annotate xarray_netcdf2netcdf.py @ 0:fea8a53f8099 draft

"planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/data_manipulation/xarray/ commit 57b6d23e3734d883e71081c78e77964d61be82ba"

#!/usr/bin/env python3
#
#  Apply operations on selected variables
# - scale
# one can also select the range of time (for timeseries)
# to apply these operations over the range only
# when a range of time is selected and when scaling, one
# can choose to save the entire timeseries or
# the selected range only.
# when scaling, one can add additional filters on dimensions
# (typically used to filter over latitudes and longitudes)


import argparse
import warnings

import xarray as xr  # noqa: E402


class netCDF2netCDF ():
    def __init__(self, infile, varname, scale="",
                 output="output.netcdf",
                 write_all=False,
                 filter_list="",
                 verbose=False):
        self.infile = infile
        self.verbose = verbose
        self.varname = varname
        self.write_all = write_all
        self.filter = filter_list
        self.selection = {}
        if scale == "" or scale is None:
            self.scale = 1
        else:
            self.scale = float(scale)
        if output is None:
            self.output = "output.netcdf"
        else:
            self.output = output
        # initialization
        self.dset = None
        self.subset = None
        if self.verbose:
            print("infile: ", self.infile)
            print("varname: ", self.varname)
            print("filter_list: ", self.filter)
            print("scale: ", self.scale)
            print("write_all: ", self.write_all)
            print("output: ", self.output)

    def dimension_selection(self, single_filter):
        split_filter = single_filter.split('#')
        dimension_varname = split_filter[0]
        op = split_filter[1]
        ll = int(split_filter[2])
        if (op == 'sl'):
            rl = int(split_filter[3])
            self.selection[dimension_varname] = slice(ll, rl)
        elif (op == 'to'):
            self.selection[dimension_varname] = slice(None, ll)
        elif (op == 'from'):
            self.selection[dimension_varname] = slice(ll, None)
        elif (op == 'is'):
            self.selection[dimension_varname] = ll

    def filter_selection(self):
        for single_filter in self.filter:
            self.dimension_selection(single_filter)
        if self.write_all:
            self.ds[self.varname] = \
                self.ds[self.varname].isel(self.selection)*self.scale
        else:
            self.dset = \
                self.ds[self.varname].isel(self.selection)*self.scale

    def compute(self):
        if self.dset is None:
            self.ds = xr.open_dataset(self.infile)
            if self.filter:
                self.filter_selection()
                if self.verbose:
                    print(self.selection)
            elif self.write_all is not None:
                self.dset = self.ds[self.varname]

    def save(self):
        if self.write_all:
            self.ds.to_netcdf(self.output)
        else:
            self.dset.to_netcdf(self.output)


if __name__ == '__main__':
    warnings.filterwarnings("ignore")
    parser = argparse.ArgumentParser()
    parser.add_argument(
        'input',
        help='input filename in netCDF format'
    )
    parser.add_argument(
        'varname',
        help='Specify which variable to plot (case sensitive)'
    )
    parser.add_argument(
        '--filter',
        nargs="*",
        help='Filter list variable#operator#value_s#value_e'
    )
    parser.add_argument(
        '--output',
        help='Output filename to store the resulting netCDF file'
    )
    parser.add_argument(
        '--scale',
        help='scale factor to apply to selection (float)'
    )
    parser.add_argument(
        "--write_all",
        help="write all data to netCDF",
        action="store_true")
    parser.add_argument(
        "-v", "--verbose",
        help="switch on verbose mode",
        action="store_true")
    args = parser.parse_args()

    dset = netCDF2netCDF(infile=args.input, varname=args.varname,
                         scale=args.scale, output=args.output,
                         filter_list=args.filter,
                         write_all=args.write_all,
                         verbose=args.verbose)
    dset.compute()
    dset.save()