551\u001b[0m \u001b[39m# E.g. Inter -> Normal -> Inter -> Normal if endtime-time == 2*dt\u001b[39;00m\n\u001b[1;32m 552\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 553\u001b[0m cur_time \u001b[39m=\u001b[39m time\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/kernel/kernelsoa.py:213\u001b[0m, in \u001b[0;36mKernelSOA.execute\u001b[0;34m(self, pset, endtime, dt, recovery, output_file, execute_once)\u001b[0m\n\u001b[1;32m 211\u001b[0m recovery_kernel \u001b[39m=\u001b[39m recovery_map[p\u001b[39m.\u001b[39mstate]\n\u001b[1;32m 212\u001b[0m p\u001b[39m.\u001b[39mset_state(StateCode\u001b[39m.\u001b[39mSuccess)\n\u001b[0;32m--> 213\u001b[0m recovery_kernel(p, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfieldset, p\u001b[39m.\u001b[39;49mtime)\n\u001b[1;32m 214\u001b[0m \u001b[39mif\u001b[39;00m p\u001b[39m.\u001b[39misComputed():\n\u001b[1;32m 215\u001b[0m p\u001b[39m.\u001b[39mreset_state()\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/tools/statuscodes.py:193\u001b[0m, in \u001b[0;36mrecovery_kernel_through_surface\u001b[0;34m(particle, fieldset, time)\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"Default sampling error kernel that throws OutOfBoundsError.\"\"\"\u001b[39;00m\n\u001b[1;32m 190\u001b[0m \u001b[39mif\u001b[39;00m particle\u001b[39m.\u001b[39mexception \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m 191\u001b[0m \u001b[39m# TODO: JIT does not yet provide the context that created\u001b[39;00m\n\u001b[1;32m 192\u001b[0m \u001b[39m# the exception. We need to pass that info back from C.\u001b[39;00m\n\u001b[0;32m--> 193\u001b[0m \u001b[39mraise\u001b[39;00m ThroughSurfaceError(particle, fieldset)\n\u001b[1;32m 194\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 195\u001b[0m error \u001b[39m=\u001b[39m particle\u001b[39m.\u001b[39mexception\n", - "\u001b[0;31mThroughSurfaceError\u001b[0m: 0\nParticle P[35](lon=-102.290871, lat=-1.041822, depth=-9.500000, salinity=34.711002, temperature=22.843367, raising=1.000000, time=46630.000000)\nTime: 2021-01-02T00:57:10.000000000\ntimestep dt: 10.0\nThrough-surface sampling by particle at (-102.2908706665039, -1.041822075843811, -9.5)" - ] - } - ], - "source": [ - "# write the particle data every hour\n", - "outputdt = timedelta(hours=1).total_seconds()\n", - "\n", - "# release CTD every 6 hours\n", - "repeatdt = timedelta(hours=6).total_seconds()\n", - "\n", - "# run the model for 24 hours\n", - "runtime = timedelta(hours=15).total_seconds()\n", - "\n", - "# CTD stuff\n", - "# initialize CTD station number\n", - "station = 0\n", - "# # Set max depth for CTD cast OLD from before adding bathymetry\n", - "# CTD_depth = fieldset.maxdepth - fieldset.mindepth\n", - "\n", - "# create a ParticleFile to store the output\n", - "# Note: Do not specify the outputdt yet, so we can manually write the output\n", - "output_file = pset.ParticleFile(name=\"ADCP_CTD_test.zarr\")\n", - "\n", - "for time in np.arange(0, runtime, outputdt):\n", - "\n", - " # check if time is a multiple of repeatdt\n", - " # TODO add time\n", - " if np.isclose(np.fmod(time, repeatdt), 0):\n", - " station += 1\n", - " # create a ParticleFile to store the CTD output\n", - " ctd_output_file = pset.ParticleFile(name=f\"CTD_test_{station}.zarr\")\n", - "\n", - " cur_lon = pset.lon[0]\n", - " cur_lat = pset.lat[0]\n", - "\n", - " # release CTD particle\n", - " pset_CTD = ParticleSet.from_list(fieldset=fieldset, pclass=CTDParticle, lon=[cur_lon], lat=[cur_lat], depth=fieldset.z_start, time=time)\n", - "\n", - " # # release CTD particles OLD way all at once\n", - " # pset_CTD = ParticleSet.from_list(\n", - " # fieldset=fieldset, \n", - " # pclass=CTDParticle, \n", - " # lon=np.full(CTD_depth,cur_lon), \n", - " # lat=np.full(CTD_depth,cur_lat), \n", - " # depth=np.linspace(fieldset.mindepth, fieldset.maxdepth, num=CTD_depth),\n", - " # time=time,\n", - " # ) \n", - "\n", - " # Casting the SampleS and T functions to kernels\n", - " Cast_CTD_kernel = pset_CTD.Kernel(CTDcast) # Casting the CTDcast function to a kernel\n", - " Sample_S_kernel = pset_CTD.Kernel(SampleS) # Casting the SampleS function to a kernel\n", - " Sample_T_kernel = pset_CTD.Kernel(SampleT) # similar for temperature\n", - " # Choose which kernels to use for CTD\n", - " CTD_kernels = Sample_S_kernel + Sample_T_kernel + Cast_CTD_kernel\n", - "\n", - " # record the temperature and salinity of the particles\n", - " pset_CTD.execute(CTD_kernels, runtime=outputdt, dt=timedelta(seconds=1))\n", - "\n", - " # write the CTD particles to the output file\n", - " print(\"CTD time!\")\n", - " ctd_output_file.write(pset_CTD, time)\n", - "\n", - " # write the initialised particles and the advected particles\n", - " output_file.write(pset, time)\n", - "\n", - " pset.execute(kernels, runtime=outputdt, dt=timedelta(minutes=60))\n", - " # print(f\"Writing time {time}\")\n", - "\n", - "output_file.write(pset, time + outputdt)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/nethome/0448257/.conda/envs/Parcels/lib/python3.11/site-packages/xarray/coding/times.py:618: RuntimeWarning: invalid value encountered in cast\n", - " int_num = np.asarray(num, dtype=np.int64)\n" - ] - } - ], - "source": [ - "import xarray as xr\n", - "# Open and combine the CTD output files\n", - "da = xr.open_zarr(\"CTD_test_1.zarr\")\n", - "for i in range(2, station+1):\n", - " da = xr.concat([da, xr.open_zarr(f\"CTD_test_{i}.zarr\")], \"obs\")\n", - "# Write the combined output to a netcdf file\n", - "da.to_netcdf(\"CTD_test.nc\", mode=\"w\")\n", - "da.close()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Do some plotting to check output" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import xarray as xr\n", - "from mpl_toolkits.mplot3d import Axes3D\n", - "\n", - "# Open output and read to x, y, z\n", - "ds = xr.open_zarr(\"ADCP_CTD_test.zarr\")\n", - "# ds = xr.open_zarr('tmp.zarr')\n", - "x = ds[\"lon\"][:].squeeze()\n", - "y = ds[\"lat\"][:].squeeze()\n", - "z = ds[\"z\"][:].squeeze()\n", - "U = ds[\"U\"][:].squeeze()\n", - "V = ds[\"V\"][:].squeeze()\n", - "# salinity = ds[\"salinity\"][:].squeeze()\n", - "# temperature = ds[\"temperature\"][:].squeeze()\n", - "ds.close()\n", - "\n", - "# Plot Particle depth\n", - "fig = plt.figure(figsize=(13, 10))\n", - "ax = plt.axes(projection=\"3d\")\n", - "cb = ax.scatter(x, y, z, c=V, s=20, marker=\"o\")\n", - "ax.set_xlabel(\"Longitude\")\n", - "ax.set_ylabel(\"Latitude\")\n", - "ax.set_zlabel(\"Depth (m)\")\n", - "ax.set_zlim(np.max(z), 0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot CTD casts" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/nethome/0448257/.conda/envs/Parcels/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast\n", - " flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype(\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Open output and read to x, y, z\n", - "ds = xr.open_dataset(\"CTD_test.nc\")\n", - "x = ds[\"lon\"][:].squeeze()\n", - "y = ds[\"lat\"][:].squeeze()\n", - "z = ds[\"z\"][:].squeeze()\n", - "U = ds[\"U\"][:].squeeze()\n", - "V = ds[\"V\"][:].squeeze()\n", - "# salinity = ds[\"salinity\"][:].squeeze()\n", - "# temperature = ds[\"temperature\"][:].squeeze()\n", - "ds.close()\n", - "\n", - "# Plot Particle depth\n", - "fig = plt.figure(figsize=(13, 10))\n", - "ax = plt.axes(projection=\"3d\")\n", - "cb = ax.scatter(x, y, z, c=U, s=20, marker=\"o\")\n", - "ax.set_xlabel(\"Longitude\")\n", - "ax.set_ylabel(\"Latitude\")\n", - "ax.set_zlabel(\"Depth (m)\")\n", - "ax.set_zlim(np.max(z), 0)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Dimensions: (trajectory: 1, obs: 1)\n", - "Coordinates:\n", - " * obs (obs) int32 0\n", - " * trajectory (trajectory) int64 32\n", - "Data variables:\n", - " U (trajectory, obs) float32 dask.array\n", - " V (trajectory, obs) float32 dask.array\n", - " lat (trajectory, obs) float32 dask.array\n", - " lon (trajectory, obs) float32 dask.array\n", - " time (trajectory, obs) datetime64[ns] dask.array\n", - " z (trajectory, obs) float32 dask.array\n", - "Attributes:\n", - " Conventions: CF-1.6/CF-1.7\n", - " feature_type: trajectory\n", - " ncei_template_version: NCEI_NetCDF_Trajectory_Template_v2.0\n", - " parcels_mesh: spherical\n", - " parcels_version: 2.4.2\n", - "3\n" - ] - } - ], - "source": [ - "\n", - "da = xr.open_zarr(\"CTD_test_2.zarr\")\n", - "print(da)\n", - "da.close()\n", - "print(station)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "py3_parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/OLD/ctdCMEMS.ipynb b/src/OLD/ctdCMEMS.ipynb deleted file mode 100644 index 2f60d385..00000000 --- a/src/OLD/ctdCMEMS.ipynb +++ /dev/null @@ -1,296 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Local ADCP Particle test with CMEMS data" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from datetime import timedelta\n", - "import numpy as np\n", - "import math\n", - "\n", - "from parcels import (\n", - " AdvectionRK4,\n", - " ErrorCode,\n", - " FieldSet,\n", - " JITParticle,\n", - " ScipyParticle,\n", - " ParticleSet,\n", - " Variable,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read sample input data" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1\n", - "5727\n" - ] - } - ], - "source": [ - "# Load the CMEMS data (3 days manually downloaded)\n", - "example_dataset_folder = \"../Data\"\n", - "filenames = {\n", - " \"U\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"V\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"S\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-so_hcst_R20210113.nc\",\n", - " \"T\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-thetao_hcst_R20210113.nc\",\n", - "}\n", - "variables = {'U': 'uo', 'V': 'vo', 'S':'so', 'T':'thetao'}\n", - "dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth':'depth'}\n", - "\n", - "# create the fieldset and set interpolation methods\n", - "fieldset = FieldSet.from_netcdf(filenames, variables, dimensions, time_periodic=timedelta(days=3))\n", - "fieldset.T.interp_method = \"linear_invdist_land_tracer\"\n", - "fieldset.S.interp_method = \"linear_invdist_land_tracer\"\n", - "\n", - "# determin top and bottom layer in the hydrodynamic data\n", - "fieldset.mindepth = math.ceil(fieldset.U.depth[0])\n", - "fieldset.maxdepth = math.floor(fieldset.U.depth[-1])\n", - "\n", - "# set initial location\n", - "ini_lat = -31\n", - "ini_lon = 32" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create particles and initalize" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING: dt or runtime are zero, or endtime is equal to Particle.time. The kernels will be executed once, without incrementing time\n" - ] - } - ], - "source": [ - "# Create and initialize Variable particles to sample the ocean\n", - "class SampleParticleInitZero(ScipyParticle):\n", - " \"\"\"Define a new particle class with Variables init Nan\"\"\" \n", - " salinity = Variable(\"salinity\", initial=np.nan)\n", - " temperature = Variable(\"temperature\", initial=np.nan)\n", - " U = Variable('U', dtype=np.float32, initial=np.nan)\n", - " V = Variable('V', dtype=np.float32, initial=np.nan)\n", - "\n", - "# define function sampling Salinity \n", - "def SampleS(particle, fieldset, time):\n", - " particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# define function sampling Temperature \n", - "def SampleT(particle, fieldset, time):\n", - " particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# define function sampling u and v as in https://docs.oceanparcels.org/en/latest/examples/tutorial_sampling.html\n", - "def SampleVel_correct(particle, fieldset, time):\n", - " particle.U, particle.V = fieldset.UV[time, particle.depth, particle.lat, particle.lon, particle]\n", - "\n", - "# Attempt for CTD like particle \n", - "depthnum = fieldset.maxdepth - fieldset.mindepth\n", - "# Initiate CTD like particle set \n", - "pset = ParticleSet.from_list(\n", - " fieldset=fieldset, pclass=SampleParticleInitZero, lon=np.full(depthnum,ini_lon), lat=np.full(depthnum,ini_lat), depth=np.linspace(fieldset.mindepth, fieldset.maxdepth, num=depthnum)\n", - ")\n", - "Sample_S_kernel = pset.Kernel(SampleS) # Casting the SampleS function to a kernel.\n", - "Sample_T_kernel = pset.Kernel(SampleT) # similar for temperature\n", - "SampleVel_kernel = pset.Kernel(SampleVel_correct) # Casting the function to a kernel.\n", - "\n", - "# only execute the sampling kernels to record the init values of the particles\n", - "pset.execute(Sample_S_kernel, dt=0)\n", - "pset.execute(Sample_T_kernel, dt=0)\n", - "pset.execute(SampleVel_correct, dt=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Determine ship course and add as kernel " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# change advection to ship movement\n", - "# Cruising speed Pelagia (and Anna Weber) is 9 knp https://www.nioz.nl/application/files/3614/9744/8746/Pelagia_Technical_specifications-2016.pdf\n", - "# survey speed nog iets lager? Zoals bij https://schmidtocean.org/rv-falkor/ship-specifications/\n", - "# 7 knp = 13 km/h = 3.6 m/s\n", - "\n", - "def ShipVel(particle, fieldset, time):\n", - " speed = 3.6\n", - " target_lat = -50\n", - " target_lon = 20\n", - " # determine ship direction\n", - " heading = math.sqrt((target_lat - particle.lat)**2 + (target_lon - particle.lon)**2)\n", - " # calculate e/w and n/s speed (m/s)\n", - " lat_add = (target_lat - particle.lat)/(heading/speed)\n", - " lon_add = (target_lon - particle.lon)/(heading/speed)\n", - " # convert to lat/lon\n", - " lat_add_deg = lat_add / 1.11e5\n", - " lon_add_deg = lon_add / (1.11e5 * math.cos(particle.lat * math.pi / 180))\n", - " # add to particle position\n", - " particle.lat += lat_add_deg * particle.dt\n", - " particle.lon += lon_add_deg * particle.dt\n", - "\n", - "# cast the ships velocity function to a kernel object\n", - "ShipVel_kernel = pset.Kernel(ShipVel)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run simulation" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO: Output files are stored in CTDtest.zarr.\n", - "100%|██████████| 86400.0/86400.0 [01:46<00:00, 812.82it/s] \n" - ] - } - ], - "source": [ - "# set output file name and dt\n", - "output_file = pset.ParticleFile(\n", - " name=\"CTDtest.zarr\", # the file name\n", - " outputdt=timedelta(hours=6), # the time step of the outputs\n", - ")\n", - "\n", - "# Choose which kernels to use\n", - "kernels = ShipVel_kernel + Sample_S_kernel + Sample_T_kernel + SampleVel_kernel\n", - "\n", - "# Execute code and save to file \n", - "pset.execute(\n", - " kernels, \n", - " runtime=timedelta(days=1), # the total length of the run\n", - " dt=timedelta(minutes=60), # the timestep of the kernel\n", - " output_file=output_file,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Do some plotting to check output" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import xarray as xr\n", - "\n", - "# Open output and read to x, y, z\n", - "ds = xr.open_zarr(\"CTDtest.zarr\")\n", - "x = ds[\"lon\"][:].values.flatten()\n", - "y = ds[\"lat\"][:].values.flatten()\n", - "z = ds[\"z\"][:].values.flatten()\n", - "U = ds[\"U\"][:].values.flatten()\n", - "V = ds[\"V\"][:].values.flatten()\n", - "salinity = ds[\"salinity\"][:].values.flatten()\n", - "temperature = ds[\"temperature\"][:].values.flatten()\n", - "valid_particles = salinity>0\n", - "ds.close()\n", - "\n", - "# Plot Particle depth\n", - "fig = plt.figure(figsize=(15, 10))\n", - "ax = plt.axes(projection=\"3d\")\n", - "# cb = ax.scatter(x, y, z, c=salinity, s=20, marker=\"o\")\n", - "cb = ax.scatter(x[valid_particles], y[valid_particles], z[valid_particles], c=U[valid_particles], s=20, marker=\"o\")\n", - "ax.set_title('Zonal velocity at CTD measurement locations', size = 14)\n", - "ax.set_xlabel(\"Longitude\")\n", - "ax.set_ylabel(\"Latitude\")\n", - "ax.set_zlabel(\"Depth (m)\")\n", - "ax.set_zlim(np.max(z), 0)\n", - "fig.colorbar(cb, shrink=0.7)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "py3_parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/OLD/leafmap_example.ipynb b/src/OLD/leafmap_example.ipynb deleted file mode 100644 index 7377c680..00000000 --- a/src/OLD/leafmap_example.ipynb +++ /dev/null @@ -1,716 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Local ADCP Particle test with CMEMS data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "parcels environment, at the moment developer: https://docs.oceanparcels.org/en/latest/installation.html\n", - "with conda install -c conda-forge leafmap ipyleaflet \n", - "reduced geojson geopandas???" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Use interactive map to determine ship course " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "3a6fa9d3c17b4b3a94e12bdabebc0a04", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Map(center=[0, -100], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zoom_out_te…" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import leafmap \n", - "from ipyleaflet import Rectangle \n", - " \n", - "m = leafmap.leafmap.Map(center=(0, -100), zoom=5) \n", - "# Draw a rectange to indicate region where data will be collected \n", - "m.add_layer(Rectangle(bounds=((5, -125), (-10, -75)))) \n", - "# Add a point at port of departure: Puntarenas, Costa Rica \n", - "m.add_marker([9.97625, -84.83836]) \n", - "m " - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([ 2., 6., 10., 14., 18., 22., 26., 30., 34., 38., 42.,\n", - " 46., 50., 54., 58., 62., 66., 70., 74., 78., 82., 86.,\n", - " 90., 94., 98., 102., 106., 110., 114., 118., 122., 126., 130.,\n", - " 134., 138., 142., 146., 150.])" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "np.linspace(2, 150, num=38)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[-87.011719, 2.899153], [-87.626953, -3.337954], [-100.195313, -2.372369], [-96.591797, 3.337954]]\n" - ] - } - ], - "source": [ - "# Save data and read it back to get coordinates\n", - "line = m.user_rois\n", - "coords = line.get('features')[0].get('geometry').get('coordinates')\n", - "# import geojson\n", - "# m.save_draw_features(\"data.geojson\")\n", - "# with open('./data.geojson') as f:\n", - "# gj = geojson.load(f)\n", - "# features = gj['features']\n", - "# coords = features[0].geometry.coordinates\n", - "print(coords) " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "24.0" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "86400/3600" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[868.9349120887674, 781.0994283573966, 683.4303161156888, 889.0583972945243, 783.0875836005266, 1044.7548529427208, 966.2714290317624, 971.5508106070295, 718.6857702835648, 962.1652999572291, 806.6225218889897, 680.2915369286145, 923.2245417902343, 958.1489537614556]\n" - ] - }, - { - "data": { - "text/plain": [ - "12037.326354648507" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import math\n", - "def haversine(lon1, lat1, lon2, lat2):\n", - " \"\"\"\n", - " Calculate the great circle distance in kilometers between two points\n", - " on the earth (specified in decimal degrees)\n", - " \"\"\"\n", - " # convert decimal degrees to radians\n", - " lon1, lat1, lon2, lat2 = map(math.radians, [lon1, lat1, lon2, lat2])\n", - " \n", - " # haversine formula\n", - " dlon = lon2 - lon1\n", - " dlat = lat2 - lat1\n", - " a = (math.sin(dlat/2))**2 + (math.cos(lat1) ) * (math.cos(lat2) ) * ((math.sin(dlon/2))**2)\n", - " c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))\n", - " r = 6371 # Radius of earth in kilometers. Determines return value units.\n", - " return c * r\n", - "\n", - "coords = [[-85.429688, 2.547988], [-93.251953, 2.547988], [-100.283203, 2.635789], [-106.435547, 2.723583], [-114.433594, 3.074695], [-121.464844, 2.547988], [-130.869141, 2.460181], [-130.693359, -6.227934], [-121.904297, -6.402648], [-115.400391, -6.402648], [-106.699219, -6.140555], [-99.404297, -6.053161], [-93.251953, -6.053161], [-84.902344, -6.140555], [-84.375, 2.460181]]\n", - "distances = []\n", - "for i in range(len(coords)-1):\n", - " distance = haversine(coords[i][0], coords[i][1], coords[i+1][0], coords[i+1][1])\n", - " distances.append(distance)\n", - "\n", - "print(distances)\n", - "sum(distances)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## OLD stuff" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt \n", - "\n", - "import pyproj\n", - "from shapely.geometry.polygon import Polygon\n", - "from shapely.geometry import shape, Point" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Compute ship route as intermediate points beteen CTD stations" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [], - "source": [ - "# Initialize lists to store intermediate points\n", - "sample_lons = []\n", - "sample_lats = []\n", - "\n", - "# Loop over station coordinates and calculate intermediate points\n", - "i = 0\n", - "for i in (range(len(coords)-1)):\n", - " startlong = coords[i][0]\n", - " startlat = coords[i][1]\n", - " endlong = coords[i+1][0]\n", - " endlat = coords[i+1][1]\n", - "\n", - " # calculate line string along path with segments every TODO hour or 5 min = 3.6*60*5 = 1080 m, for now 5 midpoints\n", - " g = pyproj.Geod(ellps='WGS84')\n", - " # r = g.inv_intermediate(startlong, startlat, endlong, endlat, del_s = 1080)\n", - " r = g.inv_intermediate(startlong, startlat, endlong, endlat, 5, initial_idx=0)\n", - " # store all intermediate points \n", - " sample_lons.append(r.lons) # stored as a list of arrays\n", - " sample_lats.append(r.lats)\n", - "\n", - "# initial_idx will add begin point to each list (but not end point to avoid dubbling) so add final endpoint manually\n", - "sample_lons = np.append(np.hstack(sample_lons), endlong)\n", - "sample_lats = np.append(np.hstack(sample_lats), endlat)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read sample input data" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from datetime import timedelta\n", - "import math\n", - "\n", - "from parcels import (\n", - " FieldSet,\n", - " JITParticle,\n", - " ParticleSet,\n", - " Variable,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-108.457031 3.337954\n" - ] - } - ], - "source": [ - "# Load the CMEMS data (3 days manually downloaded)\n", - "example_dataset_folder = \"../Data\"\n", - "filenames = {\n", - " \"U\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"V\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-uovo_hcst_R20210113.nc\",\n", - " \"S\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-so_hcst_R20210113.nc\",\n", - " \"T\": f\"{example_dataset_folder}/glo12_rg_1d-m_2021010*_3D-thetao_hcst_R20210113.nc\",\n", - "}\n", - "variables = {'U': 'uo', 'V': 'vo', 'S':'so', 'T':'thetao'}\n", - "dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth':'depth'}\n", - "\n", - "# create the fieldset and set interpolation methods\n", - "fieldset = FieldSet.from_netcdf(filenames, variables, dimensions, time_periodic=timedelta(days=3))\n", - "fieldset.T.interp_method = \"linear_invdist_land_tracer\"\n", - "fieldset.S.interp_method = \"linear_invdist_land_tracer\"\n", - "\n", - "# determin top and bottom layer in the hydrodynamic data\n", - "fieldset.mindepth = math.ceil(fieldset.U.depth[0])\n", - "fieldset.maxdepth = math.floor(fieldset.U.depth[-1])\n", - "\n", - "ini_lon = coords[0][0]\n", - "ini_lat = coords[0][1]\n", - "print(ini_lon, ini_lat)" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO: Compiled ArraySampleParticleSampleVel_correct ==> /tmp/parcels-382783/lib348184e9bb192099d44b70860e7789a1_0.so\n" - ] - } - ], - "source": [ - "# Create and initialize Variable particles to sample the ocean\n", - "class SampleParticle(JITParticle):\n", - " \"\"\"Define a new particle class with Variables\"\"\"\n", - " U = Variable('U', dtype=np.float32, initial=0.0)\n", - " V = Variable('V', dtype=np.float32, initial=0.0)\n", - "\n", - "# define function sampling u and v as in https://docs.oceanparcels.org/en/latest/examples/tutorial_sampling.html\n", - "def SampleVel_correct(particle, fieldset, time):\n", - " # TODO attention: samples particle velocity in units of the mesh (deg/s or m/s)\n", - " particle.U, particle.V = fieldset.UV[time, particle.depth, particle.lat, particle.lon, particle]\n", - "\n", - "# Attempt for ADCP like particle TODO accurate depths \n", - "depthnum = 5\n", - "# Initiate ADCP like particle set \n", - "pset = ParticleSet.from_list(\n", - " fieldset=fieldset, pclass=SampleParticle, lon=np.full(depthnum,ini_lon), lat=np.full(depthnum,ini_lat), depth=np.linspace(5, 1000, num=depthnum)\n", - ")\n", - "\n", - "# Casting the function to a kernel\n", - "SampleVel_kernel = pset.Kernel(SampleVel_correct) \n", - "\n", - "# only execute the sampling kernels to record the init values of the particles\n", - "pset.execute(SampleVel_kernel, dt=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run simulation" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CTD time!\n", - "367200.0\n", - "370800.0\n", - "374400.0\n", - "378000.0\n", - "381600.0\n", - "CTD time!\n", - "385200.0\n", - "388800.0\n", - "392400.0\n", - "396000.0\n", - "399600.0\n", - "CTD time!\n", - "403200.0\n" - ] - } - ], - "source": [ - "# create a ParticleFile to store the output\n", - "# Note: Do not specify the outputdt yet, so we can manually write the output\n", - "output_file = pset.ParticleFile(name=\"LeafmapADCPtest.zarr\")\n", - "\n", - "# write the particle data every hour\n", - "outputdt = timedelta(hours=1).total_seconds()\n", - "\n", - "# Choose which kernels to use\n", - "kernels = SampleVel_kernel\n", - "\n", - "c = 0\n", - "for i in range(len(sample_lons)):\n", - " # write the initialised particles \n", - " output_file.write(pset, time)\n", - " \n", - " if sample_lons[i] == coords[c][0]:\n", - " print('CTD time!')\n", - " c += 1\n", - "\n", - " # set the particle lon and lat\n", - " pset.lon[:] = sample_lons[i]\n", - " pset.lat[:] = sample_lats[i]\n", - " pset.time[:] += outputdt\n", - " time = pset.time[0]\n", - " print(pset.time[0])\n", - "\n", - " # execute the kernels i.e. sample at the new location\n", - " # pset.execute(kernels, dt=outputdt)\n", - " # print(f\"Writing time {time}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[-117.64258 -117.64258 -117.64258 -117.64258 -117.64258]\n" - ] - } - ], - "source": [ - "198000-194400 \n", - "print(pset.lon)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Do some plotting to check output" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import xarray as xr\n", - "from mpl_toolkits.mplot3d import Axes3D\n", - "\n", - "# Open output and read to x, y, z\n", - "ds = xr.open_zarr(\"LeafmapADCPtest.zarr\")\n", - "# ds = xr.open_zarr('tmp.zarr')\n", - "x = ds[\"lon\"][:].squeeze()\n", - "y = ds[\"lat\"][:].squeeze()\n", - "z = ds[\"z\"][:].squeeze()\n", - "U = ds[\"U\"][:].squeeze()\n", - "V = ds[\"V\"][:].squeeze()\n", - "ds.close()\n", - "\n", - "# Plot Particle depth\n", - "fig = plt.figure(figsize=(13, 10))\n", - "ax = plt.axes(projection=\"3d\")\n", - "cb = ax.scatter(x, y, z, c=V, s=20, marker=\"o\")\n", - "ax.set_xlabel(\"Longitude\")\n", - "ax.set_ylabel(\"Latitude\")\n", - "ax.set_zlabel(\"Depth (m)\")\n", - "ax.set_zlim(np.max(z), 0)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Dimensions: (trajectory: 20, obs: 7)\n", - "Coordinates:\n", - " * obs (obs) int32 0 1 2 3 4 5 6\n", - " * trajectory (trajectory) int64 40 41 42 43 44 45 46 ... 53 54 55 56 57 58 59\n", - "Data variables:\n", - " U (trajectory, obs) float32 dask.array\n", - " V (trajectory, obs) float32 dask.array\n", - " lat (trajectory, obs) float32 dask.array\n", - " lon (trajectory, obs) float32 dask.array\n", - " time (trajectory, obs) datetime64[ns] dask.array\n", - " z (trajectory, obs) float32 dask.array\n", - "Attributes:\n", - " Conventions: CF-1.6/CF-1.7\n", - " feature_type: trajectory\n", - " ncei_template_version: NCEI_NetCDF_Trajectory_Template_v2.0\n", - " parcels_mesh: spherical\n", - " parcels_version: 2.4.2\n" - ] - } - ], - "source": [ - "print(ds)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "shapes = []\n", - "for feature in features:\n", - " shapes.append(shape(feature['geometry']))\n", - " \n", - "lons = []\n", - "lats = []\n", - "npts_line = 1\n", - "\n", - "for set_shape in shapes:\n", - " # If the release location is a point\n", - " if set_shape.type.lower() == 'point':\n", - " lons.append(set_shape.coords.xy[0][0])\n", - " lats.append(set_shape.coords.xy[1][0])\n", - " \n", - " # If the release location is a linestring (could be multiple lines)\n", - " elif set_shape.type.lower() == 'linestring':\n", - " pointlist_lon = set_shape.coords.xy[0]\n", - " pointlist_lat = set_shape.coords.xy[1]\n", - "\n", - " for i in range(len(pointlist_lon)-1):\n", - " point1 = [pointlist_lon[i], pointlist_lat[i]]\n", - " point2 = [pointlist_lon[i+1], pointlist_lat[i+1]]\n", - " lons.append(np.linspace(point1[0], point2[0], npts_line, endpoint=True))\n", - " lats.append(np.linspace(point1[1], point2[1], npts_line, endpoint=True))\n", - "\n", - "lons = np.hstack(np.asarray(lons))\n", - "lats = np.hstack(np.asarray(lats))\n", - "\n", - "# plt.scatter(lons, lats, s=2)\n", - "# plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Compute distance travelled by ship" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from math import radians, cos, sin, asin, sqrt\n", - "\n", - "def haversine(lon1, lat1, lon2, lat2):\n", - " \"\"\"\n", - " Calculate the great circle distance in kilometers between two points \n", - " on the earth (specified in decimal degrees)\n", - " \"\"\"\n", - " # convert decimal degrees to radians \n", - " lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])\n", - "\n", - " # haversine formula \n", - " dlon = lon2 - lon1 \n", - " dlat = lat2 - lat1 \n", - " a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2\n", - " c = 2 * asin(sqrt(a)) \n", - " r = 6371 # Radius of earth in kilometers. Use 3956 for miles. Determines return value units.\n", - " return c * r" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create particles and initalize" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "### Determine ship course and add as kernel " - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "ename": "NotImplementedError", - "evalue": "Subscript not implemented for object type ConstNode", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNotImplementedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m/nethome/0448257/Virtual_ship_classroom/adcpCMEMSleafmap.ipynb Cell 15\u001b[0m line \u001b[0;36m6\n\u001b[1;32m 59\u001b[0m particle\u001b[39m.\u001b[39mlon \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m lon_add_deg \u001b[39m*\u001b[39m particle\u001b[39m.\u001b[39mdt\n\u001b[1;32m 60\u001b[0m \u001b[39m# update loc if close to target TODO target reached\u001b[39;00m\n\u001b[1;32m 61\u001b[0m \u001b[39m# if target_lat - particle.lat < 3.6*3600/1.11e5 or target_lon - particle.lon < 3.6*3600/(1.11e5 * math.cos(particle.lat * math.pi / 180)):\u001b[39;00m\n\u001b[1;32m 62\u001b[0m \u001b[39m# loc += 1\u001b[39;00m\n\u001b[1;32m 63\u001b[0m \u001b[39m# speed = 3.6\u001b[39;00m\n\u001b[1;32m 64\u001b[0m \n\u001b[1;32m 65\u001b[0m \u001b[39m# cast the ships velocity function to a kernel object\u001b[39;00m\n\u001b[0;32m---> 66\u001b[0m ShipVel_kernel \u001b[39m=\u001b[39m pset\u001b[39m.\u001b[39;49mKernel(ShipVel)\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/particleset/particlesetsoa.py:722\u001b[0m, in \u001b[0;36mParticleSetSOA.Kernel\u001b[0;34m(self, pyfunc, c_include, delete_cfiles)\u001b[0m\n\u001b[1;32m 714\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(pyfunc, \u001b[39mlist\u001b[39m):\n\u001b[1;32m 715\u001b[0m \u001b[39mreturn\u001b[39;00m Kernel\u001b[39m.\u001b[39mfrom_list(\n\u001b[1;32m 716\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfieldset,\n\u001b[1;32m 717\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcollection\u001b[39m.\u001b[39mptype,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 720\u001b[0m delete_cfiles\u001b[39m=\u001b[39mdelete_cfiles,\n\u001b[1;32m 721\u001b[0m )\n\u001b[0;32m--> 722\u001b[0m \u001b[39mreturn\u001b[39;00m Kernel(\n\u001b[1;32m 723\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfieldset,\n\u001b[1;32m 724\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mcollection\u001b[39m.\u001b[39;49mptype,\n\u001b[1;32m 725\u001b[0m pyfunc\u001b[39m=\u001b[39;49mpyfunc,\n\u001b[1;32m 726\u001b[0m c_include\u001b[39m=\u001b[39;49mc_include,\n\u001b[1;32m 727\u001b[0m delete_cfiles\u001b[39m=\u001b[39;49mdelete_cfiles,\n\u001b[1;32m 728\u001b[0m )\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/kernel/kernelsoa.py:98\u001b[0m, in \u001b[0;36mKernelSOA.__init__\u001b[0;34m(self, fieldset, ptype, pyfunc, funcname, funccode, py_ast, funcvars, c_include, delete_cfiles)\u001b[0m\n\u001b[1;32m 96\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mptype\u001b[39m.\u001b[39muses_jit:\n\u001b[1;32m 97\u001b[0m kernelgen \u001b[39m=\u001b[39m KernelGenerator(fieldset, ptype)\n\u001b[0;32m---> 98\u001b[0m kernel_ccode \u001b[39m=\u001b[39m kernelgen\u001b[39m.\u001b[39;49mgenerate(deepcopy(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mpy_ast),\n\u001b[1;32m 99\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfuncvars)\n\u001b[1;32m 100\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfield_args \u001b[39m=\u001b[39m kernelgen\u001b[39m.\u001b[39mfield_args\n\u001b[1;32m 101\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mvector_field_args \u001b[39m=\u001b[39m kernelgen\u001b[39m.\u001b[39mvector_field_args\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/compilation/codegenerator.py:526\u001b[0m, in \u001b[0;36mAbstractKernelGenerator.generate\u001b[0;34m(self, py_ast, funcvars)\u001b[0m\n\u001b[1;32m 523\u001b[0m py_ast \u001b[39m=\u001b[39m TupleSplitter()\u001b[39m.\u001b[39mvisit(py_ast)\n\u001b[1;32m 525\u001b[0m \u001b[39m# Generate C-code for all nodes in the Python AST\u001b[39;00m\n\u001b[0;32m--> 526\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mvisit(py_ast)\n\u001b[1;32m 527\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mccode \u001b[39m=\u001b[39m py_ast\u001b[39m.\u001b[39mccode\n\u001b[1;32m 529\u001b[0m \u001b[39m# Insert variable declarations for non-instrinsics\u001b[39;00m\n\u001b[1;32m 530\u001b[0m \u001b[39m# Make sure that repeated variables are not declared more than\u001b[39;00m\n\u001b[1;32m 531\u001b[0m \u001b[39m# once. If variables occur in multiple Kernels, give a warning\u001b[39;00m\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/ast.py:418\u001b[0m, in \u001b[0;36mNodeVisitor.visit\u001b[0;34m(self, node)\u001b[0m\n\u001b[1;32m 416\u001b[0m method \u001b[39m=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mvisit_\u001b[39m\u001b[39m'\u001b[39m \u001b[39m+\u001b[39m node\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m\n\u001b[1;32m 417\u001b[0m visitor \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39m(\u001b[39mself\u001b[39m, method, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mgeneric_visit)\n\u001b[0;32m--> 418\u001b[0m \u001b[39mreturn\u001b[39;00m visitor(node)\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/compilation/codegenerator.py:926\u001b[0m, in \u001b[0;36mArrayKernelGenerator.visit_FunctionDef\u001b[0;34m(self, node)\u001b[0m\n\u001b[1;32m 924\u001b[0m \u001b[39mfor\u001b[39;00m stmt \u001b[39min\u001b[39;00m node\u001b[39m.\u001b[39mbody:\n\u001b[1;32m 925\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mhasattr\u001b[39m(stmt, \u001b[39m'\u001b[39m\u001b[39mvalue\u001b[39m\u001b[39m'\u001b[39m) \u001b[39mand\u001b[39;00m \u001b[39mtype\u001b[39m(stmt\u001b[39m.\u001b[39mvalue) \u001b[39mis\u001b[39;00m ast\u001b[39m.\u001b[39mStr): \u001b[39m# ignore docstrings\u001b[39;00m\n\u001b[0;32m--> 926\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mvisit(stmt)\n\u001b[1;32m 928\u001b[0m \u001b[39m# Create function declaration and argument list\u001b[39;00m\n\u001b[1;32m 929\u001b[0m decl \u001b[39m=\u001b[39m c\u001b[39m.\u001b[39mStatic(c\u001b[39m.\u001b[39mDeclSpecifier(c\u001b[39m.\u001b[39mValue(\u001b[39m\"\u001b[39m\u001b[39mStatusCode\u001b[39m\u001b[39m\"\u001b[39m, node\u001b[39m.\u001b[39mname), spec\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39minline\u001b[39m\u001b[39m'\u001b[39m))\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/ast.py:418\u001b[0m, in \u001b[0;36mNodeVisitor.visit\u001b[0;34m(self, node)\u001b[0m\n\u001b[1;32m 416\u001b[0m method \u001b[39m=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mvisit_\u001b[39m\u001b[39m'\u001b[39m \u001b[39m+\u001b[39m node\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m\n\u001b[1;32m 417\u001b[0m visitor \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39m(\u001b[39mself\u001b[39m, method, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mgeneric_visit)\n\u001b[0;32m--> 418\u001b[0m \u001b[39mreturn\u001b[39;00m visitor(node)\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/compilation/codegenerator.py:649\u001b[0m, in \u001b[0;36mAbstractKernelGenerator.visit_Assign\u001b[0;34m(self, node)\u001b[0m\n\u001b[1;32m 647\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mvisit_Assign\u001b[39m(\u001b[39mself\u001b[39m, node):\n\u001b[1;32m 648\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mvisit(node\u001b[39m.\u001b[39mtargets[\u001b[39m0\u001b[39m])\n\u001b[0;32m--> 649\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mvisit(node\u001b[39m.\u001b[39;49mvalue)\n\u001b[1;32m 650\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(node\u001b[39m.\u001b[39mvalue, ast\u001b[39m.\u001b[39mList):\n\u001b[1;32m 651\u001b[0m \u001b[39m# Detect in-place initialisation of multi-dimensional arrays\u001b[39;00m\n\u001b[1;32m 652\u001b[0m tmp_node \u001b[39m=\u001b[39m node\u001b[39m.\u001b[39mvalue\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/ast.py:418\u001b[0m, in \u001b[0;36mNodeVisitor.visit\u001b[0;34m(self, node)\u001b[0m\n\u001b[1;32m 416\u001b[0m method \u001b[39m=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mvisit_\u001b[39m\u001b[39m'\u001b[39m \u001b[39m+\u001b[39m node\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m\n\u001b[1;32m 417\u001b[0m visitor \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39m(\u001b[39mself\u001b[39m, method, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mgeneric_visit)\n\u001b[0;32m--> 418\u001b[0m \u001b[39mreturn\u001b[39;00m visitor(node)\n", - "File \u001b[0;32m~/.conda/envs/Parcels/lib/python3.11/site-packages/parcels/compilation/codegenerator.py:717\u001b[0m, in \u001b[0;36mAbstractKernelGenerator.visit_Subscript\u001b[0;34m(self, node)\u001b[0m\n\u001b[1;32m 715\u001b[0m node\u001b[39m.\u001b[39mccode \u001b[39m=\u001b[39m node\u001b[39m.\u001b[39mvalue\u001b[39m.\u001b[39m\u001b[39m__getitem__\u001b[39m(node\u001b[39m.\u001b[39mslice\u001b[39m.\u001b[39mccode)\u001b[39m.\u001b[39mccode\n\u001b[1;32m 716\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(node\u001b[39m.\u001b[39mvalue, IntrinsicNode):\n\u001b[0;32m--> 717\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mNotImplementedError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mSubscript not implemented for object type \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mtype\u001b[39m(node\u001b[39m.\u001b[39mvalue)\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[1;32m 718\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 719\u001b[0m node\u001b[39m.\u001b[39mccode \u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mnode\u001b[39m.\u001b[39mvalue\u001b[39m.\u001b[39mccode\u001b[39m}\u001b[39;00m\u001b[39m[\u001b[39m\u001b[39m{\u001b[39;00mnode\u001b[39m.\u001b[39mslice\u001b[39m.\u001b[39mccode\u001b[39m}\u001b[39;00m\u001b[39m]\u001b[39m\u001b[39m\"\u001b[39m\n", - "\u001b[0;31mNotImplementedError\u001b[0m: Subscript not implemented for object type ConstNode" - ] - } - ], - "source": [ - "# Predetermine ship route\n", - "# Cruising speed Pelagia (and Anna Weber) is 9 knp https://www.nioz.nl/application/files/3614/9744/8746/Pelagia_Technical_specifications-2016.pdf\n", - "# survey speed nog iets lager? Zoals bij https://schmidtocean.org/rv-falkor/ship-specifications/\n", - "# 7 knp = 13 km/h = 3.6 m/s\n", - "\n", - "coords \n", - "\n", - "speed = 3.6\n", - "cur_loc = fieldset.ship_loc\n", - "target_lat = fieldset.ship_lats[cur_loc]\n", - "# target_lon = fieldset.ship_coords[fieldset.ship_loc][1]\n", - "target_lat = 50\n", - "target_lon = 5\n", - "# # slow down when close to target\n", - "# if target_lat - particle.lat < 3.6*3600/1.11e5 or target_lon - particle.lon < 3.6*3600/(1.11e5 * math.cos(particle.lat * math.pi / 180)):\n", - "# speed = speed/4\n", - "\n", - "# calculate distance to target\n", - "# convert decimal degrees to radians \n", - "lon1, lat1, lon2, lat2 = map(math.radians, [particle.lon, particle.lat, target_lon, target_lat])\n", - "# haversine formula \n", - "dlon = lon2 - lon1 \n", - "dlat = lat2 - lat1 \n", - "a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2\n", - "c = 2 * math.asin(math.sqrt(a)) \n", - "r = 6371 # Radius of earth in kilometers. Use 3956 for miles. Determines return value units.\n", - "dist = c * r\n", - "print(dist)\n", - "\n", - "# determine ship direction\n", - "heading = math.sqrt((target_lat - particle.lat)**2 + (target_lon - particle.lon)**2)\n", - "\n", - "# # OR calculate bearing\n", - "# # Convert latitude and longitude to radians\n", - "# lat1 = math.radians(particle.lat[0])\n", - "# long1 = math.radians(particle.lon[0])\n", - "# lat2 = math.radians(target_lat)\n", - "# long2 = math.radians(target_lon)\n", - "\n", - "# # Calculate the bearing\n", - "# bearing = math.atan2(\n", - "# math.sin(long2 - long1) * math.cos(lat2),\n", - "# math.cos(lat1) * math.sin(lat2) - math.sin(lat1) * math.cos(lat2) * math.cos(long2 - long1)\n", - "# )\n", - "# # Convert the bearing to degrees\n", - "# bearing = math.degrees(bearing)\n", - "# # Make sure the bearing is positive\n", - "# bearing = (bearing + 360) % 360\n", - "\n", - "\n", - "# calculate e/w and n/s speed (m/s)\n", - "lat_add = (target_lat - particle.lat)/(heading/speed)\n", - "lon_add = (target_lon - particle.lon)/(heading/speed)\n", - "# convert to lat/lon\n", - "lat_add_deg = lat_add / 1.11e5\n", - "lon_add_deg = lon_add / (1.11e5 * math.cos(particle.lat * math.pi / 180))\n", - "# add to particle position\n", - "particle.lat += lat_add_deg * particle.dt\n", - "particle.lon += lon_add_deg * particle.dt\n", - "# update loc if close to target TODO target reached\n", - "# if target_lat - particle.lat < 3.6*3600/1.11e5 or target_lon - particle.lon < 3.6*3600/(1.11e5 * math.cos(particle.lat * math.pi / 180)):\n", - "# loc += 1\n", - "# speed = 3.6\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "py3_parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/cruise_simulation.py b/src/cruise_simulation.py deleted file mode 100755 index 7a6c1b3d..00000000 --- a/src/cruise_simulation.py +++ /dev/null @@ -1,219 +0,0 @@ -#!/usr/bin/env python3 -# Script to simulate a cruise with CTD casts and ADCP data -# Simulating ADCP data near Japan because of strong winds there - -import numpy as np -import pyproj -from datetime import timedelta -from shapely.geometry import Point, Polygon -from parcels import Field, FieldSet, JITParticle, Variable, ParticleSet - -# set initial location as lon-lat EW-NS -coords_input = [[-81.25, -11.83], [-77.8, -10,71]] - -# Load the CMEMS data (3 weeks for IPO) -dataset_folder = "/nethome/0448257/Data" -filenames = { - "U": f"{dataset_folder}/PeruCoast.nc", - "V": f"{dataset_folder}/PeruCoast.nc"} - # "S": f"{dataset_folder}/studentdata_S.nc", - # "T": f"{dataset_folder}/studentdata_T.nc"} -variables = {'U': 'uo', 'V': 'vo'} #, 'S':'so', 'T':'thetao'} -dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth':'depth'} - -# create the fieldset and set interpolation methods -fieldset = FieldSet.from_netcdf(filenames, variables, dimensions) -# fieldset.T.interp_method = "linear_invdist_land_tracer" -# fieldset.S.interp_method = "linear_invdist_land_tracer" - -# add bathymetry data to the fieldset for CTD cast -bathymetry_file = f"{dataset_folder}/GLO-MFC_001_024_mask_bathy.nc" -bathymetry_variables = ('bathymetry', 'deptho') -bathymetry_dimensions = {'lon': 'longitude', 'lat': 'latitude'} -bathymetry_field = Field.from_netcdf(bathymetry_file, bathymetry_variables, bathymetry_dimensions) -fieldset.add_field(bathymetry_field) -# read in data already -fieldset.computeTimeChunk(0,1) - -### Determine ship course as intermediate points between CTD stations - -# Initialize lists to store intermediate points -lons = [] -lats = [] - -# Loop over station coordinates and calculate intermediate points along great circle path -i = 0 -for i in (range(len(coords_input)-1)): - startlong = coords_input[i][0] - startlat = coords_input[i][1] - endlong = coords_input[i+1][0] - endlat = coords_input[i+1][1] - - # calculate line string along path with segments every 5 min = 3.6*60*5 = 1080 m (or switch comment for 2 midpoints) - g = pyproj.Geod(ellps='WGS84') - r = g.inv_intermediate(startlong, startlat, endlong, endlat, del_s = 1080) - # r = g.inv_intermediate(startlong, startlat, endlong, endlat, initial_idx=0, return_back_azimuth=False, npts=3) - lons.append(r.lons) # stored as a list of arrays - lats.append(r.lats) - -# initial_idx will add begin point to each list (but not end point to avoid dubbling) so add final endpoint manually -lons = np.append(np.hstack(lons), endlong) -lats = np.append(np.hstack(lats), endlat) - -# check if input sample locations are within data availability area, only save if so -#poly = Polygon([(west, north), (west, south), (east, south), (east, north)]) -poly = Polygon([(-83, -6), (-83, -12), (-78, -12), (-78, -6)]) -coords = [] -sample_lons = [] -sample_lats = [] -for coord in coords_input: - if poly.contains(Point(coord)): - coords.append(coord) -for i in range(len(lons)): - if poly.contains(Point(lons[i], lats[i])): - sample_lons.append(lons[i]) - sample_lats.append(lats[i]) - -### Define particles and sampling functions - -# Create ADCP like particles to sample the ocean -class ADCPParticle(JITParticle): - """Define a new particle class that does ADCP like measurements""" - U = Variable('U', dtype=np.float32, initial=0.0) - V = Variable('V', dtype=np.float32, initial=0.0) - -# define ADCP sampling function without conversion (because of A grid) -def SampleVel(particle, fieldset, time): - particle.U, particle.V = fieldset.UV.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False) - # particle.V = fieldset.V.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False) - -# # Create CTD like particles to sample the ocean -# class CTDParticle(JITParticle): -# """Define a new particle class that does CTD like measurements""" -# salinity = Variable("salinity", initial=np.nan) -# temperature = Variable("temperature", initial=np.nan) -# pressure = Variable("pressure", initial=np.nan) -# raising = Variable("raising", dtype=np.int32, initial=0.0) - -# # define function lowering and raising CTD -# def CTDcast(particle, fieldset, time): -# seafloor = fieldset.bathymetry[time, particle.depth, particle.lat, particle.lon] -# vertical_speed = 1.0 # sink and rise speed in m/s - -# if particle.raising == 0: -# # Sinking with vertical_speed until near seafloor -# particle_ddepth = vertical_speed * particle.dt -# if particle.depth >= (seafloor - 20): -# particle.raising = 1 - -# if particle.raising == 1: -# # Rising with vertical_speed until depth is 2 m -# if particle.depth > 2: -# particle_ddepth = -vertical_speed * particle.dt -# if particle.depth + particle_ddepth <= 2: -# # to break the loop ... -# particle.state = 41 -# print("CTD cast finished") - -# # define function sampling Salinity -# def SampleS(particle, fieldset, time): -# particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon] - -# # define function sampling Temperature -# def SampleT(particle, fieldset, time): -# particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] - -# # define function sampling Pressure -# def SampleP(particle, fieldset, time): -# particle.pressure = fieldset.P[time, particle.depth, particle.lat, particle.lon] - -### Run simulation - -# Create ADCP like particle with accurate depths, 150 meter every 4 meters as https://rowetechinc.com/seaseven/ -depthnum = 48 -# Initiate ADCP like particle set -pset = ParticleSet.from_list( - fieldset=fieldset, pclass=ADCPParticle, lon=np.full(depthnum,sample_lons[0]), lat=np.full(depthnum,sample_lats[0]), depth=np.linspace(2, 500, num=depthnum), time=0 -) -# create a ParticleFile to store the ADCP output -adcp_output_file = pset.ParticleFile(name="./results/Peru_adcp.zarr") -adcp_dt = timedelta(minutes=5).total_seconds() # timestep of ADCP output, every 5 min == 1080 m (3.6*60*5 =m/s*s/min*min) - -# # initialize CTD station number and time -total_time = timedelta(hours=0).total_seconds() -# ctd = 0 -# ctd_dt = timedelta(seconds=10) # timestep of CTD output reflecting post-proces binning into 10m bins - -# run the model for the length of the sample_lons list -for i in range(len(sample_lons)-1): - - #vexecute the kernels to sample U and V - pset.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) - adcp_output_file.write(pset, time=pset[0].time) - - # # check if we are at a CTD station - # if (sample_lons[i] - coords[ctd][0]) < 0.01 and (sample_lats[i] - coords[ctd][1]) < 0.01: - # ctd += 1 - - # # release CTD particle - # pset_CTD = ParticleSet(fieldset=fieldset, pclass=CTDParticle, lon=sample_lons[i], lat=sample_lats[i], depth=2, time=total_time) - - # # create a ParticleFile to store the CTD output - # ctd_output_file = pset_CTD.ParticleFile(name=f"./results/CTD_test_{ctd}.zarr", outputdt=ctd_dt) - - # # record the temperature and salinity of the particle - # pset_CTD.execute([SampleS, SampleT, CTDcast], runtime=timedelta(hours=4), dt=ctd_dt, output_file=ctd_output_file) - # total_time = pset_CTD.time[0] #+ timedelta(hours=1).total_seconds() # add CTD time and 1 hour for deployment - - # update the particle time and location - pset.lon_nextloop[:] = sample_lons[i+1] - pset.lat_nextloop[:] = sample_lats[i+1] - - total_time += adcp_dt - pset.time_nextloop[:] = total_time -# write the final locations of the ADCP particles -pset.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) -adcp_output_file.write_latest_locations(pset, time=total_time) - -# ### Post-processing -# import xarray as xr -# from scipy.ndimage import uniform_filter1d - -# # rewrite CTD data to cvs -# for i in range(1, ctd+1): - -# # Open output and read to x, y, z -# ds = xr.open_zarr(f"./results/CTD_test_{i}.zarr") -# x = ds["lon"][:].squeeze() -# y = ds["lat"][:].squeeze() -# z = ds["z"][:].squeeze() -# time = ds["time"][:].squeeze() -# T = ds["temperature"][:].squeeze() -# S = ds["salinity"][:].squeeze() -# ds.close() - -# # add some noise -# random_walk = np.random.random()/10 -# z_norm = (z-np.min(z))/(np.max(z)-np.min(z)) -# t_norm = np.linspace(0, 1, num=len(time)) -# # dS = abs(np.append(0, np.diff(S))) # scale noise with gradient -# # for j in range(5, 0, -1): -# # dS[dS<1*10**-j] = 0.5-j/10 -# # add smoothed random noise scaled with depth (and OPTIONAL with gradient for S) -# # and random (reversed) diversion from initial through time scaled with depth -# S = S + uniform_filter1d( -# np.random.random(S.shape)/5*(1-z_norm) + -# random_walk*(np.max(S).values - np.min(S).values)*(1-z_norm)*t_norm/10, -# max(int(len(time)/40), 1)) -# T = T + uniform_filter1d( -# np.random.random(T.shape)*5*(1-z_norm) - -# random_walk/2*(np.max(T).values - np.min(T).values)*(1-z_norm)*t_norm/10, -# max(int(len(time)/20), 1)) - -# # reshaping data to export to csv -# header = f"'pressure [hPa]','temperature [degC]', 'salinity [g kg-1]'" -# data = np.column_stack([(z/10), T, S]) -# new_line = '\n' -# np.savetxt(f"./results/CTD_station_{i}.csv", data, fmt="%.4f", header=header, delimiter=',', -# comments=f'{x.attrs}{new_line}{x[0].values}{new_line}{y.attrs}{new_line}{y[0].values}{new_line}start time: {time[0].values}{new_line}end time: {time[-1].values}{new_line}') - diff --git a/src/cruise_simulation_CTD.py b/src/cruise_simulation_CTD.py deleted file mode 100755 index aa2cc359..00000000 --- a/src/cruise_simulation_CTD.py +++ /dev/null @@ -1,221 +0,0 @@ -# #!/usr/bin/env python3 -# # Script to simulate a cruise with CTD casts and ADCP data -# # Simulating CTD data near Japan in Eddy - -import numpy as np -import pyproj -from datetime import timedelta -from shapely.geometry import Point, Polygon -from parcels import Field, FieldSet, JITParticle, Variable, ParticleSet - -# # set initial location as lon-lat EW-NS -# coords_input = [[154, 38.1], [155, 38.1], [156, 38.1], [157, 38.1], [158, 38.1]] - -# # Load the CMEMS data (3 weeks for IPO) -# dataset_folder = "/nethome/0448257/Data" -# filenames = { -# "U": f"{dataset_folder}/JapanUV.nc", -# "V": f"{dataset_folder}/JapanUV.nc", -# "S": f"{dataset_folder}/JapanS.nc", -# "T": f"{dataset_folder}/JapanT.nc"} -# variables = {'U': 'uo', 'V': 'vo', 'S':'so', 'T':'thetao'} -# dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth':'depth'} - -# # create the fieldset and set interpolation methods -# fieldset = FieldSet.from_netcdf(filenames, variables, dimensions) -# fieldset.T.interp_method = "linear_invdist_land_tracer" -# fieldset.S.interp_method = "linear_invdist_land_tracer" - -# # add bathymetry data to the fieldset for CTD cast -# bathymetry_file = f"{dataset_folder}/GLO-MFC_001_024_mask_bathy.nc" -# bathymetry_variables = ('bathymetry', 'deptho') -# bathymetry_dimensions = {'lon': 'longitude', 'lat': 'latitude'} -# bathymetry_field = Field.from_netcdf(bathymetry_file, bathymetry_variables, bathymetry_dimensions) -# fieldset.add_field(bathymetry_field) -# # read in data already -# fieldset.computeTimeChunk(0,1) - -# ### Determine ship course as intermediate points between CTD stations - -# # Initialize lists to store intermediate points -# lons = [] -# lats = [] - -# # Loop over station coordinates and calculate intermediate points along great circle path -# i = 0 -# for i in (range(len(coords_input)-1)): -# startlong = coords_input[i][0] -# startlat = coords_input[i][1] -# endlong = coords_input[i+1][0] -# endlat = coords_input[i+1][1] - -# # calculate line string along path with segments every 5 min = 3.6*60*5 = 1080 m (or switch comment for 2 midpoints) -# g = pyproj.Geod(ellps='WGS84') -# r = g.inv_intermediate(startlong, startlat, endlong, endlat, initial_idx=0, del_s = 1080) -# # r = g.inv_intermediate(startlong, startlat, endlong, endlat, initial_idx=0, return_back_azimuth=False, npts=3) -# lons.append(r.lons) # stored as a list of arrays -# lats.append(r.lats) - -# # initial_idx will add begin point to each list (but not end point to avoid dubbling) so add final endpoint manually -# lons = np.append(np.hstack(lons), endlong) -# lats = np.append(np.hstack(lats), endlat) - -# # check if input sample locations are within data availability area, only save if so -# #poly = Polygon([(west, north), (west, south), (east, south), (east, north)]) -# poly = Polygon([(153, 37), (153, 39), (159, 39), (159, 37)]) -# coords = [] -# sample_lons = [] -# sample_lats = [] -# for coord in coords_input: -# if poly.contains(Point(coord)): -# coords.append(coord) -# for i in range(len(lons)): -# if poly.contains(Point(lons[i], lats[i])): -# sample_lons.append(lons[i]) -# sample_lats.append(lats[i]) - -# ### Define particles and sampling functions - -# # Create ADCP like particles to sample the ocean -# class ADCPParticle(JITParticle): -# """Define a new particle class that does ADCP like measurements""" -# U = Variable('U', dtype=np.float32, initial=0.0) -# V = Variable('V', dtype=np.float32, initial=0.0) - -# # define ADCP sampling function without conversion (because of A grid) -# def SampleVel(particle, fieldset, time): -# particle.U, particle.V = fieldset.UV.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False) -# # particle.V = fieldset.V.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False) - -# # Create CTD like particles to sample the ocean -# class CTDParticle(JITParticle): -# """Define a new particle class that does CTD like measurements""" -# salinity = Variable("salinity", initial=np.nan) -# temperature = Variable("temperature", initial=np.nan) -# pressure = Variable("pressure", initial=np.nan) -# raising = Variable("raising", dtype=np.int32, initial=0.0) - -# # define function lowering and raising CTD -# def CTDcast(particle, fieldset, time): -# seafloor = fieldset.bathymetry[time, particle.depth, particle.lat, particle.lon] -# vertical_speed = 1.0 # sink and rise speed in m/s - -# if particle.raising == 0: -# # Sinking with vertical_speed until near seafloor -# particle_ddepth = vertical_speed * particle.dt -# if particle.depth >= 2000: #(seafloor - 20): -# particle.raising = 1 - -# if particle.raising == 1: -# # Rising with vertical_speed until depth is 2 m -# if particle.depth > 2: -# particle_ddepth = -vertical_speed * particle.dt -# if particle.depth + particle_ddepth <= 2: -# # to break the loop ... -# particle.state = 41 -# print("CTD cast finished") - -# # define function sampling Salinity -# def SampleS(particle, fieldset, time): -# particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon] - -# # define function sampling Temperature -# def SampleT(particle, fieldset, time): -# particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] - -# # define function sampling Pressure -# def SampleP(particle, fieldset, time): -# particle.pressure = fieldset.P[time, particle.depth, particle.lat, particle.lon] - -# ### Run simulation - -# # Create ADCP like particle with accurate depths, 150 meter every 4 meters as https://rowetechinc.com/seaseven/ -# depthnum = 48 -# # Initiate ADCP like particle set -# pset = ParticleSet.from_list( -# fieldset=fieldset, pclass=ADCPParticle, lon=np.full(depthnum,sample_lons[0]), lat=np.full(depthnum,sample_lats[0]), depth=np.linspace(2, 500, num=depthnum), time=0 -# ) -# # create a ParticleFile to store the ADCP output -# adcp_output_file = pset.ParticleFile(name="./results/Japan_ADCP.zarr") -# adcp_dt = timedelta(minutes=5).total_seconds() # timestep of ADCP output, every 5 min == 1080 m (3.6*60*5 =m/s*s/min*min) - -# # # initialize CTD station number and time -# total_time = timedelta(hours=0).total_seconds() -# ctd = 0 -# ctd_dt = timedelta(seconds=10) # timestep of CTD output reflecting post-proces binning into 10m bins - -# # run the model for the length of the sample_lons list -# for i in range(len(sample_lons)-1): - -# #vexecute the kernels to sample U and V -# pset.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) -# adcp_output_file.write(pset, time=pset[0].time) - -# # check if we are at a CTD station -# if (sample_lons[i] - coords[ctd][0]) < 0.01 and (sample_lats[i] - coords[ctd][1]) < 0.01: -# ctd += 1 - -# # release CTD particle -# pset_CTD = ParticleSet(fieldset=fieldset, pclass=CTDParticle, lon=sample_lons[i], lat=sample_lats[i], depth=2, time=total_time) - -# # create a ParticleFile to store the CTD output -# ctd_output_file = pset_CTD.ParticleFile(name=f"./results/CTD_Japan_{ctd}.zarr", outputdt=ctd_dt) - -# # record the temperature and salinity of the particle -# pset_CTD.execute([SampleS, SampleT, CTDcast], runtime=timedelta(hours=4), dt=ctd_dt, output_file=ctd_output_file) -# total_time = pset_CTD.time[0] #+ timedelta(hours=1).total_seconds() # add CTD time and 1 hour for deployment - -# # update the particle time and location -# pset.lon_nextloop[:] = sample_lons[i+1] -# pset.lat_nextloop[:] = sample_lats[i+1] - -# total_time += adcp_dt -# pset.time_nextloop[:] = total_time -# # write the final locations of the ADCP particles -# pset.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) -# adcp_output_file.write_latest_locations(pset, time=total_time) - -### Post-processing -import xarray as xr -from scipy.ndimage import uniform_filter1d -import numpy as np - -ctd = 5 -# rewrite CTD data to cvs -for i in range(1, ctd+1): - - # Open output and read to x, y, z - ds = xr.open_zarr(f"./results/CTD_Japan_{i}.zarr") - x = ds["lon"][:].squeeze() - y = ds["lat"][:].squeeze() - z = ds["z"][:].squeeze() - time = ds["time"][:].squeeze() - T = ds["temperature"][:].squeeze() - S = ds["salinity"][:].squeeze() - ds.close() - - # add some noise - random_walk = np.random.random()/10 - z_norm = (z-np.min(z))/(np.max(z)-np.min(z)) - t_norm = np.linspace(0, 1, num=len(time)) - # dS = abs(np.append(0, np.diff(S))) # scale noise with gradient - # for j in range(5, 0, -1): - # dS[dS<1*10**-j] = 0.5-j/10 - # add smoothed random noise scaled with depth (and OPTIONAL with gradient for S) - # and random (reversed) diversion from initial through time scaled with depth - S = S + uniform_filter1d( - np.random.random(S.shape)/5*(1-z_norm) + - random_walk*(np.max(S).values - np.min(S).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/40), 1)) - T = T + uniform_filter1d( - np.random.random(T.shape)*5*(1-z_norm) - - random_walk/2*(np.max(T).values - np.min(T).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/20), 1)) - - # reshaping data to export to csv - header = f"pressure [hPa],temperature [degC],salinity [g kg-1]" - data = np.column_stack([(z/10), T, S]) - new_line = '\n' - np.savetxt(f"./results/CTD_Japan_station_{i}.csv", data, fmt="%.4f", header=header, delimiter=',', - comments=f'longitude,{x[0].values},”{x.attrs}”{new_line}latitude,{y[0].values},”{y.attrs}”{new_line}start time,{time[0].values}{new_line}end time,{time[-1].values}{new_line}') - diff --git a/src/sailship.ipynb b/src/sailship.ipynb deleted file mode 100644 index 0ccdf8fb..00000000 --- a/src/sailship.ipynb +++ /dev/null @@ -1,1644 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Work in progress to sail the virtual ship" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import json\n", - "import numpy as np\n", - "import pyproj\n", - "from datetime import timedelta\n", - "from shapely.geometry import Point, Polygon\n", - "from parcels import Field, FieldSet, JITParticle, Variable, ParticleSet" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Read sample input data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "21600" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Load the CMEMS data (3 weeks nov 2022 for IPO)\n", - "dataset_folder = \"/nethome/0448257/Data\"\n", - "filenames = {\n", - " \"U\": f\"{dataset_folder}/studentdata_UV_klein.nc\",\n", - " \"V\": f\"{dataset_folder}/studentdata_UV_klein.nc\",\n", - " \"S\": f\"{dataset_folder}/studentdata_S_klein.nc\",\n", - " \"T\": f\"{dataset_folder}/studentdata_T_klein.nc\"} \n", - "variables = {'U': 'uo', 'V': 'vo', 'S': 'so', 'T': 'thetao'}\n", - "dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth': 'depth'}\n", - "\n", - "# create the fieldset and set interpolation methods\n", - "fieldset = FieldSet.from_netcdf(filenames, variables, dimensions)\n", - "fieldset.T.interp_method = \"linear_invdist_land_tracer\"\n", - "fieldset.S.interp_method = \"linear_invdist_land_tracer\"\n", - "\n", - "# add bathymetry data to the fieldset for CTD cast\n", - "bathymetry_file = f\"{dataset_folder}/GLO-MFC_001_024_mask_bathy.nc\"\n", - "bathymetry_variables = ('bathymetry', 'deptho')\n", - "bathymetry_dimensions = {'lon': 'longitude', 'lat': 'latitude'}\n", - "bathymetry_field = Field.from_netcdf(bathymetry_file, bathymetry_variables, bathymetry_dimensions)\n", - "fieldset.add_field(bathymetry_field)\n", - "# read in data already\n", - "fieldset.computeTimeChunk(0,1)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# set initial location as lon-lat EW-NS #TODO should be input to function or come from leafmap \n", - "coords_input = [[-83.737793, 3.591884], [-86.879883, 4.258768], [-86.879883, -0.747049], [-86.791992, -4.740675], [-86.791992, -9.058702]]\n", - "ctd_input = [[-83.737793, 3.591884], [-86.879883, 4.258768], [-86.879883, -0.747049], [-86.791992, -4.740675], [-86.791992, -9.058702]]\n", - "drifter_input = [[-83.737793, 3.591884], [-83.737793, 3.591984], [-83.737893, 3.591884]]\n", - "coords_input = [[-80, 2], [-80.01, 2], [-90, 2], [-100, 2], [-110, 2], [-120, 2], [-125, 2.5], [-115, 2.5], [-105, 2.5], [-95, 2.5], [-85, 2.5]]\n", - "# coords_input = [[-82.924805, 4.696879], [-84.418945, 3.908099], [-86.044922, 3.074695], [-87.978516, 2.021065], [-90, 1.274309], [-91.977539, 0.483393], [-92.021484, -1.054628], [-90.65918, -2.021065], [-88.769531, -1.054628], [-86.879883, 0], [-84.990234, 1.098565], [-83.320313, 2.021065], [-81.650391, 3.513421], [-80.244141, 4.784469]]\n", - "# coords_input = [[152.8, 36.6], [156.6, 36.9]]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Determine ship course as intermediate points between CTD stations" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(-89.99982550251605, 89.99982550251605, 1112.521315199904)\n", - "(-89.8252315914032, 89.8252315914032, 1111407.073934867)\n", - "(-89.82505575223266, 89.82505575223266, 1112519.5900692847)\n", - "(-89.82505575223266, 89.82505575223266, 1112519.5900692847)\n", - "(-89.82505575223266, 89.82505575223266, 1112519.5900692847)\n", - "(-84.22838722804681, 95.5751864989223, 558910.4685414702)\n", - "(89.78134505877674, -89.78134505877674, 1112139.781805734)\n", - "(89.78134505877674, -89.78134505877674, 1112139.781805734)\n", - "(89.78134505877674, -89.78134505877674, 1112139.781805734)\n", - "(89.78134505877674, -89.78134505877674, 1112139.781805734)\n" - ] - } - ], - "source": [ - "# Initialize lists to store intermediate points\n", - "lons = []\n", - "lats = []\n", - "\n", - "# Loop over station coordinates and calculate intermediate points along great circle path\n", - "i = 0\n", - "for i in (range(len(coords_input)-1)):\n", - " startlong = coords_input[i][0]\n", - " startlat = coords_input[i][1]\n", - " endlong = coords_input[i+1][0]\n", - " endlat = coords_input[i+1][1]\n", - "\n", - " # calculate line string along path with segments every 5 min = 3.6*60*5 = 1080 m (or switch comment for 2 midpoints)\n", - " geod = pyproj.Geod(ellps='WGS84')\n", - " r = g.inv_intermediate(startlong, startlat, endlong, endlat, del_s=1080, initial_idx=0, return_back_azimuth=False)\n", - " # r = g.inv_intermediate(startlong, startlat, endlong, endlat, initial_idx=0, return_back_azimuth=False, npts=3)\n", - " lons = np.append(lons, r.lons) # stored as a list of arrays\n", - " lats = np.append(lats, r.lats)\n", - "\n", - " # initial_idx will add begin point to each list (but not end point to avoid dubbling) so add final endpoint manually\n", - " lons = np.append(np.hstack(lons), endlong)\n", - " lats = np.append(np.hstack(lats), endlat)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# check if input sample locations are within data availability area, only save if so\n", - "poly = Polygon([(-170, 5), (-170, -10), (-75, -10), (-75, 5)])\n", - "ctd_coords = []\n", - "drifter_coords = []\n", - "sample_lons = []\n", - "sample_lats = []\n", - "for coord in ctd_input:\n", - " if poly.contains(Point(coord)):\n", - " ctd_coords.append(coord)\n", - "for coord in drifter_input:\n", - " if poly.contains(Point(coord)):\n", - " drifter_coords.append(coord)\n", - "for i in range(len(lons)):\n", - " if poly.contains(Point(lons[i], lats[i])):\n", - " sample_lons.append(lons[i])\n", - " sample_lats.append(lats[i])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define particles and sampling functions " - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# Create ADCP like particles to sample the ocean\n", - "class ADCPParticle(JITParticle):\n", - " \"\"\"Define a new particle class that does ADCP like measurements\"\"\"\n", - " U = Variable('U', dtype=np.float32, initial=0.0)\n", - " V = Variable('V', dtype=np.float32, initial=0.0)\n", - "\n", - "# define ADCP sampling function without conversion (because of A grid)\n", - "def SampleVel(particle, fieldset, time):\n", - " particle.U, particle.V = fieldset.UV.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False)\n", - " # particle.V = fieldset.V.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False)\n", - "\n", - "# Create particle to sample water underway\n", - "class UnderwayDataParticle(JITParticle):\n", - " \"\"\"Define a new particle class that samples water directly under the hull\"\"\"\n", - " salinity = Variable(\"salinity\", initial=np.nan)\n", - " temperature = Variable(\"temperature\", initial=np.nan)\n", - "\n", - "# Create CTD like particles to sample the ocean\n", - "class CTDParticle(JITParticle):\n", - " \"\"\"Define a new particle class that does CTD like measurements\"\"\"\n", - " salinity = Variable(\"salinity\", initial=np.nan)\n", - " temperature = Variable(\"temperature\", initial=np.nan)\n", - " pressure = Variable(\"pressure\", initial=np.nan)\n", - " raising = Variable(\"raising\", dtype=np.int32, initial=0.0)\n", - "\n", - "# define function lowering and raising CTD\n", - "def CTDcast(particle, fieldset, time):\n", - " seafloor = fieldset.bathymetry[time, particle.depth, particle.lat, particle.lon]\n", - " vertical_speed = 1.0 # sink and rise speed in m/s\n", - "\n", - " if particle.raising == 0:\n", - " # Sinking with vertical_speed until near seafloor\n", - " particle_ddepth = vertical_speed * particle.dt\n", - " if particle.depth >= (seafloor - 20): \n", - " particle.raising = 1\n", - "\n", - " if particle.raising == 1:\n", - " # Rising with vertical_speed until depth is 2 m\n", - " if particle.depth > 2:\n", - " particle_ddepth = -vertical_speed * particle.dt \n", - " if particle.depth + particle_ddepth <= 2:\n", - " # to break the loop ...\n", - " particle.state = 41\n", - " print(\"CTD cast finished\")\n", - "\n", - "# define function sampling Salinity\n", - "def SampleS(particle, fieldset, time):\n", - " particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# define function sampling Temperature\n", - "def SampleT(particle, fieldset, time):\n", - " particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - "# define function sampling Pressure\n", - "def SampleP(particle, fieldset, time):\n", - " particle.pressure = fieldset.P[time, particle.depth, particle.lat, particle.lon]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run simulation" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INFO: Output files are stored in ./results/CTD_test_1.zarr.\n", - " 40%|███▉ | 5690.0/14400.0 [03:40<10:07, 14.34it/s]CTD cast finished\n", - " 40%|███▉ | 5690.0/14400.0 [03:40<05:36, 25.85it/s]\n" - ] - }, - { - "ename": "IndexError", - "evalue": "list index out of range", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[45], line 49\u001b[0m\n\u001b[1;32m 46\u001b[0m total_time \u001b[38;5;241m=\u001b[39m pset_CTD\u001b[38;5;241m.\u001b[39mtime[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m+\u001b[39m timedelta(hours\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\u001b[38;5;241m.\u001b[39mtotal_seconds() \u001b[38;5;66;03m# add CTD time and 1 hour for deployment\u001b[39;00m\n\u001b[1;32m 48\u001b[0m \u001b[38;5;66;03m# check if we are at a drifter deployment location\u001b[39;00m\n\u001b[0;32m---> 49\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m (sample_lons[i] \u001b[38;5;241m-\u001b[39m \u001b[43mdrifter_coords\u001b[49m\u001b[43m[\u001b[49m\u001b[43mdrifter\u001b[49m\u001b[43m]\u001b[49m[\u001b[38;5;241m0\u001b[39m]) \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0.001\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m (sample_lats[i] \u001b[38;5;241m-\u001b[39m drifter_coords[drifter][\u001b[38;5;241m1\u001b[39m]) \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0.001\u001b[39m:\n\u001b[1;32m 50\u001b[0m drifter \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 51\u001b[0m drifter_time\u001b[38;5;241m.\u001b[39mappend(total_time)\n", - "\u001b[0;31mIndexError\u001b[0m: list index out of range" - ] - } - ], - "source": [ - "# Create ADCP like particleset and output file\n", - "ADCP_bins = np.arange(5, 1000, 24)\n", - "vert_particles = len(ADCP_bins)\n", - "pset_ADCP = ParticleSet.from_list(\n", - " fieldset=fieldset, pclass=ADCPParticle, lon=np.full(vert_particles,sample_lons[0]), lat=np.full(vert_particles,sample_lats[0]), depth=ADCP_bins, time=0\n", - ")\n", - "adcp_output_file = pset_ADCP.ParticleFile(name=\"./results/sailship_ADCP.zarr\")\n", - "adcp_dt = timedelta(minutes=5).total_seconds() # timestep of ADCP output, every 5 min == 1080 m (3.6*60*5 =m/s*s/min*min)\n", - "\n", - "# Create underway particle \n", - "pset_UnderwayData = ParticleSet.from_list(\n", - " fieldset=fieldset, pclass=UnderwayDataParticle, lon=sample_lons[0], lat=sample_lats[0], depth=2, time=0\n", - ")\n", - "UnderwayData_output_file = pset_UnderwayData.ParticleFile(name=\"./results/sailship_UnderwayData.zarr\")\n", - "\n", - "# initialize CTD station number and time \n", - "total_time = timedelta(hours=0).total_seconds()\n", - "ctd = 0\n", - "ctd_dt = timedelta(seconds=10) # timestep of CTD output reflecting post-proces binning into 10m bins\n", - "\n", - "# initialize drifters and floats\n", - "drifter = 0\n", - "drifter_time = []\n", - "\n", - "# run the model for the length of the sample_lons list\n", - "for i in range(len(sample_lons)-1):\n", - "\n", - " # execute the ADCP kernels to sample U and V and underway T and S\n", - " pset_ADCP.