| Next changeset 1:4bb2f6091660 (2019-06-24) |
|
Commit message:
planemo upload for repository https://github.com/NordicESMhub/galaxy-tools/tree/master/tools/mean-per-zone commit 24f20e7459e275c14376680f9bb91cd8ac26d9a5 |
|
added:
README.md mean-per-zone.xml test-data/TM_WORLD_BORDERS_SIMPL-0.3/Readme.txt test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.dbf test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.prj test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shp test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shx test-data/TS.f2000.T31T31.control.cam.h0.0014-12.180.nc test-data/TS.f2000.T31T31.control.cam.h0.0014-12.180.png zonal_statistics.py |
| b |
| diff -r 000000000000 -r 4f14b5b97262 README.md --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/README.md Thu Apr 25 14:32:23 2019 -0400 |
| b |
| @@ -0,0 +1,8 @@ + +# Zonal statistics + +This tool allows to compute zonal statistics from geospatial raster data +based on vector geometries (shapefile). +The raster input file must be in netCDF format with geographical coordinates +(latitudes, longitudes) with the same coordinate reference system as the +shapefile. |
| b |
| diff -r 000000000000 -r 4f14b5b97262 mean-per-zone.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/mean-per-zone.xml Thu Apr 25 14:32:23 2019 -0400 |
| [ |
| @@ -0,0 +1,102 @@ +<tool id="mean_per_zone" name="zonal statistics" version="0.1.0"> + <description>over each area</description> + <requirements> + <requirement type="package" version="3">python</requirement> + <requirement type="package" version="0.13.1">rasterstats</requirement> + <requirement type="package" version="0.4.1">geopandas</requirement> + <requirement type="package" version="0.11.3">xarray</requirement> + <requirement type="package" version="1.4.3.2">netcdf4</requirement> + </requirements> + <command detect_errors="exit_code"><![CDATA[ + mkdir -p shp_tmp && + ln -s '$shapefile' 'shp_tmp/temp.shp' && + ln -s '$shapefilex' 'shp_tmp/temp.shx' && + python3 '$__tool_directory__/zonal_statistics.py' + '$ifilename' + 'shp_tmp' + '$variable' + '$ofilename' + --stat '$stat_type' + #if str($title).strip() != '' + --title '$title' + #end if + ]]></command> + <inputs> + <param name="ifilename" type="data" format="netcdf,h5" label="input with geographical coordinates (netCDF format)"/> + <param name="shapefile" type="data" format="binary" label="shapefile (shp) with polygons for which statistics will be computed"/> + <param name="shapefilex" type="data" format="binary" label="shapefile (shx) with polygons for which statistics will be computed"/> + <!--param name="name" type="text" value="" label="Shapefile name" /--> + <param name="variable" type="text" value="TS" label="variable name as given in the netCDF file" /> + <param name="title" type="text" value="" label="Title of the generated plot" /> + <param name="stat_type" type="select"> + <option value="min" selected="true">minimum</option> + <option value="max" selected="true">maximum</option> + <option value="mean" selected="true">mean</option> + <option value="count" selected="true">count</option> + </param> + </inputs> + <outputs> + <data name="ofilename" format="png"></data> + </outputs> + <tests> + <test> + <param name="ifilename" value="TS.f2000.T31T31.control.cam.h0.0014-12.180.nc" /> + <param name="variable" value="TS" /> + <param name="title" value="Mean Surface Temperature per country" /> + <param name="shapefile" value="TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shp" /> + <param name="shapefilex" value="TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shx" /> + <param name="name" value="TM_WORLD_BORDERS_SIMPL-0.3" /> + <output name="ofilename" ftype="png" file="TS.f2000.T31T31.control.cam.h0.0014-12.180.png" compare="sim_size" delta="1500"/> + </test> + </tests> + <help><![CDATA[ + +**Plot statistics** +================================================ + +This tool wraps the functionality of ``zonal-statistics.py``. + + +.. class:: infomark + + The wrapper aims at providing a utility to extract information + from geospatial raster data based on vector geometries (shapefile). + The raster input file must be in netCDF format with geographical coordinates + (latitudes, longitudes) with the same coordinate reference system as the + shapefile. + +**What it does** +---------------- + +This tools creates a png image showing statistic over areas as defined in the +vector file. + +**Usage** + +:: + + usage: zonal-statistics.py [-h] [-v] [-t] raster vector variable output + + +Positional arguments: +~~~~~~~~~~~~~~~~~~~~~ + +- **raster**: input raster filename with geographical coordinates (netCDF format) +- **vector**: input raster filename with polygons +- **variable**: variable used from raster file to compute statistics +- **output**: output filename for png file containing the resulting plot. + +Optional arguments: +~~~~~~~~~~~~~~~~~~~~~ + + -h, --help show this help message and exit + -v, --verbose switch on verbose mode + -t, --type statistic type [min, max, mean, count] + +It uses ``rasterstats`` python package to compute zonal statistics. +More information about ``rasterstats`` can be found at https://pythonhosted.org/rasterstats + + ]]></help> + <citations> + </citations> +</tool> |
