def setUpClass(cls): cls.datasetId = 'PODAAC-GHCMC-4FM02' cls.variable = 'sea_ice_fraction' cls.name = 'PO.DAAC_test_dataset' cls.file_path = os.path.dirname(os.path.abspath(__file__)) cls.format = '.nc' cls.dataset = podaac.load_level4_granule( cls.variable, cls.datasetId, cls.name)
def setUpClass(cls): cls.datasetId = 'PODAAC-GHCMC-4FM02' cls.variable = 'sea_ice_fraction' cls.name = 'PO.DAAC_test_dataset' cls.file_path = os.path.dirname(os.path.abspath(__file__)) cls.format = '.nc' cls.dataset = podaac.load_level4_granule(cls.variable, cls.datasetId, cls.name)
# specific language governing permissions and limitations # under the License. import ocw.data_source.podaac_datasource as podaac import ocw.evaluation as evaluation import ocw.metrics as metrics import ocw.plotter as plotter datasetId = 'PODAAC-CCF30-01XXX' variable = 'uwnd' name = 'PO.DAAC_test_dataset' OUTPUT_PLOT = "ccmp_temporal_std" """ Step 1: Load Local NetCDF Files into OCW Dataset Objects """ print("Loading %s dataset short name into a OCW dataset object." % datasetId) ccmp_dataset = podaac.load_level4_granule(variable=variable, datasetId=datasetId, name=name) print("CCMP_Dataset.values shape: (times, lats, lons) - %s \n" % (ccmp_dataset.values.shape, )) # Acessing latittudes and longitudes of netCDF file lats = ccmp_dataset.lats lons = ccmp_dataset.lons """ Step 2: Build a Metric to use for Evaluation - Temporal STD for this example """ # You can build your own metrics, but OCW also ships with some common metrics print("Setting up a Temporal STD metric to use for evaluation") std = metrics.TemporalStdDev() """ Step 3: Create an Evaluation Object using Datasets and our Metric """ # The Evaluation Class Signature is: # Evaluation(reference, targets, metrics, subregions=None) # Evaluation can take in multiple targets and metrics, so we need to convert
# KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import ocw.data_source.podaac_datasource as podaac import ocw.evaluation as evaluation import ocw.metrics as metrics import ocw.plotter as plotter datasetId = 'PODAAC-CCF30-01XXX' variable = 'uwnd' name = 'PO.DAAC_test_dataset' OUTPUT_PLOT = "ccmp_temporal_std" """ Step 1: Load Local NetCDF Files into OCW Dataset Objects """ print("Loading %s dataset short name into a OCW dataset object." % datasetId) ccmp_dataset = podaac.load_level4_granule( variable=variable, datasetId=datasetId, name=name) print("CCMP_Dataset.values shape: (times, lats, lons) - %s \n" % (ccmp_dataset.values.shape,)) # Acessing latittudes and longitudes of netCDF file lats = ccmp_dataset.lats lons = ccmp_dataset.lons """ Step 2: Build a Metric to use for Evaluation - Temporal STD for this example """ # You can build your own metrics, but OCW also ships with some common metrics print("Setting up a Temporal STD metric to use for evaluation") std = metrics.TemporalStdDev() """ Step 3: Create an Evaluation Object using Datasets and our Metric """ # The Evaluation Class Signature is: # Evaluation(reference, targets, metrics, subregions=None)