Tibeuleu/FOC_Reduction
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Change some error handling for better smoothing

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This commit is contained in:
Thibault Barnouin
2021-06-17 23:15:31 +02:00
parent 44a060e2ae
commit d9c45870e6
70 changed files with 31 additions and 29 deletions
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30
src/lib/reduction.py
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@@ -800,7 +800,7 @@ def smooth_data(data_array, error_array, data_mask, headers, FWHM=1.,
raise ValueError("Not all images in array have same pixel size")
FWHM /= pxsize[0].min()
#Define gaussian stdev
# Define gaussian stdev
stdev = FWHM/(2.*np.sqrt(2.*np.log(2)))
fmax = np.finfo(np.float64).max
@@ -821,15 +821,16 @@ def smooth_data(data_array, error_array, data_mask, headers, FWHM=1.,
dist_rc = np.where(data_mask, fmax, np.sqrt((r-xx)**2+(c-yy)**2))
g_rc = np.array([np.exp(-0.5*(dist_rc/stdev)**2),]*len(data_array))
# Apply weighted combination
if data_mask[r,c]:
smoothed[r,c] = 0.
error[r,c] = 1.
else:
smoothed[r,c] = np.sum(data_array*weight*g_rc)/np.sum(weight*g_rc)
error[r,c] = np.sqrt(np.sum(weight*g_rc**2))/np.sum(weight*g_rc)
smoothed[r,c] = (1.-data_mask[r,c])*np.sum(data_array*weight*g_rc)/np.sum(weight*g_rc)
error[r,c] = np.sqrt(np.sum(weight*g_rc**2))/np.sum(weight*g_rc)
# Nan handling
error[np.isnan(smoothed)] = 0.
smoothed[np.isnan(smoothed)] = 0.
error[np.isnan(error)] = 0.
elif smoothing.lower() in ['gauss','gaussian']:
#Convolution with gaussian function
# Convolution with gaussian function
smoothed = np.zeros(data_array.shape)
error = np.zeros(error_array.shape)
for i,image in enumerate(data_array):
@@ -838,12 +839,13 @@ def smooth_data(data_array, error_array, data_mask, headers, FWHM=1.,
for c in range(image.shape[1]):
dist_rc = np.where(data_mask, fmax, np.sqrt((r-xx)**2+(c-yy)**2))
g_rc = np.exp(-0.5*(dist_rc/stdev)**2)/(2.*np.pi*stdev**2)
if data_mask[r,c]:
smoothed[r,c] = 0.
error[r,c] = 1.
else:
smoothed[r,c] = np.sum(data_array*weight*g_rc)/np.sum(weight*g_rc)
error[r,c] = np.sqrt(np.sum(weight*g_rc**2))/np.sum(weight*g_rc)
smoothed[i][r,c] = (1.-data_mask[r,c])*np.sum(data_array*weight*g_rc)/np.sum(weight*g_rc)
error[i][r,c] = np.sqrt(np.sum(weight*g_rc**2))/np.sum(weight*g_rc)
# Nan handling
error[i][np.isnan(smoothed)] = 0.
smoothed[i][np.isnan(smoothed)] = 0.
error[i][np.isnan(error)] = 0.
else:
raise ValueError("{} is not a valid smoothing option".format(smoothing))