def test_add_coordinates(self): ds = xr.Dataset() TemplateUtil.add_geolocation_variables(ds, 13, 108) TemplateUtil.add_coordinates(ds) x = ds["x"] self.assertEqual((13, ), x.shape) self.assertEqual(np.uint16, x.dtype) y = ds["y"] self.assertEqual((108, ), y.shape) self.assertEqual(np.uint16, y.dtype)
def add_easy_fcdr_variables(dataset, height, corr_dx=None, corr_dy=None, lut_size=None): # height is ignored - supplied just for interface compatibility tb 2017-02-05 # reflectance default_array = DefaultData.create_default_array(FULL_SIZE, FULL_SIZE, np.float32, fill_value=np.NaN) variable = Variable(["y", "x"], default_array) variable.attrs["standard_name"] = "toa_bidirectional_reflectance_vis" variable.attrs["long_name"] = "top of atmosphere bidirectional reflectance factor per pixel of the visible band with central wavelength 0.7" tu.add_units(variable, "1") tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 3.05176E-05, chunksizes=CHUNKSIZES) dataset["toa_bidirectional_reflectance_vis"] = variable # u_independent default_array = DefaultData.create_default_array(FULL_SIZE, FULL_SIZE, np.float32, fill_value=np.NaN) variable = Variable(["y", "x"], default_array) variable.attrs["long_name"] = "independent uncertainty per pixel" tu.add_units(variable, "1") tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 3.05176E-05, chunksizes=CHUNKSIZES) dataset["u_independent_toa_bidirectional_reflectance"] = variable # u_structured default_array = DefaultData.create_default_array(FULL_SIZE, FULL_SIZE, np.float32, fill_value=np.NaN) variable = Variable(["y", "x"], default_array) variable.attrs["long_name"] = "structured uncertainty per pixel" tu.add_units(variable, "1") tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 3.05176E-05, chunksizes=CHUNKSIZES) dataset["u_structured_toa_bidirectional_reflectance"] = variable # u_common dataset["u_common_toa_bidirectional_reflectance"] = tu.create_scalar_float_variable(long_name="common uncertainty per slot", units="1") dataset["sub_satellite_latitude_start"] = tu.create_scalar_float_variable(long_name="Latitude of the sub satellite point at image start", units="degrees_north") dataset["sub_satellite_longitude_start"] = tu.create_scalar_float_variable(long_name="Longitude of the sub satellite point at image start", units="degrees_east") dataset["sub_satellite_latitude_end"] = tu.create_scalar_float_variable(long_name="Latitude of the sub satellite point at image end", units="degrees_north") dataset["sub_satellite_longitude_end"] = tu.create_scalar_float_variable(long_name="Longitude of the sub satellite point at image end", units="degrees_east") tu.add_correlation_matrices(dataset, NUM_CHANNELS) if lut_size is not None: tu.add_lookup_tables(dataset, NUM_CHANNELS, lut_size=lut_size) if corr_dx is not None and corr_dy is not None: tu.add_correlation_coefficients(dataset, NUM_CHANNELS, corr_dx, corr_dy) tu.add_coordinates(dataset, ["vis", "wv", "ir"])
def test_add_coordinates_with_channel(self): ds = xr.Dataset() TemplateUtil.add_geolocation_variables(ds, 8, 11) default_array = DefaultData.create_default_array_3d( 8, 11, 4, np.float32, np.NaN) ds["three_d"] = Variable(["channel", "y", "x"], default_array) TemplateUtil.add_coordinates(ds) x = ds["x"] self.assertEqual((8, ), x.shape) self.assertEqual(np.uint16, x.dtype) y = ds["y"] self.assertEqual((11, ), y.shape) self.assertEqual(np.uint16, y.dtype) channel = ds["channel"] self.assertEqual((4, ), channel.shape) self.assertEqual(np.uint16, channel.dtype)
def add_original_variables(dataset, height, srf_size=None): tu.add_geolocation_variables(dataset, SWATH_WIDTH, height, chunksizes=CHUNKS_2D) tu.add_quality_flags(dataset, SWATH_WIDTH, height, chunksizes=CHUNKS_2D) # Time default_array = DefaultData.create_default_vector(height, np.float64, fill_value=np.NaN) variable = Variable(["y"], default_array) tu.add_fill_value(variable, np.NaN) tu.add_units(variable, "s") variable.attrs["standard_name"] = "time" variable.attrs[ "long_name"] = "Acquisition time in seconds since 1970-01-01 00:00:00" dataset["Time"] = variable # relative_azimuth_angle default_array = DefaultData.create_default_array(SWATH_WIDTH, height, np.float32, fill_value=np.NaN) variable = Variable(["y", "x"], default_array) variable.attrs["standard_name"] = "relative_azimuth_angle" tu.add_units(variable, "degree") tu.add_encoding(variable, np.int16, DefaultData.get_default_fill_value(np.int16), 0.01, chunksizes=CHUNKS_2D) variable.attrs["valid_max"] = 18000 variable.attrs["valid_min"] = -18000 tu.add_geolocation_attribute(variable) dataset["relative_azimuth_angle"] = variable # satellite_zenith_angle default_array = DefaultData.create_default_array(SWATH_WIDTH, height, np.float32, fill_value=np.NaN) variable = Variable(["y", "x"], default_array) variable.attrs["standard_name"] = "sensor_zenith_angle" tu.add_units(variable, "degree") tu.add_encoding(variable, np.int16, DefaultData.get_default_fill_value(np.int16), 