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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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ObservationSim/Instrument/data/throughputs/z_throughput.txt
View file @ edd720e6
# z_cssc
# lambda_Angst throughput
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ObservationSim/MockObject/CatalogBase.py
View file @ edd720e6
......@@ -56,6 +56,8 @@ class CatalogBase(metaclass=ABCMeta):
"teff":0.,
"logg":0.,
"feh":0.,
"DM":0.,
"stellarMass":1.,
# C6 galaxies parameters
"e1":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 galsim
import os, sys
import astropy.constants as cons
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.MockObject import MockObject
......@@ -14,18 +11,6 @@ from ObservationSim.MockObject.MockObject import MockObject
class Galaxy(MockObject):
def __init__(self, param, logger=None):
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"):
self.disk_sersic_idx = 1.
......@@ -76,7 +61,12 @@ class Galaxy(MockObject):
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
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)
if fd_shear is not None:
g1 += fd_shear.g1
......@@ -101,10 +91,6 @@ class Galaxy(MockObject):
if self.logger:
self.logger.error(e)
return 2, None
nphotons_sum = 0
photons_list = []
xmax, ymax = 0, 0
# # [C6 TEST]
# print('hlr_disk = %.4f, hlr_bulge = %.4f'%(self.hlr_disk, self.hlr_bulge))
......@@ -114,7 +100,7 @@ class Galaxy(MockObject):
if self.hlr_disk > 3.0 or self.hlr_bulge > 3.0: # Very big galaxy
big_galaxy = True
# (TEST) Galsim Parameters
# Set Galsim Parameters
if self.getMagFilter(filt) <= 15 and (not big_galaxy):
folding_threshold = 5.e-4
else:
......@@ -122,7 +108,7 @@ class Galaxy(MockObject):
gsp = galsim.GSParams(folding_threshold=folding_threshold)
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_nominal = int(np.floor(x + 0.5))
......@@ -130,9 +116,11 @@ class Galaxy(MockObject):
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
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_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape)
......@@ -140,38 +128,42 @@ class Galaxy(MockObject):
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
# Get shear and deal with shear induced by field distortion
if fd_shear:
g1 += fd_shear.g1
g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2)
# 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)
# return False
continue
ratio = sub/full
if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot
else:
continue
nphotons_sum += nphotons
# nphotons_sum += nphotons
# # [C6 TEST]
# 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)
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.withFlux(nphotons)
if not big_galaxy: # Not apply PSF for very big galaxy
gal_temp = galsim.Convolve(psf, gal_temp)
......@@ -186,47 +178,21 @@ class Galaxy(MockObject):
# kfrac = np.random.random()*(1.0 - self.bfrac)
# gal = self.bfrac * bulge + (1.0 - self.bfrac - kfrac) * disk + kfrac * knots
# # [C6 TEST]
# print('xmax = %d, ymax = %d '%(xmax, ymax))
# # Output memory usage
# snapshot = tracemalloc.take_snapshot()
# top_stats = snapshot.statistics('lineno')
# 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 = gal.drawImage(wcs=chip_wcs_local, method='phot', offset=offset, save_photons=True)
stamp = gal.drawImage(wcs=chip_wcs_local, offset=offset)
if np.sum(np.isnan(stamp.array)) > 0:
# ERROR happens
return 2, pos_shear
stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() > 0:
chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds]
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[bounds] += stamp[bounds]
is_updated = 1
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
else:
del stamp
if is_updated == 0:
# Return code 0: object photons missed this detector
print("obj %s missed"%(self.id))
if self.logger:
......@@ -235,8 +201,6 @@ class Galaxy(MockObject):
# # [C6 TEST]
# print("nphotons_sum = ", nphotons_sum)
del photons_list
del stamp
return 1, pos_shear
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):
names=('WAVELENGTH', 'FLUX'))
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_nominal = int(np.floor(x + 0.5))
......@@ -264,7 +228,7 @@ class Galaxy(MockObject):
dy = y - y_nominal
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
......@@ -282,18 +246,40 @@ class Galaxy(MockObject):
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]
# 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_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
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_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
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
# knots = galsim.RandomKnots(npoints=100, profile=disk)
......@@ -306,14 +292,14 @@ class Galaxy(MockObject):
g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2)
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
gal = galsim.Convolve(psf, gal)
# if fd_shear is not None:
# gal = gal.shear(fd_shear)
# 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=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),
x_nominal - (starImg.center.x - starImg.xmin)]
......@@ -335,12 +321,16 @@ class Galaxy(MockObject):
sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1,
ycenter=ycenter_p1, origin=origin_p1,
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],
isAlongY=0,
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]]
star_p2 = galsim.Image(subImg_p2)
......@@ -352,12 +342,16 @@ class Galaxy(MockObject):
sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2,
ycenter=ycenter_p2, origin=origin_p2,
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],
isAlongY=0,
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_p2
......@@ -365,25 +359,33 @@ class Galaxy(MockObject):
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star,
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],
isAlongY=0,
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
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=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10,
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=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
# print(self.y_nominal, starImg.center.y, starImg.ymin)
del psf
# del psf
return 1, pos_shear
def getGSObj(self, psf, g1=0, g2=0, flux=None, filt=None, tel=None, exptime=150.):
