Mercurial > repos > climate > mean_per_zone
view zonal_statistics.py @ 0:4f14b5b97262 draft
planemo upload for repository https://github.com/NordicESMhub/galaxy-tools/tree/master/tools/mean-per-zone commit 24f20e7459e275c14376680f9bb91cd8ac26d9a5
author | climate |
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date | Thu, 25 Apr 2019 14:32:23 -0400 |
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#!/usr/bin/env python3 import argparse import warnings import geopandas import matplotlib as mpl mpl.use('Agg') from matplotlib import pyplot # noqa: I202,E402 import pandas as pd # noqa: I202,E402 from rasterstats import zonal_stats # noqa: I202,E402 import xarray as xr # noqa: I202,E402 if __name__ == '__main__': warnings.filterwarnings("ignore") parser = argparse.ArgumentParser() parser.add_argument( 'raster', help='input raster file with geographical coordinates (netCDF format)' ) parser.add_argument( 'shapefile', help='input shapefile name with polygons ' ) parser.add_argument( 'variable', help='name of the variable in raster file' ) parser.add_argument( 'output', help='output filename to store resulting image (png format)' ) parser.add_argument( '-s', '--stat', help='type of statistics [min, max, mean, count]' ) parser.add_argument( '-t', '--title', help='title for the generated plot' ) parser.add_argument("-v", "--verbose", help="switch on verbose mode", action="store_true") args = parser.parse_args() if args.stat is None: stat_type = 'mean' else: stat_type = args.stat dset = xr.open_dataset(args.raster) dset[args.variable].to_netcdf(".tmp.nc") zs = zonal_stats(args.shapefile, ".tmp.nc", stats=stat_type) df_zonal_stats = pd.DataFrame(zs) world = geopandas.read_file(args.shapefile) df = pd.concat([world, df_zonal_stats], axis=1) ddf = df.dropna() f, ax = pyplot.subplots(1, figsize=(20, 10)) visu = ddf.plot(column=stat_type, scheme='Quantiles', k=15, cmap='jet', legend=True, ax=ax, legend_kwds={'loc': 'lower left', 'frameon': True, 'title': args.variable, 'bbox_to_anchor': (1, 0.05) } ) # plot done ax.set_xlabel("Longitude") ax.set_ylabel("Latitude") if args.title is None: f.suptitle(stat_type + " computed over areas") else: f.suptitle(args.title) if args.verbose: print("plot generated") pyplot.savefig(args.output, format='png')