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correct CRPIX handlign when cropping/aligning/rotating

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This commit is contained in:
Thibault Barnouin
2022-03-14 11:22:13 +01:00
parent fd43cc87d7
commit 8d931d75f3
10 changed files with 47 additions and 27 deletions
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64
src/lib/reduction.py
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@@ -216,6 +216,10 @@ def crop_array(data_array, headers, error_array=None, step=5, null_val=None,
Returns:
cropped_array : numpy.ndarray
Array containing the observationnal data homogeneously cropped.
headers : header list
Updated headers associated with the images in data_array.
cropped_error : numpy.ndarray
Array containing the error on the observationnal data homogeneously cropped.
"""
if error_array is None:
error_array = np.zeros(data_array.shape)
@@ -282,11 +286,16 @@ def crop_array(data_array, headers, error_array=None, step=5, null_val=None,
crop_array = np.zeros((data_array.shape[0],new_shape[0],new_shape[1]))
crop_error_array = np.zeros((data_array.shape[0],new_shape[0],new_shape[1]))
for i,image in enumerate(data_array): #Put the image data in the cropped array
for i,image in enumerate(data_array):
#Put the image data in the cropped array
crop_array[i] = image[v_array[0]:v_array[1],v_array[2]:v_array[3]]
crop_error_array[i] = error_array[i][v_array[0]:v_array[1],v_array[2]:v_array[3]]
#Update CRPIX value in the associated header
curr_wcs = deepcopy(WCS(headers[i]))
curr_wcs.wcs.crpix = curr_wcs.wcs.crpix - np.array([v_array[0], v_array[2]])
headers[i].update(curr_wcs.to_header())
return crop_array, crop_error_array
return crop_array, crop_error_array, headers
def deconvolve_array(data_array, headers, psf='gaussian', FWHM=1., scale='px',
@@ -353,7 +362,7 @@ def deconvolve_array(data_array, headers, psf='gaussian', FWHM=1., scale='px',
return deconv_array
def get_error(data_array, sub_shape=(15,15), display=False, headers=None,
def get_error(data_array, headers, sub_shape=(15,15), display=False,
savename=None, plots_folder="", return_background=False):
"""
Look for sub-image of shape sub_shape that have the smallest integrated
@@ -363,6 +372,8 @@ def get_error(data_array, sub_shape=(15,15), display=False, headers=None,
Inputs:
data_array : numpy.ndarray
Array containing the data to study (2D float arrays).
headers : header list
Headers associated with the images in data_array.
sub_shape : tuple, optional
Shape of the sub-image to look for. Must be odd.
Defaults to (15,15).
@@ -370,10 +381,6 @@ def get_error(data_array, sub_shape=(15,15), display=False, headers=None,
If True, data_array will be displayed with a rectangle around the
sub-image selected for background computation.
Defaults to False.
headers : header list, optional
Headers associated with the images in data_array. Will only be used if
display is True.
Defaults to None.
savename : str, optional
Name of the figure the map should be saved to. If None, the map won't
be saved (only displayed). Only used if display is True.
@@ -390,6 +397,8 @@ def get_error(data_array, sub_shape=(15,15), display=False, headers=None,
Returns:
data_array : numpy.ndarray
Array containing the data to study minus the background.
headers : header list
Updated headers associated with the images in data_array.
error_array : numpy.ndarray
Array containing the background values associated to the images in
data_array.
@@ -399,7 +408,7 @@ def get_error(data_array, sub_shape=(15,15), display=False, headers=None,
Only returned if return_background is True.