......@@ -404,46 +406,6 @@ class Galaxy(MockObject):
final = galsim.Convolve(psf, gal)
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):
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
ObservationSim/MockObject/MockObject.py
View file @ edd720e6
import os
import galsim
import numpy as np
import astropy.constants as cons
from astropy import wcs
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, \
getABMAG
from ObservationSim.MockObject.SpecDisperser import SpecDisperser
......@@ -13,7 +15,6 @@ from ObservationSim.MockObject.SpecDisperser import SpecDisperser
class MockObject(object):
def __init__(self, param, logger=None):
self.param = param
for key in self.param:
setattr(self, key, self.param[key])
......@@ -27,14 +28,15 @@ class MockObject(object):
elif self.param["star"] == 3:
self.type = "stamp"
###mock_stamp_END
###for calibration
elif self.param["star"] == 4:
self.type = "calib"
###END
self.sed = None
self.fd_shear = None
# Place holder for outputs
self.additional_output_str = ""
self.fd_shear = None
self.logger = logger
def getMagFilter(self, filt):
......@@ -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):
self.posImg = img.wcs.toImage(self.getPosWorld())
self.localWCS = img.wcs.local(self.posImg)
# Apply field distortion model
if (fdmodel is not None) and (chip is not None):
if verbose:
print("\n")
......@@ -74,6 +77,7 @@ class MockObject(object):
if verbose:
print("After field distortion:\n")
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
self.x_nominal = int(np.floor(x + 0.5))
self.y_nominal = int(np.floor(y + 0.5))
......@@ -81,50 +85,22 @@ class MockObject(object):
dy = y - self.y_nominal
self.offset = galsim.PositionD(dx, dy)
# Deal with chip rotation
if chip_wcs is not None:
self.real_wcs = chip_wcs
self.chip_wcs = chip_wcs
elif img_header is not None:
self.real_wcs = galsim.FitsWCS(header=img_header)
self.chip_wcs = galsim.FitsWCS(header=img_header)
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):
img_global_pos = galsim.PositionD(global_x, global_y)
cel_pos = img.wcs.toWorld(img_global_pos)
realPos = img_real_wcs.toImage(cel_pos)
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,
exptime=150., fd_shear=None):
if nphotons_tot == None:
......@@ -139,29 +115,27 @@ class MockObject(object):
self.logger.error(e)
return 2, None
nphotons_sum = 0
photons_list = []
xmax, ymax = 0, 0
# (TEST) Galsim Parameters
# 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.real_wcs)
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
real_wcs_local = self.real_wcs.local(self.real_pos)
# Loop over all sub-bandpasses
for i in range(len(bandpass_list)):
bandpass = bandpass_list[i]
try:
......@@ -170,61 +144,42 @@ class MockObject(object):
print(e)
if self.logger:
self.logger.error(e)
# return False
continue
ratio = sub / full
if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot
else:
# return False
continue
nphotons_sum += nphotons
# nphotons_sum += 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)
star = galsim.DeltaFunction(gsparams=gsp)
star = star.withFlux(nphotons)
star = galsim.Convolve(psf, star)
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)
# star = galsim.DeltaFunction(gsparams=gsp)
# star = star.withFlux(nphotons)
# star = galsim.Convolve(psf, star)
star = psf.withFlux(nphotons)
chip.img[bounds] = stamp[bounds]
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
else:
# Return code 0: object photons missed this detector
stamp = star.drawImage(wcs=chip_wcs_local, offset=offset)
if np.sum(np.isnan(stamp.array)) > 0:
continue
stamp.setCenter(x_nominal, y_nominal)
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))
if self.logger:
self.logger.info("obj %s missed"%(self.id))
return 0, pos_shear
del photons_list
del stamp
return 1, pos_shear # Return code 1: draw sucesss
def addSLStoChipImage(self, sdp=None, chip=None, xOrderSigPlus=None, local_wcs=None):
......@@ -275,9 +230,69 @@ class MockObject(object):
del stamp
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,
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,
......@@ -299,7 +314,7 @@ class MockObject(object):
names=('WAVELENGTH', 'FLUX'))
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_nominal = int(np.floor(x + 0.5))
......@@ -308,29 +323,45 @@ class MockObject(object):
dy = y - y_nominal
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
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])
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]
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass,
folding_threshold=folding_threshold)
# 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)
star = galsim.DeltaFunction(gsparams=gsp)
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),
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
......@@ -345,12 +376,15 @@ class MockObject(object):
sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1,
ycenter=ycenter_p1, origin=origin_p1,
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],
isAlongY=0,
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]]
star_p2 = galsim.Image(subImg_p2)
......@@ -362,12 +396,15 @@ class MockObject(object):
sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2,
ycenter=ycenter_p2, origin=origin_p2,
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],
isAlongY=0,
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_p2
......@@ -375,23 +412,29 @@ class MockObject(object):
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
ycenter=y_nominal - 0, origin=origin_star,
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],
isAlongY=0,
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
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=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10,
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=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 psf
# del psf
return 1, pos_shear
def SNRestimate(self, img_obj, flux, noise_level=0.0, seed=31415):
......@@ -403,3 +446,88 @@ class MockObject(object):
sig_obj = np.std(stamp.array)
snr_obj = img_flux / sig_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):
sensitivity_beam = ysens
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)
modelf = zeros(product(beam_sh), dtype=float)
......@@ -239,7 +239,7 @@ class SpecDisperser(object):
# else:
# 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],
sensitivity_beam[nonz],
modelf, x0,
......
