Moved 'Data' variable to band group

gts2_client/gts2_client.py

@@ -609,12 +609,11 @@ def json_to_netcdf(out_mode, api_result, outpath, out_prefix, geo_ll, geo_ur, st
                                     [setattr(data_info_group, attr, api_result[key][tile][band][data_info][attr])
                                      for attr in api_result[key][tile][band][data_info].keys()]
                                 if data_info == 'data':
-                                    data_group = band_group.createGroup(data_info)
                                     band_arr = np.asarray(api_result[key][tile][band][data_info])
-                                    data_group.createDimension('x', band_arr.shape[2])
-                                    data_group.createDimension('y', band_arr.shape[1])
-                                    data_group.createDimension('t', band_arr.shape[0])
-                                    data = data_group.createVariable('Data', 'i4', ('x', 'y', 't'), fill_value=255)
+                                    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)
                                     data.units = "None"
                                     if level == "L1C":
                                         data.long_name = "Top of Atmosphere Reflectance"
@@ -625,9 +624,9 @@ def json_to_netcdf(out_mode, api_result, outpath, out_prefix, geo_ll, geo_ur, st
                                     data.valid_range = np.array((-2000.0, 16000.0))
                                     data.actual_range = np.array((np.min(band_arr), np.max(band_arr)))
                                     data[:, :, :] = band_arr
-                                    data_group.Band = band.split("_")[0].split("B")[-1]
-                                    data_group.Resolution = band.split("_")[-1]
-                                    data_group.Central_Wavelength = wl[str(band.split("_")[0])]
+                                    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)
@@ -661,12 +660,11 @@ def json_to_netcdf(out_mode, api_result, outpath, out_prefix, geo_ll, geo_ur, st
                                         data_info_group.setncattr_string('time',
                                                                          api_result[key][tile][msk][data_info]['time'])
                                     if data_info == 'data':
-                                        data_group = mask_group.createGroup(data_info)
                                         mask_arr = np.asarray(api_result[key][tile][msk][data_info])
-                                        data_group.createDimension('x', mask_arr.shape[2])
-                                        data_group.createDimension('y', mask_arr.shape[1])
-                                        data_group.createDimension('t', mask_arr.shape[0])
-                                        data = data_group.createVariable('Data', 'i4', ('x', 'y', 't'), fill_value=255)
+                                        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)
                                         data.units = "None"
                                         data.long_name = "Mask classes"
                                         data.standard_name = "classes"