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) \n", - " adcp_output_file.write(pset_ADCP, time=pset_ADCP[0].time)\n", - " pset_UnderwayData.execute([SampleS, SampleT], dt=adcp_dt, runtime=1, verbose_progress=False)\n", - " UnderwayData_output_file.write(pset_UnderwayData, time=pset_ADCP[0].time)\n", - "\n", - " # check if we are at a CTD station\n", - " if (sample_lons[i] - ctd_coords[ctd][0]) < 0.001 and (sample_lats[i] - ctd_coords[ctd][1]) < 0.001:\n", - " ctd += 1\n", - " \n", - " # release CTD particle\n", - " pset_CTD = ParticleSet(fieldset=fieldset, pclass=CTDParticle, lon=sample_lons[i], lat=sample_lats[i], depth=2, time=total_time)\n", - "\n", - " # create a ParticleFile to store the CTD output\n", - " ctd_output_file = pset_CTD.ParticleFile(name=f\"./results/CTD_test_{ctd}.zarr\", outputdt=ctd_dt)\n", - "\n", - " # record the temperature and salinity of the particle\n", - " pset_CTD.execute([SampleS, SampleT, CTDcast], runtime=timedelta(hours=4), dt=ctd_dt, output_file=ctd_output_file)\n", - " total_time = pset_CTD.time[0] + timedelta(hours=1).total_seconds() # add CTD time and 1 hour for deployment\n", - "\n", - " # check if we are at a drifter deployment location\n", - " if drifter < len(drifter_coords):\n", - " while (sample_lons[i] - drifter_coords[drifter][0]) < 0.001 and (sample_lats[i] - drifter_coords[drifter][1]) < 0.001:\n", - " drifter += 1\n", - " drifter_time.append(total_time)\n", - "\n", - " # update the particle time and location\n", - " pset_ADCP.lon_nextloop[:] = sample_lons[i+1]\n", - " pset_ADCP.lat_nextloop[:] = sample_lats[i+1]\n", - " pset_UnderwayData.lon_nextloop[:] = sample_lons[i+1]\n", - " pset_UnderwayData.lat_nextloop[:] = sample_lats[i+1] \n", - " \n", - " total_time += adcp_dt\n", - " pset_ADCP.time_nextloop[:] = total_time\n", - " pset_UnderwayData.time_nextloop[:] = total_time\n", - " if i % 48 == 0:\n", - " print(f\"Gathered data {pset_ADCP[0].time/3600} hours since start\")\n", - "\n", - "# write the final locations of the ADCP and Underway data particles\n", - "pset_ADCP.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False)\n", - "adcp_output_file.write_latest_locations(pset_ADCP, time=total_time)\n", - "pset_UnderwayData.execute([SampleS, SampleT], dt=adcp_dt, runtime=1, verbose_progress=False)\n", - "UnderwayData_output_file.write_latest_locations(pset_UnderwayData, time=total_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[9290.0, 9290.0, 9290.0, 9290.0, 9290.0, 9290.0]" - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "drifter_time" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "import xarray as xr\n", - "# Open output and read to x, y, z\n", - "ds = xr.open_zarr(\"../results/sailship_ADCP.zarr\")\n", - "time = ds[\"time\"][0].values\n", - "x = ds[\"lon\"][:].squeeze()\n", - "y = ds[\"lat\"][:].squeeze()\n", - "z = ds[\"z\"][:].squeeze()\n", - "U = ds[\"U\"][:].squeeze()\n", - "V = ds[\"V\"][:].squeeze()\n", - "ds.close()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 0.21141048, 0.21073838, 0.21154574, ..., -0.05740462,\n", - " -0.05878886, -0.06029826],\n", - " [ 0.22115852, 0.22025768, 0.22080159, ..., -0.06844132,\n", - " -0.07026841, -0.07221974],\n", - " [ 0.23090656, 0.229777 , 0.23005745, ..., -0.07947803,\n", - " -0.08174795, -0.08414122],\n", - " ...,\n", - " [ 0.15958248, 0.15866159, 0.16019139, ..., -0.16439535,\n", - " -0.16591409, -0.16754586],\n", - " [ 0.13169025, 0.13092402, 0.13297619, ..., -0.1893431 ,\n", - " -0.19044396, -0.19165468],\n", - " [ 0.10379802, 0.10318644, 0.10576099, ..., -0.21429083,\n", - " -0.21497384, -0.2157635 ]], dtype=float32)" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ds.V[1:10].values" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'ax' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[9], line 8\u001b[0m\n\u001b[1;32m 6\u001b[0m cu \u001b[38;5;241m=\u001b[39m ax1\u001b[38;5;241m.\u001b[39mscatter(x, y, z\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m10\u001b[39m, c\u001b[38;5;241m=\u001b[39mU, s\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m, marker\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mo\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 7\u001b[0m cv \u001b[38;5;241m=\u001b[39m ax2\u001b[38;5;241m.\u001b[39mscatter(x, y, z\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m10\u001b[39m, c\u001b[38;5;241m=\u001b[39mV, s\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m, marker\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mo\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m----> 8\u001b[0m \u001b[43max\u001b[49m\u001b[38;5;241m.\u001b[39mset_xlabel(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mLongitude\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 9\u001b[0m ax\u001b[38;5;241m.\u001b[39mset_ylabel(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mLatitude\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 10\u001b[0m ax\u001b[38;5;241m.\u001b[39mset_zlabel(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDepth (m)\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mNameError\u001b[0m: name 'ax' is not defined" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "# Plot Particle depth\n", - "fig, (ax1, ax2) = plt.subplots(1, 2)\n", - "ax1 = plt.axes(projection=\"3d\")\n", - "ax2 = plt.axes(projection=\"3d\")\n", - "cu = ax1.scatter(x, y, z*10, c=U, s=20, marker=\"o\")\n", - "cv = ax2.scatter(x, y, z*10, c=V, s=20, marker=\"o\")\n", - "ax.set_xlabel(\"Longitude\")\n", - "ax.set_ylabel(\"Latitude\")\n", - "ax.set_zlabel(\"Depth (m)\")\n", - "ax.set_zlim(np.max(z), 0)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "ename": "FileNotFoundError", - "evalue": "No such file or directory: '/storage/home/0448257/Virtual_ship_classroom/results/CTD_3.zarr'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/xarray/backends/zarr.py:429\u001b[0m, in \u001b[0;36mZarrStore.open_group\u001b[0;34m(cls, store, mode, synchronizer, group, consolidated, consolidate_on_close, chunk_store, storage_options, append_dim, write_region, safe_chunks, stacklevel, zarr_version, write_empty)\u001b[0m\n\u001b[1;32m 428\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 429\u001b[0m zarr_group \u001b[38;5;241m=\u001b[39m \u001b[43mzarr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_consolidated\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstore\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mopen_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 430\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/zarr/convenience.py:1351\u001b[0m, in \u001b[0;36mopen_consolidated\u001b[0;34m(store, metadata_key, mode, **kwargs)\u001b[0m\n\u001b[1;32m 1350\u001b[0m \u001b[38;5;66;03m# setup metadata store\u001b[39;00m\n\u001b[0;32m-> 1351\u001b[0m meta_store \u001b[38;5;241m=\u001b[39m \u001b[43mConsolidatedStoreClass\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstore\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadata_key\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetadata_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1353\u001b[0m \u001b[38;5;66;03m# pass through\u001b[39;00m\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/zarr/storage.py:2947\u001b[0m, in \u001b[0;36mConsolidatedMetadataStore.__init__\u001b[0;34m(self, store, metadata_key)\u001b[0m\n\u001b[1;32m 2946\u001b[0m \u001b[38;5;66;03m# retrieve consolidated metadata\u001b[39;00m\n\u001b[0;32m-> 2947\u001b[0m meta \u001b[38;5;241m=\u001b[39m json_loads(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstore\u001b[49m\u001b[43m[\u001b[49m\u001b[43mmetadata_key\u001b[49m\u001b[43m]\u001b[49m)\n\u001b[1;32m 2949\u001b[0m \u001b[38;5;66;03m# check format of consolidated metadata\u001b[39;00m\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/zarr/storage.py:1113\u001b[0m, in \u001b[0;36mDirectoryStore.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1113\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n", - "\u001b[0;31mKeyError\u001b[0m: '.zmetadata'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mGroupNotFoundError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/xarray/backends/zarr.py:432\u001b[0m, in \u001b[0;36mZarrStore.open_group\u001b[0;34m(cls, store, mode, synchronizer, group, consolidated, consolidate_on_close, chunk_store, storage_options, append_dim, write_region, safe_chunks, stacklevel, zarr_version, write_empty)\u001b[0m\n\u001b[1;32m 431\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 432\u001b[0m zarr_group \u001b[38;5;241m=\u001b[39m \u001b[43mzarr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_group\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstore\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mopen_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 433\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 434\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed to open Zarr store with consolidated metadata, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 435\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbut successfully read with non-consolidated metadata. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 446\u001b[0m stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[1;32m 447\u001b[0m )\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/zarr/hierarchy.py:1532\u001b[0m, in \u001b[0;36mopen_group\u001b[0;34m(store, mode, cache_attrs, synchronizer, path, chunk_store, storage_options, zarr_version, meta_array)\u001b[0m\n\u001b[1;32m 1531\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ContainsArrayError(path)\n\u001b[0;32m-> 1532\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m GroupNotFoundError(path)\n\u001b[1;32m 1534\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n", - "\u001b[0;31mGroupNotFoundError\u001b[0m: group not found at path ''", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[11], line 10\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m# rewrite CTD data to cvs\u001b[39;00m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, ctd):\n\u001b[1;32m 8\u001b[0m \n\u001b[1;32m 9\u001b[0m \u001b[38;5;66;03m# Open output and read to x, y, z\u001b[39;00m\n\u001b[0;32m---> 10\u001b[0m ds \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_zarr\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m../results/CTD_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mi\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m.zarr\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 11\u001b[0m x \u001b[38;5;241m=\u001b[39m ds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlon\u001b[39m\u001b[38;5;124m\"\u001b[39m][:]\u001b[38;5;241m.\u001b[39msqueeze()\n\u001b[1;32m 12\u001b[0m y \u001b[38;5;241m=\u001b[39m ds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlat\u001b[39m\u001b[38;5;124m\"\u001b[39m][:]\u001b[38;5;241m.\u001b[39msqueeze()\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/xarray/backends/zarr.py:898\u001b[0m, in \u001b[0;36mopen_zarr\u001b[0;34m(store, group, synchronizer, chunks, decode_cf, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, consolidated, overwrite_encoded_chunks, chunk_store, storage_options, decode_timedelta, use_cftime, zarr_version, chunked_array_type, from_array_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m 884\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 885\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mopen_zarr() got unexpected keyword arguments \u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(kwargs\u001b[38;5;241m.\u001b[39mkeys())\n\u001b[1;32m 886\u001b[0m )\n\u001b[1;32m 888\u001b[0m backend_kwargs \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 889\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msynchronizer\u001b[39m\u001b[38;5;124m\"\u001b[39m: synchronizer,\n\u001b[1;32m 890\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconsolidated\u001b[39m\u001b[38;5;124m\"\u001b[39m: consolidated,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 895\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mzarr_version\u001b[39m\u001b[38;5;124m\"\u001b[39m: zarr_version,\n\u001b[1;32m 896\u001b[0m }\n\u001b[0;32m--> 898\u001b[0m ds \u001b[38;5;241m=\u001b[39m \u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 899\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstore\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 900\u001b[0m \u001b[43m \u001b[49m\u001b[43mgroup\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 901\u001b[0m \u001b[43m \u001b[49m\u001b[43mdecode_cf\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecode_cf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 902\u001b[0m \u001b[43m \u001b[49m\u001b[43mmask_and_scale\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmask_and_scale\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 903\u001b[0m \u001b[43m \u001b[49m\u001b[43mdecode_times\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecode_times\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 904\u001b[0m \u001b[43m \u001b[49m\u001b[43mconcat_characters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconcat_characters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 905\u001b[0m \u001b[43m \u001b[49m\u001b[43mdecode_coords\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecode_coords\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 906\u001b[0m \u001b[43m \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mzarr\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 907\u001b[0m \u001b[43m \u001b[49m\u001b[43mchunks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 908\u001b[0m \u001b[43m \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 909\u001b[0m \u001b[43m \u001b[49m\u001b[43mchunked_array_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked_array_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 910\u001b[0m \u001b[43m \u001b[49m\u001b[43mfrom_array_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfrom_array_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 911\u001b[0m \u001b[43m \u001b[49m\u001b[43mbackend_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbackend_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 912\u001b[0m \u001b[43m \u001b[49m\u001b[43mdecode_timedelta\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecode_timedelta\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 913\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_cftime\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_cftime\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 914\u001b[0m \u001b[43m \u001b[49m\u001b[43mzarr_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mzarr_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 915\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 916\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/xarray/backends/api.py:573\u001b[0m, in \u001b[0;36mopen_dataset\u001b[0;34m(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, inline_array, chunked_array_type, from_array_kwargs, backend_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m 561\u001b[0m decoders \u001b[38;5;241m=\u001b[39m _resolve_decoders_kwargs(\n\u001b[1;32m 562\u001b[0m decode_cf,\n\u001b[1;32m 563\u001b[0m open_backend_dataset_parameters\u001b[38;5;241m=\u001b[39mbackend\u001b[38;5;241m.\u001b[39mopen_dataset_parameters,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 569\u001b[0m decode_coords\u001b[38;5;241m=\u001b[39mdecode_coords,\n\u001b[1;32m 570\u001b[0m )\n\u001b[1;32m 572\u001b[0m overwrite_encoded_chunks \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moverwrite_encoded_chunks\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m--> 573\u001b[0m backend_ds \u001b[38;5;241m=\u001b[39m \u001b[43mbackend\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 574\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 575\u001b[0m \u001b[43m \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 576\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdecoders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 577\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 578\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 579\u001b[0m ds \u001b[38;5;241m=\u001b[39m _dataset_from_backend_dataset(\n\u001b[1;32m 580\u001b[0m backend_ds,\n\u001b[1;32m 581\u001b[0m filename_or_obj,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 591\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 592\u001b[0m )\n\u001b[1;32m 593\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/xarray/backends/zarr.py:965\u001b[0m, in \u001b[0;36mZarrBackendEntrypoint.open_dataset\u001b[0;34m(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, synchronizer, consolidated, chunk_store, storage_options, stacklevel, zarr_version)\u001b[0m\n\u001b[1;32m 944\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mopen_dataset\u001b[39m( \u001b[38;5;66;03m# type: ignore[override] # allow LSP violation, not supporting **kwargs\u001b[39;00m\n\u001b[1;32m 945\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 946\u001b[0m filename_or_obj: \u001b[38;5;28mstr\u001b[39m \u001b[38;5;241m|\u001b[39m os\u001b[38;5;241m.\u001b[39mPathLike[Any] \u001b[38;5;241m|\u001b[39m BufferedIOBase \u001b[38;5;241m|\u001b[39m AbstractDataStore,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 962\u001b[0m zarr_version\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 963\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Dataset:\n\u001b[1;32m 964\u001b[0m filename_or_obj \u001b[38;5;241m=\u001b[39m _normalize_path(filename_or_obj)\n\u001b[0;32m--> 965\u001b[0m store \u001b[38;5;241m=\u001b[39m \u001b[43mZarrStore\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_group\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 966\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 967\u001b[0m \u001b[43m \u001b[49m\u001b[43mgroup\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 968\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 969\u001b[0m \u001b[43m \u001b[49m\u001b[43msynchronizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msynchronizer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 970\u001b[0m \u001b[43m \u001b[49m\u001b[43mconsolidated\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconsolidated\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 971\u001b[0m \u001b[43m \u001b[49m\u001b[43mconsolidate_on_close\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 972\u001b[0m \u001b[43m \u001b[49m\u001b[43mchunk_store\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunk_store\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 973\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 974\u001b[0m \u001b[43m \u001b[49m\u001b[43mstacklevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstacklevel\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 975\u001b[0m \u001b[43m \u001b[49m\u001b[43mzarr_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mzarr_version\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 976\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 978\u001b[0m store_entrypoint \u001b[38;5;241m=\u001b[39m StoreBackendEntrypoint()\n\u001b[1;32m 979\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m close_on_error(store):\n", - "File \u001b[0;32m~/miniconda3/envs/parcels/lib/python3.11/site-packages/xarray/backends/zarr.py:449\u001b[0m, in \u001b[0;36mZarrStore.open_group\u001b[0;34m(cls, store, mode, synchronizer, group, consolidated, consolidate_on_close, chunk_store, storage_options, append_dim, write_region, safe_chunks, stacklevel, zarr_version, write_empty)\u001b[0m\n\u001b[1;32m 433\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 434\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed to open Zarr store with consolidated metadata, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 435\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbut successfully read with non-consolidated metadata. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 446\u001b[0m stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[1;32m 447\u001b[0m )\n\u001b[1;32m 448\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m zarr\u001b[38;5;241m.\u001b[39merrors\u001b[38;5;241m.\u001b[39mGroupNotFoundError:\n\u001b[0;32m--> 449\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo such file or directory: \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstore\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 450\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m consolidated:\n\u001b[1;32m 451\u001b[0m \u001b[38;5;66;03m# TODO: an option to pass the metadata_key keyword\u001b[39;00m\n\u001b[1;32m 452\u001b[0m zarr_group \u001b[38;5;241m=\u001b[39m zarr\u001b[38;5;241m.\u001b[39mopen_consolidated(store, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mopen_kwargs)\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: No such file or directory: '/storage/home/0448257/Virtual_ship_classroom/results/CTD_3.zarr'" - ] - } - ], - "source": [ - "import xarray as xr\n", - "import numpy as np\n", - "from scipy.ndimage import uniform_filter1d\n", - "\n", - "ctd = 10\n", - "# rewrite CTD data to cvs\n", - "for i in range(1, ctd):\n", - " \n", - " # Open output and read to x, y, z\n", - " ds = xr.open_zarr(f\"../results/CTD_{i}.zarr\")\n", - " x = ds[\"lon\"][:].squeeze()\n", - " y = ds[\"lat\"][:].squeeze()\n", - " z = ds[\"z\"][:].squeeze()\n", - " time = ds[\"time\"][:].squeeze()\n", - " T = ds[\"temperature\"][:].squeeze()\n", - " S = ds[\"salinity\"][:].squeeze()\n", - " ds.close()\n", - "\n", - " # add some noise\n", - " random_walk = np.random.random()/10\n", - " z_norm = (z-np.min(z))/(np.max(z)-np.min(z))\n", - " t_norm = np.linspace(0, 1, num=len(time))\n", - " # dS = abs(np.append(0, np.diff(S))) # scale noise with gradient\n", - " # for j in range(5, 0, -1):\n", - " # dS[dS<1*10**-j] = 0.5-j/10\n", - " # add smoothed random noise scaled with depth (and OPTIONAL with gradient for S) \n", - " # and random (reversed) diversion from initial through time scaled with depth \n", - " S = S + uniform_filter1d(\n", - " np.random.random(S.shape)/5*(1-z_norm) + \n", - " random_walk*(np.max(S).values - np.min(S).values)*(1-z_norm)*t_norm/10, \n", - " max(int(len(time)/40), 1))\n", - " T = T + uniform_filter1d(\n", - " np.random.random(T.shape)*5*(1-z_norm) - \n", - " random_walk/2*(np.max(T).values - np.min(T).values)*(1-z_norm)*t_norm/10, \n", - " max(int(len(time)/20), 1))\n", - "\n", - " # reshaping data to export to csv\n", - " header = f\"'pressure [hPa]','temperature [degC]', 'salinity [g kg-1]'\"\n", - " data = np.column_stack([(z/10), T, S])\n", - " new_line = '\\n'\n", - " np.savetxt(f\"../results/CTD_station_{i}.csv\", data, fmt=\"%.4f\", header=header, delimiter=',', \n", - " comments=f'{x.attrs}{new_line}{x[0].values}{new_line}{y.attrs}{new_line}{y[0].values}{new_line}start time: {time[0].values}{new_line}end time: {time[-1].values}{new_line}')\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(['-86.8798828125'], '4.258768081665039')" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "lon = []\n", - "lat = []\n", - "with open('../results/CTD_station_2.csv', 'r') as file:\n", - " text = file.read().splitlines()\n", - "lon.append(text[1])\n", - "lat = text[3]\n", - "lon, lat" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "# Some sample code you can use, you only have to replace the <...> instances to make it work\n", - "lon = []\n", - "lat = []\n", - "z20 = []\n", - "\n", - "import numpy as np\n", - "for i in range(1, 20):\n", - " with open(f'../results/CTDs/CTD_station_{i}.csv', 'r') as file:\n", - " station_data = file.read().splitlines()\n", - " lon.append(station_data[0].split(',')[1])\n", - " lat.append(station_data[1].split(',')[1])\n", - "\n", - " P, T, S = np.loadtxt(f'../results/CTDs/CTD_station_{i}.csv', delimiter=',', skiprows=7, unpack=True)\n", - " z20.append(P[T<20][0])" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "32.14093780517578\n" - ] - } - ], - "source": [ - "with open(f'../results/CTDs/CTD_station_{i}.csv', 'r') as file:\n", - " station_data = file.read().splitlines()\n", - " print(station_data[1].split(',')[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[7.2, 9.2, 8.2]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# z20 = P[T<20][0]\n", - "z20" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# lat = [1, 2, 3, 4, 5]\n", - "# lon = [-80, -90, -100, -110, -120]\n", - "# z20 = [1, 2, 3, 4, 5]\n", - "import pandas as pd\n", - "import geopandas as gpd\n", - "df = pd.DataFrame({'lat': lat, 'lon': lon, 'z20': z20})\n", - "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(lon, lat)) \n", - "gdf.plot(column='z20', legend=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'cloupy'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m/nethome/0448257/Virtual_ship_classroom/sailship.ipynb Cell 19\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> 1\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mcloupy\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mcl\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mnumpy\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mnp\u001b[39;00m\n\u001b[1;32m 4\u001b[0m imap \u001b[39m=\u001b[39m cl\u001b[39m.\u001b[39mm_MapInterpolation(\n\u001b[1;32m 5\u001b[0m dataframe\u001b[39m=\u001b[39mgdf\n\u001b[1;32m 6\u001b[0m )\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'cloupy'" - ] - } - ], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Read back in... student example\n", - "import numpy as np\n", - "z, T, S = np.loadtxt('../results/CTD_station_1.csv', delimiter=',', skiprows=7, unpack=True)\n", - "\n", - "# TS plot\n", - "import matplotlib.pyplot as plt\n", - "fig, ax1 = plt.subplots(1,1)\n", - "ax1.plot(S[int(len(z)/2):-1], z[int(len(z)/2):-1], color=\"lightblue\")\n", - "ax1.plot(S[0:int(len(z)/2)], z[0:int(len(z)/2)], color=\"b\")\n", - "ax1.invert_yaxis()\n", - "ax1.set_xlabel('Salinity', color = \"b\")\n", - "ax1.set_ylabel('Pressure (hPa)')\n", - "ax2 = ax1.twiny() # ax1 and ax2 share y-axis\n", - "ax2.set_xlabel('Temperature', color = \"r\")\n", - "ax2.plot(T[int(len(z)/2):-1], z[int(len(z)/2):-1], color=\"orange\")\n", - "ax2.plot(T[0:int(len(z)/2)], z[0:int(len(z)/2)], color=\"r\") \n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[7.2, 7.2, 9.2, 11.2, 15.2, 15.2, 15.2, 15.2, 15.2]" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Some sample code you can use\n", - "lon = []\n", - "lat = []\n", - "z20 = []\n", - "\n", - "for i in range(1, 10):\n", - " with open(f'./results/CTD_station_{i}.csv', 'r') as file:\n", - " station_data = file.read().splitlines()\n", - " lon.append(station_data[1])\n", - " lat.append(station_data[3])\n", - "\n", - " P, T, S = np.loadtxt(f'./results/CTD_station_{i}.csv', delimiter=',', skiprows=7, unpack=True)\n", - " z20.append(P[T < 20][0])\n", - "\n", - "# Look up or calculate z20 or plot the profile and determine from there\n", - "z20" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import pandas as pd\n", - "import geopandas as gpd\n", - "\n", - "df = pd.DataFrame({'lat': lat, 'lon': lon, 'z20': z20})\n", - "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(lon, lat))\n", - "gdf.plot(column='z20', legend=True, aspect=None) #try aspect='equal' if your map is distorted" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.640692" - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Warm Water Volume - East (5°N-5°S, 120°W-80°W)\n", - "(40 * 111000) * (10 * 111000) * 130 / 1e15 " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "https://colab.research.google.com/drive/1dabU91WECy5cglb2mVC-8SG4muFNlQrw?usp=sharing" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "# Open output and read to x, y, z\n", - "ds = xr.open_zarr(\"../results/UnderwayData.zarr\")\n", - "time = ds[\"time\"][0].values\n", - "x = ds[\"lon\"][:].squeeze()\n", - "y = ds[\"lat\"][:].squeeze()\n", - "z = ds[\"z\"][:].squeeze()\n", - "T = ds[\"temperature\"][:].squeeze()\n", - "S = ds[\"salinity\"][:].squeeze()\n", - "ds.close()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
<xarray.Dataset> Size: 40B\n",
-       "Dimensions:      (trajectory: 1, obs: 1)\n",
-       "Coordinates:\n",
-       "  * obs          (obs) int32 4B 0\n",
-       "  * trajectory   (trajectory) int64 8B 42\n",
-       "Data variables:\n",
-       "    lat          (trajectory, obs) float32 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
-       "    lon          (trajectory, obs) float32 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
-       "    salinity     (trajectory, obs) float32 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
-       "    temperature  (trajectory, obs) float32 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
-       "    time         (trajectory, obs) datetime64[ns] 8B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
-       "    z            (trajectory, obs) float32 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    Conventions:            CF-1.6/CF-1.7\n",
-       "    feature_type:           trajectory\n",
-       "    ncei_template_version:  NCEI_NetCDF_Trajectory_Template_v2.0\n",
-       "    parcels_mesh:           spherical\n",
-       "    parcels_version:        3.0.2
" - ], - "text/plain": [ - " Size: 40B\n", - "Dimensions: (trajectory: 1, obs: 1)\n", - "Coordinates:\n", - " * obs (obs) int32 4B 0\n", - " * trajectory (trajectory) int64 8B 42\n", - "Data variables:\n", - " lat (trajectory, obs) float32 4B dask.array\n", - " lon (trajectory, obs) float32 4B dask.array\n", - " salinity (trajectory, obs) float32 4B dask.array\n", - " temperature (trajectory, obs) float32 4B dask.array\n", - " time (trajectory, obs) datetime64[ns] 8B dask.array\n", - " z (trajectory, obs) float32 4B dask.array\n", - "Attributes:\n", - " Conventions: CF-1.6/CF-1.7\n", - " feature_type: trajectory\n", - " ncei_template_version: NCEI_NetCDF_Trajectory_Template_v2.0\n", - " parcels_mesh: spherical\n", - " parcels_version: 3.0.2" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ds" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n", - "ax.scatter(x, y, c=T, s=20, marker=\"o\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "py3_parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.3" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/submit.sh b/src/submit.sh deleted file mode 100644 index 7873fa87..00000000 --- a/src/submit.sh +++ /dev/null @@ -1,11 +0,0 @@ -#!/bin/bash -l -# -#SBATCH -J VSC # the name of your job -#SBATCH -p short # request the short partition, job takes less than 3 hours -#SBATCH -t 3:00:00 # time in hh:mm:ss you want to reserve for the job -#SBATCH -n 1 # the number of cores you want to use for the job, SLURM automatically determines how many nodes are needed -#SBATCH -o log%j.o # the name of the file where the standard output will be written to. %j will be the jobid determined by SLURM -#SBATCH -e log%j.e # the name of the file where potential errors will be written to. %j will be the jobid determined by SLURM - -conda activate parcels -srun ./cruise_simulation_CTD.py diff --git a/student_input.json b/student_input.json deleted file mode 100644 index ae13abeb..00000000 --- a/student_input.json +++ /dev/null @@ -1,40 +0,0 @@ -{ - "region_of_interest": { - "North": 64, - "East": -23, - "South": 59, - "West": -43 - }, - "requested_ship_time": { - "start": "2022-01-01T00:00:00", - "end": "2022-01-22T00:00:00" - }, - "route_coordinates": [ - [-23.071289, 63.743631], [-24.873047, 63.352129], [-24.973047, 63.252129] - ], - "underway_data": true, - "ADCP_data": false, - "ADCP_settings": { - "max_depth": -1000, - "bin_size_m": 24 - }, - "CTD_locations": [ - [-23.071289, 63.743631] - ], - "CTD_settings": { - "max_depth": "max" - }, - "drifter_deploylocations": [ - - ], - "argo_deploylocations": [ - [-24.873047, 63.352129] - ], - "argo_characteristics": { - "driftdepth": -1000, - "maxdepth": -2000, - "vertical_speed": -0.10, - "cycle_days" : 10, - "drift_days": 9 - } -} \ No newline at end of file diff --git a/teaching_material/.DS_Store b/teaching_material/.DS_Store deleted file mode 100644 index 03caf760..00000000 Binary files a/teaching_material/.DS_Store and /dev/null differ diff --git a/teaching_material/Assignment/CodeOfConduct.docx b/teaching_material/Assignment/CodeOfConduct.docx deleted file mode 100644 index 5af2d752..00000000 Binary files a/teaching_material/Assignment/CodeOfConduct.docx and /dev/null differ diff --git a/teaching_material/Assignment/CourseExamination2024.pdf b/teaching_material/Assignment/CourseExamination2024.pdf deleted file mode 100644 index fa89a784..00000000 Binary files a/teaching_material/Assignment/CourseExamination2024.pdf and /dev/null differ diff --git a/teaching_material/Assignment/Cruise proposal template.pdf b/teaching_material/Assignment/Cruise proposal template.pdf deleted file mode 100644 index 2fbadde6..00000000 Binary files a/teaching_material/Assignment/Cruise proposal template.pdf and /dev/null differ diff --git a/teaching_material/Assignment/Intro letter - info for participants.pdf b/teaching_material/Assignment/Intro letter - info for participants.pdf deleted file mode 100644 index 9accb9c8..00000000 Binary files a/teaching_material/Assignment/Intro letter - info for participants.pdf and /dev/null differ diff --git a/teaching_material/Assignment/Preparatory_exercises/A01_Q1.ipynb b/teaching_material/Assignment/Preparatory_exercises/A01_Q1.ipynb deleted file mode 100644 index 14654ca1..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A01_Q1.ipynb +++ /dev/null @@ -1,345 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "0172ff30-bee8-4cc9-8146-97d65e5289fb", - "metadata": {}, - "source": [ - "### Python Assignment 1\n", - "\n", - "In this assignment you will get familiar with analyzing drifter data. The drifters that we will use were released during the Australasian Antarctic Expedition in December 2013, a project designed to characterize eddy dispersion and diffusivity along an Antarctic Circumpolar Current front. For more information you may take a look at [this scientific article](https://doi.org/10.1002/2015JC010972). An animation of the drifters can be found on http://oceanparcels.org/aaemap.\n", - "\n", - "We assume that you have completed all steps in the *Getting python-ready for Dynamical Oceanography* document and have a new environment called *dyoc*. Now check that you are in the right environment by running the following cell:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9256daff-3fdd-4893-aced-382f93bbb794", - "metadata": {}, - "outputs": [], - "source": [ - "!conda env list" - ] - }, - { - "cell_type": "markdown", - "id": "99ea69f2-3199-4a7d-b4e2-0d4bce78c7f0", - "metadata": {}, - "source": [ - "You should see an asterisk next to your *dyoc* environment. If this is not the case, you may stop the *Jupyter lab* instance using `ctrl + c` in your terminal (Mac) or Anaconda prompt (Windows). Then type `conda activate dyoc` to activate the environment and `jupyter lab` to start *Jupyter lab* again. \n", - "\n", - "Now import the following packages:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "09816b5e-3c73-48fa-98fa-81f2766743cf", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "import json\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.dates as mdates\n", - "import matplotlib.colors as mcolors\n", - "import matplotlib.cm\n", - "import cartopy\n", - "import cmocean\n", - "import geopy.distance" - ] - }, - { - "cell_type": "markdown", - "id": "257c5e38-a90c-49f2-bb2c-73b175d15b45", - "metadata": {}, - "source": [ - "Then download the file `aaedrifters.json` from http://oceanparcels.org/aaemap by clicking on the right-most of the four icons on the bottom-left. Put that file it in the same directory or folder as this notebook and load the data using the code below" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "06e5f44e-7570-4e10-9d13-96a88b173a4e", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "def reshape_jsonarrays(item):\n", - " time = np.array([d[0] for d in item[1]], dtype='datetime64')\n", - " lat = np.array([d[1] for d in item[1]], dtype='float')\n", - " lon = np.array([d[2] for d in item[1]], dtype='float')\n", - " return {'name':item[0], 'time':time, 'lat':lat, 'lon':lon}\n", - "\n", - "with open(\"aaedrifters.json\") as fp:\n", - " jsondata = json.load(fp)\n", - "\n", - "drifters = [reshape_jsonarrays(item) for item in jsondata.items()]" - ] - }, - { - "cell_type": "markdown", - "id": "7b2fbd30", - "metadata": {}, - "source": [ - "Have a quick look of the content of the new `drifter` list by running the following cell:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "440cae47", - "metadata": {}, - "outputs": [], - "source": [ - "drifters" - ] - }, - { - "cell_type": "markdown", - "id": "ee738656-47e6-4a19-9dcc-700c555f6a33", - "metadata": {}, - "source": [ - "The drifter pairs were deployed on a straight line along the cruise track between approximately (56.0°S, 157.2°E) and (58.8°S, 153.5°E) over a 25 h period starting on 11 December 2013. \n", - "\n", - "Make a simple plot of all trajectories in `drifters` using `plt.plot`, both for the complete duration of the experiment and the first ten days after release." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c5342e54-a195-4883-80ce-5c265ab9069f", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "6ce3b0b6-7469-41b2-9fcf-3b62d462d27e", - "metadata": {}, - "source": [ - "To get a better view on the trajectories, it might be nice to show the continents as well. For this we use the `cartopy` package. Now run the following cell and see the resulting map." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9de0bef7-36ae-4cc3-b025-bb1dcf89c242", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "# We use the Platecarree projection centered at 180 degrees longitude\n", - "# on Cartopy's website you can find other projections to play around with\n", - "projection = cartopy.crs.PlateCarree(central_longitude=180)\n", - "\n", - "# whenever adding data having latitude-longitude coordinates, use PlateCarree() as coordinate reference system\n", - "data_crs = cartopy.crs.PlateCarree()\n", - "\n", - "# initialisation of the figure\n", - "fig = plt.figure(figsize=(12, 5))\n", - "ax = fig.add_subplot(1, 1, 1, projection=projection)\n", - "\n", - "# plot coastlines and colour the land surfaces\n", - "ax.coastlines(resolution='50m')\n", - "ax.add_feature(cartopy.feature.LAND)\n", - "\n", - "# plot trajectories\n", - "for d in drifters[:]:\n", - " ax.plot(d['lon'], d['lat'], transform=data_crs, lw=0.8)\n", - "\n", - "# plot grid lines and format the labels\n", - "# xlocs is needed because the locator does not work so well when crossing 180 degrees longitude\n", - "gl = ax.gridlines(crs=data_crs, draw_labels=['bottom','left'], linewidth=0.5,\n", - " color='gray', alpha=0.5, linestyle='--', xlocs=range(-180,181,10))\n", - "gl.xformatter = cartopy.mpl.gridliner.LONGITUDE_FORMATTER\n", - "gl.yformatter = cartopy.mpl.gridliner.LATITUDE_FORMATTER\n", - "\n", - "# zoom out to see more land masses\n", - "ax.set_extent((142,228,-77,-32), crs=data_crs)" - ] - }, - { - "cell_type": "markdown", - "id": "ccc5136f-377d-408d-a7c3-02254c2757e5", - "metadata": {}, - "source": [ - "Complete the function `drifter_velocity` below that computes the zonal and meridional velocities of a drifter. The function takes an element of `drifters` as an argument and returns two arrays, `u` and `v`. The remaining code will plot your results for drifter 130263. Make sure the vectors are aligned with the trajectory." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a605b9eb-6774-43cb-9a19-9bd8cd5f90a3", - "metadata": {}, - "outputs": [], - "source": [ - "# ANSWER\n", - "def drifter_velocity(data):\n", - " \"\"\"compute zonal and meridional velocities of drifter\n", - " data : dictionary containing arrays time, lat and lon\n", - " u, v : array, zonal (meridional) velocity\n", - " \"\"\"\n", - " # enter your code here\n", - " return u,v\n", - "\n", - "data = drifters[4]\n", - "u,v = drifter_velocity(data)\n", - "\n", - "crs = cartopy.crs.PlateCarree()\n", - "ax = plt.axes(projection=crs)\n", - "pids = slice(1200,1550,4)\n", - "Q = ax.quiver(data['lon'][pids], data['lat'][pids], u[pids], v[pids], transform=crs, lw=0.5)\n", - "ax.quiverkey(Q, 0.92, 0.05, 0.5, label='0.5 m/s')\n", - "ax.set_title(f\"velocity of drifter {data['name']}\")\n", - "ax.gridlines(draw_labels=['left','bottom'], dms=True)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "ad1b4032-437a-4797-9502-bb98e6e04409", - "metadata": {}, - "source": [ - "Now use the function `drifter_velocity` to create maps of zonal and meridional velocity for all drifters. Part of the code to plot the results has been given below. \n", - "Hint: use `ax.scatter` to change colour along the trajectories." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dc3be3f1-312f-472e-89b1-1d3a8d390cb3", - "metadata": {}, - "outputs": [], - "source": [ - "# compute velocities here" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ac2f5a0d-7030-451f-91ef-9086075aa824", - "metadata": {}, - "outputs": [], - "source": [ - "ax = plt.axes(projection=cartopy.crs.PlateCarree(central_longitude=180))\n", - "\n", - "# plot results for u here\n", - "\n", - "ax.set_title(\"zonal velocity\")\n", - "ax.coastlines('50m')\n", - "ax.gridlines(draw_labels=['left','bottom'], transform=cartopy.crs.PlateCarree(), xlocs=range(-180,180,10))\n", - "ax.figure.colorbar(p, orientation='horizontal', extend='both', label=\"u (m/s)\", aspect=50, pad=0.08)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a7c7cfff-00de-4883-9e3c-a2ca77702ae0", - "metadata": {}, - "outputs": [], - "source": [ - "ax = plt.axes(projection=cartopy.crs.PlateCarree(central_longitude=180))\n", - "\n", - "# plot results for v here\n", - "\n", - "ax.set_title(\"meridional velocity\")\n", - "ax.coastlines('50m')\n", - "ax.gridlines(draw_labels=['left','bottom'], transform=cartopy.crs.PlateCarree(), xlocs=range(-180,180,10))\n", - "ax.figure.colorbar(p, orientation='horizontal', extend='both', label=\"v (m/s)\", aspect=50, pad=0.08)" - ] - }, - { - "cell_type": "markdown", - "id": "26b13693-4587-4d8a-9126-a24fe3146d4e", - "metadata": {}, - "source": [ - "The drifters have been released in pairs, about 13 meter apart on either side of the ship. This makes it possible to analyze the separation distance, which is a measure for dispersion. The cell below creates a list, `dists`, of dictionaries containing time, launching latitude, names and distance, $D$, between the drifters of each pair. \n", - "Run it now and plot the drifter separation as a function of time for all drifters for the first ten days after launch. You may change the scale of the y-axis to logarithmic or symmetric logarithmic with `ax.set_yscale`. How does the separation after ten days depend on launching latitude?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "366a3e9c-14df-44b4-b8f2-25ce1ca75a16", - "metadata": {}, - "outputs": [], - "source": [ - "def separation(data1, data2):\n", - " \"\"\"calculate separation distance between two drifters\"\"\"\n", - " time1 = data1['time']\n", - " time2 = data2['time']\n", - " time = np.array(sorted(set(time1).intersection(set(time2))))\n", - " tids1 = np.searchsorted(time1, time)\n", - " tids2 = np.searchsorted(time2, time)\n", - " lats1 = data1['lat'][tids1]\n", - " lons1 = data1['lon'][tids1]\n", - " lats2 = data2['lat'][tids2]\n", - " lons2 = data2['lon'][tids2]\n", - " dist = [geopy.distance.distance((lat1,lon1),(lat2,lon2)).m for (lat1, lon1, lat2, lon2)\n", - " in zip(lats1, lons1, lats2, lons2)]\n", - " return {'name1':data1['name'], 'name2':data2['name'], 'time':time,\n", - " 'lat0':data1['lat'][0], 'distance':np.array(dist)}\n", - "\n", - "lats = np.array([d['lat'][0] for d in drifters])\n", - "pairids = lats.argsort().reshape((-1,2)).tolist()\n", - "dists = []\n", - "for n,(i,j) in enumerate(pairids):\n", - " print(f\"\\ranalyzing pair {n+1}/{len(pairids)}\", end=\"\")\n", - " dists.append(separation(drifters[i], drifters[j]))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8416d797-094b-480c-b7dc-a1d1a2ec0b8d", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "840a24d2-b388-4489-ad0d-e478cefe3a91", - "metadata": {}, - "source": [ - "It is time to compare your results. Create a plot of the pairwise dispersion, $D^2$, similar to figure 5a in the [article](https://doi.org/10.1002/2015JC010972). You do not need to fit the data and calculate the slopes, but do check if the impact of the outlier drifter pair on the mean is similar." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ba5fe542-78fa-48f6-8ac9-baf9d276143e", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A01_Q1_withanswer.ipynb b/teaching_material/Assignment/Preparatory_exercises/A01_Q1_withanswer.ipynb deleted file mode 100644 index 7c912fa3..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A01_Q1_withanswer.ipynb +++ /dev/null @@ -1,751 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "0172ff30-bee8-4cc9-8146-97d65e5289fb", - "metadata": {}, - "source": [ - "### Python Assignment 1\n", - "\n", - "In this assignment you will get familiar with analyzing drifter data. The drifters that we will use were released during the Australasian Antarctic Expedition in December 2013, a project designed to characterize eddy dispersion and diffusivity along an Antarctic Circumpolar Current front. For more information you may take a look at [this scientific article](https://doi.org/10.1002/2015JC010972). An animation of the drifters can be found on http://oceanparcels.org/aaemap.\n", - "\n", - "We assume that you have completed all steps in the *Getting python-ready for Dynamical Oceanography* document and have a new environment called *dyoc*. Now check that you are in the right environment by running the following cell:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "9256daff-3fdd-4893-aced-382f93bbb794", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "# conda environments:\n", - "#\n", - "base /Users/jasperdejong/opt/anaconda3\n", - "dyoc * /Users/jasperdejong/opt/anaconda3/envs/dyoc\n", - "py311 /Users/jasperdejong/opt/anaconda3/envs/py311\n", - "\n" - ] - } - ], - "source": [ - "!conda env list" - ] - }, - { - "cell_type": "markdown", - "id": "99ea69f2-3199-4a7d-b4e2-0d4bce78c7f0", - "metadata": {}, - "source": [ - "You should see an asterisk next to your *dyoc* environment. If this is not the case, you may stop the *Jupyter lab* instance using `ctrl + c` in your terminal (Mac) or Anaconda prompt (Windows). Then type `conda activate dyoc` to activate the environment and `jupyter lab` to start *Jupyter lab* again. \n", - "\n", - "Now import the following packages:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "09816b5e-3c73-48fa-98fa-81f2766743cf", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "import json\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.dates as mdates\n", - "import matplotlib.colors as mcolors\n", - "import matplotlib.cm\n", - "import cartopy\n", - "import cmocean\n", - "import geopy.distance" - ] - }, - { - "cell_type": "markdown", - "id": "257c5e38-a90c-49f2-bb2c-73b175d15b45", - "metadata": {}, - "source": [ - "Then download the file `aaedrifters.json` from http://oceanparcels.org/aaemap by clicking on the right-most of the four icons on the bottom-left. Put that file it in the same directory or folder as this notebook and load the data using the code below" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "06e5f44e-7570-4e10-9d13-96a88b173a4e", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "def reshape_jsonarrays(item):\n", - " time = np.array([d[0] for d in item[1]], dtype='datetime64')\n", - " lat = np.array([d[1] for d in item[1]], dtype='float')\n", - " lon = np.array([d[2] for d in item[1]], dtype='float')\n", - " return {'name':item[0], 'time':time, 'lat':lat, 'lon':lon}\n", - "\n", - "with open(\"aaedrifters.json\") as fp:\n", - " jsondata = json.load(fp)\n", - "\n", - "drifters = [reshape_jsonarrays(item) for item in jsondata.items()]" - ] - }, - { - "cell_type": "markdown", - "id": "7b2fbd30", - "metadata": {}, - "source": [ - "Have a quick look of the content of the new `drifter` list by running the following cell:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "440cae47", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[{'name': '130258',\n", - " 'time': array(['2013-12-11T17:00:00', '2013-12-11T18:00:00',\n", - " '2013-12-11T18:59:59', ..., '2014-07-31T20:00:00',\n", - " '2014-07-31T21:00:00', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-56.472, -56.471, -56.471, ..., -52.507, -52.508, -52.509]),\n", - " 'lon': array([156.648, 156.658, 156.667, ..., 212.221, 212.229, 212.242])},\n", - " {'name': '130259',\n", - " 'time': array(['2013-12-11T17:00:00', '2013-12-11T18:00:00',\n", - " '2013-12-11T18:59:59', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-56.472, -56.471, -56.472, ..., -49.301, -49.286, -49.271]),\n", - " 'lon': array([156.648, 156.658, 156.667, ..., 198.133, 198.145, 198.156])},\n", - " {'name': '130260',\n", - " 'time': array(['2013-12-12T06:59:59', '2013-12-12T08:00:00',\n", - " '2013-12-12T09:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.995, -57.994, -57.995, ..., -54.323, -54.319, -54.316]),\n", - " 'lon': array([154.576, 154.577, 154.578, ..., 195.452, 195.451, 195.447])},\n", - " {'name': '130261',\n", - " 'time': array(['2013-12-12T00:59:59', '2013-12-12T02:00:00',\n", - " '2013-12-12T03:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.341, -57.351, -57.359, ..., -55.213, -55.215, -55.218]),\n", - " 'lon': array([155.463, 155.469, 155.478, ..., 205.628, 205.628, 205.63 ])},\n", - " {'name': '130263',\n", - " 'time': array(['2013-12-11T21:00:00', '2013-12-11T21:59:59',\n", - " '2013-12-11T23:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-56.836, -56.844, 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dtype='datetime64[s]'),\n", - " 'lat': array([-57.699, -57.695, -57.691, ..., -54.507, -54.508, -54.507]),\n", - " 'lon': array([154.991, 155.008, 155.02 , ..., 196.096, 196.104, 196.111])},\n", - " {'name': '130269',\n", - " 'time': array(['2013-12-12T03:00:00', '2013-12-12T03:59:59',\n", - " '2013-12-12T05:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.486, -57.489, -57.49 , ..., -52.844, -52.846, -52.849]),\n", - " 'lon': array([155.279, 155.294, 155.308, ..., 204.999, 205.016, 205.033])},\n", - " {'name': '130270',\n", - " 'time': array(['2013-12-12T00:00:00', '2013-12-12T00:59:59',\n", - " '2013-12-12T02:00:00', ..., '2014-07-31T20:00:00',\n", - " '2014-07-31T21:00:00', '2014-07-31T21:59:59'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.133, -57.145, -57.156, ..., -56.859, -56.86 , -56.861]),\n", - " 'lon': array([155.763, 155.766, 155.769, ..., 199.403, 199.41 , 199.417])},\n", - " {'name': '130271',\n", - " 'time': array(['2013-12-12T12:59:59', '2013-12-12T14:00:00',\n", - " '2013-12-12T15:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-58.805, -58.814, -58.821, ..., -62.373, -62.375, -62.377]),\n", - " 'lon': array([153.471, 153.489, 153.512, ..., 185.003, 185. , 184.998])},\n", - " {'name': '130272',\n", - " 'time': array(['2013-12-12T05:00:00', '2013-12-12T06:00:00',\n", - " '2013-12-12T06:59:59', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.703, -57.703, -57.701, ..., -57.908, -57.907, -57.906]),\n", - " 'lon': array([154.992, 155.008, 155.018, ..., 197.019, 197.019, 197.019])},\n", - " {'name': '130279',\n", - " 'time': array(['2013-12-12T12:59:59', '2013-12-12T14:00:00',\n", - " '2013-12-12T15:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-58.805, -58.813, -58.82 , ..., -55.623, -55.622, -55.622]),\n", - " 'lon': array([153.471, 153.49 , 153.514, ..., 195.457, 195.456, 195.456])},\n", - " {'name': '130280',\n", - " 'time': array(['2013-12-12T06:59:59', '2013-12-12T08:00:00',\n", - " '2013-12-12T09:00:00', ..., '2014-04-27T15:59:59',\n", - " '2014-04-27T17:00:00', '2014-04-27T18:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.995, -57.994, -57.995, ..., -57.359, -57.362, -57.366]),\n", - " 'lon': array([154.575, 154.577, 154.578, ..., 173.313, 173.315, 173.317])},\n", - " {'name': '130281',\n", - " 'time': array(['2013-12-11T21:00:00', '2013-12-11T21:59:59',\n", - " '2013-12-11T23:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-56.836, -56.844, -56.852, ..., -50.072, -50.079, -50.086]),\n", - " 'lon': array([156.161, 156.172, 156.184, ..., 200.618, 200.636, 200.653])},\n", - " {'name': '130282',\n", - " 'time': array(['2013-12-12T00:00:00', '2013-12-12T00:59:59',\n", - " '2013-12-12T02:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.133, -57.146, -57.156, ..., -53.093, -53.103, -53.114]),\n", - " 'lon': array([155.763, 155.766, 155.769, ..., 206.599, 206.62 , 206.643])},\n", - " {'name': '130283',\n", - " 'time': array(['2013-12-11T12:00:00', '2013-12-11T12:59:59',\n", - " '2013-12-11T14:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-56.043, -56.044, -56.044, ..., -56.148, -56.15 , -56.153]),\n", - " 'lon': array([157.235, 157.236, 157.238, ..., 193.257, 193.269, 193.285])},\n", - " {'name': '130361',\n", - " 'time': array(['2013-12-12T03:00:00', '2013-12-12T03:59:59',\n", - " '2013-12-12T05:00:00', ..., '2014-07-31T21:00:00',\n", - " '2014-07-31T21:59:59', '2014-07-31T23:00:00'],\n", - " dtype='datetime64[s]'),\n", - " 'lat': array([-57.486, -57.488, -57.49 , ..., -54.444, -54.437, -54.431]),\n", - " 'lon': array([155.279, 155.294, 155.307, ..., 184.488, 184.516, 184.544])}]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "drifters" - ] - }, - { - "cell_type": "markdown", - "id": "ee738656-47e6-4a19-9dcc-700c555f6a33", - "metadata": {}, - "source": [ - "The drifter pairs were deployed on a straight line along the cruise track between approximately (56.0°S, 157.2°E) and (58.8°S, 153.5°E) over a 25 h period starting on 11 December 2013. \n", - "\n", - "Make a simple plot of all trajectories in `drifters` using `plt.plot`, both for the complete duration of the experiment and the first ten days after release." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "c5342e54-a195-4883-80ce-5c265ab9069f", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "for data in drifters:\n", - " plt.plot(data['lon'], data['lat'])\n", - "plt.title(f\"trajectories of drifters\")\n", - "plt.grid()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "6d515f7a-860d-4fb6-a2f7-13dcaccd5738", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "ndays = 10 # number of days from start to plot\n", - "for data in drifters:\n", - " days = (data['time']-data['time'][0]).astype('timedelta64[D]').astype('int')\n", - " imax = list(days).index(ndays)\n", - " plt.scatter(data['lon'][:imax], data['lat'][:imax],s=0.5)\n", - "plt.title(f'trajectories first {ndays} days')\n", - "plt.grid()" - ] - }, - { - "cell_type": "markdown", - "id": "6ce3b0b6-7469-41b2-9fcf-3b62d462d27e", - "metadata": {}, - "source": [ - "To get a better view on the trajectories, it might be nice to show the continents as well. For this we use the `cartopy` package. Now run the following cell and see the resulting map." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "9de0bef7-36ae-4cc3-b025-bb1dcf89c242", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# We use the Platecarree projection centered at 180 degrees longitude\n", - "# on Cartopy's website you can find other projections to play around with\n", - "projection = cartopy.crs.PlateCarree(central_longitude=180)\n", - "\n", - "# whenever adding data having latitude-longitude coordinates, use PlateCarree() as coordinate reference system\n", - "data_crs = cartopy.crs.PlateCarree()\n", - "\n", - "# initialisation of the figure\n", - "fig = plt.figure(figsize=(12, 5))\n", - "ax = fig.add_subplot(1, 1, 1, projection=projection)\n", - "\n", - "# plot coastlines and colour the land surfaces\n", - "ax.coastlines(resolution='50m')\n", - "ax.add_feature(cartopy.feature.LAND)\n", - "\n", - "# plot trajectories\n", - "for d in drifters[:]:\n", - " ax.plot(d['lon'], d['lat'], transform=data_crs, lw=0.8)\n", - "\n", - "# plot grid lines and format the labels\n", - "# xlocs is needed because the locator does not work so well when crossing 180 degrees longitude\n", - "gl = ax.gridlines(crs=data_crs, draw_labels=['bottom','left'], linewidth=0.5,\n", - " color='gray', alpha=0.5, linestyle='--', xlocs=range(-180,181,10))\n", - "gl.xformatter = cartopy.mpl.gridliner.LONGITUDE_FORMATTER\n", - "gl.yformatter = cartopy.mpl.gridliner.LATITUDE_FORMATTER\n", - "\n", - "# zoom out to see more land masses\n", - "ax.set_extent((142,228,-77,-32), crs=data_crs)" - ] - }, - { - "cell_type": "markdown", - "id": "ccc5136f-377d-408d-a7c3-02254c2757e5", - "metadata": {}, - "source": [ - "Complete the function `drifter_velocity` below that computes the zonal and meridional velocities of a drifter. The function takes an element of `drifters` as an argument and returns two arrays, `u` and `v`. The remaining code will plot your results for drifter 130263. Make sure the vectors are aligned with the trajectory." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "a605b9eb-6774-43cb-9a19-9bd8cd5f90a3", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "def drifter_velocity(data):\n", - " \"\"\"compute zonal and meridional velocities of drifter\n", - " data : dictionary containing arrays time, lat and lon\n", - " u, v : array, zonal (meridional) velocity\n", - " \"\"\"\n", - " Re = 6371000 # radius earth (m)\n", - " time = (data['time'] - data['time'][0]).astype('timedelta64[s]')\n", - " latr = np.deg2rad(data['lat'])\n", - " lonr = np.deg2rad(data['lon'])\n", - " u = Re*np.cos(latr)*np.gradient(lonr,time)\n", - " v = Re*np.gradient(latr,time)\n", - " return u,v\n", - "\n", - "data = drifters[4]\n", - "u,v = drifter_velocity(data)\n", - "\n", - "crs = cartopy.crs.PlateCarree()\n", - "ax = plt.axes(projection=crs)\n", - "pids = slice(1200,1550,4)\n", - "Q = ax.quiver(data['lon'][pids], data['lat'][pids], u[pids], v[pids], transform=crs, lw=0.5)\n", - "ax.quiverkey(Q, 0.92, 0.05, 0.5, label='0.5 m/s')\n", - "ax.set_title(f\"velocity of drifter {data['name']}\")\n", - "ax.gridlines(draw_labels=['left','bottom'], dms=True)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "ad1b4032-437a-4797-9502-bb98e6e04409", - "metadata": {}, - "source": [ - "Now use the function `drifter_velocity` to create maps of zonal and meridional velocity for all drifters. Part of the code to plot the results has been given below. \n", - "Hint: use `ax.scatter` to change colour along the trajectories." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "dc3be3f1-312f-472e-89b1-1d3a8d390cb3", - "metadata": {}, - "outputs": [], - "source": [ - "# ANSWER\n", - "for d,data in enumerate(drifters):\n", - " u,v = drifter_velocity(data)\n", - " drifters[d]['u'] = u\n", - " drifters[d]['v'] = v" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "ac2f5a0d-7030-451f-91ef-9086075aa824", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ax = plt.axes(projection=cartopy.crs.PlateCarree(central_longitude=180))\n", - "\n", - "# ANSWER\n", - "for data in drifters:\n", - " p = ax.scatter(data['lon'], data['lat'], c=data['u'], s=1, vmin=-1.5, vmax=1.5,\n", - " cmap=cmocean.cm.balance, transform=cartopy.crs.PlateCarree())\n", - "# ----\n", - "ax.set_title(\"zonal velocity\")\n", - "ax.coastlines('50m')\n", - "ax.gridlines(draw_labels=['left','bottom'], transform=cartopy.crs.PlateCarree(), xlocs=range(-180,180,10))\n", - "ax.figure.colorbar(p, orientation='horizontal', extend='both', label=\"u (m/s)\", aspect=50, pad=0.08)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "a7c7cfff-00de-4883-9e3c-a2ca77702ae0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ax = plt.axes(projection=cartopy.crs.PlateCarree(central_longitude=180))\n", - "\n", - "# ANSWER\n", - "for data in drifters:\n", - " p = ax.scatter(data['lon'], data['lat'], c=data['v'], s=1, vmin=-1.5, vmax=1.5,\n", - " cmap=cmocean.cm.balance, transform=cartopy.crs.PlateCarree())\n", - "# ----\n", - "ax.set_title(\"meridional velocity\")\n", - "ax.coastlines('50m')\n", - "ax.gridlines(draw_labels=['left','bottom'], transform=cartopy.crs.PlateCarree(), xlocs=range(-180,180,10))\n", - "ax.figure.colorbar(p, orientation='horizontal', extend='both', label=\"v (m/s)\", aspect=50, pad=0.08)" - ] - }, - { - "cell_type": "markdown", - "id": "26b13693-4587-4d8a-9126-a24fe3146d4e", - "metadata": {}, - "source": [ - "The drifters have been released in pairs, about 13 meter apart on either side of the ship. This makes it possible to analyze the separation distance, which is a measure for dispersion. The cell below creates a list, `dists`, of dictionaries containing time, launching latitude, names and distance, $D$, between the drifters of each pair. \n", - "Run it now and plot the drifter separation as a function of time for all drifters for the first ten days after launch. You may change the scale of the y-axis to logarithmic or symmetric logarithmic with `ax.set_yscale`. How does the separation after ten days depend on launching latitude?" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "366a3e9c-14df-44b4-b8f2-25ce1ca75a16", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "analyzing pair 10/10" - ] - } - ], - "source": [ - "def separation(data1, data2):\n", - " \"\"\"calculate separation distance between two drifters\"\"\"\n", - " time1 = data1['time']\n", - " time2 = data2['time']\n", - " time = np.array(sorted(set(time1).intersection(set(time2))))\n", - " tids1 = np.searchsorted(time1, time)\n", - " tids2 = np.searchsorted(time2, time)\n", - " lats1 = data1['lat'][tids1]\n", - " lons1 = data1['lon'][tids1]\n", - " lats2 = data2['lat'][tids2]\n", - " lons2 = data2['lon'][tids2]\n", - " dist = [geopy.distance.distance((lat1,lon1),(lat2,lon2)).m for (lat1, lon1, lat2, lon2)\n", - " in zip(lats1, lons1, lats2, lons2)]\n", - " return {'name1':data1['name'], 'name2':data2['name'], 'time':time,\n", - " 'lat0':data1['lat'][0], 'distance':np.array(dist)}\n", - "\n", - "lats = np.array([d['lat'][0] for d in drifters])\n", - "pairids = lats.argsort().reshape((-1,2)).tolist()\n", - "dists = []\n", - "for n,(i,j) in enumerate(pairids):\n", - " print(f\"\\ranalyzing pair {n+1}/{len(pairids)}\", end=\"\")\n", - " dists.append(separation(drifters[i], drifters[j]))" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "8416d797-094b-480c-b7dc-a1d1a2ec0b8d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "# students may deviate from the plot below, as long as they show the time evolution of drifter separation in a clear manner\n", - "# to find the relation with launching latitude, they could also simply label the lines or print the distance values at t=10days\n", - "maxtime = np.datetime64(\"2013-12-21\") # xlim\n", - "\n", - "# plotting\n", - "ax = plt.subplot()\n", - "norm = mcolors.Normalize(vmin=-58.805,vmax=-56.043)\n", - "cmap = matplotlib.colormaps['plasma']\n", - "lats0 = list(reversed([d['lat0'] for d in dists]))\n", - "lines = []\n", - "for dist in dists:\n", - " tmax = np.argmax(dist['time'] > maxtime)\n", - " lines.append(ax.plot(dist['time'][:tmax], dist['distance'][:tmax]/1000,\n", - " c=cmap(norm(dist['lat0']))))\n", - " x=lines[-1][0].get_xdata()[-1] + np.timedelta64(4,'h')\n", - " y=lines[-1][0].get_ydata()[-1]\n", - " ax.text(x, y, str(lats0.index(dist['lat0'])), va='center', ha='left')\n", - "\n", - "# formatting\n", - "ax.xaxis.set_major_locator(mdates.DayLocator(interval=3))\n", - "ax.xaxis.set_minor_locator(mdates.DayLocator())\n", - "ax.set_title(f\"distance between drifters\")\n", - "ax.set_ylabel('distance (km)')\n", - "ax.set_yscale('symlog')\n", - "ax.grid()\n", - "\n", - "# colorbar\n", - "cb = ax.figure.colorbar(\n", - " matplotlib.cm.ScalarMappable(norm=norm, cmap=cmap),\n", - " ax=ax, orientation='vertical', label='launch latitude')\n", - "cb.ax.yaxis.set_major_formatter(cartopy.mpl.ticker.LatitudeFormatter())\n", - "cb.ax.set_yticks(lats0, labels=range(len(dists)), minor=True)\n", - "cb.ax.yaxis.set_tick_params(which='minor', left=True, right=False, labelleft=True, labelright=False)" - ] - }, - { - "cell_type": "markdown", - "id": "840a24d2-b388-4489-ad0d-e478cefe3a91", - "metadata": {}, - "source": [ - "It is time to compare your results. Create a plot of the pairwise dispersion, $D^2$, similar to figure 5a in the [article](https://doi.org/10.1002/2015JC010972). You do not need to fit the data and calculate the slopes, but do check if the impact of the outlier drifter pair on the mean is similar." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "ba5fe542-78fa-48f6-8ac9-baf9d276143e", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "# the different colours depending on launching latitude again not needed\n", - "# values are interpolated to specific time stamps before taking the ensemble mean, any other method is fine here\n", - "# results actually deviate slightly from paper, maybe worth looking into\n", - "\n", - "# plotting drifter data\n", - "ax = plt.subplot()\n", - "norm = mcolors.Normalize(vmin=-58.805,vmax=-56.043)\n", - "cmap = matplotlib.colormaps['plasma']\n", - "lats0 = list(reversed([d['lat0'] for d in dists]))\n", - "lines = []\n", - "disps_m = []\n", - "days_m = 10**np.linspace(-1.2,2.365,500) # time points to evaluate mean\n", - "for i,dist in enumerate(dists):\n", - " if dist['distance'][0] > 200:\n", - " ls = '--'\n", - " ioutlier = i\n", - " else:\n", - " ls = '-'\n", - " time = dist['time'] - dist['time'][0]\n", - " days = time.astype('timedelta64[s]').astype('int')/86400\n", - " lines.append(ax.plot(days, dist['distance']**2,\n", - " c=cmap(norm(dist['lat0'])), lw=0.5, ls=ls))\n", - " disps_m.append(np.interp(days_m,days,dist['distance']**2, right=np.nan))\n", - " # x=lines[-1][0].get_xdata()[-1] + 1/6\n", - " # y=lines[-1][0].get_ydata()[-1]\n", - " # ax.text(x, y, str(lats0.index(dist['lat0'])), va='center', ha='left')\n", - "\n", - "# plot ensemble mean\n", - "disp_m = np.nanmean(disps_m, axis=0)\n", - "disps_m.pop(ioutlier)\n", - "disp_m_corr = np.nanmean(disps_m, axis=0)\n", - "ax.plot(days_m, disp_m, 'k--', lw=2, label='average')\n", - "ax.plot(days_m, disp_m_corr, 'k-', lw=2, label='average without outlier')\n", - "\n", - "\n", - "# formatting\n", - "ax.legend(loc='upper left')\n", - "ax.set_title(f\"drifter dispersion\")\n", - "ax.set_xlabel('days since release')\n", - "ax.set_ylabel(r'drifter dispersion $D^2$ [m$^{-2}$]')\n", - "ax.set_xscale('log')\n", - "ax.set_yscale('log')\n", - "ax.set_xlim([10**(-2),2.6*10**2])\n", - "ax.grid()\n", - "\n", - "# colorbar\n", - "cb = ax.figure.colorbar(\n", - " matplotlib.cm.ScalarMappable(norm=norm, cmap=cmap),\n", - " ax=ax, orientation='vertical', label='launch latitude')\n", - "cb.ax.yaxis.set_major_formatter(cartopy.mpl.ticker.LatitudeFormatter())\n", - "# cb.ax.set_yticks(lats0, labels=range(len(dists)), minor=True)\n", - "# cb.ax.yaxis.set_tick_params(which='minor', left=True, right=False, labelleft=True, labelright=False)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A02_Q1.ipynb b/teaching_material/Assignment/Preparatory_exercises/A02_Q1.ipynb deleted file mode 100644 index fe949764..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A02_Q1.ipynb +++ /dev/null @@ -1,352 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a30f51ea", - "metadata": {}, - "source": [ - "### Assignment 2.1: Argo floats in the Tropical Atlantic\n", - "\n", - "In this assignment, you will simulate the temperature and salinity profiles of an Argo float using the Parcels toolbox.\n", - "\n", - "First, make sure you have the right environment activated and import the following packages." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cd00b0bc-2ca2-40ea-91ce-e0622a4edcc6", - "metadata": {}, - "outputs": [], - "source": [ - "from parcels import FieldSet, ParticleSet, JITParticle, Variable, AdvectionRK4, ScipyParticle, StatusCode\n", - "import numpy as np\n", - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "from datetime import timedelta\n", - "import cmocean" - ] - }, - { - "cell_type": "markdown", - "id": "e0a1719f", - "metadata": {}, - "source": [ - "For the Parcels simulation, you will need to download a NetCDF file with the hydrodynamic (velocities, temperature, salinity) data. We use data from the Copernicus Marine Environmental Monitoring Service (CMEMS) [Global Ocean 1/12° Physics Analysis and Forecast product](https://resources.marine.copernicus.eu/product-detail/GLOBAL_ANALYSIS_FORECAST_PHY_001_024/INFORMATION). For this assignment, we've compiled all the flow data you need into one file (~120MB), which you can find on Blackboard.\n", - "\n", - "Put that file into the directory that also holds this notebook and then execute the code below to create what's in Parcels called a `FieldSet` object" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "50bbbadf", - "metadata": {}, - "outputs": [], - "source": [ - "filename = 'global-analysis-forecast-phy-001-024_1641284158025.nc'\n", - "variables = {'U': 'uo', # dictionary with names of the variables in the netcdf file\n", - " 'V': 'vo',\n", - " 'S': 'so',\n", - " 'T': 'thetao'}\n", - "dimensions = {'lon': 'longitude', # dictionary with names of the dimensions in the netcdf file\n", - " 'lat': 'latitude',\n", - " 'depth': 'depth',\n", - " 'time': 'time'}\n", - "\n", - "fieldset = FieldSet.from_netcdf(filename, variables, dimensions)\n", - "fieldset.mindepth = fieldset.U.depth[0] # uppermost layer in the hydrodynamic data" - ] - }, - { - "cell_type": "markdown", - "id": "b9874515", - "metadata": {}, - "source": [ - "You can plot the two components of the flow field (at the surface) with the following code." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6811eb8f", - "metadata": {}, - "outputs": [], - "source": [ - "fieldset.computeTimeChunk() # first load the data in memory\n", - "\n", - "fig, ax = plt.subplots(1, 2, sharex=True, sharey=True)\n", - "p0 = ax[0].pcolormesh(fieldset.U.lon, fieldset.U.lat, fieldset.U.data[0,0,:,:], vmin=-1.5, vmax=1.5, cmap=cmocean.cm.balance)\n", - "p1 = ax[1].pcolormesh(fieldset.V.lon, fieldset.V.lat, fieldset.V.data[0,0,:,:], vmin=-1.5, vmax=1.5, cmap=cmocean.cm.balance)\n", - "ax[0].set_title('zonal velocity')\n", - "ax[1].set_title('meridional velocity')\n", - "ax[0].set_ylabel('latitude [°N]')\n", - "ax[0].set_xlabel('longitude [°E]')\n", - "ax[1].set_xlabel('longitude [°E]')\n", - "ax[1].yaxis.set_tick_params(left=False, right=True, labelleft=False, labelright=True)\n", - "ax[0].grid()\n", - "ax[1].grid()\n", - "cb = fig.colorbar(p1, ax=ax, orientation='horizontal')\n", - "cb.set_label('[m/s]')\n", - "gd = fieldset.U.grid\n", - "fig.suptitle(f\"velocity at depth {gd.depth[0]:.2f} m, {gd.timeslices[0][0].astype('datetime64[m]')}\")\n", - "plt.show()\n", - "\n", - "print(f\"The dimensions of the data are:\\nlon: {gd.xdim}\\nlat: {gd.ydim}\\ndepth: {gd.zdim}\\ntime: {len(gd.time_full)} ({gd.tdim} loaded)\")" - ] - }, - { - "cell_type": "markdown", - "id": "713f3bcb-dc11-411f-8bb4-499977e2863a", - "metadata": {}, - "source": [ - "Parcels uses the oceanic data in `fieldset` to represent the environment of a 'particle'. Particles are objects that by default hold information on there position and time. The behaviour of particles is determined by a kernel. A commonly used kernel is `AdvectionRK4`, which prescribes advection using a 4th order Runge-Kutta numerical scheme. The `fieldset` data is interpolated to the particle position and time, then the particle gets advected to determine velocities at the new position. This process is repeated three times in a clever way to minimize the numerical error." - ] - }, - { - "cell_type": "markdown", - "id": "11edb95b", - "metadata": {}, - "source": [ - "A few years ago, [Mike Hart-Davis](https://www.dgfi.tum.de/en/staff/hart-davis-michael/) wrote a `Kernel` for Parcels to easily simulate the behaviour of an Argo float. That code, which is also available in [this notebook tutorial](https://docs.oceanparcels.org/en/latest/examples/tutorial_Argofloats.html), is copied in the cell below. Go through it and make sure you understand what it does. For practical purposes, you may assume `particle.depth` and `particle_ddepth` both represent the particle depth.