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Commit edd720e6 authored by Fang Yuedong's avatar Fang Yuedong
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Merge branch 'develop'

parents 959f0ebc 8df06b27
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Inline Side-by-side
ObservationSim/Instrument/data/throughputs/z_throughput.txt
View file @ edd720e6
# z_cssc # z_cssc
# lambda_Angst throughput # lambda_Angst throughput
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10930.00 0.00042 10930.00 0.00006
10940.00 0.00032 10940.00 0.00004
10950.00 0.00024 10950.00 0.00002
10960.00 0.00017 10960.00 0.00001
10970.00 0.00011 10970.00 0.00001
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10990.00 0.00003 10990.00 0.00000
11000.00 0.00000 11000.00 0.00000
ObservationSim/MockObject/CatalogBase.py
View file @ edd720e6
...@@ -56,6 +56,8 @@ class CatalogBase(metaclass=ABCMeta): ...@@ -56,6 +56,8 @@ class CatalogBase(metaclass=ABCMeta):
"teff":0., "teff":0.,
"logg":0., "logg":0.,
"feh":0., "feh":0.,
"DM":0.,
"stellarMass":1.,
# C6 galaxies parameters # C6 galaxies parameters
"e1":0., "e1":0.,
"e2":0., "e2":0.,
......
ObservationSim/MockObject/FlatLED.py 0 → 100755
View file @ edd720e6
import galsim
import os, sys
import numpy as np
import time
import math
import astropy.constants as cons
from astropy.io import fits
from scipy.interpolate import griddata
from astropy.table import Table
from ObservationSim.MockObject.SpecDisperser import SpecDisperser
from scipy import interpolate
import gc
from ObservationSim.MockObject.MockObject import MockObject
# from ObservationSim.Straylight import calculateSkyMap_split_g
try:
import importlib.resources as pkg_resources
except ImportError:
# Try backported to PY<37 'importlib_resources'
import importlib_resources as pkg_resources
# flatDir = '/Volumes/EAGET/LED_FLAT/'
LED_name = ['LED1', 'LED2', 'LED3', 'LED4', 'LED5', 'LED6', 'LED7', 'LED8', 'LED9', 'LED10', 'LED11', 'LED12', 'LED13',
'LED14']
cwaves_name = {'LED1': '275', 'LED2': '310', 'LED3': '430', 'LED4': '505', 'LED5': '545', 'LED6': '590', 'LED7': '670',
'LED8': '760', 'LED9': '940', 'LED10': '940', 'LED11': '1050', 'LED12': '1050',
'LED13': '340', 'LED14': '365'}
cwaves = {'LED1': 2750, 'LED2': 3100, 'LED3': 4300, 'LED4': 5050, 'LED5': 5250, 'LED6': 5900, 'LED7': 6700,
'LED8': 7600, 'LED9': 8800, 'LED10': 9400, 'LED11': 10500, 'LED12': 15500, 'LED13': 3400, 'LED14': 3650}
cwaves_fwhm = {'LED1': 110, 'LED2': 120, 'LED3': 200, 'LED4': 300, 'LED5': 300, 'LED6': 130, 'LED7': 210,
'LED8': 260, 'LED9': 400, 'LED10': 370, 'LED11': 500, 'LED12': 1400, 'LED13': 90, 'LED14': 100}
# LED_QE = {'LED1': 0.3, 'LED2': 0.4, 'LED13': 0.5, 'LED14': 0.5, 'LED10': 0.4}
# e-/ms
# fluxLED = {'LED1': 0.16478729, 'LED2': 0.084220931, 'LED3': 2.263360617, 'LED4': 2.190623489, 'LED5': 0.703504768,
# 'LED6': 0.446117963, 'LED7': 0.647122098, 'LED8': 0.922313442,
# 'LED9': 0.987278143, 'LED10': 2.043989167, 'LED11': 0.612571429, 'LED12': 1.228915663, 'LED13': 0.17029384,
# 'LED14': 0.27842925}
# e-/ms
fluxLED = {'LED1': 15, 'LED2': 15, 'LED3': 12.5, 'LED4': 9, 'LED5': 9,
'LED6': 9, 'LED7': 9, 'LED8': 9, 'LED9': 9, 'LED10': 12.5, 'LED11': 15, 'LED12':15, 'LED13': 12.5,
'LED14': 12.5}
# fluxLEDL = {'LED1': 10, 'LED2': 10, 'LED3': 10, 'LED4': 10, 'LED5': 10,
# 'LED6': 10, 'LED7': 10, 'LED8': 10, 'LED9': 10, 'LED10': 10, 'LED11': 10, 'LED12':10, 'LED13': 10,
# 'LED14': 10}
mirro_eff = {'GU':0.61, 'GV':0.8, 'GI':0.8}
# mirro_eff = {'GU':1, 'GV':1, 'GI':1}
class FlatLED(object):
def __init__(self, chip,filt, flatDir = None, logger=None):
# self.led_type_list = led_type_list
self.filt = filt
self.chip = chip
self.logger = logger
if flatDir is not None:
self.flatDir = flatDir
else:
try:
with pkg_resources.files('ObservationSim.MockObject.data.led').joinpath("") as ledDir:
self.flatDir = ledDir.as_posix()
except AttributeError:
with pkg_resources.path('ObservationSim.MockObject.data.led', "") as ledDir:
self.flatDir = ledDir.as_posix()
###
### return LED flat, e/s
###
def getLEDImage(self, led_type='LED1'):
# cwave = cwaves[led_type]
flat = fits.open(os.path.join(self.flatDir, 'model_' + cwaves_name[led_type] + 'nm.fits'))
xlen = flat[0].header['NAXIS1']
ylen = 601
x = np.linspace(0, self.chip.npix_x * 6, xlen)
y = np.linspace(0, self.chip.npix_y * 5, ylen)
xx, yy = np.meshgrid(x, y)
a1 = flat[0].data[0:ylen, 0:xlen]
# z = np.sin((xx+yy+xx**2+yy**2))
# fInterp = interp2d(xx, yy, z, kind='linear')
X_ = np.hstack((xx.flatten()[:, None], yy.flatten()[:, None]))
Z_ = a1.flatten()
n_x = np.arange(0, self.chip.npix_x * 6, 1)
n_y = np.arange(0, self.chip.npix_y * 5, 1)
M, N = np.meshgrid(n_x, n_y)
i = self.chip.rowID - 1
j = self.chip.colID - 1
U = griddata(X_, Z_, (
M[self.chip.npix_y * i:self.chip.npix_y * (i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)],
N[self.chip.npix_y * i:self.chip.npix_y * (i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)]),
method='linear')
U = U/np.mean(U)
flatImage = U*fluxLED[led_type]*1000
gc.collect()
return flatImage
###
### return LED flat, e/s
###
def getLEDImage1(self, led_type='LED1'):
# cwave = cwaves[led_type]
flat = fits.open(os.path.join(self.flatDir, 'model_' + cwaves_name[led_type] + 'nm.fits'))
xlen = flat[0].header['NAXIS1']
ylen = 601
i = self.chip.rowID - 1
j = self.chip.colID - 1
x = np.linspace(0, self.chip.npix_x, int(xlen/6.))
y = np.linspace(0, self.chip.npix_y, int(ylen/5.))
xx, yy = np.meshgrid(x, y)
a1 = flat[0].data[int(ylen*i/5.):int(ylen*i/5.)+int(ylen/5.), int(xlen*j/6.):int(xlen*j/6.)+int(xlen/6.)]
# z = np.sin((xx+yy+xx**2+yy**2))
# fInterp = interp2d(xx, yy, z, kind='linear')
X_ = np.hstack((xx.flatten()[:, None], yy.flatten()[:, None]))
Z_ = a1.flatten()
n_x = np.arange(0, self.chip.npix_x , 1)
n_y = np.arange(0, self.chip.npix_y, 1)
M, N = np.meshgrid(n_x, n_y)
U = griddata(X_, Z_, (
M[0:self.chip.npix_y, 0:self.chip.npix_x],
N[0:self.chip.npix_y, 0:self.chip.npix_x ]),
method='linear')
U = U/np.mean(U)
flatImage = U*fluxLED[led_type]*1000
gc.collect()
return flatImage
def drawObj_LEDFlat_img(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if len(led_type_list) > len(exp_t_list):
return np.ones([self.chip.npix_y,self.chip.npix_x])
ledFlat = np.zeros([self.chip.npix_y,self.chip.npix_x])
ledStat = '00000000000000'
ledTimes = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
nledStat = '2'
for i in np.arange(len(led_type_list)):
led_type = led_type_list[i]
exp_t = exp_t_list[i]
# unitFlatImg = self.getLEDImage(led_type=led_type)
unitFlatImg = self.getLEDImage1(led_type=led_type)
# print("---------------TEST mem:",np.mean(unitFlatImg))
led_wave = cwaves[led_type]
led_fwhm = cwaves_fwhm[led_type]
led_spec = self.gaussian1d_profile_led(led_wave, led_fwhm)
speci = interpolate.interp1d(led_spec['WAVELENGTH'], led_spec['FLUX'])
w_list = np.arange(self.filt.blue_limit, self.filt.red_limit, 0.5) #A
f_spec = speci(w_list)
ccd_bp = self.chip._getChipEffCurve(self.chip.filter_type)
ccd_eff = ccd_bp.__call__(w_list / 10.)
