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Commit 2c2dac03 authored by Fang Yuedong's avatar Fang Yuedong
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ObservationSim/ObservationSim.py deleted 100755 → 0
View file @ 4afd1181
import os
import numpy as np
import mpi4py.MPI as MPI
import galsim
import psutil
import gc
from datetime import datetime
import traceback
from ObservationSim.Config import ChipOutput
from ObservationSim.Instrument import Telescope, Filter, FilterParam, FocalPlane, Chip
from ObservationSim.Instrument.Chip import Effects
from ObservationSim.Instrument.Chip import ChipUtils as chip_utils
from ObservationSim.Astrometry.Astrometry_util import on_orbit_obs_position
from ObservationSim.sim_steps import SimSteps, SIM_STEP_TYPES
class Observation(object):
def __init__(self, config, Catalog, work_dir=None, data_dir=None):
self.config = config
self.tel = Telescope()
self.filter_param = FilterParam()
self.Catalog = Catalog
def prepare_chip_for_exposure(self, chip, ra_cen, dec_cen, pointing, wcs_fp=None):
# Get WCS for the focal plane
if wcs_fp == None:
wcs_fp = self.focal_plane.getTanWCS(ra_cen, dec_cen, pointing.img_pa, chip.pix_scale)
# Create chip Image
chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
chip.img.wcs = wcs_fp
# Get random generators for this chip
chip.rng_poisson, chip.poisson_noise = chip_utils.get_poisson(
seed=int(self.config["random_seeds"]["seed_poisson"]) + pointing.id*30 + chip.chipID, sky_level=0.)
# Get flat, shutter, and PRNU images
chip.flat_img, _ = chip_utils.get_flat(img=chip.img, seed=int(self.config["random_seeds"]["seed_flat"]))
if chip.chipID > 30:
chip.shutter_img = np.ones_like(chip.img.array)
else:
chip.shutter_img = Effects.ShutterEffectArr(chip.img, t_shutter=1.3, dist_bearing=735, dt=1E-3)
chip.prnu_img = Effects.PRNU_Img(xsize=chip.npix_x, ysize=chip.npix_y, sigma=0.01,
seed=int(self.config["random_seeds"]["seed_prnu"]+chip.chipID))
return chip
def run_one_chip(self, chip, filt, pointing, chip_output, wcs_fp=None, psf_model=None, cat_dir=None, sed_dir=None):
chip_output.Log_info(':::::::::::::::::::Current Pointing Information::::::::::::::::::')
chip_output.Log_info("RA: %f, DEC; %f" % (pointing.ra, pointing.dec))
chip_output.Log_info("Time: %s" % datetime.utcfromtimestamp(pointing.timestamp).isoformat())
chip_output.Log_info("Exposure time: %f" % pointing.exp_time)
chip_output.Log_info("Satellite Position (x, y, z): (%f, %f, %f)" % (pointing.sat_x, pointing.sat_y, pointing.sat_z))
chip_output.Log_info("Satellite Velocity (x, y, z): (%f, %f, %f)" % (pointing.sat_vx, pointing.sat_vy, pointing.sat_vz))
chip_output.Log_info("Position Angle: %f" % pointing.img_pa.deg)
chip_output.Log_info('Chip : %d' % chip.chipID)
chip_output.Log_info(':::::::::::::::::::::::::::END:::::::::::::::::::::::::::::::::::')
# Apply astrometric simulation for pointing
if self.config["obs_setting"]["enable_astrometric_model"]:
dt = datetime.utcfromtimestamp(pointing.timestamp)
date_str = dt.date().isoformat()
time_str = dt.time().isoformat()
ra_cen, dec_cen = on_orbit_obs_position(
input_ra_list=[pointing.ra],
input_dec_list=[pointing.dec],
input_pmra_list=[0.],
input_pmdec_list=[0.],
input_rv_list=[0.],
input_parallax_list=[1e-9],
input_nstars=1,
input_x=pointing.sat_x,
input_y=pointing.sat_y,
input_z=pointing.sat_z,
input_vx=pointing.sat_vx,
input_vy=pointing.sat_vy,
input_vz=pointing.sat_vz,
input_epoch="J2000",
input_date_str=date_str,
input_time_str=time_str
)
ra_cen, dec_cen = ra_cen[0], dec_cen[0]
else:
ra_cen = pointing.ra
dec_cen = pointing.dec
# Prepare necessary chip properties for simulation
chip = self.prepare_chip_for_exposure(chip, ra_cen, dec_cen, pointing)
# Initialize SimSteps
sim_steps = SimSteps(overall_config=self.config, chip_output=chip_output, all_filters=self.all_filters)
for step in pointing.obs_param["call_sequence"]:
if self.config["run_option"]["out_cat_only"]:
if step != "scie_obs":
continue
chip_output.Log_info("Starting simulation step: %s, calling function: %s"%(step, SIM_STEP_TYPES[step]))
obs_param = pointing.obs_param["call_sequence"][step]
step_name = SIM_STEP_TYPES[step]
try:
step_func = getattr(sim_steps, step_name)
chip, filt, tel, pointing = step_func(
chip=chip,
filt=filt,
tel=self.tel,
pointing=pointing,
catalog=self.Catalog,
obs_param=obs_param)
chip_output.Log_info("Finished simulation step: %s"%(step))
except Exception as e:
traceback.print_exc()
chip_output.Log_error(e)
chip_output.Log_error("Failed simulation on step: %s"%(step))
break
chip_output.Log_info("check running:1: pointing-%d chip-%d pid-%d memory-%6.2fGB"%(pointing.id, chip.chipID, os.getpid(), (psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024) ))
del chip.img
def runExposure_MPI_PointingList(self, pointing_list, chips=None):
comm = MPI.COMM_WORLD
ind_thread = comm.Get_rank()
num_thread = comm.Get_size()
process_counter = 0
for ipoint in range(len(pointing_list)):
# Construct chips & filters:
pointing = pointing_list[ipoint]
# pointing_ID = pointing.id
pointing_ID = pointing.obs_id
pointing.make_output_pointing_dir(overall_config=self.config, copy_obs_config=True)
self.focal_plane = FocalPlane(chip_list=pointing.obs_param["run_chips"])
# Make Chip & Filter lists
self.chip_list = []
self.filter_list = []
self.all_filters = []
for i in range(self.focal_plane.nchips):
chipID = i + 1
chip = Chip(chipID=chipID, config=self.config)
filter_id, filter_type = chip.getChipFilter()
filt = Filter(
filter_id=filter_id,
filter_type=filter_type,
filter_param=self.filter_param)
if not self.focal_plane.isIgnored(chipID=chipID):
self.chip_list.append(chip)
self.filter_list.append(filt)
self.all_filters.append(filt)
if chips is None:
# Run all chips defined in configuration of this pointing
run_chips = self.chip_list
run_filts = self.filter_list
nchips_per_fp = len(self.chip_list)
else:
# Only run a particular set of chips
run_chips = []
run_filts = []
for ichip in range(len(self.chip_list)):
chip = self.chip_list[ichip]
filt = self.filter_list[ichip]
if chip.chipID in chips:
run_chips.append(chip)
run_filts.append(filt)
nchips_per_fp = len(chips)
for ichip in range(nchips_per_fp):
i_process = process_counter + ichip
if i_process % num_thread != ind_thread:
continue
pid = os.getpid()
chip = run_chips[ichip]
filt = run_filts[ichip]
chip_output = ChipOutput(
config = self.config,
chip = chip,
filt = filt,
pointing = pointing
)
chip_output.Log_info("running pointing#%d, chip#%d, at PID#%d..."%(int(pointing_ID), chip.chipID, pid))
self.run_one_chip(
chip=chip,
filt=filt,
chip_output=chip_output,
pointing=pointing)
chip_output.Log_info("finished running chip#%d..."%(chip.chipID))
for handler in chip_output.logger.handlers[:]:
chip_output.logger.removeHandler(handler)
gc.collect()
process_counter += nchips_per_fp
ObservationSim/PSF/FieldDistortion.py deleted 100644 → 0
View file @ 4afd1181
import galsim
import numpy as np
import cmath
class FieldDistortion(object):
def __init__(self, chip, fdModel=None, fdModel_path=None, img_rot=0.):
if fdModel is None:
if hasattr(chip, 'fdModel'):
self.fdModel = chip.fdModel
elif fdModel_path is not None:
import pickle
with open(fdModel_path, "rb") as f:
self.fdModel = pickle.load(f)
else:
raise ValueError("Error: no field distortion model has been specified!")
else:
self.fdModel = fdModel
self.img_rot = img_rot
self.ifdModel = self.fdModel["wave1"]
self.ixfdModel = self.ifdModel["xImagePos"]
self.iyfdModel = self.ifdModel["yImagePos"]
# first-order derivatives of the global field distortion model
self.ifx_dx = self.ixfdModel.partial_derivative(1,0)
self.ifx_dy = self.ixfdModel.partial_derivative(0,1)
self.ify_dx = self.iyfdModel.partial_derivative(1,0)
self.ify_dy = self.iyfdModel.partial_derivative(0,1)
if "residual" in self.fdModel["wave1"]:
self.irsModel = self.fdModel["wave1"]["residual"]["ccd" + chip.getChipLabel(chipID=chip.chipID)]
self.ixrsModel = self.irsModel["xResidual"]
self.iyrsModel = self.irsModel["yResidual"]
# first-order derivatives of the residual field distortion model
self.irx_dx = self.ixrsModel.partial_derivative(1,0)
self.irx_dy = self.ixrsModel.partial_derivative(0,1)
self.iry_dx = self.iyrsModel.partial_derivative(1,0)
self.iry_dy = self.iyrsModel.partial_derivative(0,1)
else:
self.irsModel = None
def isContainObj_FD(self, chip, pos_img):
xLowI, xUpI, yLowI, yUpI = self.ifdModel["interpLimit"]
x, y = pos_img.x, pos_img.y
if (xLowI - x) * (xUpI - x) > 0 or (yLowI - y) * (yUpI - y) > 0:
return False
return True
def get_distorted(self, chip, pos_img, bandpass=None, img_rot=None):
""" Get the distored position for an undistorted image position
Parameters:
chip: A 'Chip' object representing the
chip we want to extract PSF from.
pos_img: A 'galsim.Position' object representing
the image position.
bandpass: A 'galsim.Bandpass' object representing
the wavelength range.
Returns:
pos_distorted: A 'galsim.Position' object representing
the distored position.
"""
if not self.isContainObj_FD(chip=chip, pos_img=pos_img):
return galsim.PositionD(-1, -1), None
if not img_rot:
img_rot = np.radians(self.img_rot)
else:
img_rot = np.radians(img_rot)
x, y = pos_img.x, pos_img.y
x = self.ixfdModel(x, y)[0][0]
y = self.iyfdModel(x, y)[0][0]
if self.irsModel:
# x1LowI, x1UpI, y1LowI, y1UpI = self.irsModel["interpLimit"]
# if (x1LowI-x)*(x1UpI-x) <=0 and (y1LowI-y)*(y1UpI-y)<=0:
# dx = self.ixrsModel(x, y)[0][0]
# dy = self.iyrsModel(x, y)[0][0]
# x += dx
# y += dy
# # field distortion induced ellipticity
# ix_dx = self.ifx_dx(x, y) + self.irx_dx(x, y)
# ix_dy = self.ifx_dy(x, y) + self.irx_dy(x, y)
# iy_dx = self.ify_dx(x, y) + self.iry_dx(x, y)
# iy_dy = self.ify_dy(x, y) + self.iry_dy(x, y)
# else:
# return galsim.PositionD(-1, -1), None
dx = self.ixrsModel(x, y)[0][0]
dy = self.iyrsModel(x, y)[0][0]
x += dx
y += dy
# field distortion induced ellipticity
ix_dx = self.ifx_dx(x, y) + self.irx_dx(x, y)
ix_dy = self.ifx_dy(x, y) + self.irx_dy(x, y)
iy_dx = self.ify_dx(x, y) + self.iry_dx(x, y)
iy_dy = self.ify_dy(x, y) + self.iry_dy(x, y)
else:
ix_dx = self.ifx_dx(x, y)
ix_dy = self.ifx_dy(x, y)
iy_dx = self.ify_dx(x, y)
iy_dy = self.ify_dy(x, y)
g1k_fd = 0.0 + (iy_dy - ix_dx) / (iy_dy + ix_dx)
g2k_fd = 0.0 - (iy_dx + ix_dy) / (iy_dy + ix_dx)
# [TODO] [TESTING] Rotate the shear:
g_abs = np.sqrt(g1k_fd**2 + g2k_fd**2)
phi = cmath.phase(complex(g1k_fd, g2k_fd))
# g_abs = 0.7
g1k_fd = g_abs * np.cos(phi + 2*img_rot)
g2k_fd = g_abs * np.sin(phi + 2*img_rot)
fd_shear = galsim.Shear(g1=g1k_fd, g2=g2k_fd)
return galsim.PositionD(x, y), fd_shear
ObservationSim/PSF/PSFGauss.py deleted 100644 → 0
View file @ 4afd1181
import galsim
import sep
import numpy as np
from scipy.interpolate import interp1d
from ObservationSim.PSF.PSFModel import PSFModel
class PSFGauss(PSFModel):
def __init__(self, chip, fwhm=0.187, sigSpin=0., psfRa=None):
self.pix_size = chip.pix_scale
self.chip = chip
if psfRa is None:
self.fwhm = fwhm
self.sigGauss = 0.15
else:
self.fwhm = self.fwhmGauss(r=psfRa)
self.sigGauss = psfRa # 80% light radius
self.sigSpin = sigSpin
self.psf = galsim.Gaussian(flux=1.0,fwhm=fwhm)
def perfGauss(self, r, sig):
"""
pseudo-error function, i.e. Cumulative distribution function of Gaussian distribution
Parameter:
r: radius
sig: sigma of the Gaussian distribution
Return:
the value of the pseudo CDF
"""
gaussFun = lambda sigma, r: 1.0/(np.sqrt(2.0*np.pi)*sigma) * np.exp(-r**2/(2.0*sigma**2))
nxx = 1000
rArr = np.linspace(0.0,r,nxx)
gauss = gaussFun(sig,rArr)
erf = 2.0*np.trapz(gauss,rArr)
return erf
def fracGauss(self, sig, r=0.15, pscale=None):
"""
For a given Gaussian PSF with sigma=sig,
derive the flux ratio ar the given radius r
Parameters:
sig: sigma of the Gauss PSF Function in arcsec
r: radius in arcsec
pscale: pixel scale
Return: the flux ratio
"""
if pscale == None:
pscale = self.pix_size
gaussx = galsim.Gaussian(flux=1.0,sigma=sig)
gaussImg = gaussx.drawImage(scale=pscale, method='no_pixel')
gaussImg = gaussImg.array
size = np.size(gaussImg,axis=0)
cxy = 0.5*(size-1)
flux, ferr, flag = sep.sum_circle(gaussImg,[cxy],[cxy],[r/pscale],subpix=0)
return flux
def fwhmGauss(self, r=0.15,fr=0.8,pscale=None):
"""
Given a total flux ratio 'fr' within a fixed radius 'r',
estimate the fwhm of the Gaussian function
return the fwhm in arcsec
"""
if pscale == None:
pscale = self.pix_size
err = 1.0e-3
nxx = 100
sig = np.linspace(0.5*pscale,1.0,nxx)
frA = np.zeros(nxx)
for i in range(nxx): frA[i] = self.fracGauss(sig[i],r=r,pscale=pscale)
index = [i for i in range(nxx-1) if (fr-frA[i])*(fr-frA[i+1])<=0.0][0]
while abs(frA[index]-fr)>1.0e-3:
sig = np.linspace(sig[index],sig[index+1],nxx)
