Correctly populate product fill values in geocoded datasets

src/compass/utils/h5_helpers.py

@@ -79,6 +79,33 @@ def add_dataset_and_attrs(group, meta_item):
         val_ds.attrs[key] = _as_np_string_if_needed(val)
 
 
+def _determine_fill_value(dtype):
+    '''
+    Helper function to determine COMPASS specific fill values based on h5py
+    Dataset type (dtype)
+    '''
+    # Possible float types and float fill
+    float_types = [np.double, np.single, np.float32, np.float64, 'float32',
+                   'float64']
+    float_fill = np.nan
+
+    # Possible complex types and complex fill
+    complex_types = [np.complex128, 'complex64', np.complex64, 'complex32']
+    complex_fill = np.nan * (0 + 1j)
+
+    # Possible int types and int fill
+    int_types = [np.byte, np.int8]
+    int_fill = 127
+
+    # Iterate through all types and their fill values, then return the fill
+    # value when a match is found
+    for types, fill_val in zip([float_types, complex_types, int_types],
+                               [float_fill, complex_fill, int_fill]):
+        if any([dtype == t for t in types]):
+            print(dtype)
+            return fill_val
+
+
 def init_geocoded_dataset(grid_group, dataset_name, geo_grid, dtype,
                           description, data=None, output_cfg=None):
     '''
@@ -160,6 +187,7 @@ def init_geocoded_dataset(grid_group, dataset_name, geo_grid, dtype,
     # Associate grid mapping with data - projection created later
     cslc_ds.attrs['grid_mapping'] = np.string_("projection")
 
+    # Build list of metadata to be inserted to accompany dataset
     grid_meta_items = [
         Meta('x_spacing', geo_grid.spacing_x,
              'Spacing of the geographical grid along X-direction',