filt_bp = self.filt.filter_bandpass
fil_eff = filt_bp.__call__(w_list / 10.)
t_spec = np.trapz(f_spec*ccd_eff*fil_eff, w_list)
# print(i, np.mean(unitFlatImg), t_spec, exp_t)
unitFlatImg = unitFlatImg * t_spec
# print("DEBUG1:---------------",np.mean(unitFlatImg))
ledFlat = ledFlat+unitFlatImg*exp_t
ledStat = ledStat[0:int(led_type[3:])-1]+nledStat+ledStat[int(led_type[3:]):]
ledTimes[int(led_type[3:])-1] = exp_t * 1000
gc.collect()
return ledFlat, ledStat, ledTimes
def drawObj_LEDFlat_slitless(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if len(led_type_list) != len(exp_t_list):
return np.ones([self.chip.npix_y,self.chip.npix_x])
ledFlat = np.zeros([self.chip.npix_y,self.chip.npix_x])
ledStat = '00000000000000'
ledTimes = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
nledStat = '2'
for i in np.arange(len(led_type_list)):
led_type = led_type_list[i]
exp_t = exp_t_list[i]
# unitFlatImg = self.getLEDImage(led_type=led_type)
unitFlatImg = self.getLEDImage1(led_type=led_type)
# print("---------------TEST mem:",np.mean(unitFlatImg))
ledFlat_ = unitFlatImg*exp_t
ledFlat_ = ledFlat_ / mirro_eff[self.filt.filter_type]
ledFlat_.astype(np.float32)
led_wave = cwaves[led_type]
led_fwhm = cwaves_fwhm[led_type]
led_spec = self.gaussian1d_profile_led(led_wave, led_fwhm)
# print("DEBUG1:---------------",np.mean(ledFlat_))
ledspec_map = self.calculateLEDSpec(
skyMap=ledFlat_,
blueLimit=self.filt.blue_limit,
redLimit=self.filt.red_limit,
conf=self.chip.sls_conf,
pixelSize=self.chip.pix_scale,
isAlongY=0,
flat_cube=self.chip.flat_cube, led_spec=led_spec)
ledFlat = ledFlat + ledspec_map
ledStat = ledStat[0:int(led_type[3:])-1]+nledStat+ledStat[int(led_type[3:]):]
ledTimes[int(led_type[3:])-1] = exp_t * 1000
return ledFlat, ledStat, ledTimes
def drawObj_LEDFlat(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if self.chip.survey_type == "photometric":
return self.drawObj_LEDFlat_img(led_type_list=led_type_list, exp_t_list=exp_t_list)
elif self.chip.survey_type == "spectroscopic":
return self.drawObj_LEDFlat_slitless(led_type_list=led_type_list, exp_t_list=exp_t_list)
def gaussian1d_profile_led(self, xc=5050, fwhm=300):
sigma = fwhm/2.355
x_radii = int(5*sigma + 1)
xlist = np.arange(xc-x_radii, xc+x_radii, 0.5)
xlist_ = np.zeros(len(xlist) + 2)
xlist_[1:-1] = xlist
xlist_[0] = 2000
xlist_[-1] = 18000
ids1 = xlist>xc-fwhm
ids2 = xlist[ids1]<xc+fwhm
data = np.exp((-(xlist-xc)*(xlist-xc))/(2*sigma*sigma))/(np.sqrt(2*math.pi)*sigma)
scale = 1/np.trapz(data[ids1][ids2], xlist[ids1][ids2])
data_ = np.zeros(len(xlist) + 2)
data_[1:-1] = data*scale
# print("DEBUG:-------------------------------",np.sum(data_), scale)
return Table(np.array([xlist_.astype(np.float32), data_.astype(np.float32)]).T, names=('WAVELENGTH', 'FLUX'))
def calculateLEDSpec(self, skyMap=None, blueLimit=4200, redLimit=6500,
conf=[''], pixelSize=0.074, isAlongY=0,
split_pos=3685, flat_cube=None, led_spec=None):
conf1 = conf[0]
conf2 = conf[0]
if np.size(conf) == 2:
conf2 = conf[1]
skyImg = galsim.Image(skyMap, xmin=0, ymin=0)
tbstart = blueLimit
tbend = redLimit
fimg = np.zeros_like(skyMap)
fImg = galsim.Image(fimg)
spec = led_spec
if isAlongY == 0:
directParm = 0
if isAlongY == 1:
directParm = 1
if split_pos >= skyImg.array.shape[directParm]:
skyImg1 = galsim.Image(skyImg.array)
origin1 = [0, 0]
# sdp = specDisperser.specDisperser(orig_img=skyImg1, xcenter=skyImg1.center.x, ycenter=skyImg1.center.y,
# full_img=fimg, tar_spec=spec, band_start=tbstart, band_end=tbend,
# origin=origin1,
# conf=conf1)
# sdp.compute_spec_orders()
y_len = skyMap.shape[0]
x_len = skyMap.shape[1]
delt_x = 100
delt_y = 100
sub_y_start_arr = np.arange(0, y_len, delt_y)
sub_y_end_arr = sub_y_start_arr + delt_y
sub_y_end_arr[-1] = min(sub_y_end_arr[-1], y_len)
sub_x_start_arr = np.arange(0, x_len, delt_x)
sub_x_end_arr = sub_x_start_arr + delt_x
sub_x_end_arr[-1] = min(sub_x_end_arr[-1], x_len)
for i, k1 in enumerate(sub_y_start_arr):
sub_y_s = k1
sub_y_e = sub_y_end_arr[i]
sub_y_center = (sub_y_s + sub_y_e) / 2.
for j, k2 in enumerate(sub_x_start_arr):
sub_x_s = k2
sub_x_e = sub_x_end_arr[j]
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2.
sdp = SpecDisperser(orig_img=skyImg_sub, xcenter=sub_x_center, ycenter=sub_y_center,
origin=origin_sub,
tar_spec=spec,
band_start=tbstart, band_end=tbend,
conf=conf2,
flat_cube=flat_cube)
spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items():
img_s = v[0]
origin_order_x = v[1]
origin_order_y = v[2]
ssImg = galsim.ImageF(img_s)
ssImg.setOrigin(origin_order_x, origin_order_y)
bounds = ssImg.bounds & fImg.bounds
if bounds.area() == 0:
continue
fImg[bounds] = fImg[bounds] + ssImg[bounds]
else:
# sdp.compute_spec_orders()
y_len = skyMap.shape[0]
x_len = skyMap.shape[1]
delt_x = 500
delt_y = y_len
sub_y_start_arr = np.arange(0, y_len, delt_y)
sub_y_end_arr = sub_y_start_arr + delt_y
sub_y_end_arr[-1] = min(sub_y_end_arr[-1], y_len)
delt_x = split_pos - 0
sub_x_start_arr = np.arange(0, split_pos, delt_x)
sub_x_end_arr = sub_x_start_arr + delt_x
sub_x_end_arr[-1] = min(sub_x_end_arr[-1], split_pos)
for i, k1 in enumerate(sub_y_start_arr):
sub_y_s = k1
sub_y_e = sub_y_end_arr[i]
sub_y_center = (sub_y_s + sub_y_e) / 2.
for j, k2 in enumerate(sub_x_start_arr):
sub_x_s = k2
sub_x_e = sub_x_end_arr[j]
# print(i,j,sub_y_s, sub_y_e,sub_x_s,sub_x_e)
T1 = time.time()
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2.
sdp = SpecDisperser(orig_img=skyImg_sub, xcenter=sub_x_center, ycenter=sub_y_center,
origin=origin_sub,
tar_spec=spec,
band_start=tbstart, band_end=tbend,
conf=conf1,
flat_cube=flat_cube)
spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items():
img_s = v[0]
origin_order_x = v[1]
origin_order_y = v[2]
ssImg = galsim.ImageF(img_s)
ssImg.setOrigin(origin_order_x, origin_order_y)
bounds = ssImg.bounds & fImg.bounds
if bounds.area() == 0:
continue
fImg[bounds] = fImg[bounds] + ssImg[bounds]
T2 = time.time()
print('time: %s ms' % ((T2 - T1) * 1000))
delt_x = x_len - split_pos
sub_x_start_arr = np.arange(split_pos, x_len, delt_x)
sub_x_end_arr = sub_x_start_arr + delt_x
sub_x_end_arr[-1] = min(sub_x_end_arr[-1], x_len)
for i, k1 in enumerate(sub_y_start_arr):
sub_y_s = k1
sub_y_e = sub_y_end_arr[i]
sub_y_center = (sub_y_s + sub_y_e) / 2.
for j, k2 in enumerate(sub_x_start_arr):
sub_x_s = k2
sub_x_e = sub_x_end_arr[j]
# print(i,j,sub_y_s, sub_y_e,sub_x_s,sub_x_e)
T1 = time.time()
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2.
sdp = SpecDisperser(orig_img=skyImg_sub, xcenter=sub_x_center, ycenter=sub_y_center,
origin=origin_sub,
tar_spec=spec,
band_start=tbstart, band_end=tbend,
conf=conf2,
flat_cube=flat_cube)
spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items():
img_s = v[0]
origin_order_x = v[1]
origin_order_y = v[2]
ssImg = galsim.ImageF(img_s)
ssImg.setOrigin(origin_order_x, origin_order_y)
bounds = ssImg.bounds & fImg.bounds
if bounds.area() == 0:
continue
fImg[bounds] = fImg[bounds] + ssImg[bounds]
T2 = time.time()
print('time: %s ms' % ((T2 - T1) * 1000))
if isAlongY == 1:
fimg, tmx, tmy = rotate90(array_orig=fImg.array, xc=0, yc=0, isClockwise=0)
else:
fimg = fImg.array
# fimg = fimg * pixelSize * pixelSize
return fimg
ObservationSim/MockObject/Galaxy.py
View file @ edd720e6
import numpy as np import numpy as np
import galsim import galsim
import os, sys
import astropy.constants as cons
from astropy.table import Table from astropy.table import Table
from scipy import interpolate
from ObservationSim.MockObject._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, getABMAG,convolveGaussXorders from ObservationSim.MockObject._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG
from ObservationSim.MockObject.SpecDisperser import SpecDisperser from ObservationSim.MockObject.SpecDisperser import SpecDisperser
from ObservationSim.MockObject.MockObject import MockObject from ObservationSim.MockObject.MockObject import MockObject
...@@ -14,18 +11,6 @@ from ObservationSim.MockObject.MockObject import MockObject ...@@ -14,18 +11,6 @@ from ObservationSim.MockObject.MockObject import MockObject
class Galaxy(MockObject): class Galaxy(MockObject):
def __init__(self, param, logger=None): def __init__(self, param, logger=None):
super().__init__(param, logger=logger) super().__init__(param, logger=logger)
# self.thetaR = self.param["theta"]
# self.bfrac = self.param["bfrac"]
# self.hlr_disk = self.param["hlr_disk"]
# self.hlr_bulge = self.param["hlr_bulge"]
# Extract ellipticity components
# self.e_disk = galsim.Shear(g=self.param["ell_disk"], beta=self.thetaR*galsim.degrees)
# self.e_bulge = galsim.Shear(g=self.param["ell_bulge"], beta=self.thetaR*galsim.degrees)
# self.e_total = galsim.Shear(g=self.param["ell_tot"], beta=self.thetaR*galsim.degrees)
# self.e1_disk, self.e2_disk = self.e_disk.g1, self.e_disk.g2
# self.e1_bulge, self.e2_bulge = self.e_bulge.g1, self.e_bulge.g2
# self.e1_total, self.e2_total = self.e_total.g1, self.e_total.g2
if not hasattr(self, "disk_sersic_idx"): if not hasattr(self, "disk_sersic_idx"):
self.disk_sersic_idx = 1. self.disk_sersic_idx = 1.
...@@ -76,7 +61,12 @@ class Galaxy(MockObject): ...@@ -76,7 +61,12 @@ class Galaxy(MockObject):
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge) bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape) bulge = bulge.shear(bulge_shape)
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk if self.bfrac == 0:
gal = disk
elif self.bfrac == 1:
gal = bulge
else:
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
gal = gal.withFlux(nphotons) gal = gal.withFlux(nphotons)
if fd_shear is not None: if fd_shear is not None:
g1 += fd_shear.g1 g1 += fd_shear.g1
...@@ -101,10 +91,6 @@ class Galaxy(MockObject): ...@@ -101,10 +91,6 @@ class Galaxy(MockObject):
if self.logger: if self.logger:
self.logger.error(e) self.logger.error(e)
return 2, None return 2, None
nphotons_sum = 0
photons_list = []
xmax, ymax = 0, 0
# # [C6 TEST] # # [C6 TEST]
# print('hlr_disk = %.4f, hlr_bulge = %.4f'%(self.hlr_disk, self.hlr_bulge)) # print('hlr_disk = %.4f, hlr_bulge = %.4f'%(self.hlr_disk, self.hlr_bulge))
...@@ -114,7 +100,7 @@ class Galaxy(MockObject): ...@@ -114,7 +100,7 @@ class Galaxy(MockObject):
if self.hlr_disk > 3.0 or self.hlr_bulge > 3.0: # Very big galaxy if self.hlr_disk > 3.0 or self.hlr_bulge > 3.0: # Very big galaxy
big_galaxy = True big_galaxy = True
# (TEST) Galsim Parameters # Set Galsim Parameters
if self.getMagFilter(filt) <= 15 and (not big_galaxy): if self.getMagFilter(filt) <= 15 and (not big_galaxy):
folding_threshold = 5.e-4 folding_threshold = 5.e-4
else: else:
...@@ -122,7 +108,7 @@ class Galaxy(MockObject): ...@@ -122,7 +108,7 @@ class Galaxy(MockObject):
gsp = galsim.GSParams(folding_threshold=folding_threshold) gsp = galsim.GSParams(folding_threshold=folding_threshold)
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y, self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.real_wcs) img_real_wcs=self.chip_wcs)
x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5 x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5
x_nominal = int(np.floor(x + 0.5)) x_nominal = int(np.floor(x + 0.5))
...@@ -130,9 +116,11 @@ class Galaxy(MockObject): ...@@ -130,9 +116,11 @@ class Galaxy(MockObject):
dx = x - x_nominal dx = x - x_nominal
dy = y - y_nominal dy = y - y_nominal
offset = galsim.PositionD(dx, dy) offset = galsim.PositionD(dx, dy)
# Get real local wcs of object (deal with chip rotation w.r.t its center)
chip_wcs_local = self.chip_wcs.local(self.real_pos)
is_updated = 0
real_wcs_local = self.real_wcs.local(self.real_pos) # Model the galaxy as disk + bulge
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp) disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk) disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape) disk = disk.shear(disk_shape)
...@@ -140,38 +128,42 @@ class Galaxy(MockObject): ...@@ -140,38 +128,42 @@ class Galaxy(MockObject):
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge) bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape) bulge = bulge.shear(bulge_shape)
# Get shear and deal with shear induced by field distortion
if fd_shear: if fd_shear:
g1 += fd_shear.g1 g1 += fd_shear.g1
g2 += fd_shear.g2 g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2) gal_shear = galsim.Shear(g1=g1, g2=g2)
# Loop over all sub-bandpasses
for i in range(len(bandpass_list)): for i in range(len(bandpass_list)):
bandpass = bandpass_list[i] bandpass = bandpass_list[i]
try: try:
sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass) sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
except Exception as e: except Exception as e:
print(e) print(e)
if self.logger: if self.logger:
self.logger.error(e) self.logger.error(e)
# return False
continue continue
ratio = sub/full ratio = sub/full
if not (ratio == -1 or (ratio != ratio)): if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot nphotons = ratio * nphotons_tot
else: else:
continue continue
nphotons_sum += nphotons
# nphotons_sum += nphotons
# # [C6 TEST] # # [C6 TEST]
# print("nphotons_sub-band_%d = %.2f"%(i, nphotons)) # print("nphotons_sub-band_%d = %.2f"%(i, nphotons))
# Get PSF model
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold) psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
gal_temp = self.bfrac * bulge + (1.0 - self.bfrac) * disk if self.bfrac == 0:
gal_temp = disk
elif self.bfrac == 1:
gal_temp = bulge
else:
gal_temp = self.bfrac * bulge + (1.0 - self.bfrac) * disk
gal_temp = gal_temp.shear(gal_shear) gal_temp = gal_temp.shear(gal_shear)
gal_temp = gal_temp.withFlux(nphotons) gal_temp = gal_temp.withFlux(nphotons)
if not big_galaxy: # Not apply PSF for very big galaxy if not big_galaxy: # Not apply PSF for very big galaxy
gal_temp = galsim.Convolve(psf, gal_temp) gal_temp = galsim.Convolve(psf, gal_temp)
...@@ -186,47 +178,21 @@ class Galaxy(MockObject): ...@@ -186,47 +178,21 @@ class Galaxy(MockObject):
# kfrac = np.random.random()*(1.0 - self.bfrac) # kfrac = np.random.random()*(1.0 - self.bfrac)
# gal = self.bfrac * bulge + (1.0 - self.bfrac - kfrac) * disk + kfrac * knots # gal = self.bfrac * bulge + (1.0 - self.bfrac - kfrac) * disk + kfrac * knots
# # [C6 TEST] # stamp = gal.drawImage(wcs=chip_wcs_local, method='phot', offset=offset, save_photons=True)
# print('xmax = %d, ymax = %d '%(xmax, ymax)) stamp = gal.drawImage(wcs=chip_wcs_local, offset=offset)
# # Output memory usage if np.sum(np.isnan(stamp.array)) > 0:
# snapshot = tracemalloc.take_snapshot() # ERROR happens
# top_stats = snapshot.statistics('lineno') return 2, pos_shear
# for stat in top_stats[:10]:
# print(stat)
stamp = gal.drawImage(wcs=real_wcs_local, method='phot', offset=offset, save_photons=True)