0.01, chunksizes=CHUNKS_2D) variable.attrs["valid_max"] = 9000 variable.attrs["valid_min"] = 0 tu.add_geolocation_attribute(variable) dataset["satellite_zenith_angle"] = variable # solar_zenith_angle default_array = DefaultData.create_default_array(SWATH_WIDTH, height, np.float32, fill_value=np.NaN) variable = Variable(["y", "x"], default_array) variable.attrs["standard_name"] = "solar_zenith_angle" tu.add_units(variable, "degree") tu.add_encoding(variable, np.int16, DefaultData.get_default_fill_value(np.int16), 0.01, chunksizes=CHUNKS_2D) variable.attrs["valid_max"] = 18000 variable.attrs["valid_min"] = 0 tu.add_geolocation_attribute(variable) dataset["solar_zenith_angle"] = variable dataset["Ch1"] = AVHRR._create_channel_refl_variable( height, "Channel 1 Reflectance") dataset["Ch2"] = AVHRR._create_channel_refl_variable( height, "Channel 2 Reflectance") dataset["Ch3a"] = AVHRR._create_channel_refl_variable( height, "Channel 3a Reflectance") dataset["Ch3b"] = AVHRR._create_channel_bt_variable( height, "Channel 3b Brightness Temperature") dataset["Ch4"] = AVHRR._create_channel_bt_variable( height, "Channel 4 Brightness Temperature") dataset["Ch5"] = AVHRR._create_channel_bt_variable( height, "Channel 5 Brightness Temperature") # data_quality_bitmask default_array = DefaultData.create_default_array(SWATH_WIDTH, height, np.uint8, fill_value=0) variable = Variable(["y", "x"], default_array) variable.attrs["standard_name"] = 'status_flag' variable.attrs["long_name"] = 'bitmask for quality per pixel' variable.attrs["flag_masks"] = '1,2' variable.attrs[ 'flag_meanings'] = 'bad_geolocation_timing_err bad_calibration_radiometer_err' tu.add_chunking(variable, CHUNKS_2D) tu.add_geolocation_attribute(variable) dataset['data_quality_bitmask'] = variable default_array = DefaultData.create_default_vector(height, np.uint8, fill_value=0) variable = Variable(["y"], default_array) variable.attrs["long_name"] = 'bitmask for quality per scanline' variable.attrs["standard_name"] = 'status_flag' variable.attrs["flag_masks"] = '1,2,4,8,16,32,64' variable.attrs[ 'flag_meanings'] = 'do_not_use bad_time bad_navigation bad_calibration channel3a_present solar_contamination_failure solar_contamination' dataset['quality_scanline_bitmask'] = variable default_array = DefaultData.create_default_array(N_CHANS, height, np.uint8, fill_value=0) variable = Variable(["y", "channel"], default_array) variable.attrs["long_name"] = 'bitmask for quality per channel' variable.attrs["standard_name"] = 'status_flag' variable.attrs["flag_masks"] = '1,2' variable.attrs[ 'flag_meanings'] = 'bad_channel some_pixels_not_detected_2sigma' dataset['quality_channel_bitmask'] = variable if srf_size is None: srf_size = MAX_SRF_SIZE default_array = DefaultData.create_default_array(srf_size, N_CHANS, np.float32, fill_value=np.NaN) variable = Variable(["channel", "n_frequencies"], default_array) variable.attrs["long_name"] = 'Spectral Response Function weights' variable.attrs[ "description"] = 'Per channel: weights for the relative spectral response function' tu.add_encoding(variable, np.int16, -32768, 0.000033) dataset['SRF_weights'] = variable default_array = DefaultData.create_default_array(srf_size, N_CHANS, np.float32, fill_value=np.NaN) variable = Variable(["channel", "n_frequencies"], default_array) variable.attrs["long_name"] = 'Spectral Response Function wavelengths' variable.attrs[ "description"] = 'Per channel: wavelengths for the relative spectral response function' tu.add_encoding(variable, np.int32, -2147483648, 0.0001) tu.add_units(variable, "um") dataset['SRF_wavelengths'] = variable default_vector = DefaultData.create_default_vector(height, np.uint8, fill_value=255) variable = Variable(["y"], default_vector) tu.add_fill_value(variable, 255) variable.attrs["long_name"] = 'Indicator of original file' variable.attrs[ "description"] = "Indicator for mapping each line to its corresponding original level 1b file. See global attribute 'source' for the filenames. 0 corresponds to 1st listed file, 1 to 2nd file." dataset["scanline_map_to_origl1bfile"] = variable default_vector = DefaultData.create_default_vector( height, np.int16, fill_value=DefaultData.get_default_fill_value(np.int16)) variable = Variable(["y"], default_vector) tu.add_fill_value(variable, DefaultData.get_default_fill_value(np.int16)) variable.attrs["long_name"] = 'Original_Scan_line_number' variable.attrs[ "description"] = 'Original scan line numbers from corresponding l1b records' dataset["scanline_origl1b"] = variable tu.add_coordinates(dataset, ["Ch1", "Ch2", "Ch3a", "Ch3b", "Ch4", "Ch5"])
def add_coordinates(dataset): channel_names = [] for i in range(1, 20): channel_names.append("Ch" + str(i)) tu.add_coordinates(dataset, channel_names)
def add_coordinates(dataset): tu.add_coordinates(dataset, np.arange(1, 20))