# for the plot propose: _ = transfer_to_result(data=QSO_img, pix_sz=pix_scale, source_result=source_result, ps_result=ps_result, image_ps=image_ps, image_host=image_host, error_map=error_map, zp=zp_list[k], fixcenter=fixcenter, ID=image_ID + band_seq[k], QSO_msk=None, tag=tag, plot_compare=plot_compare) # result = transfer_obj_to_result(source_result[0], image_host[0], zp) result['redu_Chisq'] = reduced_chisq fitsFile = pyfits.open(image_folder + filename_list[k]) file_header = copy.deepcopy(fitsFile[1].header) file_header['CRPIX1'] = file_header['CRPIX1'] - qso_center_list[k][ 0] + len(QSO_img) / 2 file_header['CRPIX2'] = file_header['CRPIX2'] - qso_center_list[k][ 1] + len(QSO_img) / 2 fit_result.write("#QSO_img intensity in the band {1}: {0} \n".format( round(np.sum(QSO_img), 2), band_seq[k])) fit_result.write("#fit result of the QSO by in band {0}: \n".format( band_seq[k])) objs_img = np.zeros_like(image_host[0]) if len(source_result) > 1: for i in range(1, len(image_host)): objs_img += image_host[i]
]) thdu_fluxlist.writeto('./zoutput/' + ID + '_flux_list_sersicdiskbar.fits', overwrite=True) filename = './zoutput/{0}_fit_result.txt'.format(name_save) if_file = glob.glob(filename) if if_file == []: fit_result = open(filename, 'w') elif if_file is not []: fit_result = open(filename, "r+") fit_result.read() fit_result.write("Result for target " + ID + ":\n") ps_result_0 = ps_result[0] ps_result_0['PSF_mag'] = -2.5 * np.log10(ps_result_0['point_amp']) + zp fit_result.write("point source result:\n") fit_result.write(" " + repr(ps_result) + "\n") for i in range(len(source_result)): fit_result.write("obj {0} result:\n".format(i)) result = transfer_obj_to_result(source_result=source_result[i], image_host=image_host[i], zp=zp) fit_result.write(" " + repr(result) + "\n") fit_result.write('======================\n') fit_result.close() print("Total Magnitude Result:") print("AGN magnitude:", -2.5 * np.log10(image_ps[0].sum()) + zp) print("Bulge magnitude:", -2.5 * np.log10(image_host[0].sum()) + zp) print("Disk magnitude:", -2.5 * np.log10(image_host[1].sum()) + zp) print("Bar magnitude:", -2.5 * np.log10(image_host[2].sum()) + zp)