diff --git a/src/FOC_reduction.py b/src/FOC_reduction.py index b91afbb..df9c5a0 100755 --- a/src/FOC_reduction.py +++ b/src/FOC_reduction.py @@ -20,17 +20,17 @@ from astropy.wcs import WCS def main(): ##### User inputs ## Input and output locations -# globals()['data_folder'] = "../data/NGC1068_x274020/" -# infiles = ['x274020at.c0f.fits','x274020bt.c0f.fits','x274020ct.c0f.fits', -# 'x274020dt.c0f.fits','x274020et.c0f.fits','x274020ft.c0f.fits', -# 'x274020gt.c0f.fits','x274020ht.c0f.fits','x274020it.c0f.fits'] -# psf_file = 'NGC1068_f253m00.fits' -# globals()['plots_folder'] = "../plots/NGC1068_x274020/" + globals()['data_folder'] = "../data/NGC1068_x274020/" + infiles = ['x274020at.c0f.fits','x274020bt.c0f.fits','x274020ct.c0f.fits', + 'x274020dt.c0f.fits','x274020et.c0f.fits','x274020ft.c0f.fits', + 'x274020gt.c0f.fits','x274020ht.c0f.fits','x274020it.c0f.fits'] + psf_file = 'NGC1068_f253m00.fits' + globals()['plots_folder'] = "../plots/NGC1068_x274020/" - globals()['data_folder'] = "../data/IC5063_x3nl030/" - infiles = ['x3nl0301r_c0f.fits','x3nl0302r_c0f.fits','x3nl0303r_c0f.fits'] - psf_file = 'IC5063_f502m00.fits' - globals()['plots_folder'] = "../plots/IC5063_x3nl030/" +# globals()['data_folder'] = "../data/IC5063_x3nl030/" +# infiles = ['x3nl0301r_c0f.fits','x3nl0302r_c0f.fits','x3nl0303r_c0f.fits'] +# psf_file = 'IC5063_f502m00.fits' +# globals()['plots_folder'] = "../plots/IC5063_x3nl030/" # globals()['data_folder'] = "../data/NGC1068_x14w010/" # infiles = ['x14w0101t_c0f.fits','x14w0102t_c0f.fits','x14w0103t_c0f.fits', @@ -113,7 +113,7 @@ def main(): display_data = False # Smoothing smoothing_function = 'combine' #gaussian_after, weighted_gaussian_after, gaussian, weighted_gaussian or combine - smoothing_FWHM = 0.20 #If None, no smoothing is done + smoothing_FWHM = 0.10 #If None, no smoothing is done smoothing_scale = 'arcsec' #pixel or arcsec # Rotation rotate_stokes = True #rotation to North convention can give erroneous results @@ -122,7 +122,7 @@ def main(): crop = False #Crop to desired ROI final_display = False # Polarization map output - figname = 'IC5063_FOC' #target/intrument name + figname = 'NGC1068_FOC' #target/intrument name figtype = '_combine_FWHM020' #additionnal informations SNRp_cut = 5. #P measurments with SNR>3 SNRi_cut = 50. #I measurments with SNR>30, which implies an uncertainty in P of 4.7%. @@ -133,55 +133,40 @@ def main(): ## Step 1: # Get data from fits files and translate to flux in erg/cm²/s/Angstrom. data_array, headers = proj_fits.get_obs_data(infiles, data_folder=data_folder, compute_flux=True) + # Crop data to remove outside blank margins. data_array, error_array, headers = proj_red.crop_array(data_array, headers, step=5, null_val=0., inside=True, display=display_crop, savename=figname, plots_folder=plots_folder) + # Deconvolve data using Richardson-Lucy iterative algorithm with a gaussian PSF of given FWHM. if deconvolve: data_array = proj_red.deconvolve_array(data_array, headers, psf=psf, FWHM=psf_FWHM, scale=psf_scale, shape=psf_shape, iterations=iterations, algo=algo) - Dxy = np.ones(2)*10 - data_mask = np.ones(data_array.shape[1:]).astype(bool) - # Align and rescale images with oversampling. - if px_scale.lower() not in ['full','integrate']: - data_array, error_array, headers, data_mask = proj_red.align_data(data_array, headers, error_array=error_array, upsample_factor=int(Dxy.min()), ref_center=align_center, return_shifts=False) - im = plt.imshow(error_array[0]/data_array[0]*100, origin='lower', vmin=0, vmax=100) - plt.colorbar(im) - wcs = WCS(headers[0]) - plt.plot(*wcs.wcs.crpix,'r+') - plt.title("Align error") - plt.show() + # Rotate data to have North up - ref_header = deepcopy(headers[0]) if rotate_data: - alpha = ref_header['orientat'] + data_mask = np.ones(data_array.shape[1:]).astype(bool) + alpha = headers[0]['orientat'] mrot = np.array([[np.cos(-alpha), -np.sin(-alpha)], [np.sin(-alpha), np.cos(-alpha)]]) - data_array, error_array, headers, data_mask = proj_red.rotate_data(data_array, error_array, data_mask, headers, -ref_header['orientat']) - im = plt.imshow(error_array[0]/data_array[0]*100, origin='lower', vmin=0, vmax=100) - plt.colorbar(im) - wcs = WCS(headers[0]) - plt.plot(*wcs.wcs.crpix,'r+') - plt.title("Rotate error") - plt.show() + data_array, error_array, headers, data_mask = proj_red.rotate_data(data_array, error_array, data_mask, headers, -alpha) + + # Align and rescale images with oversampling. + 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) + # Rebin data to desired pixel size. if rebin: + if px_scale.lower() in ['full','integrate']: + 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) 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) - # Estimate error from data background, estimated from sub-image of desired sub_shape. - 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) - im = plt.imshow(error_array[0]/data_array[0]*100, origin='lower', vmin=0, vmax=100) - plt.colorbar(im) - wcs = WCS(headers[0]) - plt.plot(*wcs.wcs.crpix,'r+') - plt.title("Background error") - plt.show() + # Estimate error from data background, estimated from sub-image of desired sub_shape. if px_scale.lower() not in ['full','integrate']: - vertex = image_hull(data_mask,step=5,null_val=0.,inside=True) - else: - vertex = np.array([0.,0.,data_array.shape[2],data_array.shape[2]]) - shape = np.array([vertex[1]-vertex[0],vertex[3]-vertex[2]]) - rectangle = [vertex[2], vertex[0], shape[1], shape[0], 0., 'g'] + 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) #Plot array for checking output - if display_data: + if display_data and px_scale.lower() not in ['full','integrate']: + vertex = image_hull(data_mask,step=5,null_val=0.,inside=True) + shape = np.array([vertex[1]-vertex[0],vertex[3]-vertex[2]]) + rectangle = [vertex[2], vertex[0], shape[1], shape[0], 0., 'g'] + proj_plots.plot_obs(data_array, headers, vmin=data_array.min(), vmax=data_array.max(), rectangle =[rectangle,]*data_array.shape[0], savename=figname+"_center_"+align_center, plots_folder=plots_folder) ## Step 2: @@ -192,29 +177,11 @@ def main(): # Bibcode : 1995chst.conf...10J I_stokes, Q_stokes, U_stokes, Stokes_cov = proj_red.compute_Stokes(data_array, error_array, data_mask, headers, FWHM=smoothing_FWHM, scale=smoothing_scale, smoothing=smoothing_function) - im = plt.imshow(np.sqrt(Stokes_cov[0,0])/I_stokes*100, origin='lower', vmin=0, vmax=100) - plt.colorbar(im) - wcs = WCS(headers[0]) - plt.plot(*wcs.wcs.crpix,'r+') - plt.title("Stokes error") - plt.show() - ## Step 3: # Rotate images to have North up - ref_header = deepcopy(headers[0]) if rotate_stokes: - alpha = ref_header['orientat'] - mrot = np.array([[np.cos(-alpha), -np.sin(-alpha)], - [np.sin(-alpha), np.cos(-alpha)]]) - rectangle[0:2] = np.dot(mrot, np.asarray(rectangle[0:2]))+np.array(data_array.shape[1:])/2 - rectangle[4] = alpha - I_stokes, Q_stokes, U_stokes, Stokes_cov, headers, data_mask = proj_red.rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers, -ref_header['orientat'], SNRi_cut=None) - im = plt.imshow(np.sqrt(Stokes_cov[0,0])/I_stokes*100, origin='lower', vmin=0, vmax=100) - plt.colorbar(im) - wcs = WCS(headers[0]) - plt.plot(*wcs.wcs.crpix,'r+') - plt.title("Rotate Stokes error") - plt.show() + alpha = headers[0]['orientat'] + I_stokes, Q_stokes, U_stokes, Stokes_cov, headers, data_mask = proj_red.rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers, -alpha, SNRi_cut=None) # Compute polarimetric parameters (polarization degree and angle). P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P = proj_red.compute_pol(I_stokes, Q_stokes, U_stokes, Stokes_cov, headers) @@ -235,15 +202,17 @@ def main(): # Plot polarization map (Background is either total Flux, Polarization degree or Polarization degree error). if px_scale.lower() not in ['full','integrate'] and final_display: - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype, plots_folder=plots_folder, display=None) - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P_flux", plots_folder=plots_folder, display='Pol_Flux') - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P", plots_folder=plots_folder, display='Pol_deg') - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_I_err", plots_folder=plots_folder, display='I_err') - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P_err", plots_folder=plots_folder, display='Pol_deg_err') - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_SNRi", plots_folder=plots_folder, display='SNRi') - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_SNRp", plots_folder=plots_folder, display='SNRp') + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype, plots_folder=plots_folder, display=None) + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P_flux", plots_folder=plots_folder, display='Pol_Flux') + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P", plots_folder=plots_folder, display='Pol_deg') + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_I_err", plots_folder=plots_folder, display='I_err') + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P_err", plots_folder=plots_folder, display='Pol_deg_err') + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_SNRi", plots_folder=plots_folder, display='SNRi') + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_SNRp", plots_folder=plots_folder, display='SNRp') elif final_display: - proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, rectangle=None, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype, plots_folder=plots_folder, display='default') + proj_plots.polarization_map(deepcopy(Stokes_test), data_mask, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype, plots_folder=plots_folder, display='default') + elif px_scale.lower() not in ['full', 'integrate']: + pol_map = proj_plots.pol_map(Stokes_test, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut) return 0 diff --git a/src/analysis.py b/src/analysis.py index 2e5c614..949d83d 100755 --- a/src/analysis.py +++ b/src/analysis.py @@ -3,8 +3,8 @@ from getopt import getopt, error as get_error from sys import argv arglist = argv[1:] -options = "hf:p:i:o:" -long_options = ["help","fits=","snrp=","snri=","output="] +options = "hf:p:i:" +long_options = ["help","fits=","snrp=","snri="] fits_path = None SNRp_cut, SNRi_cut = 3, 30 @@ -15,15 +15,13 @@ try: for curr_arg, curr_val in arg: if curr_arg in ("-h", "--help"): - print("python3 analysis.py -f -p -i -o ") + print("python3 analysis.py -f -p -i ") elif curr_arg in ("-f", "--fits"): fits_path = str(curr_val) elif curr_arg in ("-p", "--snrp"): SNRp_cut = int(curr_val) elif curr_arg in ("-i", "--snri"): SNRi_cut = int(curr_val) - elif curr_arg in ("-o", "--output"): - out_txt = str(curr_val) except get_error as err: print(str(err)) @@ -34,29 +32,5 @@ if not fits_path is None: Stokes_UV = fits.open(fits_path) p = pol_map(Stokes_UV, SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut) - if not out_txt is None: - import numpy as np - - conv = p.Stokes[0].header['photflam'] - I = p.Stokes[0].data*conv - Q = p.Stokes[1].data*conv - U = p.Stokes[2].data*conv - P = np.zeros(I.shape) - P[p.cut] = p.Stokes[5].data[p.cut] - PA = np.zeros(I.shape) - PA[p.cut] = p.Stokes[8].data[p.cut] - - shape = np.array(I.shape) - center = (shape/2).astype(int) - cdelt_arcsec = p.wcs.wcs.cdelt*3600 - xx, yy = np.indices(shape) - x, y = (xx-center[0])*cdelt_arcsec[0], (yy-center[1])*cdelt_arcsec[1] - - data_list = [] - for i in range(shape[0]): - for j in range(shape[1]): - data_list.append([x[i,j], y[i,j], I[i,j], Q[i,j], U[i,j], P[i,j], PA[i,j]]) - data = np.array(data_list) - np.savetxt(out_txt,data) else: - print("python3 analysis.py -f -p -i -o ") + print("python3 analysis.py -f -p -i ") diff --git a/src/lib/plots.py b/src/lib/plots.py index c688e7a..359c052 100755 --- a/src/lib/plots.py +++ b/src/lib/plots.py @@ -996,6 +996,8 @@ class pol_map(object): """ def __init__(self,Stokes, SNRp_cut=3., SNRi_cut=30., selection=None): + if type(Stokes) == str: + Stokes = fits.open(Stokes) self.Stokes = deepcopy(Stokes) self.SNRp_cut = SNRp_cut self.SNRi_cut = SNRi_cut