def test_single_integration_returns_array_of_0(self):
assert np.array_equal(swath_number(np.array([100])), np.array([0]))
def test_monotonically_increasing_mirror_angles_returns_array_of_0s(
self, one_swath_mirror_angles, one_swath_swath_numbers):
assert np.array_equal(swath_number(one_swath_mirror_angles),
one_swath_swath_numbers)
def make_apoapse_muv_quicklook(orbit: int, data_location: Path,
saveloc: str) -> None:
"""Make the standard apoapse MUV quicklook.
Parameters
----------
orbit
data_location
saveloc
Returns
-------
None
"""
template = ApoapseMUVQuicklook()
# Load in the data
data_paths = find_latest_apoapse_muv_file_paths_from_block(
data_location, orbit)
files = [L1bFile(f) for f in data_paths]
fc = L1bFileCollection(files)
# Make data that's independent of day/night
fov = fc.stack_field_of_view()
swath_numbers = swath_number(fov)
fc.make_daynight_integration_mask()
dayside_integration_mask = fc.make_daynight_integration_mask()
# Do the day/night stuff
for daynight in [True, False]:
fc.dayside = daynight
if daynight not in dayside_integration_mask:
continue
primary = fc.stack_daynight_calibrated_detector_image()
on_disk_mask = fc.make_daynight_on_disk_mask()
daynight_fov = fov[dayside_integration_mask == daynight]
daynight_swath_number = swath_numbers[dayside_integration_mask ==
daynight]
sza = set_bad_pixels_to_nan(fc.stack_daynight_solar_zenith_angle(),
on_disk_mask)
ea = set_bad_pixels_to_nan(fc.stack_daynight_emission_angle(),
on_disk_mask)
pa = set_bad_pixels_to_nan(fc.stack_daynight_phase_angle(),
on_disk_mask)
lt = set_bad_pixels_to_nan(fc.stack_daynight_local_time(),
on_disk_mask)
n_spatial_bins = primary.shape[1]
# Do dayside specific things
if daynight:
# TODO: FF correct here
rgb_primary = histogram_equalize_detector_image(primary) / 255
# Do nightside specific things
else:
brightnesses = fit_muv_templates_to_nightside_data(fc)
no_kR = brightnesses[0, ...]
aurora_kR = brightnesses[1, ...]
for swath in np.unique(swath_numbers):
# Do this no matter if I'm plotting primary or angles
swath_inds = daynight_swath_number == swath
n_integrations = np.sum(swath_inds)
x, y = make_swath_grid(daynight_fov[swath_inds], swath,
n_spatial_bins, n_integrations)
pcolormesh_detector_image(template.solar_zenith_angle_swath,
sza[swath_inds],
x,
y,
cmap=template.angle_colormap,
norm=template.angle_norm)
pcolormesh_detector_image(template.emission_angle_swath,
ea[swath_inds],
x,
y,
cmap=template.angle_colormap,
norm=template.angle_norm)
pcolormesh_detector_image(template.phase_angle_swath,
pa[swath_inds],
x,
y,
cmap=template.angle_colormap,
norm=template.angle_norm)
pcolormesh_detector_image(template.local_time_swath,
lt[swath_inds],
x,
y,
cmap=template.local_time_colormap,
norm=template.local_time_norm)
# Plot the primary for dayside data
if daynight:
pcolormesh_rgb_detector_image(template.no_data_swath,
rgb_primary[swath_inds], x, y)
pcolormesh_rgb_detector_image(template.aurora_data_swath,
rgb_primary[swath_inds], x, y)
else:
pcolormesh_detector_image(template.no_data_swath,
no_kR[swath_inds],
x,
y,
cmap=template.no_colormap,
norm=template.no_norm)
pcolormesh_detector_image(template.aurora_data_swath,
aurora_kR[swath_inds],
x,
y,
cmap=template.aurora_colormap,
norm=template.aurora_norm)
for ax in [
template.no_data_swath, template.aurora_data_swath,
template.solar_zenith_angle_swath, template.emission_angle_swath,
template.phase_angle_swath, template.local_time_swath
]:
ax.set_xlim(0, angular_slit_width * (swath_numbers[-1] + 1))
ax.set_ylim(minimum_mirror_angle * 2, maximum_mirror_angle * 2)
ax.set_xticks([])
ax.set_yticks([])
plt.savefig(saveloc)
def test_six_swath_decreasing_mirror_angles_match_known_swath_numbers(
self, six_swath_decreasing_mirror_angles, six_swath_swath_numbers):
assert np.array_equal(swath_number(six_swath_decreasing_mirror_angles),
six_swath_swath_numbers)
def make_dayside_segment_detector_image(orbit: int,
data_location: Path,
saveloc: str,
figheight=6):
"""Make an image of a dayside detector image.
Parameters
----------
orbit
data_location
saveloc
figheight
Returns
-------
"""
# Load in the data
data_paths = find_latest_apoapse_muv_file_paths_from_block(
data_location, orbit)
files = [L1bFile(f) for f in data_paths]
fc = L1bFileCollection(files)
# Make data that's independent of day/night
fov = fc.stack_field_of_view()
swath_numbers = swath_number(fov)
fc.make_daynight_integration_mask()
dayside_integration_mask = fc.make_daynight_integration_mask()
template = SegmentDetectorImage(swath_numbers[-1] + 1, figheight)
# Do the day/night stuff
fc.dayside = True
for daynight in [True]:
if daynight not in dayside_integration_mask:
continue
primary = fc.stack_daynight_calibrated_detector_image()
on_disk_mask = fc.make_daynight_on_disk_mask()
daynight_fov = fov[dayside_integration_mask == daynight]
daynight_swath_number = swath_numbers[dayside_integration_mask ==
daynight]
n_spatial_bins = primary.shape[1]
if daynight:
# TODO: FF correct here
rgb_primary = histogram_equalize_detector_image(
primary, mask=on_disk_mask) / 255
for swath in np.unique(swath_numbers):
# Do this no matter if I'm plotting primary or angles
swath_inds = daynight_swath_number == swath
n_integrations = np.sum(swath_inds)
x, y = make_swath_grid(daynight_fov[swath_inds], swath,
n_spatial_bins, n_integrations)
# Plot the primary for dayside data
if daynight:
pcolormesh_rgb_detector_image(template.data_axis,
rgb_primary[swath_inds], x, y)
template.data_axis.set_xlim(0,
angular_slit_width * (swath_numbers[-1] + 1))
template.data_axis.set_ylim(minimum_mirror_angle * 2,
maximum_mirror_angle * 2)
template.data_axis.set_xticks([])
template.data_axis.set_yticks([])
template.data_axis.set_facecolor('k')
plt.savefig(saveloc)