"""
# Crop out any null edges
data, error = crop_array(data_array, headers, step=5, null_val=0., inside=False)
data, error, headers = crop_array(data_array, headers, step=5, null_val=0., inside=False)
sub_shape = np.array(sub_shape)
# Make sub_shape of odd values
@@ -449,7 +458,6 @@ def get_error(data_array, sub_shape=(15,15), display=False, headers=None,
print(data_array[i])
if display:
convert_flux = headers[0]['photflam']
date_time = np.array([headers[i]['date-obs']+';'+headers[i]['time-obs']
for i in range(len(headers))])
@@ -497,9 +505,9 @@ def get_error(data_array, sub_shape=(15,15), display=False, headers=None,
plt.show()
if return_background:
return data_array, error_array, np.array([error_array[i][0,0] for i in range(error_array.shape[0])])
return data_array, error_array, headers, np.array([error_array[i][0,0] for i in range(error_array.shape[0])])
else:
return data_array, error_array
return data_array, error_array, headers
def rebin_array(data_array, error_array, headers, pxsize, scale,
@@ -656,19 +664,21 @@ def align_data(data_array, headers, error_array=None, upsample_factor=1.,
raise ValueError("All images in data_array must have same shape as\
ref_data")
if error_array is None:
_, error_array, background = get_error(data_array, return_background=True)
_, error_array, headers, background = get_error(data_array, headers, return_background=True)
else:
_, _, background = get_error(data_array, return_background=True)
_, _, headers, background = get_error(data_array, headers, return_background=True)
# Crop out any null edges
#(ref_data must be cropped as well)
full_array = np.concatenate((data_array,[ref_data]),axis=0)
full_headers = deepcopy(headers)
full_headers.append(headers[0])
err_array = np.concatenate((error_array,[np.zeros(ref_data.shape)]),axis=0)
full_array, err_array = crop_array(full_array, headers, err_array, step=5,
full_array, err_array, full_headers = crop_array(full_array, full_headers, err_array, step=5,
inside=False)
data_array, ref_data = full_array[:-1], full_array[-1]
data_array, ref_data, headers = full_array[:-1], full_array[-1], full_headers[:-1]
error_array = err_array[:-1]
if ref_center is None:
@@ -723,14 +733,22 @@ def align_data(data_array, headers, error_array=None, upsample_factor=1.,
shifts.append(shift)
errors.append(error)
shifts = np.array(shifts)
errors = np.array(errors)
# Update headers CRPIX value
added_pix = (np.array(rescaled_image.shape[1:]) - np.array(data_array.shape[1:]))/2
headers_wcs = [deepcopy(WCS(header)) for header in headers]
new_crpix = np.array([wcs.wcs.crpix for wcs in headers_wcs]) + shifts + added_pix
for i in range(len(headers_wcs)):
headers_wcs[i].wcs.crpix = new_crpix.mean(axis=0)
headers[i].update(headers_wcs[i].to_header())
if return_shifts:
return rescaled_image, rescaled_error, rescaled_mask.any(axis=0), shifts, errors
return rescaled_image, rescaled_error, headers, rescaled_mask.any(axis=0), shifts, errors
else:
return rescaled_image, rescaled_error, rescaled_mask.any(axis=0)
return rescaled_image, rescaled_error, headers, rescaled_mask.any(axis=0)
def smooth_data(data_array, error_array, data_mask, headers, FWHM=1.,
@@ -1316,6 +1334,8 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
new_Stokes_cov[i,j] = sc_rotate(new_Stokes_cov[i,j], ang,
reshape=False, cval=0.)
new_Stokes_cov[i,i] = np.abs(new_Stokes_cov[i,i])
center = np.array(new_I_stokes.shape)/2
print('c',center)
#Update headers to new angle
new_headers = []
@@ -1324,7 +1344,6 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
for header in headers:
new_header = deepcopy(header)
new_header['orientat'] = header['orientat'] + ang
new_wcs = WCS(header).deepcopy()
if new_wcs.wcs.has_cd(): # CD matrix
# Update WCS with relevant information
@@ -1344,6 +1363,7 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
elif new_wcs.wcs.has_pc(): # PC matrix + CDELT
newpc = np.dot(mrot, new_wcs.wcs.get_pc())
new_wcs.wcs.pc = newpc
new_wcs.wcs.crpix = np.dot(mrot, new_wcs.wcs.crpix - center) + center
new_wcs.wcs.set()
new_header.update(new_wcs.to_header())
@@ -1359,9 +1379,9 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
new_U_stokes[np.isnan(new_U_stokes)] = 0.
new_Stokes_cov[np.isnan(new_Stokes_cov)] = fmax
return new_I_stokes, new_Q_stokes, new_U_stokes, new_Stokes_cov, new_data_mask, new_headers
return new_I_stokes, new_Q_stokes, new_U_stokes, new_Stokes_cov, new_headers, new_data_mask
def rotate_data(data_array, error_array, data_mask, headers, ang):
def rotate_data(data_array, error_array, headers, data_mask, ang):
"""
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
@@ -1437,4 +1457,4 @@ def rotate_data(data_array, error_array, data_mask, headers, ang):
new_headers.append(new_header)
return new_data_array, new_error_array, new_data_mask, new_headers
return new_data_array, new_error_array, new_headers, new_data_mask