for i in range(nxx): frA[i] = self.fracGauss(sig[i],r=r,pscale=pscale)
index = [i for i in range(nxx-1) if (fr-frA[i])*(fr-frA[i+1])<=0.0][0]
fwhm = 2.35482*sig[index]
return fwhm
def get_PSF(self, pos_img, chip=None, bandpass=None, folding_threshold=5.e-3):
dx = pos_img.x - self.chip.cen_pix_x
dy = pos_img.y - self.chip.cen_pix_y
return self.PSFspin(dx, dy)
def PSFspin(self, x, y):
"""
The PSF profile at a given image position relative to the axis center
Parameters:
theta : spin angles in a given exposure in unit of [arcsecond]
dx, dy: relative position to the axis center in unit of [pixels]
Return:
Spinned PSF: g1, g2 and axis ratio 'a/b'
"""
a2Rad = np.pi/(60.0*60.0*180.0)
ff = self.sigGauss * 0.107 * (1000.0/10.0) # in unit of [pixels]
rc = np.sqrt(x*x + y*y)
cpix = rc*(self.sigSpin*a2Rad)
beta = (np.arctan2(y,x) + np.pi/2)
ell = cpix**2/(2.0*ff**2+cpix**2)
#ell *= 10.0
qr = np.sqrt((1.0+ell)/(1.0-ell))
#psfShape = galsim.Shear(e=ell, beta=beta)
#g1, g2 = psfShape.g1, psfShape.g2
#qr = np.sqrt((1.0+ell)/(1.0-ell))
#return ell, beta, qr
PSFshear = galsim.Shear(e=ell, beta=beta*galsim.radians)
return self.psf.shear(PSFshear), PSFshear
\ No newline at end of file
ObservationSim/PSF/PSFInterp.py deleted 100644 → 0
View file @ 4afd1181
'''
PSF interpolation for CSST-Sim
NOTE: [iccd, iwave, ipsf] are counted from 1 to n, but [tccd, twave, tpsf] are counted from 0 to n-1
'''
import sys
import time
import copy
import numpy as np
import scipy.spatial as spatial
import galsim
import h5py
from ObservationSim.PSF.PSFModel import PSFModel
NPSF = 900 #***# 30*30
PixSizeInMicrons = 5. #***# in microns
###find neighbors-KDtree###
def findNeighbors(tx, ty, px, py, dr=0.1, dn=1, OnlyDistance=True):
"""
find nearest neighbors by 2D-KDTree
Parameters:
tx, ty (float, float): a given position
px, py (numpy.array, numpy.array): position data for tree
dr (float-optional): distance
dn (int-optional): nearest-N
OnlyDistance (bool-optional): only use distance to find neighbors. Default: True
Returns:
dataq (numpy.array): index
"""
datax = px
datay = py
tree = spatial.KDTree(list(zip(datax.ravel(), datay.ravel())))
dataq=[]
rr = dr
if OnlyDistance == True:
dataq = tree.query_ball_point([tx, ty], rr)
if OnlyDistance == False:
while len(dataq) < dn:
dataq = tree.query_ball_point([tx, ty], rr)
rr += dr
dd = np.hypot(datax[dataq]-tx, datay[dataq]-ty)
ddSortindx = np.argsort(dd)
dataq = np.array(dataq)[ddSortindx[0:dn]]
return dataq
###find neighbors-hoclist###
def hocBuild(partx, party, nhocx, nhocy, dhocx, dhocy):
if np.max(partx) > nhocx*dhocx:
print('ERROR')
sys.exit()
if np.max(party) > nhocy*dhocy:
print('ERROR')
sys.exit()
npart = partx.size
hoclist= np.zeros(npart, dtype=np.int32)-1
hoc = np.zeros([nhocy, nhocx], dtype=np.int32)-1
for ipart in range(npart):
ix = int(partx[ipart]/dhocx)
iy = int(party[ipart]/dhocy)
hoclist[ipart] = hoc[iy, ix]
hoc[iy, ix] = ipart
return hoc, hoclist
def hocFind(px, py, dhocx, dhocy, hoc, hoclist):
ix = int(px/dhocx)
iy = int(py/dhocy)
neigh=[]
it = hoc[iy, ix]
while it != -1:
neigh.append(it)
it = hoclist[it]
return neigh
def findNeighbors_hoclist(px, py, tx=None,ty=None, dn=4, hoc=None, hoclist=None):
nhocy = nhocx = 20
pxMin = np.min(px)
pxMax = np.max(px)
pyMin = np.min(py)
pyMax = np.max(py)
dhocx = (pxMax - pxMin)/(nhocx-1)
dhocy = (pyMax - pyMin)/(nhocy-1)
partx = px - pxMin +dhocx/2
party = py - pyMin +dhocy/2
if hoc is None:
hoc, hoclist = hocBuild(partx, party, nhocx, nhocy, dhocx, dhocy)
return hoc, hoclist
if hoc is not None:
tx = tx - pxMin +dhocx/2
ty = ty - pyMin +dhocy/2
itx = int(tx/dhocx)
ity = int(ty/dhocy)
ps = [-1, 0, 1]
neigh=[]
for ii in range(3):
for jj in range(3):
ix = itx + ps[ii]
iy = ity + ps[jj]
if ix < 0:
continue
if iy < 0:
continue
if ix > nhocx-1:
continue
if iy > nhocy-1:
continue
#neightt = myUtil.hocFind(ppx, ppy, dhocx, dhocy, hoc, hoclist)
it = hoc[iy, ix]
while it != -1:
neigh.append(it)
it = hoclist[it]
#neigh.append(neightt)
#ll = [i for k in neigh for i in k]
if dn != -1:
ptx = np.array(partx[neigh])
pty = np.array(party[neigh])
dd = np.hypot(ptx-tx, pty-ty)
idx = np.argsort(dd)
neigh= np.array(neigh)[idx[0:dn]]
return neigh
###PSF-IDW###
def psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, hoc=None, hoclist=None, PSFCentroidWgt=False):
"""
psf interpolation by IDW
Parameters:
px, py (float, float): position of the target
PSFMat (numpy.array): image
cen_col, cen_row (numpy.array, numpy.array): potions of the psf centers
IDWindex (int-optional): the power index of IDW
OnlyNeighbors (bool-optional): only neighbors are used for psf interpolation
Returns:
psfMaker (numpy.array)
"""
minimum_psf_weight = 1e-8
ref_col = px
ref_row = py
ngy, ngx = PSFMat[0, :, :].shape
npsf = PSFMat[:, :, :].shape[0]
psfWeight = np.zeros([npsf])
if OnlyNeighbors == True:
if hoc is None:
neigh = findNeighbors(px, py, cen_col, cen_row, dr=5., dn=4, OnlyDistance=False)
if hoc is not None:
neigh = findNeighbors_hoclist(cen_col, cen_row, tx=px,ty=py, dn=4, hoc=hoc, hoclist=hoclist)
neighFlag = np.zeros(npsf)
neighFlag[neigh] = 1
for ipsf in range(npsf):
if OnlyNeighbors == True:
if neighFlag[ipsf] != 1:
continue
dist = np.sqrt((ref_col - cen_col[ipsf])**2 + (ref_row - cen_row[ipsf])**2)
if IDWindex == 1:
psfWeight[ipsf] = dist
if IDWindex == 2:
psfWeight[ipsf] = dist**2
