Change background estimation to max of histogram
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Tibeuleu
@@ -40,11 +40,11 @@ globals()['plots_folder'] = "../plots/NGC1068_x274020/"
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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()['infiles'] = ['x43w0101r_c0f.fits', 'x43w0102r_c0f.fits', 'x43w0103r_c0f.fits',
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## 'x43w0104r_c0f.fits', 'x43w0105r_c0f.fits', 'x43w0106r_c0f.fits',
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## 'x43w0107r_c0f.fits', 'x43w0108r_c0f.fits', 'x43w0109r_c0f.fits']
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#globals()['infiles'] = ['x43w0201r_c0f.fits', 'x43w0202r_c0f.fits', 'x43w0203r_c0f.fits',
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# 'x43w0204r_c0f.fits', 'x43w0205r_c0f.fits', 'x43w0206r_c0f.fits']
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#globals()['infiles'] = ['x43w0101r_c0f.fits', 'x43w0102r_c0f.fits', 'x43w0103r_c0f.fits',
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# 'x43w0104r_c0f.fits', 'x43w0105r_c0f.fits', 'x43w0106r_c0f.fits',
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# 'x43w0107r_c0f.fits', 'x43w0108r_c0f.fits', 'x43w0109r_c0f.fits'] #F342W
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##globals()['infiles'] = ['x43w0201r_c0f.fits', 'x43w0202r_c0f.fits', 'x43w0203r_c0f.fits',
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## 'x43w0204r_c0f.fits', 'x43w0205r_c0f.fits', 'x43w0206r_c0f.fits'] #F275W
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#globals()['plots_folder'] = "../plots/CygnusA_x43w0/"
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#globals()['data_folder'] = "../data/3C109_x3mc010/"
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@@ -72,8 +72,8 @@ globals()['plots_folder'] = "../plots/NGC1068_x274020/"
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#globals()['plots_folder'] = "../plots/MKN3_x3nl010/"
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#globals()['data_folder'] = "../data/MKN3_x3md010/"
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##globals()['infiles'] = ['x3md0101r_c0f.fits', 'x3md0102r_c0f.fits', 'x3md0103r_c0f.fits']
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#globals()['infiles'] = ['x3md0104r_c0f.fits', 'x3md0105r_c0f.fits', 'x3md0106r_c0f.fits']
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#globals()['infiles'] = ['x3md0101r_c0f.fits', 'x3md0102r_c0f.fits', 'x3md0103r_c0f.fits'] #F275W
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##globals()['infiles'] = ['x3md0104r_c0f.fits', 'x3md0105r_c0f.fits', 'x3md0106r_c0f.fits'] #F342W
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#globals()['plots_folder'] = "../plots/MKN3_x3md010/"
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#globals()['data_folder'] = "../data/MKN78_x3nl020/"
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@@ -91,19 +91,19 @@ globals()['plots_folder'] = "../plots/NGC1068_x274020/"
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#BEWARE: 5 observations separated by 1 year each (1995, 1996, 1997, 1998, 1999)
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#globals()['data_folder'] = "../data/M87/POS1/"
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#globals()['infiles'] = ['x2py010ct_c0f.fits','x2py010dt_c0f.fits','x2py010et_c0f.fits','x2py010ft_c0f.fits'] #1995
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#globals()['infiles'] = ['x3be010ct_c0f.fits','x3be010dt_c0f.fits','x3be010et_c0f.fits','x3be010ft_c0f.fits'] #1996
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#globals()['infiles'] = ['x43r010km_c0f.fits','x43r010mm_c0f.fits','x43r010om_c0f.fits','x43r010rm_c0f.fits'] #1997
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#globals()['infiles'] = ['x43r110kr_c0f.fits','x43r110mr_c0f.fits','x43r110or_c0f.fits','x43r110rr_c0f.fits'] #1998
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##globals()['infiles'] = ['x2py010ct_c0f.fits','x2py010dt_c0f.fits','x2py010et_c0f.fits','x2py010ft_c0f.fits'] #1995
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##globals()['infiles'] = ['x3be010ct_c0f.fits','x3be010dt_c0f.fits','x3be010et_c0f.fits','x3be010ft_c0f.fits'] #1996
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##globals()['infiles'] = ['x43r010km_c0f.fits','x43r010mm_c0f.fits','x43r010om_c0f.fits','x43r010rm_c0f.fits'] #1997
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##globals()['infiles'] = ['x43r110kr_c0f.fits','x43r110mr_c0f.fits','x43r110or_c0f.fits','x43r110rr_c0f.fits'] #1998
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#globals()['infiles'] = ['x43r210kr_c0f.fits','x43r210mr_c0f.fits','x43r210or_c0f.fits','x43r210rr_c0f.fits'] #1999
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#globals()['plots_folder'] = "../plots/M87/POS1/"
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#BEWARE: 5 observations separated by 1 year each (1995, 1996, 1997, 1998, 1999)
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#globals()['data_folder'] = "../data/M87/POS3/"
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#globals()['infiles'] = ['x2py030at_c0f.fits','x2py030bt_c0f.fits','x2py030ct_c0f.fits','x2py0309t_c0f.fits'] #1995
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#globals()['infiles'] = ['x3be030at_c0f.fits','x3be030bt_c0f.fits','x3be030ct_c0f.fits','x3be0309t_c0f.fits'] #1996
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#globals()['infiles'] = ['x43r030em_c0f.fits','x43r030gm_c0f.fits','x43r030im_c0f.fits','x43r030lm_c0f.fits'] #1997
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#globals()['infiles'] = ['x43r130er_c0f.fits','x43r130fr_c0f.fits','x43r130ir_c0f.fits','x43r130lr_c0f.fits'] #1998
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##globals()['infiles'] = ['x2py030at_c0f.fits','x2py030bt_c0f.fits','x2py030ct_c0f.fits','x2py0309t_c0f.fits'] #1995
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##globals()['infiles'] = ['x3be030at_c0f.fits','x3be030bt_c0f.fits','x3be030ct_c0f.fits','x3be0309t_c0f.fits'] #1996
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##globals()['infiles'] = ['x43r030em_c0f.fits','x43r030gm_c0f.fits','x43r030im_c0f.fits','x43r030lm_c0f.fits'] #1997
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##globals()['infiles'] = ['x43r130er_c0f.fits','x43r130fr_c0f.fits','x43r130ir_c0f.fits','x43r130lr_c0f.fits'] #1998
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#globals()['infiles'] = ['x43r230er_c0f.fits','x43r230fr_c0f.fits','x43r230ir_c0f.fits','x43r230lr_c0f.fits'] #1999
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#globals()['plots_folder'] = "../plots/M87/POS3/"
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@@ -123,20 +123,20 @@ def main():
