Refactor the AWS/EPS-STerna tests

Signed-off-by: Adam.Dybbroe <[email protected]>

satpy/tests/reader_tests/conftest.py

@@ -36,11 +36,7 @@
 
 platform_name = "AWS1"
 # W_XX-EUMETSAT-Darmstadt,SAT,AWS1-MWR-1B-RAD_C_EUMT_20241121085911_G_D_20241109234502_20241110004559_T_N____.nc
-eumetsat_file_pattern = "W_XX-EUMETSAT-Darmstadt,SAT,{platform_name}-MWR-1B-RAD_C_OHB_{processing_time:%Y%m%d%H%M%S}_G_D_{start_time:%Y%m%d%H%M%S}_{end_time:%Y%m%d%H%M%S}_T_B____.nc"  # noqa
-
-esa_file_pattern = "W_XX-OHB-Stockholm,SAT,{platform_name}-MWR-1B-RAD_C_OHB_{processing_time:%Y%m%d%H%M%S}_G_D_{start_time:%Y%m%d%H%M%S}_{end_time:%Y%m%d%H%M%S}_T_B____.nc"  # noqa
-
-esa_l1c_file_pattern = "W_XX-OHB-Stockholm,SAT,{platform_name}-MWR-1C-RAD_C_OHB__{processing_time:%Y%m%d%H%M%S}_G_D_{start_time:%Y%m%d%H%M%S}_{end_time:%Y%m%d%H%M%S}_T_B____.nc"  # noqa
+file_pattern = "W_{country:2s}-{organisation:s}-{location:s},SAT,{platform_name}-MWR-{processing_level}-RAD_C_{originator:4s}_{processing_time:%Y%m%d%H%M%S}_G_D_{start_time:%Y%m%d%H%M%S}_{end_time:%Y%m%d%H%M%S}_T_B____.nc"  # noqa
 
 
 rng = np.random.default_rng()
@@ -93,124 +89,105 @@ def make_fake_mwr_l1c_lonlats(geo_size, geo_dims):
     return (fake_lon_data, fake_lat_data)
 
 
-@pytest.fixture(scope="module")
-def eps_sterna_mwr_file(tmp_path_factory, fake_mwr_data_array):
-    """Create an EPS-Sterna MWR l1b file."""
-    geo_dims = ["n_scans", "n_fovs", "n_feedhorns"]
+def aws_eps_sterna_mwr_l1bfile(fake_mwr_data_array, eps_sterna=True):
+    """Create an AWS and EPS-Sterna MWR l1b file."""
+    if eps_sterna:
+        n_feedhorns="n_feedhorns"
+        prefix = ""
+        longitude_attr = "longitude"
+        latitude_attr = "latitude"
+    else:
+        n_feedhorns="n_geo_groups"
+        prefix = "aws_"
+        longitude_attr = "aws_lon"
+        latitude_attr = "aws_lat"
+
+    geo_dims = ["n_scans", "n_fovs", n_feedhorns]
     geo_size = 10 * 145 * 4
 
     ds = DataTree()
     start_time = dt(2024, 9, 1, 12, 0)
     ds.attrs["sensing_start_time_utc"] = start_time.strftime(DATETIME_FORMAT)
     end_time = dt(2024, 9, 1, 12, 15)
     ds.attrs["sensing_end_time_utc"] = end_time.strftime(DATETIME_FORMAT)
-    processing_time = random_date(dt(2024, 9, 1, 13), dt(2030, 6, 1))
 