if IDWindex == 3:
psfWeight[ipsf] = dist**3
if IDWindex == 4:
psfWeight[ipsf] = dist**4
psfWeight[ipsf] = max(psfWeight[ipsf], minimum_psf_weight)
psfWeight[ipsf] = 1./psfWeight[ipsf]
psfWeight /= np.sum(psfWeight)
psfMaker = np.zeros([ngy, ngx], dtype=np.float32)
for ipsf in range(npsf):
if OnlyNeighbors == True:
if neighFlag[ipsf] != 1:
continue
iPSFMat = PSFMat[ipsf, :, :].copy()
ipsfWeight = psfWeight[ipsf]
psfMaker += iPSFMat * ipsfWeight
psfMaker /= np.nansum(psfMaker)
return psfMaker
###define PSFInterp###
class PSFInterp(PSFModel):
def __init__(self, chip, npsf=NPSF, PSF_data=None, PSF_data_file=None, PSF_data_prefix="", sigSpin=0, psfRa=0.15, HocBuild=False, LOG_DEBUG=False):
self.LOG_DEBUG = LOG_DEBUG
if self.LOG_DEBUG:
print('===================================================')
print('DEBUG: psf module for csstSim ' \
+time.strftime("(%Y-%m-%d %H:%M:%S)", time.localtime()), flush=True)
print('===================================================')
self.sigSpin = sigSpin
self.sigGauss = psfRa
self.iccd = int(chip.getChipLabel(chipID=chip.chipID))
# self.iccd = chip.chip_name
if PSF_data_file == None:
print('Error - PSF_data_file is None')
sys.exit()
self.nwave= self._getPSFwave(self.iccd, PSF_data_file, PSF_data_prefix)
self.npsf = npsf
self.PSF_data = self._loadPSF(self.iccd, PSF_data_file, PSF_data_prefix)
if self.LOG_DEBUG:
print('nwave-{:} on ccd-{:}::'.format(self.nwave, self.iccd), flush=True)
print('self.PSF_data ... ok', flush=True)
print('Preparing self.[psfMat,cen_col,cen_row] for psfMaker ... ', end='', flush=True)
ngy, ngx = self.PSF_data[0][0]['psfMat'].shape
self.psfMat = np.zeros([self.nwave, self.npsf, ngy, ngx], dtype=np.float32)
self.cen_col= np.zeros([self.nwave, self.npsf], dtype=np.float32)
self.cen_row= np.zeros([self.nwave, self.npsf], dtype=np.float32)
self.hoc =[]
self.hoclist=[]
for twave in range(self.nwave):
for tpsf in range(self.npsf):
self.psfMat[twave, tpsf, :, :] = self.PSF_data[twave][tpsf]['psfMat']
self.PSF_data[twave][tpsf]['psfMat'] = 0 ###free psfMat
self.pixsize = self.PSF_data[twave][tpsf]['pixsize']*1e-3 ##mm
self.cen_col[twave, tpsf] = self.PSF_data[twave][tpsf]['image_x'] + self.PSF_data[twave][tpsf]['centroid_x']
self.cen_row[twave, tpsf] = self.PSF_data[twave][tpsf]['image_y'] + self.PSF_data[twave][tpsf]['centroid_y']
if HocBuild:
#hoclist on twave for neighborsFinding
hoc,hoclist = findNeighbors_hoclist(self.cen_col[twave], self.cen_row[twave])
self.hoc.append(hoc)
self.hoclist.append(hoclist)
if self.LOG_DEBUG:
print('ok', flush=True)
def _getPSFwave(self, iccd, PSF_data_file, PSF_data_prefix):
# fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_ccd{:}.h5'.format(iccd), 'r')
fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_{:}.h5'.format(iccd), 'r')
nwave = len(fq.keys())
fq.close()
return nwave
def _loadPSF(self, iccd, PSF_data_file, PSF_data_prefix):
psfSet = []
# fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_ccd{:}.h5'.format(iccd), 'r')
fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_{:}.h5'.format(iccd), 'r')
for ii in range(self.nwave):
iwave = ii+1
psfWave = []
fq_iwave = fq['w_{:}'.format(iwave)]
for jj in range(self.npsf):
ipsf = jj+1
psfInfo = {}
psfInfo['wavelength']= fq_iwave['wavelength'][()]
fq_iwave_ipsf = fq_iwave['psf_{:}'.format(ipsf)]
psfInfo['pixsize'] = PixSizeInMicrons
psfInfo['field_x'] = fq_iwave_ipsf['field_x'][()]
psfInfo['field_y'] = fq_iwave_ipsf['field_y'][()]
psfInfo['image_x'] = fq_iwave_ipsf['image_x'][()]
psfInfo['image_y'] = fq_iwave_ipsf['image_y'][()]
psfInfo['centroid_x']= fq_iwave_ipsf['cx'][()]
psfInfo['centroid_y']= fq_iwave_ipsf['cy'][()]
psfInfo['psfMat'] = fq_iwave_ipsf['psfMat'][()]
psfWave.append(psfInfo)
psfSet.append(psfWave)
fq.close()
if self.LOG_DEBUG:
print('psfSet has been loaded:', flush=True)
print('psfSet[iwave][ipsf][keys]:', psfSet[0][0].keys(), flush=True)
return psfSet
def _findWave(self, bandpass):
if isinstance(bandpass,int):
twave = bandpass
return twave
for twave in range(self.nwave):
bandwave = self.PSF_data[twave][0]['wavelength']
if bandpass.blue_limit < bandwave and bandwave < bandpass.red_limit:
return twave
return -1
def get_PSF(self, chip, pos_img, bandpass, galsimGSObject=True, findNeighMode='treeFind', folding_threshold=5.e-3, pointing_pa=0.0):
"""
Get the PSF at a given image position
Parameters:
chip: A 'Chip' object representing the chip we want to extract PSF from.
pos_img: A 'galsim.Position' object representing the image position.
bandpass: A 'galsim.Bandpass' object representing the wavelength range.
pixSize: The pixels size of psf matrix
findNeighMode: 'treeFind' or 'hoclistFind'
Returns:
PSF: A 'galsim.GSObject'.
"""
pixSize = np.rad2deg(self.pixsize*1e-3/28)*3600 #set psf pixsize
# assert self.iccd == int(chip.getChipLabel(chipID=chip.chipID)), 'ERROR: self.iccd != chip.chipID'
twave = self._findWave(bandpass)
if twave == -1:
print("!!!PSF bandpass does not match.")
exit()
PSFMat = self.psfMat[twave]
cen_col= self.cen_col[twave]
cen_row= self.cen_row[twave]
px = (pos_img.x - chip.cen_pix_x)*0.01
py = (pos_img.y - chip.cen_pix_y)*0.01
if findNeighMode == 'treeFind':
imPSF = psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, PSFCentroidWgt=True)
if findNeighMode == 'hoclistFind':
assert(self.hoc != 0), 'hoclist should be built correctly!'
