def get_dataset(self, key, info):
if self._data is None:
self.read()
if key.name in ['latitude', 'longitude']:
lons, lats = self.get_lonlats()
if key.name == 'latitude':
return Projectable(lats, id=key)
else:
return Projectable(lons, id=key)
avhrr_channel_index = {'1': 0,
'2': 1,
'3a': 2,
'3b': 2,
'4': 3,
'5': 4}
index = avhrr_channel_index[key.name]
mask = False
if key.name in ['3a', '3b'] and self._is3b is None:
ch3a = bfield(self._data["id"]["id"], 10)
self._is3b = np.logical_not(ch3a)
if key.name == '3a':
mask = np.tile(self._is3b, (1, 2048))
elif key.name == '3b':
mask = np.tile(np.logical_not(self._is3b), (1, 2048))
data = self._data["image_data"][:, :, index]
if key.calibration == 'counts':
return Projectable(data,
mask=mask,
area=self.get_lonlats(),
units='1')
pg_spacecraft = ''.join(self.platform_name.split()).lower()
jdays = (np.datetime64(self.start_time) - np.datetime64(str(
self.year) + '-01-01T00:00:00Z')) / np.timedelta64(1, 'D')
if index < 2 or key.name == '3a':
data = calibrate_solar(data, index, self.year, jdays,
pg_spacecraft)
units = '%'
if index > 2 or key.name == '3b':
if self.times is None:
self.times = time_seconds(self._data["timecode"], self.year)
line_numbers = (
np.round((self.times - self.times[-1]) /
np.timedelta64(166666667, 'ns'))).astype(np.int)
line_numbers -= line_numbers[0]
if self.prt is None:
self.prt, self.ict, self.space = self.get_telemetry()
chan = index + 1
data = calibrate_thermal(data, self.prt, self.ict[:, chan - 3],
self.space[:, chan - 3], line_numbers,
chan, pg_spacecraft)
units = 'K'
# TODO: check if entirely masked before returning
return Projectable(data, mask=mask, units=units)
def get_calibrated_channels(self):
channels = self.get_counts()
self.get_times()
year = self.times[0].year
delta = self.times[0].date() - datetime.date(year, 1, 1)
jday = delta.days + 1
# Earth-Sun distance correction factor
corr = 1.0 - 0.0334 * np.cos(2.0 * np.pi * (jday - 2) / 365.25)
# how many reflective channels are there ?
tot_ref = channels.shape[2] - 3
channels[:, :, 0:tot_ref] = calibrate_solar(channels[:, :, 0:tot_ref],
np.arange(tot_ref),
year, jday,
self.spacecraft_name,
corr)
prt, ict, space = self.get_telemetry()
for chan in [3, 4, 5]:
channels[:, :, chan - 6] = calibrate_thermal(
channels[:, :, chan - 6],
prt,
ict[:, chan - 3],
space[:, chan - 3],
self.scans["scan_line_number"],
chan,
self.spacecraft_name)
return channels
def get_dataset(self, key, info):
if self._data is None:
self.read()
if key.name in ['latitude', 'longitude']:
lons, lats = self.get_lonlats()
if key.name == 'latitude':
return Dataset(lats, id=key)
else:
return Dataset(lons, id=key)
avhrr_channel_index = {
'1': 0,
'2': 1,
'3a': 2,
'3b': 2,
'4': 3,
'5': 4
}
index = avhrr_channel_index[key.name]
mask = False
if key.name in ['3a', '3b'] and self._is3b is None:
ch3a = bfield(self._data["id"]["id"], 10)
self._is3b = np.logical_not(ch3a)
if key.name == '3a':
mask = np.tile(self._is3b, (1, 2048))
elif key.name == '3b':
mask = np.tile(np.logical_not(self._is3b), (1, 2048))
data = self._data["image_data"][:, :, index]
if key.calibration == 'counts':
return Dataset(data, mask=mask, area=self.get_lonlats(), units='1')
pg_spacecraft = ''.join(self.platform_name.split()).lower()
jdays = (np.datetime64(self.start_time) -
np.datetime64(str(self.year) +
'-01-01T00:00:00Z')) / np.timedelta64(1, 'D')
if index < 2 or key.name == '3a':
data = calibrate_solar(data, index, self.year, jdays,
pg_spacecraft)
units = '%'
if index > 2 or key.name == '3b':
if self.times is None:
self.times = time_seconds(self._data["timecode"], self.year)
line_numbers = (np.round(
(self.times - self.times[-1]) /
np.timedelta64(166666667, 'ns'))).astype(np.int)