photons = stamp.photons
photons.x += x_nominal
photons.y += y_nominal
photons_list.append(photons)
stamp.wcs = real_wcs_local
stamp.setCenter(x_nominal, y_nominal) stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1) bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() > 0: if bounds.area() > 0:
chip.img.setOrigin(0, 0) chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds] chip.img[bounds] += stamp[bounds]
is_updated = 1
if not big_galaxy:
for i in range(len(photons_list)):
if i == 0:
chip.sensor.accumulate(photons_list[i], stamp)
else:
chip.sensor.accumulate(photons_list[i], stamp, resume=True)
else:
sensor = galsim.Sensor()
for i in range(len(photons_list)):
if i == 0:
sensor.accumulate(photons_list[i], stamp)
else:
sensor.accumulate(photons_list[i], stamp, resume=True)
del sensor
chip.img[bounds] = stamp[bounds]
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin) chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
else: del stamp
if is_updated == 0:
# Return code 0: object photons missed this detector # Return code 0: object photons missed this detector
print("obj %s missed"%(self.id)) print("obj %s missed"%(self.id))
if self.logger: if self.logger:
...@@ -235,8 +201,6 @@ class Galaxy(MockObject): ...@@ -235,8 +201,6 @@ class Galaxy(MockObject):
# # [C6 TEST] # # [C6 TEST]
# print("nphotons_sum = ", nphotons_sum) # print("nphotons_sum = ", nphotons_sum)
del photons_list
del stamp
return 1, pos_shear return 1, pos_shear
def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0, def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
...@@ -255,7 +219,7 @@ class Galaxy(MockObject): ...@@ -255,7 +219,7 @@ class Galaxy(MockObject):
names=('WAVELENGTH', 'FLUX')) names=('WAVELENGTH', 'FLUX'))
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y, self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.real_wcs) img_real_wcs=self.chip_wcs)
x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5 x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5
x_nominal = int(np.floor(x + 0.5)) x_nominal = int(np.floor(x + 0.5))
...@@ -264,7 +228,7 @@ class Galaxy(MockObject): ...@@ -264,7 +228,7 @@ class Galaxy(MockObject):
dy = y - y_nominal dy = y - y_nominal
offset = galsim.PositionD(dx, dy) offset = galsim.PositionD(dx, dy)
real_wcs_local = self.real_wcs.local(self.real_pos) chip_wcs_local = self.chip_wcs.local(self.real_pos)
big_galaxy = False big_galaxy = False
...@@ -282,18 +246,40 @@ class Galaxy(MockObject): ...@@ -282,18 +246,40 @@ class Galaxy(MockObject):
xOrderSigPlus = {'A':1.3909419820029296,'B':1.4760376591236062,'C':4.035447379743442,'D':5.5684364343742825,'E':16.260021029735388} xOrderSigPlus = {'A':1.3909419820029296,'B':1.4760376591236062,'C':4.035447379743442,'D':5.5684364343742825,'E':16.260021029735388}
grating_split_pos_chip = 0 + grating_split_pos grating_split_pos_chip = 0 + grating_split_pos
branges = np.zeros([len(bandpass_list), 2])
# print(hasattr(psf_model, 'bandranges'))
if hasattr(psf_model, 'bandranges'):
if psf_model.bandranges is None:
return 2, None
if len(psf_model.bandranges) != len(bandpass_list):
return 2, None
branges = psf_model.bandranges
else:
for i in range(len(bandpass_list)):
branges[i, 0] = bandpass_list[i].blue_limit * 10
branges[i, 1] = bandpass_list[i].red_limit * 10
for i in range(len(bandpass_list)): for i in range(len(bandpass_list)):
bandpass = bandpass_list[i] # bandpass = bandpass_list[i]
brange = branges[i]
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold) # psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp) disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk) disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape) disk = disk.shear(disk_shape)
bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp) bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge) bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape) bulge = bulge.shear(bulge_shape)
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk if self.bfrac == 0:
gal = disk
elif self.bfrac == 1:
gal = bulge
else:
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
# (TEST) Random knots # (TEST) Random knots
# knots = galsim.RandomKnots(npoints=100, profile=disk) # knots = galsim.RandomKnots(npoints=100, profile=disk)
...@@ -306,14 +292,14 @@ class Galaxy(MockObject): ...@@ -306,14 +292,14 @@ class Galaxy(MockObject):
g2 += fd_shear.g2 g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2) gal_shear = galsim.Shear(g1=g1, g2=g2)
gal = gal.shear(gal_shear) gal = gal.shear(gal_shear)
gal = galsim.Convolve(psf, gal) # gal = galsim.Convolve(psf, gal)
if not big_galaxy: # Not apply PSF for very big galaxy # if not big_galaxy: # Not apply PSF for very big galaxy
gal = galsim.Convolve(psf, gal) # gal = galsim.Convolve(psf, gal)
# if fd_shear is not None: # # if fd_shear is not None:
# gal = gal.shear(fd_shear) # # gal = gal.shear(fd_shear)
starImg = gal.drawImage(wcs=real_wcs_local, offset=offset) starImg = gal.drawImage(wcs=chip_wcs_local, offset=offset,method = 'real_space')
origin_star = [y_nominal - (starImg.center.y - starImg.ymin), origin_star = [y_nominal - (starImg.center.y - starImg.ymin),
x_nominal - (starImg.center.x - starImg.xmin)] x_nominal - (starImg.center.x - starImg.xmin)]
...@@ -335,12 +321,16 @@ class Galaxy(MockObject): ...@@ -335,12 +321,16 @@ class Galaxy(MockObject):
sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1, sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1,
ycenter=ycenter_p1, origin=origin_p1, ycenter=ycenter_p1, origin=origin_p1,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[0], conf=chip.sls_conf[0],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp_p1, chip=chip, pos_img_local=[xcenter_p1, ycenter_p1],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
subImg_p2 = starImg.array[:, subSlitPos+1:starImg.array.shape[1]] subImg_p2 = starImg.array[:, subSlitPos+1:starImg.array.shape[1]]
star_p2 = galsim.Image(subImg_p2) star_p2 = galsim.Image(subImg_p2)
...@@ -352,12 +342,16 @@ class Galaxy(MockObject): ...@@ -352,12 +342,16 @@ class Galaxy(MockObject):
sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2, sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2,
ycenter=ycenter_p2, origin=origin_p2, ycenter=ycenter_p2, origin=origin_p2,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[1], conf=chip.sls_conf[1],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp_p2, chip=chip, pos_img_local=[xcenter_p2, ycenter_p2],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp_p1 del sdp_p1
del sdp_p2 del sdp_p2
...@@ -365,25 +359,33 @@ class Galaxy(MockObject): ...@@ -365,25 +359,33 @@ class Galaxy(MockObject):
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0, sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star, ycenter=y_nominal - 0, origin=origin_star,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[1], conf=chip.sls_conf[1],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp del sdp
elif grating_split_pos_chip>=gal_end[1]: elif grating_split_pos_chip>=gal_end[1]:
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0, sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star, ycenter=y_nominal - 0, origin=origin_star,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[0], conf=chip.sls_conf[0],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp del sdp
# print(self.y_nominal, starImg.center.y, starImg.ymin) # print(self.y_nominal, starImg.center.y, starImg.ymin)
del psf # del psf
return 1, pos_shear return 1, pos_shear
def getGSObj(self, psf, g1=0, g2=0, flux=None, filt=None, tel=None, exptime=150.): def getGSObj(self, psf, g1=0, g2=0, flux=None, filt=None, tel=None, exptime=150.):
...@@ -404,46 +406,6 @@ class Galaxy(MockObject): ...@@ -404,46 +406,6 @@ class Galaxy(MockObject):
final = galsim.Convolve(psf, gal) final = galsim.Convolve(psf, gal)
return final return final
def drawObject(self, img, final, noise_level=0.0, flux=None, filt=None, tel=None, exptime=150.):
""" Override the method in parent class
Need to constrain the size of image stamp for extended objects
"""
isUpdated = True
if flux == None:
flux = self.getElectronFluxFilt(filt, tel, exptime)
stamp = final.drawImage(wcs=self.localWCS, offset=self.offset)
stamp_arr = stamp.array
mask = (stamp_arr >= 0.001*noise_level) # why 0.001?
err = int(np.sqrt(mask.sum()))
if np.mod(err, 2) == 1:
err += 1
# if err == 1:
if err == 0:
subSize = 16 # why 16?
