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Fixed bad-pix files generation

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This commit is contained in:
Андрей Мухин 2023-05-11 18:35:46 +03:00
parent fa640ad707
commit 07cfdab953
1 changed files with 625 additions and 626 deletions
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15
nuwavdet/nuwavdet.py
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@ -235,7 +235,7 @@ class Observation:
resized_coeff = (coeff).reshape(2, 2).repeat(180, 0).repeat(180, 1) resized_coeff = (coeff).reshape(2, 2).repeat(180, 0).repeat(180, 1)
return resized_coeff return resized_coeff
def get_data(self, file, E_borders=[3, 20]): def get_data(self, file, E_borders=[3, 20], generate_mask=True):
""" """
Returns masked array with DET1 image data for given energy band. Returns masked array with DET1 image data for given energy band.
Mask is created from observations badpix tables and to mask the border and gaps. Mask is created from observations badpix tables and to mask the border and gaps.
@ -248,10 +248,12 @@ class Observation:
data_mask = data[np.logical_not(idx_mask)] data_mask = data[np.logical_not(idx_mask)]
build_hist = lambda array: np.histogram2d(array['DET1Y'], array['DET1X'], 360, [[0, 360], [0, 360]])[0] build_hist = lambda array: np.histogram2d(array['DET1Y'], array['DET1X'], 360, [[0, 360], [0, 360]])[0]
output = build_hist(data_output) output = build_hist(data_output)
if generate_mask:
mask = build_hist(data_mask) mask = build_hist(data_mask)
mask = np.logical_or(mask, add_borders(output)) mask = np.logical_or(mask, add_borders(output))
mask = np.logical_or(mask, self.get_bad_pix(file)) mask = np.logical_or(mask, self.get_bad_pix(file))
return output, mask return output, mask
return output
def get_bad_pix(self, file, threshold=0.9): def get_bad_pix(self, file, threshold=0.9):
""" """
@ -330,7 +332,7 @@ class Observation:
""" """
Returns a hdu_list with positions of masked pixels in RAW coordinates. Returns a hdu_list with positions of masked pixels in RAW coordinates.
""" """
x_region, y_region = np.where(region) y_region, x_region = np.where(region)
hdus = [] hdus = []
for i in range(4): for i in range(4):
current_dir = os.path.dirname(__file__) current_dir = os.path.dirname(__file__)
@ -411,12 +413,12 @@ def process(obs_path, thresh):
rem_region = np.logical_and(region, np.logical_not(obs.data.mask)) rem_region = np.logical_and(region, np.logical_not(obs.data.mask))
masked_obs = np.ma.masked_array(obs.data, mask=region) masked_obs = np.ma.masked_array(obs.data, mask=region)
good_lvl = np.zeros(bin_num, dtype=bool) good_lvl = np.zeros(bin_num, dtype=bool)
good_idx = 0
if obs.exposure > 1000: if obs.exposure > 1000:
wav_obs = obs.wavdecomp('atrous', thresh, occ_coeff=True) wav_obs = obs.wavdecomp('atrous', thresh, occ_coeff=True)
wav_sum = wav_obs[2:-1].sum(0) wav_sum = wav_obs[2:-1].sum(0)
occ_coeff = obs.get_coeff() occ_coeff = obs.get_coeff()
binary_arr = binary_array(bin_num) binary_arr = binary_array(bin_num)
good_idx = len(binary_arr) - 1
for idx, lvl in enumerate(binary_arr): for idx, lvl in enumerate(binary_arr):
try: try:
@ -434,12 +436,9 @@ def process(obs_path, thresh):
rms[idx] = np.sqrt(((masked_obs-masked_obs.mean())**2).mean()) rms[idx] = np.sqrt(((masked_obs-masked_obs.mean())**2).mean())
for idx in range(len(poiss_comp)): for idx in range(len(poiss_comp)):
if ((poiss_comp[idx] < poiss_comp[good_idx]) and if ((poiss_comp[idx] < poiss_comp[-1] + 0.05) and
(poiss_comp[idx] < poiss_comp[-1] + 0.05) and (rem_area[idx] > rem_area[good_idx])):
(rem_area[idx] > rem_area[-1])):
good_idx = idx good_idx = idx
if good_idx == 0:
good_idx = len(binary_arr) - 1
good_lvl = binary_arr[good_idx] good_lvl = binary_arr[good_idx]
try: try: