Tibeuleu/FOC_Reduction
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fix wcs handling for zoomed observation, reduce all datasets

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This commit is contained in:
Thibault Barnouin
2022-07-05 18:13:45 +02:00
parent e1e1f8635e
commit fc38b24b0d
221 changed files with 74 additions and 19 deletions
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33
src/lib/reduction.py
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@@ -191,8 +191,9 @@ def bin_ndarray(ndarray, new_shape, operation='sum'):
return ndarray
def crop_array(data_array, headers, error_array=None, data_mask=None, step=5, null_val=None,
inside=False, display=False, savename=None, plots_folder=""):
def crop_array(data_array, headers, error_array=None, data_mask=None, step=5,
null_val=None, inside=False, display=False, savename=None,
plots_folder=""):
"""
Homogeneously crop an array: all contained images will have the same shape.
'inside' parameter will decide how much should be cropped.
@@ -393,8 +394,9 @@ def deconvolve_array(data_array, headers, psf='gaussian', FWHM=1., scale='px',
return deconv_array
def get_error(data_array, headers, error_array=None, data_mask=None, sub_shape=None, display=False,
savename=None, plots_folder="", return_background=False):
def get_error(data_array, headers, error_array=None, data_mask=None,
sub_shape=None, display=False, savename=None, plots_folder="",
return_background=False):
"""
Look for sub-image of shape sub_shape that have the smallest integrated
flux (no source assumption) and define the background on the image by the
@@ -1180,28 +1182,21 @@ def compute_Stokes(data_array, error_array, data_mask, headers,
# Stokes parameters
#transmittance corrected
transmit = np.ones((3,)) #will be filter dependant
filt2 = headers[0]['filtnam2']
filt3 = headers[0]['filtnam3']
filt4 = headers[0]['filtnam4']
filt2, filt3, filt4 = headers[0]['filtnam2'], headers[0]['filtnam3'], headers[0]['filtnam4']
same_filt2 = np.array([filt2 == header['filtnam2'] for header in headers]).all()
same_filt3 = np.array([filt3 == header['filtnam3'] for header in headers]).all()
same_filt4 = np.array([filt4 == header['filtnam4'] for header in headers]).all()
if not (same_filt2 and same_filt3 and same_filt4):
if (same_filt2 and same_filt3 and same_filt4):
transmit2, transmit3, transmit4 = trans2[filt2.lower()], trans3[filt3.lower()], trans4[filt4.lower()]
else:
print("WARNING : All images in data_array are not from the same \
band filter, the limiting transmittance will be taken.")
transmit2 = np.min([trans2[header['filtnam2'].lower()] for header in headers])
transmit3 = np.min([trans3[header['filtnam3'].lower()] for header in headers])
transmit4 = np.min([trans4[header['filtnam4'].lower()] for header in headers])
else :
transmit2 = trans2[filt2.lower()]
transmit3 = trans3[filt3.lower()]
transmit4 = trans4[filt4.lower()]
transmit *= transmit2*transmit3*transmit4
pol_eff = np.ones((3,))
pol_eff[0] = pol_efficiency['pol0']
pol_eff[1] = pol_efficiency['pol60']
pol_eff[2] = pol_efficiency['pol120']
pol_eff = np.array([pol_efficiency['pol0'], pol_efficiency['pol60'], pol_efficiency['pol120']])
# Orientation and error for each polarizer
fmax = np.finfo(np.float64).max
@@ -1393,7 +1388,8 @@ def compute_pol(I_stokes, Q_stokes, U_stokes, Stokes_cov, headers):
return P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P
def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers, ang, SNRi_cut=None):
def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
ang, SNRi_cut=None):
"""
Use scipy.ndimage.rotate to rotate I_stokes to an angle, and a rotation
matrix to rotate Q, U of a given angle in degrees and update header
@@ -1506,7 +1502,8 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
px_dim = np.array([25., 25.]) # Pixel dimension in µm
if ref_header['pxformt'].lower() == 'zoom':
px_dim[0] = 50.
new_cdelt = 206.3/3600.*px_dim/(f_ratio*HST_aper)
#new_cdelt = 206.3/3600.*px_dim/(f_ratio*HST_aper)
new_cdelt = np.abs(np.linalg.eig(new_wcs.wcs.cd)[0])
old_cd = new_wcs.wcs.cd
del new_wcs.wcs.cd
keys = ['CD1_1','CD1_2','CD2_1','CD2_2']