Output several new maps for updated rotation of 3C405
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@@ -29,10 +29,9 @@ def main():
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# 'x14w0104t_c1f.fits','x14w0105p_c1f.fits','x14w0106t_c1f.fits']
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# globals()['plots_folder'] = "../plots/NGC1068_x14w010/"
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# globals()['data_folder'] = "../data/3C405_x136060/"
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# infiles = ['x1360601t_c0f.fits','x1360602t_c0f.fits','x1360603t_c0f.fits']
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# infiles = ['x1360601t_c1f.fits','x1360602t_c1f.fits','x1360603t_c1f.fits']
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# globals()['plots_folder'] = "../plots/3C405_x136060/"
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globals()['data_folder'] = "../data/3C405_x136060/"
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infiles = ['x1360601t_c0f.fits','x1360602t_c0f.fits','x1360603t_c0f.fits']
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globals()['plots_folder'] = "../plots/3C405_x136060/"
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# globals()['data_folder'] = "../data/CygnusA_x43w0/"
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# infiles = ['x43w0101r_c0f.fits', 'x43w0102r_c0f.fits', 'x43w0103r_c0f.fits',
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@@ -46,13 +45,13 @@ def main():
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# infiles = ['x3mc0101m_c0f.fits','x3mc0102m_c0f.fits','x3mc0103m_c0f.fits']
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# globals()['plots_folder'] = "../plots/3C109_x3mc010/"
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globals()['data_folder'] = "../data/MKN463_x2rp030/"
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infiles = ['x2rp0201t_c0f.fits', 'x2rp0203t_c0f.fits', 'x2rp0205t_c0f.fits',
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'x2rp0207t_c0f.fits', 'x2rp0302t_c0f.fits', 'x2rp0304t_c0f.fits',
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'x2rp0306t_c0f.fits', 'x2rp0202t_c0f.fits', 'x2rp0204t_c0f.fits',
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'x2rp0206t_c0f.fits', 'x2rp0301t_c0f.fits', 'x2rp0303t_c0f.fits',
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'x2rp0305t_c0f.fits', 'x2rp0307t_c0f.fits']
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globals()['plots_folder'] = "../plots/MKN463_x2rp030/"
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# globals()['data_folder'] = "../data/MKN463_x2rp030/"
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# infiles = ['x2rp0201t_c0f.fits', 'x2rp0202t_c0f.fits', 'x2rp0203t_c0f.fits',
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# 'x2rp0204t_c0f.fits', 'x2rp0205t_c0f.fits', 'x2rp0206t_c0f.fits',
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# 'x2rp0207t_c0f.fits', 'x2rp0301t_c0f.fits', 'x2rp0302t_c0f.fits',
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# 'x2rp0303t_c0f.fits', 'x2rp0304t_c0f.fits', 'x2rp0305t_c0f.fits',
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# 'x2rp0306t_c0f.fits', 'x2rp0307t_c0f.fits']
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# globals()['plots_folder'] = "../plots/MKN463_x2rp030/"
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# globals()['data_folder'] = "../data/PG1630+377_x39510/"
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# infiles = ['x3990201m_c0f.fits', 'x3990205m_c0f.fits', 'x3995101r_c0f.fits',
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@@ -89,12 +88,12 @@ def main():
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psf_shape=(9,9)
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iterations = 10
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# Error estimation
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error_sub_shape = (100,100)
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error_sub_shape = (150,150)
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display_error = False
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# Data binning
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rebin = True
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if rebin:
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pxsize = 0.10
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pxsize = 0.50
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px_scale = 'arcsec' #pixel or arcsec
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rebin_operation = 'sum' #sum or average
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# Alignement
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@@ -102,13 +101,13 @@ def main():
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display_data = False
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# Smoothing
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smoothing_function = 'combine' #gaussian_after, gaussian or combine
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smoothing_FWHM = 0.20 #If None, no smoothing is done
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smoothing_FWHM = 1.00 #If None, no smoothing is done
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smoothing_scale = 'arcsec' #pixel or arcsec
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# Rotation
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rotate = True #rotation to North convention can give erroneous results
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# Polarization map output
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figname = 'MKN463_FOC' #target/intrument name
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figtype = '_combine_FWHM020_rot' #additionnal informations
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figname = '3C405_FOC' #target/intrument name
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figtype = '_combine_FWHM100_rot' #additionnal informations
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SNRp_cut = 3 #P measurments with SNR>3
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SNRi_cut = 30 #I measurments with SNR>30, which implies an uncertainty in P of 4.7%.
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step_vec = 1 #plot all vectors in the array. if step_vec = 2, then every other vector will be plotted
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@@ -1132,15 +1132,15 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, headers, ang):
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#Rotate original images using scipy.ndimage.rotate
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new_I_stokes = sc_rotate(new_I_stokes, ang, reshape=False,
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cval=np.sqrt(new_Stokes_cov[0,0][0,0]))
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cval=0.10*np.sqrt(new_Stokes_cov[0,0][0,0]))
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new_Q_stokes = sc_rotate(new_Q_stokes, ang, reshape=False,
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cval=np.sqrt(new_Stokes_cov[1,1][0,0]))
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cval=0.10*np.sqrt(new_Stokes_cov[1,1][0,0]))
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new_U_stokes = sc_rotate(new_U_stokes, ang, reshape=False,
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cval=np.sqrt(new_Stokes_cov[2,2][0,0]))
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cval=0.10*np.sqrt(new_Stokes_cov[2,2][0,0]))
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for i in range(3):
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for j in range(3):
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new_Stokes_cov[i,j] = sc_rotate(new_Stokes_cov[i,j], ang, reshape=False,
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cval=new_Stokes_cov[i,j].mean())
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cval=0.10*new_Stokes_cov[i,j].mean())
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#Update headers to new angle
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new_headers = []
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