get new images for NGC1068
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plots/NGC1068_x274020/NGC1068_FOC_IQU.png
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plots/NGC1068_x274020/NGC1068_FOC_combine_FWHM010_rot_IQU.png
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plots/NGC1068_x274020/NGC1068_FOC_combine_FWHM020_rot_IQU.png
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plots/NGC1068_x274020/NGC1068_FOC_gaussian_FWHM010_rot_IQU.png
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plots/NGC1068_x274020/NGC1068_FOC_gaussian_FWHM020_rot.png
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plots/NGC1068_x274020/NGC1068_FOC_gaussian_FWHM020_rot_IQU.png
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plots/NGC1068_x274020/NGC1068_FOC_gaussian_FWHM020_rot_P.png
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plots/NGC1068_x274020/NGC1068_FOC_gaussian_FWHM020_rot_P_err.png
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plots/NGC1068_x274020/NGC1068_FOC_gaussian_FWHM020_rot_SNRi.png
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@@ -16,20 +16,20 @@ import lib.plots as proj_plots #Functions for plotting data
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def main():
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def main():
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##### User inputs
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##### User inputs
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## Input and output locations
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## Input and output locations
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# globals()['data_folder'] = "../data/NGC1068_x274020/"
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globals()['data_folder'] = "../data/NGC1068_x274020/"
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# infiles = ['x274020at.c0f.fits','x274020bt.c0f.fits','x274020ct.c0f.fits',
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infiles = ['x274020at.c0f.fits','x274020bt.c0f.fits','x274020ct.c0f.fits',
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# 'x274020dt.c0f.fits','x274020et.c0f.fits','x274020ft.c0f.fits',
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'x274020dt.c0f.fits','x274020et.c0f.fits','x274020ft.c0f.fits',
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# 'x274020gt.c0f.fits','x274020ht.c0f.fits','x274020it.c0f.fits']
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'x274020gt.c0f.fits','x274020ht.c0f.fits','x274020it.c0f.fits']
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# globals()['plots_folder'] = "../plots/NGC1068_x274020/"
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globals()['plots_folder'] = "../plots/NGC1068_x274020/"
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# globals()['data_folder'] = "../data/NGC1068_x14w010/"
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# globals()['data_folder'] = "../data/NGC1068_x14w010/"
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# infiles = ['x14w0101t_c0f.fits','x14w0102t_c0f.fits','x14w0103t_c0f.fits',
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# infiles = ['x14w0101t_c0f.fits','x14w0102t_c0f.fits','x14w0103t_c0f.fits',
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# 'x14w0104t_c0f.fits','x14w0105p_c0f.fits','x14w0106t_c0f.fits']
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# 'x14w0104t_c0f.fits','x14w0105p_c0f.fits','x14w0106t_c0f.fits']
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# globals()['plots_folder'] = "../plots/NGC1068_x14w010/"
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# globals()['plots_folder'] = "../plots/NGC1068_x14w010/"
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globals()['data_folder'] = "../data/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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# 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()['plots_folder'] = "../plots/3C405_x136060/"
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# globals()['data_folder'] = "../data/CygnusA_x43w0/"
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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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# infiles = ['x43w0101r_c0f.fits', 'x43w0102r_c0f.fits', 'x43w0103r_c0f.fits',
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@@ -91,22 +91,22 @@ def main():
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# Data binning
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# Data binning
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rebin = True
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rebin = True
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if rebin:
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if rebin:
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pxsize = 0.50
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pxsize = 0.10
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px_scale = 'arcsec' #pixel or arcsec
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px_scale = 'arcsec' #pixel or arcsec
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rebin_operation = 'sum' #sum or average
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rebin_operation = 'sum' #sum or average
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# Alignement
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# Alignement
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align_center = 'image' #If None will align image to image center
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align_center = 'image' #If None will align image to image center
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display_data = False
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display_data = False
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# Smoothing
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# Smoothing
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smoothing_function = 'combine' #gaussian_after, gaussian or combine
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smoothing_function = 'gaussian' #gaussian_after, gaussian or combine
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smoothing_FWHM = 1.00 #If None, no smoothing is done
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smoothing_FWHM = 0.10 #If None, no smoothing is done
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smoothing_scale = 'arcsec' #pixel or arcsec
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smoothing_scale = 'arcsec' #pixel or arcsec
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# Rotation
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# Rotation
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rotate_stokes = True #rotation to North convention can give erroneous results
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rotate_stokes = True #rotation to North convention can give erroneous results
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rotate_data = False #rotation to North convention can give erroneous results
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rotate_data = False #rotation to North convention can give erroneous results
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# Polarization map output
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# Polarization map output
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figname = '3C405_FOC' #target/intrument name
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figname = 'NGC1068_FOC' #target/intrument name
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figtype = '_combine_FWHM100_rot' #additionnal informations
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figtype = '_gaussian_FWHM010_rot' #additionnal informations
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SNRp_cut = 3 #P measurments with SNR>3
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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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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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step_vec = 1 #plot all vectors in the array. if step_vec = 2, then every other vector will be plotted
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