     instrument = "MWR"
     ds.attrs["instrument"] = instrument
     ds.attrs["orbit_start"] = 9991
     ds.attrs["orbit_end"] = 9992
-    ds["data/calibration/toa_brightness_temperature"] = fake_mwr_data_array
-    ds["data/calibration/toa_brightness_temperature"].attrs["scale_factor"] = 0.001
-    ds["data/calibration/toa_brightness_temperature"].attrs["add_offset"] = 0.0
-    ds["data/calibration/toa_brightness_temperature"].attrs["missing_value"] = -2147483648
-    ds["data/calibration/toa_brightness_temperature"].attrs["valid_min"] = 0
-    ds["data/calibration/toa_brightness_temperature"].attrs["valid_max"] = 700000
+    dset_name = f"data/calibration/{prefix}toa_brightness_temperature"
+    ds[dset_name] = fake_mwr_data_array
+    ds[dset_name].attrs["scale_factor"] = 0.001
+    ds[dset_name].attrs["add_offset"] = 0.0
+    ds[dset_name].attrs["missing_value"] = -2147483648
+    ds[dset_name].attrs["valid_min"] = 0
+    ds[dset_name].attrs["valid_max"] = 700000
 
     fake_lon_data, fake_lat_data = make_fake_mwr_lonlats(geo_size, geo_dims)
 
-    ds["data/navigation/longitude"] = fake_lon_data
-    ds["data/navigation/longitude"].attrs["scale_factor"] = 1e-4
-    ds["data/navigation/longitude"].attrs["add_offset"] = 0.0
-    ds["data/navigation/latitude"] = fake_lat_data
-    ds["data/navigation/solar_azimuth_angle"] = make_fake_angles(geo_size, geo_dims)
-    ds["data/navigation/solar_zenith_angle"] = make_fake_angles(geo_size, geo_dims)
-    ds["data/navigation/satellite_azimuth_angle"] = make_fake_angles(geo_size, geo_dims)
-    ds["data/navigation/satellite_zenith_angle"] = make_fake_angles(geo_size, geo_dims)
+    ds[f"data/navigation/{longitude_attr}"] = fake_lon_data
+    ds[f"data/navigation/{longitude_attr}"].attrs["scale_factor"] = 1e-4
+    ds[f"data/navigation/{longitude_attr}"].attrs["add_offset"] = 0.0
+    ds[f"data/navigation/{latitude_attr}"] = fake_lat_data
+    ds[f"data/navigation/{prefix}solar_azimuth_angle"] = make_fake_angles(geo_size, geo_dims)
+    ds[f"data/navigation/{prefix}solar_zenith_angle"] = make_fake_angles(geo_size, geo_dims)
+    ds[f"data/navigation/{prefix}satellite_azimuth_angle"] = make_fake_angles(geo_size, geo_dims)
+    ds[f"data/navigation/{prefix}satellite_zenith_angle"] = make_fake_angles(geo_size, geo_dims)
     ds["status/satellite/subsat_latitude_end"] = np.array(22.39)
     ds["status/satellite/subsat_longitude_start"] = np.array(304.79)
     ds["status/satellite/subsat_latitude_start"] = np.array(55.41)
     ds["status/satellite/subsat_longitude_end"] = np.array(296.79)
 
-    tmp_dir = tmp_path_factory.mktemp("eps_sterna_mwr_l1b_tests")
-    filename = tmp_dir / compose(eumetsat_file_pattern, dict(start_time=start_time, end_time=end_time,
-                                                             processing_time=processing_time,
-                                                             platform_name=platform_name))
-
-    ds.to_netcdf(filename)
-    return filename
-
+    return ds
 
 @pytest.fixture(scope="module")
-def eps_sterna_mwr_handler(eps_sterna_mwr_file):
-    """Create an EPS-Sterna MWR filehandler."""
-    filename_info = parse(eumetsat_file_pattern, os.path.basename(eps_sterna_mwr_file))
-    filetype_info = dict()
-    filetype_info["file_type"] = "eps_sterna_mwr_l1b"
-    return AWS_EPS_Sterna_MWR_L1BFile(eps_sterna_mwr_file, filename_info, filetype_info)
+def eps_sterna_mwr_file(tmp_path_factory, fake_mwr_data_array):
+    """Create an EPS-Sterna MWR l1b file."""
+    ds = aws_eps_sterna_mwr_l1bfile(fake_mwr_data_array, eps_sterna=True)
 
