diff xarray_info.py @ 4:b393815e4cb7 draft default tip

planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/data_manipulation/xarray/ commit fd8ad4d97db7b1fd3876ff63e14280474e06fdf7

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/xarray_info.py	Sun Jul 31 21:20:41 2022 +0000
@@ -0,0 +1,107 @@
+# xarray tool for:
+# - getting metadata information
+# - select data and save results in csv file for further post-processing
+
+import argparse
+import csv
+import os
+import warnings
+
+import xarray as xr
+
+
+class XarrayInfo ():
+    def __init__(self, infile, outfile_info="", outfile_summary="",
+                 verbose=False, coords_info=None):
+        self.infile = infile
+        self.outfile_info = outfile_info
+        self.outfile_summary = outfile_summary
+        self.coords_info = coords_info
+        self.verbose = verbose
+        # initialization
+        self.dset = None
+        self.gset = None
+        if self.verbose:
+            print("infile: ", self.infile)
+            print("outfile_info: ", self.outfile_info)
+            print("outfile_summary: ", self.outfile_summary)
+            print("coords_info: ", self.coords_info)
+
+    def info(self):
+        f = open(self.outfile_info, 'w')
+        ds = xr.open_dataset(self.infile)
+        ds.info(f)
+        f.close()
+
+    def summary(self):
+        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):
+                line.append(s)
+                line.append(d)
+            writer.writerow(line)
+        for name, da in ds.coords.items():
+            line = [name]
+            line.append(len(ds[name].shape))
+            for d, s in zip(da.shape, da.sizes):
+                line.append(s)
+                line.append(d)
+            writer.writerow(line)
+        f.close()
+
+    def get_coords_info(self):
+        ds = xr.open_dataset(self.infile)
+        for c in ds.coords:
+            filename = os.path.join(self.coords_info,
+                                    c.strip() +
+                                    '.tabular')
+            pd = ds.coords[c].to_pandas()
+            pd.index = range(len(pd))
+            pd.to_csv(filename, header=False, sep='\t')
+
+
+if __name__ == '__main__':
+    warnings.filterwarnings("ignore")
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        'infile',
+        help='netCDF input filename'
+    )
+    parser.add_argument(
+        '--info',
+        help='Output filename where metadata information is stored'
+    )
+    parser.add_argument(
+        '--summary',
+        help='Output filename where data summary information is stored'
+    )
+    parser.add_argument(
+        '--coords_info',
+        help='output-folder where for each coordinate, coordinate values '
+             ' are being printed in the corresponding outputfile'
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        help="switch on verbose mode",
+        action="store_true"
+    )
+    args = parser.parse_args()
+
+    p = XarrayInfo(args.infile, args.info, args.summary,
+                   args.verbose, args.coords_info)
+    if args.info:
+        p.info()
+    elif args.coords_info:
+        p.get_coords_info()
+    if args.summary:
+        p.summary()