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0c28d2c0", - "metadata": {}, - "outputs": [], - "source": [ - "# Define the new Kernel that mimics Argo vertical movement\n", - "def ArgoVerticalMovement(particle, fieldset, time):\n", - " driftdepth = 1000 # maximum depth in m\n", - " maxdepth = 2000 # maximum depth in m\n", - " vertical_speed = 0.10 # sink and rise speed in m/s\n", - " cycletime = 10 * 86400 # total time of cycle in seconds\n", - " drifttime = 9 * 86400 # time of deep drift in seconds\n", - "\n", - " if particle.cycle_phase == 0:\n", - " # Phase 0: Sinking with vertical_speed until depth is driftdepth\n", - " particle_ddepth += vertical_speed * particle.dt\n", - " if particle.depth >= driftdepth:\n", - " particle.cycle_phase = 1\n", - "\n", - " elif particle.cycle_phase == 1:\n", - " # Phase 1: Drifting at depth for drifttime seconds\n", - " particle.drift_age += particle.dt\n", - " if particle.drift_age >= drifttime:\n", - " particle.drift_age = 0 # reset drift_age for next cycle\n", - " particle.cycle_phase = 2\n", - "\n", - " elif particle.cycle_phase == 2:\n", - " # Phase 2: Sinking further to maxdepth\n", - " particle_ddepth += vertical_speed * particle.dt\n", - " if particle.depth >= maxdepth:\n", - " particle.cycle_phase = 3\n", - "\n", - " elif particle.cycle_phase == 3:\n", - " # Phase 3: Rising with vertical_speed until at surface\n", - " particle_ddepth -= vertical_speed * particle.dt\n", - " particle.cycle_age += particle.dt # solve issue of not updating cycle_age during ascent\n", - " if particle.depth <= fieldset.mindepth:\n", - " particle.depth = fieldset.mindepth\n", - " particle.temp = math.nan # reset temperature to NaN at end of sampling cycle\n", - " particle.salt = math.nan # idem\n", - " particle.cycle_phase = 4\n", - " else:\n", - " particle.temp = fieldset.T[time, particle.depth, particle.lat, particle.lon]\n", - " particle.salt = fieldset.S[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - " elif particle.cycle_phase == 4:\n", - " # Phase 4: Transmitting at surface until cycletime is reached\n", - " if particle.cycle_age > cycletime:\n", - " particle.cycle_phase = 0\n", - " particle.cycle_age = 0\n", - "\n", - " if particle.state == StatusCode.Evaluate:\n", - " particle.cycle_age += particle.dt # update cycle_age\n", - "\n", - "\n", - "def KeepAtSurface(particle, fieldset, time):\n", - " # Prevent error when float reaches surface\n", - " if particle.state == StatusCode.ErrorThroughSurface:\n", - " particle.depth = fieldset.mindepth\n", - " particle.state = StatusCode.Success" - ] - }, - { - "cell_type": "markdown", - "id": "b72574d3", - "metadata": {}, - "source": [ - "Before we can run this code, we also need to define a new Particle class, that has extra Variables like `cycle_phase`, `cycle_age` etc needed by the `ArgoVerticalMovement()` Kernel. \n", - "*Note that if you get a compiler error here, you could try to swap the `JITParticle` in the `ArgoParticle` class definition for `ScipyParticle`.*" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cf19fadf", - "metadata": {}, - "outputs": [], - "source": [ - "variables = [\n", - " Variable('cycle_phase', dtype=np.int32, initial=0.0),\n", - " Variable('cycle_age', dtype=np.float32, initial=0.0),\n", - " Variable('drift_age', dtype=np.float32, initial=0.0),\n", - " Variable('temp', dtype=np.float32, initial=np.nan),\n", - " Variable('salt', dtype=np.float32, initial=np.nan),\n", - "]\n", - "ArgoParticle = JITParticle.add_variables(variables)" - ] - }, - { - "cell_type": "markdown", - "id": "ba34b258", - "metadata": {}, - "source": [ - "Now we can create a `ParticleSet`, which in this case consists of one `ArgoParticle`. We have to specify its initial position and time. Note that you could add any number of Argo floats here, all having different starting positions. We will simply use one float, however." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7f539807", - "metadata": {}, - "outputs": [], - "source": [ - "argoset = ParticleSet(\n", - " fieldset=fieldset, pclass=ArgoParticle, lon=[-37.09499], lat=[6.73472],\n", - " depth=fieldset.mindepth, time=np.datetime64('2019-07-25T11:14:00')\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "316e2277", - "metadata": {}, - "source": [ - "If we then combine the `ArgoVerticalMovement()` kernel with the built-in `AdvectionRK4()` (for the horizontal movement) and the `KeepAtSurface()` (for ending the ascent), we can compute the trajectory again. This may take a while. \n", - "*Note that `particle_ddepth` is a copy of `particle.depth` inside `ArgoVerticalMovement()`. On every time step, `particle.depth` is kept constant until all kernels have been executed. Only then are the depth changes in every kernel, `particle_ddepth - paricle.depth`, summed together to find the new depth. Therefore, the outcome does not depend on the ordering of the kernels.*" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "32ade18d", - "metadata": {}, - "outputs": [], - "source": [ - "argoset.execute(\n", - " [ArgoVerticalMovement, AdvectionRK4, KeepAtSurface], # list of kernels to be executed\n", - " runtime=timedelta(days=31),\n", - " dt=timedelta(minutes=5),\n", - " output_file=argoset.ParticleFile(name=\"argo_float\", outputdt=timedelta(minutes=5), chunks=(1,500)),\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "6a954472", - "metadata": {}, - "source": [ - "You can open the dataset and view the Argo trajectory with the code provided by Mike in his tutorial" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7ddb39e5", - "metadata": {}, - "outputs": [], - "source": [ - "ds_argo = xr.open_zarr('argo_float.zarr')\n", - "\n", - "x = ds_argo[\"lon\"][:].squeeze()\n", - "y = ds_argo[\"lat\"][:].squeeze()\n", - "z = ds_argo[\"z\"][:].squeeze()\n", - "\n", - "fig = plt.figure(figsize=(13,10))\n", - "ax = plt.axes(projection='3d')\n", - "ax.invert_zaxis()\n", - "p = ax.scatter(x,y,z, c=z, s=20, marker=\"o\", cmap='viridis_r', depthshade=False)\n", - "cb = plt.colorbar(p, shrink=0.5)\n", - "cb.ax.invert_yaxis()\n", - "cb.set_label('depth [m]')" - ] - }, - { - "cell_type": "markdown", - "id": "01e2b7ae-5b3f-4a16-8721-9c4ad3fc79a8", - "metadata": {}, - "source": [ - "Without changing the sink velocity, make the ascent twice as slow. Store your data in a different file. Make sure to define the `argoset` again, because by default the simulation will otherwise continue where the previous run ended. \n", - "Then, plot depth as a function of time for both the regular and slowly-ascending floats to check if your code works. To speed up the simulation you can set the `outputdt` to 30 minutes." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f6c0e5f3-e70f-4d7e-92ae-8ddf884d106b", - "metadata": {}, - "outputs": [], - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "id": "f0af03db-2d7b-4086-bd93-e6724b58aa8d", - "metadata": {}, - "source": [ - "Make plots of the vertical temperature and salinity profile, which were recorded during the ascents to the surface. You only have to show the regular argo float data." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "913e27fb-2f82-45c7-af1f-d33b82ba1d63", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "8caa88f6-730f-442e-871c-65b2e5c94b35", - "metadata": {}, - "source": [ - "Now present vertical profiles of temperature and salinity for a float that is not advected horizontally but only moves vertically in a similar fashion and compare to the results for the regular float. Let the horizontal position of this float equal that of the regular float when it first ascends and make sure the run duration and output time step are similar. Is the difference due to horizontal advection significant during the first ascend? And the second, third?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "57fe4989-e926-467d-8a40-aa09d5fea82b", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A02_Q1_withanswers.ipynb b/teaching_material/Assignment/Preparatory_exercises/A02_Q1_withanswers.ipynb deleted file mode 100644 index 8cf0b7b1..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A02_Q1_withanswers.ipynb +++ /dev/null @@ -1,626 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a30f51ea", - "metadata": {}, - "source": [ - "### Assignment 2.1: Argo floats in the Tropical Atlantic\n", - "\n", - "In this assignment, you will simulate the temperature and salinity profiles of an Argo float using the Parcels toolbox.\n", - "\n", - "First, make sure you have the right environment activated and import the following packages." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "cd00b0bc-2ca2-40ea-91ce-e0622a4edcc6", - "metadata": {}, - "outputs": [], - "source": [ - "from parcels import FieldSet, ParticleSet, JITParticle, Variable, AdvectionRK4, ScipyParticle, StatusCode\n", - "import numpy as np\n", - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "from datetime import timedelta\n", - "import cmocean" - ] - }, - { - "cell_type": "markdown", - "id": "e0a1719f", - "metadata": {}, - "source": [ - "For the Parcels simulation, you will need to download a NetCDF file with the hydrodynamic (velocities, temperature, salinity) data. We use data from the Copernicus Marine Environmental Monitoring Service (CMEMS) [Global Ocean 1/12° Physics Analysis and Forecast product](https://resources.marine.copernicus.eu/product-detail/GLOBAL_ANALYSIS_FORECAST_PHY_001_024/INFORMATION). For this assignment, we've compiled all the flow data you need into one file (~120MB), which you can find on Blackboard.\n", - "\n", - "Put that file into the directory that also holds this notebook and then execute the code below to create what's in Parcels called a `FieldSet` object" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "50bbbadf", - "metadata": {}, - "outputs": [], - "source": [ - "filename = 'global-analysis-forecast-phy-001-024_1641284158025.nc'\n", - "variables = {'U': 'uo', # dictionary with names of the variables in the netcdf file\n", - " 'V': 'vo',\n", - " 'S': 'so',\n", - " 'T': 'thetao'}\n", - "dimensions = {'lon': 'longitude', # dictionary with names of the dimensions in the netcdf file\n", - " 'lat': 'latitude',\n", - " 'depth': 'depth',\n", - " 'time': 'time'}\n", - "\n", - "fieldset = FieldSet.from_netcdf(filename, variables, dimensions)\n", - "fieldset.mindepth = fieldset.U.depth[0] # uppermost layer in the hydrodynamic data" - ] - }, - { - "cell_type": "markdown", - "id": "b9874515", - "metadata": {}, - "source": [ - "You can plot the two components of the flow field (at the surface) with the following code." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "6811eb8f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The dimensions of the data are:\n", - "lon: 181\n", - "lat: 61\n", - "depth: 41\n", - "time: 34 (2 loaded)\n" - ] - } - ], - "source": [ - "fieldset.computeTimeChunk() # first load the data in memory\n", - "\n", - "fig, ax = plt.subplots(1, 2, sharex=True, sharey=True)\n", - "p0 = ax[0].pcolormesh(fieldset.U.lon, fieldset.U.lat, fieldset.U.data[0,0,:,:], vmin=-1.5, vmax=1.5, cmap=cmocean.cm.balance)\n", - "p1 = ax[1].pcolormesh(fieldset.V.lon, fieldset.V.lat, fieldset.V.data[0,0,:,:], vmin=-1.5, vmax=1.5, cmap=cmocean.cm.balance)\n", - "ax[0].set_title('zonal velocity')\n", - "ax[1].set_title('meridional velocity')\n", - "ax[0].set_ylabel('latitude [°N]')\n", - "ax[0].set_xlabel('longitude [°E]')\n", - "ax[1].set_xlabel('longitude [°E]')\n", - "ax[1].yaxis.set_tick_params(left=False, right=True, labelleft=False, labelright=True)\n", - "ax[0].grid()\n", - "ax[1].grid()\n", - "cb = fig.colorbar(p1, ax=ax, orientation='horizontal')\n", - "cb.set_label('[m/s]')\n", - "gd = fieldset.U.grid\n", - "fig.suptitle(f\"velocity at depth {gd.depth[0]:.2f} m, {gd.timeslices[0][0].astype('datetime64[m]')}\")\n", - "plt.show()\n", - "\n", - "print(f\"The dimensions of the data are:\\nlon: {gd.xdim}\\nlat: {gd.ydim}\\ndepth: {gd.zdim}\\ntime: {len(gd.time_full)} ({gd.tdim} loaded)\")" - ] - }, - { - "cell_type": "markdown", - "id": "713f3bcb-dc11-411f-8bb4-499977e2863a", - "metadata": {}, - "source": [ - "Parcels uses the oceanic data in `fieldset` to represent the environment of a 'particle'. Particles are objects that by default hold information on there position and time. The behaviour of particles is determined by a kernel. A commonly used kernel is `AdvectionRK4`, which prescribes advection using a 4th order Runge-Kutta numerical scheme. The `fieldset` data is interpolated to the particle position and time, then the particle gets advected to determine velocities at the new position. This process is repeated three times in a clever way to minimize the numerical error." - ] - }, - { - "cell_type": "markdown", - "id": "11edb95b", - "metadata": {}, - "source": [ - "A few years ago, [Mike Hart-Davis](https://www.dgfi.tum.de/en/staff/hart-davis-michael/) wrote a `Kernel` for Parcels to easily simulate the behaviour of an Argo float. That code, which is also available in [this notebook tutorial](https://docs.oceanparcels.org/en/latest/examples/tutorial_Argofloats.html), is copied in the cell below. Go through it and make sure you understand what it does. For practical purposes, you may assume `particle.depth` and `particle_ddepth` both represent the particle depth.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "0c28d2c0", - "metadata": {}, - "outputs": [], - "source": [ - "# Define the new Kernel that mimics Argo vertical movement\n", - "def ArgoVerticalMovement(particle, fieldset, time):\n", - " driftdepth = 1000 # maximum depth in m\n", - " maxdepth = 2000 # maximum depth in m\n", - " vertical_speed = 0.10 # sink and rise speed in m/s\n", - " cycletime = 10 * 86400 # total time of cycle in seconds\n", - " drifttime = 9 * 86400 # time of deep drift in seconds\n", - "\n", - " if particle.cycle_phase == 0:\n", - " # Phase 0: Sinking with vertical_speed until depth is driftdepth\n", - " particle_ddepth += vertical_speed * particle.dt\n", - " if particle.depth >= driftdepth:\n", - " particle.cycle_phase = 1\n", - "\n", - " elif particle.cycle_phase == 1:\n", - " # Phase 1: Drifting at depth for drifttime seconds\n", - " particle.drift_age += particle.dt\n", - " if particle.drift_age >= drifttime:\n", - " particle.drift_age = 0 # reset drift_age for next cycle\n", - " particle.cycle_phase = 2\n", - "\n", - " elif particle.cycle_phase == 2:\n", - " # Phase 2: Sinking further to maxdepth\n", - " particle_ddepth += vertical_speed * particle.dt\n", - " if particle.depth >= maxdepth:\n", - " particle.cycle_phase = 3\n", - "\n", - " elif particle.cycle_phase == 3:\n", - " # Phase 3: Rising with vertical_speed until at surface\n", - " particle_ddepth -= vertical_speed * particle.dt\n", - " particle.cycle_age += particle.dt # solve issue of not updating cycle_age during ascent\n", - " if particle.depth <= fieldset.mindepth:\n", - " particle.depth = fieldset.mindepth\n", - " particle.temp = math.nan # reset temperature to NaN at end of sampling cycle\n", - " particle.salt = math.nan # idem\n", - " particle.cycle_phase = 4\n", - " else:\n", - " particle.temp = fieldset.T[time, particle.depth, particle.lat, particle.lon]\n", - " particle.salt = fieldset.S[time, particle.depth, particle.lat, particle.lon]\n", - "\n", - " elif particle.cycle_phase == 4:\n", - " # Phase 4: Transmitting at surface until cycletime is reached\n", - " if particle.cycle_age > cycletime:\n", - " particle.cycle_phase = 0\n", - " particle.cycle_age = 0\n", - "\n", - " if particle.state == StatusCode.Evaluate:\n", - " particle.cycle_age += particle.dt # update cycle_age\n", - "\n", - "\n", - "def KeepAtSurface(particle, fieldset, time):\n", - " # Prevent error when float reaches surface\n", - " if particle.state == StatusCode.ErrorThroughSurface:\n", - " particle.depth = fieldset.mindepth\n", - " particle.state = StatusCode.Success" - ] - }, - { - "cell_type": "markdown", - "id": "b72574d3", - "metadata": {}, - "source": [ - "Before we can run this code, we also need to define a new Particle class, that has extra Variables like `cycle_phase`, `cycle_age` etc needed by the `ArgoVerticalMovement()` Kernel. \n", - "*Note that if you get a compiler error here, you could try to swap the `JITParticle` in the `ArgoParticle` class definition for `ScipyParticle`.*" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "cf19fadf", - "metadata": {}, - "outputs": [], - "source": [ - "variables = [\n", - " Variable('cycle_phase', dtype=np.int32, initial=0.0),\n", - " Variable('cycle_age', dtype=np.float32, initial=0.0),\n", - " Variable('drift_age', dtype=np.float32, initial=0.0),\n", - " Variable('temp', dtype=np.float32, initial=np.nan),\n", - " Variable('salt', dtype=np.float32, initial=np.nan),\n", - "]\n", - "ArgoParticle = JITParticle.add_variables(variables)" - ] - }, - { - "cell_type": "markdown", - "id": "ba34b258", - "metadata": {}, - "source": [ - "Now we can create a `ParticleSet`, which in this case consists of one `ArgoParticle`. We have to specify its initial position and time. Note that you could add any number of Argo floats here, all having different starting positions. We will simply use one float, however." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "7f539807", - "metadata": {}, - "outputs": [], - "source": [ - "argoset = ParticleSet(\n", - " fieldset=fieldset, pclass=ArgoParticle, lon=[-37.09499], lat=[6.73472],\n", - " depth=fieldset.mindepth, time=np.datetime64('2019-07-25T11:14:00')\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "316e2277", - "metadata": {}, - "source": [ - "If we then combine the `ArgoVerticalMovement()` kernel with the built-in `AdvectionRK4()` (for the horizontal movement) and the `KeepAtSurface()` (for ending the ascent), we can compute the trajectory again. This may take a while. \n", - "*Note that `particle_ddepth` is a copy of `particle.depth` inside `ArgoVerticalMovement()`. On every time step, `particle.depth` is kept constant until all kernels have been executed. Only then are the depth changes in every kernel, `particle_ddepth - paricle.depth`, summed together to find the new depth. Therefore, the outcome does not depend on the ordering of the kernels.*" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "32ade18d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INFO: Output files are stored in argo_float.zarr.\n", - "100%|██████████████████████████████████████████████████████████████████| 2678400.0/2678400.0 [03:13<00:00, 13823.02it/s]\n" - ] - } - ], - "source": [ - "argoset.execute(\n", - " [ArgoVerticalMovement, AdvectionRK4, KeepAtSurface], # list of kernels to be executed\n", - " runtime=timedelta(days=31),\n", - " dt=timedelta(minutes=5),\n", - " output_file=argoset.ParticleFile(name=\"argo_float\", outputdt=timedelta(minutes=5), chunks=(1,500)),\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "6a954472", - "metadata": {}, - "source": [ - "You can open the dataset and view the Argo trajectory with the code provided by Mike in his tutorial" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "7ddb39e5", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ds_argo = xr.open_zarr('argo_float.zarr')\n", - "\n", - "x = ds_argo[\"lon\"][:].squeeze()\n", - "y = ds_argo[\"lat\"][:].squeeze()\n", - "z = ds_argo[\"z\"][:].squeeze()\n", - "\n", - "fig = plt.figure(figsize=(13,10))\n", - "ax = plt.axes(projection='3d')\n", - "ax.invert_zaxis()\n", - "p = ax.scatter(x,y,z, c=z, s=20, marker=\"o\", cmap='viridis_r', depthshade=False)\n", - "cb = plt.colorbar(p, shrink=0.5)\n", - "cb.ax.invert_yaxis()\n", - "cb.set_label('depth [m]')" - ] - }, - { - "cell_type": "markdown", - "id": "01e2b7ae-5b3f-4a16-8721-9c4ad3fc79a8", - "metadata": {}, - "source": [ - "Without changing the sink velocity, make the ascent twice as slow. Store your data in a different file. Make sure to define the `argoset` again, because by default the simulation will otherwise continue where the previous run ended. \n", - "Then, plot depth as a function of time for both the regular and slowly-ascending floats to check if your code works. To speed up the simulation you can set the `outputdt` to 30 minutes." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "f6c0e5f3-e70f-4d7e-92ae-8ddf884d106b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INFO: Output files are stored in argo_float2.zarr.\n", - "100%|██████████████████████████████████████████████████████████████████| 2678400.0/2678400.0 [00:38<00:00, 68785.46it/s]\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Answer\n", - "\n", - "def ArgoVerticalMovement2(particle, fieldset, time): # -- change kernel name\n", - " driftdepth = 1000 # maximum depth in m\n", - " maxdepth = 2000 # maximum depth in m\n", - " vertical_speed = 0.10 # sink and rise speed in m/s\n", - " cycletime = 10 * 86400 # total time of cycle in seconds\n", - " drifttime = 9 * 86400 # time of deep drift in seconds\n", - "\n", - " if particle.cycle_phase == 0:\n", - " # Phase 0: Sinking with vertical_speed until depth is driftdepth\n", - " particle_ddepth += vertical_speed * particle.dt\n", - " if particle.depth >= driftdepth:\n", - " particle.cycle_phase = 1\n", - "\n", - " elif particle.cycle_phase == 1:\n", - " # Phase 1: Drifting at depth for drifttime seconds\n", - " particle.drift_age += particle.dt\n", - " if particle.drift_age >= drifttime:\n", - " particle.drift_age = 0 # reset drift_age for next cycle\n", - " particle.cycle_phase = 2\n", - "\n", - " elif particle.cycle_phase == 2:\n", - " # Phase 2: Sinking further to maxdepth\n", - " particle_ddepth += vertical_speed * particle.dt\n", - " if particle.depth >= maxdepth:\n", - " particle.cycle_phase = 3\n", - "\n", - " elif particle.cycle_phase == 3:\n", - " # Phase 3: Rising with vertical_speed until at surface\n", - " particle_ddepth -= vertical_speed * particle.dt/ 2.0 # ------------- make twice as slow\n", - " particle.cycle_age += particle.dt \n", - " particle.temp = fieldset.T[time, particle.depth, particle.lat, particle.lon]\n", - " particle.salt = fieldset.S[time, particle.depth, particle.lat, particle.lon]\n", - " if particle.depth <= fieldset.mindepth:\n", - " particle.depth = fieldset.mindepth\n", - " particle.temp = math.nan # reset temperature to NaN at end of sampling cycle\n", - " particle.salt = math.nan # idem\n", - " particle.cycle_phase = 4\n", - " \n", - " elif particle.cycle_phase == 4:\n", - " # Phase 4: Transmitting at surface until cycletime is reached\n", - " if particle.cycle_age > cycletime:\n", - " particle.cycle_phase = 0\n", - " particle.cycle_age = 0\n", - "\n", - " if particle.state == StatusCode.Evaluate:\n", - " particle.cycle_age += particle.dt # update cycle_age\n", - "\n", - "\n", - "def KeepAtSurface(particle, fieldset, time):\n", - " if particle.state == StatusCode.ErrorThroughSurface:\n", - " particle.depth = fieldset.mindepth\n", - " particle.state = StatusCode.Success\n", - "\n", - "\n", - "argoset = ParticleSet( # ------------ redefine argoset, otherwise simulation continues from previous run\n", - " fieldset=fieldset, pclass=ArgoParticle, lon=[-37.09499], lat=[6.73472],\n", - " depth=fieldset.mindepth, time=np.datetime64('2019-07-25T11:14:00')\n", - ")\n", - "argoset.execute(\n", - " [ArgoVerticalMovement2, AdvectionRK4, KeepAtSurface], # ----- changed kernel\n", - " runtime=timedelta(days=31),\n", - " dt=timedelta(minutes=5),\n", - " output_file=argoset.ParticleFile(name=\"argo_float2\", outputdt=timedelta(minutes=30), chunks=(1,500)), # -- changed filename\n", - ")\n", - "\n", - "\n", - "ds_argo2 = xr.open_zarr('argo_float2.zarr')\n", - "fig = plt.figure()\n", - "plt.plot(ds_argo.time[0,:], -ds_argo.z[0,:], 'k', label='original')\n", - "plt.plot(ds_argo2.time[0,:], -ds_argo2.z[0,:], 'b:',label='edited')\n", - "plt.legend()\n", - "plt.grid()\n", - "plt.ylabel('depth [m]')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "f0af03db-2d7b-4086-bd93-e6724b58aa8d", - "metadata": {}, - "source": [ - "Make plots of the vertical temperature and salinity profile, which were recorded during the ascents to the surface. You only have to show the regular argo float data." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "913e27fb-2f82-45c7-af1f-d33b82ba1d63", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "# depth vs time not needed, but here for extra info\n", - "\n", - "fig = plt.figure(figsize=(12,6))\n", - "fig.suptitle(f'Temperature, salinity and time during phase 3')\n", - "\n", - "days = (ds_argo.time[0,:]-ds_argo.time[0,0]).data.astype('timedelta64[m]').astype('int')/1440\n", - "tids3 = ~ds_argo.temp[0,:].isnull().compute() # time indices during cycle phase 3 (ascent)\n", - "\n", - "ax1 = fig.add_subplot(131)\n", - "ax1.plot(ds_argo.temp[0,:],-ds_argo.z[0,:], 'k')\n", - "ax1.grid()\n", - "ax1.set_xlabel('temperature [°C]')\n", - "ax1.set_ylabel('depth [m]')\n", - "\n", - "ax2 = fig.add_subplot(132, sharey=ax1)\n", - "ax2.plot(ds_argo.salt[0,:], -ds_argo.z[0,:], 'k')\n", - "ax2.grid()\n", - "ax2.yaxis.set_tick_params(left=False, labelleft=False)\n", - "ax2.set_xlabel('salinity [g/kg]')\n", - "\n", - "ax3 = fig.add_subplot(133, sharey=ax1)\n", - "ax3.plot(days[tids3], -ds_argo.z[0,tids3], 'k-o', ms=4)\n", - "ax3.yaxis.tick_right()\n", - "ax3.yaxis.label_position = 'right'\n", - "ax3.grid()\n", - "ax3.set_xlabel('days from launch')\n", - "ax3.set_ylabel('depth [m]', rotation=270)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "8caa88f6-730f-442e-871c-65b2e5c94b35", - "metadata": {}, - "source": [ - "Now present vertical profiles of temperature and salinity for a float that is not advected horizontally but only moves vertically in a similar fashion and compare to the results for the regular float. Let the horizontal position of this float equal that of the regular float when it first ascends and make sure the run duration and output time step are similar. Is the difference due to horizontal advection significant during the first ascend? And the second, third?" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "57fe4989-e926-467d-8a40-aa09d5fea82b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "INFO: Output files are stored in argo_float_noad.zarr.\n", - "100%|██████████████████████████████████████████████████████████████████| 2678400.0/2678400.0 [03:05<00:00, 14466.90it/s]\n" - ] - } - ], - "source": [ - "# ANSWER\n", - "\n", - "# set initial position, should be anywhere close to the trajectory during ascent (phase 3)\n", - "lon0 = ds_argo.lon[0,tids3][0].compute().item() # initial longitude phase 3\n", - "lat0 = ds_argo.lat[0,tids3][0].compute().item() # initial latitude phase 3\n", - "\n", - "argoset = ParticleSet( # ------------ set initial position\n", - " fieldset=fieldset, pclass=ArgoParticle, lon=lon0, lat=lat0,\n", - " depth=fieldset.mindepth, time=np.datetime64('2019-07-25T11:14:00')\n", - ")\n", - "argoset.execute(\n", - " [ArgoVerticalMovement, KeepAtSurface], # ----- removed advection kernel\n", - " runtime=timedelta(days=31),\n", - " dt=timedelta(minutes=5),\n", - " output_file=argoset.ParticleFile(name=\"argo_float_noad\", outputdt=timedelta(minutes=5), chunks=(1,500)), # -- changed filename\n", - ")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "d62582d6-77ba-4cc0-b36f-eaab9d3108d2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "\n", - "ds_argo_noad = xr.open_zarr('./argo_float_noad.zarr')\n", - "\n", - "fig = plt.figure(figsize=(8,8))\n", - "fig.suptitle(f'Temperature, salinity effect horizontal advection')\n", - "\n", - "days = (ds_argo.time[0,:]-ds_argo.time[0,0]).data.astype('timedelta64[m]').astype('int')/1440\n", - "tids3 = ~ds_argo.temp[0,:].isnull() # time indices during cycle phase 3 (ascent)\n", - "\n", - "ax1 = fig.add_subplot(221)\n", - "ax1.plot(ds_argo.temp[0,:],-ds_argo.z[0,:], 'k', lw=2, label='argo')\n", - "ax1.plot(ds_argo_noad.temp[0,:],-ds_argo_noad.z[0,:], 'r:', lw=2, label='argo no adv.')\n", - "ax1.grid()\n", - "ax1.set_xlabel('temperature [°C]')\n", - "ax1.set_ylabel('depth [m]')\n", - "ax1.legend(loc='lower right')\n", - "ax1.set_title('profiles')\n", - "\n", - "ax2 = fig.add_subplot(223, sharey=ax1)\n", - "ax2.plot(ds_argo.salt[0,:], -ds_argo.z[0,:], 'k', lw=2, label='argo')\n", - "ax2.plot(ds_argo_noad.salt[0,:], -ds_argo_noad.z[0,:], 'r:', lw=2, label='argo no adv.')\n", - "ax2.grid()\n", - "ax2.set_xlabel('salinity [g/kg]')\n", - "\n", - "ax3 = fig.add_subplot(222, sharey=ax1)\n", - "ax3.plot(ds_argo_noad.temp[0,:] - ds_argo.temp[0,:],-ds_argo.z[0,:], 'c', lw=2, label=r'adv. $-$ no adv.')\n", - "ax3.yaxis.set_tick_params(left=False, labelleft=False, right=True, labelright=True)\n", - "ax3.set_xlabel('temperature anomaly [°C]')\n", - "ax3.set_ylabel('depth [m]', rotation=270)\n", - "ax3.yaxis.label_position = 'right'\n", - "ax3.grid()\n", - "ax3.legend(loc='lower right')\n", - "ax3.set_title('difference')\n", - "\n", - "ax4 = fig.add_subplot(224, sharey=ax1)\n", - "ax4.plot(ds_argo_noad.salt[0,:] - ds_argo.salt[0,:], -ds_argo_noad.z[0,:], 'c', lw=2, label=r'adv. $-$ no adv.')\n", - "ax4.yaxis.set_tick_params(left=False, labelleft=False, right=True, labelright=True)\n", - "ax4.grid()\n", - "ax4.set_xlabel('salinity anomaly [g/kg]')\n", - "ax4.set_ylabel('depth [m]', rotation=270)\n", - "ax4.yaxis.label_position = 'right'" - ] - }, - { - "cell_type": "markdown", - "id": "4fb06fb4-51c5-4065-85b8-35ee09c6fc3d", - "metadata": {}, - "source": [ - "Answer:\n", - "In this case, the relative error for both temperature (in $K$) and salinity are $\\mathcal{O}(10^{-5})$ during the first ascent, so there is no significant difference due to horizontal advection. In the second and third ascent, we do see large differences of a few degrees/100s of mgs/kg, especially just below the surface." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A03_Q1.ipynb b/teaching_material/Assignment/Preparatory_exercises/A03_Q1.ipynb deleted file mode 100644 index c4547b7b..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A03_Q1.ipynb +++ /dev/null @@ -1,344 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment 3.1: Computing densities\n", - "\n", - "In this assignment, you will compute densities from local temperatures and salinities. \n", - "\n", - "For this, you will need to install the `gsw` package. Assuming you have installed python via anaconda, you can open the anaconda prompt or terminal and type `conda install -n dyoc -c conda-forge gsw`. Then, restart jupyter and import the following packages." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import glob\n", - "import gsw\n", - "import warnings\n", - "import xarray as xr\n", - "import cftime\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import cartopy.crs as ccrs\n", - "import cartopy.feature as cfeature\n", - "import cmocean" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The data you will be working with was collected on a [cruise with the RRS Discovery](https://www.bodc.ac.uk/data/documents/cruise/8198/) in the Strait of Gibraltar from the 4th to 21st of April, 1998. The objectives of these cruise were to a) carry out mooring operations, b) study non-linear processes due to strong currents and c) measure biogeochemichal fluxes associated with the upper layer inflow of Atlantic water and the lower layer outflow of Mediterranean water through the Strait. \n", - "\n", - "Along the cruise trajectory, [27 CTD measurements](https://data-search.nerc.ac.uk/geonetwork/srv/api/records/e7b1b5dadc5a52d18078b9c26f9e08a8) have been taken, sampling temperature, salinity and oxygen levels. The post-processed data is available to you in the folder _RN-9598_1707497532516_, as well as additional reports. You can load the data and plot the trajectory by running the following two cells." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "datadir = './' # change to your directory\n", - "\n", - "# open datasets and sort by time of ctd cast\n", - "def decode_time(ds): # needed due to non CF-compliant units\n", - " with warnings.catch_warnings(action='ignore', category=cftime.CFWarning):\n", - " ds['TIME'] = cftime.num2date(ds.TIME, ds.TIME.units)\n", - " return ds\n", - "\n", - "files = glob.glob(f\"{datadir}RN-9598_1707497532516/b051*.nc\")\n", - "data = [decode_time(xr.open_dataset(f, decode_times=False)) for f in files]\n", - "data = [data[i] for i in np.argsort([ds.TIME.item() for ds in data])]\n", - "print(f\"Loaded {len(data)} profiles\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "bathy = xr.open_dataset(f\"{datadir}bathymetry.nc\")\n", - "fig = plt.figure(figsize=(10,8))\n", - "ax = plt.axes(projection=ccrs.PlateCarree())\n", - "tp = ax.pcolormesh(bathy.longitude, bathy.latitude, bathy.elevation, cmap='ocean', vmin=-1100,vmax=100, transform=ccrs.PlateCarree())\n", - "ax.add_feature(cfeature.COASTLINE.with_scale('10m'))\n", - "ax.add_feature(cfeature.LAND.with_scale('10m'))\n", - "ax.gridlines(draw_labels=['left','bottom'], zorder=0)\n", - "ax.plot([ds.LONGITUDE for ds in data], [ds.LATITUDE for ds in data], '-o',\n", - " transform=ccrs.PlateCarree(), c='lime')\n", - "ax.scatter(data[0].LONGITUDE, data[0].LATITUDE,c='lime', marker='*', s=150, zorder=2,\n", - " transform=ccrs.PlateCarree(), edgecolors='k', linewidths=.5, label='start cruise D232')\n", - "ax.set_title('CTD cast locations')\n", - "ax.legend(loc='upper center')\n", - "ax.set_extent([-6.05,-5.05,35.75,36.25])\n", - "cb = fig.colorbar(tp, ax=ax, shrink=.5)\n", - "cb.ax.set_ylim([-1100,0])\n", - "cb.set_label('sea depth [m]')\n", - "_=ax.text(-5.31,35.76,bathy.infoUrl, c='w', fontsize=8)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In the next assignment, you will analyze the output of CTD cast 517846, taken in the Eastern Mediterranean. First inspect the available data by running the following cell." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "data[6]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**a)** Write a python programme to plot the density profile of cast 517846 and check whether density increases with depth if a linear equation of state for temperature and salinity is taken. Use:\n", - "$$\n", - "\\rho = \\rho_0 \\left(1-\\alpha_T\\left(T-T_0\\right)+\\beta_S\\left(S-S_0\\right)\\right)\n", - "$$\n", - "with a reference density $\\rho_0 = 1027$ kg m $^{−3}$, thermic expansion coefficient $\\alpha_T = 1.0\\cdot10^{−4}$ K $^{−1}$, and haline expansion coefficient $\\beta_S = 7.0\\cdot10^{−4}$. $ T_0 $ and $ S_0 $ are the temperature and salinity closest to the surface respectively." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**b)** Is the water column stable? Explain." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "(Answer) Despite the density decreasing with depth below 400m, the water column is not unstable. The formula used to calculate density in part (a) does not include the effect of compressibility of water. In the upper levels of the ocean the effect of pressure is small and the formula is valid, but in the deeper layers it is no longer negligible." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**c)** As discussed in the lecture, the TEOS10 equations provide more accurate Equations of State. Use the `gsw.conversions.z_from_p()` function to convert the measurement pressures to depths (using the `ds.LATITUDE` value for latitude) and the `gsw.conversions.CT_from_t()` function to convert the in-situ temperature to Conservative Temperature. Then, use the `gsw.density.rho()` function to compute the in-situ density. Use the `help()` function for instructions how to use these functions." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**d)** How do the Conservative Temperatures differ from the in-situ temperatures? And how does the density computed form the `gsw` package differ from the density in the equation at a)?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The ship made two long sections on the Eastern and Western side of the Strait to measure the biogeochemical fluxes. The cell below shows the track on the Western side." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# select western passage and sort by latitude\n", - "data_west = [ds for ds in data if ds.LONGITUDE<-5.7]\n", - "time = [(ds.TIME.item() - data[0].TIME.item()).total_seconds()/86400 for ds in data_west]\n", - "\n", - "# plot\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(121, projection=ccrs.PlateCarree())\n", - "ax.plot([ds.LONGITUDE for ds in data_west], [ds.LATITUDE for ds in data_west], 'k-o',\n", - " lw=1, ms=4, transform=ccrs.PlateCarree())\n", - "ax.coastlines()\n", - "ax.gridlines(draw_labels=['left','bottom'], zorder=0)\n", - "ax.set_title('track')\n", - "ax.set_ylabel('latitude')\n", - "ax.set_ylim([35.78,36.099])\n", - "\n", - "ax2 = fig.add_subplot(122, sharey=ax)\n", - "ax2.plot(time, [ds.LATITUDE.item() for ds in data_west], 'k-o', lw=1, ms=4)\n", - "ax2.yaxis.label_position = 'right'\n", - "ax2.yaxis.set_tick_params(left=False, labelleft=False, right=True, labelright=True)\n", - "ax2.yaxis.set_ticks(ax.get_yticks())\n", - "ax2.set_yticklabels([t.get_text() for t in ax.get_yticklabels()])\n", - "ax2.grid()\n", - "ax2.set_title('latitude')\n", - "ax2.set_xlabel('days since start cruise')\n", - "ax2.set_ylim([35.78,36.099])\n", - "\n", - "fig.suptitle(\"Western section\")\n", - "fig.tight_layout()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Apparently the ship did not take the shortest route across the strait. According to the cruise report, the section was split in two parts to give the chemists more time to analyze sample of water in between. However, when they did the second part, three out of seven locations were occupied by fishing boats that they had to steer away from. One data series could still be retrieved the same day, the other two locations were still occupied forcing the crew to do other things and wait. Though there is no need to read the lengthy cruise report yourself, the document is found [here](https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/d232.pdf).\n", - "\n", - "Luckily, you do not have to wait for your data today. The following function reads a list of available CTD profiles and combines them into a single array per variable (setting values outside the measured depth interval to NaN). Make sure you understand what it does and plot a 'cross section' (data is projected along the latitude dimension) of temperature and salinity across the Western part of the Strait. \n", - "_Hint: use `plt.pcolormesh()`, which has the option to use linearly interpolated shading._" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def crosssection(data, xdim='LATITUDE'):\n", - " \"\"\"convert data for 'cross section' plot (actually projection along x-axis)\n", - "\n", - " data : list of DataArray\n", - " list of CTD cast datasets\n", - " xdim : str\n", - " horizontal coordinate in output\n", - "\n", - " x : 1D horizontal coordinate\n", - " y : 1D vertical coordate (pressure)\n", - " temp : output temperature (y,x)\n", - " salt : output salinity (y,x)\n", - " \"\"\"\n", - " data = [ds.squeeze() for ds in data]\n", - " data = [data[i] for i in np.argsort([ds[xdim] for ds in data])] # sort by xdim\n", - " x = np.array([ds[xdim].item() for ds in data])\n", - " PMAX = np.max([ds.PRES.max() for ds in data]) # max pressure measured\n", - " y = np.arange(1,PMAX+1,2)\n", - " # below: one-line function taking in dataset and returning variable interpolated to pressures y\n", - " vinterp = lambda ds, var: np.interp(y, ds.PRES, ds[var], left=np.nan, right=np.nan)\n", - " temp = np.array([vinterp(ds, 'TEMPST01') for ds in data]).T\n", - " salt = np.array([vinterp(ds, 'PSALPR01') for ds in data]).T\n", - " return x,y,temp,salt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now repeat for the Eastern section (longitude > -5.33). Do you see a pattern corresponding to the exchange of water between the Atlantic Ocean and Mediterranean Sea?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The following cell makes a T,S diagram for the linearized equation of state. Add a scatter plot of the density computed from the CTD measurements in the Eastern section and compare your results." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "lat,p,temp,salt = crosssection(data_east)\n", - "\n", - "# calculating linearized density RHO\n", - "f = 0.005 # add margin around measurements\n", - "T = np.linspace(np.nanmin(temp)*(1-f), np.nanmax(temp)*(1+f), len(p))\n", - "S = np.linspace(np.nanmin(salt)*(1-f), np.nanmax(salt)*(1+f), len(p))\n", - "RHO = rho0 * (1- alpha * (T-T[0])[:,None] + beta * (S-S[0])[None,:])\n", - "\n", - "# plotting\n", - "fig, ax = plt.subplots(1, 1, figsize=(10, 5))\n", - "CS = ax.contour(S, T, RHO, colors='k', levels=np.arange(1025,1030,0.5))\n", - "ax.clabel(CS, inline=1, fontsize=10, fmt='%.1f')\n", - "ax.set_xlabel('salinity [psu]')\n", - "ax.set_ylabel('temperature [°C]')\n", - "ax.grid()\n", - "ax.set_title('Eastern section')\n", - "\n", - "# add your scatter plot here\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Answer: the colors confirm (again) that the linearized equations are a good approximation near the surface only." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Repeat the above plot for the Western section and compare both sections. Explain what you see." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A03_Q1_withanswers.ipynb b/teaching_material/Assignment/Preparatory_exercises/A03_Q1_withanswers.ipynb deleted file mode 100644 index 7313132d..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A03_Q1_withanswers.ipynb +++ /dev/null @@ -1,1140 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment 3.1: Computing densities\n", - "\n", - "In this assignment, you will compute densities from local temperatures and salinities. \n", - "\n", - "For this, you will need to install the `gsw` package. Assuming you have installed python via anaconda, you can open the anaconda prompt or terminal and type `conda install -n dyoc -c conda-forge gsw`. Then, restart jupyter and import the following packages." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import glob\n", - "import gsw\n", - "import warnings\n", - "import xarray as xr\n", - "import cftime\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import cartopy.crs as ccrs\n", - "import cartopy.feature as cfeature\n", - "import cmocean" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The data you will be working with was collected on a [cruise with the RRS Discovery](https://www.bodc.ac.uk/data/documents/cruise/8198/) in the Strait of Gibraltar from the 4th to 21st of April, 1998. The objectives of these cruise were to a) carry out mooring operations, b) study non-linear processes due to strong currents and c) measure biogeochemichal fluxes associated with the upper layer inflow of Atlantic water and the lower layer outflow of Mediterranean water through the Strait. \n", - "\n", - "Along the cruise trajectory, [27 CTD measurements](https://data-search.nerc.ac.uk/geonetwork/srv/api/records/e7b1b5dadc5a52d18078b9c26f9e08a8) have been taken, sampling temperature, salinity and oxygen levels. The post-processed data is available to you in the folder _RN-9598_1707497532516_, as well as additional reports. You can load the data and plot the trajectory by running the following two cells." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loaded 27 profiles\n" - ] - } - ], - "source": [ - "datadir = './' # change to your directory\n", - "\n", - "# open datasets and sort by time of ctd cast\n", - "def decode_time(ds): # needed due to non CF-compliant units\n", - " with warnings.catch_warnings(action='ignore', category=cftime.CFWarning):\n", - " ds['TIME'] = cftime.num2date(ds.TIME, ds.TIME.units)\n", - " return ds\n", - "\n", - "files = glob.glob(f\"{datadir}RN-9598_1707497532516/b051*.nc\")\n", - "data = [decode_time(xr.open_dataset(f, decode_times=False)) for f in files]\n", - "data = [data[i] for i in np.argsort([ds.TIME.item() for ds in data])]\n", - "print(f\"Loaded {len(data)} profiles\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "bathy = xr.open_dataset(f\"{datadir}bathymetry.nc\")\n", - "fig = plt.figure(figsize=(10,8))\n", - "ax = plt.axes(projection=ccrs.PlateCarree())\n", - "tp = ax.pcolormesh(bathy.longitude, bathy.latitude, bathy.elevation, cmap='ocean', vmin=-1100,vmax=100, transform=ccrs.PlateCarree())\n", - "ax.add_feature(cfeature.COASTLINE.with_scale('10m'))\n", - "ax.add_feature(cfeature.LAND.with_scale('10m'))\n", - "ax.gridlines(draw_labels=['left','bottom'], zorder=0)\n", - "ax.plot([ds.LONGITUDE for ds in data], [ds.LATITUDE for ds in data], '-o',\n", - " transform=ccrs.PlateCarree(), c='lime')\n", - "ax.scatter(data[0].LONGITUDE, data[0].LATITUDE,c='lime', marker='*', s=150, zorder=2,\n", - " transform=ccrs.PlateCarree(), edgecolors='k', linewidths=.5, label='start cruise D232')\n", - "ax.set_title('CTD cast locations')\n", - "ax.legend(loc='upper center')\n", - "ax.set_extent([-6.05,-5.05,35.75,36.25])\n", - "cb = fig.colorbar(tp, ax=ax, shrink=.5)\n", - "cb.ax.set_ylim([-1100,0])\n", - "cb.set_label('sea depth [m]')\n", - "_=ax.text(-5.31,35.76,bathy.infoUrl, c='w', fontsize=8)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In the next assignment, you will analyze the output of CTD cast 517846, taken in the Eastern Mediterranean. First inspect the available data by running the following cell." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
<xarray.Dataset>\n",
-       "Dimensions:                 (INSTANCE: 1, REFMAX: 3, MAXZ: 395, TIME: 1)\n",
-       "Coordinates:\n",
-       "    LATITUDE                (INSTANCE) float64 36.11\n",
-       "    LONGITUDE               (INSTANCE) float64 -5.188\n",
-       "    PRES                    (INSTANCE, MAXZ) float32 ...\n",
-       "  * TIME                    (TIME) object 1998-04-14 10:25:00.000018\n",
-       "Dimensions without coordinates: INSTANCE, REFMAX, MAXZ\n",
-       "Data variables: (12/16)\n",
-       "    SDN_CRUISE              (INSTANCE) |S80 ...\n",
-       "    crs                     int32 ...\n",
-       "    SDN_EDMO_CODE           (INSTANCE) int32 ...\n",
-       "    SDN_STATION             (INSTANCE) |S80 ...\n",
-       "    SDN_LOCAL_CDI_ID        (INSTANCE) |S80 ...\n",
-       "    SDN_XLINK               (INSTANCE, REFMAX) |S138 ...\n",
-       "    ...                      ...\n",
-       "    DOXYPR01_SEADATANET_QC  (INSTANCE, MAXZ) float32 ...\n",
-       "    DOXYPR01                (INSTANCE, MAXZ) float32 ...\n",
-       "    PSALPR01_SEADATANET_QC  (INSTANCE, MAXZ) float32 ...\n",
-       "    PSALPR01                (INSTANCE, MAXZ) float32 ...\n",
-       "    TEMPST01_SEADATANET_QC  (INSTANCE, MAXZ) float32 ...\n",
-       "    TEMPST01                (INSTANCE, MAXZ) float32 ...\n",
-       "Attributes:\n",
-       "    date_update:  2023-03-11T06:57:14+0000\n",
-       "    comment:      \n",
-       "    Conventions:  SeaDataNet_1.0 CF-1.6\n",
-       "    featureType:  profile\n",
-       "    title:        SeaDataNet NETCDF PROFILE Climate Forecast 1.6 - GENERATED ...
" - ], - "text/plain": [ - "\n", - "Dimensions: (INSTANCE: 1, REFMAX: 3, MAXZ: 395, TIME: 1)\n", - "Coordinates:\n", - " LATITUDE (INSTANCE) float64 36.11\n", - " LONGITUDE (INSTANCE) float64 -5.188\n", - " PRES (INSTANCE, MAXZ) float32 ...\n", - " * TIME (TIME) object 1998-04-14 10:25:00.000018\n", - "Dimensions without coordinates: INSTANCE, REFMAX, MAXZ\n", - "Data variables: (12/16)\n", - " SDN_CRUISE (INSTANCE) |S80 ...\n", - " crs int32 ...\n", - " SDN_EDMO_CODE (INSTANCE) int32 ...\n", - " SDN_STATION (INSTANCE) |S80 ...\n", - " SDN_LOCAL_CDI_ID (INSTANCE) |S80 ...\n", - " SDN_XLINK (INSTANCE, REFMAX) |S138 ...\n", - " ... ...\n", - " DOXYPR01_SEADATANET_QC (INSTANCE, MAXZ) float32 ...\n", - " DOXYPR01 (INSTANCE, MAXZ) float32 ...\n", - " PSALPR01_SEADATANET_QC (INSTANCE, MAXZ) float32 ...\n", - " PSALPR01 (INSTANCE, MAXZ) float32 ...\n", - " TEMPST01_SEADATANET_QC (INSTANCE, MAXZ) float32 ...\n", - " TEMPST01 (INSTANCE, MAXZ) float32 ...\n", - "Attributes:\n", - " date_update: 2023-03-11T06:57:14+0000\n", - " comment: \n", - " Conventions: SeaDataNet_1.0 CF-1.6\n", - " featureType: profile\n", - " title: SeaDataNet NETCDF PROFILE Climate Forecast 1.6 - GENERATED ..." - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data[6]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**a)** Write a python programme to plot the density profile of cast 517846 and check whether density increases with depth if a linear equation of state for temperature and salinity is taken. Use:\n", - "$$\n", - "\\rho = \\rho_0 \\left(1-\\alpha_T\\left(T-T_0\\right)+\\beta_S\\left(S-S_0\\right)\\right)\n", - "$$\n", - "with a reference density $\\rho_0 = 1027$ kg m $^{−3}$, thermic expansion coefficient $\\alpha_T = 1.0\\cdot10^{−4}$ K $^{−1}$, and haline expansion coefficient $\\beta_S = 7.0\\cdot10^{−4}$. $ T_0 $ and $ S_0 $ are the temperature and salinity closest to the surface respectively." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "rho0 = 1027; alpha=1e-4; beta=7e-4\n", - "ds = data[6].squeeze()\n", - "rho = rho0 * (1- alpha * (ds.TEMPST01-ds.TEMPST01[0]) + beta * (ds.PSALPR01-ds.PSALPR01[0]))\n", - "imax = rho.argmax()\n", - "plt.figure()\n", - "ax = plt.axes()\n", - "ax.plot(rho, ds.PRES, lw=2, c='k')\n", - "ax.invert_yaxis()\n", - "ax.grid()\n", - "ax.axhline(ds.PRES[imax], c='g', ls='--', lw=1)\n", - "ax.axvline(rho[imax],c='g', ls='--', lw=1, label=r'$(\\rho_{max}, z(\\rho_{max}))$')\n", - "ax.legend()\n", - "ax.set_ylabel(f'depth [m]') # assuming 1 dbar = 1 m\n", - "ax.set_xlabel('density [kg/m3]')\n", - "ax.set_title(f\"lat: {ds.LATITUDE.data:} lon: {ds.LONGITUDE.data}\")\n", - "fig.tight_layout()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**b)** Is the water column stable? Explain." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "(Answer) Despite the density decreasing with depth below 400m, the water column is not unstable. The formula used to calculate density in part (a) does not include the effect of compressibility of water. In the upper levels of the ocean the effect of pressure is small and the formula is valid, but in the deeper layers it is no longer negligible." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**c)** As discussed in the lecture, the TEOS10 equations provide more accurate Equations of State. Use the `gsw.conversions.z_from_p()` function to convert the measurement pressures to depths (using the `ds.LATITUDE` value for latitude) and the `gsw.conversions.CT_from_t()` function to convert the in-situ temperature to Conservative Temperature. Then, use the `gsw.density.rho()` function to compute the in-situ density. Use the `help()` function for instructions how to use these functions." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# ANSWER\n", - "P = ds.PRES\n", - "S = ds.PSALPR01\n", - "T = ds.TEMPST01\n", - "Z = gsw.conversions.z_from_p(P, ds.LATITUDE)\n", - "CT = gsw.conversions.CT_from_t(S, T, P)\n", - "Rho = gsw.density.rho(S, CT, P)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**d)** How do the Conservative Temperatures differ from the in-situ temperatures? And how does the density computed form the `gsw` package differ from the density in the equation at a)?" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "fig = plt.figure(figsize=(8,4))\n", - "ax1 = fig.add_subplot(121)\n", - "ax1.plot(T, Z, 'k-', lw=2, label='in-situ')\n", - "ax1.plot(CT, Z, 'k--', lw=2, label='conservative')\n", - "ax1.grid()\n", - "ax1.set_ylabel('depth [m]')\n", - "ax1.set_xlabel('temperature [°C]')\n", - "ax1.legend()\n", - "\n", - "ax2 = fig.add_subplot(122, sharey=ax1)\n", - "ax2.plot(rho, Z, 'k-', lw=2, label='linear')\n", - "ax2.plot(Rho, Z, 'k--', lw=2, label='TEOS10')\n", - "ax2.yaxis.label_position = 'right'\n", - "ax2.yaxis.tick_right()\n", - "ax2.set_ylabel('depth [m]', rotation=270)\n", - "ax2.set_xlabel(r'density [kg m$^{-3}$]')\n", - "ax2.grid()\n", - "ax2.legend()\n", - "fig.tight_layout()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The ship made two long sections on the Eastern and Western side of the Strait to measure the biogeochemical fluxes. The cell below shows the track on the Western side." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# select western passage and sort by latitude\n", - "data_west = [ds for ds in data if ds.LONGITUDE<-5.7]\n", - "time = [(ds.TIME.item() - data[0].TIME.item()).total_seconds()/86400 for ds in data_west]\n", - "\n", - "# plot\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(121, projection=ccrs.PlateCarree())\n", - "ax.plot([ds.LONGITUDE for ds in data_west], [ds.LATITUDE for ds in data_west], 'k-o',\n", - " lw=1, ms=4, transform=ccrs.PlateCarree())\n", - "ax.coastlines()\n", - "ax.gridlines(draw_labels=['left','bottom'], zorder=0)\n", - "ax.set_title('track')\n", - "ax.set_ylabel('latitude')\n", - "ax.set_ylim([35.78,36.099])\n", - "\n", - "ax2 = fig.add_subplot(122, sharey=ax)\n", - "ax2.plot(time, [ds.LATITUDE.item() for ds in data_west], 'k-o', lw=1, ms=4)\n", - "ax2.yaxis.label_position = 'right'\n", - "ax2.yaxis.set_tick_params(left=False, labelleft=False, right=True, labelright=True)\n", - "ax2.yaxis.set_ticks(ax.get_yticks())\n", - "ax2.set_yticklabels([t.get_text() for t in ax.get_yticklabels()])\n", - "ax2.grid()\n", - "ax2.set_title('latitude')\n", - "ax2.set_xlabel('days since start cruise')\n", - "ax2.set_ylim([35.78,36.099])\n", - "\n", - "fig.suptitle(\"Western section\")\n", - "fig.tight_layout()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Apparently the ship did not take the shortest route across the strait. According to the cruise report, the section was split in two parts to give the chemists more time to analyze sample of water in between. However, when they did the second part, three out of seven locations were occupied by fishing boats that they had to steer away from. One data series could still be retrieved the same day, the other two locations were still occupied forcing the crew to do other things and wait. Though there is no need to read the lengthy cruise report yourself, the document is found [here](https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/d232.pdf).\n", - "\n", - "Luckily, you do not have to wait for your data today. The following function reads a list of available CTD profiles and combines them into a single array per variable (setting values outside the measured depth interval to NaN). Make sure you understand what it does and plot a 'cross section' (data is projected along the latitude dimension) of temperature and salinity across the Western part of the Strait. \n", - "_Hint: use `plt.pcolormesh()`, which has the option to use linearly interpolated shading._" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def crosssection(data, xdim='LATITUDE'):\n", - " \"\"\"convert data for 'cross section' plot (actually projection along x-axis)\n", - "\n", - " data : list of DataArray\n", - " list of CTD cast datasets\n", - " xdim : str\n", - " horizontal coordinate in output\n", - "\n", - " x : 1D horizontal coordinate\n", - " y : 1D vertical coordate (pressure)\n", - " temp : output temperature (y,x)\n", - " salt : output salinity (y,x)\n", - " \"\"\"\n", - " data = [ds.squeeze() for ds in data]\n", - " data = [data[i] for i in np.argsort([ds[xdim] for ds in data])] # sort by xdim\n", - " x = np.array([ds[xdim].item() for ds in data])\n", - " PMAX = np.max([ds.PRES.max() for ds in data]) # max pressure measured\n", - " y = np.arange(1,PMAX+1,2)\n", - " # below: one-line function taking in dataset and returning variable interpolated to pressures y\n", - " vinterp = lambda ds, var: np.interp(y, ds.PRES, ds[var], left=np.nan, right=np.nan)\n", - " temp = np.array([vinterp(ds, 'TEMPST01') for ds in data]).T\n", - " salt = np.array([vinterp(ds, 'PSALPR01') for ds in data]).T\n", - " return x,y,temp,salt" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 0.98, 'Western Section')" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "x,y,temp,salt = crosssection(data_west)\n", - "\n", - "fig = plt.figure(figsize=(7,8), constrained_layout=True)\n", - "zmax = 350\n", - "ax = fig.add_subplot(211)\n", - "p = ax.pcolormesh(x,y,temp,shading='gouraud',cmap=cmocean.cm.thermal)\n", - "ax.invert_yaxis()\n", - "[ax.axvline(lat,c='w',ls=':') for lat in x] # dotted lines at cast locations\n", - "ax.axvline(35.962, c='w', ls='-') # divides two straight sections\n", - "cb = fig.colorbar(p, label='temperature [°C]')\n", - "ax.set_ylabel('depth [m]')\n", - "ax.xaxis.tick_top()\n", - "ax.yaxis.grid()\n", - "ax.set_ylim([350,1])\n", - "\n", - "ax2 = fig.add_subplot(212, sharex=ax)\n", - "p2 = ax2.pcolormesh(x,y,salt, shading='gouraud', cmap=cmocean.cm.haline)\n", - "ax2.invert_yaxis()\n", - "[ax2.axvline(lat,c='w',ls=':') for lat in x] # dotted lines at cast locations\n", - "ax2.axvline(35.962, c='w', ls='-') # divides two straight sections\n", - "cb2 = fig.colorbar(p2, label='salt [psu]')\n", - "ax2.set_xlabel('latitude [°N]')\n", - "ax2.set_ylabel('depth [m]')\n", - "ax2.yaxis.grid()\n", - "ax2.set_ylim([350,1])\n", - "fig.suptitle('Western Section')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now repeat for the Eastern section (longitude > -5.33). Do you see a pattern corresponding to the exchange of water between the Atlantic Ocean and Mediterranean Sea?" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "data_east = [ds for ds in data if ds.LONGITUDE>-5.33]" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER (extra)\n", - "# Repeating code for track here, simply for completeness\n", - "time_east = [(ds.TIME.item() - data[0].TIME.item()).total_seconds()/86400 for ds in data_east]\n", - "\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(121, projection=ccrs.PlateCarree())\n", - "ax.plot([ds.LONGITUDE for ds in data_east], [ds.LATITUDE for ds in data_east], 'k-o',\n", - " lw=1, ms=4, transform=ccrs.PlateCarree())\n", - "ax.coastlines()\n", - "ax.gridlines(draw_labels=['left','bottom'], zorder=0)\n", - "ax.set_title('track')\n", - "ax.set_ylabel('latitude')\n", - "\n", - "ax2 = fig.add_subplot(122, sharey=ax)\n", - "ax2.plot(time_east, [ds.LATITUDE.item() for ds in data_east], 'k-o', lw=1, ms=4)\n", - "ax2.yaxis.label_position = 'right'\n", - "ax2.yaxis.set_tick_params(left=False, labelleft=False, right=True, labelright=True)\n", - "ax2.yaxis.set_ticks(ax.get_yticks())\n", - "ax2.set_yticklabels([t.get_text() for t in ax.get_yticklabels()])\n", - "ax2.grid()\n", - "ax2.set_title('latitude vs. time')\n", - "ax2.set_xlabel('days since start cruise')\n", - "\n", - "fig.suptitle(\"Eastern section\")\n", - "fig.tight_layout()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "x,y,temp,salt = crosssection(data_east)\n", - "\n", - "fig = plt.figure(figsize=(7,8), constrained_layout=True)\n", - "zmax = 800\n", - "ax = fig.add_subplot(211)\n", - "p = ax.pcolormesh(x,y,temp,shading='gouraud',cmap=cmocean.cm.thermal)\n", - "ax.invert_yaxis()\n", - "[ax.axvline(lat,c='w',ls=':') for lat in x] # dotted lines at cast locations\n", - "ax.axvline(35.898, c='w', ls='-') # divides two straight sections\n", - "cb = fig.colorbar(p, label='temperature [°C]')\n", - "ax.set_ylabel('depth [m]')\n", - "ax.xaxis.tick_top()\n", - "ax.yaxis.grid()\n", - "ax.set_ylim([zmax,1])\n", - "\n", - "ax2 = fig.add_subplot(212, sharex=ax)\n", - "p2 = ax2.pcolormesh(x,y,salt, shading='gouraud', cmap=cmocean.cm.haline)\n", - "ax2.invert_yaxis()\n", - "[ax2.axvline(lat,c='w',ls=':') for lat in x] # dotted lines at cast locations\n", - "ax2.axvline(35.898, c='w', ls='-') # divides two straight sections\n", - "cb2 = fig.colorbar(p2, label='salt [psu]')\n", - "ax2.set_xlabel('latitude [°N]')\n", - "ax2.set_ylabel('depth [m]')\n", - "ax2.yaxis.grid()\n", - "ax2.set_ylim([zmax,1])\n", - "fig.suptitle('Eastern Section')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Answer: Yes, we see an exchange pattern. On the Western side we see warm and \"less-salty\" (< 37 psu) Atlantic water on top of colder salty (> 37 psu) water flowing out the Mediterranean. On the Eastern side, the warm and less-salty water flowing in from the Atlantic sits on top of the cold and salty Mediterranean deep water." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The following cell makes a T,S diagram for the linearized equation of state. Add a scatter plot of the density computed from the CTD measurements in the Eastern section and compare your results." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Eastern section')" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "lat,p,temp,salt = crosssection(data_east)\n", - "\n", - "# calculating linearized density RHO\n", - "f = 0.005 # add margin around measurements\n", - "T = np.linspace(np.nanmin(temp)*(1-f), np.nanmax(temp)*(1+f), len(p))\n", - "S = np.linspace(np.nanmin(salt)*(1-f), np.nanmax(salt)*(1+f), len(p))\n", - "RHO = rho0 * (1- alpha * (T-T[0])[:,None] + beta * (S-S[0])[None,:])\n", - "\n", - "# plotting\n", - "fig, ax = plt.subplots(1, 1, figsize=(10, 5))\n", - "CS = ax.contour(S, T, RHO, colors='k', levels=np.arange(1025,1030,0.5))\n", - "ax.clabel(CS, inline=1, fontsize=10, fmt='%.1f')\n", - "ax.set_xlabel('salinity [psu]')\n", - "ax.set_ylabel('temperature [°C]')\n", - "ax.grid()\n", - "\n", - "#------------ ANSWER ----------\n", - "CT = gsw.CT_from_t(salt, temp, p[:,None])\n", - "rho = gsw.rho(salt, CT, p[:,None])\n", - "ps = ax.scatter(salt, temp, c=rho, cmap=cmocean.cm.dense, edgecolors='k', linewidths=.1)\n", - "fig.colorbar(ps, label=r'$\\rho$ [kg m$^{-3}$]')\n", - "ax.set_title('Eastern section')\n", - "#------------ ANSWER ----------\n", - "plt.tight_layout()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Answer: the colors confirm (again) that the linearized equations are a good approximation near the surface only." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Repeat the above plot for the Western section and compare both sections. Explain what you see." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "lat,p,temp,salt = crosssection(data_west)\n", - "\n", - "# calculating linearized density RHO\n", - "f = 0.005 # add margin around measurements\n", - "T = np.linspace(np.nanmin(temp)*(1-f), np.nanmax(temp)*(1+f), len(p))\n", - "S = np.linspace(np.nanmin(salt)*(1-f), np.nanmax(salt)*(1+f), len(p))\n", - "RHO = rho0 * (1- alpha * (T-T[0])[:,None] + beta * (S-S[0])[None,:])\n", - "\n", - "# plotting\n", - "fig, ax = plt.subplots(1, 1, figsize=(10, 5))\n", - "CS = ax.contour(S, T, RHO, colors='k', levels=np.arange(1025,1030,0.5))\n", - "ax.clabel(CS, inline=1, fontsize=10, fmt='%.1f')\n", - "ax.set_xlabel('salinity [psu]')\n", - "ax.set_ylabel('temperature [°C]')\n", - "ax.grid()\n", - "\n", - "#------------ ANSWER ----------\n", - "CT = gsw.CT_from_t(salt, temp, p[:,None])\n", - "rho = gsw.rho(salt, CT, p[:,None])\n", - "ps = ax.scatter(salt, temp, c=rho, cmap=cmocean.cm.dense, edgecolors='k', linewidths=.1)\n", - "fig.colorbar(ps, label=r'$\\rho$ [kg m$^{-3}$]')\n", - "ax.set_title('Western section')\n", - "#------------ ANSWER ----------\n", - "plt.tight_layout()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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zAFi5cqXfWM/vvfder6Jtp/ueOp2e71O59tpr+c1vfkNFRUWvtGdBEATh4iMasoIgBNzhw4d7fQEGSElJISwsjHnz5qHRaLjjjjt49NFHcTgc/PnPf6apqclv+U8//ZRXX32VG264geTkZGRZ5oMPPqC5uZl58+b5lhs9ejQbN27kk08+ISoqCrPZTEZGBr/61a9Yu3Yt06dP5/vf/z4ZGRk4HA6Ki4tZvXo1f/nLX4iNjT1vr0NmZiYpKSn893//N7IsY7PZ+OSTT1i7du1Zb3P+/PnMmjWLRx99FLvdzmWXXcZXX3112o2eHnPnzuW3v/0tkiTx/PPP+82bPXs2v//975Fl2e9ZXJPJxB//+EfuueceGhsbWbJkCeHh4dTV1XHgwAHq6ur485//TEtLC3PnzmXp0qVkZmZiNpvZtWsXa9as4aabbvJtb/To0XzwwQf8+c9/ZuLEiSgUCi677DJuv/123n77bRYtWsR//dd/MXnyZNRqNeXl5WzYsIHrr7+eG2+88axfw9PxP//zP1x99dXMmzePH//4x3g8Hp5//nmMRiONjY2+5U73Wh7oeK+55hp+97vfsXTpUh5++GEaGhp48cUX++yF7Mvo0aMBeP7551m4cCFKpZIxY8Ywb948FixYwGOPPUZrayszZszwVS0eP348d911FwAjR47kjjvu4KWXXkKpVHLFFVeQnZ3NSy+9hNVq9av+e7rvKbPZTEJCAh999BFXXnklNpuN0NBQEhMTT/sczJgxg4cffpj77ruP3bt3M2vWLIxGI1VVVWzdupXRo0fz7W9/+7S3JwiCIAxxgaszJQjCpW6gqsWA/Le//c237CeffCKPHTtW1ul0ckxMjPzTn/7UV5F3w4YNsizLck5OjnzHHXfIKSkpsl6vl61Wqzx58mT5jTfe8Nvv/v375RkzZsgGg0EG5NmzZ/vm1dXVyd///vflpKQkWa1WyzabTZ44caL8xBNPyO3t7bIsn6ha/Nvf/rbXMfVUWK2rq+vzWIuKigZ8TY4cOSLPmzdPNpvNcnBwsHzLLbfIpaWlvSq6nsl+mpub5fvvv18OCgqSDQaDPG/ePDknJ+e0qxbLsiyvXr3aV026paXFb15jY6OsUChkQF67dm2vdTdt2iRfc801ss1mk9VqtRwTEyNfc8018rvvvivLsiw7HA75W9/6ljxmzBjZYrHIer1ezsjIkJ988knZbrf77WfJkiVyUFCQLEmSX+Vdl8slv/jii75rxGQyyZmZmfIjjzwiHzt2zLdcQkKCfM011/SKsadqcU9MPXrO9euvv37K1+jjjz+Wx4wZI2s0Gjk+Pl7+zW9+4ztPJzuda/lUx/vaa6/JGRkZslarlZOTk+XnnntO/sc//nFa11hXV5f84IMPymFhYb7t9qzT2dkpP/bYY3JCQoKsVqvlqKgo+dvf/rbc1NTktw2HwyH/6Ec/ksPDw2WdTidPnTpV3r59u2y1WuUf/vCHfsuezntKlmV53bp18vjx42WtVutX/fhM31OvvfaaPGXKFNloNMp6vV5OSUmR7777bnn37t2+ZWbPni2PHDlywNdJEARBGNokWT7F6OmCIAiCIAinsG3bNmbMmMHbb799RlWxBUEQBOFsiIasIAiCIAhnZO3atWzfvp2JEyei1+s5cOAAv/nNb7BarRw8eNCvCJUgCIIgnA/iGVlBEARBEM6IxWLhiy++4OWXX6atrY3Q0FAWLlzIc889JxqxgiAIwgUhemQFQRAEQRAEQRCEYUVx6kUEQRAEQRAEQRAEYegQDVlBEARBEARBEARhWBENWUEQBEEQBEEQBGFYEcWe+uD1eqmsrMRsNiNJUqDDEQRBEARBEIRhTZZl2traiI6ORqEYXn1pDocDp9M5aNvTaDSiMN4gEA3ZPlRWVhIXFxfoMARBEARBEATholJWVkZsbGygwzhtDocDi8GES/YM2jYjIyMpKioSjdlzJBqyfTCbzUD3G81isQQ4mvPP5XLxxRdfMH/+fNRqdaDDuag9+uij/PWvf+WGG27gn//8Z0BiEOf70nGu5/rBBx/k3Xff5cEHH+Sll146DxEKg+lSf2/feOONrF+/nscee4yf/exngQ7nvLvUz/dwc9VVVzFx4kSef/55CgoKePfdd/n73/9OeHg406dP54477mDixIl9rnuxnOvW1lbi4uJ837OHC6fTiUv2MM6UiFI6955kj+xlf3UxTqdTNGTPkWjI9qEnndhisVwyDVmDwYDFYhnWH5BDndPp5P333wfgoYceCti1Jc73peNcznVrayuffPIJENjrVTh9l/J7u7y8nA0bNgCXzvV6KZ/v4aasrIx9+/axbt06LBYLv/zlL6mqquLxxx+ntbWVd955h7Vr17J69WqysrJ6rX+xnevh+tieSqFAJSnPeTuSGPh00IiGrCBcIKtXr6a+vp7IyEjmz58f6HAEYUDvvvsuDoeDrKwsJk2aFOhwBGFAb731FrIsc/nll5OSkhLocATBzyuvvILJZMLpdLJ+/Xpyc3P56KOPfI3Wn/3sZyQmJrJp06Y+G7KCIPRNNGQF4QLpSSWeNmMGf/q//6OtvZ2ExCR0ahVmoxGDTkd0dDRJiYmoVCpy8vIor65GpdHgcbsJNpkYN2bMsCuQIAxPr7/+OgD33HPPsL17LlwaZFn2fb7ee++9gQ1GEPrgcDhITk5m6dKlHDx4kFtvvZWsrCxkWcbj8aBQKLjmmmvYvXt3oEMVBiChQBqEAV8kRJfsYBENWUG4AOrq6vj0008BuGzaNJLS0khKTSUvJwedVovd0YXb7aH80GFWffYZYaGhzLjiCrIiInzb8Hq9/GfdOhZedZVozArnVX5+Pl999RUKhYK77ror0OEIwoB27txJTk4Oer2eJUuWBDocQejlxRdfZNu2bXz++ecoFAomT56MLMtIkoRK1f1VvKioiFmzZgU4UmEg0vF/g7EdYXCIhqwgXADLly/H7XaTlpHB+MsuY8ToMezcsR2LxYpao2Hk2HG+Xq/a6mp27/waR2cnBoPBtw2FQsGYSZPY8tVXzL788kAdinAJ+Ne//gXAvHnziI6ODnA0gjCwnt7Ym2666ZJ4NlYYXmRZRqVSMWvWLGbNmkVJSQlut9v3N1+WZfbs2cO2bdtYvnx5gKMVhOFFNGQF4QL429/+BsDcq64iJi6ekqIijCYTWp2OxORknC4npUVFSAoFHq+XhORk1n/5JUtuvdVvOwqFgsEbxUwQevN6vb6GrEjTFIY6h8PBO++8A4jrVRiaehqsXq8XhUJBQkKC3/zNmzfz2GOPcdNNNxEWFhaIEIXTJHpkhx6RnygI59nBgwfJzs5GpVIxdeblBAUH43A46LB3kJicjMvlIj8vD5VGiyxDh72D5qYm4pOS+XjVql7bUyjPvWKeIPRn48aNlJSUYLVauf766wMdjiAM6OOPP6a5uZm4uDjmzp0b6HAEoV/9PRI0efJkfvazn/Hss89e4IiEMyVJ0qD9CINDNGQF4TzrSXubPmsWZrMJj8eD+3gpfYCSokI0Gg0AHq8HpVKJRqOhoa4WjV7Prq+/9tue0yn6ZIXzp+d6ve2229Dr9QGORhAG1nO93n333SjFTT5hmPF6vej1ehYvXkx8fHygwxGEYUekFgvCeeRyuXj77bcBmHPllYSGhVFSVITJbKa2tsa3jFcGt8dLbU0NSBIhoaGYrMG0t7eTn3+M6JgYYmJj6ezsBLc7kIckXMTa29t57733AJGmKQx9VVVVrFmzBuhuyArCcNFT6Omtt94iODiYq666Stw4HAYUx+sWD8Z2hMEhemQF4Tz6/PPPqampISwsDIPBQFBQEA21tVisVhrq62ltbaGpuRmtVkttTQ1Gk4nomFicTicNdXU4uxxExyew/ssNlJaUcHDvXmZPnx7owxIuUu+99x4dHR2kp6czderUQIcjCAN666238Hq9TJ8+nfT09ECHIwh+Wlpa2L59O8eOHfNNk+XuYVckSaKhoYGnn36au+++WzRihwnJ15Q99x9hcAT0ldy8eTPXXXcd0dHRSJLEqm88D9hfXvlvf/vbAbf7/vvvM2LECLRaLSNGjODDDz88j0chCP3rSXu78847+fH3vsf6tWvRGfQU5R9D9sps37IVhSTR2NgISBjNZtpaWwkKtnHZtGlMnDKVxORkEtNS2bJ+PfMuv9yvkrEgDKY33ngDEGPHCkPfyWPH3nPPPQGORhD87dq1i/vuu48ZM2Ywfvx4Xn31VaD7e21HRwcAISEhFBQUsHXr1kCGKgjDWkAbsna7nbFjx/KnP/2pz/lVVVV+P6+99hqSJHHzzTf3u83t27dz2223cdddd3HgwAHuuusubr31Vr7+xnOGgnC+NTQ08PHHHwPdaZoqlYofffe70NlJTnY2TU2NJCQn0djYSHNjIyaziaaGRlIyMtDpdBQVFFBcWEBLczOZI0YSHBmN2WwO8FEJF6uioiI2bdqEJEli7FhhyNuzZw/Z2dnodDpu/UZ1d0EItJ/85Cfo9XqOHj3Ks88+y5dffskXX3zBzTffzPe//30+/PBDvF4vACNHjgxwtMLpkgbxnzA4AvqM7MKFC1m4cGG/8yMjI/1+/+ijj5g7dy7Jycn9rvPyyy8zb948Hn/8cQAef/xxNm3axMsvv+wr0S8IF8KKFStwOp2MGzeOsWPH+qZfs2gR1yxaxMfr1hFss5Gp1fL1V9vQGgyER0ZRXlJCsM1GUkqKb53ykhLCIyMpKS0lQRSEEM6DniF3rrzySuLi4gIcjSAMrKc39oYbbiAoKCiwwQjCSQoLCzl8+DCrVq0iODiYpKQknn/+eaqqqoiPjyc/P5/vf//7GAwGFixYEOhwBWFYGzZJ2jU1NXz22Wc88MADAy63fft25s+f7zdtwYIFbNu27XyGJwi9DJT2tv/gQVRaLTq9nsTkZLJGj6K+tg6vx01UTAzBISF+y8cmJGAymThWWHhBYhcuLV6vV6RpCsNGV1cXy5cvB0RRMmHo2bNnD/Hx8bS2tgKQnZ1Na2srr776KitWrGDjxo2kpqayZs0aX6+sMDyI4XeGnmFTtfif//wnZrOZm266acDlqquriYiI8JsWERFBdXV1v+t0dXXR1dXl+73nw8flcuFyuc4h6uGh5xgvhWO9UI4cOcKuXbtQqVTccsstfq9tU3MzzQ4HaRkZAHjcbkaOGsX+Xbtwu9xoNBpqqippb2tHUiqQvTJqlYqYuDjyD9ad83kS5/vScbrnesuWLRQVFWE2m7nuuuvEtTFMXSrv7Y8++ojGxkaio6OZPXv2RX+8/blUzvdwM2nSJBobG/nrX/9KZmYmf/rTn5gzZw4jR46ktbUVvV7PFVdcwfr16/F4PHg8nlNu82I518M9/sFKCxapxYNn2DRkX3vtNe688050Ot0pl/3mnY6eMuf9ee6553j66ad7Tf/iiy8uqcI6a9euDXQIF42e3q0JEyawe/fuPpdpqary+318Zia0NpO/q/fz3G4gv7oSgNWrVw9KjOJ8XzpOda7/+Mc/AjB58mQ2btx4ASISzqeL/b394osvAjB16lQ+//zzAEcTeBf7+R6OrrrqKv70pz8RFBTE1KlTycnJ8fvb/e677zJy5Mgz/ns+3M91T6ErQRgsw6Ihu2XLFnJzc1m5cuUpl42MjOzV+1pbW9url/Zkjz/+OD/60Y98v7e2thIXF8f8+fOxWCxnH/gw4XK5WLt2LfPmzUOtVgc6nGHP7Xbz7W9/G+gu+LBo0SK/+TsPHSI8NrbPdbdu+YrUjAyCbLY+t1uafZhFV115TvGJ833pOJ1zbbfbWbZsGQBPPPEEM2fOvJAhCoPoUnhv19TUsHfvXgCefPJJsrKyAhxR4FwK53u4WrRoEX/5y1+oq6tDlmVmzZrFp59+ys0338x7773nSzU2mUyntb2L5Vz3ZDwOV4rj/859O/IgRCPAMGnI/uMf/2DixIl+BXP6M23aNNauXcsPf/hD37QvvviC6QOMvanVatFqtb2mq9XqYf2BcaYuteM9X9atW0dVVRUhISFcf/31vV5ThUJBR0cntdXVKBQKkCRkrxeP10NrSwsh4eHY29uoqapGUiiQJPB6ZSRAZzYP2jkS5/vSMdC5/uSTT2hvbyc5OZk5c+aIZ3cuAhfze/vdd9/F4/EwefJkxowZE+hwhoSL+XwPd5GRkSgUCl5++WWeeOIJXnvtNa688kr+8Ic/EBwcfMbbG+7nejjHDiK1eCgKaEO2vb2d/Px83+9FRUXs378fm81G/PHKrK2trbz77ru89NJLfW7j7rvvJiYmhueeew6A//qv/2LWrFk8//zzXH/99Xz00UesW7dOjNMlXDA9acVLly5Fo9H0mu/s6KDD5SImLg6n04nJbEaSJDatW4ctNAR7ezvVVdUkpab6red2uzm8p+80ZUE4Wz3X67333isascKQ1zPWsSjyJAw1paWlfPjhh2zbto0bbriBO+64A4VCgdfr5dprr2Xy5MkoFApUKtVZNWIFQegtoA3Z3bt3M3fuXN/vPem999xzj++P1YoVK5BlmTvuuKPPbZSWlnb3ah03ffp0VqxYwc9//nN+8YtfkJKSwsqVK5kyZcr5OxBBOK65uZlVq1YB/Vd/raqtxRYVRVFhIfb2dlzOLsIjI3G6PRjUamqqqkhKTcXr9VKcn4+kUKBQKJBlGZ3RSO6xY2SkpV3AoxIuViUlJaxfvx5AjB0rDHn79+/n4MGDaDQabr/99kCHIwg+TU1N3HvvvZSXl5OVlcX3vvc9vv76a15++WXfd9SBHnEThofBqjgsemQHT0AbsnPmzEGWB84Tf/jhh3n44Yf7nd9XYZIlS5awZMmScw1PEM7YypUr6erqYtSoUUyYMKHX/P2HDmGLiKSyrIKgkBBCwsLxeD2UFBVjCwnBHBSE0+VElmXyjmSTMXJUrw/NwwcPkBAXd1qFzwRhIG+++SayLDNnzhwSExMDHY4gDKjnBvfixYtFj5YwpPz6179GpVKxbt06oqOjWbFiBT/5yU+48cYbmT17Nl6v9/hjRR2XVBFRQTjfhs04soIwHJyc9tbXXbuiyiqO5eVhCwtDb9D7Su+7XS7MFgtGgwGvx0t5aQkp6Rl9biNjzFiy846d70MRLnKyLPOvf/0LEGmawtDndDp9Y8fed999AY5GEPytWrWKRx55hPj4eFQqFcuWLWPBggX84x//ALprY3zxxReimN4wJ6EYtB9hcIhXUhAGSW5uLjt27ECpVHLnnXf2mu/1eqmoriI0PMJX8EBGpraqGmtwMJJCoqPDjtPhwOvxou7j+doe7S73eTsO4dKwbds2jh07htFo5Oabbw50OIIwoP/85z/U1dURERHB/PnzAx2OIPhkZ2cTFBTkG+WiJ9Pw4YcfZuPGjRQVFQHw+9//nlGjRgUsTuHcSZwo+HRu/4TBMiyqFgvCcNBTNGfBggVERkb2mu/xeHA5XYRFRBB9fPid1pYWFJKCuJPSOstLS7F32HG73Ti7HOgNxl49s17Ze/4ORLgk9Fyvt9xyy2kPASEIgdKT7bJs2TJUKvHVRRg6oqOjufbaa3tNnz59OrGxsbz22mv86Ec/4osvvqCkpCQAEQrCxUv8NRCEQeDxeHjzzTeB/tM0VSoVao2W+ro6Ojo6kIHGujoSU1P8ljNbLJSUlKDW6tDp9dRU1+J1u0lMTUGpVAKgUYhkCuHsdXR0+MblvvvuuwMcjSAMrL6+ns8++wwQafDC0BMcHMyPf/xj3w1BWZZ9RYGWLVvGihUrqK6uZuLEicT2M4a8MFwMVn+q6JMdLKIhKwiDYP369ZSXlxMcHMzixYv7XOb9Tz5hzMSJdHZ04JW92EJCSUlPp6q8nNKSYuITEmlrbaWhsZFJM048RxMajq/4U9aoUbS1tBATGnKhDk24CK1atYrW1lYSEhKYPXt2oMMRhAG98847uFwuJk6cKFIzhSHp5KyWniF3ZFnmgQce4OWXX2br1q2+CvHC8CWhQJLOvSNBkkVnxGARDVlBGAQ9aW+33347Wq221/z29nZanC4MbW3EJSaiVCqpq62huqKChORkcrOzcbncdHZ2kD5ydK/1JUkiITmF7H37GZEQS2J8aq9lBOF09aQV33333X7DlwnCUNTz+drfkGaCECg5OTn8+c9/RqPRYDKZGDVqFFdffTVGoxHAVzPj888/Z86cOYENVhAuQqIhKwjnqKWlhQ8//BDoP+1t1X/WkDVmLEEnDRkRFh5BWHgEx44eJTk9nfa2NhyOrn73o9PriQ4JZnRW1qDGL1xaKioqWLt2LSAaBsLQd+jQIfbu3Ytare53PHlBCIR//OMf/P73v0ehUKDX6zEYDHzyySf87W9/4+abb+bWW2/FarXy2GOP8cgjjwQ6XGEQDFapJlHuafCIhqwgnKN3332Xzs5OsrKymDRpUp/LuJVKDu7dgyyDWqNCrdaQNWo0JrOZqNhYOuzt1FRWYrQGDbivgSoZC8Lp6Bk79vLLLyclJeXUKwhCAPVkD1x77bWEhoYGOBpBOOGXv/wlP/7xj/nBD36AQqEgNzfXl0L86quv0tzczE9/+lN0Ol2fBSCF4Udx/N9gbEcYHKIhKwjnqOeL1j333NPnuK/7s7MxWoMZP2IEkiTR2txMbU01xQUF6PR6UjMyKDx2DK1eh+ztvxqxLMtoFOIunnD2ZFn2u14FYShzu9289dZbgCjyJAwt2dnZaLVabrrpJt/jGRkZGWRkZHDjjTfy2muv8eijjxITE8PSpUsDHK0gXLzELQFBOAf5+fls3boVhULBXXfd1Wt+XkEh7SotGSNH+hq5lqAgUjMyUWo0OJ1O3G43DXV16PR6Oux2CvJyKS4ooDg/n/a2Nt+2aktLGJ2ZecGOTbj47Ny5k5ycHAwGA7fcckugwxGEAX3++efU1NQQFhbGwoULAx2OIPiEhYVhNBp56aWXkGUZWZZxu914vV5sNhs/+clPuOeee9i8eTMejyfQ4QqDZHDGkBUjyQ4m0SMrCOegp3dr3rx5REdH95pf2dSMLTauz3XjEhJpqq9jx5bNWIOtqDU6ssYk+i1TVlxMl6MTV3s7Y1KSUKvVg34MwqWjp2jOjTfeiMViCWwwgnAKPdfrnXfeKT77hCElPDycBx98kN/97nckJyfzne98p1ehx/DwcHbv3u0bNk8QhMEnGrKCcJa8Xi//+te/gP7T3jo97n7X1+n1uN1uPF4vFquNsD6eoYlLTKTkSDbXXTGnz7RlQThdDoeDFStWACJNUxj6Ghsb+fjjjwGRBi8MLT3jxH7ve9+jra2NJ598kpdeeokHH3yQG264AYVCwd69e1m5ciXPPvtsoMMVBpEkDdLwO4OwDaGbaMgKwlnauHEjpaWlWK1Wrr/++j6XcTgcFBcUIEkSsiwTHhWJwWD0zZdlaGpoYMrl/Y/laQgKprOzE4PBMOjHIFw6Pv74Y5qbm4mLi2Pu3LmBDkcQBrRixQqcTidjx45l3LhxgQ5HEHx6biorlUp+/vOfc8cdd/D666/z1ltv8cwzz5CYmEhXVxfLli3jzjvvDHC0wmASVYuHHnFLQBDOUk/a22233YZer+81Pyc/H61WT2JKCgnJySSmpNDS2ERFWSkArc3NdLS3ERISNmDqkSkoiIbGxvNyDMKloycN/q677hKpbsKQJ8aOFYai6upqKioq8J5UmDElJYVf/epXZGdnc/ToUV5++WW+/vpr0RsrDJrNmzdz3XXXER0djSRJrFq1ym++LMs89dRTREdHo9frmTNnDtnZ2X7LPPLII6SkpKDX6wkLC+P6668nJyfHN7+4uJgHHniApKQk9Ho9KSkpPPnkkzidzgtxiGdN9MgKwlloa2vj/fffB/pO06yuqaHW4SI2MdFvelRsLE0NDdTX1lBdUUFbawuJqSk4OjvR9dEYBmhrbCBi7OjBPoRB0d7ezs9//RwKlRqv2829t93KuLFjAh2W8A1VVVWsWbMGEA0DYeg7cuQIu3btQqVSiR4tYUhZunQpLpeL++67j9mzZxMTE4NOp0OhUKDVaklLSyM5OVncLLxISSiQBqEP8Ey3YbfbGTt2LPfddx8333xzr/kvvPACv/vd73jjjTdIT0/nmWeeYd68eeTm5mI2mwGYOHEid955J/Hx8TQ2NvLUU08xf/58ioqKUCqV5OTk4PV6+etf/0pqaiqHDx/moYcewm638+KLL57zMZ8voiErCGfh/fffp6Ojg/T0dKZOndprfnFlFUFRMb7fmxsbKco/BkjoDXqKCwsx6HQkpKQQFhFB3qFDZE2Y2Oe+9JKEZgiOH/vzXz9HSFQs6WPHoVZ1x7duz17eePc9Xn7mVwGOTjjZ8uXL8Xq9TJs2jfT09ECHIwgD6skeWLRoEeHh4QGORhC67d+/nx07djBlyhQefvhhoqOjWbp0KTfeeCMZGRkEBQUB8OSTTxIVFcV3v/vdwAYsDDpJkgalXsmZbmPhwoX9Vm6XZZmXX36ZJ554gptuugno/gyNiIhg+fLlPPLIIwA8/PDDvnUSExN55plnGDt2LMXFxaSkpHD11Vdz9dVX+5ZJTk4mNzeXP//5z0O6IStSiwXhLJyc9tbXB5JTlgHweDwc3r+PspJi0keMZNykSWSMHMX02XMwmM10dXVxcNdOImzBHN61i84Ou28bHo+H6oJ8Jo7MuiDHdCZe+dvfiU5JIzk9nYlTp5M5ejRxiYmEhoaTkJLKj37xy0CHKBwnyzJvvvkmIIo8CUOfx+PxjR0rsgeEoeSrr75i7ty5rF69mo6ODh566CH++c9/Mnv2bO6//35WrVrFjh07eO655xg7dmygwxWGgdbWVr+frq6uM95GUVER1dXVzJ8/3zdNq9Uye/Zstm3b1uc6drud119/naSkJOLi+h5ZA6ClpQWbzXbGMV1IoiErCGeoqKiITZs2IUlSn2PHwom7bYXH8tBqtYwaNx6D0UhleTklhUU01NUzYsw4GmrrGD15KrbEZEZNmkRzQwM5+/bQVlWBuq2ZedOn9vn8baB1oCAlPQ2X20VpURGlxUU0NNRjMBnRGY2odQbk4415IbAKCgo4cuQIOp2OW2+9NdDhCMKA1q5dS2VlJSEhIVx77bWBDkcQfCZOnMj8+fNxOBxoNBp+8YtfUFVVxbvvvkttbS1Llixh3rx5ZGRkMHPmzECHK5wHPanFg/EDEBcXh9Vq9f0899xzZxxTdXU1ABEREX7TIyIifPN6vPrqq5hMJkwmE2vWrGHt2rX9ZvwVFBTwxz/+kW9961tnHNOFJFKLBeEM9Qy5c+WVV/Z7J8uq1WC3tyMBlmAbrc0t1NZUEx0X73sWtqqiHIPRiLOrC5Wq+60YFRePJSiYUJVEenLyBTmeM+VwOAgND6elqQWk7mGIlEoFsgySQoHX48VoMvLHV17h+9/7XqDDveStX78egBtuuMGX+iYIQ1VPtsvSpUuH5CMVwqVr6tSpjB8/Hq1Wi9frxev1olKpuO6667juuus4dOgQY8eO5fHHHw90qMIwUVZW5jem+zfHIj4T38wO7Bkm6mR33nkn8+bNo6qqihdffJFbb72Vr776Cp1O57dcZWUlV199NbfccgsPPvjgWcd0IYgeWUE4A16v1/f8Vn9pb41NTXR0OTm8dx+NDY2EhodTU11FcnqGX0GnqJhYkjIyyTtyxG99o9lMdVPzeTuGc5Wfn49ao6Wjww5ImCxBJKVnERoRBZICi9VKZ0cn7a2tgQ71ktfV1cWWLVsAkVYsDH3Nzc2+apwirVgYinoaGgqFwncD2uPxAN3ZWkC/mVrC8DfYPbIWi8Xv52waspGRkQC9el9ra2t79dJarVbS0tKYNWsW7733Hjk5OXz44Yd+y1RWVjJ37lymTZvG//3f/51xPBeaaMgKwhnYunUrRUVFmM1m30P1JyssKeFAaTn6yGgmz5xJdFwsxQX5JKSk9rk9o8mE5ht3wgAcbm8fSw8NoaGhtLa2oFJrSExLJzwqCkmSsAYHk5CSijUkBIPJyI9//ONAh3rJW716NW1tbURHR3PVVVcFOhxBGNDKlSvp6upi1KhRTJgwIdDhCMJp6alQ3NLSwpNPPhngaITzSZJOFHw6t5/BiykpKYnIyEjWrl3rm+Z0Otm0aRPTp08fcF1Zlv2ey62oqGDOnDlMmDCB119/HYVi6DcTRWqxIJyBnrS3W2+9FYPB4DfP7XZzrKqGyIRE37To2DgO7N5NQkr/bzWD0dRr2lD+6IiMjKTTbmfclGl+0zs7O2isrcMSFIQtNPycUmSEwdGTBr906VIxHIQw5J2c7TIYlUEF4UISQ0UJ50t7ezv5+fm+34uKiti/fz82m434+Hh+8IMf8Otf/5q0tDTS0tL49a9/jcFgYOnSpQAUFhaycuVK5s+fT1hYGBUVFTz//PPo9XoWLVoEdPfEzpkzh/j4eF588UXq6up8++vp9R2KRENWEE6T3W7n3XffBfpOezuSm0dEfILfNEmSkE5xR8vpdFKUX4BGqyHm+DO3Js3QfmuaLRZfWlVnZwdVpaXojEbCY2JoaWxEazBQW19PeGhogCO9dNXU1PjGjhWpbsJQl5eXx/bt21EqlSxbtizQ4QjCGRsOvVfCuQnUOLK7d+9m7ty5vt9/9KMfAd3fRd944w0effRROjs7+c53vkNTUxNTpkzhiy++8I0hq9Pp2LJlCy+//DJNTU1EREQwa9Ystm3b5hvi7IsvviA/P5/8/HxiY2P99j+Ui3cO7W/LgjCEfPDBB7S3t5OSktJnRUKXLKPqoxchOjaOlqYmrMHBfW5XpVSSkJJCh91OcUEhJq2aiel9pyIPFcbjva1er5ey4mJSM08MEWQLC8MWFsaO3Hwuc7qIjo4KVJiXtOXLl+PxeEhLSyMra+gN4SQIJ+vpjV2wYMGQvvsvCMKlSzr+bzC2cybmzJkzYGNSkiSeeuopnnrqqT7nR0dHs3r16gH3ce+99w7LWhqiISsIp+lUY8cqkHE4HFSXVyApFMheL2GRkYRFhJObnY3JYumV3llVUU5wSAgABqMRlVpJWmQEQVbreT+ec5EeF4NXlikrLiIpLd1vXk1lJY7OTjRaLTtLK9GWlhMbZGF0ZkaAor009VyvV1xxRWADEYRT8Hg8vjT44fhFShAEQQgM0ZAVhNNQUlLiG8akvzRNrUZLSXk58ckpvoZudUUFjfV1pI8YQc6e3VhDQ1HqDHR2dNDS3IRCUuAwdaJSqzGaTETHJdDQVEc8sX3uY6gYP2okr320muCwUL/GeVV5OXqDgfCoaL/l6+x29mUfYfzIERc61EvS/v37OXjwIBqNhssvvzzQ4QjCgNavX095eTnBwcEsXrw40OEIwoA++ugj1qxZw0MPPSSKkl1iJEmBJA1CavEgbEPoJhqygnAa3nzzTaA7vSMxMbHX/IbGRqo7unpVJ46MiaG1uYncfXtZfOVc3G43b63+D2MnTib2pO1UlpXSYbcTFhGBd+g+iuDT2dmJTqumpamJuKQT07scDiJjejfCtXo9u/ccpt3RhUqhICkmisjjz2UIg6+nN/a6667DZOpdTEwQhpKetOLbb79dFIkThrw///nPfP7554SFhYmGrCAEmGjICsIpyLLs+6LVX9pbXkkpHV0u2oqKQJaxBAURZLMBYAkKhrAwDAYD2/bsZfLM2b1Sk6Pj4ikuyMdssWDTDf0vci2tregNBgxKpW/Q7ZrKSiKio3st29RQT1NjI5kTLkOhUNDR2cnqr/dgVUrcvOjqAER/cXO5XLz99tuAKPIkDH2tra188MEHgEgrFoa+iooK3zAnYqzjS0+gij0J/ROvpCCcwrZt28jPz8doNHLzzTf3mt/U1ExJdS1hEZHEJyURn5yMjEx+zlHfw/luSYEsy7Q4Xf0OKxGXmETegf1kpA7tQk8AkRERNDY0EhMXT3lRIdBdfVmr0/stJ8syTY2NJKam4XF7KMzNpamhgZDIGNokNa+seJ8de/YG4hAuWqtXr6a+vp6IiAjmz58f6HAEYUDvvvsunZ2dZGVlMWnSpECHIwgDeuutt/B6vcycOZOUlJRAhyNcYIMzhqwkhhcbRKIhKwin0NMbu2TJkj7TNHcdzSFj7Dg0Wq2v4RpsCyExNY3Swu5GnkLqbuh5lf0nQSiVShKih0e1TpVKRfGxXOz2dmw2GzkHD2ANslJZVuq3XHlxEXFJyQAUF+QTnZCIvb0dtVZDYnoGMSlplHd5eP+LL/F4PIE4lItOT1rxsmXLfEMkCcJQJcaOFYYLWZZ9n68ie0AQhgbxLUcQBtDZ2cnKlSuBE2lExSUlHM7J6V7AK6ONiqEo/xhIEgpJgcfrAVkmKTUNALfbjcLZhVKpRHa7+92XLMtYTMbze0CD6Jc//C9eXfFv5sy/GpfbTUtTI421dUTFxvmNp6dUKqmtqiIqLp7y4iIS09IpKSxApWokOCQUj8eNQ6nh43UbuHHBVQE8ouGvvr6ezz77DBBftIShr6CggC1btqBQKMTYscKQt2vXLnJyctDr9dxyyy2BDkcICAWD0wco+hEHi2jICsIAPvzwQ1pbW0lISODyyy/nXytW4nA6MZpMyLJMWVUlWeagXkWePB4PRw4eRJa9FOfnY7XZ+GLXXtoaGwkOD0enN/TaV31lBXPGjLxQh3bO9Ho9N86ZzWvL32T6nCuRgAlTp7J7xw7ik1OxhYb6eqgdnZ3ojSYsQUEU5BwlJWuEr/fFeHzA7qqyUopLSkhMSAjUIQ17y5cvx+VyMXHiREaNGoXL5Qp0SILQr57e2Hnz5hETExPgaARhYD29sTfddBMWiyWwwQgBMVhpwSL7ZPCIWwKCMICTx45969//xiNJmCwWnG4Xbo8Hg8lMXFJSr/WUSiVxSUmERUSSnJFBSFgYEfEJpI+fQFFeLi6n02/5tqYm4qxmdDrdhTisQZOclMgzP/0JFk8XRYcOUFtZQVh4OGq1kvLiQpoaGqirqQa6iz7JQFRcfJ8f4lFx8ezOyb/AR3BxOTlNUxCGMq/XK8aOFYYNh8PBO++8A4jPV0EYSkSPrCD0o7y8nHXr1gGwdOlSvti8BS8yjq4u9Ho9kqTAYgvpd32T2UxDXW2v6ZljxpG362siYmLxAlqlRHJEOPGxgz92rNvt5lBODu3O7p45rVJJcuzg93zMnDqVmVOnUlJewZY9e4lJSCQouLtqc0dbG5KkwOV24fF4CI048RxwU0MDbc3NSIruYljNTc2+KsjCmTl06BB79+5FrVZzxx13BDocQRjQxo0bKSkpwWKxcP311wc6HEEY0Mcff0xzczOxsbFcccUVgQ5HCJjBqVos+hEHj2jICkI/3nrrLWRZ5vLLL+fw0aO0tLbgcHShPd6I9cpeLGERA25DoneDTJIkJL2BmWNHndOYiS6Xi0M5OXS6u4sk6VVKRmdmolarAbDb7Wzdf5CIpGQsJzUMDxR1F2Tyer3sOnCQFocTlyyjlMCsVjNhZNZZx5UQG0NcdBRrtm4jJCkVSZJITk+noqSEpqp6JKXSt2xlWRlanZ7Y5BOVHyNj41i9ZRsLZ07ze85WOLWe7IFrr72W0NDQwAYjCKfQkz1w2223odfrT7G0IARWz/V69913ozzp75hwaZEkBZI0CMPvDMI2hG6iISsIfTi5OuE999zDkdxcZJWakIhw1GoNZqsVl9tNfU0NZUVFyLJMkM2GJSjIbxte2dvn9nVGE4dz85g4ZnSveW63G4/Hg1arpbmlhWPFJXS6PcjI3T2qMdGo1Wr25OYRkZCI5ngjVZZlNu7Zy2WZGQQHBbHvaA6Ryb2HB7BFRtBeUcrGr3cRmpxKyDcajOt37mbmuDEYDIaz+oOtUCiYP30qOw8corW+FndMLDEJCdjCQtm2aRNut5suRxcKhYLg4w2uttYWmuvrAVBrtOw8cIip48ee8b4vVW632zd2rEjTFIa69vZ23n//fUBcr8LQV1VVxZo1awCRViwIQ01Abwls3ryZ6667jujoaCRJYtWqVb2WOXr0KIsXL8ZqtWI2m5k6dSqlpaW9N3bcG2+80ed4TQ6H4zweiXCx+frrr8nNzfVVJywpKcUaFIzeYCIsIhKDyYzRYmXS5bOIOz52rNvtoiA3x1fgqLSokNj4vgsXeb0eWru6032rqqs5fPQom7dtY8uevWzef5DtR3P4dP0GdhzJwRgVTWhcHGFx8ViiY8irqWX7gYNEJib5peBKkkRUUjIHj+Xjcrno8MoDHqM1xr+6sCzLFOUfo0OGLTnHWLNzD5v37KW6pnd69KmoVCqmTxzPfTcsprmyHAC9wcgVVy8ke/dOGmqqCY/uTnEuysvF2dVFbFIysUnJWIKDOVhSQXNL6xnv91L1+eefU1NTQ1hYGAsXLgx0OIIwoPfeew+73U5aWhrTpk0LdDiCMKC3334br9fLtGnTSE9PD3Q4QgBJg/hPGBwB7ZG12+2MHTuW++67j5tvvrnX/IKCAmbOnMkDDzzA008/jdVq5ejRo6csiGOxWMjNzfWbNtyK6AiB1ZNGdPPNN2OxWEgbMQKFQoHeoMfpctHZ3s7EaTP81rGFhmEJCqYwLw+dSoHT0YXqeJrvyepraggKCaGuooKP1q4jKiERh9sDZgthJz0/mm/vIL6vAdcVSkyhYf3GrjZbyC8oQG+xDniMao1/bPk5R0lISe0V86HySgAiI8IH3F5fJElicmYau3KOYY2Oxd7eRnhUFA31DQCUFuYTk5CIWqPxraM3GEgbM47NBw6zeNb0M97npagne+DOO+/0pZYLwlB18lic4nl4YSiTZVkU0ROEISygDdmFCxcO2HvwxBNPsGjRIl544QXftOTk5FNuV5IkIiMjT7mcIPTF4XCwYsUKoPsPl8vlwmA0gQIa6hswWixYbSEUFxYgIXU/K2u1EhIahkqlQi3BNTOmsXrDJooL8olPSkahUOD1eiktKsRgMBIUbKPs2DHGzOhuqDXk55OUemIIn+bmZqwnpSmfrLWlhfgB3geW4GC6aqpxdHVgsQ7cmO3R2FBPSHi4XyO2qrICV1d3deWv9u3j5qsXnNa2vik8NJRFM0I4mneMiooyYkeMwePxIssysiz7NWJPpg4Oo6C4hJREMRzPQBobG/n4448B8UVLGPqKiorYtGkTkiSJsWOFIW/v3r0cPnwYrVbLbbfdFuhwhAATz8gOPUP2lfR6vXz22Wekp6ezYMECwsPDmTJlSp/px9/U3t5OQkICsbGxXHvttezbt+/8ByxcNHqqE8bFxXHFFVfw6erVeL0e6mpqSc0agcvpJjYxiYTkFOKTk0lMSUWhUFBWUgKANSycw0eOYjObaW1qpKKkhLKiIipKSohLTCI8KorqinLSjqco2dvbMVnMfjG0NDdh66dgj95gwN7e3m/89rY2QkNs6E56d1eVV1BcUEhJYRGlhcW91mlrbiHoeAVmh8PBsaNHCQoOJi4pibikJEKTUvl863a6urrO5KX0kSSJERnpxBy/wWQLDaOipLj7BkE/dEYjJdU1HMnNpbau7qz2eylYsWIFTqeTsWPHMm7cuECHIwgD6hly54orriA+Pj7A0QjCwHqyB2644QaC+rm5LFxKJLqbTuf6IzJRBsuQLfZUW1tLe3s7v/nNb3jmmWd4/vnnWbNmDTfddBMbNmxg9uzZfa6XmZnJG2+8wejRo2ltbeUPf/gDM2bM4MCBA6SlpfW5TldXl98X9NbW7mfzXC4XLpdr8A9uiOk5xkvhWE/H66+/DnQPuePxeKioqUGjMxAcGkpddTUTpk1DpVbh9bh961isVtwuN00N9XR1dlKpUBISFU2S2UppUSGh4RGERYTj8XgoL8rH0dZO4oQJeNxuOuztaDRaPO4T2wu22aiprCQsondV5NCwMPLzcklJ6/tZHXtDPRETxqPX61mz5StUeiN6owHZ6wEkPF43SqC8qIjY42PgSrLsO56KkmKS07vfKz3T9Hod+vh4tu8/wIwJ48/6tdVI4HC7MZqM1NfW4OzsQPZ4ei3X2dlJbWUlBoMeD3qOlVSjyi1kTFIskeFnnuJ8Meu5XpctW9brPSze25eWoX6+Tx47tq/rVTgzQ/18D3dOp5Ply5cDgb9eL5ZzPdzjF4YeSe6pTBNgkiTx4YcfcsMNNwBQWVlJTEwMd9xxh++DBGDx4sUYjUbfwNSn4vV6mTBhArNmzeJ///d/+1zmqaee4umnn+41ffny5RgMhjM/GGHYamxs5MEHH8Tr9fLKK68QEzP4Y64KwmApKyvj//2//4dSqeQf//iH6DEQhrTs7GyeeOIJ9Ho9r7/+uqhdIQxp27dv5/nnnyc4OJi///3vYtidQdDR0cHSpUtpaWnBYrEEOpzT1traitVqZWn07WgUfT8OdSacXifLK1cMu9dhKBqyPbKhoaGoVCpGjBjhNz0rK4utW7ee9nYUCgWTJk3i2LFj/S7z+OOP86Mf/cj3e2trK3FxccyfP/+SuMBcLhdr165l3rx5l3yhmJdeegmv18vUqVN56KGH2LJ9O21eqKutJTohAWeXi+gBntnMz8kh2BZCSHjvYkylRYWER0bTVF2JUa8nNDzc93xoSWEhsQnxKJUn3pL2DjtVFRUkp6bBSQVR6srLyYyLQaVSUVhegcPtQZZl9GoVybExBB9vzOzZs4fD5dVkjRmDTn/iC6PX46HywF5U4dF88Pa/+NZDD+HyeCmvrUNlMBCbmDjga6RvayEzve/shtNRUlFBdlkVtpg4cg8dxBISRuhJRa7KS4qIiInv90uDqrmWyaOykGUZTT/P114qHn/8caC73sDSpUt7zRfv7UvLUD/fPY8G3Xbbbdx0002BDeYiMNTP93D3t7/9DYD777+f6667LqCxXCznuifjcbgSz8gOPUO2IavRaJg0aVKv6sN5eXkkJJx+8RdZltm/fz+jR/cer7OHVqtFq9X2mq5Wq4f1B8aZutSO95tkWebNN98E4L777kOtVtPhctPpdJI2chQd9nYaGuqJ7auS8HEej5ewqKg+5ymVagwmE46gYIxaDSVFRWSMHAlAUloax3JyCA6xERbenU6sVCgxqdV01FThVSiRZRmdSsm00SPR6/UAhIf1X734w48/ZtK8hRhMfT+HGhkbQ1JGJpPGjgGgobGRzzZtxhMX71eAqbmxieamRiRJgcftIlQtMUqlOutqo6mJicRGRnIwNw+9RoNWq6WkIB+lSoVKraapoZGYpNQ+162rqqStsYHKzkM4urpQOdoZm5rM2BGZZxXLcObxeHzZKj3Xa38u9ff2pWYonm+73c57770HdDcMhlp8w9lQPN/DXW1tLZ9//jkADzzwwJB5fYf7uR7OsQtDU0Absu3t7eTn5/t+LyoqYv/+/dhsNuLj4/npT3/KbbfdxqxZs5g7dy5r1qzhk08+YePGjb517r77bmJiYnjuuecAePrpp5k6dSppaWm0trbyv//7v+zfv59XXnnlQh+eMMzs2bOHI0eOoNPpfNUJdUYjrU4X+3fvJiI6GpVajdfr9Rt/tUdTQz0R0X03Yk9mCw2juriIxJQUjuXkoDcYiImLIyo6mtqKcpxNTdiCgwkLsjJx+tmPsXjj4sWUd/b/PIrH48XlcrHvyBFsZjMJcXHcdcP1rNq0hbi0DACqystRqtTEJ59ovLucTtZ+tZ15M6addWNWp9MxeewYau07cbhdGExGIqJj8Ljdfs8Kn6ymohyNzoA1PJK2lhb0BgP6sHD2lNVyuLCIOxYt6PO8XKzWrl1LVVUVISEhXHvttYEORxAG9MEHH9De3k5ycjIzZ84MdDiCMKC3334bt9vNpEmTyMrKCnQ4whAhoUAahDq5g7ENoVtAG7K7d+9m7ty5vt970nvvuece3njjDW688Ub+8pe/8Nxzz/H973+fjIwM3n//fb8/gqWlpX5fXpubm3n44Yeprq7GarUyfvx4Nm/ezOTJky/cgQnDUs9YcTfccAPW48PWKCUFpcVFJCSnolCpcLW3s2PjBqbOmet33dnb22gpLyVhTP+FkLyy1/f/dXU1uDvtRIeFERVio6O1mTiLhUlpfRcxOxtTp07lzc/W9Du/vLSEa2+9HY8kUWq3k7vtayZmpjEiLobKpiZUWi0er5eIbxScUms0WOKT2HXgEJPHjTmnGL0uJx6FmrCoaCpLikGSaGqoIyohqVcjubPTgUZnwOl0EndSw9poMiPLMp9u3sbiOZfOF+Seapp33HHHJZ9iLQx9J4/FKcaOFYa6nuv13nvvDWwggiAMKKAN2Tlz5nCqWlP3338/999/f7/zT+6dBfj973/P73//+8EIT7iEdHV1+dI0e/5w1dTWkp9/DJ3OiBfQqrWkjxpNW3MLR/bvp7PTTrAthJqKShbOmMqUK+ayYd8BwuITe22/sqyUkLDuarter5eYoCDmzxm8Rmt/2mprkGXZ74tjbVU1ALGJib7peqMRvdHIjiM5LJw+FU15BdsOHCJt/MQ+t6tQKGg8y6F4TubssKOw2KipKCcmsbvxGhYZRcGRw6SOPPE4QE1lBeHR0dRWVvo1YntIkoTHEkJRaRlJ8XHnHNdQ19zc7HveUHzREoa60tJS1q9fD3RnUQnCULZ//34OHDiARqPh9ttvD3Q4wlAiSX41S85pO8KgEH3bggB8+umnNDY2Eh0dzVVXXUVzSwt5lVV4JAVBYaGkjhhFbGIiOr2BsKgoRoyfQExCEs6uLiSvm/TUFHQ6HVMyM2gpL6Opvnvc09bmZorzj2EwmTCZu8eKrSw4xpWXX5iew4fvupODO7b53TDq6LT7LSPLMi6nE1mWCY1P5NDRHJLi40iKix1w2y7vuRc8V6rVaHV6YhJONKq1Oh0x8XHkHTpAe0szAA67HY1Wh0LR/4e/0WyhqKrmlDfHLgYrV66kq6uLUaNGMWHChECHIwgDevPNN5FlmTlz5pB4imJyghBoPb2xixcvxmazBTgaYSjpKfY0GD/C4BiyxZ4E4ULq+cN11113oVQq2XvoMF1KFXX19cyaNKXPVLjImFjqqqv8hpCwBQdx5ZTLqG9oYN3Wr1AF2UhM7a7wK8syNcXFTMpIu2Bl/FUqFTER4RTmH0OpUCAh4XS5UAFul5uC7Gw6Ozsxmkx4vTKOjg7CTUbGjhyB8qRjlmWZipIS3G43kkKB7PXibG855/g6nW5iQ0J6TbcEBTNyXDC7N3zJnEnjCYsLJ7e2qs+7mLIsU1ZYiAyoNWreWr+dUIOG8SkJRPZRPfpiINI0heFClmW/61UQhjKXy8Xbb78NiGwXQRgORENWuOTV1NSwevVqoPuL1oEjR1CYLcRHRlJSXoFe3/9YwnqjifAgM6XlFeRX1dDm7C6uZFQpGT9qFFaTkZLqWmRkNEoFV0+9DJXqwr3tGhoaUVqCSAoJ9U07dvQIAEcOHSA4JJyUrJGUFRWiVCoxGE3YHZ188uV6Jo7I4lBVDUFh4eQdySYxNR3VSRUHO9rb2b53P9MmjDvr+PT9VFTuERUdxYRR3ZWd67/eTavd22uZorxcYpNTUX7jdd2SV8IsSSIiLLTXOsNZbm4u27dvR6lUsmzZskCHIwgD2r59O8eOHcNoNLJkyZJAhyMIA/rPf/5DXV0dERERLFiwINDhCEOMKPY09IiGrHDJW758OR6Ph8mTJ6M/XqU4PNRK9qFDaDTdwzLJskx1RTlul5uI6Gg0x4drkr1evF4FeQ3NWKJiOLlZVtXWRldjE1PG9j/00/lWWl2N9aRGbFNjAx63BwCT2UpMQgL5R4+QNmIk9vZ26muqUet0OIAvvt5FXIiN/Lq6Xo1YAIPJhN3rpaSsjIS4s3suVasZuBR/aNCJcZznTJpA+SeraW9twWTpLsbV1NCALTyiVyMWwBQexYGCEuZfZA3Znt6tBQsWEBkZeYqlBSGweoqSLVmyBNMpblwJQqD1XK/Lli27oDedheFBkqRByYISmVSDR9wSEC55PX+47r33XqoaGjFbrNjb25AlJVabjcqyUsqKCgkJCycuKYmGuloK83Lxer14nF00uDxYQno3lgxmM+UtbXg8ngt8RCd887OyvbWN8Kjuxk9wiI2KkhJSMrNoaWqkubGR+JRUVCo1Xo8Xoy2M0uY2yosLezViexgtFkrrGs46PqMkUVKQT1lhIaUFBTQ1nNiW2+0m3Hzii69CoeDu668lyNlGdXEhsizT3tqCOSi43+3XdzrPOrahyOPx+MY6FmlvwlDX2dnJypUrAZFWLAx99fX1fPrpp4C4XgVhuBC3m4RLltfr5cCBAxw8eBCNRsNtt93G4eISAKqqqknOyKCqvAyNTk/wSQ3VqNg4ZFkme98+woOMGMKi+92HLTqWo3nHGJWVed6Ppy8J0dHsLSknKLT7WdHQiAhfISprsI22tnaUSiWN9fUkpqVTkJtLVGwcesOJdOr41HQO7tqJLSwMWZYJj4pGe9JzwWdb9Km4vILaLhexSSm+u5MtTY0U5eWRlJ5Oe3kJc2fP6LXeFdOm4HK5OJSbR4Nn4MrJF1vdp/Xr11NeXk5wcDDXXXddoMMRhAGtWrWK1tZWEhISmD37/FdpF4Rz8c477+ByuZgwYQKjRwcuk0oYwiRF989gbEcYFKIhK1xy3vvoI9QGA1VV1fz7re7erZGjRxMUFIREd0PWK0NxQT72djtZY8b22oYkSUTGxOBoriPUaOx3XwqFAntnJ3a7HVmWL3hqXXBQEKq8Y3i9XhQKBXq9nsqODrTg6/1sqKvDFhZOVXl5r0YsgMFoJHXESFqaGomKjaOqvAyP201sYhIA1XV1bNuzDw1e3vn0P4TGxKMzGAEZg8GA1Wwi0momIy6GqIjuIYi6urrYU1ROWFyi376swTZ0ej1lB/eyZMFV/abfqNVqJowaiUKhoNzt7jO1GEDlcXIkJ5fgoCCiIiP6XGY46Ukrvv322/2KjAnCUNST7XL33Xf7jbstCEORGDtWEIYf0ZAVLilvrfw3qSNGcPjwYeISE9i/Zw8Ayx56iBWffEKwwUhwdAx1NTVkjB5Dc1NTv9sKjYigztFOTUUZUXEJfS5TX1PDxs8+YU92Mm63m6aGBiaNGc2i+fPPy/H1Zdaky/jXux9gDA8nMTWNiMhImtuaqa2swGC20N7WSlxSMk0NDb0asT0MRiP1Nd3jz0bFxmFva6O6ohydwUCbo4tNe/fT2dlJ5mVTCA2PpKy4CLM1CEmhwOGVKWpso8ldwRiHg5SEeA7k5GGL6fu5Wq1OT1BoGNrjzyEPZGxWJnkbtmGOTfSb7uzqoqwwH6vFSiFGOssbUOUVMT45jsTYmDN7AYeI1tZWPvjgA0B80RKGvoqKCtatWweINE1h6Dt8+DB79uxBrVZzxx13BDocYYgSxZ6GHtGQFS4ZBQUFJKank334MGMnTmDvzp00NTYSFhHBtTfeiEql4uutX2Hfuxuj2UxZcTEmi2XAbSpVKjxd3WOw9tV7WHosjxtvvZ1gmw1ZlikpKqS0qIg3V6zgrgs00LokSeg1KiSvl/1f7yAk1IYCOLR3N8mZIwgOCaWlqbHfHpO2lhYa6+twdHZSUlgAskxYZBTtbW1UlpZisdkozi8gdeRoUrJGsPurrYy6bIpfL6ksyxQezWZ/ZwcpCfE4PF4kSaK2sgJnVxeyLBMZG4daowHA4Tm9nGBJkpgzJpPNh3LRhEWiPl6cq/BoNuljT4yvajBbwWzl69JaNGo10cd7hoeTd999t/tmQWYmkyZNCnQ4gjCgN998E6/Xy8yZM0lJSQl0OIIwoJ7sgWuvvZbQ0IurQKAweESxp6FHNGSFS8aOvXvJHDOWsPBwQkJDef+ddwBYcO21lBQWAeDyeqmubuSyWXPQ6nTkHj5El8PRPXaqLIMsExkTi06vp6WpieAgKzabjY2btpCcNRKzNQiADrudI/v2oFVJlBQVUVFRjvv40DzjJ01m59atvnTfs9HZ2clnX65H1mhBKeF2OAk26Jk7fVqfPZljR46gziPT2tLsm7bs/gfpcDjYtHYd7W2tWIJseL1eSgoK8NI98Lezq4tOezujJ070i7WipBhHZwexyckcO3KEqIQEtDodeYcPkTluQq9UX0mSSM4aSVl+DscKi7C3t1Fd10RETCx6g6G7KnR5GbIsE5OQiOoMPuPDQ0O4ec40jh4roLmjkaqqahIzR/S5rCkknENF5cOyIXtyUTLxR1AYyk4eO1ZkDwhDndvt5q233gJE9oAgDDeiIStcMlQaDblHjxIRE01jQwMb164FYMG115GYksKhQwdJSE0j3O1Fq9PR1FCPRqfDZA3C3taG1WbDGhRESUE+oeERtNbXkDJ2NDlHjtJlt+NpaiDnyGGCI6NY9+mnjJsyGVtYKEqlCoVCwquXcbtcHDl0iNiEBN5csYJ7li494+Po6urinU8/o6KiAo1Wh1anQ6VWUVntoLndzi2LrkapVPqtk5GWxpZ/v8eUWbMozMsD4MCe3bjdHlLSUiguLMDV2UlLSwspI8f4NVq9Xi+52dlkjhrla0DFJCTSWF+PLIOkUKDV6pAkCZfLhVan7zNuSZJQqjS0d3TS4nCRmJbhNy8qLp72tlZqKsqJ0p86rfib2x6RngrAepeHTm3/z482DsNKxvn5+WzduhWFQiHGjhWGvJ07d5KTk4Ner+eWW24JdDiCMKDPP/+cmpoaQkNDWbRoUaDDEYYySRqkYk/iZvRgEUnawiVDKcuYLRa8Xi8fv/ceLpeL9Kwspl1+OXk5OaRkjqC5uQXb8Qq/5SUleL0ySpWK2MQk3C43RXl5hIRFkH/kEEatmo0bt6C02LjsinlYEpKJHzseh8tFUFgIJouZ2PgETMeHkJEkiaiYGPQmI3V1dTS3tp3xMciyzN/e+CfbtmzF7fFiMJlwuT1UVlQQFhZBaXk5ew4c7HPd62Zfzo7Nmwm22QAYf9llJCQl0tbSwuQRI5iYmUbyiNG9eokVCgWJGVmUFRf5TY+KjaO5sQGj2USH3Y7X60Wn7/sZ2x5er5f6xgZCk1L7nG8yW2hrbGB8Rt/zT4d8ir8PHq+XfdlH2LLvEF8fOExnZ+dZ7+tC+de//gXAvHnziIkZns/4CpeOnt7Ym266CcspHs8QhEDryXa58847Ufcz1JwgQHem2mD9CINDvJLCJeOmxYvxetw0NzbywYoVAFx3080UHjtGbW1ddy/m8Q+XwrxcLMHBJKamYTmeLmwLDSUxLZ266irCo+MoLi4l67LJWINPjGOq0xuIS8sgNDKa8MgoyoqLUarUaHUGgkJCaGxsQKvT0dHRQXpy0mnFXd/QwLa9+3n7k9X8e90GJly1gId+9BMyRo9Bq9MzacZMMrJGkZOTgynIyhebN/e5nYiICB5YchOFhw4AsH3TBgqPZrNg6mTmzJxBq1Pu1ZPbQ6lU4vF4/aaFRkRQV12Fy9FFU30d9ra2ftfv4XF0oDNbBlzOarViPofqziEGHR63u895jXW1tNntFMtGmnTB1GiCeP/rQ+zJPnrW+zvfvF6vryEr0jSFoc7hcPDO8cc2xPUqDHWNjY18/PHHgLheBWE4EqnFwiVDoVAQGxLCex99TPbBg6hUKubMm0dQSAhHc3MoLSqkpPAYTreb6vIKpsyZ2+d2ElLTKC0sQFJr+n1WMW3MGAqPHSPYFkJzUzNhkRF02u24nG7Uag0qjYqFp1G5uKKqmpzqWuwOJ3HpGSBJfPLevzGYLETGxuFRKMnLO4ZKpSJz3GUolEoUejOvrfoEW1AQwWYTQXodDpebLo8XJTBvzhx279zJ/bfc4nf32Y084AfCN4+1qb4epVJJcFgYXmRqKsvQGYwYzBaCw3o/g2pva2VcQgyOUwzuqlCcW8rN2KwMctd/hSnW/0ZBZ0cH9rZ2YtKy/KZbIqLJb2shqKSUlIT4c9r3+bBp0yZKSkqwWCxcf/31gQ5HEAb08ccf09zcTGxsLHPn9v0ZKghDxYoVK3A6nYwZM4Zx48YFOhxhyJOO/wzGdoTBIHpkhUvKxAkT6Dxe8GjMhAm4PG4OHjjA3AULQaFkxPjLSEhJJSwqEntbG+XFRdRUVvhtQ5Ik3C4ncSlp/e4nKDgER5eTxLQ0EpKTMRiMhISFk5iaikanR6U8vXtIuWUVBIdH4Pa4kYFP3/030fFJTLviKqJi44iOTyAoJJTI+ASS0jPQ6nSERUaROu4ybImp1HZ5ya5tptMSijc4HFdwOHsq6vvcl0458AerLPv3yLY0NxESEoK9uRmlQoHZbKWhpor927dSVVbqt2xTfS2hng4mjRtDjC2Yzvb2fvcTrNWc1mvTH0mSWHDZGNw1ZXS0tgDgcbupyDlMdGLfveB6s5Wcitpz2u/50pP2dvvtt6PX9/38sSAMFT1pxXffffcpMzQEIdBEUTLhTEgMUmqxaH4NGtEjK1xSXC4XK46nFc+9ah6dnQ6mXD4LWZbp7HISGh2Mo7OT9rZ2LB0dxCYm0eXopLSwAJ1eT3hUNABdnZ3U1VRhb2/D6/USHhXtNwarLMsE22woFAoqykpxOV1IkoQsy6g1akzmUz83VlNbi8pspqK0hJj4BMqKiwgJjyA+NRW9wUBddRWxiUmUFRdjtljp6OgAICwyCgB7ux2P10t0QqLfds1BwbRWQE5+AaOzMn3TU6IiOFjbjPF4KvXJWpubMJnNvt9LCwsIDY/A6Opk5oRx1NXXs3bb19hsY9BbLHQ0N1OZ3UB4WBgmnZbZKTFEhHU/e5ycEE/Olm3IRiOSJNHW0kxTfQOyQsLlcBBr1mO32zEajadxRvsWZLVw/aypVFRVU13fgE6tRp0Yj2uAddpdnrPe3/nS1tbGe++9B4hqmsLQV1VVxZo1awBxvQpD39GjR9m5cydKpZI777wz0OEIgnAWRENWuKR88cUXvuqEmWPGEBHdXTinrLSEqLgEAEoLCxlz2YlxOrU6PfHJKTTW19NQW0tIeDgOZxeh1iB60kzKi4qxBFt92yvKzSFzxAiO5RwlLiER3Uk9aY7OTipKSk4Za2NTMyaLlaaGRpRKJUUFBZiDggkNjwC6ex4rS0uJju+Ou766irjkE+M1NtRUE5vc//iNFc1tjD7p9/iYGBqaWyipr8N6vOAVQH1NNdVlJYSGhVNSUEBddTWjJ06kq9NOSkwUsiyzIzuHmNHjT6QfH38tm8tLmJCR2qtRevWMqWzdu5/8qhrU5mCiEpP95q/Ze5jZI9MIPV6Y6mzFREUSExUJQPnXewdc9hwzms+L999/n46ODtLS0pg2bVqgwxGEAb399tt4vV6mTZtGenp6oMMRhAH1ZLssWrSI8PDhNySbcOGJcWSHHtGQFS4pPX+45l19NTVVVUw9/hys1+NFpVJRWVaKQqWiuCAfhUKB1+tFrVYTE5+ALTSUkoJ8GuvrCAoOIS4p2fdh1FhXR2V5KSazBQmQO9qorarq1YjtsLdTV1NLRHQMufkFZKT239CMi4lmR14h0fHxVJSUUFdThdUWAnT3+Pb08Pak70nfHJP2FB+UXe7ePZDjR44gvrGJT7dsQ2W2dvcsh4YybvJU3zKW4GBqyksZER1BVEQEh4/mYIyO7/ODOSg2gQN5+UwfPxaA+oZGckrKcHplNAolBr0RW0xcr/XMkbHsPJrPohmTBzyGMxETZCbX0YVa0/fQPuGGMxvy50LouV7vuece8YdPGNJkWfYb61gQhjKPx+MbO1Zcr4IwfIkkbeGScXJ1wslTp9Hc3ExrS/czlCGhodRUVlBRVkZUXDzxySnEJiYRn5yCLSyMgtwcAFxOJ0iQnJ7h17CwhYWRlJZB9u6dxOqUTB41is4Ou68R6+zqIj83h9bmFuKTkgiLCOdwSSmFA/TMmkwm1B4nKpUKt9uFQlZgb2vH4/EgSRJerxerzUZjXR0Astf/GVZOVVSpn4aRLTgIoy0EizUIhSTR2tREWVEhZUWF3fsMthGu1zH2eFpynb0T1QBDFjQ5ugDYfegIWwrK6bKGIQeHU9rehTEiut/1OpQampqbBzyGMzEyPRUaKpH7eF06asqZmNX/M8+BUFRUxKZNm5AkibvvvjvQ4QjCgPbs2UN2djY6nY5bb7010OEIwoDWrVtHZWUlNpuNa665JtDhCMOFpBi8H2FQiB5Z4ZLxzjvv4HQ6Sc/IQJYkEpNTqCovR6PRUl9bR25ODhNmzkaj9e+Z0+r0RMXFUVVehiRBaubIPrdvNJkIDY8gPbk7TfZAcbFvXlH+MdJHnFhPbzCSOmIkZQ31aCoriY3uu0E3edRINu3ZR2xCIkcPHaC5vo6ywgIS09LRaLSolErqm5uwhYVhtdloqq8nODS0ex9GI/a2NownPdt6smB9/0WVGuvriYo3+aUqe71eCnKOkJSeifGk54G9wEAlXbwyFJeVU+WWsISE+qa7XE60uv6LF5ltoVTV1BAcFDTA1k+fJEncMHs6m/ccoLLNQRcSStlLpEnHrPEjMBmNFJaWUVhdj1sGo1rRZ1r0hdIz5M6VV15JXFzvXmtBGEp6iubccMMNBA3Se1YQzpee7IGlS5ei1Q69bBxhaBqsMWDFOLKDRzRkhUvGX/7yFwCmz5lLSHQUETGxlJeUoFJraGpsxGA2o9Xp+lxXpzdQ21VFS1Mj5cVFAETGxqFS+b+FlCf1TNqON4CqysuJS0zsc7tBIaEUVpb325DV6/UsmDGNI7l5zJ0+g6/27eXYkWy8Xi9J6RmUFxehVCooyDlCZEwczQ3d49QaTCbCIiMpOHqU2OTkPtNpx6an9rnPjo4OrLYQgkJC/KYrFApSs0ZSkHOUyzNPNHCNSgXOPrfUzaBSUVhdi8EW6TddrdHi6Oz0S70+WVtDPdEjTm+s3dOlVCqZO3kC0J1a1pOWLcsyn23eQYvOit7Y/XxwJ/D+19lMT44kNfHCDstz8tixomiOMNR1dXWxfPlyQFyvwtDX3NzMqlWrAHG9CsJwJxqywiVh9X/+w+HDh1Eqldz98MNs+GItXklBa3sHaJrIGD2W8tJSaiorcHZ1dafuejxExMT4eg1dXV3oDUZiE5OQZZmK0hK8Hg/xJ/VaalUn+ibtra0Y7O10HV+vP519PKt6MkmSGJmZAYDNbOSzrdvJ2b+PomO5mK1WGmtrkVHS0daKTqfnwNfbCDabiY6LIzLYQlP+UQxBNhxeUEsQrO1+2+v6abRv27sfhUqD2+XqlTIsSRJKIDUp0TdtZGoy67NzCY6M6bUte0sTWVHhZFdU8829RUTHUHTsGPEpfTeojV4nXV1dbN6zn9LqWhxuD3qNhvhwG2PSUrBaTl35eSAnDw2y80A2ndZI9N+4MWGOiGZbQTlxUREX9K791q1bKSwsxGQycdNNN12w/QrC2fjss89obGwkOjqaefPmBTocQRjQypUrcTgcjBw5kokTJwY6HGFYEePIDjWiIStc9DweDy+89BIA02bNJvvgQcKioiguLOSyy+cSGhGBLMvUVVcxYtx4dPoTabMVpSVodTpCwyNwuVyMGDse6G7QxSYk4ujsoLy4iNjj45NGWU80rvTWYKrKK/B+Y/zVbxr4SVZ/WWlpbDucQ3hUDE5nF9agYGLjE/F6vXQ5OjGZrZitFkaE2xiZmdnnNlwuF6sry3tNLymv4Eh5JS69hWCzmZqqSpxdXcQnp/g1+gxGg996ZrOZsbFR7C8qwRodi1KpRJZlmqoqSLZZSIyLJbfyxBitdVVVdHU5kGUZo9FIdXkZkbEnUmdlWaY8L4fWliaqHW66HJ2ERccTaupOkbYDaw7mMTbSRmaqf7Xjs1XSbEcdFtTnPFNEDPuO5DF1/Og+558PPWmat956KwaD4RRLC0Jg9aRpLlu2TIwdKwx5PZ+vooiecKZEavHQIxqywkVv34ED7Nu9G4C0zCzSRoykorICr0JFaET3UDbF+ccYN2Uaim9U/o2JT6Ak/xgajRZXVxelhQWYrVaCjz/rqdMb8Hg83Q23smJGxkWz93A2AF0eDykZGRzas6fPFFpZlinMP4bH6eSTbV+jlMCsUTM6NYUgq7Xf43HY2wmOiESr09Pe2uKrXmy2BtFht9Pa2EDypPFn9BpVVFdzqKoBS2Ssb1p0fAKyLFNw9AhpJz3fq1H2/gBOjI0hPjqKQzm5OFweVAqYMmG0r9c33KyjuKWZ+poaIqJjCYnsHranpqKc9pYWmjtbMQbbcLvdlFVVkzBiNN5yNbLsJSYxGbWm+3ne2spKujo7USgVbMotorimlikjswgO6v/1Oh12t4egfuZJkkS7y31O2z+jWOx2/v3vfwOimqYw9NXW1vKf//wHENerMPTl5eWxfft2FAoFy5YtC3Q4giCcI9GQFS56n3z6Ga0tLZgtFhbedBNlRUUUFBYydsp0AFqamnB2uXo1YnvEJaew7ct1zLhqHpIk0dLUSH5uDrHxCej0eiJjYqjKPoDJaKDM7sAa2j0enauxCYDREyeSdySbtKwRftvNPXKEpPSMXj0YX+fkMW1EJpZ+ijTpLVY62tvRG43EJnX3SMqyTGlBPh32diSvF30/z532J6e0Akt47+d0JUkiMjaO+toaQsO7e65DdH2n2CoUCsaOyOpz3tjMTHau+g/JY040sHu2bbJayDCqGZGeyuY9+9CPn0RFaTHRCYlUlZb4GrEVxUUEhYQSFnUiThlYeyiXK0amntOYs+pT3JXvq/F+vnzwwQe0t7eTnJzMzJkzL9h+BeFsLF++HLfbzeTJk8nK6vv9LwhDRU9v7NVXX01UVFSAoxGGncGqOCx6ZAeNeCWFi96mjRsAGDl2LCNGj8bhcqKQFDidXRTl5eHxeNAZ+m/4KRQKElJTfSlI1mAbyekZlJcUA+D1yqgUCiLSMrD6NaZONI5iExLJz82hsb57qJzK4+m0faXhhcbGc6SgsM9YSsvLUWq0xCYlY7YGUVlWSnlxEeXFRYRGRKLTGzD009AcSHOXq995JouFTrsdr9dLc2khU8aOOuPtH8k7RnxW3+uZzFaK6rsb/Q0dx8tGyTJKlQrF8QZkZ0cnSpUag6l3496t1PLh5h38Z8de1u/aR2V1zRnHF2Xq/zVrb6pnROKFqxos0t6E4eTksY4FYSjzeDyiiJ4gXGREj6xwUWtubmb7V18BMO6ySbhcLkJCwnC7vXjcHtJGpAP4xpPtT19jj4ZHRVNfU4PC6cBgC+nVoxubkMCxnKOkZmRiMBpJy8yiubGR3EOHcNrbCZ8c22ubPVq6+q4D3NLahkarpbOzg/riGuISk3w9lvU11UgKBY1NTQMeS18GfooX3PY2zPYmZs6cdlbPwDV1dqHqp4cZoNXp6RWH1+vF6+1+3eurq3y9zycrLyzEFBRMdNZYvHRXGt5aUkdcVS3TzuCZ1imjMvhkxwF0kf7Vibs67JgdzezM9dDoOAZAqEHN2OQ4osLDTnv7p6u0tJT169cDiLFjhSFv//79HDhwAI1Gw+233x7ocARhQBs2bKC8vJygoCAWL14c6HCEYUiSpEG5wSxuUg8e0ZAVLmorV67E6XQSn5hIfHIypYWFJKWn09DUTMboMVSWluL1emhpbCSuj4YSQG1VJaHhEb2mmywWiqoqCVNLhCeP6DVfo9WSmJJKSWEhksuJ2WxGLcG0kVmU1tYNGLe3j4YzQKeji5bmZux2OwaDkdrqamLiuxtfoRGRmCwWWvoo5HQqZnX/jVNnVxeT0lPISk874+32ONVHds8tAOPxOKLiEigvKUb2djdtFYreW6irrsIaGorR7F+92BgUTEV7GwUlpaQknN6wOSajkeunjWNndh419i7cXhmjSkGQ7KJeG4zOEoLu+G7agXU5ZczscpIU17tS87l48803kWWZOXPmkNjPkE2CMFT09MYuXrwY2zmk9gvChdBzvd5+++39Vu0XhAFJ0iClFouG7GARDVnhotbzh2vJzTcze9588nKOUllVjSU4mKJjeWi0WrxeLzq9npxDB8kcPcZv/faWFrocDsKj+h7n1Sh7GJGaSUVnB4Y+hthRq9XEJyWhamlk1EnPj9U2NiDLcr935XTK3m/Nrbv30WmwMHL8ieECuroc5B89Surxbev0BmwRkb3WPZWkUBuFra0Y+xjSpqOmgszLp5/xNk+WGBHGnppmDOa+izIF67qH+UmNDONwYwsGsxWdXofH46U4LweNVtdrOKCujk5CIno/4+T1elFrdRRU1592QxbAYDAwZ9I4v2nLv9yBLiKk17J6Wzi7CsoGtSEry7JfWrEgDGUul8s3dqwo8iQMda2trXzwwQeAuF4F4WIinpEVLlq5ubns2LEDpVLJlQsX0tbSgqOjA7PFQntbOw11tbS2ttLa0oJaq0X2etm+cQN5hw+Rl32YAzu/Ji/7MB63m/wjR6gqK/Pbfkt9HZdfNoG4uFjs9fX9xlFbVkpWerrftNEZGdSVl/Zatqmxgbwj2bTZ29m6dz8FRcUAFBSX0KEzofvGUCxarY7YpGQqSk9sS32GhZ4AMlJTiFbLNFWU+dKo7a0t2CtLmT1u9DmnwcRGR6G2N+P19k5ibquvYVRSd5p1amICCTqJ5ppKwiOj0esNeD0e6spLKTx62H/Fb/TSNjc2UlpYQGVpCXU11eTXNPL1gW+scwbyCoogKLTf+U5DEKXlFWe9/W/atm0bx44dw2g0smTJkkHbriCcD6tXr6auro6IiAgWLFgQ6HAEYUDvvfcenZ2dZGZmMnny5ECHIwxXx1OLz/VH9MgOHtEjK1y0enq3FixYgNFsob6tDZPVSnlZKbJChdliRZZlDGYLsiwjA2arhabGBiKjY0gfOQqX04kkSajUauzt7ZQWFhCfnILH48HdVE/oxO4e3ITwUKobG7F8I72uo72dSLOp13OlGo2GMQlxHCgsJCw+EYVCQXlpCRqtzm+om8oOO2Vf7wSlCn1o3xUWNVotbteJYk2qs0x7GZuVyUi3m8O5eXiBpJAg4sb0PRbt2bh6+hS27NlHbacbpdGM29GJSeFlUkIs0REnUrfHj8gis7OTw8cKMWkhIzWeMVnzqKypZcvRQizRcd1DDnlPpF83NzbS5XAQm5Tit88Kp5Mvd+zmyqmXnXG8docDjbb/53p1BhPNrW2cfp/vwHqu1yVLlmAymQZpq4JwfvRcr8uWLUOlEl8lhKHt5KJk4vlE4ewpGJw+QNGPOFjEXx/houTxeHjzzTeB7jSi+vp6ymtqcXm9aLR6DFYr0XGJBIX4p422NDZQcPQIDkcnJQUFqDVaZGTcTic6vR6tTkfh0WyMBh2JkScaX6mJiShKSiktL6PT40GSFGgVElFBFjL7GZImJiqKqIgIDh3Noa6pCa3O6BvXtofeYMSlUlNeWEDk8YZsWXEh9dU1mK1WouMTMBiNSCcVmgrSa876dVOpVIwb2ft538GgUCiYPWkiXq+XhoYGjEYjhm/0MPfQ6/VMGjPSb1pMZARLQkPYk51Du9OFrqvVl27c2tzUqxELoNZoqG1XU9/QSGjImT3DFxkawqGCWgyWoD7n2xvrsSTY2LbvEF4gLsxGQuzZpRp3dnaycuVKQKQVC0NffX09n376KSDSNIWhr6CggC1btqBQKLjrrrsCHY4gCININGSFi9L69espLy8nODiYxYsX8/EX6+hyOgmLiqauvgGzJahXIxbAagvBZA1Cpnv82JO1NjfR2W7HZNSTlp6Oq96/YFNyQjzJCfF4PJ7u5zRPep6zPwqFgrEjR7Bj3wHq3V5KC4sAyD96lLyj2YTHxmG326kuLSEmMZmw6GjiktMYOWkqAFWlJTjsRej13YUrmmuqmJQ8WH2E54dCoSAs7Owq/qpUKt/wP7I8js82b8cdEo1igDvsJlsoOSXlzDzDhmxURDjGo4XIBPU5v6WimA1eD8aQ7psPBWUt6PNKWDRlLCZj7+elB/LRRx/R2tpKQkICs2fPPqN1BeFCW758OS6XiwkTJjBq1JkPxyUIF1LPkDtXXXUVMTGDW6BPuLQEqmrx5s2b+e1vf8uePXuoqqriww8/5IYbbvDNl2WZp59+mv/7v/+jqamJKVOm8MorrzBy5IkOgUceeYR169ZRWVmJyWRi+vTpPP/882Rmnsi8e/bZZ/nss8/Yv38/Go2G5ubmcz3U8070bQsXpZ60t9tvvx2tVktpeTnxyanY7XYUkoSzq4uyokLKigqpqfCv8puSNQJ7W1uvbVqCgunqciBJClqbmogO6/v5SaVSeVqN2B51DQ0cOJaP2WolNimJHVs309zWSlxKGpJCRVhEFAtvuYPkrFFMmD6LqLh46qqqKCsswO31olBrKMk/RldNFZclxhEe2v9zncNNWWUVn+/YzTsbtrN8w3Y+/WonucfH2JUkiWtmTSPa237K7bhcLsrKK2g76bx6vV4qK6tobGzsd70rxmXRWVWMx+PxTfO43ZTs/5qQ9NG+RiyA3mSBsHjW7Dx4xsfZk/Z299139xrGSRCGmp7PV9EbKwx1Xq9XXK/CsGe32xk7dix/+tOf+pz/wgsv8Lvf/Y4//elP7Nq1i8jISObNm+f3nWfixIm8/vrrHD16lM8//xxZlpk/f77f9xun08ktt9zCt7/97fN+TINF9MgKF51vVicsr6jAKUOno5OQsDDaOxwkZ2b57oh1OTrJP5JNUkYmSqUSpVLZ53A7AOExMZTlZBOsVhKRmd7nMmfiy40bOVbXyITpMwEoPJaHjIQtLByXy4VS62XSzFmUlxRjDQ5GqVJRcPQIkXEJhESe9MyspCAyyELEeRjbNFCKy8rZW1GPKSSKk/vOc1pa6ThylPEjus/hpDGjKG7a0ec23C4XJfm5mA1GalUdOAqrCZI8KNxOmrxKFBYb7i4HHfW70SsgMTqcMckJhNiCAQgOsnLnldPZk32UyqZ2JCDWZsYRGYVao+21v067ndr6Fj7+cguTRmUQFRF+yuOsqKhg7dq1gEgrFoa+w4cPs3fvXtRqNXfccUegwxGEAW3atImSkhIsFotfD5YgnBVJMUjD75zZNhYuXMjChQv7nCfLMi+//DJPPPEEN910E9B9szEiIoLly5fzyCOPAPDwww/71klMTOSZZ55h7NixFBcXk5LSnYH49NNPAydurg8H4ta/cNF59913fdUJJ02aREVFBZagIJAkOjqdZI4Z55fWodXpSckaQVlRd09fbXVln2nHADqdHr3sYeZlE/ucfybKKyr4Yus2xk89MbTNV1+uIzQiko6OTjxuD9Gx8Wi0OpoaGoiKT6C8qJD41HRkWaa8uJDy4kLsbW3EJaewu6gct9t9znH1R5ZljuYdY2/2EQqKS87bfnocKq3EFNK7Ya43W8iva/W7i5hos+DqcvRatjT/GAnpIwiJS0Sr12MNjaCosQ17UDTGyDj0BiPm4BAi0kYgB0eQ3+pi9eFCDufl+7ZxMC+f/Lo26j0qat1KDhRV4lL3fra3ND+PttZWYtNHYQ9NYnVuDe9v2E5XV9eAx/nmm2/i9Xq5/PLLfX9MBGGo6vmCc+211xJ6EWV/CBennt7Y2267Df1ZVPQXhJMNRsXik9OTW1tb/X5O9X2hL0VFRVRXVzN//nzfNK1Wy+zZs9m2bVuf69jtdl5//XWSkpKIi4s7uxdjiBANWeGi0/NF695770WSJJrtHZjMFmorq0jO7LvwkiRJKBUKZFmmrrISszWoz+Xqyku5ceHVvaoQn42//Ost4pJS/BrVHrcbg8GIUqnEbLWi0Xb3+klIeL1evLJMaWE+7W0txCQkEZOQREd7G0W5RwlPTGHfkZxzjqsvBSWlrNqygzKvmhZ9EHntLj7esp2qmtrzsr/6hgac6v6/dFiiYjiYk+v7fdLoEdicLbQ1nHhuubywgMiERL/X197WhskahFrTuyCW1RaCo7MTU0gEeyuaaG9vZ+ehI2S3elGHx2INjSAoLBJNRAJOp9Nv3YqiAiLiEn3j2jo67LQ0N1HS5uYvH35OTW1dr/2BGDtWGF7cbjdvvfUWIK5XYehrb2/nvffeA8T1KgxNcXFxWK1W389zzz13xtuorq4GIOIbxUIjIiJ883q8+uqrmEwmTCYTa9asYe3atWj6+D40nAS0Ibt582auu+46oqOjkSSJVatW9Vrm6NGjLF68GKvVitlsZurUqZSW9h5/82Tvv/8+I0aMQKvVMmLECD788MPzdATCUJOfn8/WrVtRKBQsW7YMgLziYlqam7EEh6Aa4NlVjU7H0T27aGts6HO+LMvYNEp0Ot2gxKo1GOAbz/vLCgUulwuv2w2S5BvT1RYWRlVZCU31dcQlpxIWGe1bJzQyivjUdMoK83F4eo/Teq6qa2vJrm0mKDbB1wDUGQyYYxL4Or+Yjo6OQd9nc0sLelP/Q99IksRJo+8AMGfSBBaNSiLU0URwZyPBCg9anX9juLmhnuCwvtPGAbR6ffdYw+FR7MnJ52hNM1qDqdcyzs5O3+9erxcZCZW6+7WpqyzH3tpCVEIyUQlJhGdN4JPsCrbs7f3s7M6dO8nJyUGv13PLLbf0G5cgDAWff/45NTU1hIWFsWjRokCHIwgDev/997Hb7aSlpTF9+vRTryAIp9KTWjwYP0BZWRktLS2+n8cff/zsQ/tGASlZlntNu/POO9m3bx+bNm0iLS2NW2+9FYejdzbbcBLQhuypHl4uKChg5syZZGZmsnHjRg4cOMAvfvGLARsS27dv57bbbuOuu+7iwIED3HXXXdx66618/fXX5+swhCGkpzrhvHnziImJYduuXWRNnITBZMQWFkJleVl3kafiIkoK8mluOlHop721hcumTmHGnLlsW/c5zQ31vnltTY10VZYx67IJgxarWquh026n66QPkcumTaOpoQ6X20WnvQN7e/eD+iazhbbmFoJsoX32BisUiu6hes7DB1JOaTnmkL5TCK1RsRzMze9z3rlIiIujvb7/3t6OtlYijj/HerIgq5Vp40Yxc/xobMFBveafqlCgSqXG4+4ek7egtBx9eGyfy+mNRpqOx9dUW+PriW1vaUKlVhNy0o0GAKMtlMIuDUePFfpN78keuOmmm7BYLAMHJwgB1nO93nnnnWdU0E4QAkGMHSsMNklSDNoPgMVi8fvRanvX3jiVyMhIgF69r7W1tb16aa1WK2lpacyaNYv33nuPnJycYd/ZF9CG7MKFC3nmmWd8Dyd/0xNPPMGiRYt44YUXGD9+PMnJyVxzzTWEh/dfQOXll19m3rx5PP7442RmZvL4449z5ZVX8vLLL5+noxCGCq/X62vI9lQnLGtoIjgkFL3RhL3dTnBoKLFJycQmJhGfkorH7aGyvAwASfZSUVqK3qAnOiqSd179A5qWBrStDUyICWPejCmDWlG2o7kVpVLB4T27fdOyRo2hrroKr9cNspeWpiZK848RGhGB2+Ui9viQQNXlZVQUF1JRXEh1WSmyLBMeHYNWOfhv6XaXZ8D5baeYfzbUajWhWoWvR/qblPYWYqOj+pzXI1iv6bW+3mDC3trS7zr2tlYM5u4GpVIh9Xu+QyIikWSZ1uJcOtuacR5/Pre1qbHfHl+NwURO1YnefofDwYoVKwBRTVMY+hobG/n4448BkaYpDH3FxcVs3LgRSZK4++67Ax2OIJw3SUlJREZG+opGQnf14U2bNp0yE0GW5bN6LncoGbJVi71eL5999hmPPvooCxYsYN++fSQlJfH4448PWHlu+/bt/PCHP/SbtmDBggEbsl1dXX4nsrW1FegessPlcp3TcQwHPcc43I9148aNlJSUYLVaWbRoUXfVX40Or8dNW0sr6WPH09xQT72jEmSZ4NAwgm026qqryN6zi8z0NFqamnA5nWjUau667TYmjMjwbX+wX59rrpzLln37cXU52LVlE2GRkURERTN/0TV89u67WGyhBEeEU1VWTGtzMx63E4e9jeqyMqITE9FoujMTnK4uinOOEBkXT4RBf8o4z/R8yx4vsmeAxqrXc16uneljR/HFjl3I5mB0xu7GpdPVhau+mjljR51yn6PTU8jbugtjxIlxdYNtNkoK8jCaTL2W73J0opS6b2jYGxuZOiqDHRXVGIP7rgStkV3cPGcysizzt882YTJbUEoSePt/rexOty/uDz74gObmZmJjY5k5c+Z5eQ0vlve2cHrO5/l+++23cTqdjBkzhpEjR4praggQ7+/+vf766wDMnTuXyMjIYf8aXSznerjHjySdOrXrdLdzBtrb28nPP5H9VlRUxP79+7HZbMTHx/ODH/yAX//616SlpZGWlsavf/1rDAYDS5cuBaCwsJCVK1cyf/58wsLCqKio4Pnnn0ev1/s9JlJaWkpjYyOlpaV4PB72798PQGpqKqY+vjcNBZLcX5fHBSZJkt8Av9XV1URFRWEwGHjmmWeYO3cua9as4Wc/+xkbNmxg9uzZfW5Ho9Hwxhtv+E4edA/eft999/V71+Gpp57ylZw+2fLlyzEYelcnFYamP/zhD2zYsIH58+fzne98J9DhCMKA/ud//oc9e/awZMkS3/PcgjBU/fSnP+XYsWPcf//9LF68ONDhCEK/ZFnmW9/6FjU1NfzgBz9gzpw5gQ5JOK6jo4OlS5fS0tIyrB6naW1txWq18t3xz6FVnnudlC6Pg1f2PX7ar8PGjRuZO3dur+n33HMPb7zxBrIs8/TTT/PXv/6VpqYmpkyZwiuvvMKoUaMAqKys5MEHH2TPnj00NTURERHBrFmz+OUvf0lGxokOm3vvvddXgPJkGzZsGLLvoyHbkK2srCQmJoY77riD5cuX+5ZbvHgxRqORd955p8/taDQa/vnPf/qNb/f222/zwAMP9PtAc189snFxcdTX1w+rN9rZcrlcrF27lnnz5g3b557a2tqIi4ujo6ODTZs2MW3aNAD++cEqwmLiyD2WT0JKOl1Oh686sSzLSHSP/dllb8dsNpIxchQlBfnUV1Uy+8orcTbUMTqr70rHg8XtdvPyq3/G7nTi7nLx/YcfICysdy9gS2sr67LzCQ7vO6W2paGOWalxvjFQ+3Om57u1rY2tR45hjojuNa+lvJiF0yYNShXn82XTnoOU2N24jr/Hw2JiUSqUNDc10t7STFNFCcnJSSjVGvRKBSkRNjKSE4Huc/P5jr20qkwYjleytjc3Eix3smDqRBQKBR9s2Q22aBpqqqkqKyZlxFi0fQzzIMsysd5mJo/KZO2mr7hh0Xy8Xi+bNm9m2tSp5+XYL4b3tnD6ztf5PnLkCOPGjUOlUlFcXDzg4z3ChSPe333bunUrV1xxBSaTibKyMoxGY6BDOmcXy7lubW0lNDRUNGTPsCEr9G/IphaHhoaiUqkYMWKE3/SsrCy2bt3a73qRkZGn9cDzybRabZ8PWKvV6mH9gXGmhvPxfvzxx3R0dJCWlsbll1/eXdXW66XL7cXhcmMOsiEpFcSnpPnWkWWZotwcOh0OgsMjiE9JpbCokGNHsrnltttQKBR0SYrz/pqo1Woe//GPaGtr+//svXd4G+eV7/8Z9EoUgiQI9iZSvXdZstxkxb3H3U5xfjfJzWa9Wd/NZr1xNu1u9ibx5u5N9m52k9y4O3HcEjfZlmTL6oWq7L0XEAAJEh3z+wMiKIggRYqUSEnzeR76MWbeeecMNADmvOec76GmqZmOPjdRhFE1oO1d3Vgzk4sPAZjT7XQ5ndgzJvaQOdF/71SrlXVzizlUXY9focJgtjLg7MFAlOtWLp02FecLRQiB1MysUdvNtjTMtjQsei0PXpPckVQqldy+eT0dXd3Ut3chIFAyP5e0M/oM+6ICWpmc1MwsAoEAzfXVFM5dhFwx8vUqiiJ1J8tpFyIca3Wya8fHRKNRihctpzJiYnB/OVvXr5z+iz/jOi7Vz7bE5Jnuf+/hxeStW7eSlTX6syQxs0if70SGW0Tde++9mM3mmTVmmrnU/60vZduBGUstlhibWevIqlQqVq5cSVVVVcL26upq8vLyxjxu7dq1bNu2LaFO9oMPPpCk1y9zzuzFOaxO+PGuz1i8bj1H9u0lJTWddEfiA5ggCBSWzeX4oQPIlUoEQSC7sAh7Ti5V1TXMLSu9aN81uw4ewRWNOaMAx3vdnGhsZuOShfH0dqNeT5PHlzTaBxAMBtBqJq94NxHSUlO5cW0qbo+H7p5eshaWXjKr3DqFjPGkDLTKcwtkZWakkznGAoFGPnKTiAgUL1hKZ3MjQ94BdAYjohhFjEbJnTOPzpYmTLnFfPaXrwFw1S13ozNZ6AwG2HPkBGuXLpjUtUlIXGgikUjcMZBEySRmO0NDQ/zhD38AJFEyCYkrgRl1ZM9VvPy3f/u33HfffWzcuDFeI/v222+zY8eO+DGPPPIIWVlZ8SbCf/VXf8XGjRv553/+Z2677TbefPNNPvzww3GjuBKXNg0NDXF1wocffji+3R0Ika1QMNA/wLwVY6dumswW1NqRqKJCqSQsU9DW2sKKosJpsbGppYWWHidhUUQhCOSk2cjLiUVXDx4/ScBowXxGVoAhxQwpZnYeOcbW9THbC/JyOfLJXtTanKTnCPb1ULJh1bTYOxZmkwmzyTSlObp7eunu7SXdZiM9LXlbn+lkYVE+7xyvx2Ab7YiGgkGKrGP3q50IuWYdTdEoMpns9GKtgMFkRmcwkmIdidx2NDWQmVdIQ8UxWmurUKrUrL7hZgCUKjU1zl7WTskSCYnpZ9u2bbS3t2O1Wrnppptm2hwJiXH505/+xMDAAAUFBWzYsGGmzZG43BCEeA/YKc8jMS3MqCN78ODBhOLlJ598EhgpXr7jjjv493//d3784x/zjW98g9LSUl577bWEL6fm5uaEFhnr1q3j5Zdf5h/+4R94+umnKSoq4pVXXmH16tUX78IkLirDLXeuvfZacnNHFGojp++LFJNp3BpOo8kMRBO2pWfl4K46jmnZ0inbt/fIUXxqHfr0TFSnt9V5PHSWH2XV4kW0e7xYsq1jGUdbRydZmbFI7aKcTI73ONFbUhOGDbr6mO9Im9W98np6neyprCWk1qM3W6hs7ERdVcfaeSXYrGNc/zRgtZhZmG7geG8vBuuI4xwYGsLTWMlQUQG1DU10uTw0e4YIRKKo5DKyjBrWL1mAQjH+1+TaJQto/2gXQWtOvN2P1+3Cnldw1kgBmVzOrrdfA2D55i3ojSOLAv2B8PRcsITENDLci/OBBx44rx6HEhIXkzN7x05nuzwJCQABYVqeswRm77PapcaMOrJXX331mH0ih/nCF77AF77whTH3nxmdHebuu+/m7rvvnqp5EpcA0Wg0Ia34TAYGYm2U0uwZRE9HzJLhcfWhVqlodFeTnV+A4nQNR2Hu2CnsE6W2oRG/1jCq3YvBZGJwQMaRY8eR6ceWNDekmGnv6Y07ssUFeajVHZxqbsNz2vExaZQszbKTnz17a9cGvF52VNRhtGfHnXmD2QJY2H6ihptWLLygCuGLy+aQ2dvL8foWfOEoLe0dRFQacucvwymK7N5fTsG8xajSrXH7ekSRP368m3uuXT/uQoggCNx17QYOnTjFUNSH19U3xmqrSCgYYM97bwBw1S33JOxVyqQfNonZhdvt5o033gCktGKJ2U9LSwsff/wxIKUVS0hcKczaGlkJiYmwa9cuGhoaMBqN3HnnnfHtzr4+hgYGiUajZOflU1tTS17xnKRzuJ29LFu7DlEUqa+soGjuPFyd7ayehnrF9j4XuiRqvwB6o5Gexi4iqvEduLN9ohxHJjmO5MrFs5Wj1XUY7ckdbWNmNuWVNaxbtviC2pBus3Gtzcb2/YfJnLsovrDR2dJMbun8+OsBtxtPnzP++vd/+YjPrV1Gxjhp0IIgsGLhfFYsnM/hU1V83OmJ18gOYzRb2P3uG3g9bixpGSxYnZj25jAmRrtEUWRgYACFQiG1AZOYEV599VUCgQDz589n2bJlM22OhMS4/P73v0cURa6++mry8/Nn2hyJyxFBNk2pxVK2wHQhObISlzTD0dh77rkn4WG/uqmZ5WvWcHjPbpatXYcpxUB3e9sowafmuhpyC4s5vGc3i1auwpGXT3tLM9la1bSo8QYjUcabRaHWogqPnVLq7u5kydzi+OvO7m7aunuRCbBgTsklowDoDoRQjFOK6gpcnCbp4XCYtsEQKcaRH5FwJIpSGYvDunt7CYWCZBUUJRz3QUUz6/1+CnPGVo0eZtm8UhaXFvN/X38fXfHC+HaDycxnf/kTAOtvuhPZGVHejuYGXJEAx6pqWFRawt6jpzjZ6WFIpkaMRrApoizLz6CsKH8qly8hMSmG0zQfe+yxWV22ICEhiuKY2VkSEtOGpFo865AcWYlLlsHBQV599VVgdNrbQCBEfe1hHLl5HNm3l4A/QEZ2Ls11NYSCISLRCD7vIEazCbPNxsCAh6baWorKynA2ulm/4YZpsVFxjnRRhQzyHRlUOp0JwkAAwUAAiwyMRiNDQ0N8dOgYfpUBg8WCKIpU7T5MkdXIyoXzxph99nCuZtUXq5t1U0sLWutZPXrP+Cfy9ntGObEAWms6+2paJuTIAsjlch7Zuol39x1jQGlAYzTjdvZQdXg/AKULFtPR3ACAGI1iSk1DZ0xhf5eHivrt9Kdko7RlM+z7B4GdTS6iYgPzis+uvZWQmH6qq6vZs2cPMpmMBx98cKbNkZAYlz179lBTU4Ner5dKyyQkriAkR1bikuVPf/oTXq+XwsLCUeqEVTU1aK029BYb8+xZ9LtdOLu6GPJ6saTZQASDMYV0RxZNtTXI5DLUWi0Dnn5yMzOnLfqQbjTQFwigSiKSEvD7sZtSKMrLRRSbqOloJShXoFCpiQz04zAbWbEiJjb1wf5y1I48hqtpBUHAlJlN66AXdVU1i0qTp03PFsxqJYPj7ddMLrJcVVdPb/8gMkFgbkHOhJWUjQYDoe4ulCrVyMbTXnRfTzeWtERl4/bGhlh9tVxGNBLlxXe3c/2qxaSlnlucyqDXc881a2nr7KK1q5eX33uFaDTCwkWLmbf+GpTqJLF6pZrWkJLUJNkAapOFg41tkiMrcVEYjm5t2bKFzMxLq5RB4spjOHvgrrvuwmAYW3dCQmIqCIIMYRrSgqdjDokY0jspccmSrHcsQHtnF+kFJRTNXRB3IFPMFgpKy1CoVZgsVhx5+WQ4smhvbsRgNOIbHMSWYcfZ3YVFO33KnPNK5xDs7iAUDCZsDwWDRJxdlBbH0oaL8/PYunYl184rYXV2OrdsWM2KhfMBqG9qJpqSOmpuAI3eQH23a9rsHY9zCbONx8LCfLzdHUn3ebvaWVQysTZHfW43f9yxm+MDUfq0Vno1Ft450cCOA4cndHx6WhqqYKJLnWIy43H24h8aTKhpba6pwubIwlFQhD23AEdBEW6Fnt+9t5OmltYJnQ8gy57B6sXz+fiD9wDYtOVzyZ1YoK+rg9SssUXGvDIdPb29Ez63hMT5EIlE4mrwksiTxGzH5/PxyiuvANL9KiFxpSFFZCUuSZqbm+PqhI888kjCvsOV1aTnjk4PBZgzfyG7P/oAszUVo9mMSq1BrlBgSDEx0O+hr72VedddNa22XrN2NcdOVdDr9MX7yKYbdCxYPbrnq8FgGLWa3NHnQWsYOwI4EIoSiUTGVdY9X0RRZN/R43QODOGPiMgEkVSthsXF+ZNqmWM2m1hbmM2+mgYEoxWtwYDP60Xwulg3p4AU48R6uX54+CRaR37CNmNqGs6AnwPHT00ozXpRTiYH253oTrcwMlmtdLa2EAz48Dh7MaXa6He5MNnSUZyune3tbCfo82FzZGGzO/jLiSYKmju4Yc2yCb3v5eXlHDt2DJVKxabrtuAbY1w4PH6tsFytYcjnP+f5JCSmwvbt22ltbcVsNnPrrbfOtDkSEuPy5ptv0t/fT15eHps2bZppcyQuZ6Qa2VmH5MhKXJI899xzY6oT+qKgT3KMKIq0NzejTzEDAvWVVZTMnctQOIwYjdJSV0tupv2CiJosmjf3vI89lzWiKE6LzdFolGOVVXgDIeSCQIEjg+O1DQi2TEwpNs5M3t1VUcvGeSVYLZYJz5+VaefOTDuNLS24+j1Y01LIW1o64eMra+qQWTOS7lOpNTR29rByAvMU5+ciyARONrfj9IUQBQGrSsaCHBvHmjsg1YbX4473ge3r6kCt0WKzj6hP27Lz6BdF3vxkH3duXnfOcw5nD9x2220sKs7jk84h1NpEJWJXdxdBvw+vuw+DeYxFgv5ecrLWTOAqJSTOn+E0zfvvv39aRO8kJC4kw/frI488IvWOlbjAyJieZFbpPp0uJEdW4pLjTHXCZGlE/V4vYmcHAZ8PQRCIilE0Wj0eVx85hcVknu4PWxqNUnX0CESjGM0mBlxu/OaJRQYvJoVZGexq7EZvttDb2YlvaAhBJsRSfaMiqWphyj/end09fHaqGnN2HnKtnDDwwdEKzKmpGBWjvyZMmdkcq2vg6hUTd2SHyc/JIf88bOwZGEStS55iDTAYYcKR6aLcHIpycxBFkWg0Gj9mXkk/b+8/hniGPJV/aAhrxkiNoLOrE//QEDKZQCQS5l9eeIOCNBMbFs/HnpE+6lyhUIgXXngBiKXBzynM51DdZ4S1ufExAb+fgN9HwbzFtNZWJXVkw+EQxVat9KAmcUHp7+/nT3+KqWtL6q8Ss522tja2bdsGjM7OkpCQuPyRHFmJS44z1QnvuuuuhH01DY30uVzY84tIs484H71dnag0Wrra2giHQxhSTNgyMpi7dDnHDuyls62NjVu34uzqpLG1jfzs5D1PZwJ7ejr66nram9wYTBasGfaE/c6GGvoHBiacnns2oiiyt7KW1LzEOlVBJsc4VmQQ6PNdnJY5w5zTfROjk3byBEFIcHzNphQeuGYtr76zjWgkAoKATDGyv7utFY1OjzV95N8gFAxQVVVB/Y79lNmMWCxWZALMzc/BajHz7rvv0tPTQ0ZGBlu2bAHgzo0reG9vOV0hOdrUDLqa68kuiaVFp2fn0VpbhSU943T2ALi7OygxClyzfsXYly+KhEIhVGcKWUlITJI//OEP+Hw+ysrKWLVqdPmDhMRs4vnnnycajbJ+/XqKi4vPfYCExBQQBGFaMuCkdmbTh+TISlxyDKcR3X333Qn1pKIosv3QERauXI1ao004pt/TT09XFyqlAoVSxYBngOa6WormzqOwdC4HPtmOIAjY7JnUtLXPKkcW4KolC/jj3qMYTOZR+1ILSth3sprr1yyf0Fzdp8WCPjxYjkwmo7+3G+ucBaPGneuLNnLOpjrTS1l+Du9XNGFMTUu6P02nmpYfB7lczn033cBzH+5BnZETnzMajRIKBklzxFrwhIJBulqaUKo15MyZy4Crjyq3B6tSxGS1Unu8EbsiFL9fH3roIRSno9tqtZrbNq1mwOulobkVmVnHcDdhlUZDTkkp7t4eOpsb8HpcEAqSXVrIe3uPsLQoB3v6yHvQ3tXD7opGWvoDiDIFBnmUEpueq1csmvJ7IXHlMZaInoTEbONc2VkSEtOOVCM765AcWYlLijPVCc9Oe6uorkFrsY1yYlvq6+nr7SW/uITU09HMflcfvV2dVB0/yooNG7FYbfHx7kAw1nJlFqVwnqxrJC0nH4+rD6/bjXC6P200EsVgMuH3DPDhvkOExCgqmZx0ow6ZTIY3EEQhCMwtKkCn01FZU0t13wAAuvRMBLmc3qEA8iTpw1ExOu77oJdPz/vjcrs5Vd9MSBTRyGUsmlOETqcbNS7VaiFDUY8nGECpSlSWHuztYkPRxHq8TgSZTMb1i+fwQXkl4VAEgK7WZuw5sbR0URRpra8lr3REXMqakYk1I5Oe9lZkchlGq42m7i7efvttIHmaptFgYNG8MjoG/HSetc9sS6Pf5SSnuAy1VocX8AJvHG9jhb2PFfNL6epx8tbRRpQWOylnFIbXhMP079zP59Yvm7b3ROLyp66ujk8//RRBEHj44Ydn2hwJiXE5cOAAFRUVaLVa7rnnnpk2R0JCYgaQHFmJS4o33nhjTHXCQDiMLMkqV3NDPcs3bEKhHOlVmmKxkmKxEolEOH5gH+mOM/okymRTajVzIQhGRfq6uxBFkayCxBRgV28P7oF+yubOQS+T4XL2Ut7SQW5hEQqTkTDwu7feQ6mUozIYyS+eg7uzeWSCMa41K6+Alvo68opLRu3zDw2RYzVP+boOnjhF/UCAFFusttQPvH34JIvsqcwtHt2S59rVy9l39ASNnd34RBliNEyaRsWGomyyM+2jxk8FR0Yaj95g482PduLu94AoIjudhtzd1kJWYfI0NktaBg2nyimat4B9294hHA6zbNkyFi5cSDAYpNfpJNVqRX1Gb+GyrDQa691oDCnxbZ3NjWTmF6FQJPbY1ZhT2d/ejU5RxYnWPpSW0Q68XKGgdUhHR1f3dLwVElcIw9Gt66+/nqys2ZWVIiFxNsP365133olpgr3EJSSmhCCL/U3HPBLTguTISlxSnJn2dnaksN/tJhwOJ2yLRqNYbGm0Nzchk8VSQqKRKNa0NAwpJtLsDirLD7F87dr4MXq57IK0spkKOqWMAY8bhUJJW2MDYlQkPSsblVqFxZZGX08XMpmMcDiMx+WisLQMgL6eXlqa6sksLMQ3NIQjN2+U42pOtdHX0401LVGoSC6XY7am0lhxkpyS0njUtt/ZQ4ZCYOGCqaWu1jY20RIU4k7sMKYMByd6ukmz9GFLHV2ju3rxAlYDwWAQhUJxwSLnJ6tq6fB40aeYwNNDv2+QAY8Lo8lCJByJt+YZJhjw09XajEKpIrOwjN6ePj74w/MA3HLLLfz5s4N0+qIo9CmET7aQrpGxceEczKYU8rKzyGpooyukic8rRqOjnFhnRzsBvw+ZTMYfDvUgCHKyUkiKJsVMVavkyEpMjGg0KvWOlbhk8Pv9vPTSS4AkSiYhcSUjObISlwznUidU6PT01DaQU1QSr+1qqquN1RwWJvaV7e5oJ+D3k5qegchIPahvcJBsyxiewQziHfCCIMOeV4AgxBSLO1uaUMgVZGRnk1NYTHtLC8GAP36t/W43gWAAsyUVW3oGLY0NyGQyxEgkYW6jKQVnbRc6gwHNWS1hhJCfm1YvpbOnF+9gELlMxrLSAkwpU3+P6rqcaMdop2O0pXOqsZmNSRzZYS6UqNHQ0BBvfnYI0ZqJShdLOQ8pUkiNtjLQ0womy6jyFlEUaWuoI3fOSKpxb3srrXXVyBUKdHllDBrtxPW49AbcPh//8dZHzMnLwtXXi0lvINR6DLdCR0SuIhxKXJTpammMqRkLMvy+IZQaPdFI4pizcQ94kaSfJCbCzp07aWpqIiUlhdtvv32mzZGQGJe3334bl8tFdnY211xzzUybI3GFIIk9zT4kR1bikuG5554jGo2yYcMGioqKRu1v7+wkv6iIEwf2smDlGgRBwO/zUTx/dOQwPdNBc23N6ShkNOYYNjeh8Q+yaMt1F+FqJo6zz0WzXyCnaCTFVxAEMnPz8fQ5cfX2YrHZ8DhjjubwF6SrtxdzWhqqM+pJI5FIUvXf/OISKg4dxGFPxx+J9aVN1apYX1qIzWol3WZLctTUGAyGGF0Je8b+cHTazzkRPjx4HGVmQcI2pUoNWUXIWqsJdjQQDoUS+vd2NjeSVTgn4ZhP//xHAJZedR0yS2Lac193F4GAH0teMdU93Wj0qTS2taO32MjIyQego7E+Pj7o9yOTK/C6XWiNJsynVZM7m+rGvI5IOExNZx/zT685VNc30tLbD0BZTgZZmckXESSuTIazXe677z60Wu05RktIzCzD9+vDDz886zKoJC5jpNTiWYfkyEpcEkxEnTAqV+Dq7kan17P3w/dJsVgxpo7u6zmMPTeXYwf2Ybea8bQ3YxQibL3h2vOyr7KmlnZ3P8GoiAKw6tUsnT9/WlbdjtU1Ys6M1av1u1wxFVtAazBisaXR1lCHTC7DYjHT73aPHCiTEfD70eljys5ZuXm0NNSTk19w9ikAmJOTyeZVY7d3mW4U5xCLUszAimWfy40LNfox9of0qXxuXg4NrW18XHGc3LmxRRJRFBMEs8KhELvfeR2Aq269G+GMH61wKITfN0R6dh5t9TWkWFIJBPyIgizuxA7POews93V1YEnPxNPXG2/JAyBXKAn4hlBrRy8JdDbVkTNnEXQe48UP9+LVpaPSxPr+njrZjf1UPXdtXj2rRM0kZgav18sf/xhbeJHSiiVmOx0dHbz33nuAlFYsIXGlIz3BSFwS7N+/n8rKyjHVCYeGhmhqbqFk7nwUCiUbbriRDEcWqfaxBYBUKjVCyM/SZUtJUcpZu2jBeTmeuw4epjMqQ5vhwJSZhT4ziyG9hfd37ZmyaFSP00l1exfRaJSGqlOAiCO/EEd+IUqlksbqCiKRCD6XE7M1FY1Wy9DgYPx4qy2Nvp5YnaRMJkNvNNLT2ZFwDlEUcTXVs3rBPC4maVr1mO9PKBjEYTIk3XchaenoRG8dO/qss6TS2tXFysULefy61UR7mgkMDQKJ982JvZ/gcfZgtKSyaN3mhP3dbS1k5OTT1dKEI7+IwQEPzVWV5JbOT5jDnptPS/Wp2Ht02plNzUwUdkrLysXV3YGre0TzOBQM0F5fjSUtIy7xHzLnoNKMOLsao5k+nYPXPvpssm+RxGXIa6+9xuDgIMXFxaw9Qy9AQmI28sILLxCJRFizZg2lpaUzbY7ElcRw+53p+JOYFiRHVuKS4Ex1wpSz6jNFUeSlN95CZ7ZSceoUMqWK9pZmTFYrbqdzzDmDgQAl9jTsGhVXr1qJxWyetF2NLS0EtMZRETG5XI4hO48jJ09Oes4z2VdRhVqnp7W+lvw5c0mxjNSMGkxm8ufMxd3TRVpqTLExPdNBe1Mj0Wg0prIrkxGJhOMiWLb0DDT6mK1tTQ00nDqO3tvHTetXJ215cyFZPr+MobamUduj0ShiTxvz5lz85vZ6rYaA3zfm/mDAj16jASDdlsqD163jKoeOVNGbMG44rXjd1ttPq2WfmSZ9usbmtBMvl8uRKRWjWgrJ5HJySsrobKrH3dNJJBJKapM9rwitwUj9icN0NFTT39tNVmEJBpOZAVffmNcik8modoVpbG6hqqYO15nRfIkriuFex4899phUuyUxq5F6x0rMKIIwkl48pT/pe3a6kFKLJWY9Z6oTnv3DJYoi73yym5wV6xPqZIIBP23NTfR7PKRnOpLP29vJXTdcN6UHt5YeJzpb8qivXC7HORg477mramsxZjhw1jeg0mjGtDOnqJg8nYr+3k5CEZGCNCsDjXWIPj9dba3kFhbTUF2F2ZqKNS2NFKMJF2CUwzWb1qPXj5VIe2FRqVTcvG4F+46fomsoQCga6yNr12tYu2n9jDxQFxfks79hL2jG6Enr7qVk+ZqETUV5OTjSbbzwaTmatGy8HjeHd8REya665W787j4UkeAZR4in/ysSDoeQK1XI5Qr8vqFRYlsyuRxHQRFKlYqulibScgpGKRkDaHR6QqEQWmQEg2HaGxsRiBIJ+skbJ7CdmpXPv7+3j4IFK/DXN5CmCHL1gkIcGWnnfrMkLgsaGxvZsWMHgiAkFdGTkJhNHDlyhBMnTqBWq7nvvvtm2hwJCYkZRnJkJWY9b731Fm63m5ycHDZv3pywr/zkKZSZuaPEHlRqDbbMLMKRMK0NdWQXJIpDdbW2sMRunbKzFD5dEzvmfs4/tdgz5EdtsaFSKbBm5o45zpKeSTTs4aplS0btq6qto6qtmay8PILBIDWnTiAEfVgFuHHdGpTK0U7RxUStVrNxxdIZteFslufb2d/uRGtOTdju8/SxIi95zbVWq+XGRYV8dKyWz7ZtIxwKklNSRrrZSIY4gFOjorW2CuRy/IODuHu60Gh1hEMhgn4fOqORnpZGcuYkT+/2uvvQ6g201lSQP3e0eFlrXRW5cxahPkukp/bIHjCoR40fJuAbJC2nCJlcjs5sYxB483AD961VYj2PDAWJS4/hljvXXHMNOTk5M2yNhMT4DGcP3H777Zil7yiJi4ykWjz7kBxZiVnPeOqEnV4fqjRL0uMUSiVuVx+29AzaG+tGUjlEkdS0NAb8waTHTQalbPwvI9UUlOnkQiwhVa3REAr6Uao0ScdFo1HkYwj2lBYXUVpcRG19A95IlCXLFpKWmso777xz3nZd7pQW5qNWtXOssZ0+XwhRAJtWxYq8TPKzk0f3AbLtGTxqz+Cnf/s1AO6+/VbK0ozUB1WoUw2ceWTtkb3klC6MtVBSqfB7+8nIK6K9vhrHGerHoijSWluFTCZHrVXRWVdNMyI5ZYviP4Tuni4MRtMoJxagcP4y6Bs7vb2/rxd7XuIij8Kayb6KBraunV0LDBLTjyiKcUdWEs2RmO0EAgFefPFFQEorlpghZELsbzrmkZgWJEdWYlbT0dHB+++/DyR/0ApFxVF9MkVRpLGmGrlKzYJV64lGInS2NKNWKsjOy4+P8zs7mSqFDjsnuvownlG7OkzA78c+BcGi0oJ8PqmowZGdw4mKGjJyC5OOG+xqY8GmVePOVVw4olQcCiWvtZQYIT/bMa7TOhYVFRUcP3YUhULB1//b/8fH9U70ttH3RvHSNXjrjlFgs7D/8FFCIniOHKBkyXIqD+4mxWpDplASCQcJ+rykaeRsnF/IoruuIRgMsu94FX2+MDIBtPQzaCtJYg1xJWXf0AAagzlhX7+zB40ueVp5u2fqizwSs59du3ZRV1eHwWDgzjvvnGlzJCTG5Z133sHpdJKZmcn1118/0+ZISEjMAiRHVmJWM6xOuHbtWubMmTN6QGj0A3dDTRWOguJ49FauUJBVUMiQ10tbcxNZuXkAeM4Qt4lGoxyrqKTPFyAqxmo15+RkkZ42fq2gw26n09mH0+3CYB6JDPsGB5EN9DF/1crzuOoYBoOBNLUC7+AgFr2GAZcLoyUx+uwfHGBOWorUQmWWMJw9sHXrVtpdXvRj1E8DOAfDuML9zN+4BblCQTgUpO7EEaLBIP29XShkMqxaOY/duBGHfaTnaywdeyS9+L19RxlMdoIz6G+px60zIZPJEUWRIa8Ha4YDc1qifdFIhM6mBsRomH95/TM0coGiVA3XLJ+HRpM8I0Di0mU4TfOee+6ZsVp5CYmJMny/Sr1jJWYMqY/srENyZCVmLaIoxn+4xkp7G/C4kaf60JxOqxwcGEBnNCX9kdMZDLh7u+PH6ZWx2z8cDvP+7r0Ys/NRG0aOO9jcQVH/AKVFySOhwyybP4+2jg4aOjpjfWQFyLVaKJ57/k7sMCsXLaSipha3f5DWlloElQYEORqdjkyLkbIMKwtLy6Z8HompE4lEeO6554DY/RqKijDGs1a/qw+lxYbNMVKTqFCqKF26mp62ZmTOVubMmYNKzjmrrC0aBU1D0XEXMx64djkfHGtENDuQKxR0NtWTYk1cpBFFkeaaSrKK5yXU7zQBz207wIbSLOq63YRFAatWztrFc2e8xlri/BkaGuIPf/gDIKVpSsx+uru74yUxUhq8hITEMJIjKzFrOXz4MCdPnkSj0SRVJxRFEZk+hZ62FqwZmeiNRvqcPdhzC5LMFsNkS6O9uYnQ4ACrS/IB2Hf0OKbcwlHF9yZbGpWtLeRlOc4ZjcrKzCQrM3NC19XS3k5deydD4QgCYFApmJOTTcYY0d9gJMqQykDZ6qvi2wb6esnSyVlYmjylVOLi8+GHH9Le3o7VauXmm2+moq6BNl84nt57Js6uTrJK5iadJy0rl85QCJc21s+2sbqbvPoWtqxbkXT8yoVzOfyX3cjS80btC4ViqtnZ9gyeyM6ivKKavsFBCnNTqOxpRnXGMd0tTTgKy5KKUISseTy35yQ5JQsAaA+IlL+7n1uXFZKfPbH7XmJ28ac//YmBgQEKCgrYsGHDTJsjITEuL774IuFwmJUrVzJv3sXteS4hEWe6esBKYk/ThhTblpi1nEudsLKmFrlaTVFpKWH/IC211XS3tY47p4BAS20lYtBHaXGsT2mfPzimglxqVjYnqmundB1nUlPfQFWvG509C1t2LqnZuajTHRxt6aS5rW3U+M6ubk71+TCelaJqtNpojSipaWicNtskpsbw/frAAw+gVqtZPLeUYE/y+zEqRpNuj3NGdFVrNNMmmNhXfpyOzk58Pt9ZQ2XctLyYUHdTrH/wafz9LrJFd/y1IAgsnVdKttWIyy8iQ6Sz+gQtNacQRZFIJIJsjHQ9QRBQqXUJr5W2XN4+XJdwTolLh+E0+EcffVQqTZCY9Zx5v0pIzBjDjux0/ElMC1JEVmJWEgwG4+qEY/1wtbsHCAViEac0eyZp9kyCfh993V1Y0zOSHtPX2UpRSSkmIRJ3XkPRsZM3BUEgGIlM5VLiiKJITVc3tpz8UfvM6elUt7WSm5WVsP1kUyt6S/KWL2q9gdrOLkoKRs8ncXFxu928/vrrwEiapiAIbFlSwnvltWjtufH7zT84gBCaeH/hYCBAT3sLTrkc44CCiK8FuwY2zi8iLTUmJJXrsPOVjDQOHK+kbyiIQi6wYJGDNKslQaF6+4FjHO9XotKlI6ghzRarD++vLSdVN74wWbLFHpklmwPHK7GmGGjq8SAgMjfPjiMj+T0rMTtoaWnho48+ApB6x0rMeo4ePUp5eTkqlYr7779/ps2RkJCYRUzIkf3FL34x6Ykff/xxjEbjpI+TkAD485//TF9fHw6HY0x1wmA0SjQaRRTF+EO2PTuHhrpaLGnpox68h7xeUvR6QqEA8+eXxrcrziGDrpRPT7SiqrYOsz1rzP1yo4m29g6yHCOpmoOh8aNdg+HpcbIlpsarr75KIBBg/vz5LFu2LL49y57Bo9elcvB4Ja5AGAVQlJVKgyyHsXIHRFGE01FOURRpb6wj98z+snoDXuCtwzXctWouZlMKAHK5nDVL5ifMdaKyBoA/7zkKgUGaohY0KYkOq0wmY0hjpbX2FIoeD1p9CpkFJaM+P2KSyGsoFOSj4/VoM4tRac0AHC3vJEdRz93XrJZ65c1SnnvuOURRZNOmTRQUjF2KISExGxjOdrn11luxWkerwEtIXCwEZAjTINQkSAmx08aEHNlvfvObZGdnT1glrqWlhZtvvllyZCXOmwMHDgDw0EMPjXnfeVwuPINDHNm/D4VSRdA/RH5RCXmFhRzb/QkZufnYc/KIRqM0VJ4kRa+hZE4p1Qf347CPpOpaNWc38Bmhr6OdaxZOj5hSMBRCoR37M6E3GvEMuMlixJFVygXGa5ajlByFWcHwg9Zjjz02ynlTKBSsWbogYVtGWiq/fm83lvxSzqatrpqsglhv166WJrIKk6h1A4pUB/sr6rhhzeh+r9FolFc+3I1bnYoD6FPZaOv0kp5zlur10BCNlUcxpzkoXn9jLAMh4Keh8ihpjjyMpth4r8eFRj86Ytvb3kxm4eKEbWqjhc6oiXd3H+Zz65cntV1i5jhTRE8SeZKY7YRCIV544QVASiuWmAVINbKzjgmnFh88eJD09Imli0kOrMRU+fGPf8yXvvQltKfViM+mqraOXq+PrOJS9IbY/ebu66Oq4gREI2RmZ9Pb3kpvWzNKlQp7uo2CklKqjx/ljuuvSZhrxfy5bNt/CEtuQYITMuhxkW82TFtbivRUKyd7XBjNlqT7XV1dzJ2TGB3JsRip8gdQqtSjxouiiN1w5bVEEUWRfeUnaB0YIhgWUSkEMg1a1i5ZMCO1ftXV1ezZswe5XM6DDz44oWP0Oh2PXrOSV7bvwyvXYbCk0u/sIeAbxJ5bFBeIiopiUrGoYdq9yfu9bttXjteUi+rMWtwkq8jNlcfIKp6HzmiKbxOjIjqDmeaq4+SVLSI06CEiCtgcuQnH9rucGFOTC5TJZDKONbsorqklLzcHtXr0/SsxM+zZs4eamhp0Oh133333TJsjITEu7777Lj09PWRkZHDjjTfOtDkSEhKzjAk5st/97ncxGMavnzqTv//7v5fSPySmTFFRUdLtoiiy/chxihYuQy6X09vVydDgICkWK/NWrKKtsYFAKMLStesRBAGvx0Nj9SlU4TA3r1s9aqFFo9Fw49pVlJ+qxOUPEAW0chlzMzPIyRo7FXiy2DMyONHQDGM4sppoaJRt8+eUULfjMyJpOQmRaVEUCXY0suLqddNm36WAKIq8tWM3YnoO6nQrw+6RUxT50/Zd3Ll5w0V3ZodFSLZs2ULmBJWrASxmE//fHTfg8/moqasjrbiE8vpWOhUj9p8rNVcco7y7vs+PMk1I6N0jnDXY3dOFzmSJO7GiKNLRUINGZyAtO5+07Hw8Xa04FH6G5KMXc7x93diLEpWXnR2tDPa78Xn7sWXl8ZdWiFaWU5Ai56Y1CyWHdhYwfL/efffdk/pdl5CYCYbv14ceegjFOIt6EhIXBSkiO+uYsCM7Gb797W+flzESEhOhuq4eVYol5sR2dyHI5WQXjji9BaVziUQi1FZWUDJ3HgaTifkr1iBzdmA2mZLOqVQqWbl44QW3feW8UnYdPYElJy/+oxwMBOjvaGXz8tEpooIgcOvV69l39AStfUMEwiIquYDdqGHtprVXXFP445XVRFIdKM+6bkEQUGYWcOjEKVYuWjDG0dNPJBLh97//PXD+aZparZZFC2I2Z2ZmcvBEBTXdTgaCUaIDTiB/zGND/U52HzmJQatiYWlxLDU4GGRIlHP2nW60WOnv64n3jw34fciVI2n1nU11pOcUJkSATRnZeEWRVG8TJrGXJneAcETEopWxIFVOz+n6dK/bhcfZQ2pmDpaMbERRpLetCU9vNzZHDu3Ac9v28cWbrpLqZmcQn8/Hyy+/DEhpxRKzn97eXt5++21ASiuWkJBIzoSXt3w+H9u2bWPz5s2jokb9/f3s2LGDLVu2SCvuEhccn9+PcNqRGfJ6E5zYYeRyOSm2dNx9fZitVgRBoNsfJhQKoVQqJ33Ojq4uWrt7kCFQkO3AakkeVT0XppQUPrdhLScqKvEEggiAzaBn/fq1Yz7gC4LAmiUX3sm+FGhze1Fa7En3yWQyOgZ8SfddKLZv305raytms5lbbrllWuZcsWAuwx1jfT4fz31SjjotO2GMx9mLu6ebtJwSToU0hH0h9ry7m81zcyjJz0EeHV1ZbTCZ6WppxOuWYzBbQRRjwlJAJBxGLleMSmOOhEP0tDXTEQqQE5aTrlexvDiTgpwsgsEgv3z/MEJKGgPuPjILRmp5BUEgLTufQY8Ld08X5rQMBvQOjlXWsHhu8ppfiQvPm2++SX9/P3l5eWzatGmmzZGQGJeXXnqJUCjE0qVLWbhQ+g2UmAUIsqRlOuc1j8S0MOF38j/+4z/413/916T1rykpKfziF7/gP//zP6fVOAmJZAwO+YiEwrG+l4qxI5Jmayoejyv+2pKRSXPr+H1mzyYQCPDBZ3s51tVHMCUVf4qVvfUtbN+3P+4ETBZBEFg4by4bli5m/dLFlJUUS1GqCRIcp1USQPgitzQdFs25//770Wimv15Zq9XyucWFRHuaCQX8AAwODDDo8eAonodSHTunQqFEbsvlw5peunqd5JqSLyhm5OQTcLWT5u/AoRMJeD1ALCXYlpWXMDYYCNDRUEt6TiGZRfMIm3PoUGbw+ikXB05UoVKpWJ5lpKuxhvScwqTn05ss+Ie8AChVaup7B6flfZE4P4bv10ceeUTqHSsx6xlOK5ayByRmDVIf2VnHhH/JXnjhBb75zW+Ouf+b3/xm/EtHQuJC0dbRiVuhwevpA1FEdo5VLYGRL4uhgQFMKSlJx0XG6BX7yaFy9Nl5GEzm+DaTLQ15moM9R45O/gIkpoRBOX4qte4c+6eT/v5+/vSnPwEXNu0t257B41vWsy5VRqHgRuduIS03ef24ypzG4ZpmNi0sJuJsG7U/ONjPNfPyuGvzKr58yyaW55joaW1CkMmIRsIJY/s6WsgqnjtqkUWpN7Gzzs3Q0BBXLZtPdopq3IWYM1sVRKLRMT9rEheWtrY2tm3bBki9YyVmPydOnODQoUMolUqpd6yEhMSYTDi1uKamhsWLF4+5f9GiRdTU1EyLURJXFtFolKMVlfhDERQyGXML88YUIalta8frCxMMBKk5cRR5EjXfYYa83oQomTI4hC01Nf46EAhw+MQp3KEQoiBDiEYwqVUsKStFp9PR6+wjpNElnVsul9PjCxAOhyUBiotIWU4mnzb1oDePFpPzewcoy0hNctSF4Q9/+AM+n4+ysjJWrVp1wc83b07MeW3zBPCOM657MITRoCdHJ1LZcAKbDjxt9TjMepbk2ykrGom83rtlE2999BkHmvvoGBogu3ikD+14vfLUqQ72nqjhmlWLsadaGO0yn4EoMtjvxuPsoVcmcOq1vZg1Mual67h29SIpG+Ei8fzzzxONRtmwYQPFxcUzbY6ExLgMB0Zuuukm0tKSq6NLSFx0JLGnWceEI7LhcJienp4x9/f09BAOh8fcn4xPPvmEW265BYfDgSAIvPHGGwn7h3synvm3Zs2acef83e9+N+oYQRDw+/2Tsk3i4tDc1s4bu/bj0pgImGwM6M1sO17FoROnko6vbmoljIwl666ibMlytDo9gwMDScf2drSSnukAoL+3m/m5IwrE0WiU7fsPosnMwp6bT2ZOLva8ArT2LD4tP0YgEKClswNTqm1M262ObOobGs//4ifIcLuZP+zYy3Mf7eGVHfv45FD5FRnZysq0M8eoYMCZ+F006HKSowhTUpA3xpHTz/CD1qOPPnpRnbFzfWn3OXv5ny+9y5GeEH5lbEHIlFXAQCBEZtroBYBbr13PvevnIxt0MeTtH9lxjmtyegZ5f085rT1uOhpr6WysJRQc3Q7I5/My4PGQnluCObuYFHsuUXM2x3wm/vDRvnNer8TUEUVRStOUuGQIh8M899xzgCTyJDG7EATZtP1JTA8TDiXNnz+fDz/8kOXLkze437ZtG/Pnz0+6bywGBwdZvHgxjz/+OHfddVfSMTfeeCO//e1v469VKlXScWeSkpJCVVVVwrYLUb8mMTV8Ph9v7tyFzpxK59EjFJbNRaPVYbE76BoYoKa+gZLCkb6qR05WkFESGwMQDoWIRqJ0NDWATIZarcFgMiOXyWhtqEGvN1BXWYFOiLJp6UKy7CMiQccrKkkrSJ6emZZXwMnqGuQyGeJpVdZkBPx+NBehj+vbO/cQtDhQpJkZjlP3iiJ//Hg3d1+z7opTLl42fy75Ljcn6psIRKKo5AKrS7JJt4296DDd1NXV8emnnyKTyXj44Ycv2nkBMo0qPOHk92VnUwPalEwyT/d3FaIR6D5KT3sLaTkFvH/wFPdeszrhmPrmNnY0DpC7dAM9bc14+3owpzsQo2MvlPS7ehnwhdFrUiE9lQxizlJXUy2W9Ey0+tid2tvehCCCzTF6gUEml9PgN9LU2o7NYqKuqZUUo578nOxRYyWmxoEDB6ioqECr1XLPPffMtDkSEuPy/vvv09XVhc1m46abbpppcyQkJGYxE3Zkv/CFL/Dkk08yf/58br755oR9b7/9Nj/4wQ/42c9+NqmTb926la1bt447Rq1WY7cnVykdC0EQJn2MxMXl1KlT/N13/oF3//JntDo9ucXF6PQGlq5Zx+abb8OenUNDV3uCI9vc14/WHnvIDfj9tDU1kltSmvBA7+zqpK7yBGs2baa9pYkBVx/Z2Y4EJxagPxDAMIbYiSAIeAIh1i9ewLsHy0l1JH+wDrmd5M69sCmlJ6tr8aWkozorfTnWbiafg8crWL3k4rWbmS1YLWY2LjfP2PmHo1vXXXcdWdPYa3girFk0l8oP9kFaonPY19WB0WJBZzTHnMrmBgRE0tQQCoapP3kMizkFZ5+LVOuI6vbB2naUxtjnIy0rF1EUcfd04RvwjLmQM9DTSWZJ4n0nCAL2/BLaak5gtVjRhTysSNNzkrF7lar1Kbz08WHk5gyUZjuhFi+m4/vYWJpJWVHuVN4miTMYFnm68847SRlDJ0BCYrYw/P364IMPnleXAQmJC4aUWjzrmLAj+8QTT/DJJ59w6623UlZWRmlpzIGoqKigurqae++9lyeeeGLaDdyxYwfp6emYzWY2bdrED3/4Q9LT08c9xuv1kpeXRyQSYcmSJXz/+99n6dLRPTolZo5vfOMbeP0Bfvrcq+iNRo7u30P1iePs2vY+J48c4p4vfoW87EQHoT8YQnv6/ztaW8ibUzZq3tQMO6FggPqqSnKLimiprqJXP7rO9Vx6w1FivWUz9Rr6h4bQ6BLn8LpdFKRd+HrMZqcHVUpG0n2CINA2MHTBbZBIJBqNTrl37FRQKpV8fuMSPjh0irYhUJlSCQy4iPb3oEtfBEBbbRUZ+UUoZDLoOUpGbiGiTE5PayOnauq4avWK+Hyd3hAq7cj8giBgSbeTYrXRWncKe0EZsjOi/r0Np7BmjywwnY011cbja/PIOP09XfGn3eNez4DCRJo55kgrtXqG0PPnyl5USgWFuY5Jvz8Sifj9/njvWClNU2K243K5ePPNNwHpfpWYhQhMkyM79SkkYkxKpeb555/n1ltv5cUXX6S6uhpRFCktLeV73/se995777Qbt3XrVu655x7y8vJoaGjg6aef5pprruHQoUNj9qstKyvjd7/7HQsXLqS/v59//dd/Zf369Rw9epSSkpKkxwQCAQKBQPx1f3+sTiwUChEKje7HeLkxfI0X61q7u7s5ePAg/+d3/w/HgliqeuGcUoa8Xg7t/pQ//vbX/OjJ/853fvTPhFaNLECEgyHE03WhMkEW//+zSc/Mou5kOdFImJK5ZUTCYfr7+9FqR57WFTBKpfVMlIiEQiGWzC3jZHUNba09RJUaomIEVSRMQXoqRXm5F/w9C4YiME6KZzgSnbQNF/vf+3Jjx44dNDU1kZKSwk033TQj76NGo+bW9Uvx+Xx0dHWTPq+Itw6ECUUj9Pf1Yk5LRyGLCZgBdDfXg0yOKIrsPtXMwrIS9KcXZ2RE4+PORCETyC2aQ7TtONY0O6GoiFktozDHSJ1MA2Ly+1JrttHd44z3WrZpYGCMsdFoNHb+M/YP9XsY6h/gjx8386VbN2I0jh3RlUgk2Wf79ddfx+VykZ2dzVVXXSV97i8jLsfv8hdeeIFgMMjChQtZsGDBZXVtU+Fy+be+1O2XmH0I4vk2w5xmBEHg9ddf5/bbbx9zTEdHB3l5ebz88svceeedE5o3Go2ybNkyNm7cyC9+8YukY5555hm+973vjdr+4osvotMlV62VOH+am5v5yU9+wl133cXmzZuJRCIIgpDQ1/DJJ59k3bp13H333TNoqYTEaP71X/+V7du3c/311/O1r31tps2RkBiX73//+xw6dIi77rrrotdzS0hMlr/927+lpqaGL3zhC9x6660zbY7ENDM0NMQDDzyAx+O5pMoc+vv7MZlMPHnLa6iV+inPFwgN8rO377rk3ofZyCXVNyQzM5O8vLxJtfmRyWSsXLly3GO+/e1v8+STT8Zf9/f3k5OTww033HBF3GChUIht27Zx/fXXX7R6lP3793PkyBHmrVxF0coNyGQyIpEIMpkMQRBYvmEjjfW1fO5znwNifV7/+b9+T8HcBWQ4smlpbMSRl590blEU6aivobutiQ3XXo9cLiPQ08VVSxcljGtoaaG2o5v0nBwEQUAURXra28i1mJhTWHih34IJ0dXdw0e1HTh7e8gqKEZxxr+Pq7eLTPzcsGHtpOaciX/vywWv18uDDz4IwHe+8x3WrVs3wxaNcPBEJccHdfR0tJKWlUd/nxO5XEZhsJku6wJEWaIoWGdzHcVmJesWFPKXE50oU0aLZSldzTx0w5pRdbK/fmcfYUvy2nGLv4PPb16RsG3nwZOUdwdRmmPpxpFwCG9bLUpzJrrTPZo762tIyyseda5oJExv7THWzs3hhtULrzhxs8lw9me7s7OT8vJyAL73ve8xZ86cmTVQYlq53L7LKyoqqKmpQaFQ8L3vfY+MjORlNVcil8u/9XDGo4TEdDFhR3bv3r188YtfxO/388Mf/pDPf/7zF9KupDidTlpaWsjMzJzwMaIoUl5ezsKFC8cco1ark6YqK5XKS/oLY7JczOv95je/ycMPP8y3v/HfufXOu7jqptvQWazIRBGtGKK9vpa1a9bE7fn0cDmFZfMwmlJob27E3ddLVmFy1eHGylP4vW42XL+FxppqsnLzkMtko65tTmEhhbm5nKyqJhQVkQsi1y5bMiFl7ItFdpYD1ZHj5MyZlxCxBrCkO+jp7iAQCIzZd3c8rrT7ezp46623GBwcpLi4mI0bN86qHqhrliyg/v1ddEajRAUZg4Ne7Nl50NuMKJOPcmQFuZI+bSaDQwFW2dXsrK5BactGozPgd3eTpQ5z87Urk34erl+cx19O9SAYE/s7Cp52blgzZ9R9dd3aJawaGOBgZSOhiIgtVY3CUcwHrSAKcnzeAdQpFpApRtWvCwo5gjGNqpCN7g8O8MVbNsyq9302MvzZfuWVV4hEIqxdu3bSXQUkLh0ul+/yF198EYiVlWVnS+rlybjU/60vZdsBEGSxv+mYR2JamLAj+9WvfjUumrRw4ULuuOOOMetUJ4rX66W2tjb+uqGhgfLycqxWK1arlWeeeYa77rqLzMxMGhsb+fu//3tsNht33HFH/JhHHnmErKwsfvzjHwOxVec1a9ZQUlJCf38/v/jFLygvL+f//J//MyVbJaaX5cuXc+rUKX7yk5/wy1/+khf+3+9Ys2YNeXl57Nq1i7S0NB559DF2HirHFwxS396FiEBEFImIAkazheMH92G2pJJdWBR/sHV2ddLX04kYDiGXyykqm0tjTTVz7cmFmRQKBYvnz7uYlz559OZRTuwwxvRMjlTXc9WyRUn3S0wvw+qvwz2uZxOCIPDAlg3s2F/Op7WVCMpztIYSBJRqDe8eOo7G5sCcX4aruxNXeyNZRgU3X70hoa78TEryc3jAoGNfRRMd3hAyQSDHpGLd1fMxjrGokmI0cs3KxAXFvTWf4lPnM+DqxZY1joBUZi6uzhbENAflp2pYOl+KLJ6LM3vHSqI5ErOdSCQi9Y6VmP1IqsWzjgk7sn19fWRnZ5ORkUEgEGBoaGjKjuzBgwfZvHlz/PVweu+jjz7Kr371K44fP87vf/973G43mZmZbN68mVdeeQWj0Rg/prm5OeEh3+1288QTT9DZ2YnJZGLp0qV88sknrFp1YdukSEyOSCSCXC7nqaee4pFHHuHgwYO8+eabeL1evvWtb2HMyKTKDwZTLOJTkOqgfM9n5JQtRH66FU326XmO7duD7XQKktliZfWmazmw8+P4ubRaHUU5ORf9GqcLfyTKeDFifzh60Wy5kmlsbGTHjh0IgjBraw0FQWDz6qUU5XTyX+/sgqyxW9hET4ul+ZQGzKbYQo8l3Y4lPaYg/OZn5Xz+urHT1tNtqdxy1dSUu+/fvJQ3d5+gfWhg3J7NkXAQmUJJNBrlnQNVfFLrwh8WMWsEFmWlsHbJ3CnZcTly+PBhTpw4gVqt5r777ptpcyQkxuXDDz+kvb0dq9U6qsWjhISExFhM2JH9zne+w0MPPYTFYuGxxx7DYrGc+6BzcPXVVzOe1tT7779/zjl27NiR8PrnP/85P//5z6dqmsQF5sw6N7vdzs033xz/8TpyqoKWqAqVeiSi1NHSzNxlq+JO7JnzzFu+CmdHC9n5I3Wt2QVFDA0OotPrSc/Kor2zC5PJdIGv6sKgkiU+3J/9wK9RSCkqF4PhljvXXHMNubmzu8dprsPOU/dv5VfvHsCeJJMrFPCPfJbG+A7uFnV0dvdgT09Lun86SDEaeHjLGhpbWnnus3r09uRRWVdnG6Z0Bz1tTdjzlxIEZEA/sK3Zw8ETb7Bl7RLmFOVfMFsvNYajsbfffjtms3lmjZGQOAfD2S7333//lIMkEhIXDJkQ+5uOeSSmhQk7sl/+8pe58cYb6e/vl2ptJKaVYccsGAyiUqlocQ2gSk/sIRsJRVCOUbsqVyjo9/TTUl+HTC4jK6+AzNw8elrqySsswut2UZZjvxiXckFwGNU4RZHOliYi4QgyuQzEmCK3ggjXXrV8pk287DkzTXMmeseeD3q9ns8tzqPm1LGE7YP9bjy9XTgKS+nrbMOcOrovt29wELfLzVufdrKyLJ8l8+Zc0FTq/Jxs1uQ7Oezxo1QnpkT7vB4UKjWurnbs+SO9o6ORCF3Ntai1ejSZK/hDtR/D8T1sLE1n6dzk9fNXCoFAIF5vKKVpSsx23G43b7zxBnDpfL9KXKFIqcWzjkmpFudcwumZEjPL4OAgen1yyfLhB+RXXnkFi8WCR53C2TGgqBihraEehNh4MSqi1euxpsdSinUGI9kFhYSCQeorT5GZk4uzu5vMrBzkfh+21KmlQM4k6xfP53+/8jaZ8xahUifWLLramxn0+zFzaUabLxV27dpFfX09BoMhoUZ/tlOSn03NqWPIO0/RPCig0OjRGlLILJjDYGcjkVAErSFx0ai9sQ6FRkdqdiEh4FNniNd//x5LHQZuu3b9mPXaU+X6NYtRHzrJ7to2osYMopEwXpcThUqN1Z5NZ3NDwvjOxmrsBWXx7w+lSkNAlcO7NW4EoZbFpUWzro75YvHOO+/gdDpxOBxcf/31M22OhMS4vPrqq/j9fubNm8fy5dLCrISExMSZ0BPJZOWyBwYGzssYicuXL37xi3z00Udj7ne5XDzzzDM88sgjaDWJaUXBQJABtwdHfgFZ+YU48grIKihEpVbT0dwYG3Q6PVKpUuHIy+f4gX0sWb2WmpPHWFBwaS/AeAeHSM0rjDuxrt4e2hsb6GhqYMgfYm9F/QxbePkznPZ2zz33jLkgM5t59NbrefK29azPNzPfAgvUHv77TavJNiUujHS3t2C02TGnjSjDyxVKMkoWcKgrwHPvfjpuOchU2bh8Pv/j3k0sVPUScLaRnluE1Z5NNBpFiITi4wb6ejHZ7KMc1Z6WBvqcTl7a38k/vbyb5z84SFtnzwWzd7YyLJrz0EMPoVBcUl32JK5Azsx2uVIXnyQuEYZVi6fjbxJ88skn3HLLLTgcDgRBiGcwDCOKIs888wwOhwOtVsvVV1/NyZMnE8Z85StfoaioCK1WS1paGrfddhuVlZUJY1wuFw8//DAmkwmTycTDDz+M2+0+n3fqojGhXziLxUJHRwfp6aNT0JKRlZVFeXk5hbOkF6fEzPLWW2/x6quvcvDgQX76059y2223AYm1nhaLhbq6Ok6ePInTH2TojONj9bEr6OloJ+j3A6BQqsjIzsY3NISzsx31Gc6vWqMl9XRd35xFS+nqdZI5xX50LrebY7UN9PmCiIBBpaAww0Zxft6U5p0IFY0tGKxpDA4M0FBxkhSrFblCSTQSxWi10tTTTX1LG4U5WeeeTGLSDA4O8uqrrwKXdtqb2ZTCtasS1a1XFaazvcmF2hjTPAgFgpi1yR31jLxi6lsb2Hf0FGuWTH95iSiKHK2opavfh9Fk5ptL53G8vh1fWMSskXPCb8B9eqx/aGCUynFnQxWpWQUolCMlCG3AC7sbeWi9gCNjdJ/cyxG32817770HSGnFErOf6upqdu/ejUwm46GHHpppcyQkZiWDg4MsXryYxx9/nLvuumvU/p/85Cf87Gc/43e/+x1z5szhBz/4Addffz1VVVVxgdzly5fz4IMPkpubS19fH8888ww33HADDQ0Ncd2aBx54gNbW1vhvyBNPPMHDDz/M22+/PSE733rrrUlf2/XXXz9mh4SJMCFHVhRF/vM//3PCvSpDodC5B0lcMTzzzDN84QtfIBAI8KUvfYlIJMKdd96ZsPI6rGI8f/58BoeGeHvPQcy5sTq3SDhCXeUpZDI5SpUKQ4oZjU5LfVUFjtx8ThzYQ25hEc31dWh0WtLtDnT62L0ql8txDvqnZH+P08lnVfWY7FmYz9he5fYwWFHJ4rllYx06LURE6He58PQ5mbdyTcI+Z2cHBouVHacayc3MkKIvF4DXX38dr9dLYWEhV1111Uybk4Df76eiLpZyOyc/d9LR4vklBcjlTRyob6d7SCQ6TrRVJpcjyOTUO32sGXPU+dHe1csfd1cxqLWjUFkB2L2znjXZWraujbXskcur+Kjdh0I1+gdv0ONCb7YlOLHDiCmZvLK9nPVzs1hUWoBGc462RJc4n3zyCeFwmJUrVzJv3ixvLSZxxTMcjd2yZQuZmZnnGC0hMcPMUI3s1q1b2bp1a9J9oijy7LPP8p3vfIc777wTiH2uMjIyePHFF/nKV74CxJzSYfLz8/nBD37A4sWLaWxspKioiIqKCt577z327t3L6tWrAfj1r3/N2rVrqaqqorS09Jx23n777ZO6LkEQqKmpmVLgc0JPvbm5ufz617+e8KR2u/3Sb3osMS1UVVVx/Phxdu/ejUaj4Utf+hJPPfUUwWCQz3/+8/FxZ6oY63U6Mo06jhw5gEZnoKutjcy8Quw5uTFhJ1cfnS3N2LPz6GxtISs/Ju4EMOB20dXelpD+ONVEyPKaBkz20dFOXYqJ2vZWygKBC6qymGrQcqC5iZyi0V8iqfZM2hpqceQXcehEJauXLLhgdlypDD9oPfLIIzOa9haNRjlaWUUwLJJmNtLc1UuTN4w+LZZie/xgBZkquG7N8knZWVaYR1lhHqFQiH97Z/+4Y0VRJBCZ3nZP0WiUl3ZVErXkJ/wgKc2Z7Ov1Yq2oY8ncIlYtKqXDdYATngBqrR6ftx+tIQWAoX43tuyx+9C2+9Vs7zHwUe1xFmco+NyGpdN6DbOJjz+OtR6TorESs51oNBpPg7+Us10kriBmodhTQ0MDnZ2d3HDDDfFtarWaTZs2sXv37rgjeyaDg4P89re/paCgIK5/tGfPHkwmU9yJBVizZg0mk4ndu3dPyJEF6OzsnHAG75ntVM+XCTmyjY2NUz6RxJXJM888w2233RaPgnz3u99lYGCAL3/5y/h8Ph5//HEgSUsZtQaLxYrP56d44WLMqSPyTykWKykWK03VlaRYU2moOAaiiCCAI6+A3q4ulPIR91U3hfY0oVAIVygySnxqGEtmFieqa1i+8MI5kNYUY8L1n43NnkVfVyeppvG6zUqcDy0tLfHa7kceeWTG7DhWVUN5ay/a9Cxkchk1HQP0dDixpo/UieptdlyRCNv2HOSGdSsnfQ6lUkmeRUPHGPuH+t3oDEYUkUHe+ewwTZ4gkahIqlbB0vx0yorOL81+79EKwqbcpIINCo2Bgw3tLDmtQnzbppUsbeukvL6DA5V1YDjtkJ7rmeC0SJxgTOfDqjqqm9/lqkWFLJt/YdWYLzZHjx6lsbERlUrF/fffP9PmSEiMy/bt22lpacFsNnPrrbfOtDkSEhedszWI1Gr1pAMjnZ2dAGScVUKXkZFBU1NTwrZf/vKXPPXUUwwODlJWVsa2bdtQne4IMpYDmp6eHj/HuXj00UcnlSb80EMPkZKSMuHxyZAaUEpcMERR5PXXX+ev/uqv4ttycnJ45ZVX+NrXvsb3vvc9nn/+eYBRD5MWgw5Lmg2Xyz2mE+fILyAY8JPuyCK7oBB7di71Fadw5OUhE6GloR5XRxvzi88/ZcHn86FUj/2hFASBcPTCid8A9PS5MJqtCdvCoRC+QS+iKKLWagkG/Cjll88D+WzhueeeQxRFNm3aREHB2BG/C0ldcwvH+wLo7TlxxWCtwUhuSRmu3m4ikUh8rFwupyMIQ0NDY003LhvmFxDobh61PRIO4+7pRIiG6fFFaRDSiJqzEKzZ9GntvFs/wN6jFed1zs7+4LhKyN2DkYTXuVl2br1qKf/wyA1kRdoI9vcgyGREwmOXtIjRKK6uNnramrFll+CzLeTdZhXf+/1H7Dty4rzsno0MR7duuukmrFbrOUZLSMwswyJ6n//85y/7lH+Jy4ThiOx0/BF7Jh4WVjKZTPz4xz+egmmJz4BnB4gAHnzwQY4cOcLOnTspKSnh3nvvxe/3jznHWPOMxW9/+9tJRVl/9atfYbNNTb9CKqiTuGD4fD4+/PBDNmzYEN8WjUaRyWT89V//NR0dHTzxxBO0tbXx1FNPASMfopLCAnb84Q0MJgvtjTFVXlEEfUoK5tTYTa9UqQkFg2g0OiDWTza3uISeznZUGg1Gk4l0MYRpCqs9BoOBaMA35v5gIECm7vyL1CeCIyOdQydb0FtS8fT14fW4UCiUqDQa+rq7CQwNolarmJeffUHtuNIQRTH+oDWTaW+nWrvRmJKLlWUVFNPV0kRm3oiTbUjLpKqhiaXz5076XOmpVh5cX8YrOw7RG1IiV6mIhELIAJvNhqy/E0XO6OwDld7E7qY2Fs/xTVq0QSETIDLe/uTb1Wo1D96wGqfLTU1TO9uO1SB3jK4JDQV8+Ie8qPVmbLaREgG5Qok8s4w/lDdwoG47n79mCTarZVK2zyZCoRAvvfQSMLPZAxISE6G/v5/XXnsNkNLgJS4lpim1+HQaUUtLS0JE8nzK1Ox2OxCLqJ5ZZ97d3T0qSjvsMJeUlLBmzRosFguvv/46999/P3a7na6urlHz9/T0jJpnNiFFZCUuGDqdjvXr1xONjtTUDUdeMjIy+H//7//x1FNP8Zvf/IZgMBh3Yitq6vjTrv1Y84oJBoOkZ+WQmVeAI78AQSajoepUvAZ20OPGfkZ/Y6VKxWB/P+mZmZisqQSmeA0ymQybRjFmy5Gh7g5Ki4umeJbxsaVaMRNgwO0i6PfhyC8iPTsXsy0dR34heaXzUAQGSEuVIjDTyZ49e6ipqUGv1ydVCbxYuHzBMffJZLJRabWiKJ471XYcMtJS+cY9N/DV6xawwq5hsSOF1fkmPr8si6B67EUhtS2Lg6dqJ32++bk2goNjt3grtI7/w55qMbNmyTy+vHU5Gk8j4eDIp77f2YWrqw211oDBnLyXdGpWAcea+/jpSx8RCEz1G2PmePfdd+np6cFsNrNly5aZNkdCYlz++Mc/4vP5KC0tTajJk5C4kkhJSUn4Ox9HtqCgALvdzrZt2+LbgsEgO3fuZN26deMeK4pi/Hdv7dq1eDwe9u8f0crYt28fHo/nnPNArHVPX18fEHN+X3vtNU6cuPAZT5IjK3FBEQQh7rye6dAOp0N+5Stf4X/9r/8V//A2trZR4/GhsaTR0txEycLFyM9Q4k0xW8gpLKG1oQ7f4CByhWxUyoMggEYbi9IGx4n0TJRFJUVUHz6A3zeSrimKIp31NawpK74oNXZXLyqlr7UBW+Zo0SmZXI4xp4Sm1vYLbseVxLDI01133TUtggTni+wMrzTg99PWUE97UwNtDfUMDgyMUjPzdrUzr2jqrc/s6WnctGE5d21axta1S0m1mAmPk8Tj7uniWH0b2w8cp6fXOeHzFOVlk6dwJXw/DCP0d7BxYf7E7E1L5Rt3rudz+RHmqrrprjmMSqMjI68Y4Rw9+1Is6RiLV/HDV/ewff+lmWo8fL9u3LhRUi+XmPUMZ7s8+uijl1WdusRlzjSnFk8Ur9dLeXk55eXlQEzgqby8nObmZgRB4Jvf/CY/+tGPeP311zlx4gSPPfYYOp2OBx54AID6+np+/OMfc+jQIZqbm9mzZw/33nsvWq2Wz33ucwDMnTuXG2+8kS9/+cvs3buXvXv38uUvf5mbb775nEJP//mf/8mKFStYvnw5v/rVr7jjjjv46KOP+PznP89//Md/TP59ngTSr53EBaG5uZnXX3+d3bt3c/vtt3P//fcn1MENqxRnZmZyyy23xLfXtHWhtaZz8LNdlCxZkXTuYce2pa6K+UuXjdp/ZgsShWxq9auiKPLJ0ZPMW7marrZWnF2dCIKAGI2SkmIiFA5Paf6JYjGbsFjHriPQGk3UdfSQl+24KPZc7vh8Pl5++WVg5tU0bXoVg0B3ayu9na2YbSMpPv0uJ/2uvnhqcSgYoMA0ebGIiaBSqdDJRq8MBfx+elsbMadnItrmczIIh/e3UKCt446rV07oIfXBG9fx3u5yTnb5GYgoUYghCixKrllbQLpt4pkGgiCwdN4clgJKucCR/piIxbm+BURi0W2dvZjPugZRH61k3eIL21ZrOunt7Y33+bvmmmtm2BoJifGpr6/n008/RRAEKQ1eQmICHDx4kM2bN8dfP/nkk0BsIeh3v/sdTz31FD6fj69+9au4XC5Wr17NBx98EF+E12g0fPrppzz77LO4XC4yMjLYuHEju3fvThB4euGFF/jGN74RV0C+9dZb+bd/+7dz2ve///f/5uTJkwwNDZGbm0tDQwNpaWn09/ezcePGhNY/0815ObKffvop//f//l/q6ur44x//SFZWFs899xwFBQUJ9ZASVyYul4vHHnuM1tZW5s6dy9e//nX27dvHs88+O2rscM3sML3eITzdp1AolajUY4s/KBQK8kvmjNo+4HZhMsXSH32DgxRNMd32RGUVxqxcADKyRmpQ/b4hujs62H6wjc+pVaRNsVh9IgzHqzxOJ95+N8IZkW69MYVUg5RgMV28+eab9Pf3k5eXx6ZNm2bUlmXFeby8cx9DIZHSpasSPi8dzQ2kWG30tLehlUUpsOjYuGLJBbOlJFVN/VnCD862JhxFiU6f2pRKSzjMB3vL2bL23K1uBEFg6/ql3CiK+Hw+1Gp1Qkuu82Hr+qXI9hylvK0LxLFTM6KRSEImdigc4U+76/jwVB+BsEiqTs5Ch47r1iyctZGjl156iVAoxJIlS8jPz59pcyQkxmU4e+D6668nK2t0lpGExKxlhtrvXH311WOWuMWmE3jmmWd45plnku53OBy888475zyP1WqNi7BOBrlcjkajQaPRUFxcTFpaTKQ1JSXlgv9uTvrJ97XXXmPLli1otVqOHDkSz60eGBjgRz/60bQbKHHp8aMf/QiFQsGHH37Ia6+9xr/+67/y8ssvs3PnToD4h9Hn8yU8lH+8dz9DwSDhYDieGjwWwYCfltpaPH2u+La+ni4CAx5s6RkE/D40g26KC/KndC0un39Uml5DTQ3d3U4ycgtxzF/KroZO3v1s3wWvrzOr5Ti7OglHwmTmF2HPLcCeW4Ajv4hoNMpQv/uCnv9KYjjt7ZFHHhlXUfdikG5LRQwFKV6weJQtKrUWZ1c7/a313LFyPhuXLb6gtmxZs4SU/ibCgZjKYX+fkxRbchEIuUJBRbcvacrwWAiCgE6nm7ITG7d37WK+dcdq7l5oItJdk3RMV2MVqVn5APi8Awy4nFgKliK35KJLy8Onz2ZPXwovfzB+j92Z5MxexxISs5loNMrvf/97QBJ5krgEkcmm7+8yQqFQxNWPh5/1IeYbXmgm/U7+4Ac/4N///d/59a9/jVKpjG9ft24dhw8fnlbjJC5N3njjDb7yla+Qm5uLQqHgoYceYsuWLfzXf/0XEHtY/eCDD1i/fn38mPJTFYRMaXj6+jCnpZFiMuHsGqujZawdSOniJYQjYSqPHuHkoYN4WxowKGW4G2pxEGLTquSpyVOhpb4emyM7ITprsFhRZOTw0YEj036+MymzWxgc8GBJizkO4VCIjsZ6OpoaAPAI059OeqXQ1tnFX3Yf5rfb9vDTF9+KiybMhgctr9eLJtWesM03OEhTTRUavYG5y9eSv+IqXjtUzScHj15QW+RyOY9svYprHTKyIr2o+tvQp5jHHB81ptHc2nZBbToXcrmctSuX8t9uWkaqr4G+tga8bifOtga6m2tIyx2pc+93dpPqGN1mSS5XUDVooLFl7O+kmeLEiRMcOnQIhULB5z//+Zk2R0JiXD755BMaGxtJSUnhjjvumGlzJCQkpoGPP/44XtJkMpni230+X/zZ/0IxaUe2qqqKjRs3jtqekpKC2+2eDpskLmFOnjyJ2WyOy4kPR1+feOIJduzYQUNDzOn6+c9/zoIFI208OjxeVGo1yAScXZ10d3bQVFNJfeUpImfVoXa3tZKRGasFtdrSKF20FIPBQFpGBiFBQVhnpKbHxf6jUxdtsRn0hILB+LWEotF4yvOZ/TsBAhojXT09Uz7nWBh1WmyZMQe6s7mBnrbmeO1fwOejzdnPofLjF+z8lyv1za1sq2rHa0hHl5HDof17iUajzFm0FN80iIVNlZb2DiwZibXPXW0t5BSXotUb4tv0NjvNUR0HT5xfP9fJsKC0iNuvWsq6ufnjjgsHfBj042dXXCxSLSaeuO0qvrwpD42nHoVaRUZeCcrTzeBjjJ0CpdSZONrQfeENnSTD0dibb755yv34JCQuNMPZLsNCMxISlxQzJPY02zEYDAkpxJ2dnQCkp6ezbNloLZvpZNKObGZmJrW1o1ss7Nq1i8LCqStlSlzaOBwObr755lHb161bR3Z2Nr/5zW9wuVx88MEHCano/kgUZ3cXSrUWhdZA4cLlLFm/mbw5c2mtr+P4/j0011TR3liH0ajHZE2sfc2dU4YnFCUtKxtregbm7Dw8GiM7Dxya0vXMLSlmsLMVAHdfHyq1lua6Wlob6uhua6W5rpbGmioikQgGs4Wmjm5a2zvYXX6cz44cp6G5ZUrnPxPPgBeNTk9PeyvBQAAEGRk5edhz89EZU5DJ5ew8Ofn2J1c6+2pb0Vpi9RyiKLLzrT8AcPUd93OoqXvcupSLgT09DW9fb/x1T0c7Gdl5SceqtFqqu9wXyTJYOreIYN/YUcpUwYctNXnbm5liTmEuT3/5DgrVA6PTns/xcBGMzOy9cDbhcJjnnnsOmHlRMgmJc+H1evnjH/8ISPerxCWKwDQ5sjN9IReWYbGoi8GkxZ6+8pWv8Fd/9Vf85je/QRAE2tvb2bNnD9/61rf4x3/8xwtho8QlhMVi4W/+5m8wGGKRIvG0MIwgCDz00EO8/PLLdHZ2snz5crKzR9Jz5QJ0dveg0pvIyBl5SBcEgZySUly93bi62ikqG1s4Rjzrm0GpUuFGicvtxmI2n9f1CILAdSuWsvvYSfr63ARFGQVzEoVtRFGkvuIUBWVzOVnXQGtYhs4Yc7SP9g1yrGE3N6xaOuXV51xHJofKG3B2tZNdNAe9cSR9w2i2YDRbaKw6wYmqWhaUFk/pXFcKre3tBLUmhmXF6k6U095Qi0qjYc0NN6NQazhVXcv80pIZs9FiNmORhRkODocCAdTj3EsDkVi2wHTVmY6HRqNhSYaGowNDhMIR+p09CIIMERGlGOaeVbN3cfPLd17LmzsPcbI7gszsIBoJIwS9Y44XRZHgQB8vbjvMQDCKUS1jWX4qZcXJFxUuBu+//z5dXV3YbDa2bt06Y3ZISEyE1157jcHBQYqLiyfUl1JCQuLS5GIGACbtyD711FN4PB42b96M3+9n48aNqNVqvvWtb/H1r3/9QtgocYkx7MRCrKVFNBpFFEW++MUv8uyzz7Jr1y4+/vjjhGOUQT+hcITcMR4KLbZ0ettbz3lut9OJt9+DKIqYbTZMtjRqmltZdZ6OLIBOp+O6NSv5cPc+omnZo/YLgkBOcTFHd+9i0fqrEtIrNHo96PW8+sFHlOUXIJfB/OLC83JqrRYzVlmQDpU67sSGQ0G6WlviCsYyQcHBU9WSIztBXO5+NPqRHrHD0dhV12xFZ4ht9wV9M2LbmayfV8T7x+rQpk+gvVJUvKgCVdesWkTnX7ZTM6QmLWfEcQ14+6lt62FecT4Q+2HbU36Kyi4vgyERrUKgxKZl44rpVwPucbrYXt5AndNPKAJpejnL882sWjTSC08QBG6/egVbAwEqahvRKBUMZBXyTsMQCvXodGhvWxVVlkzUKhPIoTcM1ccGWNF+mJs3XtjUqbEYTit+8MEHUalUhEKhGbFDQmIiDN+vUu9YiUuWGVItvtS4mJ/vSTmykUiEXbt28Td/8zd85zvf4dSpU0SjUebNm5fgvEhcmVRWVvKrX/0KlUqFwWBgwYIF3HjjjfG+rnK5nAcffJD333+fq6++OuHYAoedJn/nuPOrz1AyHhzw4urtRhAEFAolGdnZ9PV0YbFayMqPibU4u7voaW9nniNtWq7PG4Gxqv1EUcSWlTXqwzs4MEBPRzu27GL6tDHH6M2DJyhI0bJ68YJkU43L9SsWUNe3L2ZPvwePsxd7XmH8vKIo0lp5DKfLRarFMun5rzTyc7M5sL8Svc1OMOBn97tvAbDx1rsB8PW7cRRPz/0zFdJtqdyyXMmhqjo8YgB3bzdmW3rSsRk65UX9EXG5PbRFjZjtierFakMKNQEV+49XsmphGa9+uJc2RQZyfax+fhA4PBSl8d1dPLJ1w7TZ3N3bx+921hIxOsAMSsANvN84RJ/3KDeuS1R2VqvVLJk/4uD2Dhxlf/sgCmPs3z0aiRDurSWqMqDWmxKOVeqMHHIKFNY0MK9ktEjUhaSvr48333wTkNI0JWY/jY2NbN++XeodK3FpIzmys45JObJyuZwtW7ZQUVGB1WplxYrpV4WVuDT5r//6L37+858jk8nQarXodDrefvttfv3rX3PXXXdx7733YjKZ+B//43/wla98ZdTxRYWFvFteNe45ZHIZXa0tBAIBNHo9jvxY9CcY8FN59AhZOXmYLCO1s6npGZhTbXQ1JW+7MVnG0/3p7eqM2zOMKIp0t7eRf1YqsinDQfuglxNVNSyYZMqqQa9Hdvr7z9XTRVZhYi9dQRDImbuYj45Ucu81ayc195WI0WAgTRllCDi880MGBzxYMzJZsCqmqG0IeXHYJ7/gcCEwm1K4dlUstf7dz/bjCoVQnKEcD+Bz9bC6aHTWwIVk76kGVObkLXgUag0n29pRK2tolaWhUCTaK5PJ6NPlsLf8FGuXzp8Wez4qb4g5sWfbotGxv2OQ1W4PFrMpyZExtq5fzBq3h/0VzQTCImkGBVWyFNqEzKTjFVoD5Y3dzCspoKKmkQN1TlxDYbRKGWV2LRuWz7sgEfKWlhZKS0sRBIElS5ZM+/wSEtPJcMudzZs3k5ubO8PWSEhIXC5MOrV44cKF1NfXU1BwcVefJWY3//iP/8jf/M3f8M1vfhOZTEZVVVU8hfiXv/wlbrebv/3bv0Wj0WC320cdX9PYTDQSJpzk4XwYYcCNO+DDlpmN1+OhtTGmgCxGo+QUleLsaCHdISZEduRyORG1flpqBg3KsY9XqdQEfD40upGYbWdLSzw6fDYavYH67jYWlCbdPS42tQJPnxNTavKIHIBH0NHd20u6pGJ6Tq5bsZA3dx1m+xsvA3DVzXfGFKo7G9myetEMW5ecG9et5NPDx2joGiKs1BENBUlVw8bCLPKykjtcwzj7XJTXNtHnCyEIkK5TsWpBKRqNZtzjxsIbFGGcj5YnEKWi3YNCldzZlcnl1Dp9TNeyS01PAOUY+lJKYxoHK5u5fs3CceewmE1sWTsy5tCb+2Gc7lYDgSgf7j3BzlYZSm0GqMEDtHdGOfXmZzxx2/ppd2YXL17M0aNHcblc5x4sITGDiKIYd2Sl7AGJSxopIjshVAndAC4sk3Zkf/jDH/Ktb32L73//+yxfvjyeNjrMcNsViSuHkydPolarufPOO+MPa6WlpZSWlnLHHXfwm9/8hqeeeoqsrCzuv/9+yk9V0O4ZIhQVUStk2NRKjrR3kWJL4+SB3Sxcc9Wohz5vexMP33w9L7y/Hd/gIFkFRQn7O1ua0JkstDU3kZ2Xn7DPlJlFbX0DpSXnXzfa2d1DT28vGrmGFPPolF2VECXs7gHdSI1vJBJGqRr76bc/eH69Xa5aWMxLOw6SO39s4Sut2Up7t+TITgStVsvVC4t4aO8uAG7Zcj3zNH4WX79+1tZxCYLAxuWLuUoU8Xg8aDSaCTmi9c2t7KjtRGPNgNO/My2iSMMnh7h9zSJMKcbxJ0iCWgGMo+ugUcrwR4jl+CbB2dFKz6Cbn725F5VMoChVzcYlc9DrJt+2RxRFAhFxrFMB4A9Fx9mbHKNKhmec/b5+F9s8qejNiYtLMpmMTkUeH+07wfVrp39RRBAErGcpuEtIzDZ27dpFXV0dBoOBO++8c6bNkZCQuMAcPHjwop1r0o7sjTfeCMCtt96a8JA3rE57dm9NicuftLQ09Ho9P/3pT/nFL34BxOqpZTIZVquVb33rW5w8eZKdO3eis2ejsOcht5lQAwMeN7XNHVjtDvRGE1Z7Dk3VFQR9fjJycvENDSIOurn/2qtIMRrxI6c4Z7QglD0nj5a6GnTq0aGhYCCANmWccMo5cLk97K1tImveIlqbGhnyerFn58Sv09PezJqSAgKhICd6XegnWJsqjPf0Pw4F2Q7WFtipG/SiOd1HtK+nk6DPj4hIWmYW4YCf1AzpAXeiPP/880QiEdauXcsX77ltps2ZMIIgYJ6gkJkoiuw81YjGnvj5EQQBZXouO49WcutVKydtw8K8dCpPulHrRy9iiqJIkVWDNxhJ6gh2NdeTYs1AnRFLhw4BlSGo3XaEx69bguGshdJzIQgCNp0c/xj7I5EwGefxXbAgJ4XGej8K1ejFgnDQR0u3G1PJ3KTHymQyTnX4uH7SZ5WQuDwYFnm65557RgU/JCQuKaSI7Kxj0o7s9u3bL4QdEpcw6enpfOlLX+JnP/sZhYWFfPWrX0WtVo8as33nTm75q79HrojddpFIhO7OLnJKRmpI5QoFBWXzcTt7iASGyM3LYahHicVsoq2jM6E1j9fjxjc4iDU9A7lCgcWWRs3RA2g1GtIdWfFxIVcPufPXnPf1nahvwGSP1dxl5+Xj9w3R0VSPIAiIosiCdDP5ObHzKRQtVLS24/IFCXj76Xf1kWJJ7lCm6s4/9WLz+lW0friHIVGkr7sDa4YDS5odURTpaWtGGHCSc9Wl45DNJKIoJqhpXq6cqKpBnjp22nGHX8Tv9086xbggJ4u5DR1UBVQo1SPHiqKI1t3E1VvX0NrZTd3JPpR6c3z/UL8Hjc6IWjf6wTZszuWjQ1Xcdh5qwAsdOvb2hZArRsdlNd42Vi6afNuP5QvmUNu+j0q/DcUZWRbhkJ+cUBNHlGPX3MLp9GsJiSuQoaEhXn31VUBKK5a4DJAJxIVKpjrPFYDf7+fYsWN0d3eP6tt+6623Tss5Ju3Ibtq0aVpOLHF5MByJ//rXv87AwADf/e53+elPf8qXvvQlbr/9dmQyGYcPH+aVV17h7ke/GHdiAdqbGskqTC52ZE5No7OpDrlCgfL0573X5cJostDX3cXQoJcUswWzzUZ3eyvhUIisgiJs6RnojEZaG+rJLihk0OOmJGNqqrNuf5AzNbk1Wh25hSOpzW5nV/z/i3JzKMrNiffQenfXXqJR8+hUaWc36wpypmTX+tJcXvq0nNy5IymLgiCQnp2Hf8DCiZp6FpTM3j6es4XDhw9z4sQJ1Go1991330ybc8Ho9wVRjONwqQxmenqd5GTHFmXqmlro6POgEAQWzSlAN06q7y0bV5B5oooT7R24fRG0ShkFVjWbt65BqVRSkJPF6h43ezqcqFNiBaxeTx+2rLG1FuqcY8VVx+fa1QtxfniASq8e1WmV4Wg0iqK/mXs3lJx3uvh9N6zmwPEqTrS68AajGFUyFhWk4PU7KHf2jnusInp+1yIhcanz+uuvMzAwQEFBARs2bJhpcyQkJC4S7733Ho888gi9vaN/H6czg3fSjuwnn3wy7v6NGzeetzESlx7DD4VyuZx/+Id/4P777+e3v/0tzz//PD/4wQ/Iz88nEAjw0EMPseq6LQnHigjjP1QKMkRRJF0fi/Kkms3sOVrDgMdNitnCgNtNJBIhMzefaDRK7fGj5BfkYDCm4PV4cDbUsDA/h9KiqTlz0fMIpgxf19YNa/j00BHaBwLIDCmE/T5SZCKr87PIsicXv5ko/QMDOIpH0hkH+/vpdznjLYlORLySIzsBhqOxt99+e0KabkdXN0cbWun3h1HIBLJMWlYuvDAKtBcDg0ZJ2Du2mFrI6ybNlounf4A/7z/OkMaMRm8CEco/O8E8q4aNy8eu81yxoJQV4wg8X7VsPsXdPRyqbsUbEgkxOK69/vDka1kh9tm77/pVNLZ2cLyhm1BUJE2vYN31a6cs+LZyYSkrz9KJ2nXoJHqTlYG+LozW0Z/paCRCSeqkf2olJC4Lfve73wHwyCOPXLLfnRIScaTU4gnz9a9/nXvuuYd//Md/JCNjas+74zHpX9ez+39CYuNbqUb2yqGzszPmSGZmxn+gioqK+Kd/+ieefvppmpubqaqqYtmyZdjtdt7bd3hS84siDLY2cu2GVQAIMhn+oUFKFi6Jn2/A7aKh6hQFpfOw5+YhirH7z56dg37AOWUnFiBFNfbHRBTFcdWMBUFg44plRKNR+vr60Ov1aLXaKdsE0DXgQ6GKpWW21degNaSQlpVLV2szwUEvx1p7uWFpKdYJ1lBeiQSDQV588UUgMa34eHUt+9sH0JrTQANhoCYSpfbDz7jvmrUoFJeeY7KobA6HP9iNIiN564sMtYBGo+EPnxyEtDzOTDDW2zKp8Q9hOFXFsnnnIbV9msz0NG5Oj2VI7Dx4nENecczFLLNm5HMliiLdPT2oVaoJ1wTnZ2eSnz2+gvN0sGxuAR9Vn8QVCDDU70KXMlIjHw4F8TQc4Y5vTq/ATTQaRRDOsRAoITHDtLS08NFHHwGXd9mGxJWDKAiI0/C9Ox1zzHa6u7t58sknL6gTC+fhyJ4t9R8KhThy5AhPP/00P/zhD6fNMInZzwMPPEAoFOLxxx9n06ZNZGVlodFokMlkqNVqSkpKKCwsjEdBciwp1Af8qE7X0cnlAqFgkHAoiEqtSUg7BlAFvNx67bWoVCqi0Sg7T9biyC+io7kRmSAgiiBXKsguKKatoZ6sgkJ6W+pJTYsph0amqSytLDebg82dGFJHKwC721tYt3LJOeeQyWTYpllBWH76i7CzuZFURw6u7k6621qIhEIMeQcIRaL8y/Nv8Y9fvGfanOfLjT//+c84nU4yMzO54YYbAPD5fOxtcqJPS+xFKpPJENPy2HHwKNetWT4T5k4JQRDYWJbLzrpuNNZEdd1QdwtXr1lIRW09IWNGUtVflUbHyfY25EIVvV4/SpnAkjkFpBgnr3QMsG5xGQf+fBC5dXTf20g4zFx7LKF/+4ETlLcNMCg3IoZDpCkDbCi1s6Ak/7zOO93odDqWZyk46LIy5B2gt22kfl4I+3n4+sVTdjirqqoIBAIMDQ2xaNGicdO8JSRmC8899xyiKLJx40apZaOExBXG3XffzY4dOygqKjr34CkwaUfWZBpdY3X99dejVqv567/+aw4dOjQthknMbsrLy9m7dy+rV6/miSeewOFw8MADD3DHHXdQWloaj5p897vfJTMzk6997WssLJtD15799IfNqDQaAv4grfW1mFJtuJ1OIuEwJmsqRrOZ7pZGbt+wKt6L6mhFJT5BibuuBq3BSJTT9bmRMM211SjPEpeKRCLo1eM14Zg4mRnpzPX5ON7chD49E6VKhc/rJdLfx7rSovPuvzlViuw2Gpo8MeVkZy+CIMPd00l2cRlZRXMA6O9z8r1fv8KPvi6ldSVjOK344Ycfji+4HK6oHeXEDiMIAi39wYtm33RTlJdDikHH0dpmnL4wMgEyDCpWXrUUrVbLwap6lJrk4mQDLhc9XU6CxnQUypgjdWpvFXMtKjatmHxrGaVSyc2Lsnj7eBsKy4g4W9DnJV/u5uoVa3j3syMc9xqRm0wML8UMAn+pdCOKDSycc2EejvtcHrYdrqO6y08gLJJqULAsx8imlfOSjr9541K0+05woGEIb2oGYiRIumKIq8qyWDbv/H7EXW4P27Z/wh9ffpE3Xn8Ng8HA3LlzMRqNbN68mfvuu4/8/PwpXKWExIXjTBE9SeRJ4rJBSi2eMP/2b//GPffcw6effsrChQtRnlXW9I1vfGNazjNt+XFpaWlUVVVN13QSs5zPPvuMzZs388c//hG5XM4///M/88tf/pJnn32Wz33uczzyyCPY7XZ+/OMfs3Pnzvhx1hQD+/YeQFBqKFu2alSkor2xnu62RlI1KtJtqfHtfV4fna3N5JfOQ28cafPhG/QSDLTR73QSyMpGrY45vp72Fq7duHbarrc4P4+ivFw+2PkpHf4QMqUKvUZNY1sHNqtlRlJNC3KzSamsw61QEPT7GXD3Ubp0VcKYFGsqxnXX8H//8Gf+233ToxB3udDd3c0777wDJKa9+cLReI/VZAyFL+3yibTUVK5LTU26Tz6GkmI0GsXj6iV/bqLDqk3NoNo3iOLgYZbOK5t0pLCsKJcceyq7j9fi8kdRyWF+aSolBXMZ8Ho52h1GaR7dLkdhMPNZddsFcWRd7n5+va2CoCEbzKAGvMDH7UG6P9zPPdetSnrctasXcM0qkbb2TtQqJWlpE8/ACAQC+Hw+TCYTQz4fr358nDqPihd/8hNkcjlf/s4vuHZ5AW0N1Rw6dIg33niDPXv28OSTT06LLkV7ZzcnmjqJipBjNTB/jlRbLzE19u7dS3V1NTqdjrvvvnumzZGQkLjIvPjii7z//vtotVp27NiR8LwvCMLMObLHjh1LeC2KIh0dHfzP//k/Wbx48bQYJTH7Wb58OeFwGL/fj8Vi4emnn+bpp5/m7bff5p//+Z+5++670Wq1lJaWxpUK65tbqPeG0OiNOIrKkqbbOfILqTt2iEJHYurjiYpK8ucuwdPnxNPnBCAjOxet3oAtMxtXbw89rU2Uzi3D1dbC6pKCaa8f23WonHCqg4wzHta9osjbn+7hlqtmpm7y7ms38C+vb8fZ3kHu3ORKO4Ig0K80EggERrVFupJ54YUXCIfDrFy5knnzRiJtasX4941WcflGtstyMqk+2Y7WnBiV7Wppwp43OrLY1dJIOBThgMHIwU9OYlVEWJ6fwbziiTmYp2oaqGh3E46AVSdj/aKSuDNcXt2E0mwf89iesIa+vj6s1untl/zhodqYE3sWCqWK424dq9s6yc1KbpcgCGRnTbwut6Glg23lrdT3iUQVGox48fW7UGUtIRDppb3uGE/89B2smfkc9fby2G2LeOyxx/jwww/52c9+xsMPP8xf/vIXFiwYR2VrHERR5NUP99EY1KMyxGp7jzX42FX1GZ/ftAhTyvmljUtIDIs83XXXXRjPs/xAQmLWIUVkJ8w//MM/8E//9E/83d/93QXNCJz0k/eSJUvi9T9nsmbNGn7zm99Mm2ESs5s1a9awdOlS1Go10Wg01t5CoeCWW27hlltu4fjx4yxevJhvf/vb8WPqOnpApsLn96MZJ3IjV6lYMifxoTkoynH39pKZVxCrVRRFOpobUanU2DIdqLVa8kxaDIMuNqxeGk9Jni46OrvoE1QYzrJbEASMOYUcOH6StUsv/kKOXC6nwGqgqz2CyTo6AtTeUEu/y0kkFOalN9/loTtvvug2zlbG6h27vKyYis+OY0hzEI1G8brdqLVa1KfrjLONl+9igD09DXtFHa5IBNkZCr+CIIz6IeporMecZketPWNhZ2iQd0+2EY5GWTRn7JRaURR5/t3PaJOlo1TbQIBWHxx57xh3LMumJD8b8Rw17jKlGp8/cH4XOg41PQFIGb3d5+3H63Lym22dFGW2M9ehZ/mCOee9YNbc3s1zuzuI6jIZzuZ2dg6iT4v11R7sd2K0ZNBSeRBrZj6i2sKO4208ftMK7rjjDu644w6WLVvG22+/fd6O7LufHaFVbsc72EWwt5cBVy/RaASj2cZv3/mMb37+xvOaV+LKxufz8corrwBSWrHEZYYATIdPdvn7sQSDQe67774LXtY26dkbGhqor6+noaGBhoYGmpqaGBoaYvfu3ZSVlV0IGyVmKcPRPZlMFo9GDqtWNzQ0ALHaw2GGQmF6u7qwZowfsdBrtQkCMr3OPkxZeWQVFMU/EIIg4MgrQK5Q0O/qQ6PW8Lmr1rFq0YJpd2IBato6MJgtSfcJgkDP0MzVTa6fW0AkFE5oNj3gdnPqwB4EuZKSJauxF5TQpU7nh69s46PdB2fM1tnC0aNHOXr0KCqVivvvvz9hn06no8ykoPzTjzh1aB/IBPrdLtoaanFVH2PTsvNzGi4Vbtm4mpyoC39XC4P9bvp7OpENuRPGhIJBZHJF3Il19XTS0ViHb3AAfyDIC9v2sfPgsSSzx/hgz1E61Tko1YkiZHJLFm8eaiYSiVCUlUbQ604+AaANunBkjh2xPV+CSTLH3T0dBHyD2LKLkKWV0RBO5606Jf/xxq5RTd4nyvajLUR1iZknkUgYpSpWc5+eW0pWyWKOfPgyzrZ6ZHI5ze4IkUgkvpB800038cEHH5zX+aPRKJW9fvo6W/EPDiCTycifv4ySpetQqtXU9Qzy2YHy85pb4srmzTffxOPxkJubm7TThYSExOXPo48+Gl/QupBMOiK7c+dO7rvvvlEpisFgkJdffplHHnlk2oyTuPQYFszxeDx897vfTdgnCBCKRJHLojGhpjEiGbJwkJb2DnIcMYf3WH0T6dk5Scda0tJpra9FO7X2kOckdI5msqEkD7N9LjfH6hoZDEWRCWBP0bJkbvKU6qmQnZnBivwM2loaycwrJBIO01ZfQ1ZxGQGfj47GOkyp6ehNFsKhMJ9Ut7M6/dJrHzOdDKe93XrrrQmpqYFAgHf3ltMyJLJow7WEQ0F62lpQqtRk5hfj6+uip89NduaFlZOfSQRB4JpVS7n6dMsonU5HryuLd+tcaAyxUGVvRxvp2flAzImVyxUo1Rp8g4OY0zOxZefxWWMrJ2rf5qv33Tzqnq/sGkJmTl6nK5qz2Hu0kvXL5pOlqKMH86gx4VCQFQ4DgiDQ63RxuKYVfyhCmkHF6sVlU1oBtullnKnNHw4FCQf9pDoS06UVShWdYj7v7DrKzRuXTvo8NT0BFMnXxuKsuvkLvP7zv+K//setrNz6KCuvuha5XE40GqW/v59PP/2UlStXTvrcAF3d3QzJDQy46snIK0FrGAlD27Lysdpz+NOevayfgCq7hMSZSL1jJS5bpNTiCROJRPjJT37C+++/z6JFi0aJPf3sZz+blvNM+hvm8ccfx+PxjNo+MDDA448/Pi1GSVz6PPjggzz99NMJ2/zOXowWK47cfNoa6pIe1+92oTRZ2NPm4o0du/H5fAycDpFEIhHaGuppb2qgrbGBvp7u+HFL8qY/MnMmGvn4H5Wz91c3NPHeiToGDGlELRmEzRk0RXW89vEuwuHwtNv38J03E3R2MOTtp7u1GZ0xhYDPj0qjxZ5XhNZgRKFQkpFbQP7cK7uWPRQK8cILLwCj04rf+PQg3hQHFntMRVehVJGZX4RGb6CvuxOtNYNDtS0X3eaZYLhllE6nIzfLgT06QOT0vXtmD9PA0BChYBCVVo89L/ZeKZQqMvIKUeTN583te0bN7Q6MLZglk8lw+2LnuXfzUlJ9zQmR2ZCni/kaN9euXsS7nx3h/37aTPmghcqgjZ29Bn72+h4a2zrP+7qX55sIB3zx166uVqyZ+UnHCoLAqc7zS29OFsiVyWREQiPZHY7iRXzt/2xn/Z1f5eiO13j2r+9k48aNPProoyxZsoShoSH+7u/+7rzOr9fp6GtvQmswJTixcVvkcnQZBbS1d5zX/BJXJu3t7Wzbtg2QesdKXIYMO7LT8XeZc/z4cZYuXYpMJuPEiRMcOXIk/ldeXj5t55l0WGasSFpra2vS1jzj8cknn/Av//IvHDp0iI6ODl5//XVuv/32+P7HHnssXsc2zOrVq9m7d++487722ms8/fTT1NXVUVRUxA9/+EPuuOOOSdkmMTWSrcKabTZa2jrxDngREWmoOoVcocBsS8OYYqanvRVXdwcLV66OHZBiYtvBo8jkSpxOJwNuF1kFRfH7b7DfQ2NVBYpoiFVLrr6g1zO/KJ+PT9VhSh/tMIeCQRwmffx1OBzmQEMHKY7EKLJcoUDmKODTw8fYvGrZtNonCALfevBWfvfnjxkYCKLWGggGfEnTuIf79TY0NTGnuHha7bgUePfdd+np6SEjI4MbbxypAaxrasGrtaIGnF0dhAIxB0WhUmGzO+hoqgegxeNLNu1lz62bVvPJoWPU9gwSCQzR7+xBqdGi0esZ8g5iyXAQCYfpbm1CEGKff5lCzpBCTn//AClnCAedSzBLc3q/RqPhsc+tp62zm+qWbuQCLF1RhtFoYN/RSo54DCiNI+nJQwMefN4ov3nvEP/46JbzEmBbu6SMHs9hDnUNoTCkIiAk/c0bprmjm+ffP8xgSMSkEVg1J4PC3Kwxxw+TaZLjPGub2Z5Ld2MlGfkx8bHo6Vrl9Xd+lUVrrqNU2cyBvbvwer1861vfYsuWLaSOoUB9LlJSUlD63aRkjS3MZclwcLiijizHxAWsJK5snn/+eaLRKOvXr6f4Cvx9kZCQiLF9+/aLcp4J/8ovXbo0vgp/7bXXJjwgRCIRGhoaEh4KJ8Lg4CCLFy/m8ccf56677ko65sYbb+S3v/1t/PW56h/37NnDfffdx/e//33uuOMOXn/9de6991527drF6tWrJ2WfxPRyrLoGU94crOmJD0WdLY10tzShNxgoXZSYoudXGTD6XAz0h8gumoOrt4ehQS+CANFIlIycPIIttRfcdrPJxJxUIzW93aTYRura/IODqLx9LF03cm8dPlmJMXO06inEHM6OwQtTT6vX6fjavTfzx4/3crC+nTTL+A+4FQ1tV6QjO5z29uCDDyZ8jzX1uBAUOhqrTiGKIgPuPoa8AxgMRoYG+pGdFrkLXuLtd84XQRDYtGIxm4h95/9p5346QwqCgQD6FBNet5t+Vy/2vJHFplAwQEdjLUcq69i0akl8riKblsYxsvVDni5WLi9N2JZlTyfLnlhPeqTFg0IbcxgH+914+3rQW2zYsgoYGnDxk5c+5rEbluHImHgbnGFu3bSMNb19HKxq5XjPAGPFXLsaqzA7SqkLxRayI5MXOwABAABJREFUOv1wcq+bTe0urlszfi31mmIrb1YNolCPLIIJgoDFnoe7/hD6jAKUeivhUICUUDfLi7UMRBeyxr4Qk0Zg/YJsMjPSJn1tZ7IiP40aYfxFhfcO16JSq9my4fxSmCWuHERRjH+/SiJPEpclUmrxrGPCjuxwpLS8vJwtW7ZgMBji+1QqFfn5+WM6o2OxdetWtm7dOu4YtVqN3T7xtNFnn32W66+/Pq6W++1vf5udO3fy7LPP8tJLL03KPolzEwqFAEblvp+NKIqImpRRTiyAPSefFn8FKpUKlTpxoUJvttDX2YI9fy6N1RWk2h1k2mIRhHAoRGdzI6rz01qZNAvmlJDZ56KisRlfKIJSLmNumpXCRYkLJP5wBEE99pdUIDJ+jfBUmZudxu5T9cgVyf9NXN1d2IAej5c+lxurxXxB7JiN9Pb28uc//xkY/aAlAI2VJ3F1dyFXqBAFEX2KBVO6naF+N57eTrKK5iCPxBYiRFGkorqOQDhMSX4OBr2eKwW5XM4t65byxqeHONbdSWZRKa7uLhyFcxLGKVVqckrmcbLpZIIje92yEn738QnCpsQFn9DQAGuztQnR27FwDkVRaiHo9zHkcZGeVxLfpzNawGjhhd31PHGt+rzayKTbrHzOZmXDwgL+11+qUKQk/g45O5qwZObFxZmGUehM7GxyU5zVQX7O2JHMlQtLcHmPs6u+H1lKbFw4MES6rJcHH76KSCRCY1s3Rp2G440Ce3pMKHVGIqEg8rCK8o862Dq3j/VLS0fN/fK2o/QHBQxqgRVFVubPyU9qw923buHbv3kPTVFyp9vT20lm2XI+ru2mz/sJ99849Z61EpcvBw4coKKiAq1Wy7333jvT5khISFwBTNiRHRbuyc/P57777kOj0ZzjiOlhx44dpKenYzab2bRpEz/84Q9JT08fc/yePXv467/+64RtW7Zs4dlnn73All6ZvPbaa3zjG9/gySefHLdW6+DRY+SWLYi1M/GcbmeiGUkJNKfZUQpjeKQKBV1tLTgKilEolfR2tBPw+1AoFChVKvoHvRyvqmFhaUny46eRVKuFDdbxFVpU56inVQrjpypOlf+fvfMOj+us8v/nTm+apt57cZN7T5xmJ04P6QkhoS2wdELZZXchBBZYCCTAj7ILAQIkIQlppNtpjnuXm3rvozKapunl/v4YS/JYM7JlyzXzeR4/j3XLe99755b3vOec75lTUcrs+jY6+rrRGSb66vN46G9vxmUbprzURIstwH/94UVKMnR84+MfjkHH3//+d4LBIIsWLWLevHkx64wKKdb+PgSZDLlKhSE1HbfLSX9Ha9QT6w/RdPgwGrWKH//1FaRqLfqcEqQyJVs/qKNQK3L9JYvHBc8udlQqFXevW43ync3saKqjcPaCuNsJgkBQmUIoFBr3gBv0KXxybTWbDzTRNuInGBZJ1UhZVJ7GvIqSkzq+/Ohltg/1I5MrGOppGy8NJ5FKSc0uxBlR87fXNnPJgnLmzyo/pedOr09hXaWWd9ocSNUT6TORcHiSETuGTGtke103A8M2IgjMKsnFaJich3r1ynmsnu9h9+E2AmGRgnQ9s8pXja/Pykhj54EGjrjSkamjk3y1W19BpTNSsuBS3qpzUZ4/QkZaVLDsjW2HAWj2ZRBBCl5o2OtmSdc+blu7eNLxBUFgTXkqh9weFOrY0mKhUJD+9mZMWXkgkbGlrofV8/opmEad3CQfLsa8sR/5yEfQ6+PUsEqS5AJHFATEGRi/zUQbSaJMO4HobCbvX3vttdxxxx0UFhbS3t7Od77zHa688kr27ds3STV5DIvFQmZmrKJoZmYmFkti8Q+/34/fPxE85nQ6gai3cczjeDEzdo6ncq5//vOfGRoawuVyJdy/zzLAm1t2YSgoRSaTozMYGR2xYvX50