Extract gridmet, Translate to hru, Load to netCDF
- Free software: MIT license
- Documentation: https://gridmetetl.readthedocs.io.
- Create conda env as follows
- conda create -n gmetl python=3.7
- conda activate gmetl
- conda install -c conda-forge numpy matplotlib pandas geopandas xarray netcdf4 requests dask
- conda install -c conda-forge jupyterlab
- OPTIONAL:
- conda install -c conda-forge git
- conda install -c conda-forge pip
- Clone repository
- cd gridmetetl
- Develop code:
- pip install -e .
- Use code
- pip install .
From your conda environment created above:
(gmetl) B:\gitbmi\gridmetetl>gridmetetl -h
usage: gridmet_etl [-h] -t extraction type [-p YYYY-MM-DD) (YYYY-MM-DD]
[-d numdays] [-f output_file_prefix] -i input_path -o
output_path -w weight_file
[-v [GridMet_Variables [GridMet_Variables ...]]]
map gridded climate data to polygon using zonal area weighted mean
optional arguments:
-h, --help show this help message and exit
-t extraction type, --extract_type extraction type
extract method: (days) or (date)
-p (YYYY-MM-DD) (YYYY-MM-DD), --period (YYYY-MM-DD) (YYYY-MM-DD)
option: start date and end date of retrieval (YYYY-MM-
DD)
-d numdays, --days numdays
option: number of days to retrieve; if specified take
precedence over -s & -e option
-f output_file_prefix, --file_prefix output_file_prefix
option: prefix for output files
-i input_path, --inpath input_path
input_path (location of HRU shapefiles)
-o output_path, --outpath output_path
Output path (location of netcdf output files by
shapefile output)
-w weight_file, --weightsfile weight_file
path/weight.csv - path/name of weight file
-v [GridMet_Variables [GridMet_Variables ...]], --variables [GridMet_Variables [GridMet_Variables ...]]
over-ride default vars
### Do an ETL:
gridmetetl -t date -p 2018-09-01 2018-09-02 -i ../../GitRepos/onhm-fetcher-parser/Data -o ../../GitRepos/onhm-fetcher-parser/Output -w ../../onhm-fetcher-parser/Data/weights.csv
### Additional examples: https://github.com/nhm-usgs/gridmetetl/blob/master/Examples/Example_code_usage.ipynb
- TODO
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.