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[WIP]: Long-forgotten commit - bad pixel search #120

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[WIP]: Long-forgotten commit - bad pixel search #120

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37 changes: 24 additions & 13 deletions jwst_reffiles/bad_pixel_mask/badpix_from_flats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -668,8 +668,6 @@ def average_last4groups(hdu_list):
"""
filename = hdu_list[0].header['FILENAME']
dims = hdu_list['SCI'].data.shape
dims = hdu_list['SCI'].data.shape
dims = hdu_list['SCI'].data.shape
group4 = np.zeros((4, dims[-2], dims[-1]))

# for multiple integrations
Expand All @@ -678,19 +676,19 @@ def average_last4groups(hdu_list):
# dims[1] = number of groups
if dims[1] < 4:
raise ValueError('Input file {} has fewer than 4 groups.'.format(filename))
group4[0, :, :] = np.mean(hdu_list['SCI'].data[:, 0, :, :], axis=0)
group4[1, :, :] = np.mean(hdu_list['SCI'].data[:, 1, :, :], axis=0)
group4[2, :, :] = np.mean(hdu_list['SCI'].data[:, 2, :, :], axis=0)
group4[3, :, :] = np.mean(hdu_list['SCI'].data[:, 3, :, :], axis=0)
group4[0, :, :] = np.mean(hdu_list['SCI'].data[:, -4, :, :], axis=0)
group4[1, :, :] = np.mean(hdu_list['SCI'].data[:, -2, :, :], axis=0)
group4[2, :, :] = np.mean(hdu_list['SCI'].data[:, -2, :, :], axis=0)
group4[3, :, :] = np.mean(hdu_list['SCI'].data[:, -1, :, :], axis=0)
ave_group = np.mean(group4, axis=0)

elif len(dims) == 3:
if dims[0] < 4:
raise ValueError('Input file {} has fewer than 10 groups.'.format(filename))
group4[0, :, :] = hdu_list['SCI'].data[0, :, :]
group4[1, :, :] = hdu_list['SCI'].data[1, :, :]
group4[2, :, :] = hdu_list['SCI'].data[2, :, :]
group4[3, :, :] = hdu_list['SCI'].data[3, :, :]
group4[0, :, :] = hdu_list['SCI'].data[-4, :, :]
group4[1, :, :] = hdu_list['SCI'].data[-3, :, :]
group4[2, :, :] = hdu_list['SCI'].data[-2, :, :]
group4[3, :, :] = hdu_list['SCI'].data[-1, :, :]
ave_group = np.mean(group4, axis=0)

# change format so it is 3 dim
Expand Down Expand Up @@ -1123,12 +1121,14 @@ def read_files(filenames, dead_search_type):
data : numpy.ndarray
3D stack of data
"""
integrations = None
for i, filename in enumerate(filenames):
with fits.open(filename) as hdu_list:
# Get some basic metadata
instrument = hdu_list[0].header['INSTRUME'].upper()
detector = hdu_list[0].header['DETECTOR'].upper()
aperture = hdu_list[0].header['SUBARRAY'].upper()
ngroups = hdu_list[0].header['NGROUPS']
try:
rampfit = hdu_list[0].header['S_RAMP']
except KeyError:
Expand Down Expand Up @@ -1156,7 +1156,13 @@ def read_files(filenames, dead_search_type):
'The inputs for the saturation check '
'cannot be slope images.').format(os.path.basename(filename)))
else:
exposure = average_last4groups(hdu_list)
# Only create a mean image if there are more than 3 groups
if ngroups >= 4:
exposure = average_last4groups(hdu_list)
if integrations is None:
integrations = copy.deepcopy(exposure)
else:
continue
else:
raise ValueError('Unknown dead sarch type option: {}.'.format(dead_search_type))

Expand All @@ -1166,7 +1172,8 @@ def read_files(filenames, dead_search_type):
comparison_instrument = copy.deepcopy(instrument)
comparison_detector = copy.deepcopy(detector)
comparison_aperture = copy.deepcopy(aperture)
integrations = copy.deepcopy(exposure)
if integrations is None:
integrations = copy.deepcopy(exposure)

# Consistency checks
if instrument != comparison_instrument:
Expand All @@ -1177,7 +1184,11 @@ def read_files(filenames, dead_search_type):
raise ValueError('Inconsistent apertures in input data!')

# Stack the new integrations onto the outuput
integrations = np.concatenate((integrations, exposure), axis=0)
try:
integrations = np.concatenate((integrations, exposure), axis=0)
except ValueError:
print(i, filename)
raise ValueError("Cannot concatenate. Integrations shape: {}, exposure shape: {}".format(integrations.shape, exposure.shape))
return integrations, comparison_instrument, comparison_detector


Expand Down