BmM6E0mdCkp2Pq6MBxX4sY1bCHbbMRm9SCTShjq6UStTSHtmN84MzePmkE7oVA9cyvOfajs7JJCXqupR5cWf8CXpZGd8fvqo1dfwu+efZWA2zVeIqW/tR6v10tOQTFgR28wodYZGB518R+/eJyHv3DxC3OMDbTuu+++Sb/B1v2HkMqlpGbkkFNSTuvhGowZ2RRXzsXS2UZOSbRmqHWgD5U5A4026uUTwyHcPi+H3RGann2LJWW5LJ1TfkbKQE2X03m2T5YbLltJbdtzqBQKiMQPu5ZqDZPezSqlgquXT/YEnmxfS81y2sNhvCOD5JTPRXHMxFjQ76P94DYyCyvxpM3lzc4Q79Xv4JIKMwurEte3TcSKeWWk6nrY09KH1RNGIYWgIohEjH++1v5OagSRZl8mAgJv1TVRYQpz25XzJ010KORyLlkU9ao6HA62bNlCamoq5eXRibn9HXbk8hwggsdp44NnHsXrdvDvTx4CuYkdhzu47pIUGlu72dsvZ4kGJEz0S6JSUTMsUnKkibmVk/Nh161ciGJvLZuaujDnl0XTH1obCIZCVCxcNW78601p/OWt3XzrvvVJJdrzhLPxfJ8sPp+PZ555BoimbZwPfbqYOJ9+69PhQu9/MrT4/EMQxROVnY8lHA7z2GOP8dxzz9HV1UUgEJvvNzIycmodEYRJYk/H09/fT2FhIc888wy33npr3G0UCgV/+ctfYmpDPvXUU3zqU5/C5/PF3ed73/seDz/88KTlTz/9NBqNJs4eSQCsViv/8i//QiQS4Xe/+x3Z2cmZ+iTnL52dnXzlK19BJpPxpz/9KekxSHJe0dzczAsvvMCuXbtQKpXcf//9XHfddUB0svXYyduuri4KCgrOVVeTJJnE9u3b+elPf0pqaiq///3vPzSRKUmmh8fj4d5778XhcFxQ32Cn04nBYOCrX9yDUqk78Q4nwO8f5Re/XnrBXYfzkWl7ZB9++GEef/xxHnzwQb7zne/wn//5n3R0dPDyyy/z3e9+90z0cZzs7GwKCwtpbm5OuE1WVtYk7+vg4OAkL+2xfPvb3+bBBx8c/9vpdJKfn8/VV1/9objBgsEgb7/9NuvWrTthruuxPPLII+PqhJ/61Kdi1rlGR9l4qAlNWjbWIQtylRa1Nv7D39/Zga2vi+qqcpyiBKlUjizopcCcwuLZVQD84Y0PEJQqUjOzx1V3jycUDDJXHaai7ORCE880Xb19NPUN4g6FkSKQplGwsKo8YTTBmcLv9/PMm+/ROOSjaM4CIqEgBaMtHPEbiYhHS6lIBIabDvLTb372rPbtbDIW+n7ddddx9913T17/2P+RXjKHzIJiWg/XUDI3Kjw20N1JRl4hAH6/F4/DiTE9+j6xdLaSVTjh4XNYo2JkhtR0VBodPscQmfIg65fNRaNWTzrmmeZUn+3pEg6H+eM7e3F4wyhVKgxp0esjiiJDvZ2YpV4+dePaGT/ukxt2MayMX2MaYKing7Tcophl6SEL961bRFf/AP/c1Y5HmYlMoUQURXD1cUWFCYlE4IMGK4PuCK6RQVJzitEaouJpkXCY0HAb1TkKDvvykEgmBuyiKGLt7SA1J/47KOS28q9X5ZFmNk5ad9VVV1FUVMQf/vAHNm7cyJYtW5DL5Xz7+48gTcmkYsmVVC67OuoNLVjI2JTxLO0QH7msmv97rYZhMZ2F0kPUhKujocXHYI7084WbE6ul/+YfGxGz5zDS10VKWk7CHHts3Xz55qRw4vnA2Xq+T4bf//73AHzqU5/ixhtvPKd9uRg5n37r02Es4vGCRcIpFC5N0M5FzrF21bEIgoBKpaKsrIybb74Zs9l8WseZtiH71FNP8Yc//IHrr7+ehx9+mHvuuYfS0lKqq6vZuXMnX/7yl0+rQ1NhtVrp7u6e0vO3cuVK3n777Zg82Y0bN7Jq1aqE+yiVyrjGhVwuv6BfGNNlOucriiJ/+9vfgGht4eP3q23vQpsZFXLxev3o03MStuX3+/iXm64mKysTj8dDMBhEr9eP57u9u3MPwVAQqUKJVJHYCJQppYTE0fPmNystKqS0qPBcdwO5XE6KWonGlIJ71E3A7QIlpOYUIkqkhENB+tqacIvS8+bazTShUIinn34agE9+8pNxzzNFpUCUSEEiRaZSR/8PRBDG/y8iISJIECVSQqEgEoVyfJ3LNkIwAhmFZUe3BaUpiwGfj9/84y1uXbOYyrKSM5ofnYgz/S6Ty+VkK8OE1GlodHqODfNJLyjFbekkGAzOeIRLWKoiIiT2/EQEyaT1Pc4I4XCYf+zsJmIoRgJEIKr2ZSjghX0taA2pBEQ9LmcnmWXzkStUjGfwy6TIsqo41N9AwH0AWd4ipNLop9RlG0JtzEzYJ4kug8bOoUlqw21tbdTW1vLPf/4Tk8lERUUFP/vZzxgYGMCk09PR38mbf/geUqWWsoWXj+8X9DhYsjALuVyOTiFj0D92z0onGbJapWzqe0BtRBSkBEUBQX7M+R7HaERJOBw+azoZSU7MuR6rWCwWNmzYACR+vyaZGc71b326XMh9B5KhxdOgpqaG/fv3Ew6HqaysRBRFmpubkUqlVFVV8dvf/pavf/3rbN26ldmzZ5/ycaY9J2CxWMZFUnQ6HQ6HA4AbbriB119/fVptjY6OcuDAgfHCuO3t7Rw4cICurq7xOnk7duygo6ODTZs2ceONN5KWlhZTE/b+++8fVygG+MpXvsLGjRv5yU9+QkNDAz/5yU945513+OpXvzrdU00yBXv27KGhoQG1Ws0dd9wxab3VMxFyfqLHVSKVkpoanZHRaDQYDIbxwf6WfTWEzNkUlpQQ8LixWvqBqCFt6eqkr7Odvo523C4X7uEBSgril735sLNi/mwQI4w6bKTlxIYkSmVy8spnJ/bAXARs3LgRi8VCWlpaQqX0u6+7CtuQhVAoSDg8MYwXjzHLlGoNfq8bAI/DTopxosTRqMOG6Zg6w+FQiN7WRkZtVsyzV/JOv8j/vrGDXQdrsdvtTDOr47zHL1Gj0cWPYNFmFbLzSOJImlNFp5j6ExbvGgsCbD3QRFgf/10RFAXkOhNu5whKTUpCQadhNyjyF+EY6Ga4tw1rXzv2wW4iCfKEjz3+8ezbt4+CgoJxb0VtbS1Op5Pf/va3vLvhdb7x0E8xZRfRun8TYiR6b4YCXpZn+SgpyEUURQYHegj6PHGPGQ76WVA4dThceGw4EJlaBl4mBs+L/O8k5w9PPfUU4XCYFStWUFk5WUU7SZIkHz5uvvlm1q5dS19fH/v27WP//v309vaybt067rnnHnp7e1mzZs0kgd7pMm1DNi8vj/7+qDFRVlbGxo0bgahhM92Qyb1797Jw4UIWLoyG8D344IMsXLiQ7373u0ilUg4fPszNN99MRUUFDzzwABUVFezYsYOUlIlSCl1dXeP9AVi1ahXPPPMMf/7zn6muruaJJ57g2WefTdaQnWHGRHNuvfXWuOHXx47VBCEaepiQSJj9dQ2TFgeDQQa8IaRSKdqUFEpLSxju7cJpt9HT1hItxVNQTHZhMX6vm1FLNym6089duBgpzM9nuK+bjLyiuOsFQSAjJ5/ICQaxFyrH1o5NNAivKivFLI9g6WjDN+ocN4JUag1up318O7lCidftQqVNwTN6TJjUcQI4/R0tZBdXYM6K1jr1uEYZcAbY2GLnD9s7+PWrO9iwfT9+v/+iMGod/qnvHbt/5uvvLihKJehxxV0X8HnHPaXHogw6eO9wb0LP+JiQkUSQJBQ18ns9qHR6pDIZaXnFZOSXkJ5XTOHsRXic1oT9DbsGmF8x2YBetWoVIyMjPP744zz99NN87nOf48orr2TBggUEAgH+9dZVXLV6CSPtNegC/eQKfdw6S+TmK6Khwu/tqsWhn49jqGdS26GAj1kaC0urpzYwDKro9TBm5GAb6E64XWmqIin2lGScY2vHnk0x0CRJzgljHtmZ+HeR88gjj/CDH/wgxkbQ6/V873vf46c//SkajYbvfve77Nu377SOM+3Q4o985CO8++67LF++nK985Svcc889/PGPf6Srq2vaVvXll18+5QBuLFRlKjZt2jRp2e23387tt98+rb4kOXl8Pt94Td5EHy6TWo7j6P9zCotpa2okv2zyQGrUYcOcamLEF5i0rrm1DcNRIwBAo9OxYMlijhw6QsncBbHHS88ioDOwv7aBRXOqTu3EpsDlctHd24den0JeTuIw6fOZDJ086nVN4DHSmjNwuVwYDIa46y9URkZG+Oc//wlMrh17PP/2ibv4+Z+fZVQi0HZ4H6XVSzBlZDHQ3UHA58OUkUVaTh5DvV0Evd6EHyPniBVjeta4seSy2wgG/GQezaeNRhTYGHIH2N2/F4UgUmhUctncYrIz0mbu5M8iMonAVOa4XDLzH+6q0kIW9dew3yYgV09MYgW8HkYs3WQWxb5zhloOo88qxBewkmjKK+aTlOCEXNYBUnMnKwADKFRKfG4HKm3scxQJh5mXEY5bhic3N5evfvWr/Pd//zdZWVl85CMfYceOHQCoj+ZWtzcd4aO338i37lo2af+aLjcSuYn0ggqghpH+DiJIoqWIJBJyi078TFfnGnm/34dCpUIMh/COOlDrYveTOPu4avX0VZ+TXLzU1NRw5MgRlEold91117nuTpIkZ5Rk+Z2Tx+FwMDg4OClseGhoaDz6yGg0ThINni7TNmT/53/+Z/z/t99+O/n5+Wzbto2ysjJuuumm0+pMkguDV199FbvdTl5eHldeeWXcbRZUlPL89gOkF0ZzAjOysuhtbSI1Ow+VRoMoivS2NaNRKcgvLkYcGZjUhlwuJxwIITsmp8LS20PhrHmTtgVQqNU0D/WQWM5k+ni9XjbXHMGFFH16Jt5BF/tbd1FdlEtR/oUVxnzl4jkcDogJQ72lQR9arfas9uls8OyzzxIIBKiurmbBggVTbisIAt/45N04HE7+/toGGne8iy4tG5lCyehwP8GBNuZWlFGWn8LiqvnsP1TH/v52dNnFMRaQ1+2K8X67HTYyCyYEgHrbGsksLIsRLrMCz+9t586lApnpEyHLFwoFRiWdcZb7PB6G+zvJy1QhiuKM5whfd8lCSlo6qekcxOUPo5ULVBXpaFbpaXVYkBqyCPrcGELD6FJ0yDV6JE47oWAAmTyOd/6Y3zF8gjDheJgy87D2dqDyDRLWFyKRyRFcPSzOVXDT5UuOOYxIe2c3oihSUlTA1772Nb72ta+xZ/8hhm0O/vbkk3z2s5/ljjvu4LnnnqOtrY1XXnkl7jGt7jAy48TfqTlFMTmyI+7hE/Z7WXUVFtseal0q0vOKsA32M2obAjGCQSVjdk4Kay6rINVkPGFbST48jHljb7nlFkymqWusJ0mS5MPDzTffzCc/+Ul+/vOfs3TpUgRBYPfu3XzjG98Yr1Cze/duKioqTus40zJkg8Egn/nMZ/jOd75DSUl0ULZ8+fJk2O6HjLEP1/33359QYl+fkkLANUJ7g4+0rGxSjCYEUaSj8TBqjQ61RoOMMAp59BY0yCe3U1ZSzKGtu9FnT6iShiJMKevvCsxsaOxbO/ehzStmzIei1upAq2N/7xByuYzcrKwp9z+fWLlwLvte340qdcKjHA4FGXXa0WhTKDTIkSVQhL6QGbtfT+SNPRaDQc/nPjo59/t4Llu1jHl2B7vqWnGKPpzDFvRpWce59Ygx3py2YYzpWXHVtyXGLP65tQajwciAJ4QEyDcoWDWnmDTz+T1IXDW3nM4th8AcneAJh0JYOltRaVPIKZlFeyjE717fzpLCVJbNm9moiaqyQqrKYoXVFs+DUbeblo5uDCk6Bqwh3h2IPsmmzHz62+rILpk9rjQMgCDgs/Xj16ox5xTSVbcPa18HqTlFMW1rDSbcg51oM+KLuWXrpXzzjlU0tXTgC7qZW7kk5tnaur+erU12XLI0BEFAu3MnJYYwfW4pAwEDck0JS2//Jq/94zEef/xxrrrqKn75y1+iS5A6oZFLmGpOW3WS6e83XbaUBb0WDrT1E8iUY1SaWFVdnixDlyQugUBgXEQvGVac5EOBwImFX062nYuc//u//+NrX/sad999N6FQCACZTMYDDzzAo48+CkBVVRWPP/74aR1nWqNWuVzOSy+9xHe+853TOmiSC5dj1Qmn+nD19vdjGXFQOruQcDhMT3srbqeD9KwcsvOjYkP9ne2EQkGcll4uXTRnUhuCIFCWbqRj1IVGl4JteAi7dQjzceU0jkU6gy+H+qYW5Bnxw4h1qenUdfReUIasTCZjTXk6W7ujQd/9nS1IlGp0BjOOkUEMGpHhEdt5bzBNh/r6enbv3o1UKuXee+89I8cwGw1cu2oR1wK1ze1sbe5BplDgcTnQpBwNzTzGkPWOukjPjx+WOmLpQyoz4VdkgCKqptsJtO9o4bZFBeRlJy4jdq7R6bTcuXouHxxsosvuo6ffQtG8peNGvFQmg7QCdg25UDa0ML+q7Mz3SatlwdFUg+5B53hfBEEgs7CCwc4m3M4RCucsn8j7zC3G1t9OSqCZ7MIyBns76KwdQqVNQSaVopYEuWpOBk6fkoOjoUl5uCG/hzWlBiQSCVUVk8vwbN5Xz8Z2CTJtPp6hXup3vEXnkZ0UzF7Bshs+jVwGYiRC1aqbyZ+zGpXPwhdumkdebu6ktsaoylJwKH6qMOHRYZZfmk8wGGTbgXosrhCCIJBvVLBi/qxJ+a4FuVkU5F4477Uk547XX38dq9VKdnY269atO9fdSZIkyXmETqfjD3/4A4899hhtbW2IokhpaWnMhOyJouROhlPKkX355ZcT1gdKcnHz5JNPEg6HWblyZdxwAI/HwwcH6mgYsJNbMReH04UYCZOZnUNecSmjDjtD/X2kZ+fgctjINqZwSUVhwpDW+VWVCI1N1NQfQaI3UlRSistuI8Vowuv2YB+OhiSb0rNQadRkpcxcSYgB5ygKQ3rC9TZ/cMaOdbZYNLscjaKdxlrILCwbLx2j0uoYBZ7Z0cj9a+aiT7k4RLP+8pe/ANHasVPVkp4p5pQXM7usiIaWNjbsrYeU+QDjSrNAwrzaSCRCwOcjo2Cy8SMxZPHekU7uP48NWQCDPoWbLl1Mb/8Azx/Rxw0jVmhSqOnqOyuG7LEUZJkIdtuQa6JeWalMjiCVUTR3xaR+mrKLCbqs3FwhIJ9TQVlR/iSvpCiKyLYcoKbXD/pcxEgEubuPS0r0XLZk8sTc2D5bGu3IUvLxjtp5+RcP4rT2o0/NYctzv8A+0M3Vn3oY4ahxqTOmA+kcabdOaciuX1FJ26uH8Khitwn73VxSGD3ub1/fTdiYj3B0tq/HHqHmlW187KqFJ/W8i6LIixu2UNPpIRAWMKtC3HXVPIoLC064b5KLk7Fol/vuu++ijOZJkmQSEmAm9B4+BHp5Tz75JPfddx86nY7q6uqYdd/85jd55JFHZuQ4037zlJWV8YMf/IDt27ezePHiSQbImawjm+TcIoriuGEQzxsbCoV4eft+FFlF5OtjZ/R725rIKyxEZzBiH7HiGLGii/i5e92JC6dXV1ZgsbkgNdrmYF0dwwP9pBhMZBZEPVvDlj76Wup4YN3q0z3NccQppWtIKARzvmN1jCZcJ5hy2VnXytXL55/FHp0ZwuHweK3jsxn2JggCs8pLKS3M59VtB+jxy5ApFHjdLtTaqOJ6JBxGclyI/HBfF2m5iesOW/wybHY7JqMx2kYkwvYDdbQOewmERcxqKYvLsinKO/diZM29Q6hSjAnXD/rA7/dPW+n+dCjKyyZrfztWJsSWBISEObu+YIRNh3pZNqsw7jaCIHDjmoWsDwY53NCCVCplXtXyKRV9jzS04NdkIwG2/OPXSKRS7v/B3/F7PPS1HOadv/w3lSvWUzhnJWIkgiCREPR76bROPWmWotPyxZvn887uRnCAwtNLqk7O0rlGFs+dz+Nv7CBiKoiJZhMjYRwyE69sO8x961dO2X4oFOJbv3wZSfo8FCYdMsAJ/OyVNq6e3cfNV62Ycv8kFx+Dg4O88cYbwPTSNpIkuaBJ1pE9ab74xS9iNBq54YYbYpZ/7Wtf45lnnjl3huzjjz+O0Whk3759kySTBUFIGrIXMfv3759SnXDP4XrkmfEH4rklFVg6WykoLUMAeusO8PVP3HfSxx7xBjAf/b8gSMgvK48ZMKZl5WBKy+BwayeZ6TOj+mrWqOkLheLmMgLoVRfmDHSPw8dUfutum++s9eVM8s4779DX14fZbJ70Ij0bKBQKbrtiGTa7g7buPho7ehn060nPKaC/M1qaJwaRScZtTHs6I0PDI5iMRkKhEH9+YzsufSESVTR82Q20HbKyZsTJ8uqZV+6eFif4Rp+rT/jdl8/jb+8cYkSeiUyhQogzs+73erANdKNPzcJrquaDIXj/n0dYUajk6pXVk7aXy+UsmjfrpI4fDIUQJNGnr3HnBq564NsY0nMZ7mln3mW30XZwCwfeeYbCOSsRJBJaD3zA+3/7MQ899sQJ29ZqNFy3ei5vvNHFt+5cgvyoSF5Hdy9W9EQ8bpzDAwR8PlwOH3JNKgqVnl53gFBgO/dcszjhxMJjf30TRe4yJJLY+9OQWcJbhxu4avlowvzdJBcnTz/9NKFQiCVLlkxSJU2SJEmSZ555hrvvvptXXnmFNWvWAPClL32JF198kffff3/GjjNt53Z7e3vCf21tbTPWsSTnH8eqExqPeoWOZdDtn1KRdEwvVxRFblt7+bRqEY4FZno9HpCr4u4rlcnococIBmcm5Ld6ViUey+S6jABuu42q3OwZOc7ZJnycJ9k+NMBgdwcDXe34vd5J6y9Uxu7Xe++996x6/o7HZDSweN4s7r1xLZ+9ah7VGheLMlR4uxsIBY+R6PG78XsSe8tDzmHyj95zb+8+zKihaNJzINcZ2dTmwjWauJ2zQUVuBn6XPeH6NKV4Tn4Tgz6FL966mlvKBeZorOgk/knb2CxdZBZWxpSekRiy2T6gYltN/Wkdf15VGYKrj8GuRlRaPcqjJYPG1JEXrfsonbU7sA10AbD71T+QXlBJYepJqjXFwWJ14LTb8I46SUnNwh/SkF60BGNGMRp9KsbsMpoDhfzmxd0Jy+F1ulSTjNgxjNmVPPHyllPuX5ILk7HorKQ3NsmHCmEG/13krF+/nv/93//llltuYe/evXz+858fN2KrqmZusv2Uo7QDgQCNjY3jSlRJLm4CgcAJa8daj9aFSshRIzfi91AyzbyqFLmUzpZm6g4eID0vcfilNj2H+ubWabWdCEEQWLtoHn5LF6N2GwChYBBnXxdVRjVF+Ylz1s5n0jVRT7LP66GvtRGFSk16XhEZ+cWM2kdwjQye4x6ePna7nZdeegk4v9Q01Wo1ly6ay63rVvP1O9dyRWaESpmduUoHX//Iagwhe8J9i1OE8ZqiLcO+hJNGSnMWu2rP7aRiTlYGmbjiGkYBt5NFRee2Vm51VSk3XzqfK2ZnEQlPlNixD/VjzMyPu49MqWFvuyPuupNFLpezMFeO1pBO+dK148v15gzsg13kVS1Bn5rNwXefxTtqp+3gZq659X7WLIrmE7s9HnYfqKfmcAORyMkptDsddlRaPcb0bKz9Fgzpk3OwAYYkheyoaYi7LkScMkVHEQQBeyBxJEGSi4+DBw9y4MABFAoF99xzz7nuTpIkZ42xOrIz8e/DwN13380Pf/hDLrnkEl599VU++OCD0y63czzTjo30eDx86UtfGp+Na2pqoqSkhC9/+cvk5OTw7//+7zPawSTnB6+99hpWq5WcnJy46oSiKGJ3uI7JPptMJBTEaumnOi+xgFIiXA4bOaWzEKTSKWtRipEI0ml4ek+EwaDnxktX0j8wgGXYikoup2rNZHEYu8PBoeZ2vGERhUSgqiCH7MyMGevHTLJkVjGbB7uwWXrJLomdFTNn5RL0mdlxoI6VCy7ccLHnnnsOv9/PnDlzWLx48bnuTlwEQaC6qjxm2Q1LyvnH9gZILRi/x8KhIBpnD9dfvWx8O3cwMmV4uDsw/fqnM83tVy7nta376XRHjetwKITgsLCyyMz8yrMr9JSIy5fOofO1bXRGcpDJFYQCPpRpiSMtLKMiwWBwPGz3VLjpsoUE392HZO0tqNOjOf6yiIdZBjehSA+zV15H/e6NuIZ7KCip4hv3XoJapeKZt3ZzZFBAos8hEg7z6oFdrKk0cPmyqZ/TkZACrSGqRB4IShLeNxKplIY+D6viFOKWiFNPWKul5/5+S3L2GIt2ufHGGzGbzVNvnCRJkg8NiYSAMzIyWLhwIb/97W/Hl42V4Dldpm3Ifvvb3+bgwYNs2rSJ9evXjy9fu3YtDz30UNKQvUgZm7hIpE743rbtpOYX0lCzD53BiCCRRL0xYoTswmKctmGGuruQZZi49PKbp3Vsy+AgyoxcpFIp2fkFtLV3kJmgfIlvqJdZZ0B4JDszk+wEqreHGps5OOAgJS0qRuUF3mu1UNDbz6WLzj/RJN1RgTZTRvwBu1yl5lBfDysXnMVOzTBjA60HHnhgynD3843sjDQ+f8MKth+oY8AdRoJIcbqWhZddGnMeOrmEqUwLneLce8ikUik3X7aUUbeb5o5ulDIZs1ZPngQ6lwiCwAM3rKamtpkjvTZ84ak9rgKRKetYn+wxb1+7hKtdoxxsioYQz1tTgT5FhyiKrF+Yxdor/8qh+t289957ZKaZeerNPTT4cpDoo9dOIpUSSilgY7sbmbyBSxYmDtOy+cKgHev/1IQS2KOZGh+Tg7CjjNr6+Oy1807QcpKLhWAwOF47NhlWnORDR7KO7JTU1NTEXV5aWorT6RxfP5PjgGkbsi+//DLPPvssK1bEDkhmz55Na+vMhHQmOb84Vp0wXpim3eHgYM8QEZmLsuqFMXl7oihSv28nMgnklRQxPzt12sdv6x1Aa4zO+kplMuSCSMDnRaFSx2wX8HqoyjBMK/f2dBkcHubwkHvciB1DazTT53FT39LGrLL4oXznGqVGl1B4edjPaXuezhVNTU3s2LEDiUTCffedvKDY+YJMJmPNksmiQsdSlqaiPhg/MiEw0s+yteePN12n1bJwTnxDyzI4xOH2PoJhkVSNnKXVk+uanmkEQWDR3AoWzYWBoWF+934vspT476kSs/y0+9fQ0MDvfvc7FAoFOp2OuXPnIq8qHG+3orSIT33yE2zYsIHLL7+c4RE7dSNKpNrJv7VMqWV7Uw+XLEx8PIVEwHv0/xLp1OHIuab4Q4J//chyvv/UXvQ5sQar3+uiQj9CYcHSKdtNcvHw5ptvMjg4SEZGRowzI0mSJElmUsTpZJn2F3loaIiMjMkhk263+7yaaU8yczz11FOEQiGWLl0aV53wYHM7Kr2JnJLKSYM8QRCYtXgFmhQD3a2tdNo9vLJ1DzW1Jy+a4g8GGXU6xnPCispK8YxYGOhsIxQMEgoG8Fq6qFCFWDE/fv3GM8WR9h605vj5fkqNltaBkbPan5lCIp6+5+lcMRY9sH79erKzL0xBrhOxbnk1Kc6OSXmSoVE7V5QaSLkAFGRf/WAPf9/fR0vYTCep7HVp+e1r2+i1nLsc7cz0NGYZ/YTDk/3dEfcwa+ZMLm3k9njYVVPH7gN1JxSa++Mf/8jtt9/O+++/z+bNm9m0aRM//vGPue222/jDH/6AwxH1CP/bv/0bL774IgCHW/qQahNPAA4HdVgGEl+zYrNqPFfZaNbjcQ7H3U7q7uWyxfFDvjPS03j4/uWYvIdxDzbgGmgiNHyYK/IcfPGea6Y85yQXFyeKzkqS5KJGEKJ1ZE/330VqLx06dOik9RsAamtrT1tradpvoaVLl/L666/zpS99CZhwD//hD39g5cqpa9EluTA5kTqhKxgmggRZAu+dIAgE/AGyi8vQZOUB0BEM0r9lJ9ddmjgM2DI4xP6WDob9IRRqGf1dHYRCIfJLyigoKUEURQZ6uvFbB/nM7TchCAK1jS10jbgIi2BQSVk6uwKVaqpswtPDE5r6gXUnitU7D/A7R1AY4+cr5+lP3/N0LjhXtWPPNlKplE9efwm7DzXQMuwhEBYxqaUsnp9DQW7WiRs4x2zZf4QOzKj0EyJCEqkU0op4ZU8zn7sh/ZxNjN65bilvbTvEgV4PbpkRMeAjTxvkikXZVBTnjW8niiLPv7uXI4Mg0WcjiiJv1u5jWaGaay+Jn1Lw3e9+l69//et89atfRSKR0NjYyNatW3nvvff47W9/i91u55vf/CYqlYqsrOjveDJXYapLtWbxbJre2IFHX4Q+NQ2/rwf7QBuGjGIEQSAcCqIL9HHP5cXjaQfxSDWb+OYDp+aBs47Y+aCmgz57GJkEyrMUXLZ0VtIQusCwWq28+uqrwMX9fk2SJCHJ0OIpWbhwIRaLhfT0k9PCWblyJQcOHKCk5NQjF6f9Ffnxj3/M+vXrqaurIxQK8ctf/pLa2lp27NjBBx98cModSXJ+cuDAAQ4ePIhCoeDuu++Ou40AiBERj8uJ02YFQKs3kmI0jW8jVygJBYPjQk0yuRyvPp26phZmV0z2AgwNW9na3IkuI4cx/78xNRVRFOlorKe4ajaCIGBMTaU4x0w4HOaF93fgN+Yg10QfIKco0ry5hnVzi8nPOTODe6kYmTJXURanTuX5QokmQGecOrkhp5VVsyd7ni4E3n//fbq7uzEajdx0003nujtnFIlEwooFs5n5jPAzT73FhcxoiLsubMhh35EGlpxkbdaZRhAErr1kPtdEIgwMDKLRqDEYJvf1H+/spdabiUQvGd8PQx7bB33Idx5h7Yq5MdvX1taiVCq59dZbxyeJKisrqays5CMf+Qh/+tOf+Na3vkVubi733nvv+H7zynJ4u6kTqS5+5EeazEVmRuJIFJlMxieuWcbbu2tpGQmQooigVAwT7m1lSfU8ctJ0LJm38oxNHDS0dvO3DwYIqyeiI9rbRfa17OILty5Eq9WckeMmmXn+/ve/EwwGWbhwIdXVU6c/JEmS5MOHKIp85zvfQaM5ufd6IBA48UYnYNqG7KpVq9i2bRs/+9nPKC0tZePGjSxatIgdO3Ywb15S8OFiY8wbe9NNNyVUJ0zTKPhg70FKNVqyCqIiTM4RK11N9eSWlEfzWhUKnCODMYMlhVJFl22QeNl8h9o60cURIxIEgaz8QoYt/cgFkaIUNfOr5rJh+17C6UXIj2lfEATUmfm8c6iFj2dnzuhAze/3s3n/YZp7+slQ6FHFeWhFUSRHp46z9/nBdasXsXl/HXWDHrzyFMSgj2xVhNWzcyktzDtxA+chYyJPd9999xn1xCc5PUa8IQzG+OukMhnD7tP/uJ0uEomE7Oz4E2Au1yhHhiVIUyZHLcgUKna3D3PlskhMVEN6ejparZaf//zn/OpXvwKiEQQSiQSz2cw3vvENamtr2bx5M3fdddd4aH+q2cjs1CYavBGE46Ikwr5RVleaOBFKpZIbLl3EgYZWtjYN4S6Yi1SupNExgChxsXgKJfhEhMNhtu6ro8cRRBCg0Kxk5YJZkzQSnv2gm7A6tmSaIAiMyIp4cVMdH7t+ybSOm+TcMfZ+TYo8JfnQIsxQWPBFGlq8Zs0aGhsbT3r7lStXjpcVPFVOKa5n3rx54wZOkouXYDDIU089BUwdRtQ7NMKiS6+KhgYeRW9OJcVkpqe1CWNaBmqNBsdwnJqS4fihucPeAIYE4zO1Vou3v5ObLr8EtVqNKIp0uwJo44ihAMjScjnU0MT8WZUJz2E6iKLIa9t2o8otodScTWt9HTnFZTGh1aIoEujvYOnl52+4vSAIrF2xgKtEEavVilqtRjtFaOH5jtPpHM8rTA60zm8U0qk/4vLzOJIB4FBzJ9KU+CrmAH5NNo3N7cyqLB1flpGRwac//WkeffRRSkpK+PznP49SqYzZLyMjg717907KT7/nmiW88O5+DllEhJRo+R2Vr481lQZWLzw5z/Xh5nY2tHiQpeSOf/ilxixaIiLPvL2Te69ZdXInDwyP2Hji3VoC+sKoASxC+2CEPS9u55PXLECfEs3R3n2wEbciN6EYR21fiHA4fMHm43+YOHLkCPv27UMmkyVrxyb58JIMLZ6STZs2nfVjnpIhGw6Heemll6ivr4+K+cyaxc0335zMd7nIePPNNxkaGiIzMzOhOmEwGMTiF0iLMxARBAFNip6O+oOkZ+VQUFY+aRtNggFtIjXdMbIz0sdncTweDyGZMuG2Mrkcp3f0BC2ePIcbmpBl5I//XVI1i96OdsKRCAgSZKEAVTmprLp85Vl7JkRR5J2tOzjc0Y/D7UGQSDCZ0zDoU0jTqphTkElxfm7cfQVBIC0tftjihcTzzz+P1+ulsrKSZcuWnXiHJOeMQqOKRPJEPoeV+csLE6w9PzjRGEQUI3RbBtnXYcfuE9HIYW6uji984Qu4XC4eeughfv7zn/PpT3+aW265BYlEwv79+3n22Wf54Q9/OKk9iUTCHeuWcIPXS21zJ3KZlHlVy6aVx76zeQCZdvI7QBAEOv06+geGyM48ubymF7c1EjQUxVwHiUSCV1/ES1vreODa6PM3MhpCIk38DvSKWpxOJybTib3KSc4tY86LG2644aTz35IkSZLkTDPtUfaRI0e4+eabsVgsVFZGPVxNTU2kp6fzyiuvJMOLLyLGwog++tGPJjTImlrbSE1Q0xUgNTOb4d4uAl4P5opYj6jH5WBezmQFbACdPPEMfSQSwaCc8H6qVCoIJg5FFEURhXTmhIsGnB5kxglVWEEQyCueSFT3DvSwZvGCGTtePERRpKa2noFRP16vl9rWDuR6MypjOgYDZBdO9McFbOqw4XR7mF81eTLhYuHYsLekgvr5zaXzSvjHrhYkxtj0gaDfR5UhQpp5smHT1tXDgNWJRi2nurLsnP7GC6qK2dhQi6CPr4rt6jrE5kA5MrU+WhsgDO2tAeq6dvOf//mf3HPPPfz5z3/mySef5L//+78pKirC7/dz33338dGPfjThcdVqNUuqE9eMTUQgEKBvVGQs00EURYa626MThoIAoshT7/TyLzdegkGfMmVbPf0DWEIpyBPMHXZ6lIzY7JhNRvRqKWJkckj0GEo8pKRMfbwk555QKMSTTz4JJEWekny4EQUBcQa+PTPRRpIo0zZkP/3pTzNnzhz27t07Potqs9n4+Mc/zmc+8xl27Ngx451McvaxWq289tprwNRhmj6/n+EBO0F/AEGIGplp2bkoj+YniqKI22WntCLWQ+a2j1CskVCUHz8XsywzlQaniwgSrAMWBImAKIJUKkErhfWXTYTsSqVScnRy3An66BnqY8GaBSd97ifiRMLiJ/ImnwpOl4uaxlYc/jABn5dB5yjm4llItHrq6nZizMxHbzJjGx4ip3iyeJZKb2RPVzezS4vOQO/OPa2trWzZsgVBEPjYxz52rruT5ARkpJq5c3kZW4+002n3E4qImFRSFuboWTF/Ucy2A0NWXtvbhE1qQKlJIewIsqV5J5dXZTG3PPEk2plEo9EwP0tCjTOIVBar1u4Y7EGZWhQ1YoFR2yCRSJgUUyZt4Ry27K1jzdI5fP/73+c73/kOXV1dNDY2smjRonGl4plGFEVEYcKY7GttIKOoAukx3lIReOK9I3xybTUpusQpBr0DI8i18YW6AOQpqXT09GM2GVm5sJINB3YR0BTE3XZOtiwZyXUBsHHjRiwWC2lpaVx33XXnujtJkiRJMs60vyAHDx6MMWIBTCYTP/zhD1m6NFkU/WLh6aefJhgMsmjRooRedqfTydMbtlC5bDVpWRMha5audhQqNamZWVi62snJyydf4iXgHMQfEVFJJSwpziE7M743FqCqtIT2TZvpC0rIK5nIMwsFg7g6W4hEYoVUVs8u5dX9TSjTY0PnfC47C7L1k3LRTocUuYSRKcRRUhQTj1V7dw8NPQOMBkNIBcjUqlgyp+qk+3OwoYmdda0ElDqyC4tBBV1DTeSVRRVRXXYb6pQURDGCWqvDYUtct1aTkcf+2kYWzZmZXOHzib/+9a8ArFu3jtzc+CHUSc4v0lPNfOSy+AJyY4RCIZ7b0QDmAsaeGKlMjmjKY2OzlRRNP4W556ZW8C1XLEKx5SD7evxEUnIQIxGUnj5yFS5c+okJuhd+9iUi4SALrrqTwrkr2OsLI5PW0T7sRxQh3yTn6quvRqFQTHG000OpVJKpEvEA9iELpuz8GCN2jIA+nw8ONHPDJQsStmXUqQl1e5Epo+5dt9NGwOdFn5qBVCoj4HWSZjIC0XDj21Zl8czOYURVbPqCPtjFzWvmHt88AHaHk12HOglGoCgrhbmVRady2klmiLFol3vvvfeM3qdJkpz3SI7+m4l2kswI0zZkKysrGRgYYM6cWLn/wcFBysriF1NPcuExlg+TKIxIFEV+9Ke/M//yq1GqYhXHsgqKGejpxDEywlBvJ1ctmMWly6enTBmJRHCKcnIKY2fyZXI5xtIqtuw/yBXLFo8vTzWbuGXpLPY2tNHn8hERwaiUsrQgk7Ki+N6AU2XR7Epe3FGDIWdyux6HjaV5Ua9KTX0DTc4QamPm+CC8acDCvn9uoDwvB5NGyeI5VcgT1N/92ytvIWYU4pOpyS2Mep5cDjspxonBv9tpR6nSIAgQ8PtQqhNLnguCQCB8JvzF55ZIJDJuyCZFni4udhxsQDTlx81JletT2dPcd84MWUEQuH7NAq4JhTjS2IpMImFO1QqeeKsG19GaXJa2Wnoa95NXuZBXf/PvpJgyKK1exZGrP0Z6fjkqnYHGnjD/9l/3UlZSzPW33UtZpoYl8ypmPHR6SbGZ97pGCXg96NMSX7MWq3/KdirLikg5uAOLS47f40ZrMKMzpGKz9BAOBSnPUFGQN6FFP39WMamGQbYc7KHXHkYmjdaRvWLpAjRx1CpffreG7S0gaKNiWptavWTu3s4nrp9Nmtl4aief5JQZGRnhn//8J5B8vyZJklQtnh7t7e188MEHKJVKFi1aNJ6SOpNM25D90Y9+xJe//GW+973vsWJFtILhzp07+f73v89PfvITnE7n+LZ6vX7meprkrDGmTiiXyxOqE763dSem7PxJRuwYmXmFHNjyDllZmVwxTSMW4GB9A9qjXt6B3l6CAT8GcyopBgOCIGBxB8Zr0o5hNOhZu3zBtI81XVQqFZfPKmFrfRuKtEzkCiWiKOKy9DI320xRXi4ej4faQRf6oyWEovVvG8jIy8c0dxF+oF8U+fsHu7liTil2p4tGywgOfwgBsPX3os0tIDgyTFbhRPiky2aL+VsikRIK+ZFIZCjVGqyDiSR0IBwKkaKObzRfyGzevJmOjg70ej233HLLue5OkhPgGh1lx+E2XIEIWoWEFbOLMBrifysso0GEKRSOLa7gmermSSOTyVhwTJRDilJgrLh0V/0eiqtXcce//S8SiZQNf/oB9dvf4NDW1yhffAWzVt1IJBJi9zsvUfXfz1PvzuBIU5At9dv4l+sXThniO12Wzq3AH6zjlZ5ESRhRgsdNdg0NWxketlFclDde0mp2poKBLpH0/IlomdScIiKRCIKraVKbeTkZ3JNAD+FYPthdz9YuPVLtxHdFqlAzTBF/eq2Ob91/8srKSWaGZ599lkAgwLx581iwYMG57k6SJB9KNm/ezCOPPMK+ffvo7+/npZdeihnviKLIww8/zO9//3tsNhvLly/nN7/5zbjTcWRkhIceeoiNGzfS3d1NWloat9xyCz/4wQ9i6qTv37+ff/u3f2PPnj1IpVJuu+02Hn30UXQ63fFdOiG/+MUv+PrXv45Op0Mmk2Gz2Vi8eDGPP/448+fPP+1rMsa0nds33HADdXV13HnnnRQWFlJYWMidd97JkSNHuPHGGzGZTBiNxqQK4QXMWBjR9ddfn1CdsMs+ikw5kQcbjxSjGc3YiG6aeINhRoYG6WxtwZCaSk5RCYFAgPamRrweL2GJbEYKKZ8qOVmZ3HnFSqpUImk+O7lhJ3deuoR5lVExpYONreNGLEBPWyt5ZRWotbEiUfqcQv7x/g6OOEJI03Ix5xaiNKXhl6tIz46GJx5bmkKpUuHzeMb/Ts/Nxz48TOio2JUYDiX8PYLDfTNWguh8Yux+veuuu067HlmSM8vuQ0384s169o+aaQ6kcWDUzP97u5FtB+rjbi+cIOP8fJzUXl6VQ8htByCntJqSBWsIBf0EA35W3/pFHvzzfm7/5v/idlh5+Rdf4s3//Q9Sc0spmB3VEZDK5NiVxTz3Xu2M9+2ShbNZO3dqD7ZZHR0WtHT08bMnt/Kjl3p5Yp+cbz2+l5/+6Q0CgQDdrggpqVn4vR4Gu1sZ6mlnuDf6r9UhodeSeEJtKnY0OJHK4z/DA+FMDta1nlK7SU6dseispIhekiRMlN+ZiX/TwO12M3/+fH7961/HXf/Tn/6URx99lF//+tfs2bOHrKws1q1bh8vlAqCvr4++vj5+9rOfcfjwYZ544gneeustPvWpT4230dfXx9q1aykrK2PXrl289dZb1NbWnnIkxg9/+EO+/e1vY7PZsFqttLa2cumll7Jq1Sq2bt16Sm3GY9oe2ffff3/GDp7k/ONYdcKpbl6v14fd4UYikSGRCEQiIiBizshGpYmGt7rsI9xx3eWn1A/byAgSpZ7s/EKGLX0olCrMGZmY0tLpaKzHoFGfF7k6VeWlcZf7I8dJQglC3FqJoWAQlSkNlXZCudM2NIjeGJ0IEiNijOc5NSub7rYWco8KOgmCQGZePkP9fXQ21ZNTXEZXUz15pRVIjxFR8Q71ccWcojMyEGlq66KhbwRRhCy9gmXVs87agGd0dJTnn38eSKppnu909w3wdpsf+XFKxXJDNu932Mk291JSEJvfXGBS0TMSirmXjyVPP/EOcI2Osv1wCyPeCDIJVGbpqa46++ku+TmZXFowwJYeF3lVi8gqnYNMrmSwo4HU3OhEV+WydeTPWspAez1/e+hOVt/2hUnttDoVDFttpKXO7KTwpQurqHnjIBLTZKG9kM/N4uJUuvoG+cM7vUh0xaiOvpq0acWMiCLf+NVrGLIyQe1i1D6MOauAEUsXgiBBIpHg83h5/t29fOWj0xMFikQi9NsjqI5Lmw4Fg9gHOxEEgcffipC3d5hFJVrWrp6TNKzOMPX19ezatQupVDqlmnaSJB8azlFo8bXXXsu1114bd50oivziF7/gP//zP7n11luB6ARUZmYmTz/9NJ/97GeZO3cuL7zwwvg+paWl/PCHP+S+++4jFAohk8l47bXXkMvl/OY3vxnXoPnNb37DwoULaWlpmXb66OjoKB//+MfH2youLubRRx/FbDbz9a9/nV27dk2rvURM25C97LLLZuTASc5PNm7cyMDAAOnp6QnVCUVRxGp3Mmf5mkkDid62ZtJz8vD7fRhNJmo7eikvLpp2PyJyJV2trTisQ+hNqQT8PgL7d1M2dz65xaU4WutOOIipa2qlZdCOPyKik0uYW5hDfs6ZUQU9HrVMiuOoARqJRJDEMWIBBnp7yC4oilkmCCCVK/B7vaTn5DLY00Vm/kRdTa0uhZFBC+aM6Lmk5+Qhk8vpbKxl1GZFazDSuH8napWaVL2Wypw0Fq+YTcpxoSGBQICtNfUMe0JIJVCZZWRORQknSzgc5skNOxiQpiNXpQLQYg2z+5/buGfNnLglVGaaF198EbfbTXl5OatWJcMOz2d2N/Uh1caP8JBpjexpHphkyC6dN4uaV7cSMBdN2ifisLByRXQiqbG9m1cP9SMzZY9/1Tp7/Oxv3cL9166eVr3VmeCaVdUUtnaxp2UQeziMRiJhUaWSnSMeJGo9kXAYr8uG3xudLa++/PZJbch06XT0Dsy4IatWq7l1cR4v7e0CU/74ezToHGZJlsCCWfN54tV9SHQ5k/YVBAF52lyGBmpR6YPojGmM9HeSllc63k4kEqGx+SCWgUGy4gj6tbT3sKdxCH8Q0vRSLltUQkqKDkEQkB33mgyHglh7m8komMi5tQIbmkN0Duzk07etJMmZY0x74NprryUzM/Mc9yZJkiTxaG9vx2KxcPXVV48vUyqVXHbZZWzfvp3PfvazcfdzOBzo9fpx5Xi/349CoYj5Xo5FuW3dunXahmx1dTU7duyYtN9dd90Vt176qXJKuvc+n49Dhw4xODhI5DjP00033TQjHUtybjhWnTCRCNHeQ0coXrQiriGZW1JOV3MDVksPSy+5lEAoRGtnF6WF0xNc2rR1B4aMLAorZyOVSIiIIvbhIVrragn4/RSlp025/yubdmJVpiLXRgdSfmBD8xBzh0ZYMX/2lPueLuFwmHA4RFvzERQaHYgRwuFwwu2Pv44KpQq1LoXB3i7yyypBEHDZbaQc9dKaMzJxjIzQXVuD2WxGIpWSr1Fww0euITfr5Acbv397P4K5cDwHsa3Ty56WLdy//uQG/q9tq8GqKUB+TP8Dfj9DzhC/+OcO5hZmUZqmZsm8qjPmOfnzn/8MwP3335/0zpznWD1hmCJFe8Q7+RkRBIH71i7mtR1H6PYIKIyZBFx20qVerlhYSEaqmXA4zKs1ncjSCmP2lSmU2OSFbNx5kPWrFs706ZyQqtICqkpj33sdL+zCih6JVIpUrsTjsLLmrq/F3T/k92BMSZwja3c4qWnoJgJUFaSTm33iHNQxyovyeDAvi+0HGrB5wyhlsHRhEalH1YYPd7lQpMaf9FOotNgDYdSCBJdtiIyCqJfZMWzB73UjkUhQao38+JktfP2OSyjImXgnPf36bvYNpCBXHe2rC7Y11XPPpelUVxVRma2gdSJzAttAJ+n5syb1QSKVUWfP4GBdK/Nnx4+KSXJ6hMNh/va3vwFJkackScY5hbDghO1AjK4QRA3Q6VbZsFgsAJMmmzIzM+ns7Iy7j9Vq5Qc/+EGMkXvllVfy4IMP8sgjj/CVr3wFt9vNf/zHfwDQ398/rT4B/PznP+fWW29FoVBw5513jo/RduzYQXl5+bTbS8S0Ddm33nqL+++/n+Hh4UnrBEGYcsCe5PzmWHXCqdSK39xzhMpllyZsx+NykJOXi0KpAiV0DQ1Py5BtaGrClJ1DfmklHY11hEJBQoEgC1evobO5gbq9e1FUz2Hv4VoWzq6aFLK7+1AdI5p05PLY0GOV3sjhkRGKBofIyojvGTpdHE4Xr+46gCq7iIJZUWM7KvRUi8tuJ8VojNleo9XFGKkAaZnZdDQ3kJqVQ3dLI1mFxbhsNnrbWxEjEcI+D4tLclhy45XotNMXgxnLoZWa82OKcstVauzKQt7acYDrVi9KtDsQDUFvsgaRmSf2d1qHCPi9ZBREB5Z9QPdQiP2vbOET166Y8VDwjo4ONm3alKwde4GgnEK0CUCRYL1Wo+Guq5bhdrtp7+ohc1Yu6Wmp4+t3HKxHmhr//SIIAo3DPtaferdnlOuX5PPUdgthTSbG9BzyKheTlhd/ljtVsFJWvGLSclEUefHd/ezrE5DoogOXt5sHKUtp45618UulxUMmk7FmSbT8TTAY5IM9DbQMthIWweMPM9XTGg6L+NxO0vKiERw2Sw8KtRZ9ahbhUJARSzeCNoOfvbCHey8pYsXCuXywu44D1nTkqtiWRW0Of9/SS2lBBuuW5tKxoZ+wKnpeEkGScIJKJldzoHWAuZVhRFFM1qOdYd555x16e3sxm83ccMMN57o7SZKcH8xw+Z38/PyYxQ899BDf+973TqnJ49+VxwuijuF0Orn++uuZPXs2Dz300PjyOXPm8Je//IUHH3yQb3/720ilUr785S+TmZkZNzXuRFxyySU88cQTfO5zn+NLX/oS8+fPJxAIUFtbO57COBNM+83/xS9+kTvuuIPvfve7yVCTi4x//OMfBAIBqqurWbgwvgfjH2+9jUQ5taCORptCisE4/vd0C7488cpb6NJz6GxpRCKVYzCYkMnlHN67E63exJqP3IlEIqE9EqH2/V0sK85mVumEkm/bsAuZaSLndKivh3AohIhIRk4+h9p7zpghu+lgPeqc4phlgiBQXDWXlsP7qTTGGohqrRpHV3uMIQuQkZvPYE836Tl5jFj6iUQihHwe8rVy7rz5+tPq46HGloTrxgb+105RJxegzzJARDNhTIiiiMdlJ7MwdpZNKpUxqi/ijR2HuOWy6atXT8WYt+DKK6+ksLDwBFsnOddUZKjpHQjHDbMXRZHydNWU+2u1WubGEStz+kJT3qsufyThB/1sU1qYw6dVCj441EXncBCdxIPPOYjaeJz302tl/ZL4okxvbDnI3pFUpLoJ97ZMY6IjbOLZdw6SGnevxDhdo/z25YM4lIUT4cGCJ+H2kXAIY4qUQNCNSquPvpuCAYyZeTitAwS8HmQKFaGAD4nKwNO7Bnnn4FuAFokifuqCqM1l875Wrr10Hv9yNWzY00ujJUQ4nFiVetQ2SM3QMPvb9iAiIdcosnqOkUuWXHyCdueCMZGne+65Z0brsCdJkmSC7u7umAovp/KsZWVFvx8Wi4Xs7InvxuDg4CQ7zeVysX79enQ6HS+99NKkyMt7772Xe++9l4GBAbRaLYIg8Oijj1JcHDuuPVmuu+46mpubeffdd9m0aRM1NTXR0nXXX4/ZbGbevHlUV1fzi1/84pTah1MwZAcHB3nwwQeTRuxFyIlqcYqiSNeIm77ONsrnJzZKAj4PaVlRye9wOIxJPT1PXFgiRSqVIZPJKZkzD7lcgcthR2swjueFAkgkEnTZBezrH8aoGyT7aD6WNyQiB5y2EZy2YdJzC1AoVYiiyGB3J97QKCyfVpdOipERGw5BSSIfaW5hKYHORkIqLeEIpCgkVGelkrf2Et7ccwjRmDFezkgIhSgza6lIVTCo0CMBqgrnkjoDeacjo1OrPbsjcnw+X1wF4OERG7Wt3eyubcKrK0BxtL/DvZ2k5RUzarfhdowgSKKelEg4jEqro0mYXC7pdBBF8YS1jpOcX6xYMIvDr2zFqo4VHRNFEaO7g9VXnVqOs0omYSpxdJVMOC+M2DFyMtO4Z91EakR7Vz+ba/vptEafy8JUOZctyaUob3JobyQSYU+7F2lK/Im4VqeG1GlWvXthUz1OVVFMtJxcrcE7akOtm/y+cQw1c8XcAmzDg1gCPpzDFszZhQT8PoJ+L4JEglKtxZg+kWMrAt31zZinEEy2jkZ/xOKCLD5XkEUoFOL/XthLZ5yytq6RfiRSOYq0iXr2VuClGjdu7xGuuXTu9C5CkhgcDgcvvfQSkAwrTpLkWEQh+m8m2oFomdLTLVVaXFxMVlYWb7/99rgTKhAI8MEHH/CTn/xkfDun08k111yDUqnklVdeGS+nFo8xG+9Pf/oTKpWKdevWnXL/lEol1113XYzuTnd3NwcOHKCmpoaamppTbhtOwZC9/fbb2bRpE6WlybyUi4nu7u7xulH33ntv3G36+i0cOXSA9Nxi+jvayC6aPLs+6rQTDPjobmshNSML0T7MgmkOUKUSGZFIhNLZ88bDgx0jVnKKY++5YCDIQHcngkTCC3vsmNRt5OlVKKUC/mCAUaed3JKK8e0FQSCzoIhRm5XWrh5KCyardp4OvZYBtKbE/hC13kCRDhbPmzNp3V1XraaxpQ2LYwRBgJKiDPKyo9vNtH9BJRPwTrE+5Hez/VATs4tzyD7quQ6FQry4aS89QRVDgwPoTIXY+/sxpE/UyXXbbYTDofHQ4jHcjhEGBwdxu92nVIssHlu3bqW1tRWdTjeu0pfk/EYQBD51wyo27jxMw6APlz+CTiGhIk3B+itXnlLoEsCyOaXsfacOhSl+Tmdp6tSe3nNNcUE2xQVTl8QZo7WjC78qi0RXSqo1A520dvSyv3UEpx9SlLCsIp3ykvxJ2/t8PhqGQJoSu1yfmoVtoBuPcwRzVjGCRILPbcfvGaAoFa5dXoVWs5B//+M7iBINEqkUR38npqwC7APdqHWGSccSTvD7qhWxo0OZTMYl8zJo2+ZCqoztYNDnxpw9OSRbqtDyfq2Ny5f5k17E0+C5557D5/Mxe/ZsFi9efK67kyTJh57R0VFaWiai6drb2zlw4ABms5mCggK++tWv8qMf/Yjy8nLKy8v50Y9+hEajGR/Pu1wurr76ajweD08++SROp3M8Pzc9PX38+/vrX/+aVatWodPpePvtt/nmN7/J//zP/2A8Li3udMnPzyc/P58bb7zxtNuatiH761//mjvuuIMtW7Ywb968SW7pL3/5y6fdqSRnn7GySlOpE77x9jvklFRQXDmH3rZWvJ5RiqrmjgsDdbc0IlfKSc/OIa+4hJ7mBtbNK522N0Qik2FMTUV5jEdQOE58KBwK0dvWQmFlrBDIoChiqd9FUOsmuzh+7pnOlMrhDsuMG7KpZiPeditqfXQQ19fZTiQcQSKRIIoioVCAefMSTwBVlpXMuNEaj4VVJbzX15FwfSAEh/1m9u3pRxjZQXZmJq29/aRWLMLt7MWYnoXP40YQwwx1t5OeXwyiiHfUQUbB5GuuNZhxWQemnP2bLmPe2DvuuAPtKeQJJzk3SKVSrl29gPhFBE4NnVbLqgItOywO5NpYA0pq7+KqK2au8PqpUltby+zZs0/bM6xRqYiE7EjlU0e5/HWnC0F99D0ehEPbnKzuOsBNly+I2c4yOExEaYprGJsy8xEjEXwd76NMMZKhk7NocQ5rFlaMR2t84qpZ/PHtBrwuO4IgYLd0Y84pmtSW22HD5x4G4r//wh4bK2ZPVkmeP7uEtcOHebfeikQdnST0ukZQaRNHpoRVuew+2MKlyyZPGCY5OcZEHx944IHzKpohSZJzzjkqv7N3716uuOKK8b8ffPBBIPqMPvHEE3zrW9/C6/Xy+c9/HpvNxvLly9m4cSMpKdFJwH379o2XuzleRbi9vZ2ioiIAdu/ezUMPPcTo6ChVVVX83//933mvQTJtQ/bpp59mw4YNqNXqcaGVMQRBSBqyFyDhcJhNmzYB8IlPfCLhdrtbe9Gb0ujv6iQtr4BwMEjdvl0EvB50BiO2oUEQQ1x2bVQYIq+8ihaLhfJpxtYr5AoQps6mt3R3UVBRNWm5IAjkVC+h7dD+KT/Aw94A3T296LQaTKaZKW+Rk5WFqrEDMNDRWE9OcWmM4FQ4FKK2s4fykjNTz/VkGTMoQx4XUq0xZt1gdwcppmjYoyLFhKgzcqjlCKaMaJmOUDBIwG9DrU0hu7icjrpDQATH8CBZRYnN8PTCcl56ezN3XHvlafff4/Hw3HPPAcmwtyRRLlk4m7TWTvZ3WLC6w8ikAsVmJZeuXYj2aF3rc8XQ0BALFiygoKCAffv2ndbMdm5OFmnSDhykxF3v6j4CRSBVGzi2noBMrWdb7yglTe3MrZh4H2emp4KvFhTxdQ9EMcJHr13BkuqKuOtnlxbwVY2K3726F4QUECYLjrhsw4SCQfKrqhnoaCA1O/a9HQ54WV0cSKi6fO2aeSyaZWXHoV5G/RH8ikFqXYnLQAiCQDCcNL5OlebmZrZv345EIuG+++47191JkuT8YoZVi0+Wyy+/fFyoM25zgsD3vve9hEJRJ9p/jLEUwwuJaRuy//Vf/8X3v/99/v3f//2s1+ZLcmZ49913GRkZwWw2c/318YWERFFErlIzZ9kl2K1DBLxejOkZZOQVYBsawNLZijZFj6WjJWYgMzDqm3ZupCTgIRI+LulNFCe1k1DNUiZDGye/c+w8+tpbQYzwRoeLUGAIk9jEkpJsKoqnVyIoHisqivjH5j1kl82apJoslckImPOoqatn0ZwzWwJojHA4zKH6ZoLhMBVF+RgNE7kYV5doOdhlYdAdZMjhAYkMfVomKs1E+K8gCKhSjChU2mOWSfB7PehTM9DqjegMJvw+LxpDdEIgEg4z3NsZFfkSBBAjmLPyOdDl4PYZyJN98cUXcblcFBcXc8kll5xWW0kuHqpKC6kqPf9Ev5566ilCoRCpqakzEp515dx0nj9oR6qObSsS9GHWJv4me91u/vp2B/JtA0iAknQ5ly/IpTItQluCtHltoI/F8yYrJx9LfnYG37zzEh579n3sggmfx4VKM2Foe5x20vOjhmdmUSEj/S2EQwICAkLYze3LM7hsRfWUx8hMT+WWq6Ie2XA4zHcf30OQ+O/rsM9OWcF0Ja+SjDEW7XLNNdeQkzPZS54kSZIk5xPTNmQDgQB33XVX0oi9iBhTf73rrrsS5hU98/LrGMyZtNYeRCKVotZo6WpuQKFUUVgxi+H+XohEyCuJDR0TpQoCgcC08pW+9LG7+NWLb6E3paI3mQHIyiugq7mBwopoKHGMsdzTTTAYRBCEqLEriogBD6FgANlxxmRPSxNZRaVIx0o1aLQEgU0dI0gEgbKiyXlk0yEvO4v8dDMo44fRSmUyum0epi5uc2p09/RyoL6Jotxs5s2uYmtNHXu67EhMuUgkEjZvbqJAHeLG1dFQy8rifOZWlFBzpJ4PRhKftzkrn5G+dlTaYsSjdaPFo9rxoYAPn8dFRl4xI5ZudIY0rJZuMgorxt8Roigy2NmE2+PnUH0z82fH9+4cy+HGNva3W3H4I6hlAuXpatYsmYNEIokReUq+h5LMJKNuN03t3ShkMuZUTj8tIh4zLUq2eG4pgqSNTUd66POoEaQyjBIHK8r01PeYgcn1/uxDvcgVamSmuYhAGGj2Qut7Fm6sTsFyuBuPKvYdIPEOceuq3JO6Biajnoc/cxOP/u1N2gYCZBVHva4elx2NfiLiRa5UkVk08Y2IRCL8Y98R3m/zkIqdm9fMpaSoiMMNnWw6NETncCiqGZAh58qFWVSW5CKVSllUrGBHbxiJZHJQdInBSU5mBS9srOFQZwCHO4JeLVBdqOTGK2Ync2enIBKJjHtkkiJ6SZLE4Rx5ZJMkZtqG7AMPPMCzzz47XiQ3yYWN3W4frx17//33J9zuvX2HUetNSBUK5AolAb8Pn9eDwZxKW90h0rNz2fXOGyy95FJ6O9oRgIgoohXEaQ8cTEYjV1dXsKmhlUg4jDEtHalMRk5hMW11h9GolHi9UbminrYWzJk5qI4LH7Q0eRGGuxCzJgajow47KebUCSP2GJQGM/s6+k/bkAWQyJUxYX3H4w9PtXb67D5whH9sq0WfU4wpo4ymfi9PvPt3sivno0ydOB+lKROLKPLy5n2MXS1RFOns7SMsL0Yqk8dtPxIO47INkVlQTFpuIe21+8nIL2HE0oNUrkAileF2WHGNDBDw+8cHsWMIgkBmUSWW9gjbj7Se0JB9c+sB9tnUyFTZoAEPMGSL0PTqNq5ZUMC7774LTH2/JkkyHcLhMC9t2keLU0BujNZCfbt+J6tKTSyvnpzCcLIcPHiQAwcOoFAouPvuu2esv4tml7Bodgk2m41AMEhG+iwEQaBzYM+kemeiKBIK+DGk5U5qxz4a5JkP+qguScdmPQhqM6IgJc8k5dI1+eRknnyZMkEQePBj1/LyuzvY1HgIU8FsfKNOUtKm9uoFfF6cPj2kzeJ/t9qRvvYqAWUxMnUO0qMBJB1e+NP7I3zUH6R6VhG3rlvI6Cu7OdSvRaqOTnaG/KMUaIe577p5/OrpHfSHShBkAgoD+IDd/dD+9z187b4VyZqzCXj//ffp7u7GaDRy8803n+vuJEly/iEwM3Vkk4bsjDHtt3k4HOanP/0pGzZsoLq6epLY06OPPjpjnUty5hlTJywoKGDRovh+wp6eHgSlCoVajVqnR0REAKRyBfbhYVIMxnGPqN/vp2TWhMjGQEcrrZ3dlBZOz0BcuWQR5cVFvL1jL61drchVKoxKObcvn0tRfh4NLa1saulAZzBNMmIBsirmkuLsA98gXa4gojqFoe42Cuck9oUOeMKEQqHTHuSo5RLcU6zXyE9NnTUeNbVN/H17I6ULJpShlSo16tRslJrJeXSCINAf1lGKlY5eC28f7iRiKMLa3UVGfnwhlpH+LlL0JoJ+H3Kliqyicnqb60hJzYjmydYeQKHWYM7IIRiO309RFBEkUg73DLF7Xw1pqWaKCwsmeXu6ei3sGZShSIkVcJJIJFjVRXz/x48giiKXXXbZKdc1S5LkeJ55Zzf98lzkxuj9KJXJiRjz2NTjQiFvYeGsxDmZUzEmmnPjjTeSmjrz4a7H5/dXF+npbe+LWWYb6MKUGRuGG4mEGepswJRVjEKVQ7MXRFUWam8Xn1pfRm5WGqeCIAh8ZO0qbrlKZM/hJloVcvb39KDLLIq7fX/rEfKrlo6L+Un1CiyDLoxG8+SNlWbe3NtN9ayoxsADNy/HMjDM/oZ+IqJAeZ6eyrJVbN5VS3+wGEEyeaQ4GCnmg10NXLU6WZ4nHmPRA3ffffeMivMlSZIkyZli2iP2w4cPj9cpOnLkSMy6pLrdhcfYh+uKK65I+Pv94Hd/IrtyAbkl5ai10fxJp82K1dKHKIrRnFm/l2vu/Cgjlh4ikQiOkRFU6mgY2baWLgpysiZNepyItFQz99xwddx1s8rL2NPYhspclHD/QW+YB9YuIxwOMzIywiFlkJ4pjicKEsLh8GkbspU56WzvdaJKmVwbzO91My8zziDtFOjuH+B///kelSuuilnu84yi1sYXgwFQ6Ixg62RDbS+ytEIkgEohx+tyoE6JVX31uV3IZRIy8soZ6G4nEolgysyhoHIu/XX76LNa0BlM2IYGGOhsofrK2ycdb7i3k0g4hCiC2pTD2wM6GAig3r+TZcVGLlk4oTy9r6UfRYIamQCvvRqNHkiKPCWZKfoHhujya1EoJr//ZOoUdrb2npIhGwwGefrpp4Gzd7/On1VCb3sDYjAA8qhOgChGkEhj32kjvW1kFMaqKPt9HkZsEX7y9B7WzM9heVUW+bmnVi9eEASWVVeyrBrYsJvGwOTc+FHbMMaM/BhF+pH+LvRpRQnbtfjNHDhcz4J50XdGVmYa12XGGt21Xf5JKvfH9quu289Vcdd+uHE6nTz//PNAMqw4SZKEnCPV4iSJmfaIfaxMy0ywefNmHnnkEfbt20d/fz8vvfQSt9xyS9xtP/vZz/L73/+exx57jK9+9asJ23ziiSfiKu96vd7kDONxjKkTSqVSLrvssoTbGfPLKZu3MGaZ3pSKTm+k5dA+5Aolw329uOxWRu0O+iMdGNPS8bjdWAcG0KTo2FfbwIoF82a0/1kZGdinWB8IR2PspFIp6enpFHl8tHa5UCYw8oyyyIzkT5UU5NNvPUyr045GbwSiHsnupgZSpGE6I1mEQi3MqTw1Lw9Ar2WQ372+E21qForj8nEFhJNSp5Mbs8ajEDPyChju72XIPoxCrUVAIOgaQqbRk5EXFdDJzC8m4LRSIQwwv7qcnGsmBjvBYJDhERuP77Cg0k8Y6sO9HehM6bhGBjGlZaNQT3jPQ8p8Nvd5iETqWLM4Kn7lCSTud1f9fgb7utBoNNx2220nPL8kSU6Guk4LipTEyuWDXilerxeZTIbP50On053UpO2bb77J4OAgmZmZrF+/fia7fEKuq/BzqNuO0xdBr/czNDqCQhd9LsVIBIlMFnMO9qFeBATMOdHa4PuGYdfbQ1xa2M9NVyw4rb7cdsUC/vjabvrETGTKqHEdFYRroXBOrJCUGInEzXsdQ6HS8ug/3uNOm4/rL10Q93cIBKd+9wVCJ343fhh5/vnn8Xq9VFZWsnz58nPdnSRJkiQ5KU7Z9dTS0kJraytr1qxBrVZPW5kWwO12M3/+fD7xiU9MOTB9+eWX2bVr10kr6On1ehobG2OWJY3YyYx5Y6+++mrM5lgvocPppLOnl+FhKxqdnv7OdiAa4pmRFw0JlUil6FPTGXU6WHrlWvraW5mzZMV4YWWNLgXSMxkZGqBrYJiptS+nj04uxTbFfZeiiB0QlRbms6t5G8E4hmzQ56E6yzgj/fL7/YTDImGHne7ePkK+UUQBcmctQCZXYAMGnD4Ovb2Nm1afWnmQp97bi0JvJmAfmbROqdFiG7JgIL43JeCavA9AWnY0h87ncSN39vHZj65jx8F6uuwWghEwq6Qsmp9LXvaCSfvK5XKyMzPIVrRjO7osEokQiUSQK6LP3rFG7BgylYZdHd1csjBabzdFJYkmtAHBQAD7YG9UW0EqZd/GaMmd22+/fbw2WpIkp80J7Br3qIOn3jtAz6hARKpAL/iZk6Vm/ar5U37zxt6vH/3oR896TubS6gpWLZ6IgPntCzvpiUTf8T63A7XOOL7O63ZGnz1zdkwbMrWJrT0esg81s7S6/JT7olAo+NdbL+FwYxsNvUM0dw8xGFSTYp78ftIYTLhtQ2gN8aMynNYecmavYMegjK2/fZV7r5pLdVVJzDYZRgm9A4n7k54iUN/YhscboLIsH50uWYcaYkXJktF1SZIkICn2dN4x7a+r1Wrlzjvv5P3330cQBJqbmykpKeHTn/40RqORn//85yfd1rXXXsu111475Ta9vb188YtfZMOGDQlLwxyPIAhkZWWddD8+jITD4XF1wmNrxXm9XjbVHMYhykGuoKFzhMJZ88fVYUPBAF3NDWQXlqBQKjFnZNN8cB9tB/czZ9lKpFIpwWCAwb5eBCGar5makcVwi3XGz2Hx7Aoat9SgzcwbX+ay2xh12NHq9cwz6ybtc9PKBby28yBOuR6lLhpG67VamGVWsmze1CUgToYRu53nt9cipOYjpJpIOZoWN9TTgWd0dFyFWaFUQWYh7+w5zM2XJZ797u4fYFdjN33OACKQoZVRoFcyihqNNoWh3s7x3NVjkStVeFwONMeFCkciEfIVPjiuutGxqDRaVGEtMpmMSxdPz4u+fmExf/qgCXVGESP93aRmFzJi6cKcnbgsSlify//7+xuUFuaRb1RysHkY56gHRJHUnGg+nHfUycH3o2HFybC3JDPJrMJMdu22oIzjlR2121Ao1Iyo8tEcfcQiwEF3GMfbu7j76vjTc1arlVdffRU4P+7Xe9fO4fevHsQqzUOu0uC2DaHWRc/XYx8e98Qej1ShYU9LP0tP/9XIvMoS5lWCze7gN283Y3OHCfq9yJUTpdI0KUbslia0RA1ZMRLB73UhV6qRSOWEQqMoVNEJt1FFFr/452Gqd9XxiY9chkEfndy6dGEuNf8cAOXknGR7fx0NbgUH+k1I5SmwrYHqfJF7rlvwoRaAamtrY/PmzQiCwMc+9rFz3Z0kSc5fkobsece039xf+9rXkMvldHV1MWvWRG7bXXfdxde+9rVpGbInIhKJ8LGPfYxvfvObzJkz58Q7HGV0dJTCwkLC4TALFizgBz/4wXhebzz8fj9+v3/8b6fTCUTDJYPB4KmfwHnMu+++O65OuH79erZs2UIwGOTNnftQZhWiA44cOkLxrGpAhEhUxUcmlZJfWoGlo4Wc4jL8bhdel42s1CKMJhOWzjaQSNDqdHhcLlz2EYb6etCqlAQCgRmd6ZVIJKwszmRHew8RuRqnfYQUg4msvAIcgxb6RRHriA19yoRBq1QouG3NUvosA3QP2ZAKMHdFFSqVakZ+641765Cac0GMxHh6MnLyGexqQW+INSxHRBlDw9aY+q5jtHf3sbFxELk+fXxM5gTerm9AptKgNxjR6XRY2uooqJwfs29aRha9LXVInArk6QVIZXJCNgulRilXrZrPO++8gxgOJnyX5qYoTul6ZKaZ+MyVVfzlze3YLDbSsnKRiiIyQQQxvhKUgMhgRE84YORIu4OIpQ5Nxhw0KUYgeh1b9rxLwOvGlJ7F0qVLL9rncqYZu07J65WY9FQTBfJmBiMpk/KWPCMW0gsrJ927Egm0uTW0d/WQlz3Zs/jkk08SDAZZsGABs2bNOmvXP9HvrdWo+Oqdy9hf20LHoI8jDhsCUQ+sXCoiJYFKG9DZO8hfXt3LgDOIXCqhLEvBZYvLUJ9ilJNOq+G2hem8uq+L7sEO0vNiVcwz83PoqduJRKZBrtCg1BjxuEfwOIdJLcxDQpiRvg5EILdsASOCwPefPUS5wc/Hb1pFZpqJ21bY+eeOLkTVhFKza+AIekMOEbWJaFG2MKjTOTIk8scXdvLJWy+8cNqZer7/9Kc/AXDVVVeRmZmZfF+ch1ws7/ILvf9Jzj8E8WSS6Y4hKyuLDRs2MH/+fFJSUjh48CAlJSW0t7czb948RkdHT60jgjApR/bHP/4x77//Phs2bEAQBIqKivjqV786ZY7szp07aWlpYd68eTidTn75y1/yxhtvcPDgQcrL44dHfe973+Phhx+etPzpp59GcwphnxcCjz32GB988AHr16/nc5/73LnuTpIkU/Lwww9TU1PDnXfeyb333nuuu5MkyZR8/etfp7W1lU9/+tPccMMN57o7SZIkJBKJ8LnPfY7BwUG+9rWvTamXkSTJ6eLxeLj33ntxOBzo9ZMn8M9XnE4nBoOBLz5aj1J9+qlNfq+LXz8464K7Ducj0/bIut3uuMbd8PDwjBYa37dvH7/85S/Zv3//tLx4K1asYMWKiXCv1atXs2jRIv7f//t//OpXv4q7z7e//W0efPDB8b+dTif5+flcffXVF+UN5nK5uOeeewD4r//6LxYuXMjbb79NSlYenpR0RFFk3+7dFM9bmrCNSCRCZ90hVCopTquVNI0MmTkqHpRbXDbpNxNFEVd7Hfddt27Gz+eDfYexquKXthBFkQLRydJ5s+Kun0lqG5rY554632qwtZaSOROlHwJeLysylBQV5MVsNzA4xAtHhlDpDMc3wVBvFxFRRJ+WgUKpJhIJ09vagKWjBalESjDgZuXylYRTMpArVfg9LlJCTtZWl5KZnkowGOTtt9/m0jVr+OBgM52OIKIqhYBzhJDbiURrBpUeSWCUQoOUqxdXknIKeWTPvr+fI70uzDklDPW2kZ5XOh6iPkYkHMba10Zm4YTw1UBXbCiy0zrAgYMHAShY/3ncWh13XDYDsY4fAsZ+63Xr1k1bNfzDyOiom7e376fLHsGLBqvTjVQhx5iWFlcJvFwxwnUrY0u5HDlyhNbWVmQyGQ8//DDp6Sdfi/V0mc7vPThsY/OBLmqaLGAoQaGOTcUIBvy4RywYMuKnBcw2DHDnugUz0u/uvgE6+mzIZCImrYa/bA0gV8YfLA507ydvdmyElX2gCwBDej6CIBAJeDELQ9y5ppzMdDORSIR//+1elIbEZeBWFdq4ds3sGTmfs8VMPN+bN29mcHAQvV7PQw89dNFO3l/oXCzv8rGIxwuVpGjx+ce0Ddk1a9bw17/+lR/84AdA1JMaiUR45JFHuOKKK2asY1u2bGFwcJCCgon6d+FwmK9//ev84he/oKOj46TakUgkLF26lObm5oTbKJXKuEa4XC6/oF8YiXj55Zfxer1UVVWxatUqQqFowqQgkSBIpfR2tKM1pROORIWUBnq6EISoEq7BnIYmJQXniBW/z0NWfgUj/RayqirotznRGk0IR0s9jDqd2IeHALBbB3E7HPzp2Rf5zEfvnNEQ4yFvEIkmvtKlAAw6Amfld8zKTMd7eABVijHuer/Pi1ShoK+rk5yiaE6a1GOnvHRynp3TNYpcZ0SMU0YiNa+I/vZmbIMDeH1egv4g+tQs5l42B0tHE27bEJ2OMIJrCAkRlCo5itwCXtnfxifXGsevRYpOx0cuX0YoFGJwcJDnd9oJFR07QDTRBzz1QS3/sn7xtAXTyjN09EnSGexqQ65OwdLdhlqnx5AWDWl0DPfjczvILqpAPOZ+CAMRYeL33P/ePxEjEQrnLMWcW4pMMnRRPpdnkov1XTbTHGzp47AnG+nRfEvj0XlM62Anhghoj6qQA4RDQXKM6knXdazkzg033HDSAoUzzcn83rnZGdyTncE918JTr+/ikF2NRKYYX28b6seUVUI4QQLCkd4gH52he6qkMI+Swuhk3j82HESiTE8Y7CyRm4gw8X5wDveh0JpRaQ2IHM3oUOgYQcdf3m3h2x9diUQiIRSRIBOnqOEtSC7YZ+R0nu8nn3wSgDvvvBODYfLEaZLziwv9XX4h9z3J+cm0DdlHHnmEyy+/nL179xIIBPjWt75FbW0tIyMjbNu2bcY69rGPfYy1a9fGLLvmmmv42Mc+Fre8TiJEUeTAgQPMmzezpV8uZJ544glgsjphmlZNa8BPJCKSU1hC46Ea1DoDmQXF4540+/AA9uFBgt5RsvLyGertoaC8AhGBoNtF+qyod2LU6cRlH0Gl1tDeWI9Ko0Wp0dHtEXnoj89Rlann3hunFvo6eWIHWpFIhKG+HqRSGalZ2ZPWnymyMjIwim34MMZd7xzspaRyFh6Xk5GBfjRKBSuLs+NuW1yYz8bWw6jMk9cLgoBMKqWz4QiphZUUjF1zuw2lJgVjRi6jtmEAwqKA2xOkt72NnKJidh1uYtWCWO+0TCajqddK0FQU90oFjQVsO9jEVcun5wVdNn82ta9vRVpcgd/rgXAAr3MEr9NGyNZH5pwVmDMmi7IJRMb/Hw6H2f3GUwBULL0CS3sD61bkTtonSZLTxe3x8F6TG6l+8jNnzCjEZmmNMWTVoz0smXfJ+N9+v58P9tTyhz89AcDKNVedkpr/ueCj1y8nf3cd+9oHsXlAo4QUgxfnFH33BATC4fC4Sv1MEYycYIPj+hT0edGnTp4wECMRuoZDfP//3segNyKLuBIf02cn4nfyv8/twxMQMWslrKpOp6I0sQf3YsDtdvOPf/wDOD9EyZIkOe+RHP03E+0kmRGmbcjOnj2bQ4cO8bvf/Q6pVIrb7ebWW2/lC1/4AtnZ8QfliRgdHaWlpWX87/b2dg4cOIDZbKagoIDU1NhwUblcTlZWFpWVlePL7r//fnJzc/nxj38MRHPpVqxYQXl5OU6nk1/96lccOHCA3/zmN9M91YuS1tZWtmzZgkQiiVErBqgsK6Fx6x60Oi0u2wgqjY7sotKYbYxpmSjVWoY7XbidDvKLS5Ar5IQGOklPUREMBpDLFTisw+gMJlrrD6M1GDGmppOeE51xH+ztotU6zLOvb+Su668+7XMyq2Xj9WT7OtoQEcjIzSccDtHX2U6G4D3tY5wsV1WX8fK+VuTHDaxsg/2YzNHZbk2KntH+Ti5fuYDC3PjPjFqtplAnEK+KxFBvFz2dHWSUziGjYCIk1+O0IVMoCXg9pOdPqJD6vR76Wo6QmpmFRQjEPV7HiA9BaUx4Xp02f8J1iRAEgY9ft5p3dh2i2eVDopKi0xspTVMwK38Ofz8QvwyQIS0Td38LclMutdveYqS/E7lSxYobP45So+O9ph6yMofIyzp7IZtJLn52HW5DEseIHUMUJdGSUiE/+sAQd142Z9xI7bUM8dTWFuoamnCMDKM1mPGVXcNvXtrGJ9YvOqUSW2ebNctms2bZxN+bd9fyektiQ9ygYsaNWICCNAX7LeGE9WQDXnvM30KcqJVIOISluYnUrFl4JBI8AfAIERRuOyqtMWZbURQJWevZLFmCVBb1FvV74dBbTq6pPsI1l86d1P7FwgsvvIDb7aasrIzVq1ef6+4kSZIkybSZtiHb1dVFfn5+XHGkrq6umFDgE7F3796YcOSxPNUHHnhg3Gt4Mv05Nu/Obrfzmc98BovFgsFgYOHChWzevJlly5ZN0cqHh7GSO2vXriUvLzYvUxAE1i9fwKaaI9TsP0j15evjtqHW6pCpNagkIgazGZfdRnlWOgX5uTy/6wj55VUIgoB9aBABCdn5RTjtNvo6OxAQkcnkFM+ay6G9O7lzBjwWC0oLeKu+m2GrnYz8QmTyaHicVCYju7AE/6iTmvomFs6qOEFLp092Rhp3r5Tz+BubCauihquECOb0VFIME+U9MtPTEhqxY1y3oppn39uDQ5WBXBUtUdHf2UpnUz2VSy/DNTI8vm0kHCYY8COVKzCkx3o5lWoNBbMW0la7n+x5xXGPFTmB5Ft4WpJwE0gkEq5euYB40xVz2vqp9/uQyWNDlvUhG/deXsqfNx6gq24vALNXrUd1NEcxpM/nd6/vZ2l5JnPzUykrvri9JknODv7Q1De5XK5gnmKQokIzcypWxax7cUczEUMB+9/5EQDzr7gFhUrNqKqIV7bVcs+6xHoD5yurF1fx9uHdBDWTv+miKFKdr4iz1+mzanEl7x3cyaikaNI676gNt6sPn7sUlXYsDHby7zbU3U5q9uyYb4shNRfbYCcuu4XU7HIkEileRx+GSDdixlIk0tjhkFShZ0PNCHNKB8nLyZjJUzxvSBSdlSRJkgQky++cd0zbkC0uLqa/v5+MjNgXu9Vqpbi4mHA4sYz/8Vx++eVMRzQ5Xl7spk2bYv5+7LHHeOyxx066zQ8TkUhk3JD9+Mc/HncbnVaLXCIlo6h0yg+bGBEpmlUFgM86yKqbrgJgbnonvXYbCNDZ0kBGbgE+n48Ucyou20g0BDkUoqOxHplSxTsfbGbd5aenkpiZnsZiq413Xe5xI/ZYlDo9h3u7WXjm9Z4AMBkNVBZk49XHGpSiKDLU10s4FCRdceL7XqlUcv+1l1DX3EarZZDDzZ1YnUH05gzU2pQYQzYUChLw+8gpjT1Jj8vJqN2KIAgEAkFy9PEHn+laKfYpHt1M7cx7Xm66bAmZB+s51NvHiDeMUiqhJFXBFVdVI5NJQWPm0KZo7dhF6+4AwDHUT8DvIxKSs/FgD0fsSooatvPR9SuTA7Ekp0W6XkF4MDjulTsekzLMdWuWTbrPGls7scvSCLns1G3fCMDiq+8YX99ij9bnVqvVXEhIpVLuWpPL01ssRNQT77JIJEyO0MnNV8SvoXu6SCQS/uXGSv76ViMDwUxkcjWiKBJwdFBmcKCeNZuBzlo0hgyMmYVEIrGxyAGfl1GrFTEgQyKVY0jLG9d4ECMRJFI5nQ1bkCoUSGUSvFI5ZsPEUMjjtOJz2xGOjjT/+HwPD35yzSkJ3p3PdHZ28v777wMka8cmSXKyJA3Z845pG7KJcn5GR0enLQaT5OyyefNmOjo60Ov1MWWOjqXXMkBXUIlUOvWtIVdEDSLvqJMVlRMz9mtXL6euuY2NA334RkfRGkwoVGq8o6NkF5bEtOHzeNixZ9NpG7IA3kCAjLyihOsjujQ6u7spzD873rsCs45ab2DcsB7s7SEQ8JOek4dcocQx0Mcrm3dzzfL5J1T7TtGoaOvqZVRpxpAhwe2wAdEcsDHkCuWk92J/WyMag4n0vKgXVmdKo7ZnhNnF7pjthkdsKPDjHe5FnTY5/zTiHGL5ypOPtJgOy+fPYvn8ycsbW9porj2Id9SBPi2LwjnL6G+rx5RVgP6oWFQw4KOnrRZXehZvbT/ItasXnJE+JvlwsHhuBe/Wbscrm6zSK0YiVOeo4n77Bmxu5Co9+95+nnAwQFZxFdmlE3XPJbo0unr7qSwrmbTv+c7c8gK+kWZgc00H/Y4wCgnMztewYuElZ3TiKDszlX97YBWH69voGbahksPKBVHBuSfe3IM6bRnW/k76mvaMT9Sl5pQy3NWGGFaSV7YSgFDQz3BfM1p9Gi5bP2k5lUikMlKzoykZwaAXe3/7+HGd1j6kUjnmzImUmlHgsSeP8IU7q0g1XzxiSGOT2ldccQWFhfGVqZMkSZLkfOekDdmxsF9BEPjOd74TI9EeDofZtWsXCxYsmPEOJpk5xsKI7rrrroTegYauftT6VDxuD07rMPrUtLjbScQgXks3s7LNVFfG1uedXV6Cy+OluaGejLxC+jvbyDku1xZApdGQXrUAm92ByXh6AwTxBNNbUpmMYDB0WseYDvNnVdK+aQdeQw526zBKjZa0nIlQbkNmDm7gla17ueOq+LlJrZ09vHWgjQGvgMpYjMRpRxRFIpEwAZ8XnSkV+2A/xoxsBEEgHJ4oND7Q2Up6fkmMd0ml0TGKjhe3HCadqDjNS5v30R9SoTLkIcgtDLbXklpQiVQqIxIOI3X2cn11Ppnp8e+DM0Vmeir7N/wdgIVX3Ya1v5PMoqrxwbPN0kMw6MeYUYAIbDw8gFHXwMr5VWe1n0kuHgRB4O5Ly/jbphaCKQXj91rQ56ZEOcwNa1bG3U+rlBAOh9j/9vNANHrgWCMv5LaRlVEWd98LAbPJwC1XxpltOgvMm1XC8TKNN6+s5A8bapHklZCeV4K1tx2lxkhX3W6M5tkxNR5lciVpORUMdBwmNadiUviwXK4ez8UVIxFCfi/6rMnCUS4hj5fea+bTty+Z8XM8F4iiyF/+8hcgcXRWkiRJ4pCsv3PecdKGbE1NDRB9AR4+fBiFYiJEUaFQMH/+fL7xjW/MfA+TzAijo6M8/3x0oDXVh+tIUws2sRd1SgrSiEhfezMSiZSsY7ypoz0tXF6SwaLquQln5ZfPn8POuqiQ11Qz98bMHLbsP4Baa8AfFtHIBBZXlWCYZv3esvwcDh9sR2OKLwAUHLFQsmj5tNo8HQRB4JbLV7L7UB3b7ENkV0wMx4b7ewkGAiCK6FJSaO/uoTg/Nl+51zLIy4f6UaQWE+lqR6s34naMoNGb8fs8DHa1klcxl1AgwEBnM6nZBWQWlOEcHiAlNRr2Hy9E0jvqYmBwlPR0+PVzb2GoXILqqGBLamYW5oxM+lsbKdFLmFOcy+IrV52TkF2f10vrgR0AzF1zEwqVdrwfI5ZuVFo9Rt0x18yUzobWUQLBOsry0ujoG0KtkLFwTkUy5DjJSVOYm8m/35XKln0NWFxBZALMnWVmVlliIZxFcyt55r1n6G6oQSKRsuCqj8Ssz9eGpv0+u1jo7LFwoGmQkAglmRoWzj05g77fMkTfoJW87HQy02NFH01GPV+8cT4f7G+m3RrAHgmgNZhRq9NijNhjSS+YjWOoE1PmZK+4RCYjEgnjGOrClBFfQwCgvitMIBCIGftcqGzbto3W1lZ0Oh233Xbbue5OkiQXDEk79vzjpA3ZsVyKT3ziE/zyl79E/yH9MF+oHKtOuHJlfM/CU2+8h1+XSaYpFaVGOy6iFQz4ady/C0NqOqMjg3z9jmswGSZ+f1EUcbvdKBSKmI/8gopieiIRJFMoW/a2NaMzmNEpzADYgeZdjawqNDGv4uS9GGaTkXRJgNE4oe+hgJ/yNG2MKNjZQBAEllXPZn+fA4BRpx370CCpWbnYrUOEIiI9nR28MdDO5+/OZc/hemyeIEqZhH67B4UpZ7wdAFNGDs6RIaQSGf6Ah96WWvTmDDILyxju68I+0IvgsUL5EjTHlAkZY7C7HblSTUbRbHAfIJQ2i4M7dpKZm0lOcdn4sXLKqog4elky79x5N5966ikikTAFFXNRqNQYM6Ihz6IoEg4GUesme/Blah2v1jQi1vSDTEEkHGbDkQHWzsli6bwzL/SV5OJAJpNxxfKTV6oVBAFb3WYgWiIq5ZjJNKmrj/WrL7yQ4tMlEonw55d3UWc1IlNHozl2dPl5p2Y7n7pxLmZj/PFDr2WYFza10jWaglRlJLSrn2JDK3ddVU566oRYnkaj4dpLol7i59+t4YgbIlPk+Ee9rvFHjsbMErobt6PVZcZVQB4jgA6Hw0F6+oWvlj4WnXX77bej1V5cub9JkiT5cDHtkf2f//znpBF7ATIWRjSVOmHbiAcRCPh9DPV20dfeTMDnQ65QklVYgi5Fh1apiDFidxw4wtPv7eLZvY38ZXMNL27eTVt3DwDVpYV47cOEQ/FDegd7uzBmZKMzmWOWa9Oy2NntwGZ3TOscr1+9BJ2zD49taHyZe6iPXNHJpYumVwP1VAiHwwnEy0REUcQ2aCHFlEZfTw/atBxSc4spnLuEgbCG7/3tTXbaNTSHzRzxG6kdGB3fW6FS4XO7kCujOej61HQ0KQZ8bheWzmYa925mqL2e66pz+fV/fJ7ryjWEA76YHoxYetGZ0tGnZRPwegAY7m0nJS2HUS8c3rOPvo7W8e2HvBFCCX63M40oiuMDrS9/9pPMNnjxe6I1IG0DPZiy4uc5e90ufEERpTEbY2YxpuxSBkYFnt7eTn1r19nqfpIPGeFwmDdfewWA9desJTzYhLVpP+GeI1QaIP0iyqs8WV5+7yCNo/nI1BPnLpUrGRaK+OubdXH3cThd/P6NdnpD+UhVRgBkajPdgTx+988mPN74ZdTWLilD5e4+iV7FF9gTBIGU1Ez8geGY9IzjkYZHMJlMCddfKHg8Hp577jkgGVacJMm0EWbwX5IZYdpiT0kuPDo6Onj//fcRBIH7779/0vq6hiYASuYuhKP5QobU6KxzT0sj2UWlGFLTad6/gwXlReP7vbtrP4NyA8pMI2NyRRFgW3tUTbckP485ZhWbrcOEgkFk8thQ12AgiEoTfzZYbc5gf1M7Vy1bcNLnKZVKuWnNcmx2B81dPUgEmLN63imrhQ5ZrTR19SMAs4rzE+bx7j5UR53FiT0QQYJItk7O0vJ8inKjuavpGgVdXR1k5hXR09VFdvGEdzDg9yPINeOCTGNIpBOebWN6Fj0tDeSUVpGanY/TOgiIGFIzCQZ8VBkF7r12zbho1LIFczncv2u8tm70OD4MGXlEwmH62huYUyght2weEWHCW+60DtDT1kJeyYR39lxQU1PDkSNHUCqVfOqTn8BoNPKbf+7Cjp5IODQpzw2ixq9jsJfMogkvsiAIqHRGnMMe/vDqLu6/2o/HH6DXHkQiwKxcA7PLE4cSJklyMrzzzjv09fVhMplYd9U6tncJqHMr8QN7nCL7/r6XO1flMqfszAimnW+Ew2H2twcQ1PHnyeu6/Tz2ty1EpGp0SoGFpTqWLajk/T1t+BSTxeYA3Ip8PtjbwrWXHp8xC0ZDCp+5djY/+9s2EpmhQa8DQYgfGeTz2FHpdaQVljDU3II5ozzudk6/j/99YQf/evuqM1I/92zx0ksv4XK5KC4u5tJLLz3X3UmS5MIiqVp83pE0ZD8EHKtOGK/O786GdrISpP3kllZg6Wwju6gUvcnMrJxovpLd7qDbBzrtZMVdtTmNA+19lOTnsXLBHMwpGl7feRBtdtG4eFQoGEQMBqbs92ggMuX6RJiMBpadhnhUOBzmn1v2MCiqUBui53toXyu5ijA3XLIkxsB7b/cBWoNa5Km5GI8ucwMbGvq5RoSivGzm5afTNtSMpaebUAS629qIvsVEnNZBiqsn5+5GjouTy8gror+9EZ0xFX1qBjpTGtbOBgq1EZbPqZykfHxpVQ4vH7YiTYn2XxAkjFh6GLUNoVCqAT/DPe0Yc0vGQ671qZn0tw0jiiJZWuk5G6yNeWNvvvlmjEYjAFfNzeEfNcMY0nOwD/Zgyoz1yo70d5KWNyEoJooiAx2NhMMhHMMWJIKEn/1jF36PC7lSwdzV13Ck3ktu/VZWVmVjdfrQaxTMn1WWzKlNMi3G7terr72ebf1apDrd+DpBEBD1BTy7o4+vZ5gw6OPncF5MWAYGGcVEPC324d4WUozZ9Is6CMFACJr2+anr2MmId+rhSKsl8ffCbNTzpbuW8ZuX2vHLY8WaIpEws9Os7HUME/CaURyTR+sdHcEfsGHIzGWkr52AOIptuB1T2sQElxiJYB1qJLWwhJ6IkhffqeGOay5c0aex+/X+++8/6+k2SZIkSTLTJA3Zi5yTUSf0S5SAJ+46QRAQJBL8Xi96v425FWsBqGvvRpeauEj8cCBCMBhELpdTWVpMZWkxlsEh6jv7CIsiaToVgnnqEHWF9NwYFK9t3YszJQf1MQaN2pTOcDjMhh37WL8qOohxjY7S6AihNk8uO6U0prO7pYeivGwqigsR399BrztCxeJLYwylcDh+OSu1To/LNkyKKWr4K1QqcksqGXXYadm/FYEIs5esRCaX80G/j90tW7njskVoj6qJVxTn8xFBYFtDH13OMI6hfvIqF2LKzEMihsFzAHNOIX1t9WSVzBof0GQUVtLXXM89qypn7oJOg0AgwNNPPw3E3q9Vpfncp5CxpbaP3bY+Ium5MYMwMSLGiFsN97QhSKQ4B3oxpOVgysxHrtTgcY7gHBlg/3uvUrn4Eg7bA3RHQihUBsKhIBuP7OD6RbnMKUuWo0hyYhwOBy+//DIApYvWIlXq4m+YksPWA21cv+bcqP+eTVJ0WggNALHXwmUbQKtPR6GOXS6VKzkykoVgP4wkY7Ji8BgnUqbPzkjlX28SeWN7F/U9AYKiApM6yOIyJZlmM92KIpzDFpz2QRAFfB4HPp8dpdKIo1eGIbUYg17APthBR9NmlCo9gigQCgVQp5iwW3pIyy/hUE+Q2yKRC9II7Onp4d133wWiaUZJkiSZJkmP7HlH0pC9yNm6dSttbW3odDpuvfXWuNsIRD2fA10diBLp0aLxEjLzi6LrBQFrfxerqybCNk/kK5VIZeOG7BhZGelkZUwIZTg8B+lKUJc44HVTkXt2S74AOJxO+oPSGCN2DIlUSvtwcPy8DjV3oDZnJmyr3xNh2Grlhe11uFQZlFdO9vYl8v4ZUtMZsfTR1XiYnJJKZHIFbocNl7UfvV5Pel7BeKi2XKUipCrk9Z2HufPKCe9ueVEe5UV5tHZ08ze5DoVaE3MMiURCVsksrL3tpOdHvZlSqYyqVAWzyopitrU7HPQPDJGfk4VOl2CwPgO8/vrrWK1WsrOzWbduXcy64vxsivOzue/qhTz79h4anSpkuqjHOeSfyCkey1O29rVjyiwgLa8Ma08bUrkcdYoZjc6IkFNC077NLLji5vH9pDI5QX0BLx+yYtCqyctOPFGTJAnAc889h8/nY/bs2aizKpkqxmTQfWoRJhcaer2e0tQQPcddjIB3FF1W/PelRKZAkE2dAlKcfuLhSm52Gv9yWxrhcBi/349arUYQBHbW1CMIAob0bAzHaDUNd3cgFzJQqCbejcaMIowZRQz1NJCeO/HNEyMRBlob0GekMTo6il6vJxyOKhmrVPFrDJ9v/O1vf0MURS677DKKi5NpFUmSJLnwSRqyFzlj3tg77rgjrjqhKIoMDAxSkKsnI79oPEc2FAzQ1VRPQcUsBrs7yMzJRThGLCPbpKdjcBSVJr5Ro4oET5iburJ6Fp3v7UTIjP2ghoIB0kMOSgvPvmpuS1fPlMapOiOX+qZWqudUEYrEFw+xDQ3gGfUQ9Ht5/I1tpJQuROJuizuDL///7L13eBzZdaf9VlXnHJEzwJxzGk7OOc9ogoJlW1rZ67j2Wuv1yl555bC7/uT12l4nyZJGmpxHkxPJYRrmBIDIGY3QOcf6/mgCYBPdYAKHIKff5+Ezg65bt25V366qc885v6PWEI9GUJ9hZALYyiogHSXqGcA7Oko6EcNotVK9JL9XZzSlZtzjxWHLFSQ50jOO1phfaVMUxRwd+FjYz6ZVUzm8o+Me3tnfQX9UgdJgJ3m8lTpDhns2LrokYZITYW9PPfUUCkX+25Moinzltg2Mu70c7RhEBnQlVfyyK4habyQZj4IgIkoqnNXzGelppbRu8eSLptZgwUI1oigRDQXQGs6IDNDZ2dU8wKNFQ7bIWZiYr1/72tcQlcKMhqx6FiL1fT4f8USCEqdzThtOd6yr4N8+GiWjmfoNCWdxQej1epIJFwlV2bRtmvgg161ZdM7HlyQpp9b9knnVvHW8FdFYPvmZLMskQin0zun3XgCDuZRI0I1uIj1DFDFZaol723B7S3n+43ZahhKkBCUObYq1DVru2Lp8zn4vp4voFb2xRYpcGIKY/Tcb/RSZHYqG7FXMuagTHmlpo7RpCUT7GRvoJS2D2VGCVm+grLaB9iP7sdjsyJkUTZVTBl5jXQ37O3dCHkN2qLcLQzrOW7sPYVCKrF6Qvy6sSqXi8Rs3svNIM/2BOPFUBr1CYJHTxIb1X1zN19MRBQG5gJcYIJ1KolZnPaGVdjOt/WHUpwlW9badxGgvx1ZRSjjgI5XOKv8W6s9WVkF/2wkqGhdNM3THB7opKStDq9dTXtuAq7cbZ3XhVXSNxU7vkGuaIRtN5Te4Jzh9bKb4GPU1SwAIBEM881k7aVMl6lM51GpLGcPAv390lO/cvT7H436xjI2N8fbbbwPnpqbpsFu58bSSHMf7dzAsG5AUSsK+cbQGE/7RQRyVDXmvf2ntIjyuzumGLDDgn5KNSaVSvL/7OK0jcUKJDEa1yJIKLbdsXDZnX1qLXHra29vZtWsXoijy1FNPcaBjlH2e/G3TiSjLFl143v6xk91saxlhKKpGUKgxZTpZXaPnlk2XXo39Qmiqr+DXbxX58MAg7a4EybSMTgjMuI/dpOTODeW8uK2HkYQDhVpPKhakQuvl0TsaMRovPBLEaDCwtETmRDgzWWInFg6i1hRWIdYarXhHuicNWQCVRg+hFD/62EVSXYbKAiqyiTmf9qbwBPbx1N3rL3icl5I9e/bQ1taGTqfj4YcfvtzDKVLkyqX42J9TFA3Zq5gJdcKGhgauueaavG3e+fwYakcVAM6qWhAlvKMugl43JVW1ZNJpdAYjimSEijPCwu5Yt5x39x8jYbCh0RmQZZm2Iweonb8ElVZLFIgCr+w/yeY6Jwsa6qYdX6VSccO6lTOeR0dPH+5ACJNWzcKm/EbJbLFswTw+/3AfmpKqvNtl3wjz12fr8DbV1bC7bRfpU4bsUG8Ptop6FMqs1RfyeycNz/xlebJUNi2i8+AuDDYnklJNJp1AIUk4SpxoT/OiK9VqErEoKk1+T3cqmUCnmq7aZVSLEC98zrIsk8lkSI+28407Vk1+vvNYJ2lTfhXRuKmGXYdPct26c6+3eTZ+8YtfkEqlWLt2LYsXLz7v/X/lns289ukhjruSqLUGIiE/6XQKhWrqemXSKTzDfSBkDfiwz43ZUTpNPVs6taaQyWT4p9d34dbUI+gEBB2EgN3uDH1vfMY3772maMx+SZmIdrntttuoqKjAbLHQ+sYRgppcQb1MOk29aoRlC7Zc0HGOt/fw8tEQkr4K7amfdwITn40miHx6kPuuX31R53GpqK8p49dqpryrHd0D/MMHfhSa6QZ9JpVgVYOB+ppy/vDpcto7+xj1+Smzm2ism518/UdvWcPz7x/g+JiEZCxFkiQy6fzaEJPkuW9LChVJdSnhgId42I9aZ0JvtiNKCg6P6NjaP8TQmJ9kSmZ+XQllJV98ikw+JubrQw89hNF49YuOFSlS5MtB0ZC9ijmbOmHv4BDa8nrMVjsMj0x+bi0pI+Tz4nePodZoESWRBvv0h7HJZOTRGzfT2duHy+OjvaePxqWrEM9Qu9U7y9nZ2U9tRRkazXRhpEIMukb46Ggncb0dldZI0h1nd9durl1QTVNd/lqiF4tCoWBpqYmWaASlJjfkLBEOsqrKlmO43L1hKa/vOoJf0pOIJyeNWAClSk0iHkOl1qDW6vKHsQJhn4f6hQtJp1KEgz5K6xtQKqcbpPayCgZ7uiiracg7dikwysLNG6d9vn5hFUc/G0R5mmdhglQijibq4hq7nc03XZ+jVNzrjUOB6HBBEOj1zaw6fb5MzNevf/3ryLLMx3tPcHQgjDcqo1PAwjI1t25ciK5AyLokSTx001ruS6XYd+gEf/3zI+jNU/M2EYvidfXirFkw+R3ayuvxj/aRjEUw2qbCr+tt2eu/fX9z1og9w1gVRZGBTBXvfLIHq9WESadl8fzp7YpcnWQymUk1+IkwTb1Ox7fvXs67e07S4ooTTYJFI7C8Ssvt12y+4GN9emIEST99QUmhVHHIleGGQBDTFaCG3FRfxfVNh9nWGURST403nYyz3DHK5jWn5fc31pC/CM6FI4oiX7l9HT5/gGPt/QgCfBaN4y6QuhzyjqAz5aZkyLJM//AoxngHWq0dk76eWNjHqLsDg9NOLOTjf7/iRWPPLri+eXSYedYOnrpzRcH71hdBLBbjueeeA4phxUWKXAyCICMIM0e5nWs/RWaHoiF7ldLf3z+pTpivdizA0e5hzPYSOKPUC4DBYsXV20UkFKS6vo6FlYXDuhpra2ishR5PGFGSkGWZoZ5uAERRIJORgQz7T5zkmjXnptoZCod5+2g3Kkc1EyadUqUGZzWfdI1h1GspdV6ale4tq5agPNbCsaF+4iojciaDIRNlXbWdlQtzX6+Od/QRTUvEM3BmyqyttIKh3g7KapuwOMsY7e8mmYhjOs1g8rgGcA90sHLL9WQyGcIBH75RF87K/DUnRTlD1DeO1pJ77vGgl60N+fPmypwOrqsdZVu/F6XeSiaTfXPzjw2xzCny2H94NO+xMjN4kQHSZ2wfHXez/VAbHl+YpgoTaVFD20iMeErGrpdYP8/JogJqwEeOHOHw4cPZcPPHH+eZt/fSnihHVFkRVRADDgeh642D/If71qAtsCDSO+Cie8hNLBzmO/dv4v+9dRhHZVZkyzc6QMmpvOuwb5xYODDpmR0fGiKVSGAtq0QRGmLrpmy7kyNRBMky7TixcAj/+BA7LHa0UTOpZBzjkT3cvqKMZQuKIipXO5988gn9/f1YLBbuu29KMMxo0PPIzbPnIQ0GgwxFlJOe2DORTGUcaO3lhvWzFxlxKbn3xpXMq+ljT7MLbyiDUSOyqsnI2jwlyC4VFrOJrWuz6RMGTTfPbPMiqHJDjDPpFNGwF4MlNwppfKgZlcaBkBGJhb1IkhKN3oJGb8HtakNrM6O1TXmhBY2NA70hOv/pQ27b2MDmlY3ntZg7W7z++uv4/X5qamq44YYbvvDjFyly1VBULZ5zFA3Zq5RzUSf0RpMwwzM1k0mTiIapVyWYV3/2ciSRVBqTLNPT2kzN/EUkEwncrmEEQUCp1rG/rYctq89NDGNfcwcqR/6wVpXFycGOPu64RIYswPpli1i/DEbHxpBEEbs915spyzI/feNDApY6lPZqTEAkGJzWj1ZnIOAexWQvoaS6nnDAx0hfF5lEjIV2NZvmOXnRJTHS101pTT2SQkEsWjjcrdqsZstCJ/s7h3GFEsgylBqUXNtQxvz6/MYvwNbVi6krc/HMB/sIZnRgA6VGx1gkyrG2bpbNnz5Hyo1KOqavcUxSYVROXosfv7GDk0EDems1KWWS/Z+3UNG0DEEhgAKCaeg4FOAGzwluXL9kWl8TYW/XXHsD//zmHoLaeai0029PAW0dn+5v445rcnMDff4gP//wOK0jCdIZAa3Rikqrp35ekq5D26hZuhGlKjvZQ95RZFnGXpnr2Y4GvYTadvK1O9ZiNWc95/G0DGeI9GQyGXyjA5TWTYmRKZRqospqXjnqxqAbpr66nCJXLxPz9bHHHrukhkk8HgepgBV7igKac3OWRU01LGoqfK/6Ilm5pJ50potfvN9CUlWFQqkh6OsnEhpFb5xKL0mnknjHuwh4hnCWL8FozZYJCvlcBNwD2MvnYy+dj8/bCbbsPhG/m0jQjbW0HhS1vNcB7x89xh0rDVy3/tyFq2aDiWiXp59++oosG1SkSJEihSgaslchp9eOLRRG9Mttu+ge8aKNyqQTMWxKGOnvJSODxVmKVq8nHo0wr8TEjetX5e3jTFSSgKuvh+qmBbj6epEUCspqswZSLBJmPBjgk937uHHz2cUwxqPJM8sQ5m6PJAtvnEVKnNPVfls6enh193EEUwlW1WkvsXk8mFZnGQGvm+GOZmxGHRpJoqHcwLqmBdRWZlfu66ur+MVb73FiTx8Gix2/x00sFKRu0TKU6mz/mXSa1Ggvd29ehtNuo6Emfw7vTHze2k+mdBkWUYDoYbQGCyHBzuvNXgShh6Xz6nLab1pUw7bntxHPSKSScdRaA6U1jSTiUSJjQ2jK7Ay/s5+AexSPaQl6a9bi8wz3UjlvugiNQmvi485RVjT5sNssk58nk0l+/vOfA1C28UFcCSNW23SF7QlaXTHuOO1vWZb5t3eOMhDRodBqsVimvjNFyTxqHY2MNH+Kc0E2tzkeCU0zYn2jgyQTcSRVDf/r9Ta0ypMQD5ARVciaEJJSgaOiFlGS8Az34qzOH/go6Ox8eKCThiE3saSM06hk3fIFxZDjq4hgMMjLL78MnJso2cVgt9uxCO3EseTdnoz4mL8yvyJ5kcLEYjGOtHQjCQIrlzaxqKmcH/z4Q7yyE2djLaLUQCIWZejkHgzmUgSlSDoTpW7hjYji1MqWwVKG3lSC29WOo2IByFkjMZ1MEIv4cVTOJxb2E3B70VtKUOkqeeuYH0k+is2so7628qzq/hfL0NAQ77//PnDp52uRIlc7gpBT6OGi+ikyOxQN2auQCXVCvV7PI488Mm37e5/toR8zsegQjipL9kHqOkJJVS2ymPUOZtI2YuEgazZO954VosKgxhNJ4h5xYXY40eqnLFGNTk9V00IOthzhhk2FVYEnONuP/HLdAz7atY99YzIptYmSklyvm7W0guGedsrrco0cnU7HSquT2zbnDzm0Wsz8xlO54b1+f4B3PtuLPyFj0utoKLWy7q6tF7ya7vX5afYqUJoUIOe6WRV6K5+dHMoxZA83d/Czj4+TUphRKZSUldUgKZT0thzAXlqDpXYFPsCTSjPq91FqnXq5E2YYo9JYwp4Tvdy11TL52bvvvsvo6Ch6i52FG29hfHBgxnOJp3MXDA6eaMcjlROPDGCvbJzWXhBFHA2rCI50o7GUozXmhhF6RwZQaQ2otAYifjfW8gYCY4M4GpZNnoucyTDc3Ya9PBslcGYe+ATjg914BIHBU+HI6bEkH53YyVeubaKuanpZkSJXHi+++CKRSIQFCxawYcOlDYkVBIG1tSa2u+JISvW07dWqANUV5xdWfKK9mxN9PpIZKDMpuHb1wllVH5/LyLLMS+8eZH93hrQ661V9ZfcBti7W8d2v38S7u1tpGR4ikpQp0Ymky51onfWkkwni3mSOETuBIIqoNAaSiejkZ/6xftR6K2Nd7aiVZgyGKkLDLsZi7UhqBc9HS1Ab1IifHmdphcBjty1DrZ7+/c4GzzzzDJlMhi1bttDU1HRJjlGkSJEil4uiIXsVMhFG9NBDD2EwTHdrHh30Yigz4aisRaM3kIiGc7aX1tTTsu8zahoaGA6du6DPlhWLOP7LHSRkGYfewNhgP6lUkimzU8ZYWsnxk+0sWzh/pq4o06vomKEMTplh5nC7S0Hv4DDbOsapmLeU0YGeadvVWi328mpGejvJZNLYDGrsOhVLKy2sWnx+eXNms4nH77pllkYOh9v6UZ4hXDI+2EMGkaB3DElS8H9f34tJo8CuSvLuiXE05krMai1aowWASNCPtaQKvXWqH//4MPbK3LDksy1ShBO56ioT83XljQ8iKZRAAfWVU9h1uYZy92gEUbLPaEArdFYswR4C0RBG+5RBKcsyyXgMs7OK8YEOHFVNjPW346zJVUoVRBFH1UI8QydRqvO/9PvGhtGZ7Gj0U4JekkJJ3FjHM9u7+c+P2L80BsPVzOnRLrPpafcHgmw72EmvJ40gQINDybWrG7lxwxJC2w5ycDiDZMrO3WTER7UqwJO3nFu0DGRD4n/05i66k6Uo1dnfcFtUZveL+3j6ukZqKwvXz75aeOndQ+wZLEHUSJNPpaS6mg9ao4hiFw/dlHuf/uFLnzNONmLD6py+SDaByVaJd7QLlNlFtkQsAnElNvuU4WiyVmKikjFXMxqjA0EQiKS0bG/xsv/kx2xcWsbGRaU01FXM2vkWa8cWKTLLFHNk5xxFQ/YqIxqN8vzzzwP5H1y9/QOg1uFzjyEpNQz3dKI5tRLs6u9BUmlwlFdidZbhKKsg6Xed87F1Wi1NpRY6fHGGejqxlZaj0eYq/w73dtMph85qyG5cvpi2D/cglUzPzU25h1m7fmGevaboGxzC7fNTVVaK024753OYiQOdQyg02ZBXjU6fV4VYrdFQVteI7Bng23dunDMhpaebhr7RITCCvaIOV383ZfWLUesMBIAAsOvoISzOCmLhMGbHlNc57HfjOCMkV6nWkohFUJzmLZqp1BCAWTvl1XC73bz55psArL45Gz1gdpTiHxvE7JyeI52Kh1m31EZb9wA7Wobp8yYYH3VjrbEhnKXC+JI6J51jKUbGh7CW1Z66FoNYSquJBL3ozHYiAS9ao41UMol3pBdREAEBWc6g1hnQGew44yeJpKpOGd1TJKIRTPb8ubFJQxXv7zyMTqsjnpaptOtYtiC/+nSRuUtXVxfbt29HEASefvrpWeu3b3CEH33cS1I7NeeHR+Dgq8f51VubuPe61dwQCnGwpZd0BuatdJ63J/bN7YfpF2pRqqfuSYIgkDLW8Nz2dv7w8ZI5c7+6FITCYfZ1y4ia6V5VSanlsxNj3LIlkxP1srbBxC9PxhBEEVnOIAj5IzFkWSbod2GuzH5/yUgcZ1V+ZX17yQK8w90IUtaTayvLGsiHR2F/n59rG0e4/+ZzX6CYif3799PS0oJGo+HRR/OL+hUpUuTcKYYWzz2KWf9XGaerE15//fXTtvuDQRAEgh4PGp2estpGrKdCZEur6tAZTIwO9CJI2TUOoyr/g7sQy+sriQT9aPWGaUYsQHltPcO+6aJIZ6JQKHho8woMwWEi7hFkWSbic6PxD3HXygYs5ullbCDrNf3pB3t4q93LwYiBFw7389xHe/D6A+d1HqfT3t3Hh58fpd3lm/zMZHPiHR3O2z6ViLOkzDinXgrnVTpIhv1Egv7JsFj/uAujrRS1Ltdrn0rE0FuciFLu7SHf+RgsdnwjZ4QCn6pLm4+0f4gtK6Y8G88++yzJZJLG+Qspa8gKoGj0BpQqAe9Ib86+ydA4W8qjKBQSzx3wMCyUo7TVonNUkExEyKRTBc8/HQuzal45v/XASkokz6SxnUknkRQqYiEfOqOVaMiHSmvAPdiJvbwRW3kDtvJ67BWNSJKKaCTC9euXYY1PD3+eySPsGerhk84k20Ys7Bm38vzRDH/z/C5Gxj0F9yky95gouXPzzTdTVXX+eeqFeHlnd44RO0FUU8XLOzoAMBoMXLduCTduWEJ1xfl5T2VZ5thQrOA9KaSp5OCJ9vMf+BXE4eZeZE1hEbaIopLmk11A1nu9Y99xOkYiZNwn0BkMeEbbCu7rdrWh0AsolALu4Q4koXDEkChKBMdGUGtN6E25goUKjZkPmmVefP0jxt3e8zzD6Ux4Yx944AHM5un1e4sUKVLkSqdoyF5lTIS9FaodW1NZQSYaQqnVojNOf7BpDUbS6TRyOkXU72VZ7fmFOdVWVSImolidhV+0BM0MKk6nYTYZeei69Ty5cQHr9FEeW1XLYzdsoKyAWvGY28M7JwZIWipRnwrv1JhshE2VvPDZEVKpwoZOPsKRCD95Zyfv9kTozFiJo8wx0BwVNQx2niQamjKSg2NDNEg+rl0zt8ph1FSWUakKEPa5Mdqy300yHkOjz60/OWXgTZcrLuRp1ZksBD1TdYgdVQ2MdDeTSsRz2mVCY9yzwopBPyXkNPGi9Wu/8g1SgSnvv6WkHGuJE6+rA89wO45wM791SxV3XLOCD46NIOqnvOxmRxn+sT5EhYJ4NJR3jBXKcRY01mA06Pkvv3InNUIvyYgfS0kV3pFeNHoz0aAXpVqLe6CTkpqF0176tUYrCAIalcSv3bWGOnGYdHAsey2jIaRMPN+h8Y0MYLA4MTizXmD3UA++sWG6PGl+8Oxedh9qybtfkblFJpOZvL/OpmhOZ+8grqS14Pa+sB7X6PhFHSMajRJIFg5rlxRKRv355++VzsDQKC++c5htB4fxDHcSDRZYPJJlkGV27j/O7/3dO7x6PMm+rjAh0YpnpJeAp41EbPr9JZGIkMz4qFm0DmtpDaIsIIkzp75otTbcfbkLB/FwAPdgO8gS+7yL+IvnB/iHF/YxOnZhi13xeJxnn30WKIo8FSkyawiz+K/IrFAMLb6KGBwcnFQnLJQPYzGbiYz0U76ucP5lSWUtbXs/5vbF5VRVnL9AzcKaSmIzbJfPEgJ6JiajkSULF5y13f62XpTW/OOVnLV8frSVzaunG5iRaJSdR07S54uRlGWsaoll1U6O9rqIWWsm69hmMhmMVjuekSFspRWoNFoqGxfgHx8h6PMQHennD5+8E6vVcl7n90XxxI2r+PNffDr1QR7vjCAIGMxOfCP90+rI6kxWQt4xDNbcXFtraTVj/Z3EPINIBjuSpERSKPCc3MnCpjo0Oj0OvcTmDdU5tX9PnDjBgQMHUCgUfPObv0LviI9fNo+gMGUNbZVGi62klMWGAI/cnFW67ujuwyfYOPOVvKJhASN9nYz2tqA3O7GW1SIIAomwl3pdkCdvn6pfLIoiv3rfFrr7hzjWPc5ht5e4vhrPcDeOqibC/sKeEIuzmmGvhxVLdHz1jnV4fX56Boaxmo3sb7NxPE/lpFQijlqXXTBwdTfjqGxCUmZnVdjv5WefDXO0bYBvPTZ7OdFFZp/t27fT09ODyWTi/vvvn7V+R90BFOr8ESaQze8edI1RVnLh5cY0Gg0KZlZ61yiuvnXt93Yc570jGSSNEyQntlIIB8bxurqwluWG9uszQ3SNqnn78DhqvRNBEHPUzasWrKZt57uoteWYHfMQBYmgfxCFXsRgdyJKCvyjQ6hFJylxtOCYZFlGFCVUKjP+8UHMjkqS8SjhwBj2iimhwGRGYn97mM8+f4P1i2w8/cC1OWrvZ+PNN9/E6/VSWVnJTTfddO4XrUiRIgUphhbPPYqG7FXEuagTdvUNEJX0KBSFV+dFSeK+zStZs2TmPNRCVDrMtKezuUY+9xjhgH9S7TGTSaNNX5qV/+FgAgo4NgRBYCg0/bihcJjnth9BtlWDNVsyNAC81TyAQqXh9CIwZruTcMCHSqPD1dOBye6c9Gqng+P8l6/fizGPuNZcQaPRsKS2lL4Jx3QBD6tSoyUWDiIpFNnc0VMqv3qTlfHBbiSlEq3BMtk+k8mwuETk1++7m/7BYfqGx6goWUhj3c0zjmfCG3v33XfjcDhwOBzUVfjYc7wXbyyDRpJZPs/B/IapeRgMR1Dm8eiLkkR5/XxSyQTzki1YLBJavZF51YVzCeurK6ivruCerct47r39fK4U8bh6puW+nkk4MXXdrBYzVkt2DpiMRtreayWhy41imAg59rj6sFc2IilVRII+wr5xdCYbjuoFnPSN8xc/+YhfvXs1Tnth71yRy8eEN/bRRx9Fp5ueNnGhlNiMpJpDKApEqqQiXipKL06ISRRFFpSo6C4QlCIHh9l484VFkaTTabbvb6F9JE4iLVNuktiyrPqiDO/Z4GRnP+8dk5A0ub8nvcmBpFAS8rownFr4TCeiLChP8lmfCqVGTyoZn8zRD3pGiUeCCKKIvW4+6sgADnEvPX4VjqYNSJICd/9JAOLBGBZzBelkgnBgDL1pemkk72gXJlslnpEOPP1dpKIxYlEvlfPWTrVxdRMKjIEMWmsD+3vCfPb9X2JVh/nHP/8VFIqzv7pNzNenn34aqYDKepEiRYpc6RQN2auE02vHzhRG9Mb2fQSDAVy9nZTV5ldhjHpcrNh8YUYswJolCzn2wR6iogpJkqioyz1OYNRFR08fTXU1F3yM2WLbodasEXsGiUQKc2nui5jOaCKTyRD0utEaDMSjEcZ721hUYeXhr9x+yesBzgZLKk10tmf95UqVhlg4OC282FpayWhfB3LEx5jfg0prwFndhEKpQq9RUZoawCbF8MZktAqBBeVatqzagiiK1FZXUls9PdfvTFKpFM888wyQGz1gt1pySvOcSVNdFekTrZPqrWcixwPccsMmShznLvAlCAJfuX0dt3p87DzUxntHC+dTy7KMRZvfc2WzmPjVm5p4d383J0diJGQlFlUKlZDEPdiDf2wYpVqPUpUiGvTiqJpabDJYHERx8C/vtfK7D6y8IubSl4lQKMSLL74IzL76a2NdFaV79+AuUDi7Wh+mvPTia8Xevq6Bf/2wg6Q+d6ElHQ1wy3z9Bc25aCzGP7y2H6+qbjIUfyQAhz8Y4LF1YZbOny7W90Wx59gYkir/AoBGZ8btcqM3Z1AnB7luqQFf3EB0OEo6lcBemf1tekf6UWn0k2W9oqEA4YzMcDrCykVmfAM7CMQVZIIpEs4ayGSvgc5kJ+gZwjPSicVRiygpSMTDeFwdaPQW/GO9OMoXTi7wxlRWRjpPUNKwmLB3hGjIi0ptwOqsI+AewGQtR2+0k4hHePq7L/HELXXcc+vGgufucrl45513gKJacZEis0nRIzv3KBqyVwn79u2jpaUFrVY7ozrh0Y5uyuvmEQuHcPV2giBQVjllUMqyTKU6g8lkLNjH2ZAkiZuXNfDcZ4epXjB9ld9UUsbezsFZN2RL9EpGCmyTZZlS/XRPW48vjqrAO2Imk5mWZ2wwWzCYLQQ9o2yyJVh/251oNJqLHPkXx/KFjRzq2AGA2VnGcF8Xgiii1k75nlOJGBtrtTx84zXsP9ZGJJ4kkxzFYrYwf8vii5obE7z//vu4XC4cDgd33nnnOe9nNBiYZ5HpKlChp1YXOy8j9nTsNgv33rSejHCQz935Sz+J4SGuWb0iz95ZShw2vnq7LVvWJ5nkcGsvz3zah85RhcFWRzToZXyglbL6/AtFMV0Nb207iFKtZ8CXQhSgwaHiujXzisbtZeSVV14hHA7T1NTEli1bZr3/h66p58cf95PU5ooRaWKDPHTr7NT+LHXY+PZtC/jkUBcdo/FsHVmjxMaVTpbNr7ugPl/ffhyfun56upfOyUt7+ljUWHXZvIHjoZnLeFVaUjywLsyKpWuRJIkfv3MIncmGe7ALQRBIp5JkMml0puz9xD8+DLKMvbKRaCjA7iOd2BzrUVn0WCwQGOonGQ1PRgUZbRXIskxgvJ+MnEah1KDWGUknYtjLc1X7NToLao0J90AHCBnS6RSldQtxD7ZicdbhG+/FbK8hk0qit1Tyyu4IH+x5ju/95q15z+3nP/856XSaDRs2sHDhhS9KFylS5AyK5XfmHEVD9iphwhv7wAMPYDLlz7f64U9eZO1N96BSTxlemXSagc4WnEYIeN2MdZ3gG9964qLHE4/FKK0r/AKW0Fnp7u2nvjZ/iYILYe38Gl473IfSMt0yTY/3sfGWDdPHmZbJJ8vhrKxmdLCPkuq6vMeySSmu3bLpIkd8efjKrRt455130EYGsRnUxEfaUGqUWCxWjGqJZQ0mVi/JXquNqxZfkjFMhBU/8cQTqFTnVxP4oeuX8+/v7GNIdqI8VQ4pGY9SIo/y2G0XX7binutW0P/SLoaoQZROu0VGRnlovQO1Wl1451MIgkBHn4tXDsfRl069SGqNVrTGNVljtmHBNGM56B1jV1LA4Dw1h2UYHoNDrx7m23cuwWopnEtZ5NJxei3OS6FGXltZym/fq2X7wS76PCkQoN6h4tpVizEZZy9dwW418/CNs1PaRZZlmocTUGBKpvRV7DrUyta1S2bleOeLXi0wk1hDZYmJ1SumtBfMGgGN3kgiFiaTTuEd6cdWnq2RnUmnSMaj2CsakGWZsY4uyqpzr6PJVk006Ec+rf65IAiYndkF22Qiytigi5KK/IalIIqQEghHxjFYywi6B7CWNuAb68VW2oh7sA2zo4bR/hMo1DqCCif/6W/3cP9qiMVikzWqT68dWxR5KlKkyNVO0ZC9CjgXdcKW9i4UNUtzjFjI5hZW1s+H8eOM9HdSoVOeU/7N2QjHYqjUuS9gsiwz2NNNRs7GZrwzkmB9MMzapbOzYlzmdHDrghifNvcT19lQaXXEgj4smRC3blg8+aA/HaMqf5ioKEkIokAs5EdjyFV3TgQ8bG28uJy1y8nES9Z/uHtd3mtyqfF6vbz++uvAhb1oqdVqvnX/NZzs7OPkkAcZaGw0sHT+7HjKJEniNx+9hj2HWjkxECGRlikxSWy9roZSp/2c+9l2dARBnV/121rWgHe4D7XBRNjrYUJAPhJ0U1I7b1r7iLaGVz9r41fuXjttWzqdJhAIYDQaZ+W3WySX3t5ePvnkk1mvHXsmVrOJ+25Yecn6n23i8TihlDJHR+B0BFEkEJ3ZK3opWVano/1gKncx6hTpVJIVjbkj37i4kgMfDlFSu5DRvpMoVdrJe6XX1Tdp1HqG+3CU51/gc1QuYKBjL9WNuWG/mXQKj6sTlVqHQpn7DE7EwoR8LgREUokIEf8YBmsZmXSSRCyM3uTEO9KNtayR4c4DlDesRqnSEvQMIaeigJff+sEv+d63t1JXW8mhQ4c4fvw4arWaxx577EIvX5EiRfJQDC2eexTfeq4C3njjjUl1whtvvDFvm5MuLxp9Cb7xUaKh4GRujixn0KjVlACCILJiwezkNFWWOjl4fBCtxXbqODKdLc1Yy6rxjY0Q8LoJaXW8dqCTd3cf5tsP3YbDdvEiNw01VTTUVNHZ04c3GKS8uoTKsmUF2zfatbSn0pO1VU/HohbZXK7k2OAgo5EUyFBpUrNuXhnz6mfPk/xl47nnniORSLB8+XJWrbpw79CCxhoWNF6aPGtBENi0ehGbVl94H/3eNAXSHpEUKoJeNzJqLCVTOeSWknoC7kHSqRQGS67R3O4RCIZCk4Ji4UiE17Y1c2I4SVwwoJIjLCyVuG/rAiyzEP5dJMtE7dgbbriB2trLl/M511Cr1eikwkrIsixjUF++t7XNaxdyrHMn7YGayecdZAUHF1gG2bh6c077ilInt84f44P2DFGtnuC4C0tpbfbZIAiTRq2cyCAZ80eRSAolOrMNf6gDOSGCLJDOJPC7e5AkPSlfFEfZVFhxyDdCOpnAduoeEPQNIynUhMfGERUSkYCHisbVRINexvpPUFK9BKVKy9hAKzq9jfipEmeyZOS//P1+6mzbCQ3tBuC+++7Dai0KxxUpUuTqpmjIXgWcizphLC3jGXEhSdI0kaeI3wPRrLLlprWzE3ZW4nBgoYMJneChnm7MJRV4x4bJpGXmr9qQE6L37zuauXd5NfPrZ8cwaTzH/Nsb1q1g7MNdjKucqDRTOYgx9zC3Lq5iQUMNq5dM1VC9FGGFXzYm5uvVLkIiIjO9Gu9p2yUlxjzlokz2SjwjnTmGbDqZwOsLsmvvYW69cQvpdJp/fO0QPnUdohmyM9dGewz+31vH+a0HVqIr5tReNKeL6M3V+erx+tlzvJdYQsZh+OJK6AiCwJIyFc3R/NvFYD9bVq/7wsZzJoIg8K3HtvDhZ8c50h0lEJUxawVWNui4ccvmvPfy69YtpqFyhD0tSQZMDtr6TuCoX55TQ1smv9r7BJJCQUnDVNke91AXCxffRtjnwdvvwu8ZxGyrJJNJk4iGsJVmn8duVztGSzlGy1SedDwaZLT7OAZ7GdGQB43egm+0B4O5DO9oN3qdEYgQ9o0hqcy0uyRe/+cfAcWw4iJFLgVFj+zco2jIXuG4XC7effddYOYHVzwUJBETKa1pmLZNbzRDFGLBAB8fOMrtm6aHL14It6xZyuu7DoO9krQMQa8bAZGqpumhk5byGt4/1k1TbdU0gaVLiSAIPHbLFlrau2gbGSeVkbGoRdZtXYTJaMxpV+TiaWlpYe/evUiSxJNPPnm5hzONYCjEwKCL8jInFrP57DvMQEOJmvY8dWUBPENd2MsK55DrDA5CvnH0ZjtjfR2IogqLs4kPhxLs/9nnlGhCeFUL8upFhNQ1bDvQzh3XLL+o8ReBnTt30tnZicFg4KGHHrrcw5nG29uPsK0jg6gvAUAYTbBBBz39I8xrqLrkx7/32sUMvH4Iv7o25x4pR9w8sK70soe6C4LALVuXccvWc9+nuqKU6ops6sjJrgF+sWsYpUpL37GDqLUWkvEw7lA79vLpzzEAFLmGrpzJIMsyQZebkvLFeEe6SMRChP1jWJ3ZcOWAdwijtQKVOjfcWa01YhEaGB9tQVRkvcCZdIZoyINKbSAW8QFQWr2ESCRK38nPSMbDqHVmhsYT537SRYoUOSeKhuzco2jIXuFMqBNu3LiRBQsW5G3j8fpo6XNRuWhmb6vWaKDfP3sPP5PRwFO3buFISxs94RCC1oAoFf71qpw1HDjRyrpll0ZgaCYWzWtgUYH3kiKzx4R364477qD0Imtjzia+QJBXd7TQ4ROR9E5SBzppMKa4Z1MTpReognzDygo6P3KR0U4XH7MJI8jq6YtKE2j0ZgKebkKeMezlCyZr0SqUakJUMR7wkEwOYinJb6x0jFyaWs1fNiZEcx5++GH0+kLZoJeHfUc7+LRXi3TauCZCaH++rYc/ri695Dnwep2O33pwLdsPttE2EieZkikzS2zZUDlpDF7JLGioYkP3GO8ckikpncoziATdjA+exFGZ+8wN+IYwnJYiI8sy1To/fX0nMVuyv3draQOB8X4iYfekIZtKxlAVyKdXafTIKUhlplzfYf8YzspFuAdHATWZTAajtYK2Q28DsHTT4+wbqKL//3zEtx5bSXnpuef2FylSpMiVxBfn+ioy65yrOuGuYydJSQrUWt2M/ZltTiJpmUxm9gQ6BEFg5eIFqMUMAqDWFR6DKEmE4jMFYxa5kkmn0/zsZz8D5lbYWzKZ5J/fPkpvpgKlqQxRklAZSxiggn/7sJ1AMHRB/dZXl/HVax2UMEgqFsyGJ4aHWWwY5hv3rCUZ9RXcN+QbRVKo0Ojtk0bs6WgMNhKxwsZq6vJp7Fw1RCIRXnjhBWBuzdcJdp/0IKnyG9dJbTXb95/8QsahVqu5ZdMyfuP+tfzOw+t4/JbVV4URC9Db7+LD40rUhtzz0RntGMwVDLZ9Rjg4jt/dj891CIvUjUUZIu7pQRvtZ6NjjO9+8y4sQghJMZVXa3JUozVMLZCdLeLHalAQDYzhaj+KHMugVVoY6TmB8tT3rzeVMNJ7hMGOvQDULbqeZCxCv1vF9/9xJx6vf7YuSZEiX2omPLKz8a/I7FD0yF7BnKs64a6jrWgMdjyuQezlhcPNDGYLYjx0SUJ7M5EgaYWWRLRAQhVZw1ynKK6tXK18+OGHDA0NYbPZuPvuuy/3cCbZfrCVsK4mb5huQl/J9sOd3L21cO3YmVjQUMWChir6B4bx+AM01S9Gf2oxp2bfboZlS979jOlh5FQGwVk4ikKjNRELB9Hopws7lZsvT+3Oq4lXX32VYDBIfX09W7eeR2zqF8RIoLCYmCAIuHyFhZiKnBs7Dw8jqkumfR7yjZCIhjEaS1ElAzQ4ZG6/ZhlLF+YXA7txdTUftOTWpjbZK/C7+zDba3JycPMx7olQXXsNGp1l8jM7EAsOA0ME3P2M9B8jk0lhL5tPZcNalKpsjnw6neTP/n4Xf/Yfr8FiLorAFSlyUQhy9t9s9FNkVihaDVcwE97Y+++/H4vFUrih1kzd4hXEY5EZH5gGs5kas6bg9oshHE/id4+RThd+uUqMD7B2WbF4+9XKRFjxV77ylXOqxfpF0TWemNEj0jV+8WG61VXlrFiyYNKIBXj8pgXo4n25QjKZDOZEN//56a3ctKZ+xj4FQUSWp7teheg41yw7t/xIWZZ5f+dR/voXe/kv/7aHP//ZHl796BCx2AwFOL8kTNxfv/rVr36hefvnilqaeUwq5dwb85WGOzj99xVwDyEKCmylDRgd81AYG3AlGvnxe0EOHOvK289N1yxDmRzK+Uyh0iKLMtGwF0lSkkzkX+RNxELo9I4cI3YCvWnKyG7+/GUAVmx9etKIBZAkJUrrcn76+vGznm+RIkWKXGkUn3RXKIlEgl/84hfAzGqa73y0jVgkQufxw8QiYQ5vf5+g3zO5PR6N0Pz5NgAyY31ct+rS5KeqbSUYTBZ846MMdLZO2+4eHuDaeaUFVZeLXNn4fD5effVVYO6FaZ7FGUI6c2lWTkudNr775FpuqfPSpBthvn6EO5sC/OenN2MxG1nSUEIq4im4v0n0YhF8ZNIpIGsEK0K9PLzWRFX5dC9SPn78+m4+7rfgU1SBsZqIupp97hL+/uX9xONf3jzb/v5+PvroI2DuqhUvqMhfAgYgFQuwZp7jCxzN1YlenfuKJMsyyXgEnXF6zmkkkuJHLx/n7Y+PMTQ8lrNNqVRyzxYLcsKb87mlpI7x8ZMkMn6Geg9MM2ZTqThDPQewl84s4DDYdYjR/uOIkoKFa+7P26ZrzEj/4MiM/RQpUuQszFZYcTG0eNYohhZfofzyl7/E7XZTXl7OLbfckrfNyOgYn7SN0LRqI5IiK/ohyzJ9rccY6mzH4ighHguRSma9Lw9vXXPJSnakZZmqpoWM9HUT8nppP7gXpVZDJpNBFAUigQCfx1wsm9949s6KXHG88MILxGIxlixZwpo1ay73cHKoMisY8hXeXm0tbDBcLEqlkps3569zXFHmZIG1g46YdZrHOJ2IcOeqEq5Zs5DPj5zEG05h0kpsXLnxnL2Hx1q7aA2XoFBOXzxyK+v5+PM27thauAbz1czPfvYzZFnm2muvpb5+Zs/45eKW9Y2cfL2FqGa6932hJUBD7dLLMKpLx7HWLoY9UbRK2Lhy/iUXsgJYvcDE0aEoCmX2uRh0D2K259YQTycTeEY6MVrL0ZjW8HELfHB4hKWVnXzjkfWTv8cta+djM/ez/cAQQ54MkgS1dhl1HNwYCYVcREJjpNMpBARkZERJwmSvOWsObeuBNwBoWHoLWkP+2rEKjZWeATfVlVdH/nKRIkWKwGX2yG7fvp177rmHiooKBEHgtddeK9j2W9/6FoIg8MMf/vCs/b788sssXrwYtVrN4sWLJz1BVxMTYW9PPfVUwRIHP35vN42rNk0asZDNnapdtBylSkVZbT0arQHNqfqpKtWle2H3DQ+gUCipbJhPw7KV2MvLKa2qZd6yVTQuWUk6leDEYGHvU5Erm9Nrcc61UkbXrGxECg3l3SZExtiytDrvti+Cr9+zjkX6ITLhUSC7ECVF+rmlKc7WtYsQBIENKxdy+5albF696LxCYA92+SZf0PPRMvzlDC8+vXbsXIseOB2bxcR/uHs+i40jiME+4t5eDMlBAJ644+wl1Lp6Bnn23UP86+sHeenDQ4yOzc3775BrnL9+Zic/25/h0wELb3eZ+bOfHeSzg5dezGrl0kZWVoyTSWXV/NPpBAplblqEd7QLZ+WinNBfSW2leayK5986kNN20bxqvvX4Ov7sOxv4b9/awNce3sj3vnMv850ZTKXlIAnYyhqxljVgK2vE4qxDUiqJhNwFx5hKpejv+ByA0uplBdOHMukUOk3Rd1GkyMVQFHuae1zWu1o4HGbFihV84xvfmLFG32uvvcbevXupqMgvT386u3fv5rHHHuP73/8+DzzwAK+++iqPPvoon332GRs2bJjN4V82RkdHefvtrMx+oRctt9tNSpt/ZRagtG4eXc1HkDNpDBYbcGnVgsVEiJG+bkpr6lGq1Dgraya39bc1YyutxO8evqRjKHJ5aG9vZ9euXYiiyFNPPXW5hzMNk9HA01treHlXFx7RiVKtJZ1MYEi4uG9dNeUlly9EU6FQ8LV71+Px+mnuHEApCaxZtnZW6nPGkzOHTMfOsv1qZc+ePbS1taHT6Xj44Ycv93BmxGm38vSdU/f5ZDLJ22+/fdbFopc/OMDufi0KzakQ9DB8/nof964a45o1+cu4XQ7S6TT/9n4bUU3d5MuKIAhkDFW8dcKPxdDL0vn5BZZmi68/tJHte5s5cHIchSFJwDeEzpJ9F4lHAmj0+Z+zgiBwqEPmgVgMjaaw9oRKpeK3H9/Mc2/t4M2dfZis1Tnfn9FawXDnIXSG6eHMsixz8ODBbB6twcGaa77JSNcRlHrDtDrVBnGY1cuz70Atbb18fnScYFTGrBfZsqqUhvrK8742RYp82SjWkZ17XFZD9o477uCOO+6Ysc3g4CC/+Zu/yXvvvcddd9111j5/+MMfcsstt/Dd734XgO9+97ts27aNH/7whzz77LOzMu7LzS9+8QtSqRRr165l8eL8Oa0Hjh7HVlbYk6TVG/CPjlBeV4OQSXOpDdl5TU0caWsmFPBR2TAfjU5POOhjpLebRCJBeW0j7oH8QhlFrmwmvFu33nor5eXll3k0+amrKuP3Hy2jub2HMV8Ai0HF8oWb5oz32GY1c81a86z26TBI9MyQBus0fDklFCbm60MPPYTRePWpvO472s6eQTMKTa43XtQ5eePQOE3V45RdxsWb09m+v4WIOr+iuKg2s7N56JIbsgDXbljMtafWwf/1+b20nnKQRkJTtWDzkVZV0NLWy6rlMy8OSJLEk/ddT2XZCf7fSzsxW5swmsuyxwiOkkyHGR9uxWSrRqXOltyJhr3EQsM0f/oxAPNX3o13rJtoyIPfPUBgdABLaQ2WknqEpI+7r3cgCAIv/fIAnzXrUKhPhRh7s9EZt6xyc+dNyy/iKhUpcnbOptBdpMj5MqfjTDKZDE8//TR/8Ad/wJIlS85pn927d/O7v/u7OZ/ddtttM4Ykx+PxHGGTQCAAZFe3k8m5V8JgIqz46aefLji+aDJNJDyOyZZf9CWTTqPTq1ErlYR8ftAqL+m5rplXx/HuAQwmE4PtzciZNJJChdFswV5eRdfxgyyqKZ+T1/tqY+IafxHXOpPJ8NOf/hTIhsHP9e93Xl0lE7IqqVTqso5lNpjpu960tJJD7/SBzpnzeSToI+obwdCkIBqN5nh/A8EQB04MkMzI1JQYWNh0+cKuLwXRaJTnnnsOuDLm65mcy297f7sXlaqMfIuXks7KZ4f7uO+G2V00uVCGPAkUQuGiyMPeL/4Z/dhdS/jRS4fo8ztRijKinMxb6xkgnY6hUSnOeYxbVs9HIWT4lzePI6rDRHxutBYr5nILYkwgHfcRDGUFm1QaA5IksH//fgDKq5YipGKUl89HbyohGvYSDXvoP/EhWzeWsWrpTRw43MaeNj1qjRZIEw37iIW9pNMJnnnTR0+fi0fuWVss0zMH+SKf25eKrq6ugpouVwqXyyO7fft2/uf//J8cOHCA4eFhXn31Ve6///7J7bIs82d/9mf88z//M16vlw0bNvD3f//3k7aTx+Phe9/7Hu+//z79/f04HA7uv/9+vv/972M2T93v29ra+IM/+AN27txJIpFg2bJl/Pmf/zk33HDDxZ/0JWJOG7J/9Vd/hUKh4Ld+67fOeR+Xy0Vpaa6YQWlpKS6Xq+A+f/EXf8Gf/dmfTfv8/fffR3dauYy5QHd3N0eOHEGhUGC1WidDjPMxjyCMFQ7XLa8yAn6wZXNoP/jgg9kebg63LKzMHs8hARMCMz4Y9eEoyebnznQ+RWaXS/19Axw5coT+/n70ej0qlar4/V4mCn3Xa60AA7kfqoFTDrn333+/YJ9dPuhqOzYbw5sz7NixA7/fj9PpJBwOX7HzdabfdoUCKhQzpHFE4e23+y/BqM4fA7BWPcNY1JfnmVFnhTrrRE7xzLnFbSeh7eT5lb55cK0O8JKVMfGf+jQJhE5r5eWXv/wlqVSK+vp6vvX4RCix69S/CaxAfPI6bW0odFQ1EGXXzh3nNdYiXyxfxHP7UvHss8/S3z837i0XisAsGbLn2f5sqZh//dd/zd/8zd/w7//+78yfP58///M/55ZbbuHkyZMYjUaGhoYYGhrif/2v/8XixYvp7e3l29/+NkNDQ7z00kuT/dx1113Mnz+fjz/+GK1Wyw9/+EPuvvtuOjs7KSsru8izvjTMWUP2wIED/O3f/i0HDx487/C+M9vLsjxjH9/97nf5vd/7vcm/A4EA1dXV3HrrrZhMpvMb+CXmD/7gDwC45557ePzxx/O2kWWZv3vhHUZCCYJuN0gCJVV1aPUGbKWVhHweRvs6WbR2Hd5RFwnfKAv0MlpnBYtrKyktcebt92KJRqP87XNvMh6KggwKUUIWQS0KfPPuG6itOnsOdJGLJ5lM8sEHH3DLLbdccuXPF154AYAnnngiZ/XwasEfDPHzD48zTgnSqdqN6YiP+aYwj9265rKHJp/Ldx2ORNh1pIdP9vejsK2Ytj2dCLHQPExrsAopjziUnR5++4mNk39nMhne23mC4/1xfJE0WrXIonIlt22aj0E/txYGz+Qf//EfAfjmN7/J3XfffZlHc/6cy/f99y8dYEwufK9dZB7lsVun5sFL7x3gkMuAQpNdtZdlGWVsgMevr2Je3aVNFWhu6+G5QxkUqvyiZIuNozx88/Q5+0WyY28rb+8XkVS5Xkw56eehrWpWL7sw1etIJMorHx7i0JAKoz03f3V8sIPEeIx3390DgL16K7s6lufcb1KJGEHfMIIgEg570BhNCKlRLJXZlInRgRMoVTpSyThmezUqVTZkWc5kGBs+xp98Zw3VledWxqvIpeeLfG5fCjKZzLRoySLnzkypmLIs88Mf/pA//uM/5sEHHwSyKTKlpaX84he/4Fvf+hZLly7l5ZdfntynsbGR//E//gdPPfUUqVQKhULB+Pg4HR0d/OhHP2L58myawV/+5V/yD//wD5w4caJoyJ4vO3bsYHR0lJqaKVGgdDrN7//+7/PDH/6Qnp6evPuVlZVN876Ojo5O89KejlqtRq1WT/tcqVTOqRtGMpmcrB37jW98o+DYXnj/M0509FJSVUdp40Iy6RTuURfx3h48Y6OUVNUiiwKyIBIOBWlavBx6j+DTl/Bh1zjzRj1sWTX7pRuUSiV/8utP0jc4xPs7PwdRYvWCBlYvO7ew8SKzy6We38FgcFIx/Fd+5Vfm1G9ptnj+k1bcqgYEYCIAUtDZaUtYeXfXCe69ftXlHN4kM33XFrOZ+VV2PmzRIJCnjrPKzL7uAYzlhryZ9EPJCprb+1ixOFs66/+98BndiVoEpYhohjhw2Atdr5/gdx5ZhU53aUp8XSxDQ0OT3o5vfvObV/R8nen7Xlyt46NeMe8iSyoeYu2Cksl9P9nbzMHxMkSNauq7FyCureMXn/bxva+XX9LrtGLJPHY2f0Z/pm7aeFWxYW68oeGyf083XrMMna6d7Qdd9I0LIGdoKBe4aV0JK5bU5d0nmUyya38b0bhMVamepYumG7tms5JvPHQd6rf3ccQj5IQvZwQlI66juPqPIUkSTYtvJSMr4FT6YTwSIBwcw1aS9dIabVk37OhQkpZD72EvbUJGRTIFttLFCIJAWoZI0E086kdUWPjzv9vGj/73E7N7sYpcNHPtvfRc2bZtG93d3RgMBkKh0Nl3mKPMRbGn7u5uXC4Xt9566+RnarWa6667jl27dvGtb30r735+vx+TyTSZPmS321m0aBE//elPWb16NWq1mn/6p3+itLR0zpVNPJ05a8g+/fTT3HzzzTmf3XbbbTz99NN84xvfKLjfpk2b+OCDD3JWft5//302b958ycb6RfHuu+8yNjZGaWkpt99+e942Pn+ADz4/yuJNNxDyehBEEYUosXj9VnpbjjA+2I+jvJKK+nn0t7eg12lzXhB0FhudoSClPX001dXkPcbFUlNZwa8+ev8l6bvI3OHFF18kGo2yYMGCq0Yx/HS6+4cYiJtR5nEyCqLIoYEEd6XTSFIe43CO0drnQ6G2FdyeEvVk0ilEafojQ6HU0jPsZsViOHSig85IOZJqes5gQFnLR5+3c8/1c1NQ5plnniGTybBlyxaamprOvsMVyk2bltDcu4thuT7n3p9OxVlT6mdh05Qw0b72EKLCkrefhKaa7ftPctOmS1uv9tcf2MgrHx3m6FCKCCbEVJj5ToE7t9ZS6iw8Z79INq6ex8bVWb0NQRBmLGW3fU8Lb+/0k1RUIggCqWSU0m27+Op986ksny6y9fjta+DdAxweFBD15VmxnHSSwb5saZ81a9ag0Vpy9gkFRrCXzpvWV0nFEmRZJhbyEQyOUVqZNWJlWWZ8qBWDuXRSvCqZKOO//PX7/P6vrsdus0zrq0iR82FCRO+BBx7gZz/72WUezdxhQpNngkKOtZmYcN7lS6vs7e3Nu4/b7eb73/9+jpErCAIffPAB9913H0ajEVEUKS0t5d1338VisZzXmL5ILqshGwqF6OjomPy7u7ubw4cPY7PZqKmpwW7PlZtXKpWUlZWxYMHUg/arX/0qlZWV/MVf/AUAv/3bv821117LX/3VX3Hffffx+uuv8+GHH/LZZ599MSd1CZkQeXryyScLrsj96/OvUFrTiG/UhcnmxGCxIWcyuHo7sZVVEg74SMbClFSUE3S7qKyrBzlXTENjMHJyaPSSGbJFvhxMzNe5WDt2Nuga8qDUFS5xFVXYGHKNUF0590PmBc6iJJlJIwjTjdN4LELIO8zxWAyDRqBnLIykqirYTctglHsudrCXAFmWc+br1YwkSfzHxzfzwa4TnOiPEU7I2PQiqxca2bx6fU7bsUAasUB2jSAIjAcurdo9ZEtQPXrbWh5Kp3F7PJiMDTOWs7mcnO0F9HhLL6/tzCAqqyZz5BRKLe5EDf/8Yiv/7Tc2TVv4EkWRJ+5cx93BEMdO9iGK8E5YReehbP76jTfeSE/AP9k+Gvah1Rc28C32WlLJKDqdnaB3CFtJA56RDuxl8xDF7LHjsSCR4DghtPzw33bx/T+48wKuRpEiWcLhMC+++CKQfX+9kg3Z2fbIVlfnCiZ+73vf40//9E8vsM9zS6sMBALcddddLF68mO9973s57b/zne9QUlLCjh070Gq1/Ou//it33303+/btm7NVJy6rIbt///4cJayJPNWvfe1rky8VZ6Ovrw/xtJCbzZs389xzz/Ff/+t/5U/+5E9obGzk+eefv+I9Qm63mzfffBOY+UXrRJ+bqoVVGCw2FEolo/3dAJTXzWNsoAejxU774b2U1tRispcQDYfyClpFUpf+BaXI1UtXVxc7duxAEASefvrpyz2cS4JKEmbMv5cTEYz6S5NvPtusWFDKx62jSJr8L8A6KTJNmdU70osoKrCVNOID3mmVCbvdCJphTI78D7z4HBWC3r9/Py0tLWg0Gh599NHLPZxLjiRJ3L51OfnjeqbQKgVmqNCERln4jU6WZfYeOsmRrjCRBNgMApuXOJnXeGFK15IkUeK8Mn5Phdh+YBRRmf+3EcrUsH1PCzdsye/hNhkNbFmbLbf34uv/h7B/FK3Rxpo1a3Ad1zM61ExJxWJiER9WR13BMYiSksG2z9DozJCR6W3biUZrRhQlZFnGM9KOWmee9Mx6Ij7+x999yO/8ymb0czzHvcjc5OWXXyYUCtHY2MjGjRvPvsMcZrYN2f7+/hwtnvP1xgKTuasulyvH2MyXVhkMBrn99tsxGAy8+uqrOU6xjz/+mLfeeguv1zs5pn/4h3/ggw8+4Cc/+Ql/9Ed/dN5j+yK4rIbs9ddff141pfLlxX766afTPnv44YfnfCH78+XZZ58lmUyyatWqySTsM2nu6GH+umuxOKcSsrUGE6lkguGedsrr5nHy4C60RgutB/ZSVl2Lyp6/zILyKvSgFfnimCi5c/PNN1NVVdhDdyWzbmkjH7QcA2N+j2uNMTGnw3FOp6q8hKUl3TT7LNMMVjnu4Z6NpXzUMkpanRV/CXpcaLRmNHrLZDtBEDA45hHwDhILB9Hop5fwKDOfX5h1MplkcHgEu9V8SWu6TiycPvDAAzmlCL7sLK5Sc8idf1s66mHD0vxzX5Zl/uXFXZwMVCEpsi9Ewx44+qGfO1zN3Lwlf/3zq53+0VTBty5BFBkYPbfSKu2HPgJgyab7UCqVlDctxdXbwUDffgz6EqIRH1qdJWcfWZYZH2lDRGTe0tsA8Hv6SafiIAqE/SPE4yEsznokaerlVquz4E1Z+PcXD/MbX7/yU7SKfPFMhBVfrdFZF4PJZLpoUdn6+nrKysr44IMPWLUqq8uRSCTYtm0bf/VXfzXZLhAIcNttt6FWq3njjTemRbZEIhGAHOfgxN+ZTOEyaJebOZsjWySXiRetr3/96wXb7O1wYXFWTvtcoVSh1RuJRcIoFEqaNlyLxzVIb1sLfW0tmG0O1tqgs/UkeoOeVCqFkSS/3HWYapueZQuaijefIudMJpOZfHDNNF+vdDQaDdfO0/JJbxhJrc/dGBnj5o1zMwynEF+7fx0vvXeIgz1p0uoKUokI5Vovt24tZeXiOhpqhnl37yBtIzIRv4eSmmV5+zFZK/GOd0wzZDPxAJvWnptH7eiJdl76uINhbxpRX4JOO8Y8Z5q7N9dQM8tKqvF4nGeffRa4uufrhXD75iY6Xj1BUJGbZpJORNlSn6SsZHpOJ8DHu07QFqpBUuQuXEhqM+8edbO4cYyKsivbu3ohKMRsEZ1CSPnL0ebg9Xp5/713Adi0eevk51ank9VNOrzuMU40D1NdmxuF5hlpx+5oyMlzt9hrSKcS+L0DRPzjiGp1jhE7QSIa4vNBLxsOHmft6kubE13k6qK3t5ePP/4YyKYCXulcLrGns6Vi/s7v/A4/+MEPmDdvHvPmzeMHP/gBOp2OJ57ICrYFg0FuvfVWIpEIzzzzDIFAYDI/1+l0IkkSmzZtwmq18rWvfY3/9t/+G1qtln/5l3+hu7ubu+666+JP+hJRNGSvAE6cOMGBAwdQKBR85StfydsmFAoxGpdIugZJxGOIUjZMSM5k0JvMWJxljPZ3E/Z5iIaDKLU69GY71fMXo1GpYOQIRmclI4N9VDQsAIWSIaB3LM7u1o9RynFGggkEoKmmnOU1ZcxvqP1Cr0ORK4Pt27fT09ODyWS6KkvunM7NG5di1LWxu22QAV8KSYQmh5IbNlfSVDf3c2NPRxRFHr1jDQ8kk5xs78FkNFBTPX9ye0NtOd+pLSeZTPKDH+9nJt1JMRXNCbvOhIe5bZmOpfNnvmeEwhH+9ZXDdAfsqHTLseggGvLiHR+mW7eIf36nn9+4V6K8xD5jP+fDm2++idfrpbKykptuumnW+r0asJiN/McHl/Le7nZahxLEEuA0CWxYYWLzmsKK3Id7oohi/jB1UWtn15FBHv4SGrLza9QcGci/LZWIsHy+5ax9PP/88yQSCZYtW8b/+u6TvPPOO9y5wEd9VSmV5SX83QsHcSxU4RnqxmbNhgenkjEkpTqvWFssEsAz2oVGayId9hHxj1HZtAFRFEnEwgQ9g6g1Jpyly/jZL73sPLiHB25voKaqWJqnyNmZiM664YYbqK2tnSZudKVxuQzZs6Vi/uEf/iHRaJTvfOc7eL1eNmzYwPvvvz8ZyXTgwAH27t0LME3MsLu7m7q6OhwOB++++y5//Md/zI033kgymWTJkiW8/vrrrFhxecuczUTRkL0CmPDG3n333TgL5AjF43F83nEspRWkUklEScJWVoUgCPjHR/C5R0mlkmj0WiSFipDfT/W8Rag1Wshk82G9o8PUzM9dbU3EYnijYHHWYCs3k0mnaR3qpcvdzo2RCGuXLrqk517kymPCG/voo4/mzb++2tiwfD4bljOZJnGlRy8olUqWLp6ueHr6dq1aIjRDGv36hQ7qy314wmkMaoHNKxZgNp09NPinbx5lMFGL6rSIJ63BikZvYXywHWf1Aj7e18uTd82eITsxX59++ukrQmH6i8ZsMvDobedXRsofzkBh4V4CsXNPKRp2jeEa81BdUYLDXlhc7UrglmvqaH22i7iQW49RlmWanKMsXXTNWfs4PTpr4l6zYeXCyVw3sxZ0JhuSQklf215UGT2JaJDqhuk6IQPd+1BrTNQ2bSGTSREOjiIIEv2tn1G1YDMB9wDOsilxTZXWxoAP/vm5Xn7n60ocjiv7+yhyaZFledKQLUa7XBxnS8UUBIE//dM/LSgUda6pnGvXruW999670GFeFoqG7BwnlUrxzDPPADOLPBkMBmLhINFgAEdlLZl0itH+biSFAkdFDYMdLfhGBlm+eSvjw4Mo1WrU2lwjw2DJfTnMZDJ4x1xZD+0pREnCWd1A2Ofh0xM9rFjQdEXWNCtyaQiFQpPqhF+2B9eVbsCeD4trNGzrzr8tk0qwstHE2hXTjeGRMQ9v7+imuS9OPCVTapFYv8DALVuXMjg8RofbgJRHkFYQBBSShnQqQfvwueURngsul4t33nkH+PLN10uJWScSm0HYy6g5+29lYGiMVz7tosdrQNJY8AzuRUz6UGnMoNCi10gsq9dzw9oqwqEQer2OqsqyGftMpVJs+7yF3vEUogCNZSq2rFk0LSfsUlFWYuPbD6d589MeTvZDGi1GZYgV8xQ8ctems+7f2trK3r17kSSJJ598Mm+bjYudHP44gFpnwlRahqTQ4D/aN63d6GAzpRVLUaqm6jqrNUbisQCCINJz4lMaF904uS3kd5FIRBAQkJH52Yt7+N3/cMcFXIUiXxZ27dpFR0cHer2eBx988HIPZ1aYi3Vkv+wUDdk5zvvvv4/L5cLhcHDnnYUl8H/0+kfUL1uHpFAQ8IwTDQURBJF4NMzYYC8Gq53g+BBKlRoxTxkNAKPZmlOEY7S/h7K6/J4ZvcWGO+TlYHMbG1YsuZhTLHIV8corrxAOh2lqaroqajcXyc9Nm+ZztPsgXupyPpdlmXr9AGuWb5m2z8iYh//7UgcxRSXoQQ34ZHj3eIIx7+dUlhqQNIU9PGZ7FX53P1pLfq/p2LiXHQf6GHHHGBhxE0krkNQmSs0imxaZuGbdwmn7/PznPyedTrNx48acsm5FLo4V9VrePZmeLOdyOumoh03LZw6793j9/NObPcQUVYhqmbH+ZkSlHrWpCq0hO0cysswnhzvYfuQERkc9mZSPMn0Pt64rYfWyhml9jrm9/L83WgipaiYXnZr9aXa27OY7D6zAZDTMwpmfnepKJ9950kksFiMQDGK3LTrnSICJ6IE77riD0tJSksnpizrzG6u5vvcwn3YCgoDJUYH+WgfjLW04S7JzPJ1MoFCoc4xYgGQiStDnIpNJYbFU4R3tAgFkwGAuxWCeWijo9UX52Yt7efqRK7siRJFLx0T0wCOPPILB8MX8vi41oiAjCuceUTJTP0Vmh6IhO8eZuBE88cQTBYusH205iVs0Y5EkBtpbsJSUU1I9UdQ8zmB7M46KapTq7P6yLCPnqRuZSiaQ1Kc92ARhxpVqGYlkpvhjLDLF1V47tkgWrUbDbz+2kje2tXK8N0E4msFqlFjZoOaeGzbn/e7f3dWTNWLPQFSo2N+nw6j2IsumgvMmEQ+jVOuosU2Paf5kdzNv7Y0jak/l7emqiAfGSARDiIYGXj0Yxe0/zH03r5zcR5blHDXNIrPHTZuX0DGwi45QdU5eZjoR5NalWZXsmfj48y5iiqyx6xvtwVLaQMgzNGnEAriH2rCVNk72LymUuNNG/vnNdup395JAh0ohsKhGzU2b5vGLD1oJq2s5fXaJooRPrOP5D5r5tQdza+heajQazXnVw02n05P1N882X++9cSULa/t5+aMuxhJRFCotolFJKhlHoVQT8A1hdU4Z+4l4GL+nH2QZpUpLJiMhyxnM1hpSySijI63YS7N5db7xHjKZDAICn+xNEQ2/x6997dbi/b5IDpFIhOeffx4o3l+LXFqKhuwcxuv18sYbbwD5w95kWeaFD3dzzBWkvHExw93tlDcsyDE+lSo1dUtW0XF4LyVlFaSSCQRRQEQkHo3khBe7XYOU1DZNO04hMnIam1579oZFvhT09PTwySefIAjCVaFOWGRm9HodX7lz9Tm3b+1PZN2weZDUVhJyElVyiKRqurELEA6MYXPa2LoiNwWiu3eYt/ZnpozYifGZnEgRFUHPMEZbOTvaI2xZ5cNhtwBw6NAhjh07hlqt5rHHHjvn8yhydgRB4FuPbmbXgVaOdUcJJzI4jCIbFjtY2HR2z3fnaeHjsiwT8g5jcdZNfhYPB9AabNPEi3xjfag1DsblUwZvEj5pTfDWp78kqbAgqboJ+0dRaLRo9AaMznJUai3tHhVenx+rZe6WXvroo48YHBzEarVyzz33nLX9/MZqvttYzV//+07GqcdRNx93TztpbwJJUE0anlkv7FBOLiyAd6yHseFW9AYHJn0Zrt6jJFMxymtWkIpHiYTdiKLEnuPg+7u3+YP/eGfRmC0yyWuvvUYwGKSuro5rr732cg9n1iiGFs89vpjEkCIXxHPPPUc8Hmf58uWTtaFO54M9h3DrKlGqdWQyGURJUdCDWjVvMZZ0hMHmwzgqqolGQowN9ROLhCfbqNQaAp7xyb8lSSKZiBccnxgLsHh+I32Dw+w72kx7V+9FnG2RK50Jb8ENN9xATU3NWVoX+bKRTM0cvZHMCNyyykAmMV0PORwYQy8FeXCtkkVN1Tnbdh4ZRlTlD0nW6Mwkoqdq42ns7D3WP7ltwhu7acv17D8+RP/gyHmdT5GZEQSBLWsX8e1HVvP7T67la/euZmHTud0XTp8pE8bR6fWNI8Fx9KZc4cNUIoYgC2j1U3MhmYjhHenCVLUZvbGCVDRBaeUKSsuWoxbtuJqbGTxxFM9okI92HLrwk/0CmIh2+cpXvoJaXWBFKA+/dv8yKpV9pGIB7HXzsC+aT0YxSMCXzZsN+gaxl+QuYLtHOjCayiirWIrRVIbZVk1Z+VLMxgpcfUdIpWLYnA0oVTpEUcHRtjR/83/fnLVzLXLlc3p01heVg17ky0nRIzuHmSnsTZZl2sejSA4Ro8WGq6cdk710WjvfmIt4JIIgiiQFDWsWlCFGB5EcZnoHh+hrHkOr1eGwgSbhZ54lQzDiYiSSwqQS8HSdoHThdK+LZ6iXa+ZV8JN3d+OVTKj1JpLjUT5p3c2Ni6toqquetk+Rq5fTwzSLojlF8lFqFRlN5N+WyaSptCvZumExBl0n2w8P0DuWJpNJY9HEWdOoZEFtA6lMhkg0ik47FQkyHpjZQD49FSl+ytGXSCT48b9n56tt0ZO8d9zC2wfGmefs4usPrszpv8gXT22JAvdw9v/lU+GuiVgYlUZfcJ+AZwhbSW5urN89gKNyIXImQ9g/iqMi63UMuAcRRJGK+jWTbT/rjOJ9bicOU4ZD7R6SSitarZp5ZSpuXl+H8zIqJvv9fl599VXg/O+vVouJ335iI109g3QP+VApZDZ+9RH+8v9+gD8uI5ymmRGPBgj4shc+GHAhyxmUSj3pZJSMnEZAIBWLEo34iUX9GM3lGEylpNMpmvt6+fdffMrXn7h+tk67yBXKwMAAH374IXB11I49naJHdu5RNGTnKC0tLTOqE8bjccKoMAE6o4mR/m4SsQh6k2WyzdhgLzqjGbNjSqChD5DDwzyyvoHy27Mqiclkkrfffptv33/TNAXieDzOO3uP0elNoHNUEPF7UUTGeWBFAx+1uBAdNZPRgkqNlrSmindax3hEr6XM6Zjlq1JkrrJz5046OzsxGAxXjTphkdll0yIzr+yPIimnG4mGdB9b1mXFwdYtb2Td8sbJUgHb97by0QE/n/frEEUJYdtxVjfAY3evQRRFtCogPK3LSeRTLwyZTJoya/aR9/2//keCAT96Uwm1C7Nhb5LaQlfAwr+/cpjvPHl2Bdkil47r19Rw7LV+kooSBAH0ZiceVxeOimxdY5XWRCzsQ6O3TO6TL6x1whPkG+vFWtoIQDKW9dAbLeU5bUP+UXZ70licdYiKBvzuflKECUmVtLzWya/fWUtV+eWpffvCCy8Qi8VYtGgRa9eunbZ9eGScnfuHGRpJIUqwsE7NDdcsyMnBbairpKFuKmz/gTsW8v3/uwedMlvvNxr2koiFsDub8Ll7QJZBhrHh49Q1bUWSsu8GNkc9wcAIPv8AKpWBcGDsVDSYkm37oiiVO3jyka2X9oIUmdP87Gc/Q5Zltm7dSkPDdOG1K5miITv3KBqyc5Qz1QnPRKVSIaan3Bu1C5bS3XIUa0lWICOdSiLLMjqjBciuao8P9pLJyCAI/OjdvTx90xpqzlKuQK1Wc/+1a4lGo/QODOFcVIvdtopt+44i2PN7XRUmJ5+39nFv0