def _create_refl_uncertainty_variable(height,
long_name=None,
structured=False):
default_array = DefaultData.create_default_array(SWATH_WIDTH,
height,
np.float32,
fill_value=np.NaN)
variable = Variable(["y", "x"], default_array)
tu.add_units(variable, "percent")
tu.add_geolocation_attribute(variable)
variable.attrs["long_name"] = long_name
if structured:
tu.add_encoding(variable,
np.int16,
DefaultData.get_default_fill_value(np.int16),
0.01,
chunksizes=CHUNKS_2D)
variable.attrs["valid_min"] = 3
variable.attrs["valid_max"] = 5
else:
tu.add_encoding(variable,
np.int16,
DefaultData.get_default_fill_value(np.int16),
0.00001,
chunksizes=CHUNKS_2D)
variable.attrs["valid_max"] = 1000
variable.attrs["valid_min"] = 10
return variable
def test_add_geolocation_attribute(self):
default_array = DefaultData.create_default_array_3d(
8, 6, 4, np.float32, np.NaN)
variable = Variable(["channel", "y", "x"], default_array)
TemplateUtil.add_geolocation_attribute(variable)
self.assertEqual("longitude latitude", variable.attrs["coordinates"])
def _create_counts_uncertainty_variable(height, long_name):
variable = tu.create_float_variable(SWATH_WIDTH,
height,
long_name=long_name,
fill_value=np.NaN)
tu.add_units(variable, "count")
tu.add_geolocation_attribute(variable)
tu.add_chunking(variable, CHUNKS_2D)
return variable
def _create_angle_uncertainty_variable(angle_name, height):
variable = tu.create_float_variable(SWATH_WIDTH,
height,
long_name="uncertainty of " +
angle_name,
fill_value=np.NaN)
tu.add_units(variable, "degree")
tu.add_geolocation_attribute(variable)
tu.add_chunking(variable, CHUNKS_2D)
return variable
def _create_easy_fcdr_variable(height, long_name):
default_array = DefaultData.create_default_array_3d(SWATH_WIDTH, height, NUM_CHANNELS, np.float32, np.NaN)
variable = Variable(["channel", "y", "x"], default_array)
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.001, chunksizes=CHUNKING_BT)
variable.attrs["long_name"] = long_name
tu.add_units(variable, "K")
tu.add_geolocation_attribute(variable)
variable.attrs["valid_min"] = 1
variable.attrs["valid_max"] = 65534
return variable
def _create_counts_variable(height, long_name):
default_array = DefaultData.create_default_array(
SWATH_WIDTH, height, np.int32)
variable = Variable(["y", "x"], default_array)
tu.add_fill_value(variable,
DefaultData.get_default_fill_value(np.int32))
variable.attrs["long_name"] = long_name
tu.add_units(variable, "count")
tu.add_geolocation_attribute(variable)
tu.add_chunking(variable, CHUNKS_2D)
return variable
def _create_geo_angle_variable(standard_name, height, orig_name=None, chunking=None):
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"] = standard_name
if orig_name is not None:
variable.attrs["orig_name"] = orig_name
tu.add_units(variable, "degree")
tu.add_geolocation_attribute(variable)
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01, -180.0, chunking)
return variable
def add_quality_flags(dataset, height):
tu.add_quality_flags(dataset, SWATH_WIDTH, height, chunksizes=CHUNKING_2D)
default_array = DefaultData.create_default_array(SWATH_WIDTH, height, np.uint16, fill_value=0)
variable = Variable(["y", "x"], default_array)
variable.attrs["flag_masks"] = "1, 2, 4, 8, 16"
variable.attrs["flag_meanings"] = "suspect_mirror suspect_geo suspect_time outlier_nos uncertainty_too_large"
variable.attrs["standard_name"] = "status_flag"
tu.add_chunking(variable, CHUNKING_2D)
tu.add_geolocation_attribute(variable)
dataset["data_quality_bitmask"] = variable
def add_bt_variable(dataset, height):
# bt
default_array = DefaultData.create_default_array_3d(SWATH_WIDTH, height, NUM_CHANNELS, np.float32, np.NaN)
variable = Variable(["channel", "y", "x"], default_array)
variable.attrs["standard_name"] = "toa_brightness_temperature"
variable.attrs["long_name"] = "Brightness temperature, NOAA/EUMETSAT calibrated"
tu.add_units(variable, "K")
tu.add_encoding(variable, np.int16, FILL_VALUE, 0.01, 150.0, chunksizes=CHUNKING_BT)
tu.add_geolocation_attribute(variable)
variable.attrs["ancilliary_variables"] = "quality_scanline_bitmask quality_channel_bitmask"
dataset["bt"] = variable
def _add_angle_variables(dataset, height):
default_array = DefaultData.create_default_vector(height,
np.float32,
fill_value=np.NaN)
variable = Variable(["y"], default_array)
variable.attrs["standard_name"] = "platform_zenith_angle"
tu.add_units(variable, "degree")
tu.add_geolocation_attribute(variable)
tu.add_encoding(variable, np.uint16,
DefaultData.get_default_fill_value(np.uint16), 0.01,
-180.0)
dataset["satellite_zenith_angle"] = variable
dataset["solar_azimuth_angle"] = HIRS._create_geo_angle_variable(
"solar_azimuth_angle", height, chunking=CHUNKING_2D)
def _create_bt_uncertainty_variable(height, long_name):
default_array = DefaultData.create_default_array(SWATH_WIDTH,
height,
np.float32,
fill_value=np.NaN)
variable = Variable(["y", "x"], default_array)
tu.add_units(variable, "K")
tu.add_geolocation_attribute(variable)
tu.add_encoding(variable,
np.int16,
DefaultData.get_default_fill_value(np.int16),
0.001,
chunksizes=CHUNKS_2D)
variable.attrs["valid_max"] = 15000
variable.attrs["valid_min"] = 1
variable.attrs["long_name"] = long_name
return variable
def _create_channel_refl_variable(height, long_name):
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"] = "toa_reflectance"
variable.attrs["long_name"] = long_name
tu.add_units(variable, "1")
tu.add_encoding(variable,
np.int16,
DefaultData.get_default_fill_value(np.int16),
0.0001,
chunksizes=CHUNKS_2D)
variable.attrs["valid_max"] = 15000
variable.attrs["valid_min"] = 0
tu.add_geolocation_attribute(variable)
return variable
def _create_channel_bt_variable(height, long_name):
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"] = "toa_brightness_temperature"
variable.attrs["long_name"] = long_name
tu.add_units(variable, "K")
variable.attrs["valid_max"] = 10000
variable.attrs["valid_min"] = -20000
tu.add_geolocation_attribute(variable)
tu.add_encoding(variable,
np.int16,
DefaultData.get_default_fill_value(np.int16),
0.01,
273.15,
chunksizes=CHUNKS_2D)
return variable
def _create_refl_uncertainty_variable(height,
minmax,
scale_factor,
long_name=None,
units=None):
default_array = DefaultData.create_default_array(SWATH_WIDTH,
height,
np.float32,
fill_value=np.NaN)
variable = Variable(["y", "x"], default_array)
tu.add_units(variable, units)
tu.add_geolocation_attribute(variable)
variable.attrs["long_name"] = long_name
tu.add_encoding(variable,
np.int16,
DefaultData.get_default_fill_value(np.int16),
scale_factor,
chunksizes=CHUNKS_2D)
variable.attrs["valid_min"] = minmax[0]
variable.attrs["valid_max"] = minmax[1]
return variable
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"])