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# Initial crop
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display_crop = False
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# Error estimation
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error_sub_shape = (10,10)
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error_sub_shape = (80,80)
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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 = 10
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px_scale = 'pixel' #pixel, arcsec or full
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pxsize = 0.05
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px_scale = 'arcsec' #pixel, arcsec or full
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rebin_operation = 'sum' #sum or average
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# Alignement
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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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# Smoothing
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smoothing_function = 'combine' #gaussian_after, weighted_gaussian_after, gaussian, weighted_gaussian or combine
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smoothing_FWHM = None #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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# Rotation
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rotate_stokes = True #rotation to North convention can give erroneous results
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@@ -146,7 +146,7 @@ def main():
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final_display = False
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# Polarization map output
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figname = 'NGC1068_FOC' #target/intrument name
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figtype = '_bin10px' #additionnal informations
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figtype = '_combine_FWHM010' #additionnal informations
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SNRp_cut = 5. #P measurments with SNR>3
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SNRi_cut = 50. #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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@@ -163,15 +163,13 @@ def main():
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# Deconvolve data using Richardson-Lucy iterative algorithm with a gaussian PSF of given FWHM.
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if deconvolve:
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data_array = proj_red.deconvolve_array(data_array, headers, psf=psf, FWHM=psf_FWHM, scale=psf_scale, shape=psf_shape, iterations=iterations, algo=algo)
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# Rotate data to have North up
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if rotate_data:
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data_mask = np.ones(data_array.shape[1:]).astype(bool)
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alpha = headers[0]['orientat']
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mrot = np.array([[np.cos(-alpha), -np.sin(-alpha)], [np.sin(-alpha), np.cos(-alpha)]])
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data_array, error_array, data_mask, headers = proj_red.rotate_data(data_array, error_array, data_mask, headers, -alpha)
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# Estimate error from data background, estimated from sub-image of desired sub_shape.
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if px_scale.lower() not in ['full','integrate']:
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#data_array, error_array, headers, background = proj_red.get_error(data_array, headers, error_array, sub_shape=error_sub_shape, display=display_error, savename=figname+"_errors", plots_folder=plots_folder, return_background=True)
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data_array, error_array, headers, background = proj_red.get_error2(data_array, headers, error_array, display=display_error, savename=figname+"_errors", plots_folder=plots_folder, return_background=True)
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# Align and rescale images with oversampling.
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data_array, error_array, headers, data_mask = proj_red.align_data(data_array, headers, error_array=error_array, upsample_factor=10, ref_center=align_center, return_shifts=False)
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data_array, error_array, headers, data_mask = proj_red.align_data(data_array, headers, error_array=error_array, background=background, upsample_factor=10, ref_center=align_center, return_shifts=False)
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# Rebin data to desired pixel size.
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if rebin:
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@@ -179,9 +177,11 @@ def main():
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data_array, error_array, headers = proj_red.get_error(data_array, headers, error_array, data_mask, sub_shape=error_sub_shape, display=display_error, savename=figname+"_errors", plots_folder=plots_folder)
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data_array, error_array, headers, Dxy, data_mask = proj_red.rebin_array(data_array, error_array, headers, pxsize=pxsize, scale=px_scale, operation=rebin_operation, data_mask=data_mask)
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# Estimate error from data background, estimated from sub-image of desired sub_shape.
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if px_scale.lower() not in ['full','integrate']:
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data_array, error_array, headers = proj_red.get_error(data_array, headers, error_array, data_mask, sub_shape=error_sub_shape, display=display_error, savename=figname+"_errors", plots_folder=plots_folder)
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# Rotate data to have North up
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if rotate_data:
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data_mask = np.ones(data_array.shape[1:]).astype(bool)
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alpha = headers[0]['orientat']
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data_array, error_array, data_mask, headers = proj_red.rotate_data(data_array, error_array, data_mask, headers, -alpha)
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#Plot array for checking output
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if display_data and px_scale.lower() not in ['full','integrate']:
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