FillValues: add unittests & small bug fix to make it work

Author: mhidas

ncwriter/template.py

@@ -375,10 +375,10 @@ def createVariables(self, **kwargs):
             if dimensions is None:  # no kwargs in createVariable
                 ncvar = self.ncobj.createVariable(varname, datatype)
             else:
-                var_c_keys = list(self._create_var_opts(var))
+                var_attr = var.get('attributes', {})
+                var_c_keys = list(self._create_var_opts(var_attr))
 
-                var_c_opts = dict(
-                    (x, var[x]) for x in var_c_keys)
+                var_c_opts = {x: var_attr[x] for x in var_c_keys}
 
                 ureq_fillvalue = [
                     x for x in cwargs.keys() if x in self.fill_aliases
@@ -391,11 +391,11 @@ def createVariables(self, **kwargs):
                 var_c_opts.update(cwargs)
 
                 # user precendence
-                if (ureq_fillvalue and vreq_fillvalue):
+                if ureq_fillvalue and vreq_fillvalue:
                     [var_c_opts.pop(x) for x in vreq_fillvalue]
                     fv_val = [var_c_opts.pop(x) for x in ureq_fillvalue]
                     var_c_opts['fill_value'] = fv_val[-1]
-                elif (ureq_fillvalue and not vreq_fillvalue):
+                elif ureq_fillvalue and not vreq_fillvalue:
                     fv_val = [var_c_opts.pop(x) for x in ureq_fillvalue]
                     var_c_opts['fill_value'] = fv_val[-1]
                 else:

test_ncwriter/test_template.py

@@ -173,6 +173,43 @@ def test_create_file(self):
         ds_global_attributes = OrderedDict((k, dataset.getncattr(k)) for k in dataset.ncattrs())
         self.assertEqual(self.global_attributes, ds_global_attributes)
 
+    def test_fill_values(self):
+        template = DatasetTemplate(dimensions={'X': 10})
+        template.variables['X'] = {'dimensions': ['X'],
+                                   'type': 'float32',
+                                   'attributes': {'_FillValue': -999.}
+                                   }
+        x = np.array([-999., -999., -999., -999., -999., 1., 2., 3., 4., 5])
+        template.variables['X']['values'] = x
+        template.to_netcdf(self.temp_nc_file)
+
+        dataset = Dataset(self.temp_nc_file)
+        dsx = dataset.variables['X']
+        self.assertEqual(-999., dsx._FillValue)
+        self.assertIsInstance(dsx[:], np.ma.MaskedArray)
+        self.assertTrue(dsx[:5].mask.all())
+        self.assertTrue((dsx[5:] == x[5:]).all())
+
+    def test_fill_values_from_masked_array(self):
+        template = DatasetTemplate(dimensions={'X': 10})
+        template.variables['X'] = {'dimensions': ['X'],
+                                   'type': 'float32',
+                                   'attributes': {'_FillValue': -999.}
+                                   }
+        x = np.array([-4, -3, -2, -1, 0, 1., 2., 3., 4., 5])
+        template.variables['X']['values'] = np.ma.masked_array(x,
+                                                               mask=[True, True, True, True, True,
+                                                                     False, False, False, False, False]
+                                                               )
+        template.to_netcdf(self.temp_nc_file)
+
+        dataset = Dataset(self.temp_nc_file)
+        dsx = dataset.variables['X']
+        self.assertEqual(-999., dsx._FillValue)
+        self.assertIsInstance(dsx[:], np.ma.MaskedArray)
+        self.assertTrue(dsx[:5].mask.all())
+        self.assertTrue((dsx[5:] == x[5:]).all())
+
 # TODO: add data from multiple numpy arrays
 # e.g. template.add_data(TIME=time_values, TEMP=temp_values, PRES=pres_values)
 # TODO: add data from Pandas dataframe (later...)