else:
subSize = max([err, 16])
fluxRatio = flux / stamp_arr[mask].sum()
final = final.withScaledFlux(fluxRatio)
imgSub = galsim.ImageF(subSize, subSize)
# Draw with FFT
# stamp = final.drawImage(image=imgSub, wcs=self.localWCS, offset=self.offset)
# Draw with Photon Shoot
stamp = final.drawImage(image=imgSub, wcs=self.localWCS, method='phot', offset=self.offset)
stamp.setCenter(self.x_nominal, self.y_nominal)
if np.sum(np.isnan(stamp.array)) >= 1:
stamp.setZero()
bounds = stamp.bounds & img.bounds
if bounds.area() == 0:
isUpdated = False
else:
img[bounds] += stamp[bounds]
return img, stamp, isUpdated
def getObservedEll(self, g1=0, g2=0): def getObservedEll(self, g1=0, g2=0):
e1_obs, e2_obs, e_obs, theta = eObs(self.e1_total, self.e2_total, g1, g2) e1_obs, e2_obs, e_obs, theta = eObs(self.e1_total, self.e2_total, g1, g2)
return self.e1_total, self.e2_total, g1, g2, e1_obs, e2_obs return self.e1_total, self.e2_total, g1, g2, e1_obs, e2_obs
ObservationSim/MockObject/MockObject.py
View file @ edd720e6
import os
import galsim import galsim
import numpy as np import numpy as np
import astropy.constants as cons import astropy.constants as cons
from astropy import wcs from astropy import wcs
from astropy.table import Table from astropy.table import Table
import astropy.io.fits as fitsio
from ObservationSim.MockObject._util import magToFlux, VC_A, convolveGaussXorders from ObservationSim.MockObject._util import magToFlux, VC_A, convolveGaussXorders, convolveImg
from ObservationSim.MockObject._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, \ from ObservationSim.MockObject._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, \
getABMAG getABMAG
from ObservationSim.MockObject.SpecDisperser import SpecDisperser from ObservationSim.MockObject.SpecDisperser import SpecDisperser
...@@ -13,7 +15,6 @@ from ObservationSim.MockObject.SpecDisperser import SpecDisperser ...@@ -13,7 +15,6 @@ from ObservationSim.MockObject.SpecDisperser import SpecDisperser
class MockObject(object): class MockObject(object):
def __init__(self, param, logger=None): def __init__(self, param, logger=None):
self.param = param self.param = param
for key in self.param: for key in self.param:
setattr(self, key, self.param[key]) setattr(self, key, self.param[key])
...@@ -27,14 +28,15 @@ class MockObject(object): ...@@ -27,14 +28,15 @@ class MockObject(object):
elif self.param["star"] == 3: elif self.param["star"] == 3:
self.type = "stamp" self.type = "stamp"
###mock_stamp_END ###mock_stamp_END
###for calibration
elif self.param["star"] == 4:
self.type = "calib"
###END
self.sed = None self.sed = None
self.fd_shear = None
# Place holder for outputs # Place holder for outputs
self.additional_output_str = "" self.additional_output_str = ""
self.fd_shear = None
self.logger = logger self.logger = logger
def getMagFilter(self, filt): def getMagFilter(self, filt):
...@@ -65,6 +67,7 @@ class MockObject(object): ...@@ -65,6 +67,7 @@ class MockObject(object):
def getPosImg_Offset_WCS(self, img, fdmodel=None, chip=None, verbose=True, chip_wcs=None, img_header=None): def getPosImg_Offset_WCS(self, img, fdmodel=None, chip=None, verbose=True, chip_wcs=None, img_header=None):
self.posImg = img.wcs.toImage(self.getPosWorld()) self.posImg = img.wcs.toImage(self.getPosWorld())
self.localWCS = img.wcs.local(self.posImg) self.localWCS = img.wcs.local(self.posImg)
# Apply field distortion model
if (fdmodel is not None) and (chip is not None): if (fdmodel is not None) and (chip is not None):
if verbose: if verbose:
print("\n") print("\n")
...@@ -74,6 +77,7 @@ class MockObject(object): ...@@ -74,6 +77,7 @@ class MockObject(object):
if verbose: if verbose:
print("After field distortion:\n") print("After field distortion:\n")
print("x = %.2f, y = %.2f\n" % (self.posImg.x, self.posImg.y), flush=True) print("x = %.2f, y = %.2f\n" % (self.posImg.x, self.posImg.y), flush=True)
x, y = self.posImg.x + 0.5, self.posImg.y + 0.5 x, y = self.posImg.x + 0.5, self.posImg.y + 0.5
self.x_nominal = int(np.floor(x + 0.5)) self.x_nominal = int(np.floor(x + 0.5))
self.y_nominal = int(np.floor(y + 0.5)) self.y_nominal = int(np.floor(y + 0.5))
...@@ -81,50 +85,22 @@ class MockObject(object): ...@@ -81,50 +85,22 @@ class MockObject(object):
dy = y - self.y_nominal dy = y - self.y_nominal
self.offset = galsim.PositionD(dx, dy) self.offset = galsim.PositionD(dx, dy)
# Deal with chip rotation
if chip_wcs is not None: if chip_wcs is not None:
self.real_wcs = chip_wcs self.chip_wcs = chip_wcs
elif img_header is not None: elif img_header is not None:
self.real_wcs = galsim.FitsWCS(header=img_header) self.chip_wcs = galsim.FitsWCS(header=img_header)
else: else:
self.real_wcs = None self.chip_wcs = None
return self.posImg, self.offset, self.localWCS, self.real_wcs, self.fd_shear return self.posImg, self.offset, self.localWCS, self.chip_wcs, self.fd_shear
def getRealPos(self, img, global_x=0., global_y=0., img_real_wcs=None): def getRealPos(self, img, global_x=0., global_y=0., img_real_wcs=None):
img_global_pos = galsim.PositionD(global_x, global_y) img_global_pos = galsim.PositionD(global_x, global_y)
cel_pos = img.wcs.toWorld(img_global_pos) cel_pos = img.wcs.toWorld(img_global_pos)
realPos = img_real_wcs.toImage(cel_pos) realPos = img_real_wcs.toImage(cel_pos)
return realPos return realPos
def drawObject(self, img, final, flux=None, filt=None, tel=None, exptime=150.):
""" Draw (point like) object on img.
Should be overided for extended source, e.g. galaxy...
Paramter:
img: the "canvas"
final: final (after shear, PSF etc.) GSObject
Return:
img: the image with the GSObject added (or discarded)
isUpdated: is the "canvas" been updated? (a flag for updating statistcs)
"""
isUpdated = True
# Draw with FFT
# stamp = final.drawImage(wcs=self.localWCS, offset=self.offset)
# Draw with Photon Shoot
stamp = final.drawImage(wcs=self.localWCS, method='phot', offset=self.offset)
stamp.setCenter(self.x_nominal, self.y_nominal)
if np.sum(np.isnan(stamp.array)) >= 1:
stamp.setZero()
bounds = stamp.bounds & img.bounds
if bounds.area() == 0:
isUpdated = False
else:
img[bounds] += stamp[bounds]
return img, stamp, isUpdated
def drawObj_multiband(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0, def drawObj_multiband(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150., fd_shear=None): exptime=150., fd_shear=None):
if nphotons_tot == None: if nphotons_tot == None:
...@@ -139,29 +115,27 @@ class MockObject(object): ...@@ -139,29 +115,27 @@ class MockObject(object):
self.logger.error(e) self.logger.error(e)
return 2, None return 2, None
nphotons_sum = 0 # Set Galsim Parameters
photons_list = []
xmax, ymax = 0, 0
# (TEST) Galsim Parameters
if self.getMagFilter(filt) <= 15: if self.getMagFilter(filt) <= 15:
folding_threshold = 5.e-4 folding_threshold = 5.e-4
else: else:
folding_threshold = 5.e-3 folding_threshold = 5.e-3
gsp = galsim.GSParams(folding_threshold=folding_threshold) gsp = galsim.GSParams(folding_threshold=folding_threshold)
# Get real image position of object (deal with chip rotation w.r.t its center)
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y, self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.real_wcs) img_real_wcs=self.chip_wcs)
x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5 x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5
x_nominal = int(np.floor(x + 0.5)) x_nominal = int(np.floor(x + 0.5))
y_nominal = int(np.floor(y + 0.5)) y_nominal = int(np.floor(y + 0.5))
dx = x - x_nominal dx = x - x_nominal
dy = y - y_nominal dy = y - y_nominal
offset = galsim.PositionD(dx, dy) offset = galsim.PositionD(dx, dy)
# Get real local wcs of object (deal with chip rotation w.r.t its center)
chip_wcs_local = self.chip_wcs.local(self.real_pos)
is_updated = 0
real_wcs_local = self.real_wcs.local(self.real_pos) # Loop over all sub-bandpasses
for i in range(len(bandpass_list)): for i in range(len(bandpass_list)):
bandpass = bandpass_list[i] bandpass = bandpass_list[i]
try: try:
...@@ -170,61 +144,42 @@ class MockObject(object): ...@@ -170,61 +144,42 @@ class MockObject(object):
print(e) print(e)
if self.logger: if self.logger:
self.logger.error(e) self.logger.error(e)
# return False
continue continue
ratio = sub / full ratio = sub / full
if not (ratio == -1 or (ratio != ratio)): if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot nphotons = ratio * nphotons_tot
else: else:
# return False
continue continue
nphotons_sum += nphotons
