data_process = DataProcess(fov_image=data,
target_pos=[1170., 940.],
pos_type='pixel',
header=header,
rm_bkglight=False,
exptime=np.ones_like(data) * exptime,
if_plot=False,
zp=zp) #Gain value assuming as 1
data_process.generate_target_materials(radius=65,
create_mask=False,
nsigma=2.8,
if_select_obj=False,
exp_sz=1.2,
npixels=15,
if_plot=True)
data_process.find_PSF(radius=30, user_option=True)
data_process.plot_overview(label='Example', target_label=None)
#Start to produce the class and params for lens fitting.
from galight.fitting_specify import FittingSpecify
# data_process.apertures = []
fit_sepc = FittingSpecify(data_process)
fit_sepc.prepare_fitting_seq(point_source_num=1) #, fix_n_list= [[0,4],[1,1]])
fit_sepc.build_fitting_seq()
#Plot the initial settings for fittings.
fit_sepc.plot_fitting_sets()
#Setting the fitting method and run.
from galight.fitting_process import FittingProcess
# print(ID, idx)
RA, Dec = ra_dec_info[idx].split(' ')[:2]
RA, Dec = np.float(RA), np.float(Dec)
if ID == 'J2100-1715':
RA = 315.2279713
Dec = -17.25608967
fov_image = fitsFile[1].data # check the back grounp
data_process = DataProcess(fov_image = fov_image, target_pos = [RA, Dec], pos_type = 'wcs', header = header,
rm_bkglight = True, exptime = exp_map, if_plot=False, zp = 25.9463) #!!! zp use F160W for now
data_process.generate_target_materials(radius=20, cut_kernel = 'center_bright', create_mask = False,
# detect_tool = 'sep', if_select_obj= True, nsigma=2.5, thresh = 2.5, exp_sz= 1.2, npixels = 15,
if_plot=False)
#Lines used to find PSF and set the PSF_loc_dic.
data_process.find_PSF(radius = 30, user_option = True, if_filter=True, psf_edge =30)
# data_process.profiles_compare(norm_pix = 5, if_annuli=False, y_log = False,
# prf_name_list = (['target'] + ['PSF{0}'.format(i) for i in range(len(data_process.PSF_list))]) )
# PSF_loc = PSF_loc_dic[str(i)]
data_process.plot_overview(label = ID, target_label = None)
# data_process.find_PSF(radius = 30, PSF_pos_list = [PSF_loc])
data_process.checkout()
#Start to produce the class and params for lens fitting.
# data_process.apertures = []
print(ID, i)
fit_sepc = FittingSpecify(data_process)
fit_sepc.prepare_fitting_seq(point_source_num = 1) #, fix_n_list= [[0,4],[1,1]])
# psf_error_map = np.ones_like(data_process.PSF_list[data_process.psf_id_for_fitting]) *0.01 # It is in the variance unit (std^2).
# fit_sepc.prepare_fitting_seq(point_source_num = 1, psf_error_map = psf_error_map)
fit_sepc.build_fitting_seq()
#Plot the initial settings for fittings.
exptime = header0['TEXPTIME'] #The assumed exp time.
plt_fits(data_sb)
# Obtain PSF stars:
# zp = 31.4 - 2.5*np.log10(header['PHOTMJSR']) #Calculate the correspondingly zp as DN/S #This is wrong! See 3_...
data_process_ = DataProcess(fov_image=data_sb,
target_pos=[1170., 940.],
pos_type='pixel',
header=header,
rm_bkglight=True,
exptime=np.ones_like(data_sb) * exptime,
if_plot=False,
zp=zp) #Gain value assuming as 1
# data_process_.generate_target_materials(radius=65, create_mask = False, nsigma=2.8, if_select_obj=False,
# exp_sz= 1.2, npixels = 15, if_plot=True)
data_process_.find_PSF(radius=60,
user_option=True,
psf_edge=150,
select_all=True)
# data_process_.plot_overview(label = 'Example', target_label = None)
FWHM_list = np.array(data_process_.PSF_FWHM_list)
POS_list = np.array(data_process_.PSF_pos_list)
psf_list = np.array(data_process_.PSF_list)
fwhm_bools = [FWHM_list < 4.3][0]
psf_list = psf_list[fwhm_bools]
POS_list = POS_list[fwhm_bools]
FWHM_list = FWHM_list[fwhm_bools]
near_bools = []
for i in range(len(psf_list)):
try:
_, segm_map = detect_obj(psf_list[i],
if_plot=False,
segm_map=True,
from galight.tools.astro_tools import plt_fits
plt_fits(data_sb)
#%%Obtain PSF stars:
from galight.data_process import DataProcess
# zp = 31.4 - 2.5*np.log10(header['PHOTMJSR']) #Calculate the correspondingly zp as DN/S #This is wrong! See 3_...
data_process_ = DataProcess(fov_image=data_sb,
target_pos=[1170., 940.],
pos_type='pixel',
header=header,
rm_bkglight=True,
exptime=np.ones_like(data_sb) * exptime,
if_plot=False,
zp=zp) #Gain value assuming as 1
# data_process_.generate_target_materials(radius=65, create_mask = False, nsigma=2.8, if_select_obj=False,
# exp_sz= 1.2, npixels = 15, if_plot=True)
data_process_.find_PSF(radius=60, user_option=True, psf_edge=10)
data_process_.plot_overview(label='Example', target_label=None)
#%%
psf_ids = [3, 8] #use 5 to do mock and use 10 to do fitting.
# psf_ids = [5,9] #use 5 to do mock and use 10 to do fitting.
psf_list = [
data_process_.PSF_list[i] / np.sum(data_process_.PSF_list[i])
for i in psf_ids
]
# from galight.tools.cutout_tools import psf_clean
# psf_list[0] = psf_clean(psf_list[0], if_plot=True)
# plt_fits(psf)
#%%
# data_process_.find_PSF(radius = 60, PSF_pos_list = [[341., 444.], [1925., 1127.]])
#Load the PSF data:
# PSF_files = glob.glob('psf*{0}*.fits'.format(HSCband))
# PSF = pyfits.getdata(PSF_files[0])
data_process = DataProcess(fov_image=fov_image,
fov_noise_map=err_data,
target_pos=[QSO_RA, QSO_DEC],
pos_type='wcs',
header=header,
rm_bkglight=True,
if_plot=False,
zp=zp)
PSF_loc = [35.29689501, -4.685896878]
data_process.find_PSF(
radius=20,
PSF_pos_list=[PSF_loc],
pos_type='wcs',
)
#Generate the fitting materials
data_process.generate_target_materials(radius=30,
create_mask=False,
nsigma=2.8,
exp_sz=1.5,
npixels=40,
if_plot=False)
plt_fits(data_process.PSF_list[0])
# data_process.apertures = [] #Assuming there is no host (i.e., as constant.) #!!!
# Manually input the PSF: