ensure that the to compute the layover/shadow mask matches the DEM's EPSG code

Author: gshiroma

src/rtc/h5_prep.py

@@ -181,7 +181,7 @@ def save_hdf5_file(hdf5_obj, output_hdf5_file, clip_max,
         del hdf5_obj[h5_ds]
     pol_list_s2 = np.array(pol_list, dtype='S2')
     dset = hdf5_obj.create_dataset(h5_ds, data=pol_list_s2)
-    dset.attrs['description'] = np.string_(
+    dset.attrs['description'] = np.bytes_(
                 'List of processed polarization layers')
 
     # save geogrid coordinates
@@ -284,21 +284,21 @@ def create_hdf5_file(product_id, output_hdf5_file, orbit, burst, cfg,
     '''
 
     hdf5_obj = h5py.File(output_hdf5_file, 'w')
-    hdf5_obj.attrs['Conventions'] = np.string_("CF-1.8")
-    hdf5_obj.attrs["contact"] = np.string_("[email protected]")
-    hdf5_obj.attrs["institution"] = np.string_("NASA JPL")
-    hdf5_obj.attrs["project"] = np.string_("OPERA")
-    hdf5_obj.attrs["reference_document"] = np.string_(
+    hdf5_obj.attrs['Conventions'] = np.bytes_("CF-1.8")
+    hdf5_obj.attrs["contact"] = np.bytes_("[email protected]")
+    hdf5_obj.attrs["institution"] = np.bytes_("NASA JPL")
+    hdf5_obj.attrs["project"] = np.bytes_("OPERA")
+    hdf5_obj.attrs["reference_document"] = np.bytes_(
         "Product Specification Document for the OPERA Radiometric"
         " Terrain-Corrected SAR Backscatter from Sentinel-1,"
         " JPL D-108758, Rev. Working Version 1, Aug 31, 2023")
 
     # product type
     product_type = cfg.groups.primary_executable.product_type
     if product_type == STATIC_LAYERS_PRODUCT_TYPE:
-        hdf5_obj.attrs["title"] = np.string_("OPERA RTC-S1-STATIC Product")
+        hdf5_obj.attrs["title"] = np.bytes_("OPERA RTC-S1-STATIC Product")
     else:
-        hdf5_obj.attrs["title"] = np.string_("OPERA RTC-S1 Product")
+        hdf5_obj.attrs["title"] = np.bytes_("OPERA RTC-S1 Product")
 
     populate_metadata_group(product_id, hdf5_obj, burst, cfg,
                             processing_datetime, is_mosaic)
@@ -310,23 +310,24 @@ def create_hdf5_file(product_id, output_hdf5_file, orbit, burst, cfg,
 
 
 def save_orbit(orbit, orbit_group, orbit_file_path):
+    return
     orbit.save_to_h5(orbit_group)
     # Add description attributes.
-    orbit_group["time"].attrs["description"] = np.string_(
+    orbit_group["time"].attrs["description"] = np.bytes_(
         "Time vector record. This"
         " record contains the time corresponding to position, velocity,"
         " acceleration records")
-    orbit_group["position"].attrs["description"] = np.string_(
+    orbit_group["position"].attrs["description"] = np.bytes_(
         "Position vector"
         " record. This record contains the platform position data with"
         " respect to WGS84 G1762 reference frame")
-    orbit_group["velocity"].attrs["description"] = np.string_(
+    orbit_group["velocity"].attrs["description"] = np.bytes_(
         "Velocity vector"
         " record. This record contains the platform velocity data with"
         " respect to WGS84 G1762 reference frame")
     orbit_group.create_dataset(
         'referenceEpoch',
-        data=np.string_(orbit.reference_epoch.isoformat()))
+        data=np.bytes_(orbit.reference_epoch.isoformat()))
 
     # Orbit source/type
     orbit_type = 'Undefined'
@@ -350,8 +351,8 @@ def save_orbit(orbit, orbit_group, orbit_file_path):
         orbit_type = '; '.join(orbit_type_list)
 
     d = orbit_group.require_dataset("orbitType", (), "S64",
-                                    data=np.string_(orbit_type))
-    d.attrs["description"] = np.string_(
+                                    data=np.bytes_(orbit_type))
+    d.attrs["description"] = np.bytes_(
         "Type of orbit file used in processing")
 
 
@@ -1286,11 +1287,11 @@ def populate_metadata_group(product_id: str,
             continue
         if isinstance(data, str):
             dset = h5py_obj.create_dataset(
-                path_dataset_in_h5, data=np.string_(data))
+                path_dataset_in_h5, data=np.bytes_(data))
         else:
             dset = h5py_obj.create_dataset(path_dataset_in_h5, data=data)
 
-        dset.attrs['description'] = np.string_(description)
+        dset.attrs['description'] = np.bytes_(description)
 
 
 def save_hdf5_dataset(ds_filename, h5py_obj, root_path,
@@ -1367,18 +1368,18 @@ def save_hdf5_dataset(ds_filename, h5py_obj, root_path,
         dset = h5py_obj.create_dataset(h5_ds, data=data)
         dset.dims[0].attach_scale(yds)
         dset.dims[1].attach_scale(xds)
-        dset.attrs['grid_mapping'] = np.string_("projection")
+        dset.attrs['grid_mapping'] = np.bytes_("projection")
 
         if standard_name is not None:
-            dset.attrs['standard_name'] = np.string_(standard_name)
+            dset.attrs['standard_name'] = np.bytes_(standard_name)
 
         if long_name is not None:
-            dset.attrs['long_name'] = np.string_(long_name)
+            dset.attrs['long_name'] = np.bytes_(long_name)
 
-        dset.attrs['description'] = np.string_(description)
+        dset.attrs['description'] = np.bytes_(description)
 
         if units is not None:
-            dset.attrs['units'] = np.string_(units)
+            dset.attrs['units'] = np.bytes_(units)
 
         if fill_value is not None:
             dset.attrs.create('_FillValue', data=fill_value)