# nphotons_sum += nphotons
# print("nphotons_sub-band_%d = %.2f"%(i, nphotons)) # print("nphotons_sub-band_%d = %.2f"%(i, nphotons))
# Get PSF model
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass,
folding_threshold=folding_threshold) folding_threshold=folding_threshold)
star = galsim.DeltaFunction(gsparams=gsp) # star = galsim.DeltaFunction(gsparams=gsp)
star = star.withFlux(nphotons) # star = star.withFlux(nphotons)
star = galsim.Convolve(psf, star) # star = galsim.Convolve(psf, star)
star = psf.withFlux(nphotons)
stamp = star.drawImage(wcs=real_wcs_local, method='phot', offset=offset, save_photons=True)
xmax = max(xmax, stamp.xmax)
ymax = max(ymax, stamp.ymax)
photons = stamp.photons
photons.x += x_nominal
photons.y += y_nominal
photons_list.append(photons)
stamp = galsim.ImageF(int(xmax * 1.1), int(ymax * 1.1))
stamp.wcs = real_wcs_local
stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
# # (DEBUG)
# print("stamp bounds: ", stamp.bounds)
# print(bounds)
if bounds.area() > 0:
chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds]
for i in range(len(photons_list)):
if i == 0:
chip.sensor.accumulate(photons_list[i], stamp)
else:
chip.sensor.accumulate(photons_list[i], stamp, resume=True)
chip.img[bounds] = stamp[bounds] stamp = star.drawImage(wcs=chip_wcs_local, offset=offset)
if np.sum(np.isnan(stamp.array)) > 0:
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin) continue
else: stamp.setCenter(x_nominal, y_nominal)
# Return code 0: object photons missed this detector bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() > 0:
chip.img.setOrigin(0, 0)
chip.img[bounds] += stamp[bounds]
is_updated = 1
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
del stamp
if is_updated == 0:
# Return code 0: object has missed this detector
print("obj %s missed"%(self.id)) print("obj %s missed"%(self.id))
if self.logger: if self.logger:
self.logger.info("obj %s missed"%(self.id)) self.logger.info("obj %s missed"%(self.id))
return 0, pos_shear return 0, pos_shear
del photons_list
del stamp
return 1, pos_shear # Return code 1: draw sucesss return 1, pos_shear # Return code 1: draw sucesss
def addSLStoChipImage(self, sdp=None, chip=None, xOrderSigPlus=None, local_wcs=None): def addSLStoChipImage(self, sdp=None, chip=None, xOrderSigPlus=None, local_wcs=None):
...@@ -275,9 +230,69 @@ class MockObject(object): ...@@ -275,9 +230,69 @@ class MockObject(object):
del stamp del stamp
del spec_orders del spec_orders
def addSLStoChipImageWithPSF(self, sdp=None, chip=None, pos_img_local = [1,1], psf_model=None, bandNo = 1, grating_split_pos=3685, local_wcs=None, pos_img=None):
spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items():
img_s = v[0]
# print(bandNo,k)
try:
psf, pos_shear = psf_model.get_PSF(chip, pos_img_local = pos_img_local, bandNo = bandNo, galsimGSObject=True, g_order = k, grating_split_pos=grating_split_pos)
except:
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img)
psf_img = psf.drawImage(nx=100, ny=100, wcs = local_wcs)
psf_img_m = psf_img.array
#########################################################
# DEBUG
#########################################################
# ids_p = psf_img_m < 0
# psf_img_m[ids_p] = 0
# from astropy.io import fits
# fits.writeto(str(bandNo) + '_' + str(k) + '_psf.fits', psf_img_m)
# print("DEBUG: orig_off is", orig_off)
nan_ids = np.isnan(img_s)
if img_s[nan_ids].shape[0] > 0:
img_s[nan_ids] = 0
print("DEBUG: specImg nan num is", img_s[nan_ids].shape[0])
#########################################################
img_s, orig_off = convolveImg(img_s, psf_img_m)
origin_order_x = v[1] - orig_off[0]
origin_order_y = v[2] - orig_off[1]
specImg = galsim.ImageF(img_s)
# photons = galsim.PhotonArray.makeFromImage(specImg)
# photons.x += origin_order_x
# photons.y += origin_order_y
# xlen_imf = int(specImg.xmax - specImg.xmin + 1)
# ylen_imf = int(specImg.ymax - specImg.ymin + 1)
# stamp = galsim.ImageF(xlen_imf, ylen_imf)
# stamp.wcs = local_wcs
# stamp.setOrigin(origin_order_x, origin_order_y)
specImg.wcs = local_wcs
specImg.setOrigin(origin_order_x, origin_order_y)
bounds = specImg.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() == 0:
continue
chip.img.setOrigin(0, 0)
chip.img[bounds] = chip.img[bounds] + specImg[bounds]
# stamp[bounds] = chip.img[bounds]
# # chip.sensor.accumulate(photons, stamp)
# chip.img[bounds] = stamp[bounds]
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
# del stamp
del spec_orders
return pos_shear
def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0, def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150., normFilter=None, grating_split_pos=3685, fd_shear=None): exptime=150., normFilter=None, grating_split_pos=3685, fd_shear=None):
if normFilter is not None: if normFilter is not None:
norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001 norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed, sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
...@@ -299,7 +314,7 @@ class MockObject(object): ...@@ -299,7 +314,7 @@ class MockObject(object):
names=('WAVELENGTH', 'FLUX')) names=('WAVELENGTH', 'FLUX'))
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y, self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.real_wcs) img_real_wcs=self.chip_wcs)
x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5 x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5
x_nominal = int(np.floor(x + 0.5)) x_nominal = int(np.floor(x + 0.5))
...@@ -308,29 +323,45 @@ class MockObject(object): ...@@ -308,29 +323,45 @@ class MockObject(object):
dy = y - y_nominal dy = y - y_nominal
offset = galsim.PositionD(dx, dy) offset = galsim.PositionD(dx, dy)
real_wcs_local = self.real_wcs.local(self.real_pos) chip_wcs_local = self.chip_wcs.local(self.real_pos)
flat_cube = chip.flat_cube flat_cube = chip.flat_cube
xOrderSigPlus = {'A': 1.3909419820029296, 'B': 1.4760376591236062, 'C': 4.035447379743442, xOrderSigPlus = {'A': 1.3909419820029296, 'B': 1.4760376591236062, 'C': 4.035447379743442,
'D': 5.5684364343742825, 'E': 16.260021029735388} 'D': 5.5684364343742825, 'E': 16.260021029735388}
grating_split_pos_chip = 0 + grating_split_pos grating_split_pos_chip = 0 + grating_split_pos
branges = np.zeros([len(bandpass_list),2])
if hasattr(psf_model,'bandranges'):
if psf_model.bandranges is None:
return 2, None
if len(psf_model.bandranges) != len(bandpass_list):
return 2, None
branges = psf_model.bandranges
else:
for i in range(len(bandpass_list)):
branges[i, 0] = bandpass_list[i].blue_limit * 10
branges[i, 1] = bandpass_list[i].red_limit * 10
for i in range(len(bandpass_list)): for i in range(len(bandpass_list)):
bandpass = bandpass_list[i] # bandpass = bandpass_list[i]
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, brange = branges[i]
folding_threshold=folding_threshold)
# psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass,
# folding_threshold=folding_threshold)
star = galsim.DeltaFunction(gsparams=gsp) star = galsim.DeltaFunction(gsparams=gsp)
star = star.withFlux(tel.pupil_area * exptime) star = star.withFlux(tel.pupil_area * exptime)
star = galsim.Convolve(psf, star) psf_tmp = galsim.Gaussian(sigma=0.002)
star = galsim.Convolve(psf_tmp, star)
starImg = star.drawImage(nx=100, ny=100, wcs=real_wcs_local, offset=offset) starImg = star.drawImage(nx=60, ny=60, wcs=chip_wcs_local, offset=offset)
origin_star = [y_nominal - (starImg.center.y - starImg.ymin), origin_star = [y_nominal - (starImg.center.y - starImg.ymin),
x_nominal - (starImg.center.x - starImg.xmin)] x_nominal - (starImg.center.x - starImg.xmin)]
starImg.setOrigin(0,0) starImg.setOrigin(0,0)
gal_origin = [origin_star[0], origin_star[1]] gal_origin = [origin_star[0], origin_star[1]]
gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1] gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1]
if gal_origin[1] < grating_split_pos_chip < gal_end[1]: if gal_origin[1] < grating_split_pos_chip < gal_end[1]:
subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1) subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1)
## part img disperse ## part img disperse
...@@ -345,12 +376,15 @@ class MockObject(object): ...@@ -345,12 +376,15 @@ class MockObject(object):
sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1, sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1,
ycenter=ycenter_p1, origin=origin_p1, ycenter=ycenter_p1, origin=origin_p1,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[0], conf=chip.sls_conf[0],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp_p1, chip=chip, pos_img_local = [xcenter_p1,ycenter_p1],
