pyLARDA for accessing and analysing ground based remote sensing data. It tries to simplify following tasks:
- finding netcdf files in a complex folder structure
- loading data from differently formatted netcdfs
- stitching data from consecutive files together
- simplify common plotting tasks
Documentation is available at larda-doc
requires python3.8 or newer
python3 -m venv larda-env
source larda-env/bin/activate
python3 -m pip install pyLARDA
The pyLARDA remote backend is only targeted on unix operating system.
Building the documentation requires some more dependencies:
sphinx
recommonmark
sphinx_rtd_theme
For development, local data sources and the backend, pyLARDA module can be installed with:
python3 -m venv larda-env
source larda-env/bin/activate
mkdir larda3
cd larda3
git clone https://github.com/lacros-tropos/larda.git
cd larda
python3 -m pip install --editable .
Depending on your datasource of choice:
You just need to know the link to the backend backend of choice and may move to Quickstart.
For local data it is necessary to include the source in a certain directory structure. For the setup of the config files consult the Guide to config-files.
├── larda # github managed source code
│ ├── docs
│ ├── examples
│ ├── ListCollector.py
│ ├── pyLARDA # actual python module
│ ├── README.md
│ ├── requirements.txt
│ └── run_docs.sh
├── larda-cfg # configuration files
│ ├── campaigns.toml
│ ├── [single campaign].toml
│ └── [single campaign].toml
├── larda-connectordump
│ └── [auto generated subfolder for each campaign]
├── larda-description
│ ├── [...].rst
└── larda-doc # folder if you want to generate the docs
└── ...
Make sure that the module is available at your pythonpath when in doubt use sys.path.append('dir').
import pyLARDA
link_to_backend = 'http://...'
# or use pyLARDA.LARDA('local')
larda = pyLARDA.LARDA('remote', uri=link_to_backend)
print('available campaigns', larda.campaign_list)
larda.connect('campaign_name')
MIRA_Zg = larda.read("MIRA","Zg", [dt_begin, dt_end], [0, 4000])
fig, ax = pyLARDA.Transformations.plot_timeheight2
(MIRA_Zg, range_interval=[500, 3000], z_converter='lin2z')
fig.savefig('MIRA_Z.png', dpi=250)For more examples refer to the scripts in the examples directory.
An online version of the documentation is available at https://lacros-tropos.github.io/larda-doc/.
For building simply run .\run_docs.sh, when the additinal libraries (sphinx, recommonmark and sphinx_rtd_theme are available; see above).
This version of the LACROS research data analyser (LARDA) is based on two prior versions in C and python2 respectively. Major changes are the migration to python3, netcdf4 and the inclusion of radar Doppler spectra.
Copyright 2024, pyLARDA-dev-team (Johannes Bühl, Martin Radenz, Willi Schimmel, Teresa Vogl, Moritz Lochmann, Johannes Röttenbacher, Andi Klamt)
MIT License For details see the LICENSE file.