def test_strip_invalid_lat(self):
"""Test stripping the invalid lats."""
lats = np.array([np.nan, 1, np.nan, 2, np.nan])
start, end = utils.strip_invalid_lat(lats)
self.assertEqual(start, 1)
self.assertEqual(end, 3)
def save_gac(satellite_name, xutcs, lats, lons, ref1, ref2, ref3, bt3, bt4,
bt5, sun_zen, sat_zen, sun_azi, sat_azi, rel_azi, qual_flags,
start_line, end_line, gac_file, meta_data):
midnight_scanline = meta_data['midnight_scanline']
miss_lines = meta_data['missing_scanlines']
corr = meta_data['sun_earth_distance_correction_factor']
last_scan_line_number = qual_flags[-1, 0]
# Strip invalid coordinates
first_valid_lat, last_valid_lat = strip_invalid_lat(lats)
if first_valid_lat > start_line:
LOG.info('New start_line chosen (due to invalid lat/lon '
'info) = ' + str(first_valid_lat))
if end_line > last_valid_lat:
LOG.info('New end_line chosen (due to invalid lat/lon '
'info) = ' + str(last_valid_lat))
# Check user-defined scanlines
start_line, end_line = check_user_scanlines(
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
# Slice data using new start/end lines
_, miss_lines, midnight_scanline = slice_channel(
np.zeros(lats.shape),
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat,
qual_flags=qual_flags,
miss_lines=miss_lines,
midnight_scanline=midnight_scanline)
ref1, _, _ = slice_channel(ref1,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
ref2, _, _ = slice_channel(ref2,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
ref3, _, _ = slice_channel(ref3,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
bt3, _, _ = slice_channel(bt3,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
bt4, _, _ = slice_channel(bt4,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
bt5, _, _ = slice_channel(bt5,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
sun_zen, _, _ = slice_channel(sun_zen,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
sun_azi, _, _ = slice_channel(sun_azi,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
sat_zen, _, _ = slice_channel(sat_zen,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
sat_azi, _, _ = slice_channel(sat_azi,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
rel_azi, _, _ = slice_channel(rel_azi,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
lons, _, _ = slice_channel(lons,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
lats, _, _ = slice_channel(lats,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
qual_flags, _, _ = slice_channel(qual_flags,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
xutcs, _, _ = slice_channel(xutcs,
start_line=start_line,
end_line=end_line,
first_valid_lat=first_valid_lat,
last_valid_lat=last_valid_lat)
total_number_of_scan_lines = lats.shape[0]
# Reading time from the body of the gac file
start = xutcs[0].astype(datetime.datetime)
end = xutcs[-1].astype(datetime.datetime)
startdate = start.strftime("%Y%m%d")
starttime = start.strftime("%H%M%S%f")[:-5]
enddate = end.strftime("%Y%m%d")
endtime = end.strftime("%H%M%S%f")[:-5]
# Apply scaling & offset
bt3 -= 273.15
bt4 -= 273.15
bt5 -= 273.15
for array in [
bt3, bt4, bt5, ref1, ref2, ref3, sun_zen, sat_zen, sun_azi,
sat_azi, rel_azi
]:
array *= 100.0
for array in [lats, lons]:
array *= 1000.0
# Replace NaN with fill values
for array in [
ref1, ref2, ref3, bt3, bt4, bt5, sun_zen, sat_zen, sun_azi,
sat_azi, rel_azi
]:
array[np.isnan(array)] = MISSING_DATA
for array in [lats, lons]:
array[np.isnan(array)] = MISSING_DATA_LATLON
avhrrGAC_io(satellite_name, xutcs, startdate, enddate, starttime, endtime,
lats, lons, ref1, ref2, ref3, bt3, bt4, bt5, sun_zen, sat_zen,
sun_azi, sat_azi, rel_azi, qual_flags, start_line, end_line,
total_number_of_scan_lines, last_scan_line_number, corr,
gac_file, midnight_scanline, miss_lines)