psf_model=psf_model, bandNo = i+1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
subImg_p2 = starImg.array[:, subSlitPos + 1:starImg.array.shape[1]] subImg_p2 = starImg.array[:, subSlitPos + 1:starImg.array.shape[1]]
star_p2 = galsim.Image(subImg_p2) star_p2 = galsim.Image(subImg_p2)
...@@ -362,12 +396,15 @@ class MockObject(object): ...@@ -362,12 +396,15 @@ class MockObject(object):
sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2, sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2,
ycenter=ycenter_p2, origin=origin_p2, ycenter=ycenter_p2, origin=origin_p2,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[1], conf=chip.sls_conf[1],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp_p2, chip=chip, pos_img_local=[xcenter_p2, ycenter_p2],
psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp_p1 del sdp_p1
del sdp_p2 del sdp_p2
...@@ -375,23 +412,29 @@ class MockObject(object): ...@@ -375,23 +412,29 @@ class MockObject(object):
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0, sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star, ycenter=y_nominal - 0, origin=origin_star,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[1], conf=chip.sls_conf[1],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp del sdp
elif grating_split_pos_chip >= gal_end[1]: elif grating_split_pos_chip >= gal_end[1]:
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0, sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star, ycenter=y_nominal - 0, origin=origin_star,
tar_spec=normalSED, tar_spec=normalSED,
band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10, band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[0], conf=chip.sls_conf[0],
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=real_wcs_local) # self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp del sdp
del psf # del psf
return 1, pos_shear return 1, pos_shear
def SNRestimate(self, img_obj, flux, noise_level=0.0, seed=31415): def SNRestimate(self, img_obj, flux, noise_level=0.0, seed=31415):
...@@ -403,3 +446,88 @@ class MockObject(object): ...@@ -403,3 +446,88 @@ class MockObject(object):
sig_obj = np.std(stamp.array) sig_obj = np.std(stamp.array)
snr_obj = img_flux / sig_obj snr_obj = img_flux / sig_obj
return snr_obj return snr_obj
def drawObj_PSF(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150., fd_shear=None, chip_output=None):
if nphotons_tot == None:
nphotons_tot = self.getElectronFluxFilt(filt, tel, exptime)
# print("nphotons_tot = ", nphotons_tot)
try:
full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full)
except Exception as e:
print(e)
if self.logger:
self.logger.error(e)
return 2, None
# Set Galsim Parameters
if self.getMagFilter(filt) <= 15:
folding_threshold = 5.e-4
else:
folding_threshold = 5.e-3
gsp = galsim.GSParams(folding_threshold=folding_threshold)
# Get real image position of object (deal with chip rotation w.r.t its center)
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.chip_wcs)
x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5
x_nominal = int(np.floor(x + 0.5))
y_nominal = int(np.floor(y + 0.5))
dx = x - x_nominal
dy = y - y_nominal
offset = galsim.PositionD(dx, dy)
# Get real local wcs of object (deal with chip rotation w.r.t its center)
chip_wcs_local = self.chip_wcs.local(self.real_pos)
is_updated = 0
# Loop over all sub-bandpasses
for i in range(len(bandpass_list)):
bandpass = bandpass_list[i]
try:
sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
except Exception as e:
print(e)
if self.logger:
self.logger.error(e)
continue
ratio = sub / full
if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot
else:
continue
# Get PSF model
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass,
folding_threshold=folding_threshold)
star_temp = psf.withFlux(nphotons)
if i==0:
star = star_temp
else:
star = star+star_temp
pixelScale = 0.074
stamp = star.drawImage(wcs=chip_wcs_local, offset=offset)
#stamp = star.drawImage(nx=256, ny=256, scale=pixelScale)
if np.sum(np.isnan(stamp.array)) > 0:
return None
fn = chip_output.subdir + "/psfIDW"
os.makedirs(fn, exist_ok=True)
fn = fn + "/ccd_{:}".format(chip.chipID)+"_psf_"+str(self.param['id'])+".fits"
if fn != None:
if os.path.exists(fn):
os.remove(fn)
hdu = fitsio.PrimaryHDU()
hdu.data = stamp.array
hdu.header.set('name', self.type)
hdu.header.set('pixScale', pixelScale)
hdu.header.set('objID', self.param['id'])
hdu.writeto(fn)
del stamp
return None
ObservationSim/MockObject/SpecDisperser/SpecDisperser.py
View file @ edd720e6
...@@ -155,7 +155,7 @@ class SpecDisperser(object): ...@@ -155,7 +155,7 @@ class SpecDisperser(object):
sensitivity_beam = ysens sensitivity_beam = ysens
len_spec_x = len(dx) len_spec_x = len(dx)
len_spec_y = int(ceil(ytrace_beam[-1]) - floor(ytrace_beam[0]) + 1) len_spec_y = int(abs(ceil(ytrace_beam[-1]) - floor(ytrace_beam[0])) + 1)
beam_sh = (self.img_sh[0] + len_spec_y, self.img_sh[1] + len_spec_x) beam_sh = (self.img_sh[0] + len_spec_y, self.img_sh[1] + len_spec_x)
modelf = zeros(product(beam_sh), dtype=float) modelf = zeros(product(beam_sh), dtype=float)
...@@ -239,7 +239,7 @@ class SpecDisperser(object): ...@@ -239,7 +239,7 @@ class SpecDisperser(object):
# else: # else:
# beam_flat[k] = self.flat_cube[:, originOut_y + i, originOut_x + j] # beam_flat[k] = self.flat_cube[:, originOut_y + i, originOut_x + j]
status = disperse.disperse_grism_object(self.thumb_img, status = disperse.disperse_grism_object(self.thumb_img.astype(np.float32),
flat_index[nonz], yfrac_beam[nonz], flat_index[nonz], yfrac_beam[nonz],
sensitivity_beam[nonz], sensitivity_beam[nonz],
modelf, x0, modelf, x0,
......
ObservationSim/MockObject/Stamp.py
View file @ edd720e6
import os, sys import os, sys
import random
import numpy as np import numpy as np
import galsim
import astropy.constants as cons import astropy.constants as cons
from astropy.table import Table from astropy.table import Table
from scipy import interpolate from scipy import interpolate
import astropy.io.fits as fitsio
import galsim
import gc
from ObservationSim.MockObject.MockObject import MockObject from ObservationSim.MockObject.MockObject import MockObject
from ObservationSim.MockObject.SpecDisperser import SpecDisperser
from ObservationSim.MockObject._util import magToFlux,VC_A
from ObservationSim.MockObject._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, getABMAG,convolveGaussXorders from ObservationSim.MockObject._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, getABMAG,convolveGaussXorders
class Stamp(MockObject): class Stamp(MockObject):
def __init__(self, param): def __init__(self, param, logger=None):
super().__init__(param) super().__init__(param, logger=logger)
def unload_SED(self): def unload_SED(self):
"""(Test) free up SED memory """(Test) free up SED memory
...@@ -35,9 +30,9 @@ class Stamp(MockObject): ...@@ -35,9 +30,9 @@ class Stamp(MockObject):
self.logger.error(e) self.logger.error(e)
return False return False
nphotons_sum = 0 #nphotons_sum = 0
photons_list = [] #photons_list = []
xmax, ymax = 0, 0 #xmax, ymax = 0, 0
if self.getMagFilter(filt) <= 15: if self.getMagFilter(filt) <= 15:
folding_threshold = 5.e-4 folding_threshold = 5.e-4
...@@ -46,7 +41,7 @@ class Stamp(MockObject): ...@@ -46,7 +41,7 @@ class Stamp(MockObject):
gsp = galsim.GSParams(folding_threshold=folding_threshold) gsp = galsim.GSParams(folding_threshold=folding_threshold)
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y, self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.real_wcs) img_real_wcs=self.chip_wcs)
x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5 x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5
x_nominal = int(np.floor(x + 0.5)) x_nominal = int(np.floor(x + 0.5))
...@@ -55,72 +50,237 @@ class Stamp(MockObject): ...@@ -55,72 +50,237 @@ class Stamp(MockObject):
dy = y - y_nominal dy = y - y_nominal
offset = galsim.PositionD(dx, dy) offset = galsim.PositionD(dx, dy)
real_wcs_local = self.real_wcs.local(self.real_pos) chip_wcs_local = self.chip_wcs.local(self.real_pos)
is_updated = 0
if fd_shear:
g1 += fd_shear.g1
g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2)
for i in range(len(bandpass_list)): for i in range(len(bandpass_list)):
bandpass = bandpass_list[i] bandpass = bandpass_list[i]
try: try:
sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass) sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
except Exception as e: except Exception as e:
print(e) print(e)
self.logger.error(e) if self.logger:
# return False self.logger.error(e)
continue continue
ratio = sub/full ratio = sub/full
if not (ratio == -1 or (ratio != ratio)): if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot nphotons = ratio * nphotons_tot
else: else:
# return False
continue continue
nphotons_sum += nphotons #nphotons_sum += nphotons
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold) psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
_gal = self.param['image'] _gal = self.param['image']
galIm = galsim.ImageF(_gal, scale=self.param['pixScale']) galImg= galsim.ImageF(_gal, scale=self.param['pixScale'])
gal = galsim.InterpolatedImage(galIm) gal_temp= galsim.InterpolatedImage(galImg)
gal = gal.withFlux(nphotons) gal_temp= gal_temp.shear(gal_shear)
#gal_shear = galsim.Shear(g1=g1, g2=g2) gal_temp= gal_temp.withFlux(nphotons)
#gal = gal.shear(gal_shear)
gal = galsim.Convolve(psf, gal) gal_temp= galsim.Convolve(psf, gal_temp)
if fd_shear is not None:
gal = gal.shear(fd_shear)
stamp = gal.drawImage(wcs=real_wcs_local, method='phot', offset=self.offset, save_photons=True) if i == 0:
gal = gal_temp
xmax = max(xmax, stamp.xmax - stamp.xmin) else:
ymax = max(ymax, stamp.ymax - stamp.ymin) gal = gal + gal_temp
photons = stamp.photons
photons.x += x_nominal
photons.y += y_nominal
photons_list.append(photons)
del gal
# print('xmax = %d, ymax = %d '%(xmax, ymax)) stamp = gal.drawImage(wcs=chip_wcs_local, offset=offset)
if np.sum(np.isnan(stamp.array)) > 0:
# ERROR happens
return 2, pos_shear
stamp = galsim.ImageF(int(xmax*1.1), int(ymax*1.1))
stamp.wcs = real_wcs_local
stamp.setCenter(x_nominal, y_nominal) stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1) bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() > 0: if bounds.area() > 0:
chip.img.setOrigin(0, 0) chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds] chip.img[bounds] += stamp[bounds]
for i in range(len(photons_list)): is_updated = 1
if i == 0: chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
chip.sensor.accumulate(photons_list[i], stamp) del stamp
else:
chip.sensor.accumulate(photons_list[i], stamp, resume=True)
chip.img[bounds] = stamp[bounds] if is_updated == 0:
print("fits obj %s missed"%(self.id))
if self.logger:
self.logger.info("fits obj %s missed"%(self.id))
return 0, pos_shear
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin) return 1, pos_shear
def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150., normFilter=None, grating_split_pos=3685, fd_shear=None):
if normFilter is not None:
norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
norm_thr=normFilter,
sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]),
eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
if sedNormFactor == 0:
return 2, None
else:
sedNormFactor = 1.
normalSED = Table(np.array([self.sed['WAVELENGTH'], self.sed['FLUX'] * sedNormFactor]).T,
names=('WAVELENGTH', 'FLUX'))
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.chip_wcs)
x, y = self.real_pos.x + 0.5, self.real_pos.y + 0.5
x_nominal = int(np.floor(x + 0.5))
y_nominal = int(np.floor(y + 0.5))
dx = x - x_nominal
dy = y - y_nominal
offset = galsim.PositionD(dx, dy)
chip_wcs_local = self.chip_wcs.local(self.real_pos)
if self.getMagFilter(filt) <= 15:
folding_threshold = 5.e-4
else:
folding_threshold = 5.e-3
gsp = galsim.GSParams(folding_threshold=folding_threshold)
# nphotons_sum = 0
flat_cube = chip.flat_cube
xOrderSigPlus = {'A':1.3909419820029296,'B':1.4760376591236062,'C':4.035447379743442,'D':5.5684364343742825,'E':16.260021029735388}
grating_split_pos_chip = 0 + grating_split_pos
branges = np.zeros([len(bandpass_list), 2])
# print(hasattr(psf_model, 'bandranges'))
if hasattr(psf_model, 'bandranges'):
if psf_model.bandranges is None:
return 2, None
if len(psf_model.bandranges) != len(bandpass_list):
return 2, None
branges = psf_model.bandranges
else:
for i in range(len(bandpass_list)):
branges[i, 0] = bandpass_list[i].blue_limit * 10
branges[i, 1] = bandpass_list[i].red_limit * 10
for i in range(len(bandpass_list)):
# bandpass = bandpass_list[i]
brange = branges[i]
# psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
_gal = self.param['image']
galImg= galsim.ImageF(_gal, scale=self.param['pixScale'])
gal = galsim.InterpolatedImage(galImg)
# (TEST) Random knots
# knots = galsim.RandomKnots(npoints=100, profile=disk)
# kfrac = np.random.random()*(1.0 - self.bfrac)
# gal = self.bfrac * bulge + (1.0 - self.bfrac - kfrac) * disk + kfrac * knots
gal = gal.withFlux(tel.pupil_area * exptime)
if fd_shear:
g1 += fd_shear.g1
g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2)
gal = gal.shear(gal_shear)
# gal = galsim.Convolve(psf, gal)
# if not big_galaxy: # Not apply PSF for very big galaxy
# gal = galsim.Convolve(psf, gal)
# # if fd_shear is not None:
# # gal = gal.shear(fd_shear)
starImg = gal.drawImage(wcs=chip_wcs_local, offset=offset,method = 'real_space')
origin_star = [y_nominal - (starImg.center.y - starImg.ymin),
x_nominal - (starImg.center.x - starImg.xmin)]
starImg.setOrigin(0, 0)
gal_origin = [origin_star[0], origin_star[1]]
gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1]
if gal_origin[1] < grating_split_pos_chip < gal_end[1]:
subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1)
## part img disperse
subImg_p1 = starImg.array[:, 0:subSlitPos]
star_p1 = galsim.Image(subImg_p1)
star_p1.setOrigin(0, 0)
origin_p1 = origin_star
xcenter_p1 = min(x_nominal,grating_split_pos_chip-1) - 0
ycenter_p1 = y_nominal-0
sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1,
ycenter=ycenter_p1, origin=origin_p1,
tar_spec=normalSED,
band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[0],
isAlongY=0,
flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp_p1, chip=chip, pos_img_local=[xcenter_p1, ycenter_p1],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
subImg_p2 = starImg.array[:, subSlitPos+1:starImg.array.shape[1]]
star_p2 = galsim.Image(subImg_p2)
star_p2.setOrigin(0, 0)
origin_p2 = [origin_star[0], grating_split_pos_chip]
xcenter_p2 = max(x_nominal, grating_split_pos_chip - 1) - 0
ycenter_p2 = y_nominal - 0
sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2,
ycenter=ycenter_p2, origin=origin_p2,
tar_spec=normalSED,
band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[1],
isAlongY=0,
flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp_p2, chip=chip, pos_img_local=[xcenter_p2, ycenter_p2],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp_p1
del sdp_p2
elif grating_split_pos_chip<=gal_origin[1]:
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star,
tar_spec=normalSED,
band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[1],
isAlongY=0,
flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp
elif grating_split_pos_chip>=gal_end[1]:
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star,
tar_spec=normalSED,
band_start=brange[0], band_end=brange[1],
conf=chip.sls_conf[0],
isAlongY=0,
flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1,
grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img)
del sdp
del photons_list # print(self.y_nominal, starImg.center.y, starImg.ymin)
del stamp # del psf
gc.collect() return 1, pos_shear
return True, pos_shear
ObservationSim/MockObject/__init__.py
View file @ edd720e6
...@@ -4,5 +4,6 @@ from .CatalogBase import CatalogBase ...@@ -4,5 +4,6 @@ from .CatalogBase import CatalogBase
from .Quasar import Quasar from .Quasar import Quasar
from .Star import Star from .Star import Star
from .Stamp import Stamp from .Stamp import Stamp
from .FlatLED import FlatLED
# from .SkybackgroundMap import * # from .SkybackgroundMap import *
# from .CosmicRay import CosmicRay # from .CosmicRay import CosmicRay
ObservationSim/MockObject/_util.py
View file @ edd720e6
...@@ -571,4 +571,14 @@ def convolveGaussXorders(img=None, sigma = 1): ...@@ -571,4 +571,14 @@ def convolveGaussXorders(img=None, sigma = 1):
convImg = signal.fftconvolve(img, psf, mode='full', axes=None) convImg = signal.fftconvolve(img, psf, mode='full', axes=None)
return convImg, offset return convImg, offset
def convolveImg(img=None, psf = None):
from astropy.modeling.models import Gaussian2D
from scipy import signal
convImg = signal.fftconvolve(img, psf, mode='full', axes=None)
offset_x = int(psf.shape[1]/2. + 0.5) - 1
offset_y = int(psf.shape[0]/2. + 0.5) - 1
offset = [offset_x,offset_y]
return convImg, offset
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