ZD90nC6OqFeX9hrUuTLyzXrFzLuP8yOljCiNntvyKRTmBjk6/fOmxZ+JggCO/e38drnIpKyejIPRlZXsL8/Q+LV/XztofWsaNRzcm9y8kX7dORMhgmHkzHdz6Y1m7LaAi++DMCi9Q9Oy7NsHzPSPzhCdWUpmUyGnftaOd4VJZ6EEovItWsrqaooIRyO8MbHLexpDhCJiyAnMakjPHhjI6uW1qPVaos5gxdIeamDr98S56VP+klayxgfPInBWsb4UBv2sib0ZgdjA605hiyyfOr7Pn0eTV3/CQXloM+FrfQMz+14PzqDHZUmq6zqH+slnU4ioGCktZWUHOMH/9rFH379WuqqZ35mXgpOj3bJN6f+33NDJJnKER86DAdbDvAfv7YCkym/WuzShQ0sXT7A8UMuACIhN3q9A+9YF3ZHw+R1NJrKcI+24yiZP/lbMZpKSacSDPcfp6J6GclEGEEQkSQlH3wWRmAHTxSN2S8lxeisIl80RUN2DpJOpydrxxa6EYiiSI1ZhWfib0nCWVGNd2QIa2kF40MDOKvqgGw92IGOFsrrFyAppr7yH3/Wwcaybm7YtGb6Ac5Aq9WycF7j5N+uYAJhhlqAI6HZq/VYZG4TiUR44YUXgKI6YZGZuf+WlVyz2sfeo/3EkzLldhUbV28qaPB9etCDpJy+YCaIIkf61YyNe9mwegGHT+6kw1+bY8TIsszYcAvO6oVoE918/a55CILA8eMn6Di+G4AlGx+Z1rekttLaNU5FmYP/89Nd9IdqEcWsCNBAEA52jXD/Jjfbj3jwynWoLGWoTjvm/3l+L5aPwtj0aVY0KHn49pUoFMVH7fkyv6GS/9JQSXNbD+OeCkbHvbiCerp6DyIpNSypFEilTzCWLEfS2DA5a/C62rCVT5VZmvDqn551m2+upVOJSSPWM9KJ0VyGUj0lhJhKxHH1HeY//e/3+eZ9S7jjhrM/M2eL9vZ2du7ciSiKPPXUUznbMplM9r+iHTK5+/niNbz8dgvfeHxdwb6fumM+/3PET8A/jFKpIxQYwVk6P6eNSqXFWbYI91gHjpJ5+Dz9ZFIJBFHCaq7AO9aDzuhAb7AQi/pQKLW8s81HU2M761fnL99X5Opl7969nDx5Ep1OxyOPTL+/XukUPbJzj+LTdQ7y4YcfMjg4iM1m4+677y7YbuuSel7Z34VkzYZImWwOgl4PI90niYZ8CKdK8Iz2d1PROFX03T08QCqZQGe0sD8o0vrWburOrYzdFGf5FRZ/pF8eXn31VYLBIPX19WzdWlyFLzIzDruFu26wnLXduNvNcMBAobRIUe3gaOswN11j5Vtf2cL7249xpCuKPwwqMYGCAKs3VFDlCHLNuk2T97+33nqTTCZFac2KyZzJM5FEePPDYwyE6xHFM25mShvPfdSDZChFdYbmjiAIVDWuxTfeT1JVz75+Gdczu/ntr10zaUDJskxHVy+ZdIZ5TXVFIZSzsHh+3YzbXSPjtHaPIokyJn0dz308TEqVfSbKmXQ2x1atJx4NoNaaTjNus0SDXrSGbHhtMh7J1ldVn67m34FCUlPVkK2X+sq2Pjq6P+Q3vn7jF/LdTXi3br31Vioqcuvvfn6wbcZ9T3QmSaVSBRdS6qvL+Ivfvp7/759+Sd+gA5O1Km87QRCQJBXjI+2YLJWoVLqc7WMjbUTD3skc5Uw6xT/+9AQVpRaqKi9POHaRy8NEdNZDDz2E0Wi8vIO5BAgCnPlIuNB+iswORUN2DjLx4DqbOmF5iYNHN4jsOtFNny9GWoZSrcRt6+oRgQ8GYijUmpx6sO6hfrRGM1qDaaoj2Qg+HzsPt3L9umXnNMZykwp3TC7oSSk3Tg/zK3J1MvHg+upXv1p8KS8ya8gZGc7xYS8IArddt5zbrjt724nahks2Ppy/QXyEdcvn8zc/PVHw/qYx1+EZ68JePvXi7h3tRUBAlmXi8fDkuPpCVew/2s66FfPZvreFjw/68aVKEEQRwwd72bLUyO3XLT23Ey0yjbJSB2WlU2ksddVBtu3rZtidYoFNT8/AUWTTUtyDJ3FULERrsBIJjqMzTu0z8T2HfC6sJfWTn3tcnVhsNUiKqRruZlsNPYEMP39tP09f4tqzmUyGn/70p0D+6KxAeGahs1haTzAYxGq1Tnpvz7xHm01G/uT3HuHbv/86atWUerEsy/g9/chyBpARJTWSSjnNiAVwls5naPAIAe8QJmsFoqTAUbaCv//xIX7wx7cUQ+y/JMRisWLt2CJfOEVDdo5xvuqETruN+661MTI2zvHuIdKn3v2WLmhkx8mdpNQ1CEx5AlLJRK4Rexqfd40TiR+kz58kmQGHTmR1XQkLGmuntd28YhEn3t4Njrpp29I+F+s3NE77vMjVR39/Px999BFQfHAVmV2cTgdlxk586fxqsZnYOMsXnl+Zp6NHj3L48GGUShULVlw/bXs6GWfrQgGj0YA/kkGc/s4+ycS7ecg/SjwQwOpsmHxhD3iH8Qx3YCtvQlSoON7pIxJt4bV92Xxfxal1vig1vHcsRjJ1hHtuWnFe51IkP2aTkXtvWj75tyzL7NrXynG7jZOdhxAx4PVFkBRq1FojWqMVj6sLjc6S008mk0ZAzDFiJxBEkT3Nae69OYjZdOm8Tp988gn9/f2YzWbuu+++adsteoHxGYTOdIoI3X0efvJSG12DSZChrlLB9RtLWL18Kk9YkiTqq0W80ezidDg4Tiziw2KvRZKUWY2N0TZUqsL6BxqNCY3GwvhwG0ZLGWqtibjQwL4Dbaxfe/bawUWufF5//XV8Ph81NTXccMMNl3s4l4RiaPHco2jIzjEm1AkXL17MmjVnz8ORZZlXPtlDZ1SN3poN4WkeirGr/TOuXVjORy19yKeSZzzDA9jKC5fF8ccznEw74ZQ2RJtnnMPbWik/2MG8CjvrFlRT4rADoFAo+Mp1K3hnfysjSTVqk414OIA1E+SGlXU47baLvBJFrgQm1AmvvfZa6uvrz75DkSLnwfUrLby8J4SkzBWskWWZ5TVxnI7zK4kyET1w77338Ov3VvLB3n56PRoQVdg1fjYuN3DH9dma3UadMJMYMrKcrVOaCIWwleQu3Jms5STjEQJj/Zic1SRSMi+8e5IYdpBHUekM6M1ZcR5JoWHHcTe3bU2gUk03mopcHIIgsGX9IrasB1iDLMuEw2FOdg2z74SLsUAatAFS8SAKpYZEPIxKrSfgHsDimL6IO4HWVM1f/csn3HntPBY3VXC0eQBBgFXLajEZ8wssnS8T0VmPP/54jgLxBGtXz+fdd7sK7m/V+fj52wZERQXqUzbosB9+/ks/sXgbm9dN5cP+3m/czu/+1+1o9DUkEmHsJU3EYwH83n4EQUChUBGNeBBEEZN5KsQ56B8mmYiQkWWC3gFSiQj9nfuoaliLRmdmcGSmX1GRq4mJ+fr0008Xo7OKfGEUDdk5xsSLViF1wjP56Zsf4bc0oLdOhfIq1RpS6lp2dfTxnbs28C8vv0dclkmnU0iKwiG/zprGSUkMV28HBrOd0obFZICTSTi2s5fr68bYuCIrpmExm/jKTesZd3sYHBnFUW+nsnwJAMOj4+xp7WM4mEAGKkwqNsyvpqK0mC9ztVBUJyxyqblm/QISqWY+PthPRKjIKs/GhlnVIPPEPdPLkBRClmVeeXsf//yv/w5A0rCe/c1uvnrPfNQqkWgsTlnpopx77vIGFbs686dPpMMD6HQqAu4BrPb85SWUah3BwDCxsJcjQ0NoLCvRnlJ9jUX8jPU146jOHjOtqmD/kQ42rF7AiZZORFFgyaKmYkjmJUAQBAwGA2uWz2PNlOOWj3c28/GBNAOuARwVCxAEkYycRiL/C7ksy4xEzfzrGwPo1UG0xqxx9+bOk6xdkOGxe9Ze1PcXDAZ5+eWsunahaJcJY0HKjJJmqpyQLMvY1D3EUiZEhWX6fgoz7+0YYNPaqfmt0Wh46uEa/vWZNpxlywkFR8lkUtgcDTn9DvcfQquzoVRqCHgHUKp0GE25Ss4B/zBtR99BZ7QjxuuIRQ+wdVM1VZUlFLk6GRoa4r333gOu7uisokd27lE0ZOcQ7e3t7Nq1K686YT66+wfpCAqUOfIbpyG1g/aefn794dv58ds7SZVW4B7uw1FReJUZwDMyhMVZjlqbG0akMjvZ1uehpnSUirKpB5LDbsNxmge2s3eQt5pHkExOsGQ/GwReONjHPYvjNNbmF5QocmWxZ88e2tra0Ol0PPxwgXzDIkUukhs3L+b6jRmOHG8nkcqwZP4iDIbzK/H0L8/u4u1PTxIOetEZHTSseoTWUSW9z7XzW0/Mp7xseomze29eRvfgXoZjdTkGiZz08tD1lmy/r7TPaKwIgkh4rA97+cqczzU6MyqNAc9QB/bKrJry/sN9/HKHj5hciYyM4b09XLfWzE1bF5/XuRa5MG7cspjrN2X49LNDvLfnOFpjtpbshIDRmQR8AySTcZz2hbklf1SlfN6R4vhfv4zBaiISCuP3+yitqEWnN6BIjXPd2gaWLV2Yt98JXnrpJSKRCAsWLGDjxo0ztv3Np+rZuW+AwdEUkiSwqF6N01bKT95SIBZ4ywslyjh6rJ0Vy6e8sls2LmTn3mHGAjLxWBC7MzfSQBAEKmpW4x7twOZsJJWKY7JUntk1JnM5JaULiUS8HD1yFFnxIIdb+nn8vhCrll9ddUWLZHnmmWfIZDJs2bKFefOuXrVq8dS/2einyOxQNGTnEBPerdtuu43y8vKztIY9zT1oCuS7Aqi0OoY8XhY1SfzKXdew63AzH/aOk0lXIUpTMsUTIhATpOIx1CW56oghn5ewPxtW9I8feqm1d7O23sHKhdNzYT8+0Ydknm6sKkwlfHiiv2jIXiVMzNerVZ2wyNxBFEVWLb+wPLvW9j6aXXaaP38JgEVr75+sORsVK/lgZzdP3Dc9RFmpVPK739jEp7taONEdJZaEUqvE1lWlNNRnX967+v0cHSx87IhviLKa/CkioighZLLiUN6+g6Tti5EkdXbFH4hQxZu7I8jyCW6+dgltnYPs2OuifySJKMK8WhW3bG3AYbdM9tnTl60J+rc/OYikEFlYo+amaxYWQ5bPEVEUufHaNdx4Lbzw2se8+MkIeqMDtTb3OZtOJYglfWiV9jPq1p7qR1LQ0Sui9Sux2lehtEh0DfQRCvdT1rSSto8TWLbt4L5rK1mzrAFZnu75n4jO+trXvnZWz67DbuHhe3KjnfYfbEXMk987QSoZ4+PP+vjJSyeJxjJYTTKP3LOEEqeJ9t4+rLbcBW+/p590OpH1VGfSDPcfymvETo6pZD4jQ8dQq3W0HH2LRcvv5sU3+lm+pBZJOt8yCUXmMqdHZ13N3tgic5OiITtHOF2d8FxvBP4kpJIJErEYvnEXGp0Rk82e00ZxSidcFEWuWb2ULauW8Mon++j0K1CZsw++dNiXs8+ZD+ag100qEaekZspo9QPvdYUIhE9w7Zolk5939Q0QVFoo9PgMq2x09PTRVHd+Ii1F5hbRaJTnnnsOKIYVF5nbHGpxk0wq6Dz+IQBLNjyas721L1FwX0mSuGnrUm4qUFVq88oKDnYFUKjzLygubjDhF6bnNk6gUuuJRQNo1GYkabpCvUKp49P9/Rh0bbz8URykU5EwaTjYAc2dbXzrK/VUVTjZe6CdV7ZF2NwIg149Aa+HY20xPtzxFv/9P92OXj+DclWRaTx6/410ez6lY9RPeHwMs7UGQRDxe/pABWqdAZO+Iu++fncfjrKFaDRTC3wWWw1mazXjAycpaVhMOK3j715sxv5BP4m0CoMWltWquO/GRYyMuNi+fTuCIPD0009f0PgXzKuC91pBMT3aIB4N4B1tJ+gzYrLWY9BrSMgy//DzXkqN/aRTpYjS1OuhZ6wTg7EUlTo3EsLvGyQa8aE9QygLQKnSoDPYsVhr8Lh76O/6nKr6dezc3cq11yyZ1r7Ilcv+/ftpbm5Go9Hw6KOPnn2HK5hiaPHco2jIzhEm1AktFktedcJ8iAL0t7dgto2jN1sJeEbpO3mMqqaFWJxlBEYHWXVT7gNDEAQeunE9Xp+f410DyDI0zqtg/+f92fp6Annq7PlxVk8PB1JoDezuHWL9ktikEIUvEESlKyx0odLq8AdD53R+ReYur7/+On6/n5qaGq6//vrLPZwiRQqSTEPr/tfJpJOUVC3FWbkod3vqwvtuaqxiZe1ujgxqJ728ExjFflYscLK9dYaxJaJUCL34TesKtgmlS3nxnX5E7fTol5hczhsfdPMrjxl5+RMPgjqbq5gMhrFZs+Jr6VQFf/SX2/ij76yjstwxrY8ihfm1B1fz9y+fwC820t+6G5OtAltdPYIo4hnqyutJBUgnk2is06NUBEFAr3USCXoIeYdxVi1DEAQ0QArYfmKInfs+ou/4GwDccMMNBKMZ/u2lA4wFMmiUAjrRi1pnJ5lOE/SN0uCEf3txN8lEEr3BRjoZQhIFEPUo5GGScsm0MYYCLhQqA/aSqRDQgHcAOZOhf9xBJtqBnGlAEEXisRCxaAABgXBQQJYzaLQWdAYbZkslnvGuHEM2GvYSDXvJZNKIgsjYcCvJVAyV2oB7tJ1AKDeftsiVz4Q39oEHHsBsNl/m0Vxaiobs3KNoyM4RJsKICqkT5qO55SQNS1djsk2FFJXVNtF17ACpZJJKIYCpQMin1WJm6+rsDSeZTAJgCfUzrqkAWZ58QCfjMZQabcEx+GNp/u3NHTRVlbKiqYKqUiexvgE0Znve9vGgl8p55XT39RMKRVjQVF8Me7sCmXhwFWvHFpnrVDqUnPj8RQCWbJiey11uv7j5+7VHNvLB9hPsaw4z7k+jUwssaVBz53VLUShEdhxrQVbmf3lf2aRg3ZLFvPRZ4beagGdw0ijNR1ufwPvbjpBWVhAe64YaMJhLSZ/KGJEUKiTTUv7tuRb+5HeuKQpInQc2i4k/+upaPt17kt0xMx7ZNhmxZCmtwd3VkWMMAiRiIdTawqkWOoOdwcH9VMxbM/ldyLLMeHcLZkM1SkMJO7b9BgAKy2b+9vkejM5GMukUY11t2ErrSQ7HiATdOMuW0sBhjvVp0Joa8ff2ISn1GMxZL6w3FiLk2YuzZBFabfZ5H4t4iQRGqKrfDGRrII+PnMRsqSIcGkcpqUnpGnANH6esYhkjg0eprF6TU4YoHBrH7xnAbKtCEETkTAZBFImGPSRiEWz23PmaSEQIBlwICPT3DwHLKXJ1EI/HefbZZ4FidFaRy0PRkJ0DnIs64Zl8uutzrHULc4xYAEmhpHHFeo7veI8/+aNfPa9xPHnbRlo6e2kRdRxrP4ht3mri0QiqPIZsNBTEOzKErbKWsKqGIxHYt3OIBYYYJVKaQKGDjPfxyudhImo7CrWW99oOMt+q4O6tq4sG0RXC0NAQ77//PlDMhyky93GY0oz0HUUUFSxcc3/OtkwyxDWrLs5LKQgCt163lFuvy7/9pjUa3jswvYSQSh7m/luasFn1vPzJiYLGrkL2IoiFDVlZMjEymi2RkkmlC7bzx6vY/XkLmzcUxaPOB6VSyS3XLOWWa5by1idH+ORkAEljQpQURONukokqlKrcZ6R8hu7ENORMVoH7FN7BTuzWeYiiRH/nHvyeflRqA4vWPE0wOEzGlsIz0oWzMqty7R/rx14+n3jUA4DBXEYw4EGp1qEzZudz0DeM1mjDWtpA2D+Kx98DQCgwilJjnjTIPWNdWKy1BH3D2EuaJscU9A0x1HeQqtr1OWMF0BscBP3DxKNBBFFBJOJDb7ARDfumGbEAKpUOhUJFPBZk3yGRPd/6CQsWzmPpAi233bQYtXp6WH2RK4M333wTj8dDZWUlN9100+UeziVHFLL/ZqOfIrND0XKYA7z44otEo1EWLlzIhg0bzmmfDw53Yi9QE1YURWzl1edtGAqCwIpF83j8pnX892/ew0qtF6cUIewZndbWOzpEaf1ClCot8WiYsf5OAn4/nw/E6HIFGD2xL0dEKpPJ4O84RMZWTdJchVKjRRAElPZKOnHy4kd7z2usRS4fp6sTNjU1nX2HIkUuI8888wwA85ZsRK07LZc1Mcztq1OsXnZpVVRvv2EpX7lRotwwiBztRZHoY2nlKL/xWD3VlU70Oh1rFwpkMtON0Ew6yar5GtLJaMH+1YKXmip7NoqGwiI6oqRgcCQ5K+eUyWQYHRsjEokAMOwa5dDhVsbd3lnpf65y9w0r+A+3GVjuGKFO72LLChuBYBcedxepVJxEIorP00MkMlawj0hwHIXmjHzlpDxpLB7fn40eWLDibpQqLVZbPV5XD6KkQBAEAu4hTPbssz8a9Ex2EQv70BkdxCN+vK4uvK5uVKdydPXmEqzlDZhLajCYS0ins/NAzmSQJAVBf64RC2C0VKBU6aYZsZPbzeWEQ2NEI16iMT8nT7xLJp1/fslyhkwqSTqdRJLUiGIJzc0uPjto5W//aTeJROE89SJzm9NrxxZFvIpcDooe2TnA6WGa5xr2Jc9QDxZAUl5cuK4kSdy0cQU3AW/tOEBLIjNpGPtGXVhKs8rDiWiEwLgLZ3Vu/lY6EUfuP05ZZQUyUGlS0VJSSshg40xEUaQvqWd4dIzykmKd2bmMLMs5tY6LFJnLpFKpSUP2L/7s96isTTDsDqJVCWxes/i8y/hcKOtXz2P96sLbH71nDfLr+9l/ElCVIcsyUsrF5qUKHrzzNv7y73fhjuZfuFw+X8GN1yzlk4P7ATlvmwlUMz82zoosy7z27mEONEcJRI3EI6Oo5CiSshKV2kom2U1j7UkevXch9tPUlK8mmuqraKqfUt5/4Z397Om3Eva7cQ93Ur1wM0Ote4lHA9PUjmVZJhwfR6XJnXdCJvtsTSQitB39JQBL1mbD4AVBIJNMojNmhb7SqfikB/j094WMnGK8twWtyoLNWItVV423vxvUIpbSekLeYXzuPirr1hHyjBCPhZDlNAqlljT5DUmFYmZPqQyojAYkpRqzowaFOD16K5WM43F34yyZjyBkzzMUHCUy7mNk8ASyvJj3P27m7ttXznisInOPkZER3nnnHeDLE50lMEs5shffRZFTFA3Zy0xXV9cFqROqMjOvrGcS8Ysd2iR3blmF7/099KfNqHQmkokYRke2PJBvbIiSmuxKbjqVxD3UN/mwGomJ3LHBwvzGelKpFB937cNYQAdKabDw/s4DrJhfy6KmhmKo0Rxl3759tLS0oNFoeOSRRy73cIoUmZH3338fl8uF3W7nrrvumrP5+IIg8Pj967g7FObIiR4EBFavWD6pl/Dk/fP452dPEpVrJo2XdCpBpWWQR+7egFKp5PFby/jHX7QUPEY64WPNirOXdZuJHz23m5bBSgRRRBCCZBJKtNapRUxRaaN7CP7hx0f5z7+1cfJ6J5NJdu1pIxJNU1GmY8XyqyeS49E71lL2eQufnwSDqprg8GHsZaWMjjSjVhhxOBcgSgq8493EUz7KGlcRiwYIevox2rKLE7KQXYBoP/o2yUQEi72WyropATBBEknGw2DMak9M5KSerssY93qoqj5tH1HEZq9n1NXKePA4Vns9WvtSfIMd6E0lDA8eprJmHT53HxZL/kUS+SwLI6HIGNW1mxEEAbOjhpG2w9Pa+Lx9lJQuJOAfIhhwoVCoMZrKsdqqCQZH8Yx20nxSz923n9PlLjKH+PnPf046nWbDhg0sXDhzXeSrhaLY09yjaMheZia8sTfffDNVVedeX/WpWzfxi0OD2Mqm13GTZRljZvaUgUVR5KnbN9PZO0DLwDiCGGRC6HMizyYaCmY9szVNOavEP/3sJL9hNGK3mAr+cseH+kgnk6Qr5vPJuIIP2w8z3ypyz7Vri8Ikc4yJ+frggw9e9eqERa58Jubrk08++YUbsa6RcXYfHCQSy2AziVy/eT5abWHhPACDQc+WDdNLk1RXOvlvv21h285WeoeTKCRY1Khn3eqtk/fIlcvq+c5XEvR0T5dJTqeTrF4Qpaqi5ILPp7t3mOO9JhSqU141nwu7NX9YdiBWzSc7WrjtphV8tquVX37kIUU5giCQTsWxf7iDpx9dQHXVhY9nLnHt+kVcu37q70QiQW/fIHabhYEhN/FEnMUL1xIMRWjtGkUSQKux8/L2PpLqamQpazAe35+tdbxkzcOT32soOILRXk7Qn03xMTtr8I31YC1pQKnKLvhGguPY7bmiUwC+8R4slqqcsjk2WwNjrla0GgsBdz8iIp6xLmzOBjTa3Hu6DAWVmQOBYUpqlyAI2VrIblcb8XSETCaFKGZfLdPpJAqFmrGRk4iSEoulmmjUSyIeRKezgSwTj4dobm4HNl3YxS9yWTg9OuvL4o0tMjcpGrKXkdNrx55vmGZTQx22PUcJ+XUYzNbJz2VZpvfwLv78V++fxZFmaaytorG2iuCKJv7Pe60oLWUIpwIkAuMuSmqnP0iNlQt4fW8H375nI041xM7Y7h4eQGe0oDVMhWApbBV0ZDK88uk+HrphPUXmBqerExYfXEXmOl6vl9deew344ufrG+8e4tPDIpJqKpVi24EjPHFXGcuX1F1Qn0qlkpuvXzZjm8WLGujpbmVe+RgnOuMkkwJOm8D61QZuu7FwiZ9z4XDzKIrTzkeQC2swCIJAV1+C4809vP5BHEGqmAylkxRqfJFq/uVnrfzJf7KiVF5kvPMcRKVSMa8pK3pks009n/U6HWUlU+JiK5fUs/3zVoZKNHy6fRv9nbsAWLz2IQCSiSCJ5CgG3QoymQy+sV4szlpESUk05MVgLQdcxIM+zIZcL7ecySDLmWm1X8ddJ3E45k3WiY1HA4SDo3hG20mnU6SSCZLJCHqDE43OTE/XTuoatuQYs9GIj1FXC5qQGbXBSiIRQqMyY3bWMDh8GLu1EZ3OSizqJxEPY3c24vMOEAqNUFaWXaiJRQOkk3EUkoqAX+QH//MttmysZ+uWRUXhxyuAw4cPc+zYMdRqNY8//vjlHs4XRlHsae5RNGQvI9u3b6enpwej0cj9999/3vv/5hP38sGOvXzW0kFCVEE6Ra1J4ge//uAl9T4YDQbWVig54I0iyxkiQT86k7Vg+3HM9PQPsbrWxrbhMMrT8oNSiXiOETuBKIp0+hW4vT7sVsulOI0i58mbb76J1+v90qgTFrmyee6550gkEixbtoxVq1Z9Ycfdd7CdT4/okFS5gj5pRSU//+Uw9TUOjIVyLGaJrz6yEoVCQSaTmTUBllRq5jDTM5Ez8NneEQSpNO/2aKqaT3e0cMuNX95SLAqFghs3LwWgdX82N7Z+3hpKbQKltmE2r7ZTVrqO7QcGGPNnyCRSJFPNGB0mPJ4BUr4MlEMyPAhnGLJ+Tx9mW03OZ+HgOEZT+aQRG4v4iUW8iKKEVmcjk06RTidRKiowW6uRJCUSEl0dn2C21CKJIrFYiFQySmXVGkKhUcKuISy2Giz6ahKJKGmtHU+wh9Hxk8TCfizmShLxMJHQOFXV2d+he7wLSZxawDCZyjhyZJjOXg2fHxzjN7+1Ee05liEscnmY8Mbee++9WK2F3/+uNoqhxXOPoiF7GZkIe3vsscfQ6XRnaZ2fW7Zu4Jatszmqc+O2TSswHWnh7UEf/tEEZQ2LCrZVaAwcaWln9eJ5bEh4+bx/AMlaSSToR2ssHJ6qMjtp7h5ka9GQnRMU1QmLXElMzNevf/3rX2iKwu4jHiRlRd5tGUU5n+zq4N7bVk7bJssyff1DiKJIVWXZRY9ZEIRZ/Z3WVWnZ05JAPFVPVBZmLjFTW6lk76HwjOMbdKUKbj+TRCLBZ7tOEolmcNhUbFi/8KpJPZFlmeeffw6AP/2vv8VXv7oxZ/vjd+UXQUwmk7z99tv899+7mf/vxyM5EQDZkOBcz2YiFsR6WnmcSGgMlUqHUqUj6BtGp8/m4OoNU17jdDpB4/wbAfB5+rHZ61BrjHjGukjGw9Q1bplsq1JpsavqCYVGiWpD2XrGkSjpTApJlBBFBSPDLWh1FlLJWE6pHpu9Hq+3j44eiVffOMYTj15cBEGRS0cikeAXv/gFUBR9LHL5KRqyl4lQKMSLL2Zl9q/UG8GmFYvYtGIRP3n9Qzr9XvTm6aty44M9pJIJ4iVVHDoQxJQKsKHejEYZZjwd5GBoZs+EfH5OgCKXCJfLNalOeH3mxQUAAIpZSURBVKXO1yJfHlpbW9m7dy+SJPHkk09+occe885803L7pm//ZEcz2/f78ETsCLKM3djD9eutbN00dwRU1q6cz4c7P8OTqANAZ3ISCAxjMk0XkNIohrhu6wr2Hz0MhUvbojzHN5Bde07y5rtjpORsnm0mk+bdj3bw5KONzGuarhNxpbFz5046OjrQ6/U8+OCD571/WamDpQ09NPdlJnUrjJZy/N4BLLbThJxOVzlOpxAlJclEhFQqgb1kHj53DzbHVN6z3zeIxZr16sqyTCadRK0xEvQPI2cyOBz5RbsMhhLCLjdpIYWcTpNOJVBrjAR8QwAkE2Hsp/aVZRn//8/eecfXUV75+5mZ2/vVVZdV3HvvNjY2ppliegcDSRbSNiFkf0lINgHSs5sEkk1INiyBhE7oYIrpbti4d8uWrN51pdv7zPz+uJZkWZKrjGQ8z+cj8L0z8847886dmfOec77HV4OqKOl1go3s3OvqMzdXY+B56623aG1tJTc3lwsvvHCgu/O5onlkBx9aIsIA8dJLLxEOhxkxYgTz5s0b6O6cErdfcT6Z9Kwf2FJbgc2dTXbRKAwmC0azlbi9kI/qJKIJlYsXz8NJpM92E0EvY4pzT2fX+4VQOMzqzbtZvXkPza1tx97gDORwdcLRo0cf1zZ791ewYeteWo5RW9Lb5uONT3bw7LvbeHv1TsKRvq8JDY3jocMbu3TpUnJyeg9tPV2YDUd/QzlSkP29j3fzxmqJUKow7R0zWgkkhvDKRyofrd5zGnt6YgiCwF03TSTHWo2cDGOyuhDNBryte0kl0r/ZVDJItrOOu24dgc1qZfTwvsWtUqkYE8ceWzDuQFktr6wII5PfadiIokQkMYTHn64gFOru9d256yAffrSLLVv3o54hM6Ed1+t1112HzXZyYed33DSbGaNbEOX6Q0Yg6NWm7vWJVRX1UH33VCqGXm9GECVQFURR6uHBVeQkOn36gvW31+J0p43iZCKKKEoYDH2XrzLoTeRlTyAUbiESaiUUbMHvryUa9aE/tF3AV0eb9yB2ey7ujGIEBERBpOJgDYFA4KTOg8bppyOs+NZbb0WnO7v8YR05sv3xp9E/nF1X4CCi48F1++23fyFmHa+eN4Zn11eh2NOz84oso6pgOLLwO6AzWll3sJpzpqlMK3KypjGM3tz9gaiqKkXGGNmZns7vtu89wM5aP6GkglUvMDbPwYwJx2dUnS7eWLWVrY0ykiNtcH9QUcNQSyk3XzDjCyNioqpqtzDN3pZv3L6PtdsrCckGVDlBMGFAdJYgGRzI26sZ4drPjedPwH5E3c4P1u9h5Z44ovWQeqkPVu3fzTWzMpgxcXiPfQFs3V3OpgM+/FEFq1Fg6lAbc6YOHs+VxsAiyzJPPvkkMDCiZOOGG1nbRxWcVDLEzIldYaKyLPPxZwEkfU/Feklv48P11Sw6Z/B4pjweF/9x93z27a+mqs6PQW9i7ozFVFQ20OoNk5/rZvjwLkGqJecOZfeBfcRT3b22qqoyNL+ZSRMXHnOfq9fVI0iZvS5Lqfl8+Ekpyy6dRkVFA8+9eIDWdg86nRlZTvLm26u46vIigqEoBw9GQYDhw8zMmT120JzTSCTC888/D5za9SqKIjdePZMrYzH2llZhs5oYMfxqnnt5I1v2CqDLxukpwtu0j8yccej1FsKB5iPqWR5p+Hd9VhW5U434eM9cMhHGZvZgt+dgy59IINCAv60auz2XULAZnc6Iw9kVhm+2uDFb3FQcXMNPfrmNsSNNXLSkmKFDB/+E9tlCS0sLK1ak87m16CyNwYBmyA4AlZWVfPTRRydcO3YwMyQvmy8vMrJ2VwU1vgSNDQ1kFPUtsJKyFbBrXxlzJ48lmdrNxuoaxIwhCIJAwtfEUKvM1Yu7cmRe/XgjpXEXemMO6CECNDQkONiwnusvmNPnfk4HqqqyYdtePt5RQTxjDDpHl4tFb/NQo2bw3PubuW3p59uv00VTUxOyLGMwGMkbPom1m/cwe/IodDodFTWN/OPd3dT6VLKKJhLxtQJgzep6WZcsmVQk4G+vbeXem7vUL/eUVbFyv9BlxHZgy+elTc0U5baRnZXRbdGLKzezocGJZEi/2LTGoWJXgn3V67njii/G+dY4NT744APq6urIyMjg8ssv/9z3f+G5o9lTvoX2RHehHUVOMnWYn5HDu/QEtu0oI67m9xlmFpHz2bGrjMkTeyrCHw+qqrJh427WbaxCFUwUD8lg1tR8igpzCEcibNx8kFRKZdSIbIoKc0ilUhwoq8RsNlFS3Hc5uDGjihgzquvz2DFDe10vK9PN1+8YxRvvlLG3LElKMWO3RJg8zsS1V87vdZsjqT9GHm1jU4pAIMRjT5aTTBXQ4SCSJD3tfjcP/WkHnswxiKILgM82t/PMcy/hdGWiyAL5eXrmzslm2tThhEIhzGbz5+plevXVVwkGg5SUlLBw4bEN+2NhMpmYOrlrgvema2ZxSSDIth3VAHjco3jxrSqCsQIURU57QUURRZF7eLCt9hwC/nocznwcrnz87TW4MopQAZ1kIJGIYDD0ru+hKAqtzWWYjQ6SiQi+tmoikTZy8iYQDDQSCjSSP2RKr9sWFc+mqXkvB81TePTJKu6+XaC4+PONrNDonWeeeYZUKsX06dMZP75nqbAvOgLHP5FzrHY0+gfNkB0AOrwFixcvpri4eIB7039kuJ1cvmAKABt37OX9xqOUZxBFUnI65GnBtHFEotv47GAZEUXCZpAQbWai0Rg2m5VdpeWUxpzoj1Ax1OkNVCYy2byrlOmfk2e2xdvOkx/uIWjKx5e0k6k39lhHEATKQ2aaW9vIzswgHo+zakspB1riJGWVLKvEnNG5DCse3LldKz78jA/3tNEWSjLj5l8yz2xlY6AY1a+yctcmFo6ysGp/hIag1Fl6KRYJ4snvvbZkM/ls3V3OtAnp3Kj1e72Ixj5eTizZrN5RzTVLugzZ3fsrWV9vQ2fsHq4o6gzsCeTy6ZZ9zJ12ZnhmZVlGFMVB4xX6ItER9nbTTTdhPDKO93PAYjHz7Tun8vZHpewqixGJKWS6dEwfb2XJgu6TLSm5K6exNwRRIpk6smjZ8bG3tIb/e3o7vqAFd2a63mejD9ZubsJp+pRIMhek9ITQio/qkZQ16I3ZJNV8ZDlAlmstBVkJWtqN1DclMegEPM4QFpsdRTXisInMnp7FmNFHf4bl5Xq46w4PiUSCcDiM0+k8ofIqx8qj1engk9UHSKZ65uoG/PVkZU/o/ByL+IjHArjcU0geso+ramW2/GUPTns5smrHoE8yZoyRyy8dRU5ORo82+5vDa3GerrIzToedc8/pMjrGjxvGho37qGlw8+lnZXj9NtpayrHZcwj46nC40s8mg8FCKNBIIh7GYLSSSsVRFBlRlLDYPLS3VpKV0/PZG420E4m0YjFl4MnsiqxRUTEYrDQ17MJmS9/7U8kYwUAjABarB6PJjiTpiUV8tHsrURWF517cyve/e/FpOTcaJ8bRorM0NAYCzZD9nDk8TPOLXItz3PAi3i3dg+Ts+XIBoPgbGHtuuuzCP99aRzVDkLKzsB9avi8BVe9s5+5LprCr1ofelN1rOzqDkT31DUyf0OvifqXF284fXl6PuXAioZZ6nNm9K5NC2jNbWtWI3Wrmf9/cTNBakv616SCQgv2b2rnIF2Lu5IENjQbYV17Dp/uaaQykMEgCI7MNtHjbKI0WYMrNw1B7gKzCrn4KgoBsK+SFdTtx5I7AYOrKgRWOkvgh6Y3sr29h2qGxag4kj3oHagl2V0XdWOpFZ+w9xEzU6dlW2crcacdxwAPIytW7+Kw0RHMQ9JLKmAIDF88tojC/d1XS/qauoZX311ezvy5BSoYhmRILJnuYMqH3yYf+QlEUVq3fy67KGLG4QrZL4pxpuQwr7vs3BNDY2EJDs5ehxfmIgkB5ZR05WRnk5/V+P/D7/bzyyivAwN5frVYL1142lWuPsd74MUW8+N4e0PV+XUtyPRPHnXjpoOaWNh7/Vy2+oIWMrO4h+qFgOyqjMRi6JoT87S1kZE5GFnTp/C3RwsHKBpq8ORiNVnRGaGkuJ5oYgjFo79xu+14/58zcxNXLZhCNRvl4dSmtXhmzSWDWjAKKCrsmqgwGw0mVhRs9wsy6Lb0vk+UkE8Y42LTN32NZNOLDYuluiIbDrd0MK4CWpn1kZ3cPNT5QBo/8726+9Y2JuFx2Vq3aTX19HJ1OYMqULEYfw3g/Xmpqanj//fcBWL58eb+0eTwIgsCcWWOZA1x3xXQ+3bCLf72xl1ZvEJ3eibelHJPZhcWagd1mIsN2EKPZjRw34W3ajMmST5v3IE53IS3NpZhMTuyOXGQ5ib+9BklnBFUgM6u7GJQA+NqrKRgyjYC/Hm/LAXQ6M253+nwGg00E/HV4skai15sJtNXicBWwZXsb//W7F/jed6//3M6RRk927NjB1q1b0ev13HTTTQPdnQFB6Kf8Vm0Ou/8YUEN21apV/Pd//zebN2+moaGBV155pVs91QceeIDnnnuOmpoaDAYD06dP5xe/+AWzZ8/us80nnniCO++8s8f30WgU0yCoS7Z27VrKy8ux2Wxcc801A92d04bVamVMBpQmlR6zzIosMyFbxGQysedABRWpLPTGnmUiorYiPtq8n2hKgaNUkYgkT7+gR1llHY++txvjoXIBkqRDTibRG/q+pgRB5a1P96SN2COQzC5e/WwfFY1+msPpm1qmPkae20pRfjYjhhb2bPAEOFhdx/6adgRBZfKIPHKze88xW7N5L2+VKkjmXDClQ7ZX1fhJxOw4PDba6g/iye9dmVI02Aj7WrFnHH/+0uGha0bdMURxjhjzUPzo4xyIHb0cyEDz3IqNbKrPQtRlYHKlvzsQgMo3qvn6MoGCvN7HqL+oqm3if1+rJanLBT2gh+oQPPlRAF9wD4vmjjst+5VlmT/+Yx214RKEQ+GdjRHYXtXGFXP9LJzds3RXdW0zL79XQWWrFQUDgeZVWBxZmO35yIlmij0HufL8EoYW5+Jt8/PhuoOU1yX4bPWrxGIxRo4cxYwZM07L8fQnNpuVKaNga1lPz6yiyMwarzspr/Laz2rwtsdwZ3afoFBVFVlJdTNi49EAJou7s7YopMu06A0WjMZ0TnvQ14DdkYPB2F2ISKe3s3ZjGIl1rN8iI9MVZfLhmn1kODag02cgy+C0h/G4DOTkZOB2KWRnuykqKjimlsCSxaPYuXcLwWj3CBZVVRmSXc/MmYvYuuOzHttFoz4yMkoOW19JCxsdht9Xi8czvNfIiFgslxdf2kxjg0gkko8gpO/1Gzd6GTOmii9/ecEpR1Q89dRTqKrKwoULGTbs9E4mHY25sycwd3Z6hrGhoYWK6mZUOYHDkWLo0CnYrN21Ddrb/WzZXs2ePVVs9SdpaW4iEm7FaHLi9gxFEATiEV+P/QSDzYiChNtdRCDQQEHBFHSSkVjUTyTSdkhsSqRs/4d4MoYhCAKCrGIzulm3roKfRF/gx9+/6gujP3Gm0eGEufzyy/F4PMdY+4uJIAj9EkmlRWP1HwNqyIbDYSZPnsydd97Zq1E3atQo/vSnPzFs2DCi0SgPPfQQF154IWVlZWRl9e3BcDgclJaWdvtuMBix0BVGdN1112G19q3490Xg6sXTeeGDTewP6NHb0+OV9DcxLkPhinPTL5m7a3zojX2P5YGWOAUuXS+ayF3YDH2HY9U1NLNxfz3RlIrbJDF/8jDsJ6gKqaoq/1pXRlIy47Ckt7VnZNNSW47Jau91G9nfwLSF43no9e3g6Lk84G1CNTgpS+URk8P4W+qotbspI4tkYwTP5vVcMq2A0cMKWbNlDzuqg/hjKlaDwNg8M0tmT+g1DC0ai/HPt7dSHXehM6fLIa2qbGCsq5xbls7qdvOMxmK8szuEZO/uFQv7W/Hkd3gtBMQ+a1GqmO1uIgFvpzHboYjZ6zlJxhmd33Xux+QZaarvXchGSSWYVNL93DrMIiT7bB6XefDWtm1samVjlRnJ3NMjlTTk8e6Gar505ek1ZN9cXU1S19MDKhocvLOxjvkzkqflBXHFBzupjQzt4a0X9G5eW9PApNEBXK6uH0lLazv/+1IVcaEAyaDSXr+PrMNy6XRGF3UhF397uZZrFvt59aMAMSEd+bFh3QcAFIy6mLKKBkYOSx/v5u1lrN/WRku7jMkgMm6YgQsWjcU8CJ4LN101HeXFjWwv0yPo0/dCNdnE9NEq115+csZ4bVMSQegZup5MhDGZut+QImFvt9qiAOFQS7fvksko9j6ia1RVYuUnUaz2rvWj4XbklEBCmUA8ptLavJ82q4ey8hih0AEMBiuKUkcq+RkWs56hJTYWLypg9qyeIkx2u5Vv/NskXl+xj12lceIJPQ5biknjTVxzRdqYHDHURHlV93uJTjKQTMbQ69NjLMtJdFL3358sJ9Hpep8oUFWVzZuCZGSM6+Y90elsHDhg4Y03trBs2fRetz0eVFXtfB8YTGGaeXlZ5OUdPULE7XayZNFEliyayK7dVTz1cj3VlbXo1RTBQEPnhMnheFvKyMubSEtzKd7WcixmNzrJiK+9Gp3ejDujBL+vBknUY9RbAAGD3kos5icaacdicrFpfSW//t07/Oh7l562MGyN3kkmkzz11FPA4LpeNTQG1JBdunQpS5cu7XP5zTff3O3z73//ex577DF27NjBkiVL+txOEARycwefyl0kEuGFF14AvthhxR2IosiNF8yi3ednV1ktCDBx9khczq4XqfhRagwCJGSVycWZVJQG0Vt6Go2peJQJRa5et31j1RY+azSgtx4yEGKw/o29XDHFw9Sxxzf7raoqf3hqBQnnGNRoQ7fadnqDiWjQh9neff9yIs60PB0Wi4VwXOHIAhSqqhILB8gqHImqqviaqskp6fJK6Y0WAlh4bmMLOZv3UycNRdI7wApxYE2zQtkra7n7qvk9HubPrNxGvViE7rCd6qwZ7I+7ePWjrVx1Xlfs7We7KhHsPQ2bo6tYHraeKKE3GAm1NXZ+Z7I4CPtasLp6vgjliA1MndBVamrJnLHs+ddGWnUl3feoKAw11jFtQncxmDljstixyo/O1LNkh5yMMm1875MKg4HPdjcgmfuewd5XGz+t+4/FYuyvB0MfczgpQz6fbt7Pwjn9L96xvTze5+yzYMpj9eZKLl8yqfO7j9ZXEj9kmPpbq/Dkjup126SYy9Nv7ESyp1Vy21sqqK/YiCCIjJ55Gy++W8V9X8vnjZXb+GibCUmXbjMcg9V7YE/5Jr795RlHNWZTqRQbNpcSS8DQIS6GDe3/vHZRFLnt+tlc2u5n265aBGDqxFHdjPsTb5Nei3ALog5FObp40qE1u38S+jYaAv56Mo4whKOR9s56pN6WA2RmDifobyCVjOPOKEZOJVAVGUdOOqfd2x7nb49V8o8nD2LQm3E6dUycaGHZZZMwGo1kZDi547bZKIpCLBbDbDZ3u6bOPXc8G7asxR/sEqhyuPLxth7E40n3Q6cz9sg3Fo4iueL31eB09h6NIggiW7YEWbasz82PyYYNG9i/fz8Wi4Vrrz1WEPrgZcL4Yu4rzODFV6Ns261Hb8xEQCAcau5cJxEPYzBYiMX82B05yMk4blcx4bAXg9GGKEh4W8owmpwoShi7I59gsIkIIslkhFg0gKImkZMxPn7vU3S0cd8PvvjvUIOJd999l+bmZrKzs7n44rM3X7m/Sudo5Xf6jzMmRzaRSPC3v/0Np9PJ5MmTj7puKBSiuLgYWZaZMmUKP/vZz5g69cTzjPqbV155hWAwyNChQ1mwYMFAd+dzw+1ysmBG7/UCPRaRqmDf22ZaJUYPL2ZS01Z2+OhmzCajYcZaQkweOwNfIMiqbWVUtidIqpDytxK2jUB/hNdbdOTx2rYGSvI8uF2996m0vIpdNW0kZWhqbKAybiPbaCIjr5C2hio8+SUAuLIL8DXXEfa3YXNnIun0mGItzCq2ccGc9PXmMImdTsSOsFpfcx3u3LSiqbe+kszC3hVJfeEkCUchen13L4IgijTqivlk4x4Wz+5KDm5sbuVg0IKuF2NFEEW21ye5LNnl0owke/eeqiqdBrtObyIRi/RaRsmdU0SkZgsW1zDaGytx55ZgdWcR9DbgrS/HkZGH3mRBDrcyKiPOjedP7fbyaTAY+Oa1M3hrzV5218UIxVVcFpHJhWYuXjC/h/Ezanghi2q383FFAJ2x6yU/FY8wI8fHzEkzGawk5aOHRSeOx7Y4BQLBIIrYdwSIIAhEE6dn3/6IAkdxfAbC3a/D/TVdHVFVFVHs3dMeCXoRxILOiaLdG/8FQPHohdicuTSHoqz5dDsfbRGQeql36Y0X89YHe7nm0t6fDas/3cvbq3wkhAIEQSCV8FGUWcXy68bjyXDS0NDCm+/tpKo2hsEoMm9qFksWTzvpkLEMt5PzFhy7rurxMKLQSFm1hUjYi8XaNYGi15sIJrrXaTaaHEQj7Zgt7s7vBFEilYp3eitVte9IiyOPN5GIoD8UuqwoMpKkRxBEUqk4iAImk5P2tspOA1NRZLytB8nO7hJqiydg02aorlrHPd9eiCRJKIrC6tW7Kd0fIZVSGTLEwLkLR+J02tHpdHzz7un865Wd7CtVUIUMVMVHSWGcQKgVQTw0makq6RDjQ4a5osrdJicPJ933vnN629tF4vH4SQuKdXhjr7nmGuz2wTsJdzw4HXa+vPw8KiobWflhFXvL4qTkINGID7PFRSjUTEZGCV5vemLB76tFUWTCoVayskfhbSlD0hlQlCSqkh4fqzmDlpYDyHIcq8WDyejAaLSRSsbYtKGRH//4EX72s68P9KGfNXRcr7fccstZHdotCP2T36pFFvcfg96QffPNN7nxxhuJRCLk5eXx3nvvkZnZdwjemDFjeOKJJ5g4cSKBQIA//OEPzJ8/n+3btzNyZO8GQzweJx7v8oh0FOJOJpMkk0eJZTxBHn/8cSB9I5BlGVk+hjvyc6LjGPvzWI+XOeOL2fLuPkRHz7C1VCzI9FFOkskk58+cQEllLbtqmgglFCx6gfFD3YwePpnG5haeW1eGbM+HQ0ZcszeK22gCtec5Fu3ZrNleToHHxtbKNlqiMnpBoMitx+cP0iTloDdloKoqrTEfJoMBOR5GbzChEyEebMNsS79wZmSlPf+h+r1cMM7DnOkzEASh81yOzdGztqqOeDRGh5cjEQmiEwUcnlwkQUUvCr32U01GMRpyel2GAHsbQ5xz2Jjtr2jAYHMBvV9XqjWHffsPMvxQ/q3TCIKS7Jabp6oqmbkFtNWW4ikciSsrh5bKfWQWje7xsifFmrnjiils3t/ItsoorVU70EkSFoPIlBITI3MCGIxxhg4pIMOdPl9HXmOiKHLZwvFcdkRfU6neLbuL5o1jWG4tm8sa8EdVbAaBqZOcjBs1ZUCu3+MlP0OCqhiS1PsLwBD36fn9dbTpdDhw6StJCr27ZFOJCPlZ5tPSB7cVAkrf9zqHpfuxCyhIQnp9nah2/vtI5LgfV2YxIKMqCns3vQzAxFnXIAkyksHAxh3lGIxj6Os3sbc80usx79pTxRufJBH1eehIG3GSyUpTyMr/PbOdCaPtvPx2NVZHIRarm5QC736W5P217/Bvt0xg++4m9hxSLPY4dUyZYGfh3NOvqN1xLPNmD2Xb3l1U18VRTKbO8FoAs8VMPNaIxZKOmrA7XLQ2HcBm65ocyvDk09ZShueQWI/RoEeVI+h6U2kngSR2nV85FcRisSKJMuFAHRnuHMKhegwGHVZbJqFAFVmZhQiHxjXgqyQ3d0Tn58Npbcvl4092MnPGcP726Gd42/IQhPS9pLYONm7ayq03lzBsWB5ms5HlN6dFp+rqmsnJGYPdbqOquonVa2qork1iHmImEtqOIg5Hr7PiyczH315BRkZP8SZRiiJJfV+3JtPJPzdjsVhn7dgbb7yR9vZ2rFbrCU+CDOSzuzeGFHj40m0eFEUhlZrOL37zFj6fG52kkoh7sducSKKM251LQ912dDoT4WANZrMFBJFUIoTFZCWVioAkgBol01OIw5YHqKSSMQwmEwZdHlXlAf7nj88za854Jk8agdRnCswXg4Eca6/Xy+uvvw6kIyVPpQ+D5VrV+OIgqEcWDhsgBEHoIfYE6TzahoYGWltbefTRR/nwww/ZsGED2dm9q1YeiaIoTJs2jYULF/LHP/6x13UeeOABHnzwwR7fP/PMM1gsvddIO1FaWlq46667UFWVv/71r4My9FlDQ0PjTGT79u3cf//9WK1WHn/88ZNSx9XQ+LxYs2YNv/3tb8nMzORvf/ublu+pMahZsWIFjz76KEOHDuWhhx46pbYikQg333wzfr8fh+Pk0yc+bwKBAE6nk398ugeL7dQjKCKhILfPHXfGnYfByKD3yFqtVkaMGMGIESOYM2cOI0eO5LHHHuO+++47ru1FUWTmzJkcOHCgz3Xuu+8+7r333s7PgUCAwsJCLrzwwn67wH7961+jqioLFizgS1/6Ur+02V8kk0nee+89LrjgggELGUkmk2zYUYYvlsKoE5k5prBbLm1fKIrC717biNHTXeW3viId6toXTZW7KBzVvWZPa11lZ9gwgCyn8DfX484tIuxrJZVM4MzqnlMabdjPNy+fjsvZ88amqiq/f3EjMUvvCsRtDQcRJQF3TmGv4ZPe+koy8vo+hgKhkeUXd+W8plIp/vulbaj23vP4HIk6vnnljG7jXVXXwgvrG1Bs+Xz62t+YduHN6HV68oR6blgykU8276e0NoSAzPgCCxNGFeN02PolFG7z7nI+3N5GUMhG1Bkg2sSYbIXrLph82mfXQ+EIH6wvZ29dnGgCPFaYMtzGwlmnz2vW1NzGU+8eoE3OTZenAELeMlz6OFHFRkoVyHEKzBxl59w5Xf0IBELsK6/D5w9Q0xim2ZfAYRa4/rJpZB1DOfLwsRZFkSde2khZuwfdoWRZRZFxUMMdy8aQk+U+alsniyzL/O+zn1Eb7n6dqwkfl83RMXd690iZ2voW/vZyA4ouE0VO4WutIiN7+JHNIqS8eKx+WmPDWPHGPwEYMfkKNtXPAiDHVsuYYiurdrr67JvHXM89X+4Zkv7j320A/ZBetkjn4qKquDOH9ljW1lxORlbv+fepZJgvXWNj5PDe200kEjz1whbKamzo9A5ikQChYB1miwOD0YNeaGf0cImrLhtPZVUTe/b7URQozDOSl+ekscmPy2niYPmebvfyWCxGc0sbOdmeHmGwbW3tRGNx8nKzEUWRlpY29pc1I0kwfepwdDodGzfvp74pjl4SkKQYdY0CgYCC3S4yaZydWTNG8/Lrm9m83dZ5Xbe1HOxUr21vrcDlLqStrRK9ZEKRk7gP84D62qpxuftWac/MaMLbqqIKvU/+ynKSa66SmDq1Z8RVKpXi6ac/40CpAZ3OcWh9P6PHpLjp5lmd9xlVVdm+vYym5hhms8ic2SMxGAx8/PFuPvxQRhS7T2gbDC18+cujT7rO7MMP/wGAUSOvZtP6rhxwVVUYNqKV2+8857jaGQzP7uNh0+b9/Pmvm3DYC3C5C/G1VeNw5hMKNJFIRtHpDCiyjKAqnUrTNTWbkFNJ8nInEgm3AmC1pO8JkaiXlCwjiQKxaJCkkCK7cCznzk1w4QXTB/W5OFkGcqx/9rOfAfCNb3yDSy655JTa6oh41NDoLwa9IXskqqp2CwM+nvW3bdvGxIkT+1zHaDT2muei1+v75Yahqmqn2tudd945aG+y/XW8J7vvxXMmHXvFI4jFYsQFI3qhu+GjCiqK0LsxFAsHsWZkd1uuqun1D/9O0EkkUgqKIGF25xALB2iqrewMxZXD7fznTfPIyuz9ZWbnvjKChgKkPmoH2T1FhINNNNUeJKe4pwFlEFXiYR96W09jJRWPMH2cp9t46fV65o908GFVDJ2xe06gEmln8ZTcHuuPHVnMvXkefvfIE6x/9RFuuf4qJhbpmTp+Iaqqsmj6KM6frev3GcNteyp4eauMaEy/0MoA5nx2BVSiK7Zw1zXzjrr9qRAKR3jk5T34peLO2r5NKry9L0Fj+1ZuuWzWadnvkIIcvn9nNpt3lFHX6iMQ9LMzYiNmHIVAuiJOmwpv7Y7jD+/kygsm8/RrW9hZI4EpB1V10dZYjiiZcRuG8uDfK5havJev3rL4mPvu+G1/9ZYF7DtQzfYDbaQUKM42MG/GOZRXNvLov7ZTVpdAVQWKcyQWTstk2sRTLwmi1+v599vPYe3GfewojxBPqGS7JOZPzWNocc+UgqHF+dyyNMUrH9TRlsxGUQ1Ul2/BZHYhijoUJYndFObL105gSP5wfv/YZ5TueBuAcTNvQFYlLNRywyWjcTktfLJlF4qu535kOcnUsfZe73kqAorS++82kVTQ683IvSyXFanX7wEEycG23W2MG9PTAAZ48vlNlNUNQZAEopEw4XAAd2bXZJuMlZ1lSdb95G3szolIeg+xiJ8PVjVgd8gYTU6QQ8yfBlU1LYw9rNZpe3sYny/K5Ekj0Om6Hvs5Od0jm/Lzc8jPz+n23fy5xy7SfcM1c8jP2cNnW1pobZPJzTUSCu5ClcYgSFZC4SCKLBFJRHBnlOBtq8flShuviZSCLPc9cWWzJamscmLuU5Vcoq0t0us4PvfsRg6UZqdrX3dGCWewb6/Kyy9t5eZb5nauO3p0EQ11pWzbFWTT+i0MKdRzzsISPJ4Qa9c20tCQwmAQGDXKzAUXTCTrJCd+6uvr+eSTTwAYP/aqI45dYt8eBxUVDYwaVdRj28qKOpqafRQVZXdTFh7IZ/fxMHfOeEaPyudr33wOq72QlCygqgas9kLaa7egk0wkE2HycyciyxKBQD1u9xjq67YRDLRjt+UTDDaSSgkEg15QFURRj5JSSSUVFEWmbNtHBIMzWLHyHcaOsnDrTbPIzj65iYbBzOc91nv27GHz5s3odDqWL19+yvsezNfp8aDlyA4+BtSQDYVClJWVdX6uqKhg27ZtZGRk4PF4+MUvfsGyZcvIy8vD6/XyyCOPUFtby3XXXde5zfLlyykoKOBXv/oVAA8++GCn5zYQCPDHP/6Rbdu28ec///lzP74O1q9f/4VQJxyMGI1GrELPnIvMgiIaK/eRWdjdQEwlEzRV7mLk1LndvhcEgd6i7C12F76WelxZ+ZisDkzWtEGXikeZOdpO1lHytSOxBJLuSM3iLiSDkdHmdmSnneqa7UjOAkyOTJLxKG6llevPG0arL8y7pa3o7F37SUb8zMlLMGVcT5GaJbPHYzXt59MDtdQHRARBodglcO70HCaM6pkHBmC32Xj3lae58/bbuP2S6Rw4cICf/vSnPPLII+Tk5LBw4UKWL1/OrFn9Z+B9vLMV0diLYrIgsN/npKauicKCnF62PHXeXbc/bcQegagzsLnOwdzKeoaV9OxbfyAIAjMmj2QG8L//2oxq7OllknRGPi2TaGxZTUV4BIJJ6NzWkzeCRDyCr6UKV1Yx+7wR3v5oK0sXH7+Y3ZiRRYwZ2fWSvKu0mn++7UPR59HheKoNwdMfBAhH97GgH7zUoiiyYPY4FvRdArwbE8YUMX50IW+/9xnvbTLgzuxehkZOhmhpizB5wlBKXJWkElGyc4uYPz2fYfltLJo3GbM5/du7cWkWz77diKrrOtepZITJJW0sWTin1/2PLDJSWtdX7xQUufcc7mPlOMbivYsmeb0+9pTrEQ/VVg4FmzpVfw+nvbUCT9bMtPhUMk4k7CUzu8sTKenTx/zMiw18/ctWNm6q5tNNYVJK+np+6Y1POWe2nUsungJAfX0TTc3tFBflkpHhOmrfj8WCc8ax4AhH4vYdZezaY6K+vpV2v0xtTZDGhl0YDdZOgSmzyUU47MVq7S26oJ3zl4ymdH8F0Hv/VFXB7uj5chwIhNi1U+51TARBYMf2JMuuCGOzWWlpaecvf9pOJJQDpH8E7V7YvqWU4SOjRINmTJJCVqaB0aNcgMLWrXvJz88kJ+fopWqOJF07VqEgfxoZ7pIey3U6K9u2NHUzZCsO1vPyi/tprLWi01mR5TKKh+/l6uvSavc/e+BZdDqF735v8Jb1y8hw89zTX+Xf73mCSMyOSy1CEAQKCqZyoPR9DHoLOl06JSCZjOFw5BON+UkmYwSDjbhcRbS1VYCqYDLaCYfb0OtNFORPRhR1JBIRmlv3E9el2LXXzHe+/xbLbxrFRReenonJs4UOkadLLrnkqGUvzxbEQ3/90Y5G/zCghuymTZtYvLjLm9AR3nv77bfz17/+lX379vGPf/yD1tZWPB4PM2fOZPXq1Ywf31Uiorq6ult+ic/n46677qKxsRGn08nUqVNZtWpVv76EnyhfJHXCwYYgCIzJNrIv2V15Um8wkFs8lKpd6zC5chEQUFHQ60QycvKQ5RSS1P3y760Gqs3tIeRro/ngTpx2OzICOTaJGUNdzJ085ah9Gz10CG/sKke09Z7PrYSauHnZApyO9DXR1OKlqr4Zt93CyGFdhvbIwlY+3VObriOrhxlTchla2HtNR4A5k0cxZ3JaxEwUxWPOgNbU1LBp0ybeffddIP07bGho4Ac/+AGBQIBnn32WFStW8NZbbzF27NijtnU8yLJMZWsKUx8ODZ3ZxY7y5tNmyO6tidOHkxydycGmfS2nzZDtQFVVSmsTSH3cDuIpHaXNToy2ni/hBqOF0CFDSm+08N7GapYe2ynbJ2+vaUTR9wxHF/QO3vm0hnnT5QERUhEEgQN1IJl7XuuS3sZ7G+pZMDveGe1yz7e+yjdu61l3derEoQwt9PDJ+op0HVmjwPQJHsaOmttj3Q4uOKeQsmdrkcXuv11VVcl1+Wny9x7SfTR1XwCPu/fXl9ID9Yi6rsmq3owvOZVApzd1Lgv46nrUf+0gpWby1/9bSzg+GlF0dc7+p5QCPlgTp9X7EW3tBmrqLeh0DhR5PyOHyVx/zQRcrv57Rk2eNILJhwXaJJNJfD4/q9fuY9u2AySTFlxuO4l4kFgsjNFY2DmpKImNXH1lHsOGFTJuTC37y3rfh0Ffz9w55/b4fu/eKgThaC/e2ezbV8WMGeN47eU9h4zYLlLJOO0+H5LQNVGwf0+AzZ/txm73YDJ4kOUDFA3fy/kXDqGy0k8qAcUldiZO7r1sj6qq/OMf/wBgwvgr+uxZ6jCNqeamNh5/tJxkPJsOZ7okOdmzs4FNG97myuudyNHJ7K/YyPLrHkOSdBgMVuRUjKGj4ae//HI3L/xAIggCf/rDnaxevYWnnjmAyz0KQRAYOfp89u19h0CgAYcjr1NVWq83E4n5MBosCIJAPBHGac/F76vB5RyC1ZpJLOojHG1DQMRqdqNG2oiG27E78njquTr2lb7Ct//9qgE+8jOTVCql1Y7VGPQM6N1t0aJFvXrBOnj55ZeP2cbHH3/c7fNDDz10ysno/Uk0Gu1UJzwbascOBJfOn0LzinW0GPLQGdLqnKqqIoWbmT4yl3Zbd8+Gqqo0VR0gp7h7fUqHJ4eW2oNkDem+vsmo57xphSyZfewQu8NxOR2Mcicp60WkT1VVRmekOo1YgJwsDzlZPV+Qc7MzuSq7b89vXxxvWYg///nP2Gw2EokEH374IaWlpbz22mudRusPf/hDSkpK+OSTT/rFkE3/5o/uuTqdEnTRJH0asgCx5OnXv1MUhYQi9Kgx3EE03N5rDmYHZnsG0VA7ZpubGC5CoRA2Wx9FYo9CbV0jdX4Huj4ulZhYwKZt+5k9/dTH/UQJBoOU1UsY+9DbS0l5vPz6R6xatQpBELj11lv7bMvlcnDFxUcv23Y4xUU5fOU6mRUf1nCw3oiot2EUWpkySsc1l1/Brx9eSU1bLU5X93xXVVVJJsPo9T29YoLcyLlzez+POp2QLjvSOSnb8/cRDjZjs3cZ1oIg9OkBlpNxmnw2HK6eolepRJx1GxScrtxOw0iUPJRXwSN/28z3v7vguCYuWlu9AGRmHj1P+3D0ej1ZWZlcfeU5XH1l92WxWIw1a0oJBBUcDpFz5s/CdKjG75VXjuUvf9lBMNx9UkMQ2rn66qJexZKMBglFSSGKvb/myHISo9FELBZj394kuiMO2R+oJTuzy4hNJWNEIl6yPF3PDUlysn1zOft2JbBb0x7/Ff4D6A2byc3zoDfImMwxRowqYvSYLLxtDezZswe93sDY0Ut77ZeqKhQUdP0gP/6wjGS8+znu8MYX5E0BKqioXIvbVkLCFCXTPQxRlEglY7TWNfJvN79Adq4VnT5K8TAn5ywazbjxp54ycCosWDANk2k/z77gRa/3IAgCo8dcREX5Kuz29HlUVZWsrBH4A01Ewm2Ew63IqTipZASD0Y7Vmkkk0kYyGcVq9hCJeFERsJndxJMRYmE/+YWTqaqL8ehjH/FvXz6F2b6zlPfee4+GhgYyMzO59NJLB7o7gwIttHjwMTim6b7AvPbaa/j9foqKirp5nzX6D0mS+MqyBezYV0ZpfTMpFbKtOubPn0pre4CnPqtDsHbNzAuCgM2VSWvFbjwl4zpfBiVBZawrSZaxmYOtSRKKSqZVZOZoD5PH9BSbOR5uOH8yT7y1map4BjpT2mhNRQMUGdu44fzBUfc0FosxbNgwbr75Znbs2MH111/P2LFjUVUVWZYRRZFLL72UTZs29cv+dDodRRkCzX3Yi6mon/FDT9xwP16yHSJ1R6mZmuU8/d5HSZLIc4Kvj+WKfPQSBaqqIh7yWqAkT9rj0u4PIPVidHUgiCLRPsJhTzfBYBjhGLVv31qRLglx/vnnU1jYt2DQyTBiWD7fHpZPq7cNX3uA4uIuEZkf3nsxT/9rDeu3bSchWxAFEbc9yZeuL6KtPcrHm+JI+q78PFGu56ZlubhcveeaT586itdXriehpj3jai/liowmO7FoAJv92OF9wUAjdmdJr8vC4VY8fXhyfcECVq3Zw+Jz+9aUWLN2H6vWNNPUYgFVJTdnN+cuyGHe3NHH7NfRMJlMnH9+75MNHo+Lb397Oh99XMr+A1HkFOTn61m4oIji4t5FoCZPGc0rr3xMPNZ79Ird0cqECYuor29EkW09Jrc6vIId+AP1eDK6n7f29mpcjoLOervt7VWYzS5MxiFUlB/EaLBhtw2jvhI+fLuGDdt+A8CS8y5Er+/dO2+11bNg4XmdnysronTWlTtEXcMOigqmAembqM2SRUqOk+1JG97JZBR/oJ7MjGG0tVcSbDfgshdTuRsObG8kt6ic5XdNJ2sAc0hnzhxFZmYDzz63jQPlcXQ6Kw5XPhWV67BZMwEVUZDIzRpNOOSloWl3WixMUZAOTU5Eo+1YTG5i8QAOex7+YD0gYNRbSCRj1B7cwJBhsyktz2Htuj3MnzduwI73TKQjmvDmm2/WlOAPIQrpv/5oR6N/0AzZ00xHGNHy5cs1if3TzKQxI5h0RDrfkDwTV0+K8/7OWtpEN3qTlWSglZHWOJctmc3Oslqawyn0Ikwclcnw4iX92iej0cjdV82jvLKWPdVeVFTGF3kYXvL5e7j64re//S3r1q3j3XffRRRFZs2ahaqmQ7U7DKSKigoWLlzYb/s8d2IWz28MIBq7v9irqspwh4+hRafvhWP2GCf/2hRFMvT0h+pidSycMb6XrU5HP+y8tSveqfR6OIXuJKFYC6Kpd6MlFmonIzc9uVLgSnR6rk6UkcOK0L27E9nQeyi1HG9nRMnxlTrrb3JysrAZKkjQu6c5Gffz8YcrgNMb7ZLpySDT0/2FX5Iklt94Lstv7H2bGVNaWL+5jnBUIdMlsXD+ZKxHKeUmSRLnneNmxUchJJ0Nk8VFONSC1dY1/kazk3CoHA4Zsqqqdv5OTwThKNEQgiBSXhFlcc9IXQA++ng3K95NIUn5dFxyvoCbl18PkUrtYeGC0/e7tdutLLt82rFXPIQgCJx/QQ6vvxpCkrpfQ4oS5Pzz8xAEgawsD3pjKajWHtsfTm/K8oqa6jRiY1E/er0Zk9FBW3slbmdh97rRqoGNmz8G4J7vfBOdpOf9lc2oSvr3JctxPJlebrtjcrd3hd6jUzrGPb3Q6SggEgl3Lg0EG8nMGIbPX4fVkonJ0HVsep0Fb72Fx/78Gd9/4CKqqxrYs7MRUYQpM4rJyTl+D/upMnRoHj+8L49AIMRvH/qEaHw4kmRAjscIhZqRlRSxmB+TyU6eZRJ1tZsJR3WYTU4SyQgGg5VIrB2nPR+fv5ZMz3DCYS+xeACDaEJSdZRtfwdn7lCeeV6gviHCZZdMwGw+ufvl2YTP5+O1114DtGhCjcGNZsieRurr61m5ciWg3QgGklFDCxk1tJCK6lraAyGKp5fgcbsAOHem63Ppw/CSIQwv6b3sxkCiqio6nY6FCxeycOFCqqqqSKVSnS9xqqqyefNm1q1bxzPPPNNv+50+YRjReCnvb6smYshHlHQokWbGZie55eKeeY79yZypo2jwbmVteRTRlDZQVFVFF6vl5vPyjmpw9CfnnzMeX3ALn5ZJiOa0B1pOxcgxNPGlm2by7poDbGs4PNw0TTwaQNKnX57joSauvKzkpPtgMpmYNExgS03vBtGI7DBD8gfGkJUkieljDKzb1/McAKRaP6G2phqHw8FVVw2uHLj8vCyuvuzEhFHOWzgOo2EfazbUEwtLhMLNyEkvNufIdKhoKkaWO4osN4CUhzOjkLbWcjxZPfMxPRl64vF6kHovxXU0+krzVRSFjz5pReqlTUmy8eHH9Sw458QN69PJggXjMBpL+eSTJmqrVQQBhhQKnLsol5kz0yHCBoOB8ROM7NnZfVulF82Ew1HVLs8gQCTaRoa7JD3BgNrdiAXKKj8hFvNjs2YxbNgYRo4sZt78KOvW7SceUygosDFp8iQ++XA7Lz29m4BfxuGUUBUvqprZ7byqanePfTTixW7tEofqWFeWE92M2MNprXPw8/98mWBLFrpDyfofvLGDiTMEbv3yuZ/rODocNh78ySVs+Gwv27br2bPbiJyEcKgFs8WNmlDIyBiKxzOcULCRSKQNk8GGIEgY9Na099kznECgEUnU43F1ec4z3cNobD+AwTmMTVttVFSu555/n6d5GI/Bc889RzweZ+LEiUydevxigl90jpbScaLtaPQPmiF7GnnyySdRFIX58+czYkTv4g8anx9Di4bQd9bh2UnHzVRRFERRpLi4u5rvqlWr+P73v8/VV1/d74qF50wfzfxpKtt3HyCWCDN62HDcfYRe9jdXnT+V2RNa2LC7gUhcxWMTWDRr8kl7Nk+Wa5dOY5HXx8adNSRkKM6xMGVCuvTQLVfMxPD2FjYfkJGN+ShKCm/9PgRRj8WegT6yj9svHcn40T3LdJwIN142lcCzG9jf4kYyHFLlTkYZYmvitmXHn1d6Orhq6VTaA+vZXe1AMjgBkFNxcqyN7Kj/FIDrr78ey+c0+XC6mT9nDPPnQCQSQRRFjEYjGzftIxCSycmyMHHCZdTVt/D+J5UcOBhDtSvEwjuRdPnojR5SySAAX75tONt2NLDms2QPg0pW+o6rV1WV4qLeX/C3bd9PLJHXZ25XOJrDjp0HmDxpVO8rHAepVIrPNpQST8iMGJ5NYVHvYcMnwqxZo5k1azTRaBRBEHr9jV9z3WQa6tfR1tolNJQu2dN1/pQe4d5CN2O3Y7t4IojZ5Oqxj5170t6tCWOWcbCsjZEjizGbzSxZkv6NqarKY3/9iAM7nIhiWgkv7ANFseMNbSUzc2pXGoxkxOerw2ROj5XeYCEW93fut2O9o70s+4P1GPTDu+UG6wQXezYpvGz7lIVLxrBhzUGiYRm3R8/CJRNOq/EnCAJzZo9jzuxxrFy5nffeU7A75nCg9D30OgtOZwGCIJCdPYaKqvWYTA4SsRA52WNIJiMoikwqFcfhSl8zsZifcKQNQRAwoKO+fBPWzHzaWg38+r/e56orxzBxwsDmCg9mOsKKb7/9ds3o0hjUaIbsaeJwdUJN7U1jsNNX2PusWbP44Q9/yJQpU07LfgVBYMqEk3/xPRXyc7O4KnfgywlkelwsXeTq8b0gCFx/yXSuiMfZU1qJ0ahjzMgLaWpuwWI24XT2zyy5JEl87dZ5lB+sZft+L7KqMrrIzqTx8/ul/VNBFEW+ctM8Kqsb2ba7iZQCwwqtjBo2hdzvvQp8MaNdDjfMZ83snoZQkJ/F7Td1v25bWtqormkiMzOLbVurGVKQTUlxPgJb2LA5SkpN54nqxXoWnWNi334vstozhNRqqmPxub3XcE4mFQSh71cGUZRIJI6e2300PvpoF++/10IqlYcg6FiRqsZi+QyD2UzAr8Nslhg7xszFF485KWXljnJMvWG1WviP7y9mzeo9lO4LoMgwb2E2TQ2t7N/jQKezYrfl4PPX4nKmI2sEIa2E30GHYrUk6kkmo93aD0e8HKxaC8DEscvQ6XoaBhs+3cP+7Y4eavqiqCPDOgaFnajycALtTVh0VmwGJ+qhSYnm1gNYzXmdhuzRRDQBojE/FnPvsvGCIPLemwf47KMoEm5ARFVVPn73A276yhjGTzj908EXXjiZ7OwyXnhhLyZLBnrJiLetEp2kJxbzk5M5gkCgiVQqRijciiCI+Py1uJ3pSb1gqAlVVfEcVt7I7SyiyVeOI7+IxsZ2Hv7DXvJyN/KjHy476rVxNlJaWsqGDRuQJIlbbrlloLszqNByZAcfmiF7mti0aRN79+7FbDZ3q3uroXGmoCgKZrOZZcuWDXRXzmqMRiNTJ3UJ6eTlnp6yRMOHDWH4sMEX/g5QUpRLyWHeuX/+85+Ew2FGjBjB/PkDb3APNFlZGWRlZZBMJtm2Nf2dIAhcuWw6l1ycYPuOcgQBpkyei06nY8/eKl59vYq2QCaSZCSVDDIkL8hN10/os1zX+HHFvPzadhB6DzUX1EbGj5t+Uv3ftOkAb62II0n5nR5fnc5JIuGktm4/WTljiMVh63YoK9/KN78xlUQiwZrVlbS3pTBbBWbOzKWgIBOTyXRSehSSJHHuoomcu6j79/v2VrJlczOxiIIg6aiqqCTgy8Sot6U9o4EaXI5CrJZMAsFGHPZcgqGmbm3s3rcCVZXJz5lIhsfBjFk9xQN3bGlH6qMelyTpGTa8AFHnpXRrNjrJcOh7A9BOrmcU1Q370ElGnI50vrui9F7rGCAa85Hh7D2Swx+ox2ochkRXSLIgCCjRHJ7531Lu+1U2Ntvpr1U7ZcoIpkwZwQvPr+ajj6NEQ0FiqTgmg41EIozFkkF25giqazZit2UjIqX7qcgkkxEyXCWdbSmKjM9fgwE9NfvX4Modid2eT1NzK1//xpvMn+/gK1++6LQf05lChxPm4osvJjf31KMivkhohuzgQzNkTxMdYRlXXXUVTqdzYDujoXEEsVjsmOs89dRTuN1uzj//fG3GWmNQ0XF/Xb58uRb2dgwMBgMzZ3T36o4bW8y4scXs2lVOuy9GQUEWw4ZOOWo7NpuVyRNFtu3smQerqgpTJ+mwWE7uPrFmdSOS1LuB7HIVEvDX4XCmc3ODoTweffQTWhpdiEImcipBu6+Kt98sJ5WIkkzFiYbbkFMJnPZ89JIBnc5ESo7THqxk6aXjGTlyBCXD3IweW3LMvo0ZW8KYQ+s1NXp55H92EU9ECYXb0OmM6CQLLe0HMepFovEgOl26jms44sVq8aCqKjv3psOKx425lNkLzDidPQ3WcLCnUvXheL1h/K26TiP2cCwmFwUFTuqbNtPmr8ZosFFZ+xkedwn+UCNOW3dj5GhCYalUAmMfhqqayGbVB3u45Iouxf1oNMon7++muT6O0SQydU4+o0YX97r9yXD9DQuYOauef/xjO7t2VqPTGUmmEkiCjCjqGJI/jcqqT3HYczsNVvdhRnok0kYk2o7HXUI8HgIg6WujpmEvw8aejyiWsHtPlB/+5wq+8+15ZGX1UeD8LEGWZZ588kngixntovHFQzNkTwPxeJxnn30W0G4EGoOTP/3pT7hcLi66qPdZ6Pb2dh588EHa2tpob2//nHunodE3VVVVfPTRRwiCwPLlywe6O2c0EyacWFmxG6+fRTK5nl17dIhSWihNlr1MHi9z/XVzTrofNTUJ+nAEY9CbCYaaOz/Hoj4qD1qxWzNRVRVvWzkmgx2jzopgFWhu2Y9BNJJXOB1VVXA50gawt60Cp20O9ftzqd8PH8oNZBbsZUiJlYr9ccJBGXemnqmzMjjvwim9GnnvvH2AeCwb+xF2qMXqISW3870fT0MURNaurqJ0byO+Ni+Njc20eA8gSXq+/s2lXHXN7F6PMyNTT3Nt3+cokQggyH2nYeiUIh5+ZAn5+V1G697dFXzw7l6qysqIR82IghmXJ8lFi7LY+mkLcqzn5MGRZYeOpLkh3vnv0r3VPPWX3cjRLCAtQLf5kyrGzznI8n9b1G+TTEOH5vPAA/lUVtZx34+eJxbVYzRaCIVbsVkzKRwyg5q6zQDoRWPnMaiqSiTaRmbGcFrbyjGb3Bj1NlRFwYCBvZtfwuzKxekuIBTU88CDH3PD9cM555wJZ22ViQ8++IDa2lrcbrcWjdUb/VRH9iji8RoniGbIngbeeOMN2tvbGTJkCEuW9G85Fw2NU+WNN95g7dq1fOMb3+B3v/sdV1xxBUC3GXq32015eTm7d+8eyK5qaPSgw1uwePHiHuJkGqcXURS5/bZ5NDd72bmzHgSYNHEkWVmnVo/0GLZTN8KhVjIPqdL6fNVkuIcS8NXhdhXibTtIONjMsMJ5xOIBMjPSYj4+fw0OWw4G/WEeY1WidFeA9oZcIG2ZttXDey+nqK78iDvvPu/IXbNvbxjoPcJKJ7nZvq2RZVdM48ZbuozJb3zjGwBcffWVXHVt3yXMZs3LY/eWeiSxZ7kpWQkxYlQGuzb0fV5EwUA81l3Ia+z4oYwdnz5X8XicaDSK0+lEEAScjq2sfCWKJHb3oqscPc/ZaEqrQ6VSKZ75353I0e6pDjrJwt4NKd4r2MKFl06n4mAd+3Y2IEoC02YNPaXatSUlBdx//7V89z+eJxbwIyBgtXiIxtoZVjKftraDBMMtuJyFCIKAz19Dhqs4ndvsGEIg2EAsHqSltQxRkDDoDIjBCE3eTWAxMX7iMt58U2b79o/5+tfPRZJOf03xwUZHWPFNN92E0dizNNzZjnjorz/a0egfNEP2NNAR9nbrrbeelTdCjcHNz372M5YsWUJ2djZf+cpXkGWZq6++utvsuSzLSJLE+PGfT01VDY3j4XARPS3aZeDIzvawZEn/1RsdMdxMZWXvy6IxP0Zjl3EnCl3PVFVVCATqyXAX0+6rJh4LYjFngAA2a5cgliynuhuxgC9YR1bGyB77E0Ud+zab2LmjjImTulcbSCQU9Ed5pCcS6hGfEzz//AsAFOfN4uVnNzB7QQkFQ3rmuY8dP5TFl7bz4YoAOrFLvT2lBFhymZUp00ezbf0udIKr131bXT6KS2b2ugzSufaHGyZLLp6KybKbtR82UF+tIIoqxcN1DBllpXZf722k5AjT5xQCsPqjnSRC2b16p0RRx/pP6inb56Vylw7dIeP8w1c3MXGunlnnFBOPJRg7fkRnrfLjZcyoIn5w32X84sEXicRD7D2wEo97KOFIK5mZI4la2mltKyfLMwJVVRBFHYoqE436SKXitLVVYjRYcdvysFmziSeCuCkgHGljx/qnySmZQnu7hV/9agW33z6LwsKzJ0fU7/fz8ssvA9r9VePMQTNk+5nGxkbeeecdQLsRaAw+SktL2bVrF8888wxXXnklX/va1/je975HIpHgxhtv7FxPm4DRGIysXbuWsrIyrFYrV1999UB3R6OfWHJ+EX9/rBZV7Z6fqKoqgWAj2TldOb6ycqTHUOis7agoKSRJTyIRxubKPNSGgij2vJ8JiH2GvkqSmW2fNfUwZHNzDXhbej8GRZHJy+9e2ufP//N/eL2tWM0epOB8Nn0gsv79nZyztIJl1/YMxV562TTGTWhg/ZpqAr4kDreeueeMoKg4rTo9ehKU7eiZ2yqrCc45N/uo4bCfrtnN1o1eAv4UDqeOSdNdpJIKrgwjOkMEsy2OXqejqQ58kf24LN3DmBUlxbhZSUaNSUdBeJsTCELfz4mqshZi3gnoDutS0B9m1YoEOz4RkSQDOuu7zFiYwbLr5pxQGPKCuWN56aV7ueXmP6DKFqJxH/5AHXZbDmaLG297JaGIt9s2iWSEtrZKdKKBDEchNnMGqVQcSdQhy0ncziG4HAX42hoQnBAKjuMPD1cxd14111wz67j7dibzr3/9i1gsxtixY5k5s+9JkbMZgX6qI6vFFvcbmne7n3n66aeRZZk5c+YwZsyYge6OhkY3HnjgAS6//PLOeoD3338/06dP59/+7d94/PHHO9c7VvkGDY2BoMMbe91112Gz9QzB1DgzGTlyCLctzycnp5lEIoCipJCVWtp928nM6jKoZNnHjOkSyVRatKfjPqWqCqqqoDOYicb8GPRWojH/oa2EztI43TjGe2Qs2nOb2XM9yHLvQnk2RyPz5o3r/Oz3B/nLn54CYMKIpYhi2m+gE5ysfSvJpg2lvbaT4XGQiofYt6WOj189yM+/u5Kf3PMs69fs4bYvz2PkJD8p1ddtm1nnKlx0ad/luP7xfx/z6tNRasqc+Fs8VOwz8fc/7eXdFxUq99mp2CewZ7OJg7s8hNvzsBiL8PqraAseJKHUorfVoneUU12W4Nc/fo+Xnl0PQt/1iCPRduzm/G7f+YP1mAx2Ml0l6HQmBEFEjmTy6VsK/3pyTZ9t9YXVauXlV35ARi7EYiF0OhN1DdtRVRW7LRsZmdb2KvyBeqCrLrBOpyfLPYxozE8sEaLFe5D6xt3UNe2i2buftrZK8Ico37WS2urdvPNWC//zx7dIpfpWgf6ioNWOPTYdqsX98XcirFq1issvv5z8/HwEQeDVV1/ttlxVVR544AHy8/Mxm80sWrSoW2pYW1sb//7v/87o0aOxWCwUFRXxrW99C7/f37nOxx9/3DkpeOTfxo0bT+W0nVY0j2w/oqpqtxuBhsZgQlVVXnnlFd5++20CgQAAhYWFPP/88/zgBz/gwQcfRK/Xc+utt2oPMY1BRyQS4fnnnwe02txfRMaNK2LcuCIaGprx+wMMH57OJ121ag/NLUnMZolZM0vIz5/J8899yubP4tht2YTDXrztlbgcQ1CpAwRCkVZ0kgGzydnnvexYk3We7J7qUwvPnYC39TM+XRNFFNPeY0VJ4XA1c/uXJnXb1xsvraO86jMAJo68tFs7kmjis1V1zJg9utv3AX+Qhx78iLgvByM2jIdEpUKtIf7+++203hLgS19bRFOTlz27ahER8IXg0itnEolEWfnmRrasrUFOCcRppGJfKxJW2oNeiormIOmMGIxWvG0V5GaNJm3kqySSYTzurvqwBoMFT0b6s8FWSiyQh6gOQQZiwOZmwNhACis6eua8xhJBMuzdS3ml5CROW0+1ZlHUsWV1OxddEexVzfloiKLI3x/9Nn/92+u8/1Yt0Wg7kWg7NksWspxCkiTaA3VYTC50kh5B1GE02AlHWjHozdQ170FCJMszAr2kR0DAZcsnHPGSikXJtQ/H723ms3UGysv/xQ/uO5/cQVB7/HRQVlbG2rVrEUWR2267baC7o3EE4XCYyZMnc+edd3LNNdf0WP5f//Vf/P73v+eJJ55g1KhR/PznP+eCCy6gtLQUu91OfX099fX1/Pa3v2XcuHFUVVXx1a9+lfr6el588UUA5s2bR0NDQ7d2f/zjH/P+++8zY8aMz+U4TwbNkO1HtmzZwq5duzAajd3CNDU0BgPRaJT333+f2bNn89ZbbwHpWrGiKPKd73yHhoYG7rrrLurq6vje974HoBm0GoOGV155hWAwSElJCQsWLBjo7micJvLyssnL61LTXbJkco91brhxLsUl+9j0WYjKyigtjQECIQlJNODMGEJjUyluRwFCu4jHXYLJaCcQbsZh7WpXrzMSi4cwGXt69lWxjQXn9e7hvOqaWZyzsI3PNlSRiKvk5ZuYPee8HvfKt95agaLK5GaOIcvdUx26tSne47s3X9xG3Nczf7ajduoHrzUyb7GPnBwPOTkekskkb71VTVVFA//z0w9Jhq3YLQXsKl9JUfYkRmRNpj1Uh8NQgL+5HDmVwGrOwICAv3YvIUmPoipIJgthfQtmi5v2tkoERUUVBMyWDNrbjdjMOhpatqHXm8nKHJU+1ngxBsc+Uv60GnK3/toD3cQDI9E2LCZXr+cTQJTdbP2sjEUX9O1V7gtBEPja3VdwzvxSvvfd59EpBiSdHn+wHoPOSk7WaGrrt6KTDCRTYWTFSTIVo6l1P6IokekeioCA216AL1CHrCTR68zYzBINLXvQS0bMqouqfU1886svsvC8DP7936//wj0b//nPfwJwwQUXkJ+ff4y1z14Gqo7s0qVLWbp0aa/LVFXl4Ycf5kc/+lFnys0//vEPcnJyeOaZZ7j77ruZMGECL730Uuc2w4cP5xe/+AW33norqVTqUNkwQ7e6wclkktdff51vfvObg/p61wzZfqTjRnDllVficrkGtjMaGkdgsViYP38+iURXSFhHTlVOTg7/+Mc/GDp0KH//+9+55557NMVCjUHF4SJPZ2tpDI0u5swZw5xDaaaKorDy3Q28+9YeWttjWG0emtvKqW/ahbt1CCaznVgsSNBuweMehqroycoXMduaaK1LdRdQ0rVy9a3FR1VizsrK4NLLjq6+++nGdwGYOPKyXpebzD1fv/Zs8QG919N12HLw+qvZsPoAS6/onr/4j/9ZgxJz47JnsrX0VcYVnYfRYKW5vRyb2UND6350opEsTwkCoNeZsBi7qy+3tFQQFmrIshUhSOmXVm9rHS1tZSi2QvJtBbT4q2hsW0s0GUIn6gjF/LQHV+AwZBOMekml4ritWdiMLgQq8CfbGDbmQgRRQq/vWf/2cJRTzGaZOGE0b73zY75zz0M0VDYjCRJqKkU8HmRY0Tz2lX9IIpkkEGzEavJg0FkwGiyocooMVwlt/mpMBgfhaCsuex5mY1pwq75lD22+KpyOIaRiUT549SCffPRXQgkfs6bZ+dnPvnlqHR8k3HPPPeTm5jJqVN8lnjQGJxUVFTQ2NnLhhRd2fmc0Gjn33HNZt24dd999d6/b+f1+HA5Hn4Jrr7/+Oq2trYM+AkozZPuJRCLB008/DWhhxRqDF0EQOo0ARenKAetQKb777ruZPn26ZsRqDCpqa2t5//33Ae3+qtETURS5eOlcLl4695jrxmIxYrFYZxmaxsZW1q8+mK4j69Gz4Ly52O2nln+9Y8cOKqv3I4o6xg27sNd1xk7pWcYnEpYxHWWORhAE4r3k7nrrVVzWTMIRLx57IUaDlWCkFactj9b2CqxmJ4qcxGnJpi1Ui9PY3eubSsXRiQbcti5PnKqqtLVXMDo3PVvQ7D9ItnMo3mANHvsQKhq2IaGQYx1ONBHEoreQ6R5FhjkHk77r/AXqqwmbRUwOD0antdfjkgUfEyafeuiiIAg8/Id72bWzlP/83quIGInG/bgcBWRlDKONCvyBRlraD2DQmdHpTIiHxJ5EQSIcbe30ngfDzQRCTQiCiM3kJhZpQwCUeBRfdQOIOjZuUrjh1iexW2VuumECS87rn/DLysoqXnnuAw7saKC1pZ2G2mZsNhtf/c+LqKmpY9iwkn7Zz+FkZGTw9a9/vd/b/aLRkTPaH+0AnWleHRypLn48NDY2AmmHxOHk5ORQVVXV6zZer5ef/exnfRq5AI899hgXXXQRhYWFJ9SfzxvNkO0nVqxYgdfrJTc3lwsuuGCgu6Oh0Y3q6mpeeeUV1q1bx2WXXYbD4ejm1epQKc7Ly+Pyyy8fqG5qaPTKk08+iaqqLFy4kKFDhx57Aw2NPjCZTJhMXerCubmZXHldZr/uoyN6YNqUuZgMPY03V14L51/Ss06tO0tP1NvjayBtWCpyktwhPdvrEJKKJ8OYD3lak3IMuyUTFZl4Io7N5MYXbsBt7Rk26o804zkip7W6aQf5rpEIgkB7uIFMRxHBqBe7KZNQ1EsyFaYoYyw1bXtJymGyrUVkWgow6LorNztMGYixdprVOuyW7B5lkFRVZeRUkYryesoP1DNp6nCsVkvvJ+E4mTBxNK++/X1uvPoXJBMxAsFGJEmPTmfEbHaQSMbQCQZSyRhWkwt/qAGj3oZBn95vJNpOLObHqLegKiqiTsCkt5FIRtFZDGTY8oklQzQ3HKS2thLVJPEv/VBWvP08//3ra4+p+q8oCn6/n7LSWt59bT17ttWQjOhRUqCoKXSCDlEw0NJ2EKvJg83gRpTTExh3XfUg8WiCbz9wI9ferD2rP2/6O7T4SCPx/vvv54EHHjipNo80sA8P7z+cQCDApZdeyrhx47j//vt7bau2tpZ3332XF1544aT68nmiGbL9RMeD67bbbjvhumgaGqeT9vZ27rjjDmpraxk7diz33HMP8+bN45JLLumxbkfOrIbGYOFwEb3BHuKkoZFMJnnqqbRa8Y/v/w/sZjNb1rXS1pLEYhMZO9nJxVcsxmw29dh28uwMPl2hIAg978FtgWqGDDMze37P2t6qKnf+Wzns3wCCIKKo6TZVVe2jFFEvx5GKYDW5D7WvIIl6knIMhzmTyqZteGz5NAWqEAURs86OSW/pYcR2YDO6CcgtBGOt2CQJg5CXLpck+TA52zm4x0r51giCIPD6U58wZZ6Na2+ZhyzLnQr7J8NzL/+Iu7/0EF5vArslB73BTLFnJJU1GwjFWtN9NzkRgHgyRIYjbVRE4/705ICqgqAiChKykkIn6jAYnQTDzSiyjN2SSTjaTsDfROknzyFKIrNefxWXK4eEHMdidmEQVSwmEwbJRCKugiJh0FtQUjKKmkKWkxj1HlQhiaAXMOlsJFMRGtsOYjdloqIQTYQwGtKx125TNklB5m+/eJP/+vFjfFb+6kmfH42Bp6amBoejq270yUTDdeS1NjY2kpeX1/l9c3NzDy9tMBjk4osvxmaz8corr6DX9xS1A3j88cfxeDwsW7bshPvzeaNZXP1AS0sLK1asALQXLY3Bxy9/+Ut0Oh3vv/8++fn5PPXUU3znO99h1apVLFmypHPWLhqNYjabj92ghsbnyPr169m/fz8Wi4Vrr712oLujoXFU3nnnHZqbm8nKymLp0qXo9XoWH2eQ1mVXz6ah5j3KthrR67ruxe2BemwZcW7/9wW9elgkU4SUnMCot9LaXkGOewR6yUQ8GUaWExj1lkNGaBaRuL9HfmyvdNuPcOi/6f9HE34yzNkkUzEkQUSvNx6zLqYSD+NxlTDnIpnsXAuplEpDfZhNKwuQJGPn7qIBiQ9eq+eTFS8QjQZRhAjubCM33TGP2fN7Cn8di//9+3cIBALcdfv/YpByUdQk2ZkjqKxeT0BVEUWRPM9Y/KEutdZEMpb2pKsqiUQEIV11GJPRgT/UiKqCIidBUbGbMyjwjEJRZHyhRkRBIhUJk0pGsJoLsJuzEQUBQZUwGCHDXkhboJqUGkcUzVQ37SQRCZBKhMl0FBCXTLSGakgJYLKZUFUBAxIm6ZCXWpYxCDqSqoROFpk3+hrWlb7Ux9Fr9DcCx6zcddztADgcjm6G7MkwdOhQcnNzee+995g6NS2Ylkgk+OSTT/jNb37TuV4gEOCiiy7CaDTy+uuvd4tMORxVVXn88cdZvnx5n4buYEJzvfQDzzzzDKlUihkzZjBu3Lhjb6Ch8Tny6quvcvfdd1NUVIROp+OWW25h6tSpnXVjBUFg5cqVzJ8/f4B7qqHRkw4Rvauvvhq7/cTKc2hofN50RGfdcsstJ/wSKIoid3/nIpbfW8CQce1I9hrMWZVceXsO//XXmykuyet1u+u/MpOWwAEsZjfxVIwWXwV2Syb+cCN2Sw7xVJRI1IckGYjE2ntsr5dMJFLRbt8JCETi6fy9jjq8KuqhfupR1BSSTo+sKsRTkc5lfaLXIysJCoqczDlnIvMWTmDXZ1EkqcsDFY35SKYimPV2gsEgBsmJwzicaIuL//uv3dx19T955L/fZsWrq9iycQ+yLB9lh104HA6ee+X/cd0dw/AHq5FEHRNGX0pezhQO1m2mpnk7spLqNGZTqRiKIqMoMjpJD6iYjA4C4WYkUUKWY6iKjM3sYmT+bPSigUQyRjTiR4dIhjWffOdIdEmFQFslNXXbMeoteBxFBMKN6CQDJoOd/ZVr8DYfJMOUwejcmWTbivBY85hSeD6TcxdgVHW0tpchIoKSFmms9e6jqmU3VS27cJoysaj2bnoXGqeXgaojGwqF2LZtG9u2bQPSAk/btm2juroaQRC45557+OUvf8krr7zCrl27uOOOO7BYLNx8881A2hN74YUXEg6HeeyxxwgEAjQ2NtLY2Njjd/Thhx9SUVHBl7/85f44ZacdzSPbD3Q8uDRvrMZgY/fu3bhcrs4Zv47aiRdeeCGPPPIIFRUVDB06lIceeogJEyYMZFc1NHoQi8V47rnnAO3+qjH48Xq9vPHGG8CpXa8Tp4xk4pSRx73+7PnjyMxy8NT/riY/dxiVNTsJRFqwmt2E422oqoKiylQ378BtzaXFV4HbXoBOSoftmk02YvpKdMmRnaHHQ7ImUN+yh5KsyZgNDsKxdvSikUQqSkHGaNr81WRaC2j0lRGNR4gYQrhUBbGXsOhEKo4jazjOHB/TZqYFufbs2k/cn8HhmSyRmA+3fQh1TTvJdA8lmYwiIuJxFqOqKl5/Jbs+DVO704GqtvGU9Ax5RSaGjx5C8UgX02aOOaoQz+XL5rP0ktn89D//SfWBBIqcYvqEdE3OQLCRprYyzEYXJqMdWUmBqqDIKWKJIEa9DVGQUFQZQZQQBJF8zxiCkVb0OiP+UANWkxObyY0kSliNblRVIRTzIiJRV7cFmz0Phz2tSi3LMia9naysbDKsOQgIeKz5neffrLfhMHvIsOaxu3Y1bcEwAKIqoyRlBCVFbfNBdJLAkonX89HuF4/7etE489i0aROLFy/u/HzvvfcCafHDJ554gu9973tEo1G+/vWv097ezuzZs1m5cmXn5O/mzZvZsGEDACNGjOjWdkVFBSUlJZ2fH3vsMebNm8fYsWNP81H1D5ohe4rs2LGDrVu3otfrtdqxGoOO/Px8LrusZ/mHMWPGUFBQwN///nfuvfdeVq5c2ae6nYbGQPHaa6/h8/koKirq9hDX0BiMPPfccyQSCaZMmcLkySceBnsqjBk/lJ//sUsILRAI8emaLTS3NHLRxYvZvbOcT97bStWBGuS4QEjnZejwQoaNLGTstGLGTriEd15Zz9ZVjbQ1xbBk6pg0Jo8d67biMRem82wRCERaMOpttEeaMeutyKqKwWDCG6pHUCHfObxbjm9KTlKTqGFCSRa3fXV6p6EpSVIPL66AQHugFrPJiclgJxLx4nAWA9DqO4jHUYwoSqiqSovvIHZLFt6DVsq2VaCiojduIneojpJRDmbNH8voscN6nCedTsdPf/0lIpEoD/3mear2pIjFgzhs2Zg8I9hX+QlWowODzpI2aBNRVCCa8JFIpfN4k6k4NksGeslIUo6RTMZJpeJk20tATZFlL8EfaSKaCGDW27AaXchyknDMR62/Br3ZRauvknCwkczsaVj0DgRB7DV/OcOaS5O3ggxrWuQrx5hLIBUgkYphM5hpjbWixnJ7bHe8KIrSb0q8ZwOiICD2w7k60TYWLVrU6YjoDUEQeOCBB/oUijrW9ofzzDPPnFDfBhrNkD1FOkRILr/8cjwez8B2RkPjCNxuN9/97nex2dLlEDpuZIIgcPPNN/Ovf/2LxsZGpk+fzpAhQ47WlIbG587hInqaCJnGYOfwWscDjcNh46JLFnZ+zs7JYvH5c466zdKr57L06u7fybLMU4++yrr39xKOhFEVHV6fSoZjCBUte8iwZRJNxJCVBFVtewjEvThMWehEkXAySO54F9+4/TIWLJ7UTc13zLgRWDL2E/dlde1MSGfaCoKEP9SA05YOpU4kImmP6CFDry1QTZZraKdBm+0aTjwRIhRtpaXMymerN/DGU3uIJwKIgh6dJFIwRsc9991EcUkRgiBgsZj50YN3sH7tTv7y+zUEIwkctjwK8iZS37ALb6Aeh8WDxehAVhKoigVFkdNGuiIjiXp8oQayHCXsPPgeHns+iVSIbEcJ4VgbsUSQDGsBSTmKLKcIR9uRVQWTzoqYknEZnEhmGb1kJCHHyLD2HjYeS0Zx6m0YhPTreo2/HJvqwCKZkZUUTr2Leu++470sKC0tJR6PE4lEmDRpEhbLqSlEa2gMNJohewokk8nO2rFa2JvGYKXDiIV0DlYymUSWZe68807+53/+hzVr1vDhhx8OYA81NHrS0NDAu+++CwwOw0BD42js3r2bjRs3otPpOvPSvghIksTtX72G27/a9zrJZJK3V6yktrKZCy45l5GjenpCj0QQBBZeVMA7zwaQxLTojHrI6wugKKnO0OdQ1EuGY0jXOoKIIIi0+SvJdg1HVWVC0VYynSXsPvgemY5CInEfOa4RSKKeRDKMv1LhF1//kFjKhztLz6xFQ7l2+RLmzJ/IrLnj+c/v/oOGigMYDFbycycgywkCwVZqW/eiE/X4lHqcthwkQUBBIJmKYZBMiKKEoqaNb0VJYTN5qI+UYjY6SKQiiIJIOO5HkgzoBRE5FScpJ7AaXLQHG5FV+aje0Jc/+Rk5jvxOdSC73oGcUNJqx5IZXzJ0TKEtgD179vD73/+ef/7zn9hsNsaOHYvdbmfx4sXccMMN3UJLNfpGEI7QQTuFdjT6B82QPQU61Amzs7O5+OKLB7o7Ghrd2LdvH3/5y18wGAzYbDYmTJjAxRdfjMFgQJIkjEYjt9xyC++++y6LFi0a6O5qaHTjqaeeQlEU5s+fz8iRx58vqKExEHR4Yy+99FKys7MHuDefL3q9nmVXXnrC2y2+cAoq21j9Tj3RdjeiqEcn6QlHvDgsOURiPiwmV7dtoolgZ61cDoXEtgXq8DiK2V+zhmz3CAKhJjKdRShKCr3OgCzHcJlzCUSacZnzaagp5+UnNvHqE5sQEJF1Pn72yJdo98Z55tFthAJpL7DJZGX00EV426sJh5uJJoKkkjEkUU97KoTLmo8v3Ei2s4hWfwVGnYWUnESWE1hN6XDiYKwNSdQhIpBSEijISIJEKNaGRW8nEveRSMWIp6KYJDNOS043w9ZldiGrcUxSekI6kYoQi8ew6p2E5TA6EUzCsUXFvvWtb2E0Gvnggw9wOp188sknbN68mVdffZVPP/2Ue++9l4ULFx6znbMdoZ9Ci7VQ7v5DM2RPgVNRJ9TQOJ089thjPPTQQ4iiiNlsxmKx8MYbb/Doo49y5ZVXdoo/ff/73+fuu+8e4N5qaHTn8NqxmjdWY7CTSqU6a8dq1+uJcd6FU1h8wWR27dhPSnZSczDAv56oQFEziR0yZDsUmJ3WXPSSiWjch9no6MzFFUgbtKoio8hJTHorDks2bYFq4okUmc4SWnwHcVhyqG7agV7U4TB70EkSBp0Zi9HJn7+7CSnDy813n4PTbaPNG+KD9zfz2arNWIxu7I5cWlrKyHYVEQi1oheN1LTuwG3Lx6C3EIr5MVrN+CJNJJUUiWQUnagjnowRibejyEmSqTBJOYUk6ognwzhN2aTkFPFkG4FQC6KgotcZCCWCFLhGsn7HCziNVlAVIsm0gjSqilE0E074cFuyCcsJknLgqOe4ubmZTZs2sXnzZoYPHw7ApEmTCAaDvP/++/z+97/ntttuY8WKFZroo8YZh2bIniRer5fXX38d0MKKNQYfP/nJT/jud7/LPffcgyiKlJaWdoYQ//Wvf2XKlClcd911mEymzmLaGhqDhU2bNrFnzx5MJhPXX3/9QHdHQ+OovPfeezQ0NODxeLj00hP3TJ7tCILAxMmjAZg6Dc49fxx/+K+Xqdgdp7HtANmuoSSSERRFRq8zEojEga6yQB3o9WYiCT9Oczb+cCMuWx6+cAO+UANuWwEN3lIkJNy2IchKnAxbAQApOUFKiSP5c3j9oUb21a0GASwmK+NGOxgzbSyvPb+J/LyJtLYdRFUSGPQmsl3DafVVkkhGsZkzCCYCKIEKMqx5pOQ4bcE6Uqk4iUSUcKwNpyULu9GCgEBK78QbacCAnmQygcPswaDXoRdM6IxGyht3YDeYMElGdKKE2PG6rsooSgqTaMIX85ISVW6955qjnt+Wlhby8/NZt24dw4cPR5bT4cx2u52rrrqKq666imnTpvHGG29ohuwxOJnSOX21o9E/aIbsSfLss8+STCaZOnUqkyZNGujuaGh0snv3boxGI1dffXWnQM7o0aMZPXo0V111FY8++ij33Xcf5513HsuXLx/g3mpo9KQj2uWqq67C6XQOcG80NI7O4dFZBoNhgHtz5uN0OfjJL+8AoPxAFevX7iYZLuDggWoi7SaMehv+UBOiIJGSE6ikozhi8SB2cxYpJYkOEAUJAfFQPVgD8WQIk8FOSo7hsXfk3Kq0hWrJdg6j1V9FddMO8t2j0EkG2gL1bFt7gD0bqvHYhqC2NSP7vejc2QQjXswGB257HqFoO/5gPYWeMYiqjsrWbaTkBHIiAaJMhjkPAZlUKk61rw6r3kg40kaOs4hw1Ide0hGKtBBKtJFtG47RYCThq0YniERTYSRJh0t0AaATJBLESCkJ4rKMoJf43o/vPer5HD9+PDNnzuSxxx5j9uzZjBo1CkgLeYmiiCAIXHrppaxcuZL77rvvNI3qFwMBjiMj+fja0egfNEP2JBlM6oQaGoeTlZWF1Wrld7/7HX/84x+BrgdWRkZGZ7mdNWvWcMstt3RTktTQGGji8Xin/L92f9UY7Ph8Pl599VVAu15PB8NHFjN8ZHHn53g8zs5tB2htbqe2PMGnH+/DYR5Kq78ShzUHEYlApIWS7Mn4wg2oKJ1Gg14yo5dM3fIT/ZEmMmxDSKZiNLYdYFjOdOKpMKGIj2ZfBcOyp5BlL+xcvyhjHDVte2kSAsiSQFuwHrvZQyqVQFFlJFHErLcQRyCshimwjyCaDCJhoD3SiNPoJBhtJds6hHDMTygRwCjqiaciiIIOf7iBiortOA1WdCLoRD06RSAYawPAIBmIqBEkVY8gKSjJ40tr+9a3vsVtt93G3Llz+cY3vsHXvvY18vLyUBSFQCDA6tWrmTlz5qkPmIbG54xmyJ4Eu3fvZtOmTV84dUKNLwbZ2dl85Stf4fe//z3Dhg3j61//Okajsds6TqeTsrIyzYjVGHS8+eabtLe3k5+fz/nnnz/Q3dHQOCrPP/888XiciRMnMnXq1IHuzhceo9HIjNld4a9fuWcJe3aWs+YDkX1bGygvq8Cgs9DoK8Oks6CiYjbYiSaCxJMRDJIZpC6vuaIq6CQDNc27cVpzMOotxFNhvKEa8txDuxmxAIIgUuQZT6o5QUKJI+pNNPkOYjQ5CMd82ExuZEXGH2om21FISk0iKCoGUY/T6CEhh8mxF+ANNCCnYlh0JmwGB2ZzAYIgUNm6lwJrBrKqYMSAzWBFUVXiuiQA7ZE2TJKZuJIklogzeejxCTRNnz6dPXv28F//9V888sgj/PrXv2bOnDkUFxezZs0asrKy+MEPftAPI/TFZqDqyGr0jWbIngQd3tjLLruMrKysY6ytofH5oaoqgiDwzW9+k2AwyP3338/vfvc7vvKVr3DllVciiiIbN25kzZo1/Pd///dAd1dDowcdIk/Lly/XJlo0Bj2Hi5JpSqQDw7iJwxk3MS1i1Nzk5eXn32bFC9swihnoRAPReAC9ZMRidhOINpOpK+zRRiwZxm3Nxh9pwqAzk0zFyHOO6HOfTksOe1s+w2zNIhIPoMgp/IpKUfbEdIkgUcRqsCMrMoFkgAxzLsF4K5FEAAMCyVQci96Ey5BBJBXCJBppCtahJ4xVb0dAIKkkSSlxwnICjzkDAFWUQVFRUTFINoKp1uM6R7IsI0kS3/ve91i+fDmbNm3itddeIxQK8R//8R9cdNFFeDyekzj7ZxdajuzgQzNkT5BUKsWTTz4JaGFEGoOPjhcpSZL4z//8T2666SYef/xxnnrqKX7+859TUlJCPB5n4cKFWjSBxqCjqamJt99+G9DurxqDn9LSUtavX48kSdxyyy0D3R0NIDvHw1e/dStf/datACiKQm1NHe+9uYktq6rxV8ZoC9aj15lxmD2H1pERBBVFSSFKRvyRVhKpCJLY9yuy1eigKD8HgyOfXbvrMIlmMpwFtIUaCMf9yEoSRVGIJcPY9W4kUY+EjpSSxBtuxKq3YBCMKKqCWTDSFKrBlArjMeUhCekJPEVVaE/6EQWJUCoKpEOLVQUCsQAuex5/e/dXx3VeDp8UzM3N5bLLLuOyyy47qXOsoTGYEAe6A2caK1eupLGxkczMTC655JKB7o6GRieNjY3U1dWhKF1KjsOHD+enP/0pu3fvZu/evTz88MOdubEaGoONp59+GlmWmT17NmPGjBno7mhoHJWO6KyLL75YU38fpIiiSFFxIV/+xlX8+flv8/K6X3DR8uHUtu+goX0/DnMm3mANWc6hBKNe9JIRuykDSZR6qCIfTjQZIjPfxt//9W2KS4YQS0RJJWLYjU5KsifjMGcTTvgREFBREQWRSDKEy5RNJBkkIUcxSEZkJUEg6UdM+sk2ZnYasQCiIOIxuJEEEf0hD54iK4RTYXKdRYiiRGFJ/gmfE1VVAUgkEie87dmOcKh2cX/8afQPmiF7gnQ8uG6++WZNnVBjUHHzzTdz44038sQTT1BeXk4sFgPSD3Kj0cjIkSNZunQp+fn5nWrGGhqDBVVVNRE9jTMGWZb55z//CWgl+M4kJEniK1+7mVc//TV//+Cb3PjD4Vz+b6PJHysRSfiJJgIkUhF0konGQEWf7QSjXn776H0IgsCLb/83ol4hmPASS0UQBYGS7Mm0BBvQSVJaRVk0kmMtJpwIIIl6wskIyVSUSCJEY6CKDF3f6uw2ydopWJUihUmwoxP1BOPtfW7TYaz29l2HEfX888/z5ptvEo/Hj+PMaWgMTrS32ROgvb2d1157DdAeXBqDi23btrF+/Xp0Oh133XUXixcv5oEHHmDDhg34fL7O9e6//37+8pe/DFxHNTT6YNu2bezYsQOj0ciNN9440N3R0DgqH374IXV1dbjdbi6//PKB7o7GSSAIAtNmjWPZDYv40UM38+eXv4s+p5X2cD12SxZVLbsIRr09tmsJVpM9WkSv71IM3rDneaYuyqEt3EhKThCXw4wqmE2d7yCBmJdgrDVdukVNMTZnFiadGX/cSyjSjl4Ei87cZz9NkpEO33A4EcZoMhNNhdnW+ulRj621NZ0/Gw6HO2vHdtDe3s4DDzzA8uXLe4hBavRNR45sf/xp9A9ajuwJcLg64ZQpUwa6Oxoanaxdu5bFixfz4osvIkkSv/nNb3jkkUd4+OGHueSSS1i+fDm5ubn86le/4oMPPsDv9w90lzU0utEhmnPFFVfgdrsHtjMaGseg43q96aabNEPgC0JRST5/ee5+AJLJJB+8vZZf/vCv5JiGYzNloKoqobiXc64ayT0/+naP7f/wp3S+6lUL7sGq5hOXI+S4RxKN+YgkQ6hKCqcli/ZoM6FEEJtgJkkEm2QnIScwSL1H+SmqQkJNhwG7zFnISpLMsS50ut5f4Q8ePMjzzz/Ps88+S11dHbNmzWLhwoXMmzePWbNmYTabcbvdlJeXs3v37v44dWcNmmrx4EMzZE+AjgfXHXfcocW3awwqpk+fTiqVIhaL4Xa7+fGPf8yPf/xj3njjDX7zm99w7bXXYjabGT16NPPnz+ett94a6C5raHSSSCS02rEaZwyBQICXX34Z0KKzvqjo9XouXraIi5ctOuFt//XRb7l50U+RUylQUuh1Bvz+Jix6M2bJRFIBVUkh6FIYBD3BcACfKJAtZfbani8VIKYeShUSJKJKjNWrP+hz/9/4xjeQZZlvfvOb2O12fvCDH7BmzRpGjRrF8uXL+fa3u4zw8ePHn/DxaWgMJgY0tHjVqlVcfvnl5OfnIwhCZ1HxDh544AHGjBmD1WrF7XZz/vnns2HDhmO2+9JLLzFu3DiMRiPjxo3jlVdeOeW+7tu3jw0bNmjqhBqDkjlz5vDVr34Vt9uNoiikUikALr/8ctasWcPWrVsJh8Pcd999A9xTDY2evPXWW7S2tpKbm8uFF1440N3R0DgqL7zwArFYjLFjxzJjxoyB7o7GIEOn0/HDh28kkvCDADpBj6jTkVJS+KKtJBJhjIKONl8jwVg7fsVLXayJ3YFSdgX2EUvGOtuKylGaYq0k4+nX9bAcYUPLqj73XV5ezrp163j66ae56667uOmmm/jRj37Eeeedx/Tp0/nOd77D97//fWRZPu3n4YuI2I9/Gv3DgJ7LcDjM5MmT+dOf/tTr8lGjRvGnP/2JnTt3smbNGkpKSrjwwgtpaWnps81PP/2UG264gdtuu43t27dz2223cf311x+XAXw0DlcnzMnJOaW2NDROBx3hbaIodoYcdTysKirSohW33XbbwHROQ+ModNxfb7311j7D5TQ0Bgta7ViNYzFlxjju+eV1pOQEiiqjE/QoqoQ31IjZYMUbrMVts5JMxTDqDehFkZSaICknORipYo//ADXRevYHq1EUEZMpHXa8vnb1Uetrr127lvHjx2OxWDontBcsWEBpaSl/+9vfePHFF3nmmWc63wk0TgxNtXjwMaCG7NKlS/n5z3/O1Vdf3evym2++mfPPP59hw4Yxfvx4fv/73xMIBNixY0efbT788MNccMEF3HfffYwZM4b77ruPJUuW8PDDD590P2VZ7qwde+edd550OxoanzcdDzy/38/9998/wL3R0OhJS0sLb775JqCFaWoMfsrKyli7di2iKGoTgxpH5eLLFpE3wk4sFUYhRbP/AGadGW9rDSkpQmOsnrAURpGTJOQYiVQCFZmUmiSlJgnEwjgNVgCkQ5UGjmbEAsydO5fKykrefvvtzknBBx98kBEjRgAwY8YMcnNz2bJly2k8cg2Nz48zZuo7kUjwt7/9DafTyeTJk/tc79NPP+U73/lOt+8uuuiioxqy8Xi8m/x4IBAA0sn+yWSS9957r1Od8KKLLiKZTJ7awQwyOo7ni3ZcGl1cf/31QNc13fFvjS82Z8JYP/nkk6RSKaZNm8aoUaMGdV8HO2fCeJ/p/P3vfwfg/PPPJysra0DPtTbeg5+/Pv8g1537Tdq8Sdy2DBp9W3EaLBQbcxEEkZSaIqakiMSiZFjdxNUkoiqCKiIJEma9iaReZsTsUcCxx3rIkCFceeWVfPOb3+S3v/0tkiRx4MAB3n//fZLJJNnZ2QA0NzcPyHVzpl+r/aU4rKkW9x+D3pB98803ufHGG4lEIuTl5fHee++Rmdl7QjxAY2Njj9DfnJwcGhsb+9zmV7/6FQ8++GCP71euXInFYuF3v/sdkM5D/OCDvhPsz3Tee++9ge6CxueINt5nD4N5rP/85z8DacEyTYSsfxjM430moygK//d//wfAxIkTB831qo334ObO71/Sb20dz1jPmTMHgJqaGlRV5f/9v/9HRUUFZWVllJWVsX37djIzMwfk+o1EIp/7PjW+2Ax6Q3bx4sVs27aN1tZWHn300c58145Zpd44MvZcVdWjxqPfd9993HvvvZ2fA4EAhYWFXHjhhaiq2lnT8Mc//vEXUtihw+t8wQUXdKuLpvHFRBvvs4fBPtY7duzg4MGD6PV6fvrTn+LxeAa6S2c0g328z3Q++ugjWlpacDqd/OQnP8Fs7rv25+eBNt5nFjPzxmCXer9m4koSfzKCkgKn0UZClpFRsevsjBo1h7++/9sTGuubbrqpx7vv1q1beeKJJ7j99tu55ppr+u24ToSOiMczFUHon9I5Wops/zHoDVmr1cqIESMYMWIEc+bMYeTIkTz22GN9qq/m5ub28L42NzcfVaDJaDT2WgdOr9fz/PPPE4vFGDduHHPmzPlCJ2jr9XrtYXiGU19fT15e3nFdp9p4nz0M1rHuKLlz+eWXk5ubO8C9+eIwWMf7TOepp54C4IYbbsDhcAxwb7rQxnvw4/V6EWIyCSne63IBUBIpZFUlGA0iGESiiQR6i4MMp7tzfPsa6+rqal555RXWrl3LFVdc0Vld43BjdtasWfzwhz9k2LBhA3a9nOnXqUD/GKFfXEvi8+eMU4BWVbVbPuuRzJ07t0foxcqVK5k3b95J7a9DTVNTJ9QY7KiqynnnnceIESPYvn37QHdHQ+OoJJPJTsNAqx2rMdgJBoO89NJLgCZKpnHirF+/Hkk8ulATgFHU4SdISpaJKCnctnxmXD7pqNu0t7dzxx138Oc//5l4PM63vvWtzlqxR763zpkz56gRjRoaZxoD6pENhUKUlZV1fq6oqGDbtm1kZGTg8Xj4xS9+wbJly8jLy8Pr9fLII49QW1vLdddd17nN8uXLKSgo4Fe/+hUA3/72t1m4cCG/+c1vuOKKK3jttdd4//33WbNmzQn3r7y8vFOd8NZbbz31A9bQOI1s2LCB0tJSLBYLw4YNG+juaGgclXfeeYfm5maysrJYunTpQHdHQ+OovPjii0QiEUaNGtWZg6ihcby89PyLROQ4dl3vocVJJUVMjuPWOxEUHUlVIc9SBEaFW752fWcpnd745S9/iU6n4/333yc/P5/nnnuO//iP/+Dqq6/m3HPP7fTKRiIRLBbL6TrEswIRAbEf/Kn90YZGmgH1yG7atImpU6cydepUAO69916mTp3KT37yEyRJYt++fVxzzTWMGjWKyy67jJaWFlavXs348eM726iurqahoaHz87x583juued4/PHHmTRpEk888QTPP/88s2fPPuH+PfvsswBceOGF5Ofnn+LRamicXjqiB6655hrsdvsA90ZD4+h0XK+33HLLGR9upvHFR4vO0jgV5p0zD2/cj6wovS4Py3FiyQThVAQJWDhkKYIEf3z518e83l599VXuvvtuioqK0Ol03HrrrVx00UU89thjQNoru3LlSs4555z+PqyzDlEQ+u1Po38YUI/sokWLUFW1z+Uvv/zyMdv4+OOPe3x37bXXcu21155K14AuQ1YLI9IY7MRisc7rVQvT1BjstLW18cYbbwDa/VVj8HPw4EE++eQTBEHQasdqnBRf+sqX+dHd/0FDrJ1MowOTlJ68SyopwnIMbzRAjjkTbzTIlcNupTXeTDIpM3HaxKO2u3v3blwuV2fOdof39a677uKmm26ioqKCoUOH8tBDDzFhwoTTfpwaGp83g17saSCpra3F6XSybNmyge6KhsZRee211/D7/RQWFrJ48eKB7o6GxlF59tlnSSQSTJky5ah1wTU0BgNPPvkkAEuWLKGwsHCAe6NxJiKKIk6bk2AoQE2qEZ2oQ0EgoSTI1mWQaXYTiMa4ctityKqMN97KrEtmHrPd/Px8Lrvssh7fz5s3jyFDhvD3v/+de++9l5UrV1JVVXU6Du2sQqsjO/jQDNljcOONNw64xL6GxrHoCHtbvnw5onjGabhpnGUcHqapoTGYURSl83rVogc0ToX9wWqGmoYgxiUUVUVSVeLEaU55mWKazbhhU4mkItRHa2kKt/DRS+8fs0232813v/tdbDYb0OWRFQSBW2+9leeee47GxkamT5/OkCFDTvchamh87miG7DHQXrQ0Bjv19fW8++67gHa9agx+9uzZw8aNG9HpdJ0lIjQ0BiurV6+moqICu93OVVddNdDd0TjDqYjVUltdyw3nXUXAF2TOxJFUbm7CbHFQFtxPc7QFnUvHnubjrzzQYcRC2vOrKAqqqvLlL3+Zhx9+mDVr1vDhhx+ejsM56+iYJOiPdjT6B82QPQrDhw/X1Ak1Bj1PPfUUiqIwb948Ro4cOdDd0dA4Kk888QQAl156KVlZWQPbGQ2NY9Dhjb3++us1xVeNfmFI0RDWlm085Xb27dvHX/7yFwwGAzabjQkTJnDxxRdjtVoBkCSJW265hXfffZdFixad8v406DehJk3sqf/QDNle6BCguuaaawgGgwPcm9NPMpkkEokQCAQ09dAzEIfDwahRo7jhhhsIBALHXF8b77OHwTjWWVlZlJSUcN111x3X9apx/AzG8T7TGTJkCPn5+Vx77bWD7nrVxvvs4cix/uc//8kjjzyCKIqYTCYsFguvvvoqf/nLX1i2bBlXXXUVTqeTr33ta9x8882D5trt6MfRhF4HM/1lE5wNtsXnhaCeqVfTaaS2tlYTdNDQ0NDQ0NDQ0NDoZ2pqas6onN1YLMbQoUNpbGzstzZzc3OpqKjAZDL1W5tnI5oh2wuKolBfX4/dbj8r4tgDgQCFhYXU1NR0SrhrfHHRxvvsQRvrswttvM8utPE+e/iijLWqqgSDQfLz8884YcpYLEYikei39gwGg2bE9gNaaHEviKJ4Rs0U9RcOh+OMvkFqnBjaeJ89aGN9dqGN99mFNt5nD1+EsXY6nQPdhZPCZDJphucg5MyaDtHQ0NDQ0NDQ0NDQ0NA469EMWQ0NDQ0NDQ0NDQ0NDY0zCs2Q1cBoNHL//fdjNBoHuisanwPaeJ89aGN9dqGN99mFNt5nD9pYa2j0jib2pKGhoaGhoaGhoaGhoXFGoXlkNTQ0NDQ0NDQ0NDQ0NM4oNENWQ0NDQ0NDQ0NDQ0ND44xCM2Q1NDQ0NDQ0NDQ0NDQ0zig0Q/YLxl/+8hcmTZrUWWts7ty5vP32293W2bt3L8uWLcPpdGK325kz5/+3d/8xUdd/HMCfHzjuOLpJDCFgFrQhPwOMjqXGxkQTRZsmidEgiaj1B1AuW2a6YVbizLLYYGRAJjANCXCzTEYSxK+gOGyOATMc5a7M0lKnSPD6/uG4b4f81Du9k+djY/M+P16f9/tee01ee7+Pm4/+/v4J41ZUVCAkJAQajQYhISGorKy05jRoCqyR608//RSKotzwc/XqVWtPhyYxWb7HypuiKNi1a9eEcVnbtska+WZ926bJcn3p0iVkZGRgzpw50Gq1CA4ORn5+/qRxWdu2yRr5Zm3TTMVG9i4zZ84c5OTkoL29He3t7YiNjcWqVatw8uRJAMCpU6cQHR2NoKAg1NXVobOzE1u3bp3wS56bm5uxbt06pKSkoLOzEykpKUhMTERra+vtmhaNwRq5Bq5/4brRaDT74ZeA33mT5Xt0zoqKiqAoChISEsaNydq2XdbIN8D6tkWT5XrDhg04evQoSkpK0NXVhQ0bNiAzMxPV1dXjxmRt2y5r5BtgbdMMJXTXc3Nzk08++URERNatWyfJycnTuj8xMVGWLVtmdiwuLk6efvppi42RLONWc11cXCyurq5WGBlZw3/zPdqqVaskNjZ2wvtZ2/blVvPN+rYf/811aGiovPXWW2bnIyMjZcuWLePez9q2L7eab9Y2zVRckb2LDQ0N4cCBA7h8+TIWLFiA4eFhHDlyBAEBAYiLi4OnpyceffRRVFVVTRinubkZS5cuNTsWFxeHpqYmK46epsNSuQaub2vy9fXFnDlzsHLlSnR0dFh/AjQto/M92u+//44jR47g+eefnzAOa9s+WCrfAOvb1o2V6+joaBw+fBhnzpyBiOD48ePo6elBXFzcuHFY2/bBUvkGWNs0Q93pTpos78SJE3LPPfeIo6OjuLq6ypEjR0RExGg0CgBxcXGR999/Xzo6OmTHjh2iKIrU1dWNG8/JyUlKS0vNjpWWloparbbqPGhyls51c3Oz7N+/XwwGg9TX10tCQoJotVrp6em5XVOiCYyX79F27twpbm5ucuXKlQnjsbZtm6Xzzfq2XRPlemBgQJ599lkBICqVStRqtXz22WcTxmNt2zZL55u1TTMVG9m70MDAgPT29kpbW5ts2rRJZs+eLSdPnpQzZ84IAElKSjK7/oknnphwu5GTk5OUlZWZHSspKRGNRmOV8dPUWTrXow0NDUlERIRkZmZaeuh0E8bL92iBgYGSkZExaTzWtm2zdL5HY33bjolyvWvXLgkICJDDhw9LZ2en5Obmik6nk5qamnHjsbZtm6XzPRprm2YK1Z1cDSbrUKvV8Pf3BwDo9Xq0tbXhww8/RG5uLlQqFUJCQsyuDw4OxnfffTduPC8vL/z2229mx86ePYv77rvP8oOnabF0rkdzcHBAVFQUent7LTpuujnj5bugoMB0TUNDA7q7u3Hw4MFJ47G2bZul8z0a69t2jJfrPXv2YPPmzaisrMSKFSsAAOHh4TAYDHjvvfewZMmSMeOxtm2bpfM9GmubZgp+RnYGEBEMDAxArVYjKioK3d3dZud7enrg6+s77v0LFixATU2N2bFjx45h4cKFVhkv3bxbzfVY8QwGA7y9vS09VLKAkXz/V2FhIR555BFERERMej9r277car7Hisf6tk0juR4cHMTg4CAcHMx/XXN0dMTw8PC497O27cut5nuseKxtmhHu2FowWcUbb7wh9fX10tfXJydOnJDNmzeLg4ODHDt2TEREvvjiC3FycpKPP/5Yent7JTc3VxwdHaWhocEUIyUlRTZt2mR63djYKI6OjpKTkyNdXV2Sk5MjKpVKWlpabvv86P+skevs7Gw5evSonDp1Sjo6OuS5554TlUolra2tt31+ZG6yfIuI/P333+Li4iL5+fljxmBt2w9r5Jv1bZsmy3VMTIyEhobK8ePH5eeff5bi4mJxdnaWvLw8UwzWtv2wRr5Z2zRTsZG9y6SlpYmvr6+o1Wrx8PCQxYsXm/3iIyJSWFgo/v7+4uzsLBEREVJVVWV2PiYmRtavX292rLy8XAIDA8XJyUmCgoKkoqLC2lOhSVgj16+88oo88MADpphLly6Vpqam2zEdmsRU8l1QUCBarVYuXLgwZgzWtv2wRr5Z37ZpslwbjUZJTU0VHx8fcXZ2lsDAQNm9e7cMDw+brmFt2w9r5Ju1TTOVIiJyp1eFiYiIiIiIiKaKn5ElIiIiIiIiu8JGloiIiIiIiOwKG1kiIiIiIiKyK2xkiYiIiIiIyK6wkSUiIiIiIiK7wkaWiIiIiIiI7AobWSIiIiIiIrIrbGSJiIiIiIjIrrCRJSIii1IUBVVVVQCA06dPQ1EUGAyGKd+fnZ2NefPmWXxc2dnZUBQFiqJgz549Fo8/npH3QFEUq8yLiIhoJmIjS0REVnP//ffDaDTioYcemvI9GzduRG1trel1amoqVq9ebZHxhIaGwmg04sUXX7RIvKkYeQ9effXV2/ZMIiKiu53qTg+AiIjuXo6OjvDy8prWPTqdDjqdzirjUalU0x7PrRp5D6w1JyIiopmIK7JERGTm0KFDCAsLg1arhbu7O5YsWYLLly8DANra2vD4449j9uzZcHV1RUxMDH788cdxY43eWlxXVwdFUVBbWwu9Xg8XFxcsXLgQ3d3dpnv+u7U4Ozsb+/btQ3V1tWl7bl1dHWJjY5GRkWH2rD///BMajQbffPPNtOarKAry8/OxfPlyaLVaPPjggygvLzedv3btGjIyMuDt7Q1nZ2f4+flhx44dY84PAC5cuGAaJxEREVkHG1kiIjIxGo1ISkpCWloaurq6UFdXhzVr1kBEAAAXL17E+vXr0dDQgJaWFsydOxfx8fG4ePHitJ7z5ptvYvfu3Whvb4dKpUJaWtqY123cuBGJiYlYtmwZjEYjjEYjFi5ciPT0dJSVlWFgYMB0bWlpKXx8fLBo0aJpz3vr1q1ISEhAZ2cnkpOTkZSUhK6uLgDARx99hMOHD+Pzzz9Hd3c3SkpK4OfnN+1nEBERkeVwazEREZkYjUb8+++/WLNmDXx9fQEAYWFhpvOxsbFm1xcUFMDNzQ3ffvstVq5cOeXnvPPOO4iJiQEAbNq0CStWrMDVq1fh7Oxsdp1Op4NWq8XAwIDZluCEhARkZmaiuroaiYmJAIDi4mKkpqZCUZTpTRrA2rVrkZ6eDgDYvn07ampqkJubi7y8PPT392Pu3LmIjo6Goiim94WIiIjuHK7IEhGRSUREBBYvXoywsDCsXbsWe/fuxfnz503nz549i5deegkBAQFwdXWFq6srLl26hP7+/mk9Jzw83PRvb29vU+yp0mg0SE5ORlFREQDAYDCgs7MTqamp0xrHiAULFtzwemRFNjU1FQaDAYGBgcjKysKxY8du6hlERERkOWxkiYjIxNHRETU1Nfjqq68QEhKC3NxcBAYGoq+vD8D1pu6HH37Anj170NTUBIPBAHd3d1y7dm1az3FycjL9e2QFdXh4eFox0tPTUVNTg19//RVFRUVYvHixRVdLR8YVGRmJvr4+bN++HVeuXEFiYiKeeuopAICDw/X/Rke2XgPA4OCgxcZAREREY2MjS0REZhRFwWOPPYZt27aho6MDarUalZWVAICGhgZkZWUhPj4eoaGh0Gg0OHfunFXHo1arMTQ0dMPxsLAw6PV67N27F2VlZeN+znYqWlpabngdFBRkej1r1iysW7cOe/fuxcGDB1FRUYG//voLHh4eAK5vyR4xne/MJSIiopvDz8gSEZFJa2sramtrsXTpUnh6eqK1tRV//PEHgoODAQD+/v7Yv38/9Ho9/vnnH7z22mvQarVWHZOfnx++/vprdHd3w93dHa6urqYV3fT0dGRkZMDFxQVPPvnkTT+jvLwcer0e0dHRKC0txffff4/CwkIAwAcffABvb2/MmzcPDg4OKC8vh5eXF+699144ODhg/vz5yMnJgZ+fH86dO4ctW7ZYZN5EREQ0Pq7IEhGRyaxZs1BfX4/4+HgEBARgy5Yt2L17N5YvXw4AKCoqwvnz5/Hwww8jJSUFWVlZ8PT0tOqYXnjhBQQGBkKv18PDwwONjY2mc0lJSVCpVHjmmWdu+ENR07Ft2zYcOHAA4eHh2LdvH0pLSxESEgLg+h+c2rlzJ/R6PaKionD69Gl8+eWXpm3FRUVFGBwchF6vx8svv4y333771iZMREREk1Lkvx/sISIisiO//PIL/Pz80NbWhsjIyAmvzc7ORlVV1Q1bfxVFQWVlJVavXm29gU7wfCIiIpo+rsgSEZHdGRwcRH9/P15//XXMnz9/0iZ2xE8//QSdToe8vDwrj/D/+vv7odPp8O677962ZxIREd3t+BlZIiKyO42NjVi0aBECAgJw6NChKd2TlZWF5ORkADD9kabbwcfHx7QKq9FobttziYiI7mbcWkxERERERER2hVuLiYiIiIiIyK6wkSUiIiIiIiK7wkaWiIiIiIiI7AobWSIiIiIiIrIrbGSJiIiIiIjIrrCRJSIiIiIiIrvCRpaIiIiIiIjsChtZIiIiIiIisitsZImIiIiIiMiu/A9jakDjg2PQPAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER (extra)\n", - "# here both sections are plot together for convenience, but the above two plots are sufficient\n", - "lat,p,temp,salt = crosssection([*data_west,*data_east])\n", - "\n", - "# calculating linearized density RHO\n", - "f = 0.005 # add margin around measurements\n", - "T = np.linspace(np.nanmin(temp)*(1-f), np.nanmax(temp)*(1+f), len(p))\n", - "S = np.linspace(np.nanmin(salt)*(1-f), np.nanmax(salt)*(1+f), len(p))\n", - "RHO = rho0 * (1- alpha * (T-T[0])[:,None] + beta * (S-S[0])[None,:])\n", - "\n", - "# plotting\n", - "fig, ax = plt.subplots(1, 1, figsize=(10, 5))\n", - "CS = ax.contour(S, T, RHO, colors='k', levels=np.arange(1025,1030,0.5))\n", - "ax.clabel(CS, inline=1, fontsize=10, fmt='%.1f')\n", - "ax.set_xlabel('salinity [psu]')\n", - "ax.set_ylabel('temperature [°C]')\n", - "ax.grid()\n", - "\n", - "#------------ ANSWER ----------\n", - "CT = gsw.CT_from_t(salt, temp, p[:,None])\n", - "rho = gsw.rho(salt, CT, p[:,None])\n", - "ps = ax.scatter(salt, temp, c=rho, cmap=cmocean.cm.dense, edgecolors='k', linewidths=.1)\n", - "fig.colorbar(ps, label=r'$\\rho$ [kg m$^{-3}$]')\n", - "ax.set_title('Eastern and Western data together')\n", - "#------------ ANSWER ----------\n", - "plt.tight_layout()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Answer: The profiles of the Eastern and Western section overlap near the lowest densities (top) and highest densities (bottom-right), indicating these water masses are the same. This is to be expected for the warm water flowing into the Mediterranean and the cold, salty water flowing to the Atlantic. The layers in between have different properties, meaning these water masses are not connected well. This seems to make sense as there has to be a region with no net transport between the layers of inflow and outflow. In this region, water of the same density is generally warmer and saltier in the Mediterranean than the Atlantic. " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A04_Q1.ipynb b/teaching_material/Assignment/Preparatory_exercises/A04_Q1.ipynb deleted file mode 100644 index fd7a545f..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A04_Q1.ipynb +++ /dev/null @@ -1,114 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment 4.1 Analysing stratification\n", - "\n", - "***Note that it is always important in (Climate) Physics to properly label axes (including units) and add titles and legend where relevant to your plots!***\n", - "In this tutorial, we will be using the [NCEP Global Ocean Data Assimilation System (GODAS) datasets](https://psl.noaa.gov/data/gridded/data.godas.html) to analyze the properties of stratified waters ourselves. GODAS is a global analysis and reanalysis ocean dataset covering the period from 1980 till now (updated monthly). \n", - "\n", - "Download the year 2020 monthly mean ['potential temperature'](https://psl.noaa.gov/cgi-bin/db_search/DBListFiles.pl?did=98&tid=83478&vid=1913) and ['salinity'](https://psl.noaa.gov/cgi-bin/db_search/DBListFiles.pl?did=98&tid=83478&vid=1914) from the GODAS website at https://psl.noaa.gov/data/gridded/data.godas.html (click the 'Number of files' icon to expand, search the 2020 file and hit the download button). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import gsw\n", - "import numpy as np\n", - "import xarray as xr\n", - "import cmocean\n", - "import matplotlib.pyplot as plt\n", - "import cartopy.crs as ccrs\n", - "import cartopy.feature as cfeature" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now open the the temperature and salinity files for 2020 (where of course `datadir` should point to the directory where you saved the GODAS data)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "datadir ='./' # ./ is current working directory\n", - "T = xr.open_dataset(datadir+'pottmp.2020.nc')\n", - "S = xr.open_dataset(datadir+'salt.2020.nc')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment\n", - "\n", - "**a)** Create figure by writing code that plots four panels showing potential temperature, salinity, potential density ($\\sigma_0$), and buoyancy frequency (or period) along a latitudinal section at the 30W and along a longitudinal section on the equator. What structures do you see?\n", - "\n", - "Some hints:\n", - "- You can either write your own function for buoyancy period, or use `gsw.stability.NSquared`. \n", - "- To create an array of pressure with the same size as salinity and temperature, use\n", - "```\n", - "p = gsw.p_from_z(-T.level, 0)\n", - "p_arr = p.expand_dims(dim={'time':T.time, 'lat':T.lat, 'lon':T.lon}, axis=[0,2,3])\n", - "```\n", - "- To account for the fact that $N^2$ are defined at the pressure midpoints, use \n", - "```\n", - "level = (T.level+T.level.shift(level=1)).dropna('level')/2\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**b)** Investigate the Mixed Layer Depth. A common way (e.g. in the Climatological Atlas of the World Ocean by Levitus, 1982) to define this thickness is as the depth at which the potential density becomes larger than the surface density plus 0.125 kg/m^3.\n", - "\n", - "Plot a global map of the mixed layer depth for the 2020 annual average, for January 2020, and for July 2020. What differences do you see?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A04_Q1_withanswers.ipynb b/teaching_material/Assignment/Preparatory_exercises/A04_Q1_withanswers.ipynb deleted file mode 100644 index 9eecc49e..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A04_Q1_withanswers.ipynb +++ /dev/null @@ -1,236 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment 4.1 Analysing stratification\n", - "\n", - "In this tutorial, we will be using the [NCEP Global Ocean Data Assimilation System (GODAS) datasets](https://psl.noaa.gov/data/gridded/data.godas.html) to analyze the properties of stratified waters ourselves. GODAS is a global analysis and reanalysis ocean dataset covering the period from 1980 till now (updated monthly). \n", - "\n", - "Download the year 2020 monthly mean ['potential temperature'](https://psl.noaa.gov/cgi-bin/db_search/DBListFiles.pl?did=98&tid=83478&vid=1913) and ['salinity'](https://psl.noaa.gov/cgi-bin/db_search/DBListFiles.pl?did=98&tid=83478&vid=1914) from the GODAS website at https://psl.noaa.gov/data/gridded/data.godas.html (click the 'Number of files' icon to expand, search the 2020 file and hit the download button). " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import gsw\n", - "import numpy as np\n", - "import xarray as xr\n", - "import cmocean\n", - "import matplotlib.pyplot as plt\n", - "import cartopy.crs as ccrs\n", - "import cartopy.feature as cfeature" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now open the the temperature and salinity files for 2020 (where of course `datadir` should point to the directory where you saved the GODAS data)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "datadir = '/Users/erik/Downloads/'\n", - "\n", - "T = xr.open_dataset(f\"{datadir}pottmp.2020.nc\")\n", - "S = xr.open_dataset(f\"{datadir}salt.2020.nc\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment\n", - "\n", - "**a)** Create a figure by writing code that plots four panels showing potential temperature, salinity, potential density ($\\sigma_0$), and buoyancy frequency (or period) along a latitudinal section at the 30W and along a longitudinal section on the equator. What structures do you see?\n", - "\n", - "Some hints:\n", - "- You can either write your own function for buoyancy period, or use `gsw.stability.NSquared`. \n", - "- To create an array of pressure with the same size as salinity and temperature, use\n", - "```python\n", - "p = gsw.p_from_z(-T.level, 0)\n", - "p_arr = p.expand_dims(dim={'time':T.time, 'lat':T.lat, 'lon':T.lon}, axis=[0,2,3])\n", - "```\n", - "- To account for the fact that $N^2$ is defined at the pressure midpoints, use \n", - "```python\n", - "level = (T.level+T.level.shift(level=1)).dropna('level')/2\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# ANSWER\n", - "CT = gsw.conversions.CT_from_pt(1000*S.salt, T.pottmp-273.15)\n", - "sigma0 = gsw.density.sigma0(1000*S.salt, CT)\n", - "p = gsw.p_from_z(-T.level, 0)\n", - "p_arr = p.expand_dims(dim={'time':T.time, 'lat':T.lat, 'lon':T.lon}, axis=[0,2,3])\n", - "n2, _ = gsw.stability.Nsquared(1000*S.salt, CT, p_arr, axis=1)\n", - "level = (T.level+T.level.shift(level=1)).dropna('level')/2\n", - "N2 = xr.DataArray(data=n2,\n", - " dims=('time','level','lat','lon'),\n", - " coords={'time':T.time,'level':level,'lat':T.lat,'lon':T.lon})" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "def section(da, which={'lon':330}):\n", - " \"\"\" returns time mean\"\"\"\n", - " return da.sel(**which, method='nearest').mean('time')\n", - "\n", - "def plot_section(which, title=None):\n", - " f, ax = plt.subplots(2,2, figsize=(15,10), sharey=True)\n", - " if title is not None: f.suptitle(title)\n", - " cbkw = dict(orientation='horizontal', pad=0.1)\n", - " if 'lat' in which: x = T.lon\n", - " elif 'lon' in which: x = T.lat\n", - "\n", - " # temperature\n", - " im = ax[0,0].pcolormesh(x, T.level, section(T.pottmp, which)-273.15, cmap='Spectral_r')\n", - " plt.colorbar(im, ax=ax[0,0], label='potential temperature [°C]', **cbkw)\n", - " ax[0,0].invert_yaxis()\n", - "\n", - " # salinity\n", - " im = ax[0,1].pcolormesh(x, S.level, 1000*section(S.salt, which))\n", - " plt.colorbar(im, ax=ax[0,1], label=r'salinity [g kg$^{-1}$]', **cbkw)\n", - "\n", - " # density\n", - " im = ax[1,0].pcolormesh(x, sigma0.level, section(sigma0, which), cmap='inferno')\n", - " plt.colorbar(im, ax=ax[1,0], label=r'potential density [kg m$^{-3}$]', **cbkw)\n", - "\n", - " # stratification\n", - " im = ax[1,1].pcolormesh(x, N2.level, section(1/np.sqrt(N2.clip(min=0)), which)/3600, cmap='magma', vmax=1)\n", - " plt.colorbar(im, ax=ax[1,1], label=r'buoyancy period N$^{-1/2}$ [h]', **cbkw)\n", - "\n", - "plot_section({'lon':330}, title='Atlantic section along 30W')\n", - "plot_section({'lat':0}, title='Equatorial section')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**b)** Investigate the Mixed Layer Depth. A common way (e.g. in the Climatological Atlas of the World Ocean by Levitus, 1982) to define this Mixed Layer Depth is as the depth at which the potential density becomes larger than the surface density plus 0.125 kg/m^3.\n", - "\n", - "Plot a global map of the mixed layer depth for the 2020 annual average, for January 2020, and for July 2020. What differences do you see?" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# ANSWER\n", - "def mixed_layer(PD):\n", - " return PD.level.where(PD-PD.isel(level=0)>0.0125,np.nan).min('level')\n", - "\n", - "\n", - "MXL_Ann = mixed_layer(sigma0.mean('time'))\n", - "MXL_Jan = mixed_layer(sigma0.isel(time=0))\n", - "MXL_Jul = mixed_layer(sigma0.isel(time=6))" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# ANSWER\n", - "fig = plt.figure(figsize=(20, 10), constrained_layout=True)\n", - "kw = dict(transform=ccrs.PlateCarree(), cmap='cmo.deep', vmin=0, vmax=200)\n", - "proj = ccrs.Robinson(central_longitude=220)\n", - "\n", - "def map_details(ax, title=None):\n", - " ax.coastlines(resolution='50m', lw=.5)\n", - " ax.add_feature(cfeature.LAND, color='grey', zorder=2)\n", - " ax.set_global()\n", - " if title is not None: ax.set_title(title)\n", - " return\n", - "\n", - "ax = fig.add_subplot(3, 1, 1, projection=proj)\n", - "MXL_Ann.plot(ax=ax, **kw)\n", - "map_details(ax, title='Annual MXL')\n", - "\n", - "ax = fig.add_subplot(3, 1, 2, projection=proj)\n", - "MXL_Jan.plot(ax=ax, **kw)\n", - "map_details(ax, title='January MXL')\n", - "\n", - "ax = fig.add_subplot(3, 1, 3, projection=proj)\n", - "MXL_Jul.plot(ax=ax, **kw)\n", - "map_details(ax, title='July MXL')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A05_Q1.ipynb b/teaching_material/Assignment/Preparatory_exercises/A05_Q1.ipynb deleted file mode 100644 index 17703a4a..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A05_Q1.ipynb +++ /dev/null @@ -1,219 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment 5.1: thermal wind balance\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this assignment you will analyze CTD measurements near Japan and calculate the vertical shear assuming thermal wind balance. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import xarray as xr\n", - "import pandas as pd\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import gsw\n", - "import cmocean" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First we will have to read the _csv_ files. Take a look at the comments and header of the first CTD dataset by running the following cell." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "header = pd.read_csv('Japan/CTD_Japan_station_1.csv', nrows=5, header=None)\n", - "header" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To load the data in _xarray's_ useful format, we first create a new dataset with empty data. The dimensions _trajectory_ and _obs_ represent the length of each measurement and the number of measurements, respectively." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ctd = xr.Dataset(\n", - " data_vars={\n", - " 'P':(('trajectory','obs'),np.zeros((399,5)),{'long_name':'pressure','units':'hPa'}),\n", - " 'T':(('trajectory','obs'),np.zeros((399,5)),{'long_name':'temperature','units':'degC'}),\n", - " 'S':(('trajectory','obs'),np.zeros((399,5)),{'long_name':'salinity','units':'g kg-1'}),\n", - " },\n", - " coords={\n", - " 'trajectory':('trajectory',range(399)),\n", - " 'obs':('obs',range(1,6)),\n", - " 'lat':('obs',np.zeros((5)),{'long_name':'latitude','units':'degrees_north'}),\n", - " 'lon':('obs',np.zeros((5)),{'long_name':'longitude','units':'degrees_east'}),\n", - " 'start_time':('obs',np.zeros((5), dtype='\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
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0longitude154.0{'axis': 'X', 'long_name': '', 'standard_name'...
