comparison xarray_tool.py @ 1:6baac361495b draft

"planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/data_manipulation/xarray/ commit 5cdfeb9e100109892a8490ebb4b9bff498c795b5"

0:225d0d275a24

        f = open(self.outfile_summary, 'w')
        ds = xr.open_dataset(self.infile)
        writer = csv.writer(f, delimiter='\t')
        header = ['VariableName', 'NumberOfDimensions']
        for idx, val in enumerate(ds.dims.items()):
            header.append('Dim'+str(idx)+'Name')
            header.append('Dim'+str(idx)+'Size')
        writer.writerow(header)
        for name, da in ds.data_vars.items():
            line = [name]
            line.append(len(ds[name].shape))
            for d, s in zip(da.shape, da.sizes):

        if (op == 'bi'):
            rl = float(split_filter[3])
        if filter_varname == self.select:
            # filter on values of the selected variable
            if op == 'bi':
                self.dset = self.dset.where((self.dset <= rl) &
                                            (self.dset >= ll))
            elif op == 'le':
                self.dset = self.dset.where(self.dset <= ll)
            elif op == 'ge':
                self.dset = self.dset.where(self.dset >= ll)
            elif op == 'e':

    def selection_from_coords(self):
        fcoords = pd.read_csv(self.coords, sep='\t')
        for row in fcoords.itertuples():
            self.latvalN = row[0]
            self.lonvalE = row[1]
            self.outfile = (self.outputdir + '/' + self.select + '_'
                            + str(row.Index) + '.tabular')
            self.selection()


if __name__ == '__main__':
    warnings.filterwarnings("ignore")

1:6baac361495b

        f = open(self.outfile_summary, 'w')
        ds = xr.open_dataset(self.infile)
        writer = csv.writer(f, delimiter='\t')
        header = ['VariableName', 'NumberOfDimensions']
        for idx, val in enumerate(ds.dims.items()):
            header.append('Dim' + str(idx) + 'Name')
            header.append('Dim' + str(idx) + 'Size')
        writer.writerow(header)
        for name, da in ds.data_vars.items():
            line = [name]
            line.append(len(ds[name].shape))
            for d, s in zip(da.shape, da.sizes):

        if (op == 'bi'):
            rl = float(split_filter[3])
        if filter_varname == self.select:
            # filter on values of the selected variable
            if op == 'bi':
                self.dset = self.dset.where((self.dset <= rl) & (self.dset >= ll))
            elif op == 'le':
                self.dset = self.dset.where(self.dset <= ll)
            elif op == 'ge':
                self.dset = self.dset.where(self.dset >= ll)
            elif op == 'e':

    def selection_from_coords(self):
        fcoords = pd.read_csv(self.coords, sep='\t')
        for row in fcoords.itertuples():
            self.latvalN = row[0]
            self.lonvalE = row[1]
            self.outfile = (self.outputdir + '/' + self.select + '_' + str(row.Index) + '.tabular')
            self.selection()


if __name__ == '__main__':
    warnings.filterwarnings("ignore")