line_numbers -= line_numbers[0]
if self.prt is None:
self.prt, self.ict, self.space = self.get_telemetry()
chan = index + 1
data = calibrate_thermal(data, self.prt, self.ict[:, chan - 3],
self.space[:, chan - 3], line_numbers,
chan, pg_spacecraft)
units = 'K'
# TODO: check if entirely masked before returning
return Dataset(data, mask=mask, units=units)
def test_calibration_ir(self):
counts = np.array([[
0, 0, 612, 0, 0, 512, 512, 487, 512, 512, 923, 923, 687, 923, 923
],
[
41, 41, 634, 41, 41, 150, 150, 461, 150, 150,
700, 700, 670, 700, 700
],
[
241, 241, 656, 241, 241, 350, 350, 490, 350,
350, 600, 600, 475, 600, 600
]])
prt_counts = np.array([0, 230, 230])
ict_counts = np.array([[745.3, 397.9, 377.8], [744.8, 398.1, 378.4],
[745.7, 398., 378.3]])
space_counts = np.array([[987.3, 992.5, 989.4], [986.9, 992.8, 989.6],
[986.3, 992.3, 988.9]])
spacecraft_id = "noaa14"
number_of_data_records = 3
ch3 = calibrate_thermal(counts[:, 2::5],
prt_counts,
ict_counts[:, 0],
space_counts[:, 0],
line_numbers=np.array([1, 2, 3]),
channel=3,
spacecraft=spacecraft_id)
expected_ch3 = np.array([[298.28524223, 305.16852862, 293.16212655],
[296.87900835, 306.41526012, 294.41059746],
[295.39720547, 305.02120845, 305.75051609]])
self.assertTrue(np.allclose(expected_ch3, ch3))
ch4 = calibrate_thermal(counts[:, 3::5],
prt_counts,
ict_counts[:, 1],
space_counts[:, 1],
line_numbers=np.array([1, 2, 3]),
channel=4,
spacecraft=spacecraft_id)
expected_ch4 = np.array([[325.82572316, 275.41391816, 196.21443457],
[322.35731456, 312.78320066, 249.38013251],
[304.32522137, 293.48953883, 264.14732182]])
self.assertTrue(np.allclose(expected_ch4, ch4))
ch5 = calibrate_thermal(counts[:, 4::5],
prt_counts,
ict_counts[:, 2],
space_counts[:, 2],
line_numbers=np.array([1, 2, 3]),
channel=5,
spacecraft=spacecraft_id)
expected_ch5 = np.array([[326.47287181, 272.14169523, 187.40907142],
[322.72885806, 312.39588991, 244.22910864],
[303.27173737, 291.59183911, 260.0459766]])
self.assertTrue(np.allclose(expected_ch5, ch5))
def test_calibration_ir(self):
counts = np.array([[0, 0, 612, 0, 0,
512, 512, 487, 512, 512,
923, 923, 687, 923, 923],
[41, 41, 634, 41, 41,
150, 150, 461, 150, 150,
700, 700, 670, 700, 700],
[241, 241, 656, 241, 241,
350, 350, 490, 350, 350,
600, 600, 475, 600, 600]])
prt_counts = np.array([0, 230, 230])
ict_counts = np.array([[745.3, 397.9, 377.8],
[744.8, 398.1, 378.4],
[745.7, 398., 378.3]])
space_counts = np.array([[987.3, 992.5, 989.4],
[986.9, 992.8, 989.6],
[986.3, 992.3, 988.9]])
spacecraft_id = "noaa19"
number_of_data_records = 3
ch3 = calibrate_thermal(counts[:, 2::5],
prt_counts,
ict_counts[:, 0],
space_counts[:, 0],
line_numbers=np.array([1, 2, 3]),
channel=3,
spacecraft=spacecraft_id)
expected_ch3 = np.array([[298.36772477, 305.24899954, 293.23847375],
[296.96053595, 306.49432811, 294.48914038],
[295.47715016, 305.10182601, 305.83036782]])
self.assertTrue(np.allclose(expected_ch3, ch3))
ch4 = calibrate_thermal(counts[:, 3::5],
prt_counts,
ict_counts[:, 1],
space_counts[:, 1],
line_numbers=np.array([1, 2, 3]),
channel=4,
spacecraft=spacecraft_id)
expected_ch4 = np.array([[326.57669548, 275.34893211, 197.68844955],
[323.01324859, 313.20717645, 249.3633716],
[304.58097221, 293.57932356, 264.0630027]])
self.assertTrue(np.allclose(expected_ch4, ch4))
ch5 = calibrate_thermal(counts[:, 4::5],
prt_counts,
ict_counts[:, 2],
space_counts[:, 2],
line_numbers=np.array([1, 2, 3]),
channel=5,
spacecraft=spacecraft_id)
expected_ch5 = np.array([[326.96168274, 272.09013413, 188.26784127],
[323.15638147, 312.67331324, 244.18437795],
[303.43940924, 291.64944851, 259.97304154]])
self.assertTrue(np.allclose(expected_ch5, ch5))