1latitude38.099998474121094{'axis': 'Y', 'long_name': '', 'standard_name'...
2start time2022-10-18T00:00:00.000000000NaN
3end time2022-10-18T01:06:20.000000000NaN
4pressure [hPa]temperature [degC]salinity [g kg-1]
\n", - "" - ], - "text/plain": [ - " 0 1 \\\n", - "0 longitude 154.0 \n", - "1 latitude 38.099998474121094 \n", - "2 start time 2022-10-18T00:00:00.000000000 \n", - "3 end time 2022-10-18T01:06:20.000000000 \n", - "4 pressure [hPa] temperature [degC] \n", - "\n", - " 2 \n", - "0 {'axis': 'X', 'long_name': '', 'standard_name'... \n", - "1 {'axis': 'Y', 'long_name': '', 'standard_name'... \n", - "2 NaN \n", - "3 NaN \n", - "4 salinity [g kg-1] " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "header = pd.read_csv('Japan/CTD_Japan_station_1.csv', nrows=5, header=None)\n", - "header" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To load the data in _xarray's_ useful format, we first create a new dataset with empty data. The dimensions _trajectory_ and _obs_ represent the length of each measurement and the number of measurements, respectively." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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-       "Dimensions:     (trajectory: 399, obs: 5)\n",
-       "Coordinates:\n",
-       "  * trajectory  (trajectory) int64 0 1 2 3 4 5 6 ... 392 393 394 395 396 397 398\n",
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-       "Data variables:\n",
-       "    P           (trajectory, obs) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
-       "    T           (trajectory, obs) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
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" - ], - "text/plain": [ - "\n", - "Dimensions: (trajectory: 399, obs: 5)\n", - "Coordinates:\n", - " * trajectory (trajectory) int64 0 1 2 3 4 5 6 ... 392 393 394 395 396 397 398\n", - " * obs (obs) int64 1 2 3 4 5\n", - " lat (obs) float64 0.0 0.0 0.0 0.0 0.0\n", - " lon (obs) float64 0.0 0.0 0.0 0.0 0.0\n", - " start_time (obs) datetime64[ns] 1970-01-01 1970-01-01 ... 1970-01-01\n", - " end_time (obs) datetime64[ns] 1970-01-01 1970-01-01 ... 1970-01-01\n", - "Data variables:\n", - " P (trajectory, obs) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n", - " T (trajectory, obs) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n", - " S (trajectory, obs) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ctd = xr.Dataset(\n", - " data_vars={\n", - " 'P':(('trajectory','obs'),np.zeros((399,5)),{'long_name':'pressure','units':'hPa'}),\n", - " 'T':(('trajectory','obs'),np.zeros((399,5)),{'long_name':'temperature','units':'degC'}),\n", - " 'S':(('trajectory','obs'),np.zeros((399,5)),{'long_name':'salinity','units':'g kg-1'}),\n", - " },\n", - " coords={\n", - " 'trajectory':('trajectory',range(399)),\n", - " 'obs':('obs',range(1,6)),\n", - " 'lat':('obs',np.zeros((5)),{'long_name':'latitude','units':'degrees_north'}),\n", - " 'lon':('obs',np.zeros((5)),{'long_name':'longitude','units':'degrees_east'}),\n", - " 'start_time':('obs',np.zeros((5), dtype=']" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Answer\n", - "g = 9.81\n", - "CT = gsw.CT_from_t(ctd.S, ctd.T, ctd.P)\n", - "Rho = gsw.density.rho(ctd.S, CT, ctd.P)\n", - "Pa = 100000 * ctd.P # bar to Pa\n", - "Pa0 = Pa.isel(trajectory=0)\n", - "Rho0 = Rho.isel(trajectory=0)\n", - "ctd['Rho'] = Rho.assign_attrs({\n", - " 'long_name':'density','standard_name':'density','units':'kg m-3'})\n", - "\n", - "# calculate z (xarray style)\n", - "Rhoc = Rho.rolling(trajectory=2).mean().dropna('trajectory') # rho grid center\n", - "dz = (-1/(g*Rhoc)) * Pa.diff('trajectory')\n", - "z = xr.concat((\n", - " xr.zeros_like(Pa0),\n", - " dz.cumulative('trajectory').sum()\n", - "), 'trajectory') - Pa0/(Rho0*g)\n", - "ctd['z'] = xr.DataArray(z.data, z.coords, z.dims, attrs={\n", - " 'long_name':'depth','units':'m'}).transpose(*ctd.dims)\n", - "\n", - "# # alternatively (numpy style, perhaps more intuitive)\n", - "# ctd['z'] = xr.zeros_like(ctd.Rho).assign_attrs({\n", - "# 'long_name':'depth','standard_name':'depth','units':'m'})\n", - "# for ob in range(5): # loop through obs\n", - "# rho = ctd.Rho[:,ob]\n", - "# rhoc = np.mean((rho[1:], rho[:-1]),axis=0)\n", - "# dz = -1/(g*rhoc)*np.diff(Pa[:,ob])\n", - "# ctd.z[0,ob] = -Pa[0,ob]/(rho[0]*g)\n", - "# for tj in range(len(ctd.z)-1): # loop through trajectory\n", - "# ctd.z[tj+1,ob] = ctd.z[tj,ob] + dz[tj]\n", - "\n", - "# plot depth\n", - "ctd.z.isel(obs=0).plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As you can see, the CTD sinks and rises with a constant velocity. \n", - "\n", - "__c)__ Select the data during ascent **and** interpolate to depth levels every five metres. For the latter you can use `xr.apply_ufunc`, offering a way to apply functions on a dataset that may modify one or more specific dimensions, like e.g. `np.interp`. You only have to fill in your code in the `interp_1d` function, that is being applied along the `trajectory` dimension. This function interpolates a one-dimensional array `fp`, from its (core) dimension `trajectory` to the new dimension `zlev`. If you want to learn more about `xr.apply_ufunc`, check out this [example](https://docs.xarray.dev/en/stable/examples/apply_ufunc_vectorize_1d.html), which is very related to this exercise." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "index (trajectory) of minimum depth: [200 200 200 200 200] (obs: 5)\n" - ] - } - ], - "source": [ - "# Answer\n", - "print(\"index (trajectory) of minimum depth:\",ctd.z.argmin('trajectory').data,'(obs: 5)')\n", - "trup = dict(trajectory=slice(200,None))\n", - "ctd_up = ctd.isel(trup) # select ascending portion" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# Answer\n", - "def interp_1d(fp, xp, x):\n", - " \"\"\"interpolate fp(xp) to x\n", - "\n", - " args:\n", - " fp : array(k)\n", - " variable to interpolate\n", - " xp : array(k)\n", - " coordinates of fp\n", - " x : array(k)\n", - " new coordinates of interpolated variable\n", - "\n", - " returns:\n", - " array(k)\n", - " values of fp interpolated to x\n", - " \"\"\"\n", - " return np.interp(x, xp, fp)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset>\n",
-       "Dimensions:     (obs: 5, zlev: 200)\n",
-       "Coordinates:\n",
-       "  * obs         (obs) int64 1 2 3 4 5\n",
-       "    lat         (obs) float64 38.1 38.1 38.1 38.1 38.1\n",
-       "    lon         (obs) float64 154.0 154.0 154.0 154.0 154.0\n",
-       "    start_time  (obs) datetime64[ns] 2022-10-18 ... 2022-10-18T04:46:00\n",
-       "    end_time    (obs) datetime64[ns] 2022-10-18T01:06:20 ... 2022-10-18T05:52:20\n",
-       "    z           (zlev) int64 -5 -15 -25 -35 -45 ... -1965 -1975 -1985 -1995\n",
-       "Dimensions without coordinates: zlev\n",
-       "Data variables:\n",
-       "    P           (obs, zlev) float64 2.2 2.2 2.505 3.508 ... 199.0 200.1 200.2\n",
-       "    T           (obs, zlev) float64 25.02 25.02 24.9 24.17 ... 1.821 1.814 1.813\n",
-       "    S           (obs, zlev) float64 33.82 33.82 33.84 33.97 ... 34.6 34.6 34.6\n",
-       "    Rho         (obs, zlev) float64 1.022e+03 1.022e+03 ... 1.028e+03 1.028e+03
" - ], - "text/plain": [ - "\n", - "Dimensions: (obs: 5, zlev: 200)\n", - "Coordinates:\n", - " * obs (obs) int64 1 2 3 4 5\n", - " lat (obs) float64 38.1 38.1 38.1 38.1 38.1\n", - " lon (obs) float64 154.0 154.0 154.0 154.0 154.0\n", - " start_time (obs) datetime64[ns] 2022-10-18 ... 2022-10-18T04:46:00\n", - " end_time (obs) datetime64[ns] 2022-10-18T01:06:20 ... 2022-10-18T05:52:20\n", - " z (zlev) int64 -5 -15 -25 -35 -45 ... -1965 -1975 -1985 -1995\n", - "Dimensions without coordinates: zlev\n", - "Data variables:\n", - " P (obs, zlev) float64 2.2 2.2 2.505 3.508 ... 199.0 200.1 200.2\n", - " T (obs, zlev) float64 25.02 25.02 24.9 24.17 ... 1.821 1.814 1.813\n", - " S (obs, zlev) float64 33.82 33.82 33.84 33.97 ... 34.6 34.6 34.6\n", - " Rho (obs, zlev) float64 1.022e+03 1.022e+03 ... 1.028e+03 1.028e+03" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# you do not have to change this\n", - "zlev = np.arange(-5,-2000,-10) # new depth levels\n", - "ctd_interp = xr.apply_ufunc(\n", - " interp_1d, # function to apply along core dimension\n", - " ctd_up, # arg1\n", - " ctd_up.z, # arg2\n", - " zlev, # arg3\n", - " input_core_dims=[['trajectory'],['trajectory'],['zlev']], # core dimension per arg\n", - " output_core_dims=[['zlev']], # core dimension output\n", - " exclude_dims=set(['trajectory']), # input dimension that may disappear in output\n", - " vectorize=True, # vectorizes args so interp_1d receives one-dimensional data\n", - " keep_attrs=True, # keep array attributes\n", - " on_missing_core_dim='copy', # how to handle possibly missing core dims on input\n", - ")\n", - "ctd_interp = ctd_interp.drop_vars('z').assign_coords(\n", - " {'z':('zlev',zlev, ctd_interp.z.attrs)}) # set z as 1D coord\n", - "ctd_interp" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__d)__ Plot vertical cross sections of temperature, salinity and density with longitude and depth on the x- and y-axis, respectively." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Answer\n", - "fig = plt.figure(figsize=(12,6))\n", - "ax1 = fig.add_subplot(131)\n", - "ax2 = fig.add_subplot(132, sharey=ax1)\n", - "ax2.yaxis.set_visible(False)\n", - "ax3 = fig.add_subplot(133, sharey=ax1)\n", - "ax3.yaxis.tick_right()\n", - "ax3.yaxis.set_label_position('right')\n", - "ctd_interp.T.plot(ax=ax1,x='lon',y='z',cmap=cmocean.cm.thermal,\n", - " cbar_kwargs={'orientation':'horizontal'})\n", - "ctd_interp.S.plot(ax=ax2,x='lon',y='z',cmap=cmocean.cm.haline,\n", - " cbar_kwargs={'orientation':'horizontal'})\n", - "ctd_interp.Rho.plot(ax=ax3,x='lon',y='z',cmap=cmocean.cm.dense,\n", - " cbar_kwargs={'orientation':'horizontal'})\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__e)__ Calculate and plot the vertical shear of the meridional velocity, assuming the flow is in thermal wind balance." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# Answer\n", - "Re = 6371000 # radius earth [m]\n", - "Om = 2*np.pi/(86400) # angular frequency earth [s-1]\n", - "\n", - "latr = np.deg2rad(ctd_interp.lat) # latitude (rad)\n", - "lonr = np.deg2rad(ctd_interp.lon) # longitude (rad)\n", - "dlonr = lonr.diff('obs') # longitude difference between casts (rad)\n", - "dx = Re*np.cos(latr)*dlonr # distance between cast locations (m)\n", - "f = 2*Om*np.sin(latr) # coriolis parameter\n", - "\n", - "rho = ctd_interp.Rho # density (kg m-3)\n", - "drho = rho.diff('obs') # density difference between casts (kg m-3)\n", - "dvdz = -g/(f*rho) * drho/dx # vertical shear of meridional flow (m s-1)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'vertical shear of meridional velocity')" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dvdz.plot.pcolormesh(x='lon',y='z',cbar_kwargs={'label':r'dv/dz [s$^{-1}$]'})\n", - "plt.title('vertical shear of meridional velocity')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A06_Q1.ipynb b/teaching_material/Assignment/Preparatory_exercises/A06_Q1.ipynb deleted file mode 100644 index 364d2511..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A06_Q1.ipynb +++ /dev/null @@ -1,110 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment 6.1: Upwelling near Peru\n", - "The ocean region near Peru is known for its upwelling, causing the rise of nutrient-rich bottom water to the surface and a subsequently flourishing ecosystem. Hence, it is an important region for wildlife and for the fishery industry. \n", - "\n", - "We explored this area with an ADCP device onboard the \"virtual ship\". It measured zonal and meridional velocities up to 500 metres depth. In this assignment you will process this data and interpret the results with your knowledge of wind-induced effects on ocean circulation." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.colors as mcolors\n", - "import cartopy.crs as ccrs\n", - "import cmocean\n", - "import numpy as np\n", - "from geopy import distance" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__a)__ Make a plot of the ship's trajectory. Check that it runs perpendicular to the coast of Peru." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__b)__ Calculate the distance from each measurement to the coast and add it as variable to the dataset." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__c)__ Calculate and plot the velocity components parallel and perpendicular to the coast." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Assuming constant density and no velocity variations in the longshore direction, the continuity equation may be written \n", - "$$\\frac{\\partial u_{cross}}{\\partial s} + \\frac{\\partial w}{\\partial z} = 0$$ \n", - "where $u_{cross}$ is the cross-shore velocity, $s$ the shoreward distance, $w$ the vertical velocity and $z$ the depth (upward positive). \n", - "\n", - "__d)__ Starting from the surface downward, integrate the continuity equation to find the vertical velocity. Explain what you see. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/A06_Q1_withanswers.ipynb b/teaching_material/Assignment/Preparatory_exercises/A06_Q1_withanswers.ipynb deleted file mode 100644 index a46de0af..00000000 --- a/teaching_material/Assignment/Preparatory_exercises/A06_Q1_withanswers.ipynb +++ /dev/null @@ -1,285 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Assignment 6.1: Upwelling near Peru\n", - "The ocean region near Peru is known for its upwelling, causing the rise of nutrient-rich bottom water to the surface and a subsequently flourishing ecosystem. Hence, it is an important region for wildlife and for the fishery industry. \n", - "\n", - "We explored this area with an ADCP device onboard the \"virtual ship\". It measured zonal and meridional velocities up to 500 metres depth. In this assignment you will process this data and interpret the results with your knowledge of wind-induced effects on ocean circulation." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.colors as mcolors\n", - "import cartopy.crs as ccrs\n", - "import cmocean\n", - "import numpy as np\n", - "from geopy import distance" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__a)__ Make a plot of the ship's trajectory. Check that it runs perpendicular to the coast of Peru." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Peru adcp')" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Answer\n", - "peru = xr.open_zarr('Peru_adcp.zarr').compute()\n", - "\n", - "# for convenience, define z positive upward\n", - "zu = np.unique(-peru.z, axis=1).squeeze() # convert z to 1D and positive upward\n", - "peru = peru.assign_coords({'z':('trajectory',zu)}).sortby('z')\n", - "\n", - "# plot track\n", - "ax = plt.axes(projection=ccrs.PlateCarree())\n", - "ax.scatter(peru.lon, peru.lat, transform=ccrs.PlateCarree())\n", - "ax.coastlines()\n", - "ax.gridlines(draw_labels=True)\n", - "ax.set_extent((-85,-75,-15,-5))\n", - "ax.set_title('Peru adcp')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__b)__ Calculate the distance from each measurement to the coast and add it as variable to the dataset." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "max distance: 362.62 km\n" - ] - } - ], - "source": [ - "# Answer\n", - "peru_surf = peru.isel(trajectory=0).compute()\n", - "d = xr.zeros_like(peru_surf.lon)\n", - "lon0,lat0 = peru_surf.lon.data[-1], peru_surf.lat.data[-1]\n", - "for ob,(lon,lat) in enumerate(zip(peru_surf.lon.data,peru_surf.lat.data)):\n", - " d[ob] = distance.distance((lon,lat),(lon0,lat0)).m\n", - "peru['s'] = -d.assign_attrs({\n", - " 'long_name':'distance to coast','units':'m','positive':'shoreward'})\n", - "peru = peru.set_coords('s').sortby('s')\n", - "print(f\"max distance: {abs(peru.s.min()).data/1000:.2f} km\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "__c)__ Calculate and plot the velocity components parallel and perpendicular to the coast." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Answer\n", - "\n", - "# calculations\n", - "dlon = np.deg2rad(peru_surf.lon.differentiate('obs'))\n", - "dlat = np.deg2rad(peru_surf.lat.differentiate('obs'))\n", - "lat = np.deg2rad(peru_surf.lat)\n", - "alpha = np.arctan(dlat/(dlon*np.cos(lat))).mean('obs') # cruise direction angle\n", - "Ucross = np.cos(alpha)*peru.U + np.sin(alpha)*peru.V # cross-shore vel\n", - "Ulong = -np.sin(alpha)*peru.U + np.cos(alpha)*peru.V # long-shore vel\n", - "peru['Ucross'] = Ucross.assign_attrs({'long_name':'cross-shore velocity','units':'m s-1'})\n", - "peru['Ulong'] = Ulong.assign_attrs({'long_name':'longshore velocity','units':'m s-1'})\n", - "\n", - "# figure settings\n", - "fig = plt.figure(figsize=(10,6))\n", - "norm = mcolors.CenteredNorm(halfrange=0.35)\n", - "cmap = cmocean.cm.balance\n", - "landmask = xr.where(((peru.U==0) & (peru.V==0)), 1, np.nan)\n", - "S = peru.s.broadcast_like(peru.lon)\n", - "\n", - "# cross-shore velocity plot\n", - "ax1 = fig.add_subplot(121)\n", - "p = ax1.pcolormesh(S/1000, peru.z, peru.Ucross, norm=norm, cmap=cmap)\n", - "ax1.pcolormesh(S/1000, peru.z, landmask, cmap='binary_r')\n", - "ax1.set_ylabel('depth [m]')\n", - "ax1.set_xlabel('distance from coast [km]')\n", - "ax1.set_title('cross-shore velocity (positive shoreward)')\n", - "ax1.grid()\n", - "\n", - "# alongshore velocity plot\n", - "ax2 = fig.add_subplot(122, sharey=ax1)\n", - "ax2.yaxis.tick_right()\n", - "p2 = ax2.pcolormesh(S/1000, peru.z, peru.Ulong, norm=norm, cmap=cmap)\n", - "ax2.pcolormesh(S/1000, peru.z, landmask, cmap='binary_r')\n", - "ax2.set_ylabel('depth [m]', rotation=270, labelpad=15)\n", - "ax2.set_xlabel('distance from coast [km]')\n", - "ax2.set_title('longshore velocity (positive with coast on r.h.s.)')\n", - "ax2.yaxis.set_label_position('right')\n", - "ax2.grid()\n", - "fig.colorbar(p, ax=[ax1,ax2], shrink=0.7, orientation='horizontal',\n", - " label=r'm s$^{-1}$')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Assuming constant density and no velocity variations in the longshore direction, the continuity equation may be written \n", - "$$\\frac{\\partial u_{cross}}{\\partial s} + \\frac{\\partial w}{\\partial z} = 0$$ \n", - "where $u_{cross}$ is the cross-shore velocity, $s$ the shoreward distance, $w$ the vertical velocity and $z$ the depth (upward positive). \n", - "\n", - "__d)__ Starting from the surface downward, integrate the continuity equation to find the vertical velocity. Explain what you see. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Answer\n", - "peru_d = peru.sortby('z', ascending=False) # sort downward\n", - "\n", - "# # compute dwdz - easy central difference method\n", - "# dwdz = -peru_d.Ucross.differentiate('s')\n", - "\n", - "# compute dwdz - central difference using interpolated values at cell edges\n", - "# slightly more accurate\n", - "landfilter = xr.where(((peru_d.U==0) & (peru_d.V==0)), 0, 1) # 0 in land, 1 in ocean\n", - "Ucrossi = peru_d.Ucross.interp(obs=peru_d.obs-0.5) # U at cell boundaries (toward ocean)\n", - "Ucrossi = Ucrossi * landfilter.data\n", - "dUcrossds = Ucrossi.diff('obs') / Ucrossi.s.diff('obs')\n", - "dwdz = -dUcrossds\n", - "\n", - "# # integrate dwdz\n", - "peru['w'] = dwdz.cumulative_integrate('z')\n", - "\n", - "# plot\n", - "ax = plt.axes()\n", - "S,Z = xr.broadcast(peru.s/1000, peru.z)\n", - "w = ax.pcolormesh(S, Z, peru.w.T, norm=mcolors.CenteredNorm(), cmap=cmap)\n", - "ax.pcolormesh(S, Z, landmask.T, cmap='binary_r')\n", - "plt.title('vertical velocity')\n", - "plt.ylabel('depth [m]')\n", - "plt.xlabel('shoreward distance [km]')\n", - "plt.xlim([-350,0])\n", - "plt.colorbar(w, label=r'm s$^{-1}$')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Answer: the south-easterly winds near Peru create Ekman transport away from the coast (to the left of the wind direction in the SH), leading to an SSH-gradient directed off the coast. This SSH-gradient results in a pressure gradient force directed toward the coast and a longshore geostrophic current with the coast on its r.h.s.. Due to friction at the bottom, the coriolis force of the current decreases and gives rise to a cross-shore current that is pushed up against the topography. This explains the column of water having positive vertical velocity near the land boundary. \n", - "\n", - "There are limitations to this point of view. The longshore geostrophic current does not show up at all depths near the coast. Likely, some baroclinic effects are important as well. Besides, the vertical velocity is derived assuming incompressibility and no longshore variations in longshore flow. Especially the last statement may lead to inaccurate results. Besides, ocean models often use \"shaved cells\" near the topographic boundary of reduced thickness. This needs to be accounted for before calculating water fluxes." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.1" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/teaching_material/Assignment/Preparatory_exercises/python_getting_ready_for_dyoc.pdf b/teaching_material/Assignment/Preparatory_exercises/python_getting_ready_for_dyoc.pdf deleted file mode 100644 index b077010d..00000000 Binary files a/teaching_material/Assignment/Preparatory_exercises/python_getting_ready_for_dyoc.pdf and /dev/null differ diff --git a/teaching_material/Assignment/Presentation Rubric.pdf b/teaching_material/Assignment/Presentation Rubric.pdf deleted file mode 100644 index 17ef27f2..00000000 Binary files a/teaching_material/Assignment/Presentation Rubric.pdf and /dev/null differ diff --git a/teaching_material/Assignment/README.md b/teaching_material/Assignment/README.md deleted file mode 100644 index 2956ab29..00000000 --- a/teaching_material/Assignment/README.md +++ /dev/null @@ -1,24 +0,0 @@ -# Teaching material used for 8 week VirtualShip assignment -Graduate level course material that students worked on for about 30-40 hours in groups of 3-4 students each. -Prerequisites are basic proficiency with Python and preferably Xarray. - -### week 1 -The students received the 'Intro letter' and the 'Course examination'. -The students made Preparatory assigments 1.1 and 2.1 - -### week 2 -Groups were formed, the students chose from the 'Case studies', formulated a research question and handed in a 'Code of conduct. -The students made Preparatory assignments 3.1 and 4.1 - -### week 3 -The students got feedback on their research question and handed in a 'Cruise proposal' using the 'Cruise_plan_info.ipynb' -The students made Preparatory assignments 5.1 and 6.1 - -### week 4 to 6 -The students 'Sail_the_ship' and analyse the results. - -### week 7 -The students gave a presentation about their results, it was graded using the 'Rubric'. - -### week 8 -The students handed in their science communication article (as described in the 'Course examination'). diff --git a/teaching_material/Assignment/Sail_the_ship.ipynb b/teaching_material/Assignment/Sail_the_ship.ipynb deleted file mode 100644 index a06f638d..00000000 --- a/teaching_material/Assignment/Sail_the_ship.ipynb +++ /dev/null @@ -1,143 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "https://www.youtube.com/watch?v=G82kIgc1imk\n", - "\n", - "\n", - "\n", - "### Time has come to start your expedition!\n", - "Make sure your datafiles, the JSON file and this file are all in the same folder.\n", - "\n", - "It might take up to an hour to gather the data depending on your choices, make sure your computer doesn't fall asleep while running the cells/script below.\n", - "\n", - "Meanwhile read up on some of the onboard safety procedures and browse through blogs and cruise reports if you want. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Download the latest version of the virtual ship and the bathymetry file\n", - "import requests \n", - "\n", - "files = {\n", - " \"GLO-MFC_001_024_mask_bathy.nc\":\"https://surfdrive.surf.nl/files/index.php/s/AdbtlgP3LJv6tOn/download\",\n", - " \"virtualship.py\":\"https://raw.githubusercontent.com/OceanParcels/Virtual_ship_classroom/main/virtualship.py\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - "\n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)\n", - "print('Download ready')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Sail the virtual ship!\n", - "%run virtualship.py" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Welcome aboard\n", - "\n", - "Welcome aboard, oceanography students, to our scientific research vessel! We're thrilled to have you join us for this exciting 3-week journey into the depths of the ocean. As we embark on this voyage of exploration and discovery, there are a few things I'd like to share with you to ensure a smooth and enriching experience:\n", - "\n", - "**Introduction to the Vessel:** Take some time to familiarize yourselves with the layout of the ship. Get to know key areas such as the laboratories, living quarters, dining area, and deck spaces. \n", - "\n", - "**Daily Routine:** Life on a research vessel follows a structured daily routine. We'll have designated times for meals, research activities, data analysis, and downtime. It's important to maintain this routine to ensure that our work is conducted efficiently and that everyone onboard has the opportunity to rest and recharge.\n", - "\n", - "**Safety Orientation:** Safety is our top priority. As we set sail, we'll conduct a comprehensive safety orientation. This will cover important topics such as emergency procedures, the location of safety equipment, and proper use of personal protective gear. Please pay close attention during this orientation to ensure your safety and the safety of others on board.\n", - "\n", - "**Respect for the Environment:** As we explore the ocean, it's essential to maintain a deep respect for the marine environment. We'll adhere to strict environmental protocols to minimize our impact on marine ecosystems and wildlife. Remember to dispose of waste properly and avoid disturbing marine life whenever possible.\n", - "\n", - "**Teamwork and Collaboration:** Oceanographic research is a collaborative effort that requires teamwork and cooperation. You'll be working closely with your fellow students. Embrace the opportunity to learn from each other and support one another throughout the journey.\n", - "\n", - "![Ship layout](https://ceoas.oregonstate.edu/sites/ceoas.oregonstate.edu/files/ship_design_bw_1400x500.jpg)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "\n", - "### Emergency procedures\n", - "\n", - "Before going on any research expedition you need follow a one day Safety at Sea course and get a medical check-up.\n", - "\n", - "Of course this is not needed for your virtual fieldwork, but I like to draw for your attention to the following on-board emergency procedures.\n", - "\n", - "**Safety Drills:** We conduct regular safety drills to ensure that everyone on board is well-prepared in case of an emergency. Specifically, fire and boat drills are held once a week. These drills are not just routine; they are essential survival training and should be taken seriously. To minimize disruption to the research program, science party members are usually notified in advance of the scheduled drills. In the event that you must continue working during a drill, prior arrangements can be made through the Chief Scientist.\n", - "\n", - "**Emergency Signal:** In the event of an emergency signal, your immediate action is crucial. Don life jackets, put on long-sleeved garments, and wear a hat or head covering if available. Then, proceed to the designated station indicated on the station card located next to your bunk.\n", - "\n", - "**On-Call Readiness:** Please keep in mind that while on board the ship, you may be called upon without warning to assist during your off-watch periods. Emergencies can happen at any time, and your readiness to respond promptly and efficiently is essential to the safety of all aboard.\n", - "\n", - "**Boat Drill (Abandon Ship):** The signal for abandon ship is seven or more short blasts followed by one long blast of the ship’s whistle and general alarm. When this signal is heard, report to your designated life raft station. There the Mate in charge will explain the procedures for launching and embarking into the life rafts. The rafts will not be launched during a drill.\n", - "\n", - "**Fire and Emergency Drills:** The signal is one long blast on the ship’s whistle and general alarm bell, lasting for ten seconds or more. During this drill, members of the science party muster in the designated area. Attendance will be taken and reported to the bridge.\n", - "\n", - "**Man Overboard:** If someone falls overboard, throw a life-ring into the water towards the person. Keep your eye on the person at all times and point towards the person. Shout “MAN OVERBOARD, STARBOARD (or PORT),” and call the bridge on the sound powered phone or squawk box to inform them without losing sight of the person if possible. If you hear someone hail \"Man Overboard,\" pass the word to the bridge." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Reporting\n", - "Reporting your journey is an essential aspect of our oceanographic research expedition. It allows us to share our experiences, communicate our findings, and contribute to the broader scientific community. After each scientific expedition a cruise reports needs to be written. \n", - "You can find many cruise reports online, e.g. https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/pe358.pdf and blogs from many different cruises, e.g. https://www.nioz.nl/en/blog/topic/1027. \n", - "\n", - "Reporting our journey allows us to validate the data collected during our research activities. It provides context for our findings and helps ensure that our results are accurately interpreted and understood. Detailed reports enable us to cross-reference our observations with environmental conditions, sampling locations, and other relevant factors, enhancing the reliability and credibility of our data. Our reports also serve as valuable educational resources for students, educators, and the general public. They provide insights into the process of scientific inquiry, the challenges of conducting research at sea, and the significance of oceanographic discoveries. \n", - "\n", - "I look forward to seeing the impact of your collective efforts during the presentations on March 22nd!\n", - "\n", - "Please don't worry if your results are insufficient to answer your research question. Share your failure and things you would do different a next time instead!\n", - "\n", - "E.g. Normalizing failure: when things go wrong in participatory marine social science fieldwork. https://academic.oup.com/icesjms/article/79/8/2184/6705562 \n", - "\n", - "E.g. Emotions and failure in academic life: Normalising the experience and building resilience. https://www.cambridge.org/core/journals/journal-of-management-and-organization/article/emotions-and-failure-in-academic-life-normalising-the-experience-and-building-resilience/91FD71A50A32404D8EDFFB7886FF3521\n", - "\n", - "![Our ocean provides](https://seewhatgrows.org/wp-content/uploads/2019/06/our-ocean.jpg)\n", - "![10 ways to help our ocean](https://oceanservice.noaa.gov/ocean/help-ocean.jpg)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/teaching_material/Assignment/VSC case studies DyOc.pdf b/teaching_material/Assignment/VSC case studies DyOc.pdf deleted file mode 100644 index cd18d76c..00000000 Binary files a/teaching_material/Assignment/VSC case studies DyOc.pdf and /dev/null differ diff --git a/teaching_material/Assignment/cruise_plan_info.ipynb b/teaching_material/Assignment/cruise_plan_info.ipynb deleted file mode 100644 index 6812d67a..00000000 --- a/teaching_material/Assignment/cruise_plan_info.ipynb +++ /dev/null @@ -1,316 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Additional information for creating a cruiseplan \n", - "Run the cell below to download required data and scripts" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import json \n", - "import os \n", - "import requests \n", - "\n", - "files = {\n", - " \"GLO-MFC_001_024_mask_bathy.nc\":\"https://surfdrive.surf.nl/files/index.php/s/AdbtlgP3LJv6tOn/download\",\n", - " \"virtualship.py\":\"https://raw.githubusercontent.com/OceanParcels/Virtual_ship_classroom/main/virtualship.py\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - "\n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)\n", - "print('Download ready')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Check your JSON file:\n", - "After you filled in your cruise proposal template and your JSON file, please run the following cell to check the input and correct your JSON file if necessary: " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from virtualship import VirtualShipConfiguration\n", - "config = VirtualShipConfiguration('student_input.json') " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Ship cruising speed\n", - "\n", - "The cruising speed of the research vessel (i.e. the max speed between two locations without performing operations) is 10 knots. A knot is a unit of speed, equal to one nautical mile per hour. Something traveling at one knot is going about 1.151 land miles per hour. 10 knots = 18.52 kilometers per hour. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Cruise map\n", - "\n", - "A possible way to create a list of coordinates and/or map of your cruise is to use an interactive leafmap. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import leafmap \n", - "from ipyleaflet import Rectangle \n", - " \n", - "m = leafmap.leafmap.Map(center=(0, -100), zoom=5) \n", - "# Draw a rectange to indicate region where data will be collected \n", - "m.add_layer(Rectangle(bounds=((64, -43), (59, -23)))) \n", - "# Add a point at port of departure: Puntarenas, Costa Rica \n", - "m.add_marker([9.97625, -84.83836]) \n", - "m " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can use the feature “Draw a polyline” (5th symbol from the top) to assemble a list of coordinates. Each point you click will show up as a white square and can be given as output. The blue lines can be used as transects. Double click the last point to finish the line (or click Finish). Create your output with: " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "line = m.user_rois \n", - "coords = line.get('features')[0].get('geometry').get('coordinates') \n", - "print(coords) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Total cruise time \n", - "\n", - "To estimate the cruise time, you’ll need to divide the travelled distance by the cruise speed. To calculate the distance between 2 geographic coordinates you can use the haversine function (https://community.esri.com/t5/coordinate-reference-systems-blog/distance-on-a-sphere-the-haversine-formula/ba-p/902128) or an existing python package, for example geopy (https://geopy.readthedocs.io/en/stable/#module-geopy.distance) or haversine (https://pypi.org/project/haversine/) " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from geopy import distance\n", - "newport_ri = (41.49008, -71.312796)\n", - "cleveland_oh = (41.499498, -81.695391)\n", - "print(distance.great_circle(newport_ri, cleveland_oh).nautical)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Depth sampling \n", - "\n", - "A possible way to investigate the depth where you’ll be sampling is to use the bathymetry data that the virtual ship will also use.\n", - "\n", - "An example for plotting and querying is given below." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt \n", - "import cartopy.crs as ccrs \n", - "import xarray as xr \n", - " \n", - "# Load the bathymetry data using xarray \n", - "data = xr.open_dataset('YOUR_OWN_DATA_PATH/GLO-MFC_001_024_mask_bathy.nc') \n", - "# Create a bathymetry figure and axis with Cartopy projection \n", - "fig, ax = plt.subplots(figsize=(15, 5), subplot_kw={'projection': ccrs.PlateCarree()}) \n", - "data.deptho.plot(ax=ax, cmap='viridis') \n", - "# Specify extent, add gridlines and coastlines, show plot \n", - "ax.set_extent((130,160,-70,-40), crs=ccrs.PlateCarree()) \n", - "ax.gridlines(draw_labels=True) \n", - "ax.coastlines() \n", - "plt.show() \n", - "# Query and print the bathymetry data at the specified location \n", - "station_depth = data.deptho.sel(latitude=-50, longitude=150, method='nearest') \n", - "print(station_depth.values) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Measurement options \n", - "\n", - "### Underway data \n", - "\n", - "Underway data collection, also known as underway sampling, refers to the process of collecting oceanographic and environmental data while a research vessel is in motion. This method allows scientists to continuously gather data on various parameters such as sea surface temperature and salinity. The water inlet is located onthe hull of the ship at approximately 2 meters under the surface. \n", - "\n", - "You can collect underway data during your entire cruise and may assume it doesn’t take any time to start or stop taking measurements. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### CTD \n", - "\n", - "A Conductivity, Temperature, and Depth (CTD) sensor is an instrument used to measure the physical properties of seawater in oceanographic and environmental research. It typically consists of sensors for conductivity, temperature, and pressure (which is used to derive depth). \n", - "\n", - "Throughout a CTD deployment, the research vessels needs to stay in the same location. To calculate the time needed for a CTD deployment, take the following information into account: \n", - "\n", - "Add time to lower the vessels speed to zero and set the vessel to the appropriate direction against swell, current, wind, etc = 10 minutes \n", - "Add time to deploy the CTD, and to recover = 10 minutes (2*5 min) \n", - "Add time for the way down and up, usually at 1 m/s (winch capacity) = twice your water depth (in seconds) \n", - "\n", - "https://youtu.be/7N2UsPDczTw?feature=shared \n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ADCP \n", - "\n", - "An Acoustic Doppler Current Profiler (ADCP) is an instrument used to measure the speed and direction of ocean currents at various depths. It operates based on the principle of Doppler shift, where sound waves emitted by the instrument are reflected off moving particles in the water, such as plankton or sediment, and the frequency shift of the returning waves is used to calculate the velocity of the water. \n", - "\n", - "You can deploy the ADCP on transects and choose between a shallow profiler capable of providing information to a depth of 150 m every 4 meters (the 300kHz seaSeven), or a long-range profiler capable of providing about 1000m of range every 24 meters (the 38kHz Ocean Observer). You may assume it doesn’t take any time to start or end ADCP measurements. \n", - "\n", - "https://youtu.be/mDyoZagght8?feature=shared&t=38 \n", - "\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Drifters \n", - "\n", - "A surface drifter is an oceanographic instrument used to study surface currents and ocean circulation patterns. These devices are designed to drift passively with the surface currents while transmitting data on their position and temperature. \n", - "\n", - "You may assume it doesn’t take any time to deploy drifters. \n", - "\n", - "https://youtu.be/3m_CxEE8Bhs?feature=shared&t=15 \n", - "\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Argo floats \n", - "\n", - "Argo floats are self-contained, battery-powered instruments equipped with sensors to measure temperature and salinity profiles from the surface down to depths of up to 2000 meters or more. These sensors provide high-resolution vertical profiles of ocean properties, allowing researchers to study ocean variability and climate change. \n", - "\n", - "The floats periodically descend to a predetermined depth, typically around 1000 meters, and then ascend to the surface, measuring temperature and salinity profiles along the way. In tutorial 2, you learn how to control the dive depth and duration. \n", - "\n", - "You may assume it doesn’t take any time to deploy Argo floats. \n", - "\n", - "https://youtu.be/IgcYQML5se4?feature=shared \n", - "\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Additional information \n", - "\n", - " \n", - "\n", - "Things not to worry about on your virtual cruise, but which are important when planning an actual cruise: \n", - "\n", - " \n", - "\n", - "### Planning \n", - "\n", - "Preparing for a seagoing expedition involves many months (often years) of planning. There are many forms and documents to prepare; there are many criteria to be met and logistical issues to sort out; there are even issues of personal preparation. The most successful research cruises are typically the ones that are planned early, with an awareness of both the big picture and the fine details. Research ships are often fully booked over a year in advance. Collaborative planning ensures that cruises in neighboring regions are scheduled together to minimize transit time. To gain insights into the schedules of various European research ships, you can e.g. refer to https://www.marinefacilitiesplanning.com/programme. \n", - "\n", - " \n", - "\n", - "### Diplomatic clearance \n", - "\n", - "If the cruise includes data collection and/or sampling in other countries exclusive economic zones (EEZ) the cruise leader must seek permission through diplomatic channels ref UNCLOS (United Nations Convention of the Laws Of the Seas) Part XIII Marine Scientific Research. Normal processing time is at least 3 to 6 months. This is especially important when sampling on or below the seafloor, trawling, and collecting high resolution bathymetric data. \n", - "\n", - " \n", - "\n", - "### Polar code \n", - "\n", - "Research vessels have different polar capabilities and it therefore varies in which areas they can operate at different times of the year, depending on ice conditions and minimum allowed air temperature. \n", - "\n", - " \n", - "\n", - "### Crew shifts \n", - "\n", - "Many research vessels operate on a watch system, where crew members are divided into teams (watches) that take turns being responsible for the vessel's operations. This ensures that the vessel is staffed 24 hours a day, allowing for continuous data collection and monitoring. Traditional watch schedules include the “12-on, 12-off\", “4-on, 8-off\" or \"6-on, 6-off\" rotation, where crew members work for a set number of hours (e.g., 4 or 6 hours) and then have a set amount of time off duty. This rotation continues throughout the day and night. Depending on the requirements of the research mission, modified watch schedules may be implemented. \n", - "\n", - " \n", - "\n", - "### Logistics (transportation, customs, intermediate storage) \n", - "\n", - "All equipment required at sea needs to be transferred to the port of departure before leaving. Consider these issues on how to prepare and pack your equipment in the office: \n", - "\n", - "Create a comprehensive checklist of all the equipment you'll need for your research. This includes scientific instruments, sampling tools, safety gear, and any other materials essential to your work. \n", - "Clean and calibrate your instruments as needed. Ensure that sensors are functioning properly, batteries are charged, and any necessary software is updated. Make note of any items that may require special handling or storage. \n", - "Organize your equipment in a systematic manner. Group items together based on their function or use. Clearly label each item with its name, purpose, and any specific instructions for handling or setup. \n", - "Fit your equipment in the 20-foot container. The container will be sent to your port of departure ahead of time with a cargo boat, so make sure you are packed in time for this transfer. Remember there are no shops at sea, so think carefully and plan ahead. \n", - "You are responsible for ensuring the equipment is loaded or unloaded from the vessel. You should plan to have a responsible person at the port stop for loading or unloading your equipment. Please do not assume the crew will take care of this for you. \n", - "\n", - "![Equipment preparation NIOZ](https://www.nioz.nl/application/files/9116/7500/3457/2023-01-16-packing.jpg) \n", - "\n", - "![Equipment loading](https://www.nioz.nl/application/files/7416/7810/2265/2023-03-06-container-shifting.jpg) " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/teaching_material/ElNino/Cruise_part2_IPO.ipynb b/teaching_material/ElNino/Cruise_part2_IPO.ipynb deleted file mode 100644 index 600fa515..00000000 --- a/teaching_material/ElNino/Cruise_part2_IPO.ipynb +++ /dev/null @@ -1,454 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [], - "toc_visible": true - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - } - }, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "## **Save** the notebook to your own Google Drive " - ], - "metadata": { - "id": "YflTDF1zgK_j" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Welcome back" - ], - "metadata": { - "id": "momm90ntaeaj" - } - }, - { - "cell_type": "markdown", - "source": [ - "Dear Oceanography Students,\n", - "\n", - "Welcome back to our virtual ship classroom! We hope you had a restful Christmas break after our simulated cruise. Now, it's time to dive into the next phase of our research journey.\n", - "\n", - "`Please continue your work (with your partner) and write down your name(s) and studentnumber(s) here...`\n", - "\n", - "If you didn't manage to create your own cruise results, please download a results file from Blackboard and upload it into Colab (It would be nice if not all groups choose the same!). Otherwise make sure you upload your own results :-)" - ], - "metadata": { - "id": "vQxriiFepWwi" - } - }, - { - "cell_type": "code", - "source": [ - "# Run this cell to unpack the results folder\n", - "!unzip results.zip -d ." - ], - "metadata": { - "id": "iK1pmc_Y_VPH" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "*If you are using Safari and the results folder is unpacked straight away. Click Preferences. Under the General tab, uncheck the option Open “safe” files after downloading.*\n", - "\n", - "$\\color{green}{\\text{# The following cells only need to be run if you uploaded your own data! If you use results from Blackboard the data has already been postprocessed.}}$\n", - "\n", - "The data you've gathered still requires some postprocessing before you can continue your work to extract meaningful insights.\n", - "\n", - "So make sure you install the required packages and download the necessary scripts by running the cells below. You can continue reading while the cells are being executed." - ], - "metadata": { - "id": "pxu-5Oqq_R91" - } - }, - { - "cell_type": "code", - "source": [ - "# ONLY run if you saved your own results from Dec 18th!\n", - "!pip install parcels\n", - "!pip install cartopy\n", - "!pip install xarray\n", - "!pip install cftime\n", - "!pip install cgen\n", - "!pip install netCDF4\n", - "!pip install zarr" - ], - "metadata": { - "id": "qzMKhiQ4pXYC" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "# ONLY run if you saved your own results from Dec 18th!\n", - "# Download data\n", - "import requests\n", - "\n", - "files = {\n", - " \"virtualship.py\":\"https://raw.githubusercontent.com/OceanParcels/Virtual_ship_classroom/main/virtualship.py\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - "\n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)\n", - "print('Download ready')" - ], - "metadata": { - "id": "ErdzdimhpaSj" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Please check your Results folder for the number of CTD stations you have visited during the cruise and specify as ctd_num below:" - ], - "metadata": { - "id": "8aliESboBmx6" - } - }, - { - "cell_type": "code", - "source": [ - "# ONLY run if you saved your own results from Dec 18th!\n", - "ctd_num = \n", - "\n", - "# Run the following lines to postprocess the data from the virtual ship\n", - "from virtualship import VirtualShip\n", - "VirtualShip.postprocess(ctd=ctd_num)" - ], - "metadata": { - "id": "XFO5Q0XaHStd" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "### CTD procedure\n", - "\n", - "While that's being handled, please revisit the CTD operation procedure below and the CTD manual that can be found on Blackboard.\n", - "\n", - "1. Check the CTD System: Before deployment, ensure that the CTD system is in working order.\n", - "\n", - "2. Communicate with Winch Operator: Before, during and after deployment, maintain continuous communication with the winch operator. Relay any instructions for changes in speed, depth, or other parameters.\tWarn the winch operator when CTD is coming near the bottom (100m, 50m, 20m), when to stop and hoist it back up.\n", - "\n", - "3. Depth Profiling: While the CTD is submerged, keep an eye on the data being collected at various depths as the instrument descends and ascends. Follow the predetermined sampling plan or adjust as needed based on real-time observations.\n", - "\n", - "Since the ocean is about 4 km deep in the El Nino region you would have been doing this for 2 hours straigth for every cast. Requiring quite a bit of patience and focus.\n", - "\n", - "![CTD operation](https://www.nioz.nl/application/files/8716/7933/4421/2023-03-26-CTD2.jpg)\n", - "\n" - ], - "metadata": { - "id": "ULHrJXOop8mI" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Thermocline\n", - "\n", - "If you managed to make it to the end of the practical/notebook on December 18th (perhaps in a separate notebook) you can revisit your work and find your code to plot a CTD profile. Otherwise you can start from the code below. You will use the CTD profile to locate the thermocline.\n", - "\n", - "The thermocline is typically characterized by a sharp decrease in temperature compared to the layers above and below it. Look at your temperature vs. depth plot and compare the temperature characteristics of the potential thermocline to the layers above and below. The thermocline should stand out as a distinct transition layer where the temperature gradient is steeper. In addition to temperature, consider other parameters such as salinity. The thermocline is often associated with changes in other properties as well. Analyzing multiple variables can help you indentify the thermocline and provide a more comprehensive understanding of the ocean's vertical structure. To be confident about your answer you could cross-reference your observations with existing literature about El Niño.\n", - "\n" - ], - "metadata": { - "id": "XRvpX6svNUTu" - } - }, - { - "cell_type": "code", - "source": [ - "# Plot a/any CTD profile from your cruise (use your code from December 18th, or replace the <...> instances to make the code below work\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "# Read in data\n", - "P, T, S = np.loadtxt(fname=, delimiter=, skiprows=, unpack=True)\n", - "# You might want to download the file and have in look at it in a basic text editor like Notepad, Notes or Wordpad\n", - "# to find out what the delimiter is and when the actual data begins\n", - "\n", - "# Plot the data\n", - "fig, ax1 = plt.subplots(1,1)\n", - "\n", - "# Plot temperature or salinity on the first x-axis\n", - "ax1.plot()\n", - "ax1.invert_yaxis() # depth increases downwards\n", - "ax1.set_xlabel()\n", - "ax1.set_ylabel()\n", - "\n", - "# Plot temperature or salinity on the second x-axis\n", - "ax2 = ax1.twiny() # ax1 and ax2 share y-axis\n", - "ax2.plot()\n", - "ax2.set_xlabel()\n", - "plt.show()" - ], - "metadata": { - "id": "pB0fKL1dL6OZ" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "For simplicity you can assume a depth-pressure conversion factor of 1 so 1000 m = 1000 dbar = 100 hPa = 100 bar\n", - "\n", - "`Please give the depth [m] of the thermocline visible in the CTD profile above ...`\n" - ], - "metadata": { - "id": "6fntE79RAwGn" - } - }, - { - "cell_type": "markdown", - "source": [ - "### 20C isotherm\n", - "\n", - "The thermocline is important because it can support large scale waves which play a major role in El Niño/ENSO. In studying the tropical Pacific Ocean, the depth of 20$^\\circ$C water (\"the 20C isotherm\") is often used as a proxy for the depth of the thermocline. Along the equator, the 20C isotherm is typically located at about 50m depth in the eastern pacific, sloping downwards to about 150 m in the western Pacific.\n", - "\n", - "We are currently in an El Niño event, so warmer-than-average sea surface temperatures extend across the equatorial Pacific and the thermocline is located deeper than usual in the eastern pacific.\n", - "\n", - "![El nino isotherm](https://www.weather.gov/source/zhu/ZHU_Training_Page/tropical_stuff/enso/images/el.jpg)\n", - "\n", - "Source: https://www.weather.gov/source/zhu/ZHU_Training_Page/tropical_stuff/enso/enso2.htm\n", - "\n" - ], - "metadata": { - "id": "mYCLz9j6L6zA" - } - }, - { - "cell_type": "code", - "source": [ - "# Calculate the depth [m] of the 20C isotherm for the station that you have used in the plot above\n", - "# Hint: use the first element [0] of P when T < 20, use only square brackets []\n", - "z20 =" - ], - "metadata": { - "id": "fKVISc7AKDJf" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Now, for each CTD station save the latitude and longitude and the depth of the 20C isotherm. Storing the values for lat, lon and z20 in separate arrays will make it easy to work with the data later on." - ], - "metadata": { - "id": "i-INWlTIKJ-u" - } - }, - { - "cell_type": "code", - "source": [ - "# Some sample code you can use, you only have to replace the <...> instances to make it work\n", - "lon = []\n", - "lat = []\n", - "z20 = []\n", - "\n", - "for i in range(1, ):\n", - " with open(f'./results/CTD_station_{i}.csv', 'r') as file:\n", - " station_data = file.read().splitlines()\n", - " lon.append(station_data[1])\n", - " lat.append()\n", - "\n", - " P, T, S = np.loadtxt(f'./results/CTD_station_{i}.csv', delimiter=',', skiprows=7, unpack=True)\n", - " z20.append()" - ], - "metadata": { - "id": "XWt5l1pvX9KF" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Once you fill the arrays with data from your CTD casts, please plot your data and estimate the avrage gradient [m/degree] of z20 from West to East over the region you've gathered data for.\n", - "\n", - "Perhaps you feel your data is insufficient for this. But you'll have to make an attempt.\n", - "\n", - "You can ask others for their results to combine data from the different cruises to get a better picture\n", - "\n", - "Realizing the vastness of the ocean can be both humbling and awe-inspiring. The scale of the marine environment, from the surface to the deepest trenches, is a constant reminder of the challenges and opportunities inherent in oceanographic research. The vastness of the ocean poses technological challenges for data collection as traditional methods, such as research vessels, have limitations in terms of coverage and depth. And in addition, the oceans exhibit significant variability across time and space. Limited data points can make it challenging to capture and understand these variations.\n", - "\n", - "Or, to quote Claudio Pierard (PhD student in Ocean Physics, modelling currents and other parameters to understand dynamics in the ocean at IMAU, UU) who is currently at sea: \"`Heading west towards North America in a ship puts the speed of modern travel into perspective. The ocean is massive! Distances that appear short on maps take several days to reach by ship. And our progress is limited by the weather conditions`\"\n", - "https://www.nioz.nl/en/blog/niozatsea-ocean-nanoplastics-ii" - ], - "metadata": { - "id": "9g4yiYk2yaAt" - } - }, - { - "cell_type": "code", - "source": [ - "# Code using (geo)pandas for plotting\n", - "import pandas as pd\n", - "import geopandas as gpd\n", - "\n", - "df = pd.DataFrame({'lat': lat, 'lon': lon, 'z20': z20})\n", - "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(lon, lat))\n", - "gdf.plot(column='z20', legend=True, aspect=None) # try aspect='equal' if your map is distorted" - ], - "metadata": { - "id": "STQnPqV0kOqw" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "`The gradient of the 20C isotherm (in m/degree) is...`\n" - ], - "metadata": { - "id": "bTnGXGIgLz7Q" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Warm Water Volume\n", - "\n", - "Warm Water Volume (WWV) is a key metric used in the study and prediction of El Niño and La Niña events. Warmer-than-average conditions in the equatorial Pacific are associated with El Niño. WWV represents the accumulated heat content in the upper ocean layer, typically measured in the central and eastern equatorial Pacific Ocean.\n", - "\n", - "Please make an estimate of the total Warm Water Volume in the East Pacific\n", - " (5°N-5°S, 120°E-80°W) using the depth of the z20 you've calculated. You can assume each degree of both latitude and longitude is 111 km.\n", - "\n", - "`The total Warm Water Volume in the East Pacific (in m3) is...`\n", - "\n", - "Please provide your calculation below." - ], - "metadata": { - "id": "hbB6QfL1FO4t" - } - }, - { - "cell_type": "code", - "source": [], - "metadata": { - "id": "LVqSgIn_ldBT" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "## ADCP data\n", - "Up till now we have not considered the ADCP data you've collected during the cruise. But if you're up for a challenge or have time left, please go for it!\n", - "\n", - "For this cruise you can asume you have high quality ADCP data, so the velocity components (eastward, northward, and vertical) are well measured and you don't have to worry about the backscatter intensity and ping information. You'll find the ADCP data in a .zarr file in your results folder or on Blackboard. Zarr is a file storage format for chunked, compressed, N-dimensional arrays based on an open-source specification. The format of observational data might (will!) differ from instrument to instrument and cruise to cruise, so getting some experience on how to read in different data formats will come in handy.\n", - "\n", - "Lucily most data formats can easily be handeled by different packages in python. For zarr and NetCDF data the xarray package is very useful." - ], - "metadata": { - "id": "PvkxBpwxfgsF" - } - }, - { - "cell_type": "code", - "source": [ - "# Code using xarray for reading in data and plotting\n", - "import xarray as xr\n", - "\n", - "# Open output and read to x, y, z\n", - "ds = xr.open_zarr(\"./results/sailship_adcp.zarr\")\n", - "x = ds[\"lon\"][:].squeeze()\n", - "y = ds[\"lat\"][:].squeeze()\n", - "z = ds[\"z\"][:].squeeze()\n", - "U = ds[\"U\"][:].squeeze()\n", - "V = ds[\"V\"][:].squeeze()\n", - "ds.close()\n", - "\n", - "# Sample code for a figure\n", - "fig = plt.figure\n", - "ax = plt.axes(projection=\"3d\")\n", - "cb = ax.scatter(x, y, z, c=U, s=20, marker=\"o\")\n", - "ax.set_xlabel(\"Longitude\")\n", - "ax.set_ylabel(\"Latitude\")\n", - "ax.set_zlabel(\"Depth (m)\")\n", - "ax.set_zlim(np.max(z), 0)\n", - "plt.show()" - ], - "metadata": { - "id": "5Be8DhwJiyia" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "## Final remarks\n", - "\n", - "Thank you for participating in this virtual ship classroom and exporing the vast blue expanse of the Pacific Ocean with us! We hope you learned a lot and feel more comfortable and knowledgable about research cruises. Please realise the skills you've gained during this practical will make you a more valuable assistent on any cruise. Even with these limited skills you would be able to contribute to the fieldwork and the cruise report that needs to be written afterwards. You can find many cruise reports online, e.g. https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/pe358.pdf\n", - "\n", - "\n", - "\n", - "### 5 minute survey\n", - "Please fill in the survey about these tutorials to help us improve them!\n", - "\n", - "https://survey.uu.nl/jfe/form/SV_3ITkc2KEDrlAt5s\n", - "\n" - ], - "metadata": { - "id": "lfxi0jLfizb3" - } - }, - { - "cell_type": "markdown", - "source": [ - "### Send in your work\n", - "\n", - "Please send a link of your assignment to blackboard:\n", - "\n", - "1- Assure that you **save** the notebook to your Google Drive \n", - "2- Rename it to your name \n", - "3- Follow the instructions in the screenshot below \n", - "4- Test the link in Incognito mode (private browsing). If it opens without issues or asking to log in, then send it using Black Board \n", - "\n", - "`Black Board:` \n", - "`Course Content ----> Assignments ----> Virtual ship classroom`" - ], - "metadata": { - "id": "7nXvwtbuWySz" - } - }, - { - "cell_type": "markdown", - "source": [ - 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)" - ], - "metadata": { - "id": "N08CAyTBWjd4" - } - } - ] -} \ No newline at end of file diff --git a/teaching_material/ElNino/ElNinoLesson.ipynb b/teaching_material/ElNino/ElNinoLesson.ipynb deleted file mode 100644 index 7cefbc2d..00000000 --- a/teaching_material/ElNino/ElNinoLesson.ipynb +++ /dev/null @@ -1,297 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "Latest version for IPO can be found at: https://colab.research.google.com/drive/1dabU91WECy5cglb2mVC-8SG4muFNlQrw?usp=sharing\n", - "And part two: https://colab.research.google.com/drive/13PrubhXazYvdotzrVeY4iPw3_rm4PA1s?usp=sharing" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Dear Oceanography Students,\n", - "\n", - "With excitement and anticipation, we extend our warmest greetings as you embark on an extraordinary journey with us, sailing the vast blue expanse of the Pacific Ocean. Welcome aboard the R/V Ocean Explorer, your home and laboratory for the next few weeks as we delve into the captivating realm of oceanography and the phenomenon known as El Niño.\n", - "\n", - "Before embarking on this journey please make sure you install the required packages in colab: " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "!pip install parcels\n", - "!pip install cartopy\n", - "!pip install xarray\n", - "!pip install cftime\n", - "!pip install cgen\n", - "!pip install netCDF4\n", - "!pip install zarr\n", - "!pip install leafmap\n", - "!pip install pymbolic" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Download data\n", - "import requests\n", - "\n", - "files = {\n", - " \"studentdata_UV.nc\":\"https://surfdrive.surf.nl/files/index.php/s/kpm6LAopuY1WonX/download\", \n", - " \"studentdata_S.nc\":\"https://surfdrive.surf.nl/files/index.php/s/pSXY546jD3iOLBL/download\",\n", - " \"studentdata_T.nc\":\"https://surfdrive.surf.nl/files/index.php/s/k3QwnvwhVLmXtxt/download\",\n", - " \"virtualship.py\":\"https://raw.githubusercontent.com/OceanParcels/Virtual_ship_classroom/main/virtualship.py\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - " \n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "While that's being handled, we kindly ask for your attention to the following emergency procedures.\n", - "\n", - "**Safety Drills:** We conduct regular safety drills to ensure that everyone on board is well-prepared in case of an emergency. Specifically, fire and boat drills are held once a week. These drills are not just routine; they are essential survival training and should be taken seriously. To minimize disruption to the research program, science party members are usually notified in advance of the scheduled drills. In the event that you must continue working during a drill, prior arrangements can be made through the Chief Scientist.\n", - "\n", - "**Emergency Signal:** In the event of an emergency signal, your immediate action is crucial. Don life jackets, put on long-sleeved garments, and wear a hat or head covering if available. Then, proceed to the designated station indicated on the station card located next to your bunk.\n", - "\n", - "**On-Call Readiness:** Please keep in mind that while on board the ship, you may be called upon without warning to assist during your off-watch periods. Emergencies can happen at any time, and your readiness to respond promptly and efficiently is essential to the safety of all aboard.\n", - "\n", - "**Boat Drill (Abandon Ship):** The signal for abandon ship is seven or more short blasts followed by one long blast of the ship’s whistle and general alarm. When this signal is heard, report to your designated life raft station. There the Mate in charge will explain the procedures for launching and embarking into the life rafts. The rafts will not be launched during a drill.\n", - "\n", - "**Fire and Emergency Drills:** The signal is one long blast on the ship’s whistle and general alarm bell, lasting for ten seconds or more. During this drill, members of the science party muster in the designated area. Attendance will be taken and reported to the bridge.\n", - "\n", - "**Man Overboard:** If someone falls overboard, throw a life-ring into the water towards the person. Keep your eye on the person at all times and point towards the person. Shout “MAN OVERBOARD, STARBOARD (or PORT),” and call the bridge on the sound powered phone or squawk box to inform them without losing sight of the person if possible. If you hear someone hail \"Man Overboard,\" pass the word to the bridge." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now, please continue our preperations and familiarize yourself with our research vessel and its equipment. The research vessel we are using is equipped with a CTD (Conductivity, Temperature, and Depth) and ADCP (Acoustic Doppler Current Profiler). \n", - "\n", - "The CTD profiler is your window into the ocean's physical properties. It measures the parameters temperature, salinity, and depth, providing invaluable insights into ocean stratification and circulation. You'll have to decide where and how often to deploy the CTD. A CTD casts takes approximately 3 hours in our region of interest. The data will be postprocessed for you and available in 10m bins. \n", - "\n", - "The ADCP is your radar beneath the waves. It employs sound waves to map currents and water velocity, revealing the dynamic movements of the ocean. Our ADCP, a 38kHz Ocean Observer is the longest-range profiler, capable of providing about 1000m of current profiling range. The ADCP is attached to the bottom of our vessel and will continously measure within our area of interest. The data will be postprocessed for you and binned into 50m layers. \n", - "\n", - "![ADCP figure](https://www.researchgate.net/profile/Lashika-Medagoda/publication/294279160/figure/fig2/AS:961324506951680@1606209031289/The-ADCP-mode-of-the-DVL-sensor-operates-by-looking-at-the-returns-from-scatterers-in-the.gif)\n", - "\n", - "Source: Medagoda et al. 2016. DOI:10.1007/s10514-016-9547-3" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Our mission will last for three weeks. Three weeks is found to be a good trade-off between reasearch time and time that it's still enjoyable to be on a vessel. This time frame will limit the time for our scientific mission, but please consider that even at 90°W ample evidence of El Niño can be collected. For example, the depth of the thermocline might be interesting to investigate. Deciding on a clear research question will help you in the planning and preparation of the cruise. You can read up on some information here: https://www.climate.gov/news-features/blogs/november-2023-el-nino-update-transport-options" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "$\\color{green}{\\text{Please write down your research question here:}}$" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So, let's chart our course and plan the next three weeks of research. Below, you'll find a map detailing our intended cruise area. Your mission is to determine the best research stations (= CTD sample locations) and routes to gather data that will deepen our understanding of El Niño. Consider the ocean's depth, known El Niño hotspots, and areas of interest when planning your route. Our vessels home port and place to board is Puntarenas, Costa Rica: 9°58'39.5\"N 84°50'55.9\"W.\n", - "\n", - "Run the cell below to generate the map. Once you see the map, click on the line feature “Draw a polyline” and start drawing the line. Each point you click will show up as a white square and will be used as a CTD sample location, the ADCP measurements will be conducted along the blue lines connecting the research stations. Double click the last point to finish the line (or click Finish). Your cruise plan should start and end at Puntarenas. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ee8e052126c04266b7861b06923463c3", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Map(center=[0, -120], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zoom_out_te…" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import leafmap \n", - "from ipyleaflet import Rectangle\n", - "\n", - "m = leafmap.leafmap.Map(center=(0, -120), zoom=4)\n", - "# Draw a rectange to indicate El Nino region, where data will be collected \n", - "m.add_layer(Rectangle(bounds=((5, -170), (-10, -75))))\n", - "m.add_marker([9.97625, -84.83836])\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Run the following cell to output your latitude and longitude coordinates:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "line = m.user_rois\n", - "coords = line.get('features')[0].get('geometry').get('coordinates')\n", - "print(coords) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Please rerun the cells and draw the line until you are satisfied with the result. Or make a similar vector of lat-lon coordinates yourself. \n", - "\n", - "Do ensure that the time allotted for the expedition does not exceed the designated three-week duration. Please remember to consider factors like your home port, weather conditions and any additional time needed for data collection and analysis.\n", - "\n", - "Here's a possible outline of how to check on the length of your cruise plan:\n", - "\n", - "1.\tGather the latitude and longitude coordinates of your research stations.\n", - "2.\tPlug these coordinates into the Haversine formula to calculate the distance between each station:\n", - "\n", - "![Haversine formula](https://www.auraq.com/wp-content/uploads/2019/02/charlie2.jpg)\n", - "\n", - "3.\tKnowing the vessel's cruising speed of 14 km/h, you can then estimate the time required to travel between each station by dividing the distance by the vessel's speed.\n", - "4.\tAdd time for each CTD cast you make. The ocean is around 4 km deep in the Niño3.4 area and a CTD is lowered and raised with a speed of 1 m/s. The time for deploying the CTD and transfering the samples to water bottles takes about 1 hour at each station. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We'd like to emphasize the importance of staying within our designated three-week timeframe. If your cruise plan indicates that the journey would exceed this allotted time, we kindly request that you revise and adjust your route accordingly. \n", - "\n", - "$\\color{green}{\\text{Please write down your vector of coordinates:}}$\n", - "\n", - "$\\color{green}{\\text{Please write down the estimated duration of the cruise here:}}$\n", - "\n", - "$\\color{green}{\\text{Please specify the estimated time of arrival in and departure from our region of interest:}}$" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If you have thoroughly reviewed and are content with your research plan, the time has come to take action and prepare to board the R/V Ocean Explorer! Here's a step-by-step guide on how to prepare and pack your equipment in the office before transferring it to the ship:\n", - "\n", - "Step 1: Equipment Checklist\n", - "\n", - "Create a comprehensive checklist of all the equipment you'll need for your research. This includes scientific instruments, sampling tools, safety gear, and any other materials essential to your work. Ensure that everything is in working order, and make note of any items that may require special handling or storage.\n", - "\n", - "Step 2: Preparing the Equipment\n", - "\n", - "Clean and calibrate your instruments as needed. Ensure that sensors are functioning properly, batteries are charged, and any necessary software is updated. This step is crucial for the accuracy and success of your research at sea.\n", - "\n", - "Step 3: Organize and Label\n", - "\n", - "Organize your equipment in a systematic manner. Group items together based on their function or use. Clearly label each item with its name, purpose, and any specific instructions for handling or setup. \n", - "\n", - "Step 4: Container transfer\n", - "\n", - "Your equipment will be transfered to the ship in a 20 foot container. The container will be sent to Puntarenas, Costa Rica ahead of time with a cargo boat, so make sure you are packed in time for this transfer. Remember there are no shops at sea, so think carefully and plan ahead very well.\n", - "\n", - "![Equipment preparation NIOZ](https://www.nioz.nl/application/files/9116/7500/3457/2023-01-16-packing.jpg)\n", - "![Equipment loading](https://www.nioz.nl/application/files/7416/7810/2265/2023-03-06-container-shifting.jpg)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Run the following lines to send out the virtual ship\n", - "from virtualship import VirtualShip\n", - "VirtualShip.sailship(coords_input = coords)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Please realize it will take some time to generate the data for your specific cruise. \n", - "\n", - "During this period, we encourage you to make the most of your time by familiarizing yourselves with historical CTD (Conductivity, Temperature, and Depth) output data. This preparation will equip you with valuable skills in reading, interpreting, and visualizing crucial oceanographic data. While waiting for our virtual cruise to finish, consider forming study groups or engaging in discussions with your peers. Share insights, ask questions, and collaborate on understanding the intricacies of historical CTD output. \n", - "\n", - "1. Data Structure: Explore the structure of the data. Understand the variables, units, and how the data is organized. Familiarize yourself with the columns and rows, as this knowledge will be instrumental when working with real-time data. The numpy package has a function loadtxt that you might want to utilize for this. You'll be able to read the columns into different variables in one go.\n", - "\n", - "2. Data Visualization: Practice visualizing the data. Utilize tools like graphs, charts, and maps to represent the variations in conductivity, temperature, and depth. This exercise will enhance your ability to interpret and communicate findings effectively. You might want to use the matplotlib.pyplot function with an inverted axis (e.g. ax1.invert_yaxis()) and shared y axis (ax2 = ax1.twiny()) for visualization.\n", - "\n", - "3. Quality Control: Learn about quality control procedures. Identify and understand potential anomalies or irregularities in the data. For example, take care to separate the upcast and the downcast. Samples are always taken on the upcast, so the downcast will have an undisturbed profile. \n", - "\n", - "4. Appropriate Sampling Depths: Check out the salinity sampling protocol on Blackboard and decide on 4 depths to sample using the Niskin bottles. \n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "$\\color{green}{\\text{Please generate a figure of Temperature and Salinity against depth in a new code cell below or above.}}$\n", - "\n", - "$\\color{green}{\\text{Please give 4 appropriate sampling depths:}}$\n", - "\n", - "![CTD rosette on the Pelagia ship](https://www.nioz.nl/application/files/3316/1124/8184/01-21-ctd-bob.jpg)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "parcels", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/teaching_material/ElNino/El_Nino_cruise_IPO.ipynb b/teaching_material/ElNino/El_Nino_cruise_IPO.ipynb deleted file mode 100644 index 8ce07d79..00000000 --- a/teaching_material/ElNino/El_Nino_cruise_IPO.ipynb +++ /dev/null @@ -1,492 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - } - }, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "## **Save** the notebook to your own Google Drive " - ], - "metadata": { - "id": "YflTDF1zgK_j" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Welcome aboard" - ], - "metadata": { - "id": "momm90ntaeaj" - } - }, - { - "cell_type": "markdown", - "source": [ - "Dear Oceanography Students,\n", - "\n", - "With excitement and anticipation, we extend our warmest greetings as you embark on an extraordinary journey with us, sailing the vast blue expanse of the Pacific Ocean. Welcome aboard the R/V Ocean Explorer, your home and laboratory for the next few weeks as we delve into the captivating realm of oceanography and the phenomenon known as El Niño.\n", - "\n", - "`You can work on this assignment in couples. Please write down your name(s) and studentnumber(s) here...`\n", - "\n", - "Before embarking on this journey please make sure you install the required packages and download the necessary data by running the cells below. You can continue reading while the cells are being executed." - ], - "metadata": { - "id": "vQxriiFepWwi" - } - }, - { - "cell_type": "code", - "source": [ - "!pip install parcels\n", - "!pip install cartopy\n", - "!pip install xarray\n", - "!pip install cftime\n", - "!pip install cgen\n", - "!pip install netCDF4\n", - "!pip install zarr\n", - "!pip install leafmap\n", - "!pip install pymbolic" - ], - "metadata": { - "id": "qzMKhiQ4pXYC" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "# Download data\n", - "import requests\n", - "\n", - "files = {\n", - " \"studentdata_UV.nc\":\"https://surfdrive.surf.nl/files/index.php/s/kpm6LAopuY1WonX/download\",\n", - " \"studentdata_S.nc\":\"https://surfdrive.surf.nl/files/index.php/s/pSXY546jD3iOLBL/download\",\n", - " \"studentdata_T.nc\":\"https://surfdrive.surf.nl/files/index.php/s/k3QwnvwhVLmXtxt/download\",\n", - " \"GLO-MFC_001_024_mask_bathy.nc\":\"https://surfdrive.surf.nl/files/index.php/s/AdbtlgP3LJv6tOn/download\",\n", - " \"historical_CTD.csv\":\"https://surfdrive.surf.nl/files/index.php/s/PzmwRnThh8iERwG/download\",\n", - " \"virtualship.py\":\"https://raw.githubusercontent.com/OceanParcels/Virtual_ship_classroom/main/virtualship.py\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - "\n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)\n", - "print('Download ready')" - ], - "metadata": { - "id": "ErdzdimhpaSj" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "### Emergency procedures\n", - "\n", - "While that's being handled, we kindly ask for your attention to the following emergency procedures.\n", - "\n", - "**Safety Drills:** We conduct regular safety drills to ensure that everyone on board is well-prepared in case of an emergency. Specifically, fire and boat drills are held once a week. These drills are not just routine; they are essential survival training and should be taken seriously. To minimize disruption to the research program, science party members are usually notified in advance of the scheduled drills. In the event that you must continue working during a drill, prior arrangements can be made through the Chief Scientist.\n", - "\n", - "**Emergency Signal:** In the event of an emergency signal, your immediate action is crucial. Don life jackets, put on long-sleeved garments, and wear a hat or head covering if available. Then, proceed to the designated station indicated on the station card located next to your bunk.\n", - "\n", - "**On-Call Readiness:** Please keep in mind that while on board the ship, you may be called upon without warning to assist during your off-watch periods. Emergencies can happen at any time, and your readiness to respond promptly and efficiently is essential to the safety of all aboard.\n", - "\n", - "**Boat Drill (Abandon Ship):** The signal for abandon ship is seven or more short blasts followed by one long blast of the ship’s whistle and general alarm. When this signal is heard, report to your designated life raft station. There the Mate in charge will explain the procedures for launching and embarking into the life rafts. The rafts will not be launched during a drill.\n", - "\n", - "**Fire and Emergency Drills:** The signal is one long blast on the ship’s whistle and general alarm bell, lasting for ten seconds or more. During this drill, members of the science party muster in the designated area. Attendance will be taken and reported to the bridge.\n", - "\n", - "**Man Overboard:** If someone falls overboard, throw a life-ring into the water towards the person. Keep your eye on the person at all times and point towards the person. Shout “MAN OVERBOARD, STARBOARD (or PORT),” and call the bridge on the sound powered phone or squawk box to inform them without losing sight of the person if possible. If you hear someone hail \"Man Overboard,\" pass the word to the bridge." - ], - "metadata": { - "id": "ULHrJXOop8mI" - } - }, - { - "cell_type": "markdown", - "source": [ - "### Equipment\n", - "\n", - "Now, please continue our preperations and familiarize yourself with our research vessel and its equipment. The research vessel we are using is equipped with a CTD (Conductivity, Temperature, and Depth) and ADCP (Acoustic Doppler Current Profiler).\n", - "\n", - "The CTD profiler is your window into the ocean's physical properties. It measures the parameters temperature, salinity, and depth, providing invaluable insights into ocean stratification and circulation. You'll have to decide where and how often to deploy the CTD. A CTD casts takes up to 3 hours in our region of interest. The data will be postprocessed for you and available in 10m bins.\n", - "\n", - "The ADCP is your radar beneath the waves. It employs sound waves to map currents and water velocity, revealing the dynamic movements of the ocean. Our ADCP, a 38kHz Ocean Observer is the longest-range profiler, capable of providing about 1000m of current profiling range. The ADCP is attached to the bottom of our vessel and will continously measure within our area of interest. The data will be postprocessed for you and binned into 50m layers.\n", - "\n", - "![ADCP figure](https://www.researchgate.net/profile/Lashika-Medagoda/publication/294279160/figure/fig2/AS:961324506951680@1606209031289/The-ADCP-mode-of-the-DVL-sensor-operates-by-looking-at-the-returns-from-scatterers-in-the.gif)\n", - "\n", - "Source: Medagoda et al. 2016. DOI:10.1007/s10514-016-9547-3" - ], - "metadata": { - "id": "1FXNKRWAqhBT" - } - }, - { - "cell_type": "markdown", - "source": [ - "### Research question\n", - "\n", - "Our mission will last for three weeks. Three weeks is found to be a good trade-off between reasearch time and time that it's still enjoyable to be on a vessel. This time frame will limit the time for our scientific mission, but please consider that even at 90°W ample evidence of El Niño can be collected. For a regular cruise you should decide on a clear research question beforehand. But because time is limited for this exercise, you will investigate the depth of the thermocline and the Warm Water Volume. This means the CTD casts will be your primary source of data, so please make sure you plan enough of them. If time allows you will also investigate water movement with the ADCP data.\n", - "\n", - "You can find some additional information on El Niño here: https://www.climate.gov/news-features/blogs/november-2023-el-nino-update-transport-options" - ], - "metadata": { - "id": "NpzKdhWVrWzg" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Misson planning\n", - "\n", - "So, let's chart our course and plan the next three weeks of research. Below, you'll generate a map detailing our intended cruise area. Your mission is to determine the best research stations (= CTD sample locations) and routes to gather data that will deepen our understanding of El Niño. Consider the ocean's depth, known El Niño hotspots, and areas of interest when planning your route. Our vessels home port and place to board is Puntarenas, Costa Rica: 9°58'39.5\"N 84°50'55.9\"W.\n", - "\n", - "The vessel's cruise speed is only 13 km/h, so you won't be able to travel very far.\n", - "\n", - "Run the cell below to generate the map. Once you see the map, click on the line feature “Draw a polyline” and start drawing the line. Each point you click will show up as a white square and will be used as a CTD sample location, the ADCP measurements will be conducted along the blue lines connecting the research stations. Double click the last point to finish the line (or click Finish). Your cruise plan should start and end near Puntarenas." - ], - "metadata": { - "id": "bs5bazevCpBD" - } - }, - { - "cell_type": "code", - "source": [ - "import leafmap\n", - "from ipyleaflet import Rectangle\n", - "\n", - "m = leafmap.leafmap.Map(center=(0, -120), zoom=4)\n", - "# Draw a rectange to indicate El Nino region, where data will be collected\n", - "m.add_layer(Rectangle(bounds=((5, -170), (-10, -75))))\n", - "# Add a point at Puntarenas\n", - "m.add_marker([9.97625, -84.83836])\n", - "m" - ], - "metadata": { - "id": "uLiCDRAOAssK" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Run the following cell to output your latitude and longitude coordinates:" - ], - "metadata": { - "id": "AaZ6kuMSDCiG" - } - }, - { - "cell_type": "code", - "source": [ - "line = m.user_rois\n", - "coords = line.get('features')[0].get('geometry').get('coordinates')\n", - "print(coords)" - ], - "metadata": { - "id": "HiO06AplC0pu" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Please rerun the cells and draw the line until you are satisfied with the result. Or make a similar vector of lat-lon coordinates yourself.\n", - "\n", - "Do ensure that the time allotted for the expedition does not exceed the designated three-week duration. Please remember to consider factors like your home port, weather conditions and any additional time needed for data collection and analysis.\n", - "\n", - "Here's a possible outline of how to check on the length of your cruise plan:\n", - "\n", - "1.\tGather the latitude and longitude coordinates of your research stations.\n", - "2.\tPlug these coordinates into the Haversine formula to calculate the distance between each station:\n", - "\n", - "![Haversine formula](https://www.auraq.com/wp-content/uploads/2019/02/charlie2.jpg)\n", - "\n", - "3.\tKnowing the vessel's cruising speed of 13 km/h, you can then estimate the time required to travel between each station by dividing the distance by the vessel's speed.\n", - "4.\tAdd time for each CTD cast you make. The ocean is around 4 km deep in the Niño3.4 area and a CTD is lowered and raised with a speed of 1 m/s. The time for deploying the CTD and transfering the samples to water bottles takes about 15 minutes at each station." - ], - "metadata": { - "id": "RDos0zboDLEp" - } - }, - { - "cell_type": "code", - "source": [ - "from math import radians, cos, sin, atan2, sqrt\n", - "# because we import cos, sin etc from math you can use them below as is without having to put math.sin (or np.sin)\n", - "\n", - "# Haversine template. Define a function to use later on\n", - "def haversine(lon1, lat1, lon2, lat2):\n", - " \"\"\"\n", - " Calculate the great circle distance in kilometers between two points\n", - " on the earth (specified in decimal degrees)\n", - " \"\"\"\n", - " # convert decimal degrees to radians\n", - " lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])\n", - "\n", - " # haversine formula\n", - " dlon = \n", - " dlat = \n", - " a = \n", - " c = \n", - " r = 6371 # Radius of earth in kilometers. Determines return value units.\n", - " return c * r\n", - "\n", - "# Use the function in a loop to calculate the distance between CTD stations\n", - "distances = []\n", - "for i in range(len(coords)-1):\n", - " distance = haversine(coords[i][0], coords[i][1], coords[i+1][0], coords[i+1][1])\n", - " distances.append(distance)\n", - "print(distances)\n", - "\n", - "# Sum distances to get total journey length\n", - "sum(distances)\n", - "# Compute how much time the jouney would take (at 13 km/hr cruise speed)\n", - "\n", - "# Add time for each CTD cast\n" - ], - "metadata": { - "id": "RJfRV2hBf9xP" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "We'd like to emphasize the importance of staying within our designated three-week timeframe. If your cruise plan indicates that the journey would exceed this allotted time, we kindly request that you revise and adjust your route accordingly.\n", - "\n", - "`Please write down your vector of coordinates here...`\n", - "\n", - "`Please write down the estimated duration of the cruise here...`\n", - "\n", - "Specify time needed for transit and CTD sampling separately if you want.\n", - "\n", - "On a real cruise you'd want to take care to adjust your planning so that sampling takes place during the day. If you care about your own sleep and that of the crew ;-)\n" - ], - "metadata": { - "id": "bTnGXGIgLz7Q" - } - }, - { - "cell_type": "code", - "source": [ - "# Make sure the coords variable contains the coordinates you want to sample and starts and ends at/near Puntarenas\n", - "coords" - ], - "metadata": { - "id": "3Ihhb2z7bfCc" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "### Preparation\n", - "\n", - "If you have thoroughly reviewed and are content with your research plan, the time has come to take action and prepare to board the R/V Ocean Explorer! Here's a step-by-step guide on how to prepare and pack your equipment in the office before transferring it to the ship:\n", - "\n", - "Step 1: Equipment Checklist\n", - "\n", - "Create a comprehensive checklist of all the equipment you'll need for your research. This includes scientific instruments, sampling tools, safety gear, and any other materials essential to your work. Ensure that everything is in working order, and make note of any items that may require special handling or storage.\n", - "\n", - "Step 2: Preparing the Equipment\n", - "\n", - "Clean and calibrate your instruments as needed. Ensure that sensors are functioning properly, batteries are charged, and any necessary software is updated. This step is crucial for the accuracy and success of your research at sea.\n", - "\n", - "Step 3: Organize and Label\n", - "\n", - "Organize your equipment in a systematic manner. Group items together based on their function or use. Clearly label each item with its name, purpose, and any specific instructions for handling or setup.\n", - "\n", - "Step 4: Container transfer\n", - "\n", - "Your equipment will be transfered to the ship in a 20 foot container. The container will be sent to Puntarenas, Costa Rica ahead of time with a cargo boat, so make sure you are packed in time for this transfer. Remember there are no shops at sea, so think carefully and plan ahead very well.\n", - "\n", - "![Equipment preparation NIOZ](https://www.nioz.nl/application/files/9116/7500/3457/2023-01-16-packing.jpg)\n", - "![Equipment loading](https://www.nioz.nl/application/files/7416/7810/2265/2023-03-06-container-shifting.jpg)" - ], - "metadata": { - "id": "_TbfLRGjMXtX" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Time to sail" - ], - "metadata": { - "id": "hWy45Tcnbxf7" - } - }, - { - "cell_type": "code", - "source": [ - "# Run the following lines to send out the virtual ship\n", - "from virtualship import VirtualShip\n", - "VirtualShip.sailship(coords_input=coords)" - ], - "metadata": { - "id": "4yUpEGugMZp1" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "Please realize it will take some time to generate the data for your specific cruise.\n", - "\n", - "During this period, we encourage you to make the most of your time by familiarizing yourselves with historical CTD (Conductivity, Temperature, and Depth) output data. This preparation will equip you with valuable skills in reading, interpreting, and visualizing crucial oceanographic data. While waiting for our virtual cruise to finish, consider forming study groups or engaging in discussions with your peers. Share insights, ask questions, and collaborate on understanding the intricacies of historical CTD output.\n", - "\n", - "1. Data Structure: Explore the structure of the data. Understand the variables, units, and how the data is organized. Familiarize yourself with the columns and rows, as this knowledge will be instrumental when working with real-time data. The numpy package has a function loadtxt that you might want to utilize for this. You'll be able to read the columns into different variables in one go.\n", - "\n", - "2. Data Visualization: Practice visualizing the data. Utilize tools like graphs, charts, and maps to represent the variations in conductivity, temperature, and depth. This exercise will enhance your ability to interpret and communicate findings effectively. You might want to use the matplotlib.pyplot function with an inverted axis (e.g. ax1.invert_yaxis()) and shared y axis (ax2 = ax1.twiny()) for visualization.\n", - "\n", - "3. Quality Control: Learn about quality control procedures. Identify and understand potential anomalies or irregularities in the data. For example, take care to separate the upcast and the downcast. Samples are always taken on the upcast, so the downcast will have an undisturbed profile.\n", - "\n", - "4. Appropriate Sampling Depths: Check out the salinity sampling protocol on Blackboard and decide on 4 depths to sample using the Niskin bottles.\n", - "\n" - ], - "metadata": { - "id": "9BdlHM0UYNRd" - } - }, - { - "cell_type": "code", - "source": [ - "# You'll probably want to run this code in a separate notebook as the previous cell will still be running\n", - "\n", - "# Download data\n", - "import requests\n", - "\n", - "files = {\"historical_CTD.csv\":\"https://surfdrive.surf.nl/files/index.php/s/PzmwRnThh8iERwG/download\"}\n", - "\n", - "for filename, url in files.items():\n", - " response = requests.get(url, allow_redirects=True)\n", - "\n", - " if response.status_code == 200:\n", - " with open(filename, \"wb\") as f:\n", - " f.write(response.content)\n", - " else:\n", - " print(\"Failed to download\", url)\n", - "\n", - "# Read in data\n", - "import numpy as np\n", - "P, T, S = np.loadtxt('historical_CTD.csv', delimiter=, skiprows=, unpack=True)\n", - "# You might want to download the file and have in look at it in a basic text editor like Notepad, Notes or Wordpad\n", - "\n", - "# Plot the data\n", - "import matplotlib.pyplot as plt\n", - "fig, ax1 = plt.subplots(1,1)\n", - "\n", - "# Plot temperature or salinity on the first x-axis\n", - "ax1.plot()\n", - "ax1.invert_yaxis() # depth increases downwards\n", - "ax1.set_xlabel()\n", - "ax1.set_ylabel()\n", - "\n", - "# Plot temperature or salinity on the second x-axis\n", - "ax2 = ax1.twiny() # ax1 and ax2 share y-axis\n", - "ax2.plot()\n", - "ax2.set_xlabel()\n", - "plt.show()" - ], - "metadata": { - "id": "1aXAp2stzE4S" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "`Please give 4 appropriate sampling depths [m] here...`\n", - "\n", - "For simplicity you can assume a depth-pressure conversion factor of 1.0 so 1000 m = 1000 dbar = 100 hPa = 100 bar\n" - ], - "metadata": { - "id": "RxW8sUWEYSTm" - } - }, - { - "cell_type": "markdown", - "source": [ - "![CTD rosette on the Pelagia ship](https://www.nioz.nl/application/files/3316/1124/8184/01-21-ctd-bob.jpg)" - ], - "metadata": { - "id": "m1IHzkBRfD4_" - } - }, - { - "cell_type": "markdown", - "source": [ - "## Save your work!\n", - "\n", - "Make sure you save all the files in the results folder. You'll need the files in the practical on January 8th where you'll be analyzing the data gathered during your cruise." - ], - "metadata": { - "id": "ARNRTCOEg0Yb" - } - }, - { - "cell_type": "code", - "source": [ - "# Zip the results folder so you can download it easily\n", - "!zip -r /results.zip /results" - ], - "metadata": { - "id": "8vF68xrzTVmg" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "source": [ - "### Send in your work\n", - "\n", - "Please send a link of your assignment to blackboard:\n", - "\n", - "1- Assure that you **save** the notebook to your Google Drive \n", - "2- Rename it to your name \n", - "3- Follow the instructions in the screenshot below \n", - "4- Test the link in Incognito mode (private browsing). If it opens without issues or asking to log in, then send it using Black Board \n", - "\n", - "`Black Board:` \n", - "`Course Content ----> Assignments ----> Virtual ship classroom`" - ], - "metadata": { - "id": "7nXvwtbuWySz" - } - }, - { - "cell_type": "markdown", - "source": [ - 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)" - ], - "metadata": { - "id": "N08CAyTBWjd4" - } - } - ] -} \ No newline at end of file diff --git a/tests.sh b/tests.sh new file mode 100755 index 00000000..a6203336 --- /dev/null +++ b/tests.sh @@ -0,0 +1,5 @@ +#!/bin/sh + +# Runs the tests and creates a code coverage report. + +pytest --cov=virtual_ship --cov-report=html tests diff --git a/tests/conftest.py b/tests/conftest.py new file mode 100644 index 00000000..1159768d --- /dev/null +++ b/tests/conftest.py @@ -0,0 +1,14 @@ +"""Test configuration that is ran for every test.""" + +import pytest + + +@pytest.fixture(autouse=True) +def test_in_working_dir(request, monkeypatch): + """ + Set the working directory for each test to the directory of that test. + + :param request: - + :param monkeypatch: - + """ + monkeypatch.chdir(request.fspath.dirname) diff --git a/tests/expedition/expedition_dir/.gitignore b/tests/expedition/expedition_dir/.gitignore new file mode 100644 index 00000000..fbca2253 --- /dev/null +++ b/tests/expedition/expedition_dir/.gitignore @@ -0,0 +1 @@ +results/ diff --git a/tests/expedition/expedition_dir/input_data/.gitignore b/tests/expedition/expedition_dir/input_data/.gitignore new file mode 100644 index 00000000..0f4bf3bf --- /dev/null +++ b/tests/expedition/expedition_dir/input_data/.gitignore @@ -0,0 +1,9 @@ +!argo_float_s.nc +!argo_float_t.nc +!argo_float_uv.nc +!bathymetry.nc +!default_s.nc +!default_t.nc +!default_uv.nc +!drifter_t.nc +!drifter_uv.nc diff --git a/tests/expedition/expedition_dir/input_data/argo_float_s.nc b/tests/expedition/expedition_dir/input_data/argo_float_s.nc new file mode 100644 index 00000000..7743124b Binary files /dev/null and b/tests/expedition/expedition_dir/input_data/argo_float_s.nc differ diff --git a/tests/expedition/expedition_dir/input_data/argo_float_t.nc b/tests/expedition/expedition_dir/input_data/argo_float_t.nc new file mode 100644 index 00000000..cee4478d Binary files /dev/null and b/tests/expedition/expedition_dir/input_data/argo_float_t.nc differ diff --git a/tests/expedition/expedition_dir/input_data/argo_float_uv.nc b/tests/expedition/expedition_dir/input_data/argo_float_uv.nc new file mode 100644 index 00000000..6012603a Binary files /dev/null and b/tests/expedition/expedition_dir/input_data/argo_float_uv.nc differ diff --git a/tests/expedition/expedition_dir/input_data/bathymetry.nc b/tests/expedition/expedition_dir/input_data/bathymetry.nc new file mode 100644 index 00000000..002eb339 Binary files /dev/null and b/tests/expedition/expedition_dir/input_data/bathymetry.nc differ diff --git a/tests/expedition/expedition_dir/input_data/default_s.nc b/tests/expedition/expedition_dir/input_data/default_s.nc new file mode 100644 index 00000000..7743124b Binary files /dev/null and b/tests/expedition/expedition_dir/input_data/default_s.nc differ diff --git a/tests/expedition/expedition_dir/input_data/default_t.nc 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diff --git a/tests/expedition/expedition_dir/schedule.yaml b/tests/expedition/expedition_dir/schedule.yaml new file mode 100644 index 00000000..6d55f6c5 --- /dev/null +++ b/tests/expedition/expedition_dir/schedule.yaml @@ -0,0 +1,16 @@ +waypoints: +- instrument: CTD + location: + latitude: 0 + longitude: 0 + time: 2023-01-01 00:00:00 +- instrument: DRIFTER + location: + latitude: 0.01 + longitude: 0.01 + time: 2023-01-01 01:00:00 +- instrument: ARGO_FLOAT + location: + latitude: 0.02 + longitude: 0.02 + time: 2023-01-01 02:00:00 diff --git a/tests/expedition/expedition_dir/ship_config.yaml b/tests/expedition/expedition_dir/ship_config.yaml new file mode 100644 index 00000000..c057d6b5 --- /dev/null +++ b/tests/expedition/expedition_dir/ship_config.yaml @@ -0,0 +1,21 @@ +ship_speed_meter_per_second: 5.14 +adcp_config: + num_bins: 40 + max_depth_meter: -1000.0 + period_minutes: 5.0 +argo_float_config: + cycle_days: 10.0 + drift_days: 9.0 + drift_depth_meter: -1000.0 + max_depth_meter: -2000.0 + min_depth_meter: 0.0 + vertical_speed_meter_per_second: -0.1 +ctd_config: + max_depth_meter: -2000.0 + min_depth_meter: -11.0 + stationkeeping_time_minutes: 20.0 +drifter_config: + depth_meter: 0.0 + lifetime_minutes: 40320.0 +ship_underwater_st_config: + period_minutes: 5.0 diff --git a/tests/expedition/test_do_expedition.py b/tests/expedition/test_do_expedition.py new file mode 100644 index 00000000..11e6b862 --- /dev/null +++ b/tests/expedition/test_do_expedition.py @@ -0,0 +1,9 @@ +from pytest import CaptureFixture + +from virtual_ship.expedition import do_expedition + + +def test_do_expedition(capfd: CaptureFixture) -> None: + do_expedition("expedition_dir") + out, _ = capfd.readouterr() + assert "This expedition took" in out, "Expedition did not complete successfully." diff --git a/tests/expedition/test_schedule.py b/tests/expedition/test_schedule.py new file mode 100644 index 00000000..37ee4a47 --- /dev/null +++ b/tests/expedition/test_schedule.py @@ -0,0 +1,26 @@ +from datetime import datetime, timedelta + +import py + +from virtual_ship import Location +from virtual_ship.expedition import Schedule, Waypoint + + +def test_schedule(tmpdir: py.path.LocalPath) -> None: + out_path = tmpdir.join("schedule.yaml") + + # arbitrary time for testing + base_time = datetime.strptime("1950-01-01", "%Y-%m-%d") + + schedule = Schedule( + waypoints=[ + Waypoint(Location(0, 0), time=base_time, instrument=None), + Waypoint( + Location(1, 1), time=base_time + timedelta(hours=1), instrument=None + ), + ] + ) + schedule.to_yaml(out_path) + + schedule2 = Schedule.from_yaml(out_path) + assert schedule == schedule2 diff --git a/tests/expedition/test_simulate_schedule.py b/tests/expedition/test_simulate_schedule.py new file mode 100644 index 00000000..e27fed3f --- /dev/null +++ b/tests/expedition/test_simulate_schedule.py @@ -0,0 +1,48 @@ +from datetime import datetime, timedelta + +import pyproj + +from virtual_ship import Location +from virtual_ship.expedition import Schedule, ShipConfig, Waypoint +from virtual_ship.expedition.simulate_schedule import ( + ScheduleOk, + ScheduleProblem, + simulate_schedule, +) + + +def test_simulate_schedule_feasible() -> None: + """Test schedule with two waypoints that can be reached within time is OK.""" + base_time = datetime.strptime("2022-01-01T00:00:00", "%Y-%m-%dT%H:%M:%S") + + projection = pyproj.Geod(ellps="WGS84") + ship_config = ShipConfig.from_yaml("expedition_dir/ship_config.yaml") + ship_config.ship_speed_meter_per_second = 5.14 + schedule = Schedule( + waypoints=[ + Waypoint(Location(0, 0), base_time), + Waypoint(Location(0.01, 0), base_time + timedelta(days=1)), + ] + ) + + result = simulate_schedule(projection, ship_config, schedule) + + assert isinstance(result, ScheduleOk) + + +def test_simulate_schedule_too_far() -> None: + """Test schedule with two waypoints that are very far away and cannot be reached in time is not OK.""" + base_time = datetime.strptime("2022-01-01T00:00:00", "%Y-%m-%dT%H:%M:%S") + + projection = pyproj.Geod(ellps="WGS84") + ship_config = ShipConfig.from_yaml("expedition_dir/ship_config.yaml") + schedule = Schedule( + waypoints=[ + Waypoint(Location(0, 0), base_time), + Waypoint(Location(1.0, 0), base_time + timedelta(minutes=1)), + ] + ) + + result = simulate_schedule(projection, ship_config, schedule) + + assert isinstance(result, ScheduleProblem) diff --git a/tests/instruments/test_adcp.py b/tests/instruments/test_adcp.py new file mode 100644 index 00000000..d119f3e2 --- /dev/null +++ b/tests/instruments/test_adcp.py @@ -0,0 +1,119 @@ +"""Test the simulation of ADCP instruments.""" + +import datetime + +import numpy as np +import py +import xarray as xr +from parcels import FieldSet + +from virtual_ship import Location, Spacetime +from virtual_ship.instruments.adcp import simulate_adcp + + +def test_simulate_adcp(tmpdir: py.path.LocalPath) -> None: + # maximum depth the ADCP can measure + MAX_DEPTH = -1000 # -1000 + # minimum depth the ADCP can measure + MIN_DEPTH = -5 # -5 + # How many samples to take in the complete range between max_depth and min_depth. + NUM_BINS = 40 + + # arbitrary time offset for the dummy fieldset + base_time = datetime.datetime.strptime("1950-01-01", "%Y-%m-%d") + + # where to sample + sample_points = [ + Spacetime(Location(1, 2), base_time + datetime.timedelta(seconds=0)), + Spacetime(Location(3, 4), base_time + datetime.timedelta(seconds=1)), + ] + + # expected observations at sample points + expected_obs = [ + { + "V": {"surface": 5, "max_depth": 6}, + "U": {"surface": 7, "max_depth": 8}, + "lat": sample_points[0].location.lat, + "lon": sample_points[0].location.lon, + "time": base_time + datetime.timedelta(seconds=0), + }, + { + "V": {"surface": 9, "max_depth": 10}, + "U": {"surface": 11, "max_depth": 12}, + "lat": sample_points[1].location.lat, + "lon": sample_points[1].location.lon, + "time": base_time + datetime.timedelta(seconds=1), + }, + ] + + # create fieldset based on the expected observations + # indices are time, depth, latitude, longitude + v = np.zeros((2, 2, 2, 2)) + v[0, 0, 0, 0] = expected_obs[0]["V"]["max_depth"] + v[0, 1, 0, 0] = expected_obs[0]["V"]["surface"] + v[1, 0, 1, 1] = expected_obs[1]["V"]["max_depth"] + v[1, 1, 1, 1] = expected_obs[1]["V"]["surface"] + + u = np.zeros((2, 2, 2, 2)) + u[0, 0, 0, 0] = expected_obs[0]["U"]["max_depth"] + u[0, 1, 0, 0] = expected_obs[0]["U"]["surface"] + u[1, 0, 1, 1] = expected_obs[1]["U"]["max_depth"] + u[1, 1, 1, 1] = expected_obs[1]["U"]["surface"] + + fieldset = FieldSet.from_data( + { + "V": v, + "U": u, + }, + { + "lat": np.array([expected_obs[0]["lat"], expected_obs[1]["lat"]]), + "lon": np.array([expected_obs[0]["lon"], expected_obs[1]["lon"]]), + "depth": np.array([MAX_DEPTH, MIN_DEPTH]), + "time": np.array( + [ + np.datetime64(expected_obs[0]["time"]), + np.datetime64(expected_obs[1]["time"]), + ] + ), + }, + ) + + # perform simulation + out_path = tmpdir.join("out.zarr") + + simulate_adcp( + fieldset=fieldset, + out_path=out_path, + max_depth=MAX_DEPTH, + min_depth=MIN_DEPTH, + num_bins=NUM_BINS, + sample_points=sample_points, + ) + + results = xr.open_zarr(out_path) + + # test if output is as expected + assert len(results.trajectory) == NUM_BINS + + # for every obs, check if the variables match the expected observations + # we only verify at the surface and max depth of the adcp, because in between is tricky + for traj, vert_loc in [ + (results.trajectory[0], "max_depth"), + (results.trajectory[-1], "surface"), + ]: + obs_all = results.sel(trajectory=traj).obs + assert len(obs_all) == len(sample_points) + for i, (obs_i, exp) in enumerate(zip(obs_all, expected_obs, strict=True)): + obs = results.sel(trajectory=traj, obs=obs_i) + for var in ["lat", "lon"]: + obs_value = obs[var].values.item() + exp_value = exp[var] + assert np.isclose( + obs_value, exp_value + ), f"Observation incorrect {vert_loc=} {obs_i=} {var=} {obs_value=} {exp_value=}." + for var in ["V", "U"]: + obs_value = obs[var].values.item() + exp_value = exp[var][vert_loc] + assert np.isclose( + obs_value, exp_value + ), f"Observation incorrect {vert_loc=} {i=} {var=} {obs_value=} {exp_value=}." diff --git a/tests/instruments/test_argo_float.py b/tests/instruments/test_argo_float.py new file mode 100644 index 00000000..b25e80e7 --- /dev/null +++ b/tests/instruments/test_argo_float.py @@ -0,0 +1,74 @@ +"""Test the simulation of Argo floats.""" + +from datetime import datetime, timedelta + +import numpy as np +import py +import xarray as xr +from parcels import FieldSet + +from virtual_ship import Location, Spacetime +from virtual_ship.instruments.argo_float import ArgoFloat, simulate_argo_floats + + +def test_simulate_argo_floats(tmpdir: py.path.LocalPath) -> None: + # arbitrary time offset for the dummy fieldset + base_time = datetime.strptime("1950-01-01", "%Y-%m-%d") + + DRIFT_DEPTH = -1000 + MAX_DEPTH = -2000 + VERTICAL_SPEED = -0.10 + CYCLE_DAYS = 10 + DRIFT_DAYS = 9 + + CONST_TEMPERATURE = 1.0 # constant temperature in fieldset + CONST_SALINITY = 1.0 # constant salinity in fieldset + + v = np.full((2, 2, 2), 1.0) + u = np.full((2, 2, 2), 1.0) + t = np.full((2, 2, 2), CONST_TEMPERATURE) + s = np.full((2, 2, 2), CONST_SALINITY) + + fieldset = FieldSet.from_data( + {"V": v, "U": u, "T": t, "S": s}, + { + "lon": np.array([0.0, 10.0]), + "lat": np.array([0.0, 10.0]), + "time": [ + np.datetime64(base_time + timedelta(seconds=0)), + np.datetime64(base_time + timedelta(hours=4)), + ], + }, + ) + + # argo floats to deploy + argo_floats = [ + ArgoFloat( + spacetime=Spacetime(location=Location(latitude=0, longitude=0), time=0), + min_depth=0.0, + max_depth=MAX_DEPTH, + drift_depth=DRIFT_DEPTH, + vertical_speed=VERTICAL_SPEED, + cycle_days=CYCLE_DAYS, + drift_days=DRIFT_DAYS, + ) + ] + + # perform simulation + out_path = tmpdir.join("out.zarr") + + simulate_argo_floats( + fieldset=fieldset, + out_path=out_path, + argo_floats=argo_floats, + outputdt=timedelta(minutes=5), + endtime=None, + ) + + # test if output is as expected + results = xr.open_zarr(out_path) + + # check the following variables are in the dataset + assert len(results.trajectory) == len(argo_floats) + for var in ["lon", "lat", "z", "temperature", "salinity"]: + assert var in results, f"Results don't contain {var}" diff --git a/tests/instruments/test_ctd.py b/tests/instruments/test_ctd.py new file mode 100644 index 00000000..eab53bf2 --- /dev/null +++ b/tests/instruments/test_ctd.py @@ -0,0 +1,138 @@ +""" +Test the simulation of CTD instruments. + +Fields are kept static over time and time component of CTD measurements is not tested tested because it's tricky to provide expected measurements. +""" + +import datetime +from datetime import timedelta + +import numpy as np +import py +import xarray as xr +from parcels import Field, FieldSet + +from virtual_ship import Location, Spacetime +from virtual_ship.instruments.ctd import CTD, simulate_ctd + + +def test_simulate_ctds(tmpdir: py.path.LocalPath) -> None: + # arbitrary time offset for the dummy fieldset + base_time = datetime.datetime.strptime("1950-01-01", "%Y-%m-%d") + + # where to cast CTDs + ctds = [ + CTD( + spacetime=Spacetime( + location=Location(latitude=0, longitude=1), + time=base_time + datetime.timedelta(hours=0), + ), + min_depth=0, + max_depth=float("-inf"), + ), + CTD( + spacetime=Spacetime( + location=Location(latitude=1, longitude=0), + time=base_time, + ), + min_depth=0, + max_depth=float("-inf"), + ), + ] + + # expected observations for ctds at surface and at maximum depth + ctd_exp = [ + { + "surface": { + "salinity": 5, + "temperature": 6, + "lat": ctds[0].spacetime.location.lat, + "lon": ctds[0].spacetime.location.lon, + }, + "maxdepth": { + "salinity": 7, + "temperature": 8, + "lat": ctds[0].spacetime.location.lat, + "lon": ctds[0].spacetime.location.lon, + }, + }, + { + "surface": { + "salinity": 5, + "temperature": 6, + "lat": ctds[1].spacetime.location.lat, + "lon": ctds[1].spacetime.location.lon, + }, + "maxdepth": { + "salinity": 7, + "temperature": 8, + "lat": ctds[1].spacetime.location.lat, + "lon": ctds[1].spacetime.location.lon, + }, + }, + ] + + # create fieldset based on the expected observations + # indices are time, depth, latitude, longitude + u = np.zeros((2, 2, 2, 2)) + v = np.zeros((2, 2, 2, 2)) + t = np.zeros((2, 2, 2, 2)) + s = np.zeros((2, 2, 2, 2)) + + t[:, 1, 0, 1] = ctd_exp[0]["surface"]["temperature"] + t[:, 0, 0, 1] = ctd_exp[0]["maxdepth"]["temperature"] + t[:, 1, 1, 0] = ctd_exp[1]["surface"]["temperature"] + t[:, 0, 1, 0] = ctd_exp[1]["maxdepth"]["temperature"] + + s[:, 1, 0, 1] = ctd_exp[0]["surface"]["salinity"] + s[:, 0, 0, 1] = ctd_exp[0]["maxdepth"]["salinity"] + s[:, 1, 1, 0] = ctd_exp[1]["surface"]["salinity"] + s[:, 0, 1, 0] = ctd_exp[1]["maxdepth"]["salinity"] + + fieldset = FieldSet.from_data( + {"V": v, "U": u, "T": t, "S": s}, + { + "time": [ + np.datetime64(base_time + datetime.timedelta(hours=0)), + np.datetime64(base_time + datetime.timedelta(hours=1)), + ], + "depth": [-1000, 0], + "lat": [0, 1], + "lon": [0, 1], + }, + ) + fieldset.add_field(Field("bathymetry", [-1000], lon=0, lat=0)) + + # perform simulation + out_path = tmpdir.join("out.zarr") + + simulate_ctd( + ctds=ctds, + fieldset=fieldset, + out_path=out_path, + outputdt=timedelta(seconds=10), + ) + + # test if output is as expected + results = xr.open_zarr(out_path) + + assert len(results.trajectory) == len(ctds) + + for ctd_i, (traj, exp_bothloc) in enumerate( + zip(results.trajectory, ctd_exp, strict=True) + ): + obs_surface = results.sel(trajectory=traj, obs=0) + min_index = np.argmin(results.sel(trajectory=traj)["z"].data) + obs_maxdepth = results.sel(trajectory=traj, obs=min_index) + + for obs, loc in [ + (obs_surface, "surface"), + (obs_maxdepth, "maxdepth"), + ]: + exp = exp_bothloc[loc] + for var in ["salinity", "temperature", "lat", "lon"]: + obs_value = obs[var].values.item() + exp_value = exp[var] + assert np.isclose( + obs_value, exp_value + ), f"Observation incorrect {ctd_i=} {loc=} {var=} {obs_value=} {exp_value=}." diff --git a/tests/instruments/test_drifter.py b/tests/instruments/test_drifter.py new file mode 100644 index 00000000..b7e03d6b --- /dev/null +++ b/tests/instruments/test_drifter.py @@ -0,0 +1,88 @@ +"""Test the simulation of drifters.""" + +import datetime +from datetime import timedelta + +import numpy as np +import py +import xarray as xr +from parcels import FieldSet + +from virtual_ship import Location, Spacetime +from virtual_ship.instruments.drifter import Drifter, simulate_drifters + + +def test_simulate_drifters(tmpdir: py.path.LocalPath) -> None: + # arbitrary time offset for the dummy fieldset + base_time = datetime.datetime.strptime("1950-01-01", "%Y-%m-%d") + + CONST_TEMPERATURE = 1.0 # constant temperature in fieldset + + v = np.full((2, 2, 2), 1.0) + u = np.full((2, 2, 2), 1.0) + t = np.full((2, 2, 2), CONST_TEMPERATURE) + + fieldset = FieldSet.from_data( + {"V": v, "U": u, "T": t}, + { + "lon": np.array([0.0, 10.0]), + "lat": np.array([0.0, 10.0]), + "time": [ + np.datetime64(base_time + datetime.timedelta(seconds=0)), + np.datetime64(base_time + datetime.timedelta(days=3)), + ], + }, + ) + + # drifters to deploy + drifters = [ + Drifter( + spacetime=Spacetime( + location=Location(latitude=0, longitude=0), + time=base_time + datetime.timedelta(days=0), + ), + depth=0.0, + lifetime=datetime.timedelta(hours=2), + ), + Drifter( + spacetime=Spacetime( + location=Location(latitude=1, longitude=1), + time=base_time + datetime.timedelta(hours=20), + ), + depth=0.0, + lifetime=None, + ), + ] + + # perform simulation + out_path = tmpdir.join("out.zarr") + + simulate_drifters( + fieldset=fieldset, + out_path=out_path, + drifters=drifters, + outputdt=timedelta(hours=1), + dt=timedelta(minutes=5), + endtime=None, + ) + + # test if output is as expected + results = xr.open_zarr(out_path) + + assert len(results.trajectory) == len(drifters) + + for drifter_i, traj in enumerate(results.trajectory): + # Check if drifters are moving + # lat, lon, should be increasing values (with the above positive VU fieldset) + dlat = np.diff(results.sel(trajectory=traj)["lat"].values) + assert np.all( + dlat[np.isfinite(dlat)] > 0 + ), f"Drifter is not moving over y {drifter_i=}" + dlon = np.diff(results.sel(trajectory=traj)["lon"].values) + assert np.all( + dlon[np.isfinite(dlon)] > 0 + ), f"Drifter is not moving over x {drifter_i=}" + temp = results.sel(trajectory=traj)["temperature"].values + assert np.all( + temp[np.isfinite(temp)] == CONST_TEMPERATURE + ), f"measured temperature does not match {drifter_i=}" diff --git a/tests/instruments/test_ship_underwater_st.py b/tests/instruments/test_ship_underwater_st.py new file mode 100644 index 00000000..54b8bdf0 --- /dev/null +++ b/tests/instruments/test_ship_underwater_st.py @@ -0,0 +1,103 @@ +"""Test the simulation of ship salinity temperature measurements.""" + +import datetime + +import numpy as np +import py +import xarray as xr +from parcels import FieldSet + +from virtual_ship import Location, Spacetime +from virtual_ship.instruments.ship_underwater_st import simulate_ship_underwater_st + + +def test_simulate_ship_underwater_st(tmpdir: py.path.LocalPath) -> None: + # depth at which the sampling will be done + DEPTH = -2 + + # arbitrary time offset for the dummy fieldset + base_time = datetime.datetime.strptime("1950-01-01", "%Y-%m-%d") + + # where to sample + sample_points = [ + Spacetime(Location(1, 2), base_time + datetime.timedelta(seconds=0)), + Spacetime(Location(3, 4), base_time + datetime.timedelta(seconds=1)), + ] + + # expected observations at sample points + expected_obs = [ + { + "S": 5, + "T": 6, + "lat": sample_points[0].location.lat, + "lon": sample_points[0].location.lon, + "time": base_time + datetime.timedelta(seconds=0), + }, + { + "S": 7, + "T": 8, + "lat": sample_points[1].location.lat, + "lon": sample_points[1].location.lon, + "time": base_time + datetime.timedelta(seconds=1), + }, + ] + + # create fieldset based on the expected observations + # indices are time, latitude, longitude + salinity = np.zeros((2, 2, 2)) + salinity[0, 0, 0] = expected_obs[0]["S"] + salinity[1, 1, 1] = expected_obs[1]["S"] + + temperature = np.zeros((2, 2, 2)) + temperature[0, 0, 0] = expected_obs[0]["T"] + temperature[1, 1, 1] = expected_obs[1]["T"] + + fieldset = FieldSet.from_data( + { + "V": np.zeros((2, 2, 2)), + "U": np.zeros((2, 2, 2)), + "S": salinity, + "T": temperature, + }, + { + "lat": np.array([expected_obs[0]["lat"], expected_obs[1]["lat"]]), + "lon": np.array([expected_obs[0]["lon"], expected_obs[1]["lon"]]), + "time": np.array( + [ + np.datetime64(expected_obs[0]["time"]), + np.datetime64(expected_obs[1]["time"]), + ] + ), + }, + ) + + # perform simulation + out_path = tmpdir.join("out.zarr") + + simulate_ship_underwater_st( + fieldset=fieldset, + out_path=out_path, + depth=DEPTH, + sample_points=sample_points, + ) + + # test if output is as expected + results = xr.open_zarr(out_path) + + assert len(results.trajectory) == 1 # expect a single trajectory + traj = results.trajectory.item() + assert len(results.sel(trajectory=traj).obs) == len( + sample_points + ) # expect as many obs as sample points + + # for every obs, check if the variables match the expected observations + for i, (obs_i, exp) in enumerate( + zip(results.sel(trajectory=traj).obs, expected_obs, strict=True) + ): + obs = results.sel(trajectory=traj, obs=obs_i) + for var in ["S", "T", "lat", "lon"]: + obs_value = obs[var].values.item() + exp_value = exp[var] + assert np.isclose( + obs_value, exp_value + ), f"Observation incorrect {i=} {var=} {obs_value=} {exp_value=}." diff --git a/tests/make_realistic/.gitignore b/tests/make_realistic/.gitignore new file mode 100644 index 00000000..bb473645 --- /dev/null +++ b/tests/make_realistic/.gitignore @@ -0,0 +1,2 @@ +!