ObservationSim/MockObject/Stamp.py
View file @ edd720e6
import os, sys
import random
import numpy as np
import galsim
import astropy.constants as cons
from astropy.table import Table
from scipy import interpolate
import astropy.io.fits as fitsio
import galsim
import gc
from ObservationSim.MockObject.MockObject import MockObject
from ObservationSim.MockObject._util import magToFlux,VC_A
from ObservationSim.MockObject.SpecDisperser import SpecDisperser
from ObservationSim.MockObject._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, getABMAG,convolveGaussXorders
class Stamp(MockObject):
def __init__(self, param):
super().__init__(param)
def __init__(self, param, logger=None):
super().__init__(param, logger=logger)
def unload_SED(self):
"""(Test) free up SED memory
......@@ -35,9 +30,9 @@ class Stamp(MockObject):
self.logger.error(e)
return False
nphotons_sum = 0
photons_list = []
xmax, ymax = 0, 0
#nphotons_sum = 0
#photons_list = []
#xmax, ymax = 0, 0
if self.getMagFilter(filt) <= 15:
folding_threshold = 5.e-4
......@@ -46,7 +41,7 @@ class Stamp(MockObject):
gsp = galsim.GSParams(folding_threshold=folding_threshold)
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_nominal = int(np.floor(x + 0.5))
......@@ -55,72 +50,237 @@ class Stamp(MockObject):
dy = y - y_nominal
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)):
bandpass = bandpass_list[i]
try:
sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
except Exception as e:
print(e)
self.logger.error(e)
# return False
if self.logger:
self.logger.error(e)
continue
ratio = sub/full
if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot
else:
# return False
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)
_gal = self.param['image']
galIm = galsim.ImageF(_gal, scale=self.param['pixScale'])
gal = galsim.InterpolatedImage(galIm)
gal = gal.withFlux(nphotons)
#gal_shear = galsim.Shear(g1=g1, g2=g2)
#gal = gal.shear(gal_shear)
galImg= galsim.ImageF(_gal, scale=self.param['pixScale'])
gal_temp= galsim.InterpolatedImage(galImg)
gal_temp= gal_temp.shear(gal_shear)
gal_temp= gal_temp.withFlux(nphotons)
gal = galsim.Convolve(psf, gal)
if fd_shear is not None:
gal = gal.shear(fd_shear)
gal_temp= galsim.Convolve(psf, gal_temp)
stamp = gal.drawImage(wcs=real_wcs_local, method='phot', offset=self.offset, save_photons=True)
xmax = max(xmax, stamp.xmax - stamp.xmin)
ymax = max(ymax, stamp.ymax - stamp.ymin)
photons = stamp.photons
photons.x += x_nominal
photons.y += y_nominal
photons_list.append(photons)
del gal
if i == 0:
gal = gal_temp
else:
gal = gal + gal_temp
# 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)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
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]
is_updated = 1
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
del stamp
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
del stamp
gc.collect()
return True, pos_shear
# print(self.y_nominal, starImg.center.y, starImg.ymin)
# del psf
return 1, pos_shear
ObservationSim/MockObject/__init__.py
View file @ edd720e6
......@@ -4,5 +4,6 @@ from .CatalogBase import CatalogBase
from .Quasar import Quasar
from .Star import Star
from .Stamp import Stamp
from .FlatLED import FlatLED
# from .SkybackgroundMap import *
# from .CosmicRay import CosmicRay
ObservationSim/MockObject/_util.py
View file @ edd720e6
......@@ -571,4 +571,14 @@ def convolveGaussXorders(img=None, sigma = 1):
convImg = signal.fftconvolve(img, psf, mode='full', axes=None)
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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