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))
