# 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)