| b |
| diff -r 000000000000 -r 4f14b5b97262 test-data/TM_WORLD_BORDERS_SIMPL-0.3/Readme.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/TM_WORLD_BORDERS_SIMPL-0.3/Readme.txt Thu Apr 25 14:32:23 2019 -0400 |
| b |
| @@ -0,0 +1,72 @@ +TM_WORLD_BORDERS-0.1.ZIP + +http://thematicmapping.org/downloads/world_borders.php + +Provided by Bjorn Sandvik, thematicmapping.org + +Use this dataset with care, as several of the borders are disputed. + +The original shapefile (world_borders.zip, 3.2 MB) was downloaded from the Mapping Hacks website: +http://www.mappinghacks.com/data/ + +The dataset was derived by Schuyler Erle from public domain sources. +Sean Gilles did some clean up and made some enhancements. + + +COLUMN TYPE DESCRIPTION + +Shape Polygon Country/area border as polygon(s) +FIPS String(2) FIPS 10-4 Country Code +ISO2 String(2) ISO 3166-1 Alpha-2 Country Code +ISO3 String(3) ISO 3166-1 Alpha-3 Country Code +UN Short Integer(3) ISO 3166-1 Numeric-3 Country Code +NAME String(50) Name of country/area +AREA Long Integer(7) Land area, FAO Statistics (2002) +POP2005 Double(10,0) Population, World Polulation Prospects (2005) +REGION Short Integer(3) Macro geographical (continental region), UN Statistics +SUBREGION Short Integer(3) Geogrpahical sub-region, UN Statistics +LON FLOAT (7,3) Longitude +LAT FLOAT (6,3) Latitude + + +CHANGELOG VERSION 0.3 - 30 July 2008 + +- Corrected spelling mistake (United Arab Emirates) +- Corrected population number for Japan +- Adjusted long/lat values for India, Italy and United Kingdom + + +CHANGELOG VERSION 0.2 - 1 April 2008 + +- Made new ZIP archieves. No change in dataset. + + +CHANGELOG VERSION 0.1 - 13 March 2008 + +- Polygons representing each country were merged into one feature +- �land Islands was extracted from Finland +- Hong Kong was extracted from China +- Holy See (Vatican City) was added +- Gaza Strip and West Bank was merged into "Occupied Palestinean Territory" +- Saint-Barthelemy was extracted from Netherlands Antilles +- Saint-Martin (Frensh part) was extracted from Guadeloupe +- Svalbard and Jan Mayen was merged into "Svalbard and Jan Mayen Islands" +- Timor-Leste was extracted from Indonesia +- Juan De Nova Island was merged with "French Southern & Antarctic Land" +- Baker Island, Howland Island, Jarvis Island, Johnston Atoll, Midway Islands + and Wake Island was merged into "United States Minor Outlying Islands" +- Glorioso Islands, Parcel Islands, Spartly Islands was removed + (almost uninhabited and missing ISO-3611-1 code) + +- Added ISO-3166-1 codes (alpha-2, alpha-3, numeric-3). Source: + https://www.cia.gov/library/publications/the-world-factbook/appendix/appendix-d.html + http://unstats.un.org/unsd/methods/m49/m49alpha.htm + http://www.fysh.org/~katie/development/geography.txt +- AREA column has been replaced with data from UNdata: + Land area, 1000 hectares, 2002, FAO Statistics +- POPULATION column (POP2005) has been replaced with data from UNdata: + Population, 2005, Medium variant, World Population Prospects: The 2006 Revision +- Added region and sub-region codes from UN Statistics Division. Source: + http://unstats.un.org/unsd/methods/m49/m49regin.htm +- Added LAT, LONG values for each country + |
| b |
| diff -r 000000000000 -r 4f14b5b97262 test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.dbf |
| b |
| Binary file test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.dbf has changed |
| b |
| diff -r 000000000000 -r 4f14b5b97262 test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.prj --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.prj Thu Apr 25 14:32:23 2019 -0400 |
| [ |
| @@ -0,0 +1,1 @@ +GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]] \ No newline at end of file |
| b |
| diff -r 000000000000 -r 4f14b5b97262 test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shp |
| b |
| Binary file test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shp has changed |
| b |
| diff -r 000000000000 -r 4f14b5b97262 test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shx |
| b |
| Binary file test-data/TM_WORLD_BORDERS_SIMPL-0.3/TM_WORLD_BORDERS_SIMPL-0.3.shx has changed |
| b |
| diff -r 000000000000 -r 4f14b5b97262 test-data/TS.f2000.T31T31.control.cam.h0.0014-12.180.nc |
| b |
| Binary file test-data/TS.f2000.T31T31.control.cam.h0.0014-12.180.nc has changed |
| b |
| diff -r 000000000000 -r 4f14b5b97262 test-data/TS.f2000.T31T31.control.cam.h0.0014-12.180.png |
| b |
| Binary file test-data/TS.f2000.T31T31.control.cam.h0.0014-12.180.png has changed |
| b |
| diff -r 000000000000 -r 4f14b5b97262 zonal_statistics.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/zonal_statistics.py Thu Apr 25 14:32:23 2019 -0400 |
| [ |
| @@ -0,0 +1,79 @@ +#!/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') |