imPSF = psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, hoc=self.hoc[twave], hoclist=self.hoclist[twave], PSFCentroidWgt=True)
'''
############TEST: START
TestGaussian = False
if TestGaussian:
gsx = galsim.Gaussian(sigma=0.04)
#pointing_pa = -23.433333
imPSF= gsx.shear(g1=0.8, g2=0.).rotate(0.*galsim.degrees).drawImage(nx = 256, ny=256, scale=pixSize).array
############TEST: END
'''
if galsimGSObject:
imPSFt = np.zeros([257,257])
imPSFt[0:256, 0:256] = imPSF
# imPSFt[120:130, 0:256] = 1.
img = galsim.ImageF(imPSFt, scale=pixSize)
gsp = galsim.GSParams(folding_threshold=folding_threshold)
############TEST: START
# Use sheared PSF to test the PSF orientation
# self.psf = galsim.InterpolatedImage(img, gsparams=gsp).shear(g1=0.8, g2=0.)
############TEST: END
self.psf = galsim.InterpolatedImage(img, gsparams=gsp)
wcs = chip.img.wcs.local(pos_img)
scale = galsim.PixelScale(0.074)
self.psf = wcs.toWorld(scale.toImage(self.psf), image_pos=(pos_img))
# return self.PSFspin(x=px/0.01, y=py/0.01)
return self.psf, galsim.Shear(e=0., beta=(np.pi/2)*galsim.radians)
return imPSF
'''
def PSFspin(self, x, y):
"""
The PSF profile at a given image position relative to the axis center
Parameters:
theta : spin angles in a given exposure in unit of [arcsecond]
dx, dy: relative position to the axis center in unit of [pixels]
Return:
Spinned PSF: g1, g2 and axis ratio 'a/b'
"""
a2Rad = np.pi/(60.0*60.0*180.0)
ff = self.sigGauss * 0.107 * (1000.0/10.0) # in unit of [pixels]
rc = np.sqrt(x*x + y*y)
cpix = rc*(self.sigSpin*a2Rad)
beta = (np.arctan2(y,x) + np.pi/2)
ell = cpix**2/(2.0*ff**2+cpix**2)
qr = np.sqrt((1.0+ell)/(1.0-ell))
PSFshear = galsim.Shear(e=ell, beta=beta*galsim.radians)
return self.psf.shear(PSFshear), PSFshear
'''
ObservationSim/PSF/PSFInterpSLS.py deleted 100644 → 0
View file @ 4afd1181
'''
PSF interpolation for CSST-Sim
NOTE: [iccd, iwave, ipsf] are counted from 1 to n, but [tccd, twave, tpsf] are counted from 0 to n-1
'''
import sys
import time
import copy
import numpy as np
import scipy.spatial as spatial
import galsim
import h5py
from ObservationSim.PSF.PSFModel import PSFModel
from ObservationSim.Instrument.Chip import ChipUtils as chip_utils
import os
from astropy.io import fits
from astropy.modeling.models import Gaussian2D
from scipy import signal
LOG_DEBUG = False #***#
NPSF = 900 #***# 30*30
PixSizeInMicrons = 5. #***# in microns
###find neighbors-KDtree###
# def findNeighbors(tx, ty, px, py, dr=0.1, dn=1, OnlyDistance=True):
# """
# find nearest neighbors by 2D-KDTree
#
# Parameters:
# tx, ty (float, float): a given position
# px, py (numpy.array, numpy.array): position data for tree
# dr (float-optional): distance
# dn (int-optional): nearest-N
# OnlyDistance (bool-optional): only use distance to find neighbors. Default: True
#
# Returns:
# dataq (numpy.array): index
# """
# datax = px
# datay = py
# tree = spatial.KDTree(list(zip(datax.ravel(), datay.ravel())))
#
# dataq=[]
# rr = dr
# if OnlyDistance == True:
# dataq = tree.query_ball_point([tx, ty], rr)
# if OnlyDistance == False:
# while len(dataq) < dn:
# dataq = tree.query_ball_point([tx, ty], rr)
# rr += dr
# dd = np.hypot(datax[dataq]-tx, datay[dataq]-ty)
# ddSortindx = np.argsort(dd)
# dataq = np.array(dataq)[ddSortindx[0:dn]]
# return dataq
#
# ###find neighbors-hoclist###
# def hocBuild(partx, party, nhocx, nhocy, dhocx, dhocy):
# if np.max(partx) > nhocx*dhocx:
# print('ERROR')
# sys.exit()
# if np.max(party) > nhocy*dhocy:
# print('ERROR')
# sys.exit()
#
# npart = partx.size
# hoclist= np.zeros(npart, dtype=np.int32)-1
# hoc = np.zeros([nhocy, nhocx], dtype=np.int32)-1
# for ipart in range(npart):
# ix = int(partx[ipart]/dhocx)
# iy = int(party[ipart]/dhocy)
# hoclist[ipart] = hoc[iy, ix]
# hoc[iy, ix] = ipart
# return hoc, hoclist
#
# def hocFind(px, py, dhocx, dhocy, hoc, hoclist):
# ix = int(px/dhocx)
# iy = int(py/dhocy)
#
# neigh=[]
# it = hoc[iy, ix]
# while it != -1:
# neigh.append(it)
# it = hoclist[it]
# return neigh
#
# def findNeighbors_hoclist(px, py, tx=None,ty=None, dn=4, hoc=None, hoclist=None):
# nhocy = nhocx = 20
#
# pxMin = np.min(px)
# pxMax = np.max(px)
# pyMin = np.min(py)
# pyMax = np.max(py)
#
# dhocx = (pxMax - pxMin)/(nhocx-1)
# dhocy = (pyMax - pyMin)/(nhocy-1)
# partx = px - pxMin +dhocx/2
# party = py - pyMin +dhocy/2
#
# if hoc is None:
# hoc, hoclist = hocBuild(partx, party, nhocx, nhocy, dhocx, dhocy)
# return hoc, hoclist
#
# if hoc is not None:
# tx = tx - pxMin +dhocx/2
# ty = ty - pyMin +dhocy/2
# itx = int(tx/dhocx)
# ity = int(ty/dhocy)
#
# ps = [-1, 0, 1]
# neigh=[]
# for ii in range(3):
# for jj in range(3):
# ix = itx + ps[ii]
# iy = ity + ps[jj]
# if ix < 0:
# continue
# if iy < 0:
# continue
# if ix > nhocx-1:
# continue
# if iy > nhocy-1:
# continue
#
# #neightt = myUtil.hocFind(ppx, ppy, dhocx, dhocy, hoc, hoclist)
# it = hoc[iy, ix]
# while it != -1:
# neigh.append(it)
# it = hoclist[it]
# #neigh.append(neightt)
# #ll = [i for k in neigh for i in k]
# if dn != -1:
# ptx = np.array(partx[neigh])
# pty = np.array(party[neigh])
# dd = np.hypot(ptx-tx, pty-ty)
# idx = np.argsort(dd)
# neigh= np.array(neigh)[idx[0:dn]]
# return neigh
#
#
# ###PSF-IDW###
# def psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, hoc=None, hoclist=None, PSFCentroidWgt=False):
# """
# psf interpolation by IDW
#
# Parameters:
# px, py (float, float): position of the target
# PSFMat (numpy.array): image
# cen_col, cen_row (numpy.array, numpy.array): potions of the psf centers
# IDWindex (int-optional): the power index of IDW
# OnlyNeighbors (bool-optional): only neighbors are used for psf interpolation
#
# Returns:
# psfMaker (numpy.array)
# """
#
# minimum_psf_weight = 1e-8
# ref_col = px
# ref_row = py
#
# ngy, ngx = PSFMat[0, :, :].shape
# npsf = PSFMat[:, :, :].shape[0]
# psfWeight = np.zeros([npsf])
#
# if OnlyNeighbors == True:
# if hoc is None:
# neigh = findNeighbors(px, py, cen_col, cen_row, dr=5., dn=4, OnlyDistance=False)
# if hoc is not None:
# neigh = findNeighbors_hoclist(cen_col, cen_row, tx=px,ty=py, dn=4, hoc=hoc, hoclist=hoclist)