/ctd.zarr +!/adcp.zarr diff --git a/tests/make_realistic/adcp.zarr/.zattrs b/tests/make_realistic/adcp.zarr/.zattrs new file mode 100644 index 00000000..90d4d0b4 --- /dev/null +++ b/tests/make_realistic/adcp.zarr/.zattrs @@ -0,0 +1,8 @@ +{ + "Conventions": "CF-1.6/CF-1.7", + "feature_type": "trajectory", + "ncei_template_version": "NCEI_NetCDF_Trajectory_Template_v2.0", + "parcels_kernels": "NewParticle_sample_velocity", + "parcels_mesh": "spherical", + "parcels_version": "0.0.1-16-g947e7d0" +} \ No newline at end of file diff --git a/tests/make_realistic/adcp.zarr/.zgroup b/tests/make_realistic/adcp.zarr/.zgroup new file mode 100644 index 00000000..3b7daf22 --- /dev/null +++ b/tests/make_realistic/adcp.zarr/.zgroup @@ -0,0 +1,3 @@ +{ + "zarr_format": 2 +} \ No newline at end of file diff --git a/tests/make_realistic/adcp.zarr/.zmetadata b/tests/make_realistic/adcp.zarr/.zmetadata new file mode 100644 index 00000000..d1bf51f5 --- /dev/null +++ b/tests/make_realistic/adcp.zarr/.zmetadata @@ -0,0 +1,264 @@ +{ + "metadata": { + ".zattrs": { + "Conventions": "CF-1.6/CF-1.7", + "feature_type": "trajectory", + "ncei_template_version": "NCEI_NetCDF_Trajectory_Template_v2.0", + "parcels_kernels": "NewParticle_sample_velocity", + "parcels_mesh": "spherical", + "parcels_version": "0.0.1-16-g947e7d0" + }, + ".zgroup": { + "zarr_format": 2 + }, + "U/.zarray": { + "chunks": [ + 40, + 1 + ], + "compressor": { + "blocksize": 0, + "clevel": 5, + "cname": "lz4", + "id": "blosc", + "shuffle": 1 + }, + "dimension_separator": ".", + "dtype": " None: + # add noise and convert to CSV + file = adcp_make_realistic("adcp.zarr", out_dir=tmpdir, prefix="ADCP") + + # check if CSV is ok and can be loaded + with open(file, mode="r", newline="") as csvfile: + # ignore lines starting with #, we assume that's metadata or comments + reader = csv.reader(line for line in csvfile if not line.startswith("#")) + for _ in reader: + pass # iterate through the rows to check validity diff --git a/tests/make_realistic/test_ctd_make_realistic.py b/tests/make_realistic/test_ctd_make_realistic.py new file mode 100644 index 00000000..dc266d95 --- /dev/null +++ b/tests/make_realistic/test_ctd_make_realistic.py @@ -0,0 +1,13 @@ +import py +import seabird + +from virtual_ship.make_realistic import ctd_make_realistic + + +def test_ctd_make_realistic(tmpdir: py.path.LocalPath) -> None: + # add noise and convert to cnv + files = ctd_make_realistic("ctd.zarr", out_dir=tmpdir, prefix="CTD_") + + # check if cnv is ok and can be loaded + for file in files: + seabird.fCNV(file) diff --git a/virtual_ship/__init__.py b/virtual_ship/__init__.py new file mode 100644 index 00000000..6e74f1c8 --- /dev/null +++ b/virtual_ship/__init__.py @@ -0,0 +1,9 @@ +"""Code for the Virtual Ship Classroom, where Marine Scientists can combine Copernicus Marine Data with an OceanParcels ship to go on a virtual expedition.""" + +from .location import Location +from .spacetime import Spacetime + +__all__ = [ + "Location", + "Spacetime", +] diff --git a/virtual_ship/cli/__init__.py b/virtual_ship/cli/__init__.py new file mode 100644 index 00000000..d9f62d70 --- /dev/null +++ b/virtual_ship/cli/__init__.py @@ -0,0 +1 @@ +"""Command line interface tools.""" diff --git a/virtual_ship/cli/do_expedition.py b/virtual_ship/cli/do_expedition.py new file mode 100644 index 00000000..868a1aa3 --- /dev/null +++ b/virtual_ship/cli/do_expedition.py @@ -0,0 +1,30 @@ +""" +Command line interface tool for virtualship.expedition.do_expedition:do_expedition function. + +See --help for usage. +""" + +import argparse +from pathlib import Path + +from virtual_ship.expedition.do_expedition import do_expedition + + +def main() -> None: + """Entrypoint for the tool.""" + parser = argparse.ArgumentParser( + prog="do_expedition", + description="Perform an expedition based on a provided schedule.", + ) + parser.add_argument( + "dir", + type=str, + help="Directory for the expedition. This should contain all required configuration files, and the result will be saved here as well.", + ) + args = parser.parse_args() + + do_expedition(Path(args.dir)) + + +if __name__ == "__main__": + main() diff --git a/virtual_ship/expedition/__init__.py b/virtual_ship/expedition/__init__.py new file mode 100644 index 00000000..c755d33b --- /dev/null +++ b/virtual_ship/expedition/__init__.py @@ -0,0 +1,28 @@ +"""Everything for simulating an expedition.""" + +from .do_expedition import do_expedition +from .instrument_type import InstrumentType +from .schedule import Schedule +from .ship_config import ( + ADCPConfig, + ArgoFloatConfig, + CTDConfig, + DrifterConfig, + ShipConfig, + ShipUnderwaterSTConfig, +) +from .waypoint import Waypoint + +__all__ = [ + "ADCPConfig", + "ArgoFloatConfig", + "CTDConfig", + "DrifterConfig", + "InstrumentType", + "Schedule", + "ShipConfig", + "ShipUnderwaterSTConfig", + "Waypoint", + "do_expedition", + "instruments", +] diff --git a/virtual_ship/expedition/checkpoint.py b/virtual_ship/expedition/checkpoint.py new file mode 100644 index 00000000..d3bb08a4 --- /dev/null +++ b/virtual_ship/expedition/checkpoint.py @@ -0,0 +1,51 @@ +"""Checkpoint class.""" + +from __future__ import annotations + +from pathlib import Path + +import pydantic +import yaml + +from .instrument_type import InstrumentType +from .schedule import Schedule + + +class _YamlDumper(yaml.SafeDumper): + pass + + +_YamlDumper.add_representer( + InstrumentType, lambda dumper, data: dumper.represent_data(data.value) +) + + +class Checkpoint(pydantic.BaseModel): + """ + A checkpoint of schedule simulation. + + Copy of the schedule until where the simulation proceeded without troubles. + """ + + past_schedule: Schedule + + def to_yaml(self, file_path: str | Path) -> None: + """ + Write checkpoint to yaml file. + + :param file_path: Path to the file to write to. + """ + with open(file_path, "w") as file: + yaml.dump(self.model_dump(by_alias=True), file, Dumper=_YamlDumper) + + @classmethod + def from_yaml(cls, file_path: str | Path) -> Checkpoint: + """ + Load checkpoint from yaml file. + + :param file_path: Path to the file to load from. + :returns: The checkpoint. + """ + with open(file_path, "r") as file: + data = yaml.safe_load(file) + return Checkpoint(**data) diff --git a/virtual_ship/expedition/do_expedition.py b/virtual_ship/expedition/do_expedition.py new file mode 100644 index 00000000..0b43ee8e --- /dev/null +++ b/virtual_ship/expedition/do_expedition.py @@ -0,0 +1,150 @@ +"""do_expedition function.""" + +import os +import shutil +from pathlib import Path + +import pyproj + +from .checkpoint import Checkpoint +from .expedition_cost import expedition_cost +from .input_data import InputData +from .schedule import Schedule +from .ship_config import ShipConfig +from .simulate_measurements import simulate_measurements +from .simulate_schedule import ScheduleProblem, simulate_schedule +from .verify_schedule import verify_schedule + + +def do_expedition(expedition_dir: str | Path) -> None: + """ + Perform an expedition, providing terminal feedback and file output. + + :param expedition_dir: The base directory for the expedition. + """ + if isinstance(expedition_dir, str): + expedition_dir = Path(expedition_dir) + + # load ship configuration + ship_config = _get_ship_config(expedition_dir) + if ship_config is None: + return + + # load schedule + schedule = _get_schedule(expedition_dir) + if schedule is None: + return + + # load last checkpoint + checkpoint = _load_checkpoint(expedition_dir) + if checkpoint is None: + checkpoint = Checkpoint(past_schedule=Schedule(waypoints=[])) + + # verify that schedule and checkpoint match + if ( + not schedule.waypoints[: len(checkpoint.past_schedule.waypoints)] + == checkpoint.past_schedule.waypoints + ): + print( + "Past waypoints in schedule have been changed! Restore past schedule and only change future waypoints." + ) + return + + # projection used to sail between waypoints + projection = pyproj.Geod(ellps="WGS84") + + # load fieldsets + input_data = _load_input_data( + expedition_dir=expedition_dir, ship_config=ship_config + ) + + # verify schedule makes sense + verify_schedule(projection, ship_config, schedule, input_data) + + # simulate the schedule + schedule_results = simulate_schedule( + projection=projection, ship_config=ship_config, schedule=schedule + ) + if isinstance(schedule_results, ScheduleProblem): + print( + "Update your schedule and continue the expedition by running the tool again." + ) + _save_checkpoint( + Checkpoint( + past_schedule=Schedule( + waypoints=schedule.waypoints[: schedule_results.failed_waypoint_i] + ) + ), + expedition_dir, + ) + return + + # delete and create results directory + if os.path.exists(expedition_dir.joinpath("results")): + shutil.rmtree(expedition_dir.joinpath("results")) + os.makedirs(expedition_dir.joinpath("results")) + + # calculate expedition cost in US$ + assert ( + schedule.waypoints[0].time is not None + ), "First waypoint has no time. This should not be possible as it should have been verified before." + time_past = schedule_results.time - schedule.waypoints[0].time + cost = expedition_cost(schedule_results, time_past) + with open(expedition_dir.joinpath("results", "cost.txt"), "w") as file: + file.writelines(f"cost: {cost} US$") + print(f"This expedition took {time_past} and would have cost {cost:,.0f} US$.") + + # simulate measurements + print("Simulating measurements. This may take a while..") + simulate_measurements( + expedition_dir, + ship_config, + input_data, + schedule_results.measurements_to_simulate, + ) + print("Done simulating measurements.") + + print("Your expedition has concluded successfully!") + print("Your measurements can be found in the results directory.") + + +def _get_ship_config(expedition_dir: Path) -> ShipConfig | None: + file_path = expedition_dir.joinpath("ship_config.yaml") + try: + return ShipConfig.from_yaml(file_path) + except FileNotFoundError: + print(f'Schedule not found. Save it to "{file_path}".') + return None + + +def _load_input_data(expedition_dir: Path, ship_config: ShipConfig) -> InputData: + return InputData.load( + directory=expedition_dir.joinpath("input_data"), + load_adcp=ship_config.adcp_config is not None, + load_argo_float=ship_config.argo_float_config is not None, + load_ctd=ship_config.ctd_config is not None, + load_drifter=ship_config.drifter_config is not None, + load_ship_underwater_st=ship_config.ship_underwater_st_config is not None, + ) + + +def _get_schedule(expedition_dir: Path) -> Schedule | None: + file_path = expedition_dir.joinpath("schedule.yaml") + try: + return Schedule.from_yaml(file_path) + except FileNotFoundError: + print(f'Schedule not found. Save it to "{file_path}".') + return None + + +def _load_checkpoint(expedition_dir: Path) -> Checkpoint | None: + file_path = expedition_dir.joinpath("checkpoint.yaml") + try: + return Checkpoint.from_yaml(file_path) + except FileNotFoundError: + return None + + +def _save_checkpoint(checkpoint: Checkpoint, expedition_dir: Path) -> None: + file_path = expedition_dir.joinpath("checkpoint.yaml") + checkpoint.to_yaml(file_path) diff --git a/virtual_ship/expedition/expedition_cost.py b/virtual_ship/expedition/expedition_cost.py new file mode 100644 index 00000000..cab6ab7d --- /dev/null +++ b/virtual_ship/expedition/expedition_cost.py @@ -0,0 +1,27 @@ +"""expedition_cost function.""" + +from datetime import timedelta + +from .simulate_schedule import ScheduleOk + + +def expedition_cost(schedule_results: ScheduleOk, time_past: timedelta) -> float: + """ + Calculate the cost of the expedition in US$. + + :param schedule_results: Results from schedule simulation. + :param time_past: Time the expedition took. + :returns: The calculated cost of the expedition in US$. + """ + SHIP_COST_PER_DAY = 30000 + DRIFTER_DEPLOY_COST = 2500 + ARGO_DEPLOY_COST = 15000 + + ship_cost = SHIP_COST_PER_DAY / 24 * time_past.total_seconds() // 3600 + num_argos = len(schedule_results.measurements_to_simulate.argo_floats) + argo_cost = num_argos * ARGO_DEPLOY_COST + num_drifters = len(schedule_results.measurements_to_simulate.drifters) + drifter_cost = num_drifters * DRIFTER_DEPLOY_COST + + cost = ship_cost + argo_cost + drifter_cost + return cost diff --git a/virtual_ship/expedition/input_data.py b/virtual_ship/expedition/input_data.py new file mode 100644 index 00000000..7af9ef72 --- /dev/null +++ b/virtual_ship/expedition/input_data.py @@ -0,0 +1,177 @@ +"""InputData class.""" + +from __future__ import annotations + +from dataclasses import dataclass +from pathlib import Path + +from parcels import Field, FieldSet + + +@dataclass +class InputData: + """A collection of fieldsets that function as input data for simulation.""" + + adcp_fieldset: FieldSet | None + argo_float_fieldset: FieldSet | None + ctd_fieldset: FieldSet | None + drifter_fieldset: FieldSet | None + ship_underwater_st_fieldset: FieldSet | None + + @classmethod + def load( + cls, + directory: str | Path, + load_adcp: bool, + load_argo_float: bool, + load_ctd: bool, + load_drifter: bool, + load_ship_underwater_st: bool, + ) -> InputData: + """ + Create an instance of this class from netCDF files. + + For now this function makes a lot of assumption about file location and contents. + + :param directory: Base directory of the expedition. + :param load_adcp: Whether to load the ADCP fieldset. + :param load_argo_float: Whether to load the argo float fieldset. + :param load_ctd: Whether to load the CTD fieldset. + :param load_drifter: Whether to load the drifter fieldset. + :param load_ship_underwater_st: Whether to load the ship underwater ST fieldset. + :returns: An instance of this class with loaded fieldsets. + """ + if load_drifter: + drifter_fieldset = cls._load_drifter_fieldset(directory) + else: + drifter_fieldset = None + if load_argo_float: + argo_float_fieldset = cls._load_argo_float_fieldset(directory) + else: + argo_float_fieldset = None + if load_adcp or load_ctd or load_ship_underwater_st: + default_fieldset = cls._load_default_fieldset(directory) + if load_adcp: + adcp_fieldset = default_fieldset + else: + adcp_fieldset = None + if load_ctd: + ctd_fieldset = default_fieldset + else: + ctd_fieldset = None + if load_ship_underwater_st: + ship_underwater_st_fieldset = default_fieldset + else: + ship_underwater_st_fieldset = None + + return InputData( + adcp_fieldset=adcp_fieldset, + argo_float_fieldset=argo_float_fieldset, + ctd_fieldset=ctd_fieldset, + drifter_fieldset=drifter_fieldset, + ship_underwater_st_fieldset=ship_underwater_st_fieldset, + ) + + @classmethod + def _load_default_fieldset(cls, directory: str | Path) -> FieldSet: + filenames = { + "U": directory.joinpath("default_uv.nc"), + "V": directory.joinpath("default_uv.nc"), + "S": directory.joinpath("default_s.nc"), + "T": directory.joinpath("default_t.nc"), + } + variables = {"U": "uo", "V": "vo", "S": "so", "T": "thetao"} + dimensions = { + "lon": "longitude", + "lat": "latitude", + "time": "time", + "depth": "depth", + } + + # create the fieldset and set interpolation methods + fieldset = FieldSet.from_netcdf( + filenames, variables, dimensions, allow_time_extrapolation=True + ) + fieldset.T.interp_method = "linear_invdist_land_tracer" + fieldset.S.interp_method = "linear_invdist_land_tracer" + + # make depth negative + for g in fieldset.gridset.grids: + g.depth = -g.depth + + # add bathymetry data + bathymetry_file = directory.joinpath("bathymetry.nc") + bathymetry_variables = ("bathymetry", "deptho") + bathymetry_dimensions = {"lon": "longitude", "lat": "latitude"} + bathymetry_field = Field.from_netcdf( + bathymetry_file, bathymetry_variables, bathymetry_dimensions + ) + # make depth negative + bathymetry_field.data = -bathymetry_field.data + fieldset.add_field(bathymetry_field) + + # read in data already + fieldset.computeTimeChunk(0, 1) + + return fieldset + + @classmethod + def _load_drifter_fieldset(cls, directory: str | Path) -> FieldSet: + filenames = { + "U": directory.joinpath("drifter_uv.nc"), + "V": directory.joinpath("drifter_uv.nc"), + "T": directory.joinpath("drifter_t.nc"), + } + variables = {"U": "uo", "V": "vo", "T": "thetao"} + dimensions = { + "lon": "longitude", + "lat": "latitude", + "time": "time", + "depth": "depth", + } + + fieldset = FieldSet.from_netcdf( + filenames, variables, dimensions, allow_time_extrapolation=False + ) + fieldset.T.interp_method = "linear_invdist_land_tracer" + + # make depth negative + for g in fieldset.gridset.grids: + g.depth = -g.depth + + # read in data already + fieldset.computeTimeChunk(0, 1) + + return fieldset + + @classmethod + def _load_argo_float_fieldset(cls, directory: str | Path) -> FieldSet: + filenames = { + "U": directory.joinpath("argo_float_uv.nc"), + "V": directory.joinpath("argo_float_uv.nc"), + "S": directory.joinpath("argo_float_s.nc"), + "T": directory.joinpath("argo_float_t.nc"), + } + variables = {"U": "uo", "V": "vo", "S": "so", "T": "thetao"} + dimensions = { + "lon": "longitude", + "lat": "latitude", + "time": "time", + "depth": "depth", + } + + fieldset = FieldSet.from_netcdf( + filenames, variables, dimensions, allow_time_extrapolation=False + ) + fieldset.T.interp_method = "linear_invdist_land_tracer" + fieldset.S.interp_method = "linear_invdist_land_tracer" + + # make depth negative + for g in fieldset.gridset.grids: + if max(g.depth) > 0: + g.depth = -g.depth + + # read in data already + fieldset.computeTimeChunk(0, 1) + + return fieldset diff --git a/virtual_ship/expedition/instrument_type.py b/virtual_ship/expedition/instrument_type.py new file mode 100644 index 00000000..556d8464 --- /dev/null +++ b/virtual_ship/expedition/instrument_type.py @@ -0,0 +1,11 @@ +"""InstrumentType Enum.""" + +from enum import Enum + + +class InstrumentType(Enum): + """Types of instruments.""" + + CTD = "CTD" + DRIFTER = "DRIFTER" + ARGO_FLOAT = "ARGO_FLOAT" diff --git a/virtual_ship/expedition/schedule.py b/virtual_ship/expedition/schedule.py new file mode 100644 index 00000000..a92ba55b --- /dev/null +++ b/virtual_ship/expedition/schedule.py @@ -0,0 +1,44 @@ +"""Schedule class.""" + +from __future__ import annotations + +from pathlib import Path + +import pydantic +import yaml + +from .waypoint import Waypoint + + +class Schedule(pydantic.BaseModel): + """Schedule of the virtual ship.""" + + waypoints: list[Waypoint] + + model_config = pydantic.ConfigDict(extra="forbid") + + def to_yaml(self, file_path: str | Path) -> None: + """ + Write schedule to yaml file. + + :param file_path: Path to the file to write to. + """ + with open(file_path, "w") as file: + yaml.dump( + self.model_dump( + by_alias=True, + ), + file, + ) + + @classmethod + def from_yaml(cls, file_path: str | Path) -> Schedule: + """ + Load schedule from yaml file. + + :param file_path: Path to the file to load from. + :returns: The schedule. + """ + with open(file_path, "r") as file: + data = yaml.safe_load(file) + return Schedule(**data) diff --git a/virtual_ship/expedition/ship_config.py b/virtual_ship/expedition/ship_config.py new file mode 100644 index 00000000..8e4564fc --- /dev/null +++ b/virtual_ship/expedition/ship_config.py @@ -0,0 +1,156 @@ +"""ShipConfig and supporting classes.""" + +from __future__ import annotations + +from datetime import timedelta +from pathlib import Path + +import pydantic +import yaml + + +class ArgoFloatConfig(pydantic.BaseModel): + """Configuration for argos floats.""" + + min_depth_meter: float = pydantic.Field(le=0.0) + max_depth_meter: float = pydantic.Field(le=0.0) + drift_depth_meter: float = pydantic.Field(le=0.0) + vertical_speed_meter_per_second: float = pydantic.Field(lt=0.0) + cycle_days: float = pydantic.Field(gt=0.0) + drift_days: float = pydantic.Field(gt=0.0) + + +class ADCPConfig(pydantic.BaseModel): + """Configuration for ADCP instrument.""" + + max_depth_meter: float = pydantic.Field(le=0.0) + num_bins: int = pydantic.Field(gt=0.0) + period: timedelta = pydantic.Field( + serialization_alias="period_minutes", + validation_alias="period_minutes", + gt=timedelta(), + ) + + model_config = pydantic.ConfigDict(populate_by_name=True) + + @pydantic.field_serializer("period") + def _serialize_period(self, value: timedelta, _info): + return value.total_seconds() / 60.0 + + +class CTDConfig(pydantic.BaseModel): + """Configuration for CTD instrument.""" + + stationkeeping_time: timedelta = pydantic.Field( + serialization_alias="stationkeeping_time_minutes", + validation_alias="stationkeeping_time_minutes", + gt=timedelta(), + ) + min_depth_meter: float = pydantic.Field(le=0.0) + max_depth_meter: float = pydantic.Field(le=0.0) + + model_config = pydantic.ConfigDict(populate_by_name=True) + + @pydantic.field_serializer("stationkeeping_time") + def _serialize_stationkeeping_time(self, value: timedelta, _info): + return value.total_seconds() / 60.0 + + +class ShipUnderwaterSTConfig(pydantic.BaseModel): + """Configuration for underwater ST.""" + + period: timedelta = pydantic.Field( + serialization_alias="period_minutes", + validation_alias="period_minutes", + gt=timedelta(), + ) + + model_config = pydantic.ConfigDict(populate_by_name=True) + + @pydantic.field_serializer("period") + def _serialize_period(self, value: timedelta, _info): + return value.total_seconds() / 60.0 + + +class DrifterConfig(pydantic.BaseModel): + """Configuration for drifters.""" + + depth_meter: float = pydantic.Field(le=0.0) + lifetime: timedelta = pydantic.Field( + serialization_alias="lifetime_minutes", + validation_alias="lifetime_minutes", + gt=timedelta(), + ) + + model_config = pydantic.ConfigDict(populate_by_name=True) + + @pydantic.field_serializer("lifetime") + def _serialize_lifetime(self, value: timedelta, _info): + return value.total_seconds() / 60.0 + + +class ShipConfig(pydantic.BaseModel): + """Configuration of the virtual ship.""" + + ship_speed_meter_per_second: float = pydantic.Field(gt=0.0) + """ + Velocity of the ship in meters per second. + """ + + argo_float_config: ArgoFloatConfig | None = None + """ + Argo float configuration. + + If None, no argo floats can be deployed. + """ + + adcp_config: ADCPConfig | None = None + """ + ADCP configuration. + + If None, no ADCP measurements will be performed. + """ + + ctd_config: CTDConfig | None = None + """ + CTD configuration. + + If None, no CTDs can be cast. + """ + + ship_underwater_st_config: ShipUnderwaterSTConfig | None = None + """ + Ship underwater salinity temperature measurementconfiguration. + + If None, no ST measurements will be performed. + """ + + drifter_config: DrifterConfig | None = None + """ + Drifter configuration. + + If None, no drifters can be deployed. + """ + + model_config = pydantic.ConfigDict(extra="forbid") + + def to_yaml(self, file_path: str | Path) -> None: + """ + Write config to yaml file. + + :param file_path: Path to the file to write to. + """ + with open(file_path, "w") as file: + yaml.dump(self.model_dump(by_alias=True), file) + + @classmethod + def from_yaml(cls, file_path: str | Path) -> ShipConfig: + """ + Load config from yaml file. + + :param file_path: Path to the file to load from. + :returns: The config. + """ + with open(file_path, "r") as file: + data = yaml.safe_load(file) + return ShipConfig(**data) diff --git a/virtual_ship/expedition/simulate_measurements.py b/virtual_ship/expedition/simulate_measurements.py new file mode 100644 index 00000000..7ff7868f --- /dev/null +++ b/virtual_ship/expedition/simulate_measurements.py @@ -0,0 +1,104 @@ +"""simulate_measurements function.""" + +from datetime import timedelta +from pathlib import Path + +from ..instruments.adcp import simulate_adcp +from ..instruments.argo_float import simulate_argo_floats +from ..instruments.ctd import simulate_ctd +from ..instruments.drifter import simulate_drifters +from ..instruments.ship_underwater_st import simulate_ship_underwater_st +from .input_data import InputData +from .ship_config import ShipConfig +from .simulate_schedule import MeasurementsToSimulate + + +def simulate_measurements( + expedition_dir: str | Path, + ship_config: ShipConfig, + input_data: InputData, + measurements: MeasurementsToSimulate, +) -> None: + """ + Simulate measurements using Parcels. + + Saves everything in expedition_dir/results. + + :param expedition_dir: Base directory of the expedition. + :param ship_config: Ship configuration. + :param input_data: Input data for simulation. + :param measurements: The measurements to simulate. + :raises RuntimeError: In case fieldsets of configuration is not provided. Make sure to check this before calling this function. + """ + if isinstance(expedition_dir, str): + expedition_dir = Path(expedition_dir) + + if len(measurements.ship_underwater_sts) > 0: + print("Simulating onboard salinity and temperature measurements.") + if ship_config.ship_underwater_st_config is None: + raise RuntimeError("No configuration for ship underwater ST provided.") + if input_data.ship_underwater_st_fieldset is None: + raise RuntimeError("No fieldset for ship underwater ST provided.") + simulate_ship_underwater_st( + fieldset=input_data.ship_underwater_st_fieldset, + out_path=expedition_dir.joinpath("results", "ship_underwater_st.zarr"), + depth=-2, + sample_points=measurements.ship_underwater_sts, + ) + + if len(measurements.adcps) > 0: + print("Simulating onboard ADCP.") + if ship_config.adcp_config is None: + raise RuntimeError("No configuration for ADCP provided.") + if input_data.adcp_fieldset is None: + raise RuntimeError("No fieldset for ADCP provided.") + simulate_adcp( + fieldset=input_data.adcp_fieldset, + out_path=expedition_dir.joinpath("results", "adcp.zarr"), + max_depth=ship_config.adcp_config.max_depth_meter, + min_depth=-5, + num_bins=ship_config.adcp_config.num_bins, + sample_points=measurements.adcps, + ) + + if len(measurements.ctds) > 0: + print("Simulating CTD casts.") + if ship_config.ctd_config is None: + raise RuntimeError("No configuration for CTD provided.") + if input_data.ctd_fieldset is None: + raise RuntimeError("No fieldset for CTD provided.") + simulate_ctd( + out_path=expedition_dir.joinpath("results", "ctd.zarr"), + fieldset=input_data.ctd_fieldset, + ctds=measurements.ctds, + outputdt=timedelta(seconds=10), + ) + + if len(measurements.drifters) > 0: + print("Simulating drifters") + if ship_config.drifter_config is None: + raise RuntimeError("No configuration for drifters provided.") + if input_data.drifter_fieldset is None: + raise RuntimeError("No fieldset for drifters provided.") + simulate_drifters( + out_path=expedition_dir.joinpath("results", "drifters.zarr"), + fieldset=input_data.drifter_fieldset, + drifters=measurements.drifters, + outputdt=timedelta(hours=5), + dt=timedelta(minutes=5), + endtime=None, + ) + + if len(measurements.argo_floats) > 0: + print("Simulating argo floats") + if ship_config.argo_float_config is None: + raise RuntimeError("No configuration for argo floats provided.") + if input_data.argo_float_fieldset is None: + raise RuntimeError("No fieldset for argo floats provided.") + simulate_argo_floats( + out_path=expedition_dir.joinpath("results", "argo_floats.zarr"), + argo_floats=measurements.argo_floats, + fieldset=input_data.argo_float_fieldset, + outputdt=timedelta(minutes=5), + endtime=None, + ) diff --git a/virtual_ship/expedition/simulate_schedule.py b/virtual_ship/expedition/simulate_schedule.py new file mode 100644 index 00000000..85df8696 --- /dev/null +++ b/virtual_ship/expedition/simulate_schedule.py @@ -0,0 +1,264 @@ +"""simulate_schedule function and supporting classes.""" + +from __future__ import annotations + +from dataclasses import dataclass, field +from datetime import datetime, timedelta + +import pyproj + +from ..instruments.argo_float import ArgoFloat +from ..instruments.ctd import CTD +from ..instruments.drifter import Drifter +from ..location import Location +from ..spacetime import Spacetime +from .instrument_type import InstrumentType +from .schedule import Schedule +from .ship_config import ShipConfig +from .waypoint import Waypoint + + +@dataclass +class ScheduleOk: + """Result of schedule that could be completed.""" + + time: datetime + measurements_to_simulate: MeasurementsToSimulate + + +@dataclass +class ScheduleProblem: + """Result of schedule that could not be fully completed.""" + + time: datetime + failed_waypoint_i: int + + +@dataclass +class MeasurementsToSimulate: + """The measurements to simulate, as concluded from schedule simulation.""" + + adcps: list[Spacetime] = field(default_factory=list, init=False) + ship_underwater_sts: list[Spacetime] = field(default_factory=list, init=False) + argo_floats: list[ArgoFloat] = field(default_factory=list, init=False) + drifters: list[Drifter] = field(default_factory=list, init=False) + ctds: list[CTD] = field(default_factory=list, init=False) + + +def simulate_schedule( + projection: pyproj.Geod, ship_config: ShipConfig, schedule: Schedule +) -> ScheduleOk | ScheduleProblem: + """ + Simulate a schedule. + + :param projection: The projection to use for sailing. + :param ship_config: Ship configuration. + :param schedule: The schedule to simulate. + :returns: Either the results of a successfully simulated schedule, or information on where the schedule became infeasible. + """ + return _ScheduleSimulator(projection, ship_config, schedule).simulate() + + +class _ScheduleSimulator: + _projection: pyproj.Geod + _ship_config: ShipConfig + _schedule: Schedule + + _time: datetime + """Current time.""" + _location: Location + """Current ship location.""" + + _measurements_to_simulate: MeasurementsToSimulate + + _next_adcp_time: datetime + """Next moment ADCP measurement will be done.""" + _next_ship_underwater_st_time: datetime + """Next moment ship underwater ST measurement will be done.""" + + def __init__( + self, projection: pyproj.Geod, ship_config: ShipConfig, schedule: Schedule + ) -> None: + self._projection = projection + self._ship_config = ship_config + self._schedule = schedule + + assert ( + self._schedule.waypoints[0].time is not None + ), "First waypoint must have a time. This should have been verified before calling this function." + self._time = schedule.waypoints[0].time + self._location = schedule.waypoints[0].location + + self._measurements_to_simulate = MeasurementsToSimulate() + + self._next_adcp_time = self._time + self._next_ship_underwater_st_time = self._time + + def simulate(self) -> ScheduleOk | ScheduleProblem: + for wp_i, waypoint in enumerate(self._schedule.waypoints): + # sail towards waypoint + self._progress_time_traveling_towards(waypoint.location) + + # check if waypoint was reached in time + if waypoint.time is not None and self._time > waypoint.time: + print( + f"Waypoint {wp_i} could not be reached in time. Current time: {self._time}. Waypoint time: {waypoint.time}." + ) + return ScheduleProblem(self._time, wp_i) + + # note measurements made at waypoint + time_passed = self._make_measurements(waypoint) + + # wait while measurements are being done + self._progress_time_stationary(time_passed) + return ScheduleOk(self._time, self._measurements_to_simulate) + + def _progress_time_traveling_towards(self, location: Location) -> None: + geodinv: tuple[float, float, float] = self._projection.inv( + lons1=self._location.lon, + lats1=self._location.lat, + lons2=location.lon, + lats2=location.lat, + ) + azimuth1 = geodinv[0] + distance_to_next_waypoint = geodinv[2] + time_to_reach = timedelta( + seconds=distance_to_next_waypoint + / self._ship_config.ship_speed_meter_per_second + ) + end_time = self._time + time_to_reach + + # note all ADCP measurements + if self._ship_config.adcp_config is not None: + location = self._location + time = self._time + while self._next_adcp_time <= end_time: + time_to_sail = self._next_adcp_time - time + distance_to_move = ( + self._ship_config.ship_speed_meter_per_second + * time_to_sail.total_seconds() + ) + geodfwd: tuple[float, float, float] = self._projection.fwd( + lons=location.lon, + lats=location.lat, + az=azimuth1, + dist=distance_to_move, + ) + location = Location(latitude=geodfwd[1], longitude=geodfwd[0]) + time = time + time_to_sail + + self._measurements_to_simulate.adcps.append( + Spacetime(location=location, time=time) + ) + + self._next_adcp_time = ( + self._next_adcp_time + self._ship_config.adcp_config.period + ) + + # note all ship underwater ST measurements + if self._ship_config.ship_underwater_st_config is not None: + location = self._location + time = self._time + while self._next_ship_underwater_st_time <= end_time: + time_to_sail = self._next_ship_underwater_st_time - time + distance_to_move = ( + self._ship_config.ship_speed_meter_per_second + * time_to_sail.total_seconds() + ) + geodfwd: tuple[float, float, float] = self._projection.fwd( + lons=location.lon, + lats=location.lat, + az=azimuth1, + dist=distance_to_move, + ) + location = Location(latitude=geodfwd[1], longitude=geodfwd[0]) + time = time + time_to_sail + + self._measurements_to_simulate.ship_underwater_sts.append( + Spacetime(location=location, time=time) + ) + + self._next_ship_underwater_st_time = ( + self._next_ship_underwater_st_time + + self._ship_config.ship_underwater_st_config.period + ) + + self._time = end_time + self._location = location + + def _progress_time_stationary(self, time_passed: timedelta) -> None: + end_time = self._time + time_passed + + # note all ADCP measurements + if self._ship_config.adcp_config is not None: + while self._next_adcp_time <= end_time: + self._measurements_to_simulate.adcps.append( + Spacetime(self._location, self._next_adcp_time) + ) + self._next_adcp_time = ( + self._next_adcp_time + self._ship_config.adcp_config.period + ) + + # note all ship underwater ST measurements + if self._ship_config.ship_underwater_st_config is not None: + while self._next_ship_underwater_st_time <= end_time: + self._measurements_to_simulate.ship_underwater_sts.append( + Spacetime(self._location, self._next_ship_underwater_st_time) + ) + self._next_ship_underwater_st_time = ( + self._next_ship_underwater_st_time + + self._ship_config.ship_underwater_st_config.period + ) + + self._time = end_time + + def _make_measurements(self, waypoint: Waypoint) -> timedelta: + # if there are no instruments, there is no time cost + if waypoint.instrument is None: + return timedelta() + + # make instruments a list even if it's only a single one + instruments = ( + waypoint.instrument + if isinstance(waypoint.instrument, list) + else [waypoint.instrument] + ) + + # time costs of each measurement + time_costs = [timedelta()] + + for instrument in instruments: + if instrument is InstrumentType.ARGO_FLOAT: + self._measurements_to_simulate.argo_floats.append( + ArgoFloat( + spacetime=Spacetime(self._location, self._time), + min_depth=self._ship_config.argo_float_config.min_depth_meter, + max_depth=self._ship_config.argo_float_config.max_depth_meter, + drift_depth=self._ship_config.argo_float_config.drift_depth_meter, + vertical_speed=self._ship_config.argo_float_config.vertical_speed_meter_per_second, + cycle_days=self._ship_config.argo_float_config.cycle_days, + drift_days=self._ship_config.argo_float_config.drift_days, + ) + ) + elif instrument is InstrumentType.CTD: + self._measurements_to_simulate.ctds.append( + CTD( + spacetime=Spacetime(self._location, self._time), + min_depth=self._ship_config.ctd_config.min_depth_meter, + max_depth=self._ship_config.ctd_config.max_depth_meter, + ) + ) + time_costs.append(timedelta(minutes=20)) + elif instrument is InstrumentType.DRIFTER: + self._measurements_to_simulate.drifters.append( + Drifter( + spacetime=Spacetime(self._location, self._time), + depth=self._ship_config.drifter_config.depth_meter, + lifetime=self._ship_config.drifter_config.lifetime, + ) + ) + else: + raise NotImplementedError("Instrument type not supported.") + + # measurements are done in parallel, so return time of longest one + return max(time_costs) diff --git a/virtual_ship/expedition/verify_schedule.py b/virtual_ship/expedition/verify_schedule.py new file mode 100644 index 00000000..55c34587 --- /dev/null +++ b/virtual_ship/expedition/verify_schedule.py @@ -0,0 +1,166 @@ +"""verify_schedule function and supporting classes.""" + +from datetime import timedelta + +import pyproj +from parcels import FieldSet + +from .input_data import InputData +from .instrument_type import InstrumentType +from .schedule import Schedule +from .ship_config import ShipConfig +from .waypoint import Waypoint + + +def verify_schedule( + projection: pyproj.Geod, + ship_config: ShipConfig, + schedule: Schedule, + input_data: InputData, +) -> None: + """ + Verify waypoints are ordered by time, first waypoint has a start time, and that schedule is feasible in terms of time if no unexpected events happen. + + :param projection: projection used to sail between waypoints. + :param ship_config: The cruise ship_configuration. + :param schedule: The schedule to verify. + :param input_data: Fieldsets that can be used to check for zero UV condition (is waypoint on land). + :raises PlanningError: If waypoints are not feasible or incorrect. + :raises NotImplementedError: If instrument is in schedule that is not implememented. + """ + if len(schedule.waypoints) == 0: + raise PlanningError("At least one waypoint must be provided.") + + # check first waypoint has a time + if schedule.waypoints[0].time is None: + raise PlanningError("First waypoint must have a specified time.") + + # check waypoint times are in ascending order + timed_waypoints = [wp for wp in schedule.waypoints if wp.time is not None] + if not all( + [ + next.time >= cur.time + for cur, next in zip(timed_waypoints, timed_waypoints[1:]) + ] + ): + raise PlanningError( + "Each waypoint should be timed after all previous waypoints" + ) + + # check if all waypoints are in water + # this is done by picking an arbitrary provided fieldset and checking if UV is not zero + + print("Verifying all waypoints are on water..") + + # get all available fieldsets + available_fieldsets = [ + fs + for fs in [ + input_data.adcp_fieldset, + input_data.argo_float_fieldset, + input_data.ctd_fieldset, + input_data.drifter_fieldset, + input_data.ship_underwater_st_fieldset, + ] + if fs is not None + ] + + # check if there are any fieldsets, else its an error + if len(available_fieldsets) == 0: + print( + "Cannot verify because no fieldsets have been loaded. This is probably because you are not using any instruments in your schedule. This is not a problem, but carefully check your waypoint locations manually.." + ) + + else: + # pick any + fieldset = available_fieldsets[0] + # get waypoints with 0 UV + land_waypoints = [ + (wp_i, wp) + for wp_i, wp in enumerate(schedule.waypoints) + if _is_on_land_zero_uv(fieldset, wp) + ] + # raise an error if there are any + if len(land_waypoints) > 0: + raise PlanningError( + f"The following waypoints are on land: {['#' + str(wp_i) + ' ' + str(wp) for (wp_i, wp) in land_waypoints]}" + ) + print("Good, all waypoints are on water.") + + # check that ship will arrive on time at each waypoint (in case no unexpected event happen) + time = schedule.waypoints[0].time + for wp_i, (wp, wp_next) in enumerate( + zip(schedule.waypoints, schedule.waypoints[1:]) + ): + if wp.instrument is InstrumentType.CTD: + time += timedelta(minutes=20) + + geodinv: tuple[float, float, float] = projection.inv( + wp.location.lon, wp.location.lat, wp_next.location.lon, wp_next.location.lat + ) + distance = geodinv[2] + + time_to_reach = timedelta( + seconds=distance / ship_config.ship_speed_meter_per_second + ) + arrival_time = time + time_to_reach + + if wp_next.time is None: + time = arrival_time + elif arrival_time > wp_next.time: + raise PlanningError( + f"Waypoint planning is not valid: would arrive too late at a waypoint number {wp_i + 1}. location: {wp_next.location} time: {wp_next.time} instrument: {wp_next.instrument}" + ) + else: + time = wp_next.time + + # verify instruments in schedule have configuration + for wp in schedule.waypoints: + if wp.instrument is not None: + for instrument in ( + wp.instrument if isinstance(wp.instrument, list) else [wp.instrument] + ): + if instrument not in InstrumentType: + raise NotImplementedError("Instrument not supported.") + + if ( + instrument == InstrumentType.ARGO_FLOAT + and ship_config.argo_float_config is None + ): + raise PlanningError( + "Planning has waypoint with Argo float instrument, but configuration does not configure Argo floats." + ) + if instrument == InstrumentType.CTD and ship_config.ctd_config is None: + raise PlanningError( + "Planning has waypoint with CTD instrument, but configuration does not configure CTDs." + ) + if ( + instrument == InstrumentType.DRIFTER + and ship_config.drifter_config is None + ): + raise PlanningError( + "Planning has waypoint with drifter instrument, but configuration does not configure drifters." + ) + + +class PlanningError(RuntimeError): + """An error in the schedule.""" + + pass + + +def _is_on_land_zero_uv(fieldset: FieldSet, waypoint: Waypoint) -> bool: + """ + Check if waypoint is on land by assuming zero velocity means land. + + :param fieldset: The fieldset to sample the velocity from. + :param waypoint: The waypoint to check. + :returns: If the waypoint is on land. + """ + return fieldset.UV.eval( + 0, + fieldset.gridset.grids[0].depth[0], + waypoint.location.lat, + waypoint.location.lon, + applyConversion=False, + ) == (0.0, 0.0) diff --git a/virtual_ship/expedition/waypoint.py b/virtual_ship/expedition/waypoint.py new file mode 100644 index 00000000..85e99181 --- /dev/null +++ b/virtual_ship/expedition/waypoint.py @@ -0,0 +1,16 @@ +"""Waypoint class.""" + +from dataclasses import dataclass +from datetime import datetime + +from ..location import Location +from .instrument_type import InstrumentType + + +@dataclass +class Waypoint: + """A Waypoint to sail to with an optional time and an optional instrument.""" + + location: Location + time: datetime | None = None + instrument: InstrumentType | list[InstrumentType] | None = None diff --git a/virtual_ship/instruments/__init__.py b/virtual_ship/instruments/__init__.py new file mode 100644 index 00000000..edcaa8c1 --- /dev/null +++ b/virtual_ship/instruments/__init__.py @@ -0,0 +1,5 @@ +"""Measurement instrument that can be used with Parcels.""" + +from . import adcp, argo_float, ctd, drifter, ship_underwater_st + +__all__ = ["adcp", "argo_float", "ctd", "drifter", "ship_underwater_st"] diff --git a/virtual_ship/instruments/adcp.py b/virtual_ship/instruments/adcp.py new file mode 100644 index 00000000..bca4ab94 --- /dev/null +++ b/virtual_ship/instruments/adcp.py @@ -0,0 +1,77 @@ +"""ADCP instrument.""" + +import numpy as np +import py +from parcels import FieldSet, ParticleSet, ScipyParticle, Variable + +from ..spacetime import Spacetime + +# we specifically use ScipyParticle because we have many small calls to execute +# there is some overhead with JITParticle and this ends up being significantly faster +_ADCPParticle = ScipyParticle.add_variables( + [ + Variable("U", dtype=np.float32, initial=np.nan), + Variable("V", dtype=np.float32, initial=np.nan), + ] +) + + +def _sample_velocity(particle, fieldset, time): + particle.U, particle.V = fieldset.UV.eval( + time, particle.depth, particle.lat, particle.lon, applyConversion=False + ) + + +def simulate_adcp( + fieldset: FieldSet, + out_path: str | py.path.LocalPath, + max_depth: float, + min_depth: float, + num_bins: int, + sample_points: list[Spacetime], +) -> None: + """ + Use Parcels to simulate an ADCP in a fieldset. + + :param fieldset: The fieldset to simulate the ADCP in. + :param out_path: The path to write the results to. + :param max_depth: Maximum depth the ADCP can measure. + :param min_depth: Minimum depth the ADCP can measure. + :param num_bins: How many samples to take in the complete range between max_depth and min_depth. + :param sample_points: The places and times to sample at. + """ + sample_points.sort(key=lambda p: p.time) + + bins = np.linspace(max_depth, min_depth, num_bins) + num_particles = len(bins) + particleset = ParticleSet.from_list( + fieldset=fieldset, + pclass=_ADCPParticle, + lon=np.full( + num_particles, 0.0 + ), # initial lat/lon are irrelevant and will be overruled later. + lat=np.full(num_particles, 0.0), + depth=bins, + time=0, # same for time + ) + + # define output file for the simulation + # outputdt set to infinite as we just want to write at the end of every call to 'execute' + out_file = particleset.ParticleFile(name=out_path, outputdt=np.inf) + + for point in sample_points: + particleset.lon_nextloop[:] = point.location.lon + particleset.lat_nextloop[:] = point.location.lat + particleset.time_nextloop[:] = fieldset.time_origin.reltime( + np.datetime64(point.time) + ) + + # perform one step using the particleset + # dt and runtime are set so exactly one step is made. + particleset.execute( + [_sample_velocity], + dt=1, + runtime=1, + verbose_progress=False, + output_file=out_file, + ) diff --git a/virtual_ship/instruments/argo_float.py b/virtual_ship/instruments/argo_float.py new file mode 100644 index 00000000..ad4a4871 --- /dev/null +++ b/virtual_ship/instruments/argo_float.py @@ -0,0 +1,184 @@ +"""Argo float instrument.""" + +import math +from dataclasses import dataclass +from datetime import datetime, timedelta + +import numpy as np +import py +from parcels import ( + AdvectionRK4, + FieldSet, + JITParticle, + ParticleSet, + StatusCode, + Variable, +) + +from ..spacetime import Spacetime + + +@dataclass +class ArgoFloat: + """Configuration for a single Argo float.""" + + spacetime: Spacetime + min_depth: float + max_depth: float + drift_depth: float + vertical_speed: float + cycle_days: float + drift_days: float + + +_ArgoParticle = JITParticle.add_variables( + [ + Variable("cycle_phase", dtype=np.int32, initial=0.0), + Variable("cycle_age", dtype=np.float32, initial=0.0), + Variable("drift_age", dtype=np.float32, initial=0.0), + Variable("salinity", dtype=np.float32, initial=np.nan), + Variable("temperature", dtype=np.float32, initial=np.nan), + Variable("min_depth", dtype=np.float32), + Variable("max_depth", dtype=np.float32), + Variable("drift_depth", dtype=np.float32), + Variable("vertical_speed", dtype=np.float32), + Variable("cycle_days", dtype=np.int32), + Variable("drift_days", dtype=np.int32), + ] +) + + +def _argo_float_vertical_movement(particle, fieldset, time): + if particle.cycle_phase == 0: + # Phase 0: Sinking with vertical_speed until depth is drift_depth + particle_ddepth += ( # noqa Parcels defines particle_* variables, which code checkers cannot know. + particle.vertical_speed * particle.dt + ) + if particle.depth + particle_ddepth <= particle.drift_depth: + particle_ddepth = particle.drift_depth - particle.depth + particle.cycle_phase = 1 + + elif particle.cycle_phase == 1: + # Phase 1: Drifting at depth for drifttime seconds + particle.drift_age += particle.dt + if particle.drift_age >= particle.drift_days * 86400: + particle.drift_age = 0 # reset drift_age for next cycle + particle.cycle_phase = 2 + + elif particle.cycle_phase == 2: + # Phase 2: Sinking further to max_depth + particle_ddepth += particle.vertical_speed * particle.dt + if particle.depth + particle_ddepth <= particle.max_depth: + particle_ddepth = particle.max_depth - particle.depth + particle.cycle_phase = 3 + + elif particle.cycle_phase == 3: + # Phase 3: Rising with vertical_speed until at surface + particle_ddepth -= particle.vertical_speed * particle.dt + particle.cycle_age += ( + particle.dt + ) # solve issue of not updating cycle_age during ascent + if particle.depth + particle_ddepth >= particle.min_depth: + particle_ddepth = particle.min_depth - particle.depth + particle.temperature = ( + math.nan + ) # reset temperature to NaN at end of sampling cycle + particle.salinity = math.nan # idem + particle.cycle_phase = 4 + else: + particle.temperature = fieldset.T[ + time, particle.depth, particle.lat, particle.lon + ] + particle.salinity = fieldset.S[ + time, particle.depth, particle.lat, particle.lon + ] + + elif particle.cycle_phase == 4: + # Phase 4: Transmitting at surface until cycletime is reached + if particle.cycle_age > particle.cycle_days * 86400: + particle.cycle_phase = 0 + particle.cycle_age = 0 + + if particle.state == StatusCode.Evaluate: + particle.cycle_age += particle.dt # update cycle_age + + +def _keep_at_surface(particle, fieldset, time): + # Prevent error when float reaches surface + if particle.state == StatusCode.ErrorThroughSurface: + particle.depth = particle.min_depth + particle.state = StatusCode.Success + + +def _check_error(particle, fieldset, time): + if particle.state >= 50: # This captures all Errors + particle.delete() + + +def simulate_argo_floats( + fieldset: FieldSet, + out_path: str | py.path.LocalPath, + argo_floats: list[ArgoFloat], + outputdt: timedelta, + endtime: datetime | None, +) -> None: + """ + Use Parcels to simulate a set of Argo floats in a fieldset. + + :param fieldset: The fieldset to simulate the Argo floats in. + :param out_path: The path to write the results to. + :param argo_floats: A list of Argo floats to simulate. + :param outputdt: Interval which dictates the update frequency of file output during simulation + :param endtime: Stop at this time, or if None, continue until the end of the fieldset. + """ + DT = 10.0 # dt of Argo float simulation integrator + + if len(argo_floats) == 0: + print( + "No Argo floats provided. Parcels currently crashes when providing an empty particle set, so no argo floats simulation will be done and no files will be created." + ) + # TODO when Parcels supports it this check can be removed. + return + + # define parcel particles + argo_float_particleset = ParticleSet( + fieldset=fieldset, + pclass=_ArgoParticle, + lat=[argo.spacetime.location.lat for argo in argo_floats], + lon=[argo.spacetime.location.lon for argo in argo_floats], + depth=[argo.min_depth for argo in argo_floats], + time=[argo.spacetime.time for argo in argo_floats], + min_depth=[argo.min_depth for argo in argo_floats], + max_depth=[argo.max_depth for argo in argo_floats], + drift_depth=[argo.drift_depth for argo in argo_floats], + vertical_speed=[argo.vertical_speed for argo in argo_floats], + cycle_days=[argo.cycle_days for argo in argo_floats], + drift_days=[argo.drift_days for argo in argo_floats], + ) + + # define output file for the simulation + out_file = argo_float_particleset.ParticleFile(name=out_path, outputdt=outputdt) + + # get earliest between fieldset end time and provide end time + fieldset_endtime = fieldset.time_origin.fulltime(fieldset.U.grid.time_full[-1]) + if endtime is None: + actual_endtime = fieldset_endtime + elif endtime > fieldset_endtime: + print("WARN: Requested end time later than fieldset end time.") + actual_endtime = fieldset_endtime + else: + actual_endtime = np.timedelta64(endtime) + + # execute simulation + argo_float_particleset.execute( + [ + _argo_float_vertical_movement, + AdvectionRK4, + _keep_at_surface, + _check_error, + ], + endtime=actual_endtime, + dt=DT, + output_file=out_file, + verbose_progress=False, + ) diff --git a/virtual_ship/instruments/ctd.py b/virtual_ship/instruments/ctd.py new file mode 100644 index 00000000..0d017fa7 --- /dev/null +++ b/virtual_ship/instruments/ctd.py @@ -0,0 +1,137 @@ +"""CTD instrument.""" + +from dataclasses import dataclass +from datetime import timedelta + +import numpy as np +import py +from parcels import FieldSet, JITParticle, ParticleSet, Variable + +from ..spacetime import Spacetime + + +@dataclass +class CTD: + """Configuration for a single CTD.""" + + spacetime: Spacetime + min_depth: float + max_depth: float + + +_CTDParticle = JITParticle.add_variables( + [ + Variable("salinity", dtype=np.float32, initial=np.nan), + Variable("temperature", dtype=np.float32, initial=np.nan), + Variable("raising", dtype=np.int8, initial=0.0), # bool. 0 is False, 1 is True. + Variable("max_depth", dtype=np.float32), + Variable("min_depth", dtype=np.float32), + Variable("winch_speed", dtype=np.float32), + ] +) + + +def _sample_temperature(particle, fieldset, time): + particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] + + +def _sample_salinity(particle, fieldset, time): + particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon] + + +def _ctd_cast(particle, fieldset, time): + # lowering + if particle.raising == 0: + particle_ddepth = -particle.winch_speed * particle.dt + if particle.depth + particle_ddepth < particle.max_depth: + particle.raising = 1 + particle_ddepth = -particle_ddepth + # raising + else: + particle_ddepth = particle.winch_speed * particle.dt + if particle.depth + particle_ddepth > particle.min_depth: + particle.delete() + + +def simulate_ctd( + fieldset: FieldSet, + out_path: str | py.path.LocalPath, + ctds: list[CTD], + outputdt: timedelta, +) -> None: + """ + Use Parcels to simulate a set of CTDs in a fieldset. + + :param fieldset: The fieldset to simulate the CTDs in. + :param out_path: The path to write the results to. + :param ctds: A list of CTDs to simulate. + :param outputdt: Interval which dictates the update frequency of file output during simulation + :raises ValueError: Whenever provided CTDs, fieldset, are not compatible with this function. + """ + WINCH_SPEED = 1.0 # sink and rise speed in m/s + DT = 10.0 # dt of CTD simulation integrator + + if len(ctds) == 0: + print( + "No CTDs provided. Parcels currently crashes when providing an empty particle set, so no CTD simulation will be done and no files will be created." + ) + # TODO when Parcels supports it this check can be removed. + return + + fieldset_starttime = fieldset.time_origin.fulltime(fieldset.U.grid.time_full[0]) + fieldset_endtime = fieldset.time_origin.fulltime(fieldset.U.grid.time_full[-1]) + + # deploy time for all ctds should be later than fieldset start time + if not all( + [np.datetime64(ctd.spacetime.time) >= fieldset_starttime for ctd in ctds] + ): + raise ValueError("CTD deployed before fieldset starts.") + + # depth the ctd will go to. shallowest between ctd max depth and bathymetry. + max_depths = [ + max( + ctd.max_depth, + fieldset.bathymetry.eval( + z=0, y=ctd.spacetime.location.lat, x=ctd.spacetime.location.lon, time=0 + ), + ) + for ctd in ctds + ] + + # CTD depth can not be too shallow, because kernel would break. + # This shallow is not useful anyway, no need to support. + if not all([max_depth <= -DT * WINCH_SPEED for max_depth in max_depths]): + raise ValueError( + f"CTD max_depth or bathymetry shallower than maximum {-DT * WINCH_SPEED}" + ) + + # define parcel particles + ctd_particleset = ParticleSet( + fieldset=fieldset, + pclass=_CTDParticle, + lon=[ctd.spacetime.location.lon for ctd in ctds], + lat=[ctd.spacetime.location.lat for ctd in ctds], + depth=[ctd.min_depth for ctd in ctds], + time=[ctd.spacetime.time for ctd in ctds], + max_depth=max_depths, + min_depth=[ctd.min_depth for ctd in ctds], + winch_speed=[WINCH_SPEED for _ in ctds], + ) + + # define output file for the simulation + out_file = ctd_particleset.ParticleFile(name=out_path, outputdt=outputdt) + + # execute simulation + ctd_particleset.execute( + [_sample_salinity, _sample_temperature, _ctd_cast], + endtime=fieldset_endtime, + dt=DT, + verbose_progress=False, + output_file=out_file, + ) + + # there should be no particles left, as they delete themselves when they resurface + if len(ctd_particleset.particledata) != 0: + raise ValueError( + "Simulation ended before CTD resurfaced. This most likely means the field time dimension did not match the simulation time span." + ) diff --git a/virtual_ship/instruments/drifter.py b/virtual_ship/instruments/drifter.py new file mode 100644 index 00000000..7854d4cb --- /dev/null +++ b/virtual_ship/instruments/drifter.py @@ -0,0 +1,111 @@ +"""Drifter instrument.""" + +from dataclasses import dataclass +from datetime import datetime, timedelta + +import numpy as np +import py +from parcels import AdvectionRK4, FieldSet, JITParticle, ParticleSet, Variable + +from ..spacetime import Spacetime + + +@dataclass +class Drifter: + """Configuration for a single Drifter.""" + + spacetime: Spacetime + depth: float # depth at which it floats and samples + lifetime: timedelta | None # if none, lifetime is infinite + + +_DrifterParticle = JITParticle.add_variables( + [ + Variable("temperature", dtype=np.float32, initial=np.nan), + Variable("has_lifetime", dtype=np.int8), # bool + Variable("age", dtype=np.float32, initial=0.0), + Variable("lifetime", dtype=np.float32), + ] +) + + +def _sample_temperature(particle, fieldset, time): + particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] + + +def _check_lifetime(particle, fieldset, time): + if particle.has_lifetime == 1: + particle.age += particle.dt + if particle.age >= particle.lifetime: + particle.delete() + + +def simulate_drifters( + fieldset: FieldSet, + out_path: str | py.path.LocalPath, + drifters: list[Drifter], + outputdt: timedelta, + dt: timedelta, + endtime: datetime | None, +) -> None: + """ + Use Parcels to simulate a set of drifters in a fieldset. + + :param fieldset: The fieldset to simulate the Drifters in. + :param out_path: The path to write the results to. + :param drifters: A list of drifters to simulate. + :param outputdt: Interval which dictates the update frequency of file output during simulation. + :param dt: Dt for integration. + :param endtime: Stop at this time, or if None, continue until the end of the fieldset or until all drifters ended. If this is earlier than the last drifter ended or later than the end of the fieldset, a warning will be printed. + """ + if len(drifters) == 0: + print( + "No drifters provided. Parcels currently crashes when providing an empty particle set, so no drifter simulation will be done and no files will be created." + ) + # TODO when Parcels supports it this check can be removed. + return + + # define parcel particles + drifter_particleset = ParticleSet( + fieldset=fieldset, + pclass=_DrifterParticle, + lat=[drifter.spacetime.location.lat for drifter in drifters], + lon=[drifter.spacetime.location.lon for drifter in drifters], + depth=[drifter.depth for drifter in drifters], + time=[drifter.spacetime.time for drifter in drifters], + has_lifetime=[1 if drifter.lifetime is not None else 0 for drifter in drifters], + lifetime=[ + 0 if drifter.lifetime is None else drifter.lifetime.total_seconds() + for drifter in drifters + ], + ) + + # define output file for the simulation + out_file = drifter_particleset.ParticleFile(name=out_path, outputdt=outputdt) + + # get earliest between fieldset end time and provide end time + fieldset_endtime = fieldset.time_origin.fulltime(fieldset.U.grid.time_full[-1]) + if endtime is None: + actual_endtime = fieldset_endtime + elif endtime > fieldset_endtime: + print("WARN: Requested end time later than fieldset end time.") + actual_endtime = fieldset_endtime + else: + actual_endtime = np.timedelta64(endtime) + + # execute simulation + drifter_particleset.execute( + [AdvectionRK4, _sample_temperature, _check_lifetime], + endtime=actual_endtime, + dt=dt, + output_file=out_file, + verbose_progress=False, + ) + + # if there are more particles left than the number of drifters with an indefinite endtime, warn the user + if len(drifter_particleset.particledata) > len( + [d for d in drifters if d.lifetime is None] + ): + print( + "WARN: Some drifters had a life time beyond the end time of the fieldset or the requested end time." + ) diff --git a/virtual_ship/instruments/ship_underwater_st.py b/virtual_ship/instruments/ship_underwater_st.py new file mode 100644 index 00000000..3d2050d8 --- /dev/null +++ b/virtual_ship/instruments/ship_underwater_st.py @@ -0,0 +1,75 @@ +"""Ship salinity and temperature.""" + +import numpy as np +import py +from parcels import FieldSet, ParticleSet, ScipyParticle, Variable + +from ..spacetime import Spacetime + +# we specifically use ScipyParticle because we have many small calls to execute +# there is some overhead with JITParticle and this ends up being significantly faster +_ShipSTParticle = ScipyParticle.add_variables( + [ + Variable("S", dtype=np.float32, initial=np.nan), + Variable("T", dtype=np.float32, initial=np.nan), + ] +) + + +# define function sampling Salinity +def _sample_salinity(particle, fieldset, time): + particle.S = fieldset.S[time, particle.depth, particle.lat, particle.lon] + + +# define function sampling Temperature +def _sample_temperature(particle, fieldset, time): + particle.T = fieldset.T[time, particle.depth, particle.lat, particle.lon] + + +def simulate_ship_underwater_st( + fieldset: FieldSet, + out_path: str | py.path.LocalPath, + depth: float, + sample_points: list[Spacetime], +) -> None: + """ + Use Parcels to simulate underway data, measuring salinity and temperature at the given depth along the ship track in a fieldset. + + :param fieldset: The fieldset to simulate the sampling in. + :param out_path: The path to write the results to. + :param depth: The depth at which to measure. 0 is water surface, negative is into the water. + :param sample_points: The places and times to sample at. + """ + sample_points.sort(key=lambda p: p.time) + + particleset = ParticleSet.from_list( + fieldset=fieldset, + pclass=_ShipSTParticle, + lon=0.0, # initial lat/lon are irrelevant and will be overruled later + lat=0.0, + depth=depth, + time=0, # same for time + ) + + # define output file for the simulation + # outputdt set to infinie as we want to just want to write at the end of every call to 'execute' + out_file = particleset.ParticleFile(name=out_path, outputdt=np.inf) + + # iterate over each point, manually set lat lon time, then + # execute the particle set for one step, performing one set of measurement + for point in sample_points: + particleset.lon_nextloop[:] = point.location.lon + particleset.lat_nextloop[:] = point.location.lat + particleset.time_nextloop[:] = fieldset.time_origin.reltime( + np.datetime64(point.time) + ) + + # perform one step using the particleset + # dt and runtime are set so exactly one step is made. + particleset.execute( + [_sample_salinity, _sample_temperature], + dt=1, + runtime=1, + verbose_progress=False, + output_file=out_file, + ) diff --git a/virtual_ship/location.py b/virtual_ship/location.py new file mode 100644 index 00000000..793e5312 --- /dev/null +++ b/virtual_ship/location.py @@ -0,0 +1,44 @@ +"""Location class. See class description.""" + +from dataclasses import dataclass + + +@dataclass(frozen=True) +class Location: + """A location on a sphere.""" + + latitude: float + longitude: float + + def __post_init__(self) -> None: + """ + Verify this location has valid latitude and longitude. + + :raises ValueError: If latitude and/or longitude are not valid. + """ + if self.lat < -90: + raise ValueError("Latitude cannot be smaller than -90.") + if self.lat > 90: + raise ValueError("Latitude cannot be larger than 90.") + if self.lon < -180: + raise ValueError("Longitude cannot be smaller than -180.") + if self.lon > 360: + raise ValueError("Longitude cannot be larger than 360.") + + @property + def lat(self) -> float: + """ + Shorthand for latitude variable. + + :returns: Latitude variable. + """ + return self.latitude + + @property + def lon(self) -> float: + """ + Shorthand for longitude variable. + + :returns: Longitude variable. + """ + return self.longitude diff --git a/virtual_ship/make_realistic/__init__.py b/virtual_ship/make_realistic/__init__.py new file mode 100644 index 00000000..2c9a17df --- /dev/null +++ b/virtual_ship/make_realistic/__init__.py @@ -0,0 +1,6 @@ +"""Conversion functions from zarr instrument results to realistic file formats with data adjusted to be more realistic.""" + +from .adcp_make_realistic import adcp_make_realistic +from .ctd_make_realistic import ctd_make_realistic + +__all__ = ["adcp_make_realistic", "ctd_make_realistic"] diff --git a/virtual_ship/make_realistic/adcp_make_realistic.py b/virtual_ship/make_realistic/adcp_make_realistic.py new file mode 100644 index 00000000..69c24790 --- /dev/null +++ b/virtual_ship/make_realistic/adcp_make_realistic.py @@ -0,0 +1,66 @@ +"""adcp_make_realistic function.""" + +import numpy as np +import py +import xarray as xr + + +def adcp_make_realistic( + zarr_path: str | py.path.LocalPath, + out_dir: str | py.path.LocalPath, + prefix: str, +) -> py.path.LocalPath: + """ + Take simulated ADCP data, add noise, then save in (an inconvenient educational) CSV format. + + :param zarr_path: Input simulated data. + :param out_dir: Output directory for CSV file. + :param prefix: Prefix for CSV file. + :returns: Path to created file. + """ + original = xr.open_zarr(zarr_path) + + times = original.sel(trajectory=0)["time"].values + depths = original.sel(obs=0)["z"].values + lats = original.sel(trajectory=0)["lat"].values + lons = original.sel(trajectory=0)["lon"].values + all_us = original["U"].values + all_vs = original["V"].values + + all_us, all_vs = _add_noise(times, depths, all_us, all_vs) + + csv = _to_csv(times, depths, lats, lons, all_us, all_vs) + out_file = ( + out_dir.join(f"{prefix}.csv") + if isinstance(out_dir, py.path.LocalPath) + else f"{out_dir}/{prefix}.csv" + ) + with open(out_file, "w") as out_cnv: + out_cnv.write(csv) + + return out_file + + +def _add_noise( + times: np.ndarray, depths: np.ndarray, all_us: np.ndarray, all_vs: np.ndarray +) -> tuple[np.ndarray, np.ndarray]: + return all_us, all_vs + + +def _to_csv( + times: np.ndarray, + depths: np.ndarray, + lats: np.ndarray, + lons: np.ndarray, + all_us: np.ndarray, + all_vs: np.ndarray, +) -> str: + meta = "# depths (m): " + ",".join([str(d) for d in depths]) + header = f"time,lat,lon,{','.join(['u' + str(n) + ',v' + str(n) for n in range(len(depths))])}" + data = [ + f"{str(time)},{lat},{lon},{','.join([str(u) + ',' + str(v) for u, v in zip(us, vs)])}" + for time, lat, lon, us, vs in zip(times, lats, lons, all_us.T, all_vs.T) + ] + + lines = [meta, header] + data + return "\n".join(lines) diff --git a/virtual_ship/make_realistic/ctd_make_realistic.py b/virtual_ship/make_realistic/ctd_make_realistic.py new file mode 100644 index 00000000..8b7bee24 --- /dev/null +++ b/virtual_ship/make_realistic/ctd_make_realistic.py @@ -0,0 +1,217 @@ +"""ctd_make_realistic function.""" + +import random + +import numpy as np +import opensimplex +import py +import xarray as xr + + +def ctd_make_realistic( + zarr_path: str | py.path.LocalPath, + out_dir: str | py.path.LocalPath, + prefix: str, +) -> list[py.path.LocalPath]: + """ + Take simulated CTD data, add noise, then save in CNV format (1 file per CTD). + + :param zarr_path: Input simulated data. + :param out_dir: Output directory for CNV file. + :param prefix: Prefix for CNV files. Will be postfixed with '_{ctd_num}'. + :returns: Paths to created file. + """ + original = xr.open_zarr(zarr_path) + + files = [] + for ctd_i, traj in enumerate(original.trajectory): + time = original.sel(trajectory=traj)["time"].values + reltimesec = (time - time[0]) / np.timedelta64(1, "s") + latitude = original.sel(trajectory=traj)["lat"].values + longitude = original.sel(trajectory=traj)["lon"].values + temperature = original.sel(trajectory=traj)["temperature"].values + salinity = original.sel(trajectory=traj)["salinity"].values + depth = original.sel(trajectory=traj)["z"].values + + temperature = _add_temperature_noise(temperature, depth) + salinity = _add_salinity_noise(salinity, depth) + + out_file = ( + out_dir.join(f"{prefix}{ctd_i}.cnv") + if isinstance(out_dir, py.path.LocalPath) + else f"{out_dir}/{prefix}{ctd_i}.cnv" + ) + files.append(out_file) + + cnv = _to_cnv( + filename=str(out_file), + latitudes=latitude, + longitudes=longitude, + times=reltimesec, + temperatures=temperature, + depths=depth, + salinities=salinity, + start_time=time[0], + ) + + with open(out_file, "w") as out_cnv: + out_cnv.write(cnv) + + return files + + +def _add_temperature_noise(temperature: np.ndarray, depth: np.ndarray) -> np.ndarray: + """ + Return the provided temperature with added noise. + + The noise is not a realistic nor based on anything physics, but simply an attempt to have the data look somewhat similar to a real CTD cast. + + :param temperature: The clean temperature. + :param depth: Depth measured by CTD. + :return: Temperature with added noise. + """ + surface_noise = ( + 2.0 + * (np.random.random_sample(len(temperature)) * 2.0 - 1) + * np.exp(depth / 4.0) + ) + noise = ( + 0.05 + * np.maximum(1.0 + depth / 1000.0, 0.1) + * np.random.random_sample(len(temperature)) + ) + drift = ( + 0.3 + * (np.random.random() * 2.0 - 1) + * np.array(range(len(temperature))) + / len(temperature) + ) + opensimplex.seed(np.random.randint(999999)) + noise2 = ( + 2.0 + * np.maximum(1.0 + depth / 1000.0, 0.1) + * ( + np.array([opensimplex.noise2(n / 30, 0.0) for n in range(len(temperature))]) + ** 8 + ) + ) + opensimplex.seed(np.random.randint(999999)) + noise3 = 0.1 * ( + np.array([opensimplex.noise2(n / 8, 0.0) for n in range(len(temperature))]) ** 2 + ) + + return temperature + surface_noise + drift + noise + noise3 + noise2 + + +def _add_salinity_noise(salinity: np.ndarray, depth: np.ndarray) -> np.ndarray: + """ + Return the provided salinity with added noise. + + The noise is not a realistic nor based on anything physics, but simply an attempt to have the data look somewhat similar to a real CTD cast. + + :param salinity: The clean salinity. + :param depth: Depth measured by CTD. + :return: Salinity with added noise. + """ + surface_noise = ( + 2.0 * (-np.random.random_sample(len(salinity))) * np.exp(depth / 4.0) + ) + noise = ( + 0.001 + * np.maximum(1.0 + depth / 1000.0, 0.1) + * np.random.random_sample(len(salinity)) + ) + drift = ( + 0.02 + * (np.random.random() * 2.0 - 1) + * np.array(range(len(salinity))) + / len(salinity) + ) + opensimplex.seed(np.random.randint(999999)) + noise2 = ( + 0.07 + * np.maximum(1.0 + depth / 1000.0, 0.1) + * ( + np.array([opensimplex.noise2(n / 30, 0.0) for n in range(len(salinity))]) + ** 8 + ) + ) + opensimplex.seed(np.random.randint(999999)) + noise3 = 0.003 * ( + np.array([opensimplex.noise2(n / 8, 0.0) for n in range(len(salinity))]) ** 2 + ) + + return salinity + surface_noise + drift + noise + noise2 + noise3 + + +def _to_cnv( + filename: str, + latitudes: np.ndarray, + longitudes: np.ndarray, + times: np.ndarray, + temperatures: np.ndarray, + depths: np.ndarray, + salinities: np.ndarray, + start_time: np.datetime64, +) -> str: + """ + Convert data to CNV. + + :param filename: Output file name. + :param latitudes: Latitude data. + :param longitudes: Longitude data. + :param times: Elapsed time since first measurement in seconds. + :param temperatures: Temperature data. + :param depths: Depth data. + :param salinities: Salinity data. + :param start_time: Start time of measuring. This will be in the header of the CNV file. + :returns: The CNV. + """ + formatted_time = np.datetime_as_string(start_time, unit="s") + formatted_time = ( + np.datetime64(formatted_time) + .astype("M8[s]") + .item() + .strftime("%b %d %Y %H:%M:%S") + ) + + header = rf""" +* Sea-Bird SBE 9 Data File: +* FileName = {filename} +# start_time = {formatted_time} [NMEA time, first data scan] +# bad_flag = -9.990e-29 +# file_type = ascii +# name 0 = scan: Scan Count +# name 1 = timeS: Time, Elapsed [seconds] +# name 2 = latitude: Latitude [deg] +# name 3 = longitude: Longitude [deg] +# name 4 = depSM: Depth [salt water, m] +# name 5 = t090C: Temperature [ITS-90, deg C] +# name 6 = sal00: Salinity, Practical [PSU] +*END* +""".strip() + + random_time_offset = random.random() + + rows = [ + f"{_i_col(13 + 24 * n)}{_f_col(time + random_time_offset, 3)}{_f_col(lat, 5)}{_f_col(lon, 5)}{_f_col(-depth, 3)}{_f_col(temp, 4)}{_f_col(sal, 4)}" + for n, (time, temp, lat, lon, depth, sal) in enumerate( + zip(times, temperatures, latitudes, longitudes, depths, salinities) + ) + ] + + cnv = header + "\n" + "\n".join(rows) + "\n" + + return cnv + + +def _make_column(val: str) -> str: + return val.rjust(11) + + +def _i_col(val: int) -> str: + return _make_column(str(val)) + + +def _f_col(val: float, digits: int) -> str: + return _make_column(str(round(val, digits))) diff --git a/virtual_ship/spacetime.py b/virtual_ship/spacetime.py new file mode 100644 index 00000000..b2798d7e --- /dev/null +++ b/virtual_ship/spacetime.py @@ -0,0 +1,14 @@ +"""Location class. See class description.""" + +from dataclasses import dataclass +from datetime import datetime + +from .location import Location + + +@dataclass +class Spacetime: + """A location and time.""" + + location: Location + time: datetime diff --git a/virtualship.py b/virtualship.py deleted file mode 100644 index 5e599a49..00000000 --- a/virtualship.py +++ /dev/null @@ -1,603 +0,0 @@ -import json -import os -import math -import numpy as np -import xarray as xr -import pyproj -import shutil -import datetime -from datetime import timedelta -from shapely.geometry import Point, Polygon -from scipy.ndimage import uniform_filter1d -from parcels import Field, FieldSet, JITParticle, Variable, ParticleSet, AdvectionRK4, StatusCode - - -class VirtualShipConfiguration: - def __init__(self, json_file): - with open(os.path.join(os.path.dirname(__file__), json_file), 'r') as file: - json_input = json.loads(file.read()) - for key in json_input: - setattr(self, key, json_input[key]) - - # Create a polygon from the region of interest to check coordinates - north = self.region_of_interest["North"] - east = self.region_of_interest["East"] - south = self.region_of_interest["South"] - west = self.region_of_interest["West"] - poly = Polygon([(west, north), (west, south), (east, south), (east, north)]) - # validate input, raise ValueErrors if invalid - if self.region_of_interest["North"] > 90 or self.region_of_interest["South"] < -90 or self.region_of_interest["East"] > 180 or self.region_of_interest["West"] < -180: - raise ValueError("Invalid coordinates in region of interest") - if self.requested_ship_time["start"] > self.requested_ship_time["end"]: - raise ValueError("Start time should be before end time") - if datetime.datetime.strptime(self.requested_ship_time["end"],"%Y-%m-%dT%H:%M:%S") > datetime.datetime.now()+timedelta(days=2): - raise ValueError("End time cannot be more then 2 days into the future") - if datetime.datetime.strptime(self.requested_ship_time["end"],"%Y-%m-%dT%H:%M:%S") - datetime.datetime.strptime(self.requested_ship_time["start"],"%Y-%m-%dT%H:%M:%S") > timedelta(days=21): - raise ValueError("The time period is too long, maximum is 21 days") - if len(self.route_coordinates) < 2: - raise ValueError("Route needs to consist of at least 2 longitude-latitude coordinate sets") - for coord in self.route_coordinates: - if coord[1] > 90 or coord[1] < -90 or coord[0] > 180 or coord[0] < -180: - raise ValueError("Invalid coordinates in route") - # if not poly.contains(Point(coord)): - # raise ValueError("Route coordinates need to be within the region of interest") - if not len(self.CTD_locations) == 0: - for coord in self.CTD_locations: - if coord not in self.route_coordinates: - raise ValueError("CTD coordinates should be on the route") - if coord[1] > 90 or coord[1] < -90 or coord[0] > 180 or coord[0] < -180: - raise ValueError("Invalid coordinates in route") - if not poly.contains(Point(coord)): - raise ValueError("CTD coordinates need to be within the region of interest") - if type(self.CTD_settings['max_depth']) != int: - if self.CTD_settings['max_depth'] != "max": - raise ValueError('Specify "max" for maximum depth or a negative integer for max_depth in CTD_settings') - if type(self.CTD_settings['max_depth']) == int: - if self.CTD_settings['max_depth'] > 0: - raise ValueError("Invalid depth for CTD") - if len(self.drifter_deploylocations) > 30: - raise ValueError("Too many drifter deployment locations, maximum is 30") - if not len(self.drifter_deploylocations) == 0: - for coord in self.drifter_deploylocations: - if coord not in self.route_coordinates: - raise ValueError("Drifter coordinates should be on the route") - if coord[1] > 90 or coord[1] < -90 or coord[0] > 180 or coord[0] < -180: - raise ValueError("Invalid coordinates in route") - if not poly.contains(Point(coord)): - raise ValueError("Drifter coordinates need to be within the region of interest") - if len(self.argo_deploylocations) > 30: - raise ValueError("Too many argo deployment locations, maximum is 30") - if not len(self.argo_deploylocations) == 0: - for coord in self.argo_deploylocations: - if coord not in self.route_coordinates: - raise ValueError("argo coordinates should be on the route") - if coord[1] > 90 or coord[1] < -90 or coord[0] > 180 or coord[0] < -180: - raise ValueError("Invalid coordinates in route") - if not poly.contains(Point(coord)): - raise ValueError("argo coordinates need to be within the region of interest") - if not isinstance(self.underway_data, bool): - raise ValueError("Underway data needs to be true or false") - if not isinstance(self.ADCP_data, bool): - raise ValueError("ADCP data needs to be true or false") - if self.ADCP_settings['bin_size_m'] < 0 or self.ADCP_settings['bin_size_m'] > 24: - raise ValueError("Invalid bin size for ADCP") - if self.ADCP_settings['max_depth'] > 0: - raise ValueError("Invalid depth for ADCP") - if self.argo_characteristics['driftdepth'] > 0 or self.argo_characteristics['driftdepth'] < -5727: - raise ValueError("Specify negative depth. Max drift depth for argo is -5727 m due to data availability") - if self.argo_characteristics['maxdepth'] > 0 or self.argo_characteristics['maxdepth'] < -5727: - raise ValueError("Specify negative depth. Max depth for argo is -5727 m due to data availability") - if type(self.argo_characteristics['vertical_speed']) != float: - raise ValueError("Specify vertical speed for argo with decimals in m/s") - if self.argo_characteristics['vertical_speed'] > 0: - self.argo_characteristics['vertical_speed'] = -self.argo_characteristics['vertical_speed'] - if abs(self.argo_characteristics['vertical_speed']) < 0.06 or abs(self.argo_characteristics['vertical_speed']) > 0.12: - raise ValueError("Specify a realistic speed for argo, i.e. between -0.06 and -0.12 m/s") - if self.argo_characteristics['cycle_days'] < 0: - raise ValueError("Specify a postitive number of cycle days for argo") - if self.argo_characteristics['drift_days'] < 0: - raise ValueError("Specify a postitive number of drift days for argo") - - -def shiproute(config): - '''Takes in route coordinates and returns lat and lon points within region of interest to sample''' - - # Initialize lists to store intermediate points - lons = [] - lats = [] - - # Loop over station coordinates and calculate intermediate points along great circle path - for i in (range(len(config.route_coordinates)-1)): - startlong = config.route_coordinates[i][0] - startlat = config.route_coordinates[i][1] - endlong = config.route_coordinates[i+1][0] - endlat = config.route_coordinates[i+1][1] - - # calculate line string along path with segments every 5 min for ADCP measurements - # current cruise speed is 10knots = 5.14 m/s * 60*5 = 1542 m every 5 min - # Realistic time between measurements is 2 min on Pelagia according to Floran - cruise_speed = 5.14 - geod = pyproj.Geod(ellps='WGS84') - azimuth1, azimuth2, distance = geod.inv(startlong, startlat, endlong, endlat) - if distance > (cruise_speed*60*5): - r = geod.inv_intermediate(startlong, startlat, endlong, endlat, del_s=1545, initial_idx=0, return_back_azimuth=False) - lons = np.append(lons, r.lons) # stored as a list of arrays - lats = np.append(lats, r.lats) - else: - lons = np.append(lons, endlong) - lats = np.append(lats, endlat) - - # initial_idx will add begin point to each list (but not end point to avoid doubling) so add final endpoint manually - lons = np.append(np.hstack(lons), endlong) - lats = np.append(np.hstack(lats), endlat) - - # check if input sample locations are within data availability area, only save if so - north = config.region_of_interest["North"] - east = config.region_of_interest["East"] - south = config.region_of_interest["South"] - west = config.region_of_interest["West"] - poly = Polygon([(west, north), (west, south), (east, south), (east, north)]) - sample_lons = [] - sample_lats = [] - for i in range(len(lons)): - if poly.contains(Point(lons[i], lats[i])): - sample_lons.append(lons[i]) - sample_lats.append(lats[i]) - return sample_lons, sample_lats - -def create_fieldset(config): - '''Creates fieldset from netcdf files and adds bathymetry data for CTD cast, returns fieldset with negative depth values''' - - datadirname = os.path.dirname(__file__) - filenames = { - "U": os.path.join(datadirname, "studentdata_UV.nc"), - "V": os.path.join(datadirname, "studentdata_UV.nc"), - "S": os.path.join(datadirname, "studentdata_S.nc"), - "T": os.path.join(datadirname, "studentdata_T.nc")} - variables = {'U': 'uo', 'V': 'vo', 'S': 'so', 'T': 'thetao'} - dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth': 'depth'} - - # create the fieldset and set interpolation methods - fieldset = FieldSet.from_netcdf(filenames, variables, dimensions, allow_time_extrapolation=True) - fieldset.T.interp_method = "linear_invdist_land_tracer" - fieldset.S.interp_method = "linear_invdist_land_tracer" - for g in fieldset.gridset.grids: - if max(g.depth) > 0: - g.depth = -g.depth # make depth negative - fieldset.mindepth = -fieldset.U.depth[0] # uppermost layer in the hydrodynamic data - if config.CTD_settings["max_depth"] == "max": - fieldset.add_constant('max_depth', -fieldset.U.depth[-1]) - else: - fieldset.add_constant('max_depth', config.CTD_settings["max_depth"]) - fieldset.add_constant("maxtime", fieldset.U.grid.time_full[-1]) - - # add bathymetry data to the fieldset for CTD cast - bathymetry_file = os.path.join(datadirname, "GLO-MFC_001_024_mask_bathy.nc") - bathymetry_variables = ('bathymetry', 'deptho') - bathymetry_dimensions = {'lon': 'longitude', 'lat': 'latitude'} - bathymetry_field = Field.from_netcdf(bathymetry_file, bathymetry_variables, bathymetry_dimensions) - fieldset.add_field(bathymetry_field) - # read in data already - fieldset.computeTimeChunk(0,1) - - if fieldset.U.lon.min() > config.region_of_interest["West"]: - raise ValueError("FieldSet western boundary is outside region of interest. Please run download_data.py again.") - if fieldset.U.lon.max() < config.region_of_interest["East"]: - raise ValueError("FieldSet eastern boundary is outside region of interest. Please run download_data.py again.") - if fieldset.U.lat.min() > config.region_of_interest["South"]: - raise ValueError("FieldSet southern boundary is outside region of interest. Please run download_data.py again.") - if fieldset.U.lat.max() < config.region_of_interest["North"]: - raise ValueError("FieldSet northern boundary is outside region of interest. Please run download_data.py again.") - return fieldset - -def create_drifter_fieldset(config): - '''Creates fieldset from netcdf files for drifters, returns fieldset with negative depth values''' - - datadirname = os.path.dirname(__file__) - filenames = { - "U": os.path.join(datadirname, "drifterdata_UV.nc"), - "V": os.path.join(datadirname, "drifterdata_UV.nc"), - "T": os.path.join(datadirname, "drifterdata_T.nc")} - variables = {'U': 'uo', 'V': 'vo', 'T': 'thetao'} - dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth': 'depth'} - - # create the fieldset and set interpolation methods - fieldset = FieldSet.from_netcdf(filenames, variables, dimensions, allow_time_extrapolation=False) - fieldset.T.interp_method = "linear_invdist_land_tracer" - for g in fieldset.gridset.grids: - if max(g.depth) > 0: - g.depth = -g.depth # make depth negative - fieldset.mindepth = -fieldset.U.depth[0] # uppermost layer in the hydrodynamic data - return fieldset - -def create_argo_fieldset(config): - '''Creates fieldset from netcdf files for argo floats, returns fieldset with negative depth values''' - - datadirname = os.path.dirname(__file__) - filenames = { - "U": os.path.join(datadirname, "argodata_UV.nc"), - "V": os.path.join(datadirname, "argodata_UV.nc"), - "S": os.path.join(datadirname, "argodata_S.nc"), - "T": os.path.join(datadirname, "argodata_T.nc")} - variables = {'U': 'uo', 'V': 'vo', 'S': 'so', 'T': 'thetao'} - dimensions = {'lon': 'longitude', 'lat': 'latitude', 'time': 'time', 'depth': 'depth'} - - # create the fieldset and set interpolation methods - fieldset = FieldSet.from_netcdf(filenames, variables, dimensions, allow_time_extrapolation=False) - fieldset.T.interp_method = "linear_invdist_land_tracer" - for g in fieldset.gridset.grids: - if max(g.depth) > 0: - g.depth = -g.depth # make depth negative - fieldset.mindepth = -fieldset.U.depth[0] # uppermost layer in the hydrodynamic data - fieldset.add_constant('driftdepth', config.argo_characteristics["driftdepth"]) - fieldset.add_constant('maxdepth', config.argo_characteristics["maxdepth"]) - fieldset.add_constant('vertical_speed', config.argo_characteristics["vertical_speed"]) - fieldset.add_constant('cycle_days', config.argo_characteristics["cycle_days"]) - fieldset.add_constant('drift_days', config.argo_characteristics["drift_days"]) - return fieldset - -def sailship(config): - '''Uses parcels to simulate the ship, take CTDs and measure ADCP and underwaydata, returns results folder''' - - # Create fieldset and retreive final schip route as sample_lons and sample_lats - fieldset = create_fieldset(config) - - sample_lons, sample_lats = shiproute(config) - print("Arrived in region of interest, starting to gather data.") - - # Create Vessel Mounted ADCP like particles to sample the ocean - class VM_ADCPParticle(JITParticle): - """Define a new particle class that does Vessel Mounted ADCP like measurements""" - U = Variable('U', dtype=np.float32, initial=0.0) - V = Variable('V', dtype=np.float32, initial=0.0) - - # Create particle to sample water underway - class UnderwayDataParticle(JITParticle): - """Define a new particle class that samples water directly under the hull""" - salinity = Variable("salinity", initial=np.nan) - temperature = Variable("temperature", initial=np.nan) - - # Create CTD like particles to sample the ocean - class CTDParticle(JITParticle): - """Define a new particle class that does CTD like measurements""" - salinity = Variable("salinity", initial=np.nan) - temperature = Variable("temperature", initial=np.nan) - raising = Variable("raising", dtype=np.int32, initial=0.0) - - # define ADCP sampling function without conversion (because of A grid) - def SampleVel(particle, fieldset, time): - particle.U, particle.V = fieldset.UV.eval(time, particle.depth, particle.lat, particle.lon, applyConversion=False) - - # define function lowering and raising CTD - def CTDcast(particle, fieldset, time): - # TODO question: if is executed every time... move outside function? Not if "drifting" now possible - if -fieldset.bathymetry[time, particle.depth, particle.lat, particle.lon] > fieldset.max_depth: - maxdepth = -fieldset.bathymetry[time, particle.depth, particle.lat, particle.lon] + 20 - else: - maxdepth = fieldset.max_depth - winch_speed = -1.0 # sink and rise speed in m/s - - if particle.raising == 0: - # Sinking with winch_speed until near seafloor - particle_ddepth = winch_speed * particle.dt - if particle.depth <= maxdepth: - particle.raising = 1 - - if particle.raising == 1: - # Rising with winch_speed until depth is -2 m - if particle.depth < -2: - particle_ddepth = -winch_speed * particle.dt - if particle.depth + particle_ddepth >= -2: - # to break the loop ... - particle.state = 41 - print("CTD cast finished.") - - # define function sampling Salinity - def SampleS(particle, fieldset, time): - particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon] - - # define function sampling Temperature - def SampleT(particle, fieldset, time): - particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] - - # Create ADCP like particleset and output file - ADCP_bins = np.arange(config.ADCP_settings["max_depth"], -5, config.ADCP_settings["bin_size_m"]) - vert_particles = len(ADCP_bins) - pset_ADCP = ParticleSet.from_list( - fieldset=fieldset, pclass=VM_ADCPParticle, lon=np.full(vert_particles,sample_lons[0]), - lat=np.full(vert_particles,sample_lats[0]), depth=ADCP_bins, time=0 - ) - adcp_output_file = pset_ADCP.ParticleFile(name=os.path.join("results","ADCP.zarr")) - adcp_dt = timedelta(minutes=5).total_seconds() # timestep of ADCP output, every 5 min - - # Create underway particle - pset_UnderwayData = ParticleSet.from_list( - fieldset=fieldset, pclass=UnderwayDataParticle, lon=sample_lons[0], - lat=sample_lats[0], depth=-2, time=0 - ) - UnderwayData_output_file = pset_UnderwayData.ParticleFile(name=os.path.join("results","UnderwayData.zarr")) - - # initialize CTD station number and time - total_time = timedelta(hours=0).total_seconds() - ctd = 0 - ctd_dt = timedelta(seconds=10) # timestep of CTD output reflecting post-process binning into 10m bins - - # initialize drifters and argo floats - drifter = 0 - drifter_time = [] - argo = 0 - argo_time = [] - - # run the model for the length of the sample_lons list - for i in range(len(sample_lons)-1): - - if i % 96 == 0: - print(f"Gathered data {timedelta(seconds=total_time)} hours since start.") - - # execute the ADCP kernels to sample U and V and underway T and S - if config.ADCP_data: - pset_ADCP.execute([SampleVel], dt=adcp_dt, runtime=1, verbose_progress=False) - adcp_output_file.write(pset_ADCP, time=pset_ADCP[0].time) - if config.underway_data: - pset_UnderwayData.execute([SampleS, SampleT], dt=adcp_dt, runtime=1, verbose_progress=False) - UnderwayData_output_file.write(pset_UnderwayData, time=pset_ADCP[0].time) - if pset_ADCP[0].time > fieldset.maxtime: - print("Ship time is over, waiting for drifters and/or Argo floats to finish.") - return drifter_time, argo_time - - # check if virtual ship is at a CTD station - if ctd < len(config.CTD_locations): - if abs(sample_lons[i] - config.CTD_locations[ctd][0]) < 0.001 and abs(sample_lats[i] - config.CTD_locations[ctd][1]) < 0.001: - ctd += 1 - - # release CTD particle - pset_CTD = ParticleSet(fieldset=fieldset, pclass=CTDParticle, lon=sample_lons[i], lat=sample_lats[i], depth=fieldset.mindepth, time=total_time) - - # create a ParticleFile to store the CTD output - ctd_output_file = pset_CTD.ParticleFile(name=f"{os.path.join('results','CTDs','CTD_')}{ctd:03d}.zarr", outputdt=ctd_dt) - - # record the temperature and salinity of the particle - pset_CTD.execute([SampleS, SampleT, CTDcast], runtime=timedelta(hours=8), dt=ctd_dt, output_file=ctd_output_file, verbose_progress=False) - total_time = pset_CTD.time[0] + timedelta(minutes=20).total_seconds() # add CTD time and 20 minutes for deployment - - # check if we are at a drifter deployment location - if drifter < len(config.drifter_deploylocations): - while abs(sample_lons[i] - config.drifter_deploylocations[drifter][0]) < 0.01 and abs(sample_lats[i] - config.drifter_deploylocations[drifter][1]) < 0.01: - drifter_time.append(total_time) - drifter += 1 - print(f"Drifter {drifter} deployed at {sample_lons[i]}, {sample_lats[i]}") - if drifter == len(config.drifter_deploylocations): - break - - # check if we are at a argo deployment location - if argo < len(config.argo_deploylocations): - while abs(sample_lons[i] - config.argo_deploylocations[argo][0]) < 0.01 and abs(sample_lats[i] - config.argo_deploylocations[argo][1]) < 0.01: - argo_time.append(total_time) - argo += 1 - print(f"Argo {argo} deployed at {sample_lons[i]}, {sample_lats[i]}") - if argo == len(config.argo_deploylocations): - break - - # update the particle time and location - pset_ADCP.lon_nextloop[:] = sample_lons[i+1] - pset_ADCP.lat_nextloop[:] = sample_lats[i+1] - pset_UnderwayData.lon_nextloop[:] = sample_lons[i+1] - pset_UnderwayData.lat_nextloop[:] = sample_lats[i+1] - - total_time += adcp_dt - pset_ADCP.time_nextloop[:] = total_time - pset_UnderwayData.time_nextloop[:] = total_time - - # write the final locations of the ADCP and Underway data particles - if config.ADCP_data: - pset_ADCP.execute(SampleVel, dt=adcp_dt, runtime=1, verbose_progress=False) - adcp_output_file.write_latest_locations(pset_ADCP, time=total_time) - if config.underway_data: - pset_UnderwayData.execute([SampleS, SampleT], dt=adcp_dt, runtime=1, verbose_progress=False) - UnderwayData_output_file.write_latest_locations(pset_UnderwayData, time=total_time) - print("Cruise has ended. Please wait for drifters and/or Argo floats to finish.") - - return drifter_time, argo_time, total_time - - -def drifter_deployments(config, drifter_time): - - if len(config.drifter_deploylocations) > 0: - - fieldset = create_drifter_fieldset(config) - - # Create particle to sample water underway - class DrifterParticle(JITParticle): - """Define a new particle class that samples Temperature as a surface drifter""" - temperature = Variable("temperature", initial=np.nan) - - # define function sampling Temperature - def SampleT(particle, fieldset, time): - particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] - - def CheckError(particle, fieldset, time): - if particle.state >= 50: # This captures all Errors - particle.delete() - - # initialize drifters - lon = [] - lat = [] - for i in range(len(config.drifter_deploylocations)): - lon.append(config.drifter_deploylocations[i][0]) - lat.append(config.drifter_deploylocations[i][1]) - time = drifter_time - - # Create and execute drifter particles - pset = ParticleSet(fieldset=fieldset, pclass=DrifterParticle, lon=lon, lat=lat, depth=np.repeat(fieldset.mindepth,len(time)), time=time) - output_file = pset.ParticleFile(name=os.path.join("results","Drifters.zarr"), outputdt=timedelta(hours=1)) - - fieldset_endtime = fieldset.time_origin.fulltime(fieldset.U.grid.time_full[-1]) - drifter_endtime = np.array((datetime.datetime.strptime(config.requested_ship_time["start"],"%Y-%m-%dT%H:%M:%S") + timedelta(weeks=6))).astype('datetime64[ms]') - - pset.execute( - [AdvectionRK4, SampleT, CheckError], - endtime=min(fieldset_endtime, drifter_endtime), dt=timedelta(minutes=5), - output_file=output_file - ) - - -def argo_deployments(config, argo_time): - '''Deploys argo floats, returns results folder''' - - if len(config.argo_deploylocations) > 0: - - fieldset = create_argo_fieldset(config) - - # Define the new Kernel that mimics Argo vertical movement - def ArgoVerticalMovement(particle, fieldset, time): - - if particle.cycle_phase == 0: - # Phase 0: Sinking with vertical_speed until depth is driftdepth - particle_ddepth += fieldset.vertical_speed * particle.dt - if particle.depth + particle_ddepth <= fieldset.driftdepth: - particle_ddepth = fieldset.driftdepth - particle.depth - particle.cycle_phase = 1 - - elif particle.cycle_phase == 1: - # Phase 1: Drifting at depth for drifttime seconds - particle.drift_age += particle.dt - if particle.drift_age >= fieldset.drift_days * 86400: - particle.drift_age = 0 # reset drift_age for next cycle - particle.cycle_phase = 2 - - elif particle.cycle_phase == 2: - # Phase 2: Sinking further to maxdepth - particle_ddepth += fieldset.vertical_speed * particle.dt - if particle.depth + particle_ddepth <= fieldset.maxdepth: - particle_ddepth = fieldset.maxdepth - particle.depth - particle.cycle_phase = 3 - - elif particle.cycle_phase == 3: - # Phase 3: Rising with vertical_speed until at surface - particle_ddepth -= fieldset.vertical_speed * particle.dt - particle.cycle_age += particle.dt # solve issue of not updating cycle_age during ascent - if particle.depth + particle_ddepth >= fieldset.mindepth: - particle_ddepth = fieldset.mindepth - particle.depth - particle.temperature = math.nan # reset temperature to NaN at end of sampling cycle - particle.salinity = math.nan # idem - particle.cycle_phase = 4 - else: - particle.temperature = fieldset.T[time, particle.depth, particle.lat, particle.lon] - particle.salinity = fieldset.S[time, particle.depth, particle.lat, particle.lon] - - elif particle.cycle_phase == 4: - # Phase 4: Transmitting at surface until cycletime is reached - if particle.cycle_age > fieldset.cycle_days * 86400: - particle.cycle_phase = 0 - particle.cycle_age = 0 - - if particle.state == StatusCode.Evaluate: - particle.cycle_age += particle.dt # update cycle_age - - def KeepAtSurface(particle, fieldset, time): - # Prevent error when float reaches surface - if particle.state == StatusCode.ErrorThroughSurface: - particle.depth = fieldset.mindepth - particle.state = StatusCode.Success - - def CheckError(particle, fieldset, time): - if particle.state >= 50: # This captures all Errors - particle.delete() - - class ArgoParticle(JITParticle): - cycle_phase = Variable("cycle_phase", dtype=np.int32, initial=0.0) - cycle_age = Variable("cycle_age", dtype=np.float32, initial=0.0) - drift_age = Variable("drift_age", dtype=np.float32, initial=0.0) - salinity = Variable("salinity", initial=np.nan) - temperature = Variable("temperature", initial=np.nan) - - # initialize argo floats - lon = [] - lat = [] - for i in range(len(config.argo_deploylocations)): - lon.append(config.argo_deploylocations[i][0]) - lat.append(config.argo_deploylocations[i][1]) - time = argo_time - - # Create and execute argo particles - argoset = ParticleSet(fieldset=fieldset, pclass=ArgoParticle, lon=lon, lat=lat, depth=np.repeat(fieldset.mindepth,len(time)), time=time) - argo_output_file = argoset.ParticleFile(name=os.path.join("results","Argos.zarr"), outputdt=timedelta(minutes=5), chunks=(1,500)) - fieldset_endtime = fieldset.time_origin.fulltime(fieldset.U.grid.time_full[-1]) - argo_endtime = np.array((datetime.datetime.strptime(config.requested_ship_time["start"],"%Y-%m-%dT%H:%M:%S") + timedelta(weeks=6))).astype('datetime64[ms]') - - argoset.execute( - [ArgoVerticalMovement, AdvectionRK4, KeepAtSurface, CheckError], # list of kernels to be executed - endtime=min(fieldset_endtime, argo_endtime), dt=timedelta(minutes=5), - output_file=argo_output_file - ) - - -def postprocess(): - '''Postprocesses CTD data and writes to csv files''' - - if os.path.isdir(os.path.join("results","CTDs")): - i = 0 - filenames = os.listdir(os.path.join("results","CTDs")) - for filename in sorted(filenames): - if filename.endswith(".zarr"): - try: #too many errors, just skip the faulty zarr files - i += 1 - # Open output and read to x, y, z - ds = xr.open_zarr(os.path.join("results","CTDs",filename)) - x = ds["lon"][:].squeeze() - y = ds["lat"][:].squeeze() - z = ds["z"][:].squeeze() - time = ds["time"][:].squeeze() - T = ds["temperature"][:].squeeze() - S = ds["salinity"][:].squeeze() - ds.close() - - random_walk = np.random.random()/10 - z_norm = (z-np.min(z))/(np.max(z)-np.min(z)) - t_norm = np.linspace(0, 1, num=len(time)) - # add smoothed random noise scaled with depth - # and random (reversed) diversion from initial through time scaled with depth - S = S + uniform_filter1d( - np.random.random(S.shape)/5*(1-z_norm) + - random_walk*(np.max(S).values - np.min(S).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/40), 1)) - T = T + uniform_filter1d( - np.random.random(T.shape)*5*(1-z_norm) - - random_walk/2*(np.max(T).values - np.min(T).values)*(1-z_norm)*t_norm/10, - max(int(len(time)/20), 1)) - - # reshaping data to export to csv - header = f"pressure [dbar],temperature [degC],salinity [g kg-1]" - data = np.column_stack([-z, T, S]) - new_line = '\n' - np.savetxt(f"{os.path.join('results','CTDs','CTD_station_')}{i}.csv", data, fmt="%.4f", header=header, delimiter=',', - comments=f'longitude,{x[0].values},"{x.attrs}"{new_line}latitude,{y[0].values},"{y.attrs}"{new_line}start time,{time[0].values}{new_line}end time,{time[-1].values}{new_line}') - shutil.rmtree(filename.path) - except TypeError: - print(f"CTD file {filename} seems faulty, skipping.") - continue - print("CTD data postprocessed.") - -def costs(config, total_time): - '''Calculates cost of the virtual ship''' - - ship_cost_per_day = 30000 - drifter_deploy_cost = 2500 - argo_deploy_cost = 15000 - - ship_cost = ship_cost_per_day/24 * total_time//3600 - argo_cost = len(config.argo_deploylocations) * argo_deploy_cost - drifter_cost = len(config.drifter_deploylocations) * drifter_deploy_cost - - cost = ship_cost + argo_cost + drifter_cost - return cost - -if __name__ == '__main__': - config = VirtualShipConfiguration('student_input.json') - drifter_time, argo_time, total_time = sailship(config) - # drifter_deployments(config, drifter_time) - # argo_deployments(config, argo_time) - # postprocess() - print("All data has been gathered and postprocessed, returning home.") - cost = costs(config, total_time) - print(f"This cruise took {timedelta(seconds=total_time)} and would have cost {cost:,.0f} euros.")