Tibeuleu/FOC_Reduction
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overplot IC5063 with Radio and IR

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Tibeuleu
2022-11-08 13:32:11 +01:00
parent a5d02fc0c0
commit 359e5b401f
22 changed files with 53 additions and 50 deletions
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14
src/lib/reduction.py
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@@ -246,10 +246,10 @@ def crop_array(data_array, headers, error_array=None, data_mask=None, step=5,
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.
headers : header list
Updated headers associated with the images in data_array.
"""
if error_array is None:
error_array = np.zeros(data_array.shape)
@@ -284,7 +284,7 @@ def crop_array(data_array, headers, error_array=None, data_mask=None, step=5,
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(crop_headers[i]))
curr_wcs.wcs.crpix = curr_wcs.wcs.crpix - np.array([v_array[2], v_array[0]])
curr_wcs.wcs.crpix[:2] = curr_wcs.wcs.crpix[:2] - np.array([v_array[2], v_array[0]])
crop_headers[i].update(curr_wcs.to_header())
crop_headers[i]['naxis1'], crop_headers[i]['naxis2'] = crop_array[i].shape
@@ -1606,11 +1606,11 @@ def rotate_data(data_array, error_array, data_mask, headers, ang):
Updated array containing the rotated images.
new_error_array : numpy.ndarray
Updated array containing the rotated errors.
new_data_mask : numpy.ndarray
Updated 2D boolean array delimiting the data to work on.
new_headers : header list
Updated list of headers corresponding to the reduced images accounting
for the new orientation angle.
new_data_mask : numpy.ndarray
Updated 2D boolean array delimiting the data to work on.
"""
#Rotate I_stokes, Q_stokes, U_stokes using rotation matrix
alpha = ang*np.pi/180.
@@ -1649,8 +1649,8 @@ def rotate_data(data_array, error_array, data_mask, headers, ang):
new_wcs = WCS(header).deepcopy()
new_wcs.wcs.pc = np.dot(mrot, new_wcs.wcs.pc)
new_wcs.wcs.crpix = np.dot(mrot, new_wcs.wcs.crpix - old_center[::-1]) + new_center[::-1]
new_wcs.wcs.pc[:2,:2] = np.dot(mrot, new_wcs.wcs.pc[:2,:2])
new_wcs.wcs.crpix[:2] = np.dot(mrot, new_wcs.wcs.crpix[:2] - old_center[::-1]) + new_center[::-1]
new_wcs.wcs.set()
for key, val in new_wcs.to_header().items():
new_header[key] = val