correct a bug where rotation doesn't update header when wcs.pc is identity
This commit is contained in:
Thibault Barnouin
@@ -651,7 +651,7 @@ def rebin_array(data_array, error_array, headers, pxsize, scale,
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if scale.lower() in ['px', 'pixel']:
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Dxy = np.array([pxsize,]*2)
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elif scale.lower() in ['arcsec','arcseconds']:
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Dxy = np.floor(pxsize/w.wcs.cdelt/3600.).astype(int)
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Dxy = np.floor(pxsize/np.abs(w.wcs.cdelt)/3600.).astype(int)
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elif scale.lower() in ['full','integrate']:
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Dxy = np.floor(image.shape).astype(int)
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else:
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@@ -1389,7 +1389,7 @@ def compute_pol(I_stokes, Q_stokes, U_stokes, Stokes_cov, headers):
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def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
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ang, SNRi_cut=None):
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ang=None, SNRi_cut=None):
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"""
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Use scipy.ndimage.rotate to rotate I_stokes to an angle, and a rotation
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matrix to rotate Q, U of a given angle in degrees and update header
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@@ -1411,9 +1411,10 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
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2D boolean array delimiting the data to work on.
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headers : header list
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List of headers corresponding to the reduced images.
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ang : float
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ang : float, optional
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Rotation angle (in degrees) that should be applied to the Stokes
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parameters
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parameters. If None, will rotate to have North up.
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Defaults to None.
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SNRi_cut : float, optional
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Cut that should be applied to the signal-to-noise ratio on I.
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Any SNR < SNRi_cut won't be displayed. If None, cut won't be applied.
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@@ -1450,6 +1451,11 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
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U_stokes[i,j] = eps*np.sqrt(Stokes_cov[2,2][i,j])
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#Rotate I_stokes, Q_stokes, U_stokes using rotation matrix
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if ang is None:
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ang = np.zeros((len(headers),))
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for i,head in enumerate(headers):
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ang[i] = -head['orientat']
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ang = ang.mean()
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alpha = ang*np.pi/180.
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mrot = np.array([[1., 0., 0.],
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[0., np.cos(2.*alpha), np.sin(2.*alpha)],
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@@ -1490,33 +1496,22 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
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#Update headers to new angle
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new_headers = []
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mrot = np.array([[np.cos(-alpha), -np.sin(-alpha)],
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[np.sin(-alpha), np.cos(-alpha)]])
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[np.sin(-alpha), np.cos(-alpha)]])
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for header in headers:
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new_header = deepcopy(header)
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new_header['orientat'] = header['orientat'] + ang
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new_wcs = WCS(header).deepcopy()
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if new_wcs.wcs.has_cd(): # CD matrix
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# Update WCS with relevant information
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HST_aper = 2400. # HST aperture in mm
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f_ratio = header['f_ratio']
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px_dim = np.array([25., 25.]) # Pixel dimension in µm
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if ref_header['pxformt'].lower() == 'zoom':
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px_dim[0] = 50.
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#new_cdelt = 206.3/3600.*px_dim/(f_ratio*HST_aper)
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new_cdelt = np.abs(np.linalg.eig(new_wcs.wcs.cd)[0])
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old_cd = new_wcs.wcs.cd
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del new_wcs.wcs.cd
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keys = ['CD1_1','CD1_2','CD2_1','CD2_2']
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for key in keys:
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new_header.remove(key, ignore_missing=True)
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new_wcs.wcs.pc = np.dot(mrot, np.dot(old_cd, np.diag(1./new_cdelt)))
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new_wcs.wcs.cdelt = new_cdelt
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elif new_wcs.wcs.has_pc(): # PC matrix + CDELT
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newpc = np.dot(mrot, new_wcs.wcs.get_pc())
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new_wcs.wcs.pc = newpc
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new_wcs.wcs.pc = np.dot(mrot, new_wcs.wcs.pc)
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print(new_wcs.wcs.pc)
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new_wcs.wcs.crpix = np.dot(mrot, new_wcs.wcs.crpix - old_center[::-1]) + new_center[::-1]
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new_wcs.wcs.set()
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new_header.update(new_wcs.to_header())
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for key, val in new_wcs.to_header().items():
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new_header.set(key,val)
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if new_wcs.wcs.pc[0,0] == 1.:
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new_header.set('PC1_1',1.)
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if new_wcs.wcs.pc[1,1] == 1.:
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new_header.set('PC2_2',1.)
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new_headers.append(new_header)
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@@ -1619,33 +1614,18 @@ def rotate_data(data_array, error_array, data_mask, headers, ang):
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#Update headers to new angle
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new_headers = []
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mrot = np.array([[np.cos(-alpha), -np.sin(-alpha)],
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[np.sin(-alpha), np.cos(-alpha)]])
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[np.sin(-alpha), np.cos(-alpha)]])
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for header in headers:
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new_header = deepcopy(header)
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new_header['orientat'] = header['orientat'] + ang
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new_wcs = WCS(header).deepcopy()
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if new_wcs.wcs.has_cd(): # CD matrix
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# Update WCS with relevant information
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HST_aper = 2400. # HST aperture in mm
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f_ratio = ref_header['f_ratio']
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px_dim = np.array([25., 25.]) # Pixel dimension in µm
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if ref_header['pxformt'].lower() == 'zoom':
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px_dim[0] = 50.
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new_cdelt = 206.3/3600.*px_dim/(f_ratio*HST_aper)
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old_cd = new_wcs.wcs.cd
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del new_wcs.wcs.cd
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keys = ['CD1_1','CD1_2','CD2_1','CD2_2']
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for key in keys:
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new_header.remove(key, ignore_missing=True)
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new_wcs.wcs.pc = np.dot(mrot, np.dot(old_cd, np.diag(1./new_cdelt)))
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new_wcs.wcs.cdelt = new_cdelt
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elif new_wcs.wcs.has_pc(): # PC matrix + CDELT
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newpc = np.dot(mrot, new_wcs.wcs.get_pc())
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new_wcs.wcs.pc = newpc
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new_wcs.wcs.pc = np.dot(mrot, new_wcs.wcs.pc)
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new_wcs.wcs.crpix = np.dot(mrot, new_wcs.wcs.crpix - old_center[::-1]) + new_center[::-1]
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new_wcs.wcs.set()
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new_header.update(new_wcs.to_header())
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for key, val in new_wcs.to_header().items():
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new_header[key] = val
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new_headers.append(new_header)
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globals()['theta'] = theta - alpha
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