+    tmp_dir = tmp_path_factory.mktemp("eps_sterna_mwr_l1b_tests")
+    start_time = dt.fromisoformat(ds.attrs["sensing_start_time_utc"])
+    end_time = dt.fromisoformat(ds.attrs["sensing_end_time_utc"])
+    platform_name = "AWS1"
+    processing_time = random_date(dt(2024, 9, 1, 13), dt(2030, 6, 1))
+    filename = tmp_dir / compose(file_pattern, dict(country="XX",
+                                                    organisation="EUMETSAT",
+                                                    location="Darmstadt",
+                                                    processing_level="1B",
+                                                    originator="EUMT",
+                                                    start_time=start_time, end_time=end_time,
+                                                    processing_time=processing_time,
+                                                    platform_name=platform_name))
+    ds.to_netcdf(filename)
+    return filename
 
 @pytest.fixture(scope="module")
 def aws_mwr_file(tmp_path_factory, fake_mwr_data_array):
     """Create an AWS MWR l1b file."""
-    geo_dims = ["n_scans", "n_fovs", "n_geo_groups"]
-    geo_size = 10 * 145 * 4
-
-    ds = DataTree()
-    start_time = dt(2024, 9, 1, 12, 0)
-    ds.attrs["sensing_start_time_utc"] = start_time.strftime(DATETIME_FORMAT)
-    end_time = dt(2024, 9, 1, 12, 15)
-    ds.attrs["sensing_end_time_utc"] = end_time.strftime(DATETIME_FORMAT)
-    processing_time = random_date(dt(2024, 6, 1), dt(2030, 6, 1))
-
-    instrument = "MWR"
-    ds.attrs["instrument"] = instrument
-    ds.attrs["orbit_start"] = 9991
-    ds.attrs["orbit_end"] = 9992
-    ds["data/calibration/aws_toa_brightness_temperature"] = fake_mwr_data_array
-    ds["data/calibration/aws_toa_brightness_temperature"].attrs["scale_factor"] = 0.001
-    ds["data/calibration/aws_toa_brightness_temperature"].attrs["add_offset"] = 0.0
-    ds["data/calibration/aws_toa_brightness_temperature"].attrs["missing_value"] = -2147483648
-    ds["data/calibration/aws_toa_brightness_temperature"].attrs["valid_min"] = 0
-    ds["data/calibration/aws_toa_brightness_temperature"].attrs["valid_max"] = 700000
-
-    fake_lon_data, fake_lat_data = make_fake_mwr_lonlats(geo_size, geo_dims)
-
-    ds["data/navigation/aws_lon"] = fake_lon_data
-    ds["data/navigation/aws_lon"].attrs["scale_factor"] = 1e-4
-    ds["data/navigation/aws_lon"].attrs["add_offset"] = 0.0
-    ds["data/navigation/aws_lat"] = fake_lat_data
-    ds["data/navigation/aws_solar_azimuth_angle"] = make_fake_angles(geo_size, geo_dims)
-    ds["data/navigation/aws_solar_zenith_angle"] = make_fake_angles(geo_size, geo_dims)
-    ds["data/navigation/aws_satellite_azimuth_angle"] = make_fake_angles(geo_size, geo_dims)
-    ds["data/navigation/aws_satellite_zenith_angle"] = make_fake_angles(geo_size, geo_dims)
-    ds["status/satellite/subsat_latitude_end"] = np.array(22.39)
-    ds["status/satellite/subsat_longitude_start"] = np.array(304.79)
-    ds["status/satellite/subsat_latitude_start"] = np.array(55.41)
-    ds["status/satellite/subsat_longitude_end"] = np.array(296.79)
+    ds = aws_eps_sterna_mwr_l1bfile(fake_mwr_data_array, eps_sterna=False)
 
     tmp_dir = tmp_path_factory.mktemp("aws_l1b_tests")
-    filename = tmp_dir / compose(esa_file_pattern, dict(start_time=start_time, end_time=end_time,
-                                                        processing_time=processing_time, platform_name=platform_name))
-
+    start_time = dt.fromisoformat(ds.attrs["sensing_start_time_utc"])
+    end_time = dt.fromisoformat(ds.attrs["sensing_end_time_utc"])
+    platform_name = "AWS1"
+    processing_time = random_date(dt(2024, 9, 1, 13), dt(2030, 6, 1))
+    filename = tmp_dir / compose(file_pattern, dict(country="SE",
+                                                    organisation="SMHI",
+                                                    location="Norrkoping",
+                                                    processing_level="1B",
+                                                    originator="SMHI",
+                                                    start_time=start_time, end_time=end_time,
+                                                    processing_time=processing_time,
+                                                    platform_name=platform_name))
     ds.to_netcdf(filename)
     return filename
 
 
-@pytest.fixture(scope="module")
-def aws_mwr_handler(aws_mwr_file):
-    """Create an AWS MWR filehandler."""
-    filename_info = parse(esa_file_pattern, os.path.basename(aws_mwr_file))
-    filetype_info = dict()
-    filetype_info["file_type"] = "aws1_mwr_l1b"
-    return AWS_EPS_Sterna_MWR_L1BFile(aws_mwr_file, filename_info, filetype_info)
-
-
 @pytest.fixture(scope="module")
 def aws_mwr_l1c_file(tmp_path_factory, fake_mwr_data_array):
     """Create an AWS MWR l1c file."""
     geo_dims = ["n_scans", "n_fovs"]
-    geo_size = 10*145
+    geo_size = 10 * 145
 
     ds = DataTree()
     start_time = dt(2024, 9, 1, 12, 0)
@@ -241,18 +218,40 @@ def aws_mwr_l1c_file(tmp_path_factory, fake_mwr_data_array):
     ds["data/navigation/aws_satellite_zenith_angle"] = make_fake_angles(geo_size, geo_dims, shape=(10, 145))
 
     tmp_dir = tmp_path_factory.mktemp("aws_l1c_tests")
-    filename = tmp_dir / compose(esa_l1c_file_pattern, dict(start_time=start_time, end_time=end_time,
-                                                            processing_time=processing_time,
-                                                            platform_name=platform_name))
-
+    filename = tmp_dir / compose(file_pattern, dict(country="SE",
+                                                    organisation="SMHI",
+                                                    location="Norrkoping",
+                                                    processing_level="1C",
+                                                    originator="SMHI",
+                                                    start_time=start_time, end_time=end_time,
+                                                    processing_time=processing_time,
+                                                    platform_name=platform_name))
     ds.to_netcdf(filename)
     return filename
 
 
+@pytest.fixture(scope="module")
+def eps_sterna_mwr_handler(eps_sterna_mwr_file):
+    """Create an EPS-Sterna MWR filehandler."""
+    filename_info = parse(file_pattern, os.path.basename(eps_sterna_mwr_file))
+    filetype_info = dict()
+    filetype_info["file_type"] = "eps_sterna_mwr_l1b"
+    return AWS_EPS_Sterna_MWR_L1BFile(eps_sterna_mwr_file, filename_info, filetype_info)
+
+
+@pytest.fixture(scope="module")
+def aws_mwr_handler(aws_mwr_file):
+    """Create an AWS MWR filehandler."""
+    filename_info = parse(file_pattern, os.path.basename(aws_mwr_file))
+    filetype_info = dict()
+    filetype_info["file_type"] = "aws1_mwr_l1b"
+    return AWS_EPS_Sterna_MWR_L1BFile(aws_mwr_file, filename_info, filetype_info)
+
+
 @pytest.fixture(scope="module")
 def aws_mwr_l1c_handler(aws_mwr_l1c_file):
     """Create an AWS MWR level-1c filehandler."""
-    filename_info = parse(esa_l1c_file_pattern, os.path.basename(aws_mwr_l1c_file))
+    filename_info = parse(file_pattern, os.path.basename(aws_mwr_l1c_file))
     filetype_info = dict()
     filetype_info["file_type"] = "aws1_mwr_l1c"
     return AWS_MWR_L1CFile(aws_mwr_l1c_file, filename_info, filetype_info)