#
# neighFlag = np.zeros(npsf)
# neighFlag[neigh] = 1
#
# for ipsf in range(npsf):
# if OnlyNeighbors == True:
# if neighFlag[ipsf] != 1:
# continue
#
# dist = np.sqrt((ref_col - cen_col[ipsf])**2 + (ref_row - cen_row[ipsf])**2)
# if IDWindex == 1:
# psfWeight[ipsf] = dist
# if IDWindex == 2:
# psfWeight[ipsf] = dist**2
# if IDWindex == 3:
# psfWeight[ipsf] = dist**3
# if IDWindex == 4:
# psfWeight[ipsf] = dist**4
# psfWeight[ipsf] = max(psfWeight[ipsf], minimum_psf_weight)
# psfWeight[ipsf] = 1./psfWeight[ipsf]
# psfWeight /= np.sum(psfWeight)
#
# psfMaker = np.zeros([ngy, ngx], dtype=np.float32)
# for ipsf in range(npsf):
# if OnlyNeighbors == True:
# if neighFlag[ipsf] != 1:
# continue
#
# iPSFMat = PSFMat[ipsf, :, :].copy()
# ipsfWeight = psfWeight[ipsf]
#
# psfMaker += iPSFMat * ipsfWeight
# psfMaker /= np.nansum(psfMaker)
#
# return psfMaker
###define PSFInterp###
class PSFInterpSLS(PSFModel):
def __init__(self, chip, filt,PSF_data_prefix="", sigSpin=0, psfRa=0.15, pix_size = 0.005):
if LOG_DEBUG:
print('===================================================')
print('DEBUG: psf module for csstSim ' \
+time.strftime("(%Y-%m-%d %H:%M:%S)", time.localtime()), flush=True)
print('===================================================')
self.sigSpin = sigSpin
self.sigGauss = psfRa
self.grating_ids = chip_utils.getChipSLSGratingID(chip.chipID)
_,self.grating_type = chip.getChipFilter(chipID=chip.chipID)
self.data_folder = PSF_data_prefix
self.getPSFDataFromFile(filt)
self.pixsize = pix_size # um
def getPSFDataFromFile(self, filt):
gratingInwavelist = {'GU':0,'GV':1,'GI':2}
grating_orders = ['0','1']
waveListFn = self.data_folder + '/wavelist.dat'
wavelists = np.loadtxt(waveListFn)
self.waveList = wavelists[:,gratingInwavelist[self.grating_type]]
bandranges = np.zeros([4,2])
midBand = (self.waveList[0:3] + self.waveList[1:4])/2.*10000.
bandranges[0,0] = filt.blue_limit
bandranges[1:4,0] = midBand
bandranges[0:3, 1] = midBand
bandranges[3,1] = filt.red_limit
self.bandranges = bandranges
self.grating1_data = {}
g_folder = self.data_folder + '/' + self.grating_ids[0] + '/'
for g_order in grating_orders:
g_folder_order = g_folder + 'PSF_Order_' + g_order + '/'
grating_order_data = {}
for bandi in [1,2,3,4]:
subBand_data = {}
subBand_data['bandrange'] = bandranges[bandi-1]
final_folder = g_folder_order + str(bandi) + '/'
print(final_folder)
pca_fs = os.listdir(final_folder)
for fname in pca_fs:
if ('_PCs.fits' in fname) and (fname[0] != '.'):
fname_ = final_folder + fname
hdu = fits.open(fname_)
subBand_data['band_data'] = hdu
grating_order_data['band'+str(bandi)] = subBand_data
self.grating1_data['order'+g_order] = grating_order_data
self.grating2_data = {}
g_folder = self.data_folder + '/' + self.grating_ids[1] + '/'
for g_order in grating_orders:
g_folder_order = g_folder + 'PSF_Order_' + g_order + '/'
grating_order_data = {}
for bandi in [1, 2, 3, 4]:
subBand_data = {}
subBand_data['bandrange'] = bandranges[bandi - 1]
final_folder = g_folder_order + str(bandi) + '/'
print(final_folder)
pca_fs = os.listdir(final_folder)
for fname in pca_fs:
if ('_PCs.fits' in fname) and (fname[0] != '.'):
fname_ = final_folder + fname
hdu = fits.open(fname_)
subBand_data['band_data'] = hdu
grating_order_data['band' + str(bandi)] = subBand_data
self.grating2_data['order' + g_order] = grating_order_data
#
#
#
# def _getPSFwave(self, iccd, PSF_data_file, PSF_data_prefix):
# # fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_ccd{:}.h5'.format(iccd), 'r')
# fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_{:}.h5'.format(iccd), 'r')
# nwave = len(fq.keys())
# fq.close()
# return nwave
#
#
# def _loadPSF(self, iccd, PSF_data_file, PSF_data_prefix):
# psfSet = []
# # fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_ccd{:}.h5'.format(iccd), 'r')
# fq = h5py.File(PSF_data_file+'/' +PSF_data_prefix +'psfCube_{:}.h5'.format(iccd), 'r')
# for ii in range(self.nwave):
# iwave = ii+1
# psfWave = []
#
# fq_iwave = fq['w_{:}'.format(iwave)]
# for jj in range(self.npsf):
# ipsf = jj+1
# psfInfo = {}
# psfInfo['wavelength']= fq_iwave['wavelength'][()]
#
# fq_iwave_ipsf = fq_iwave['psf_{:}'.format(ipsf)]
# psfInfo['pixsize'] = PixSizeInMicrons
# psfInfo['field_x'] = fq_iwave_ipsf['field_x'][()]
# psfInfo['field_y'] = fq_iwave_ipsf['field_y'][()]
# psfInfo['image_x'] = fq_iwave_ipsf['image_x'][()]
# psfInfo['image_y'] = fq_iwave_ipsf['image_y'][()]
# psfInfo['centroid_x']= fq_iwave_ipsf['cx'][()]
# psfInfo['centroid_y']= fq_iwave_ipsf['cy'][()]
# psfInfo['psfMat'] = fq_iwave_ipsf['psfMat'][()]
#
# psfWave.append(psfInfo)
# psfSet.append(psfWave)
# fq.close()
#
# if LOG_DEBUG:
# print('psfSet has been loaded:', flush=True)
# print('psfSet[iwave][ipsf][keys]:', psfSet[0][0].keys(), flush=True)
# return psfSet
#
#
# def _findWave(self, bandpass):
# if isinstance(bandpass,int):
# twave = bandpass
# return twave
#
# for twave in range(self.nwave):
# bandwave = self.PSF_data[twave][0]['wavelength']
# if bandpass.blue_limit < bandwave and bandwave < bandpass.red_limit:
# return twave
# return -1
#
#
def convolveWithGauss(self, img=None, sigma=1):
offset = int(np.ceil(sigma * 3))
g_size = 2 * offset + 1
m_cen = int(g_size / 2)
print('-----',g_size)
g_PSF_ = Gaussian2D(1, m_cen, m_cen, sigma, sigma)
yp, xp = np.mgrid[0:g_size, 0:g_size]
g_PSF = g_PSF_(xp, yp)
psf = g_PSF / g_PSF.sum()
convImg = signal.fftconvolve(img, psf, mode='full', axes=None)
convImg = convImg/np.sum(convImg)
return convImg
def get_PSF(self, chip, pos_img_local = [1000,1000], bandNo = 1, galsimGSObject=True, folding_threshold=5.e-3, g_order = 'A', grating_split_pos=3685):
"""
Get the PSF at a given image position
Parameters:
chip: A 'Chip' object representing the chip we want to extract PSF from.
pos_img: A 'galsim.Position' object representing the image position.
bandpass: A 'galsim.Bandpass' object representing the wavelength range.
pixSize: The pixels size of psf matrix
findNeighMode: 'treeFind' or 'hoclistFind'
Returns:
PSF: A 'galsim.GSObject'.
