Soft coded fill values and data ranges

gts2_client/gts2_client.py

@@ -613,7 +613,8 @@ def json_to_netcdf(out_mode, api_result, outpath, out_prefix, geo_ll, geo_ur, st
                                     band_group.createDimension('x', band_arr.shape[2])
                                     band_group.createDimension('y', band_arr.shape[1])
                                     band_group.createDimension('t', band_arr.shape[0])
-                                    data = band_group.createVariable('Data', 'i4', ('x', 'y', 't'), fill_value=255)
+                                    fill = api_result[key][tile][band]['fill_value']
+                                    data = band_group.createVariable('Data', 'i4', ('x', 'y', 't'), fill_value=fill)
                                     data.units = "None"
                                     if level == "L1C":
                                         data.long_name = "Top of Atmosphere Reflectance"
@@ -621,13 +622,12 @@ def json_to_netcdf(out_mode, api_result, outpath, out_prefix, geo_ll, geo_ur, st
                                     else:
                                         data.long_name = "Surface Reflectance"
                                         data.standard_name = "boa_reflectance"
-                                    data.valid_range = np.array((-2000.0, 16000.0))
-                                    data.actual_range = np.array((np.min(band_arr), np.max(band_arr)))
+                                    masked_fill = np.ma.masked_equal(band_arr, fill)
+                                    data.data_range = np.array((np.min(masked_fill), np.max(masked_fill)))
                                     data[:, :, :] = band_arr
                                     band_group.Band = band.split("_")[0].split("B")[-1]
                                     band_group.Resolution = band.split("_")[-1]
                                     band_group.Central_Wavelength = wl[str(band.split("_")[0])]
-
                 if key == 'Metadata':
                     key_group = f.createGroup(key)
                     for tile in api_result[key].keys():
@@ -664,15 +664,16 @@ def json_to_netcdf(out_mode, api_result, outpath, out_prefix, geo_ll, geo_ur, st
                                         mask_group.createDimension('x', mask_arr.shape[2])
                                         mask_group.createDimension('y', mask_arr.shape[1])
                                         mask_group.createDimension('t', mask_arr.shape[0])
-                                        data = mask_group.createVariable('Data', 'i4', ('x', 'y', 't'), fill_value=255)
+                                        fill = api_result[key][tile][msk]['fill_value']
+                                        data = mask_group.createVariable('Data', 'i4', ('x', 'y', 't'), fill_value=fill)
                                         data.units = "None"
                                         data.long_name = "Mask classes"
                                         data.standard_name = "classes"
-                                        data.valid_range = np.array((10.0, 60.0))
-                                        data.actual_range = np.array((np.min(mask_arr), np.max(mask_arr)))
+                                        masked_fill = np.ma.masked_equal(mask_arr, fill)
+                                        data.data_range = np.array((np.min(masked_fill), np.max(masked_fill)))
                                         data[:, :, :] = mask_arr
             f.close()
-        except:
+        except Exception:
             raise Exception("Something went wrong while saving as netcdf. " + traceback.format_exc())