"""
order_IDs = {'A': '1', 'B': '0' ,'C': '0', 'D': '0', 'E': '0'}
contam_order_sigma = {'C':0.28032344707964174,'D':0.39900182912061344,'E':1.1988309797685412} #arcsec
x_start = chip.x_cen/chip.pix_size - chip.npix_x / 2.
y_start = chip.y_cen/chip.pix_size - chip.npix_y / 2.
# print(pos_img.x - x_start)
pos_img_x = pos_img_local[0] + x_start
pos_img_y = pos_img_local[1] + y_start
pos_img = galsim.PositionD(pos_img_x, pos_img_y)
if pos_img_local[0] < grating_split_pos:
psf_data = self.grating1_data
else:
psf_data = self.grating2_data
grating_order = order_IDs[g_order]
# if grating_order in ['-2','-1','2']:
# grating_order = '1'
# if grating_order in ['0', '1']:
psf_order = psf_data['order'+grating_order]
psf_order_b = psf_order['band'+str(bandNo)]
psf_b_dat = psf_order_b['band_data']
pos_p = psf_b_dat[1].data
pc_coeff = psf_b_dat[2].data
pcs = psf_b_dat[0].data
# print(max(pos_p[:,0]), min(pos_p[:,0]),max(pos_p[:,1]), min(pos_p[:,1]))
# print(chip.x_cen, chip.y_cen)
# print(pos_p)
px = pos_img.x*chip.pix_size
py = pos_img.y*chip.pix_size
dist2=(pos_p[:,1] - px)*(pos_p[:,1] - px) + (pos_p[:,0] - py)*(pos_p[:,0] - py)
temp_sort_dist = np.zeros([dist2.shape[0],2])
temp_sort_dist[:, 0] = np.arange(0, dist2.shape[0],1)
temp_sort_dist[:, 1] = dist2
# print(temp_sort_dist)
dits2_sortlist = sorted(temp_sort_dist, key=lambda x:x[1])
# print(dits2_sortlist)
nearest4p = np.zeros([4,2])
pc_coeff_4p = np.zeros([pc_coeff.data.shape[0],4])
for i in np.arange(4):
smaller_ids = int(dits2_sortlist[i][0])
nearest4p[i, 0] = pos_p[smaller_ids, 1]
nearest4p[i, 1] = pos_p[smaller_ids, 0]
pc_coeff_4p[:,i] = pc_coeff[:,smaller_ids]
idw_dist = 1/(np.sqrt((px-nearest4p[:,0]) * (px-nearest4p[:,0]) + (py-nearest4p[:,1]) * (py-nearest4p[:,1])))
coeff_int = np.zeros(pc_coeff.data.shape[0])
for i in np.arange(4):
coeff_int = coeff_int + pc_coeff_4p[:,i]*idw_dist[i]
coeff_int = coeff_int / np.sum(coeff_int)
npc = 10
m_size = int(pcs.shape[0]**0.5)
PSF_int = np.dot(pcs[:,0:npc],coeff_int[0:npc]).reshape(m_size,m_size)
# PSF_int = PSF_int/np.sum(PSF_int)
PSF_int_trans = np.flipud(np.fliplr(PSF_int))
PSF_int_trans = np.fliplr(PSF_int_trans.T)
# PSF_int_trans = np.abs(PSF_int_trans)
# ids_szero = PSF_int_trans<0
# PSF_int_trans[ids_szero] = 0
# print(PSF_int_trans[ids_szero].shape[0],PSF_int_trans.shape)
PSF_int_trans = PSF_int_trans/np.sum(PSF_int_trans)
# from astropy.io import fits
# fits.writeto(str(bandNo) + '_' + g_order+ '_psf_o.fits', PSF_int_trans)
# if g_order in ['C','D','E']:
# g_simgma = contam_order_sigma[g_order]/pixel_size_arc
# PSF_int_trans = self.convolveWithGauss(PSF_int_trans,g_simgma)
# n_m_size = int(m_size/2)
#
# n_PSF_int = np.zeros([n_m_size, n_m_size])
#
# for i in np.arange(n_m_size):
# for j in np.arange(n_m_size):
# n_PSF_int[i,j] = np.sum(PSF_int[2*i:2*i+2, 2*j:2*j+2])
#
# n_PSF_int = n_PSF_int/np.sum(n_PSF_int)
# chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
# chip.img.wcs = galsim.wcs.AffineTransform
if galsimGSObject:
# imPSFt = np.zeros([257,257])
# imPSFt[0:256, 0:256] = imPSF
# # imPSFt[120:130, 0:256] = 1.
pixel_size_arc = np.rad2deg(self.pixsize * 1e-3 / 28) * 3600
img = galsim.ImageF(PSF_int_trans, scale=pixel_size_arc)
gsp = galsim.GSParams(folding_threshold=folding_threshold)
############TEST: START
# Use sheared PSF to test the PSF orientation
# self.psf = galsim.InterpolatedImage(img, gsparams=gsp).shear(g1=0.8, g2=0.)
############TEST: END
self.psf = galsim.InterpolatedImage(img, gsparams=gsp)
# if g_order in ['C','D','E']:
# add_psf = galsim.Gaussian(sigma=contam_order_sigma[g_order], flux=1.0)
# self.psf = galsim.Convolve(self.psf, add_psf)
wcs = chip.img.wcs.local(pos_img)
scale = galsim.PixelScale(0.074)
self.psf = wcs.toWorld(scale.toImage(self.psf), image_pos=(pos_img))
# return self.PSFspin(x=px/0.01, y=py/0.01)
return self.psf, galsim.Shear(e=0., beta=(np.pi/2)*galsim.radians)
return PSF_int_trans, PSF_int
# pixSize = np.rad2deg(self.pixsize*1e-3/28)*3600 #set psf pixsize
#
# # assert self.iccd == int(chip.getChipLabel(chipID=chip.chipID)), 'ERROR: self.iccd != chip.chipID'
# twave = self._findWave(bandpass)
# if twave == -1:
# print("!!!PSF bandpass does not match.")
# exit()
# PSFMat = self.psfMat[twave]
# cen_col= self.cen_col[twave]
# cen_row= self.cen_row[twave]
#
# px = (pos_img.x - chip.cen_pix_x)*0.01
# py = (pos_img.y - chip.cen_pix_y)*0.01
# if findNeighMode == 'treeFind':
# imPSF = psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, PSFCentroidWgt=True)
# if findNeighMode == 'hoclistFind':
# assert(self.hoc != 0), 'hoclist should be built correctly!'
# imPSF = psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, hoc=self.hoc[twave], hoclist=self.hoclist[twave], PSFCentroidWgt=True)
#
# ############TEST: START
# TestGaussian = False
# if TestGaussian:
# gsx = galsim.Gaussian(sigma=0.04)
# #pointing_pa = -23.433333
# imPSF= gsx.shear(g1=0.8, g2=0.).rotate(0.*galsim.degrees).drawImage(nx = 256, ny=256, scale=pixSize).array
# ############TEST: END
#
# if galsimGSObject:
# imPSFt = np.zeros([257,257])
# imPSFt[0:256, 0:256] = imPSF
# # imPSFt[120:130, 0:256] = 1.
#
# img = galsim.ImageF(imPSFt, scale=pixSize)
# gsp = galsim.GSParams(folding_threshold=folding_threshold)
# ############TEST: START
# # Use sheared PSF to test the PSF orientation
# # self.psf = galsim.InterpolatedImage(img, gsparams=gsp).shear(g1=0.8, g2=0.)
# ############TEST: END
# self.psf = galsim.InterpolatedImage(img, gsparams=gsp)
# wcs = chip.img.wcs.local(pos_img)
# scale = galsim.PixelScale(0.074)
# self.psf = wcs.toWorld(scale.toImage(self.psf), image_pos=(pos_img))
#
# # return self.PSFspin(x=px/0.01, y=py/0.01)
# return self.psf, galsim.Shear(e=0., beta=(np.pi/2)*galsim.radians)
# return imPSF
#
# def PSFspin(self, x, y):
# """
# The PSF profile at a given image position relative to the axis center
#
# Parameters:
# theta : spin angles in a given exposure in unit of [arcsecond]
# dx, dy: relative position to the axis center in unit of [pixels]
#
# Return:
# Spinned PSF: g1, g2 and axis ratio 'a/b'
# """
# a2Rad = np.pi/(60.0*60.0*180.0)
#
# ff = self.sigGauss * 0.107 * (1000.0/10.0) # in unit of [pixels]
# rc = np.sqrt(x*x + y*y)
# cpix = rc*(self.sigSpin*a2Rad)
#
# beta = (np.arctan2(y,x) + np.pi/2)
# ell = cpix**2/(2.0*ff**2+cpix**2)
# qr = np.sqrt((1.0+ell)/(1.0-ell))
# PSFshear = galsim.Shear(e=ell, beta=beta*galsim.radians)
# return self.psf.shear(PSFshear), PSFshear
from ObservationSim.Instrument import Filter, FilterParam, Chip
import yaml
if __name__ == '__main__':
configfn = '/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_new_sim/csst-simulation/config/config_C6_dev.yaml'
with open(configfn, "r") as stream:
try:
config = yaml.safe_load(stream)
for key, value in config.items():
print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
chip = Chip(chipID=1,config=config)
filter_id, filter_type = chip.getChipFilter()
filt = Filter(filter_id=filter_id,
filter_type=filter_type,
filter_param=FilterParam())
psf_i = PSFInterpSLS(chip, filt,PSF_data_prefix="/Volumes/EAGET/CSST_PSF_data/SLS_PSF_PCA_fp/")
pos_img = galsim.PositionD(x=25155, y=-22060)
psf_im = psf_i.get_PSF(chip, pos_img = pos_img, g_order = '1')
ObservationSim/PSF/PSFModel.py deleted 100755 → 0
View file @ 4afd1181
import galsim
import sep
import numpy as np
from scipy.interpolate import interp1d
import pylab as pl
import os, sys
class PSFModel(object):
def __init__(self, sigSpin=0., psfRa=0.15):
# TODO: what are the nesseary fields in PSFModel class?
pass
def PSFspin(self, psf, sigSpin, sigGauss, dx, dy):
"""
The PSF profile at a given image position relative to the axis center
Parameters:
theta : spin angles in a given exposure in unit of [arcsecond]
dx, dy: relative position to the axis center in unit of [pixels]
Return:
Spinned PSF: g1, g2 and axis ratio 'a/b'
"""
a2Rad = np.pi/(60.0*60.0*180.0)
ff = sigGauss * 0.107 * (1000.0/10.0) # in unit of [pixels]
rc = np.sqrt(dx*dx + dy*dy)
cpix = rc*(sigSpin*a2Rad)
beta = (np.arctan2(dy,dx) + np.pi/2)
ell = cpix**2/(2.0*ff**2+cpix**2)
#ell *= 10.0
qr = np.sqrt((1.0+ell)/(1.0-ell))
#psfShape = galsim.Shear(e=ell, beta=beta)
#g1, g2 = psfShape.g1, psfShape.g2
#qr = np.sqrt((1.0+ell)/(1.0-ell))
#return ell, beta, qr
PSFshear = galsim.Shear(e=ell, beta=beta*galsim.radians)
return psf.shear(PSFshear), PSFshear
\ No newline at end of file
ObservationSim/PSF/__init__.py deleted 100755 → 0
View file @ 4afd1181
from .PSFModel import PSFModel
from .PSFGauss import PSFGauss
# from .PSFInterp.PSFInterp import PSFInterp
from .PSFInterp import PSFInterp
from .PSFInterpSLS import PSFInterpSLS
from .FieldDistortion import FieldDistortion
\ No newline at end of file
ObservationSim/Straylight/SkybackgroundMap.py deleted 100644 → 0
View file @ 4afd1181
from ObservationSim.MockObject.SpecDisperser import SpecDisperser
from ObservationSim.MockObject.SpecDisperser import rotate90
import galsim
import numpy as np
from astropy.table import Table
from scipy import interpolate
import galsim
import astropy.constants as cons
import os
import time
try:
import importlib.resources as pkg_resources
except ImportError:
# Try backported to PY<37 'importlib_resources'
import importlib_resources as pkg_resources
###calculate sky map by sky SED
def calculateSkyMap_split_g(skyMap=None, blueLimit=4200, redLimit=6500, skyfn='sky_emiss_hubble_50_50_A.dat', conf=[''], pixelSize=0.074, isAlongY=0,
split_pos=3685, flat_cube = None, zoldial_spec = None):
# skyMap = np.ones([yLen, xLen], dtype='float32')
#
# if isAlongY == 1:
# skyMap = np.ones([xLen, yLen], dtype='float32')
# for i in range(len(conf)):
# conf[i] = os.path.join(SLSSIM_PATH, conf[i])
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)
try:
with pkg_resources.files('ObservationSim.Straylight.data.sky').joinpath(skyfn) as data_path:
skySpec = np.loadtxt(data_path)
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.data.sky', skyfn) as data_path:
skySpec = np.loadtxt(data_path)
# skySpec = np.loadtxt(skyfn)
spec = Table(np.array([skySpec[:, 0], skySpec[:, 1]]).T, names=('WAVELENGTH', 'FLUX'))
if zoldial_spec is not None:
deltL = 0.5
lamb = np.arange(2000, 11000, deltL)
speci = interpolate.interp1d(zoldial_spec['WAVELENGTH'], zoldial_spec['FLUX'])
y = speci(lamb)
# erg/s/cm2/A --> photo/s/m2/A
s_flux = y * lamb / (cons.h.value * cons.c.value) * 1e-13
spec = Table(np.array([lamb, s_flux]).T, names=('WAVELENGTH', 'FLUX'))
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, ignoreBeam=['D','E'])
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]
# sdp = SpecDisperser(orig_img=skyImg1, xcenter=skyImg1.center.x, ycenter=skyImg1.center.y, origin=origin1,
# tar_spec=spec,
# band_start=tbstart, band_end=tbend,
# conf=conf2,
# flat_cube=flat_cube, ignoreBeam=['D','E'])
#
# 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:
# skyImg1 = galsim.Image(skyImg.array[:, 0:split_pos])
# origin1 = [0, 0]
# skyImg2 = galsim.Image(skyImg.array[:, split_pos:])
# origin2 = [0, split_pos]
# 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 = 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
def calculateSkyMap(xLen=9232, yLen=9126, blueLimit=4200, redLimit=6500,
skyfn='sky_emiss_hubble_50_50_A.dat', conf='', pixelSize=0.074, isAlongY=0):
skyMap = np.ones([yLen, xLen], dtype='float32')
if isAlongY == 1:
skyMap = np.ones([xLen, yLen], dtype='float32')
skyImg = galsim.Image(skyMap)
tbstart = blueLimit
tbend = redLimit
fimg = np.zeros_like(skyMap)
fImg = galsim.Image(fimg)
try:
with pkg_resources.files('ObservationSim.Straylight.data.sky').joinpath(skyfn) as data_path:
skySpec = np.loadtxt(data_path)
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.data.sky', skyfn) as data_path:
skySpec = np.loadtxt(data_path)
# skySpec = np.loadtxt(skyfn)
spec = Table(np.array([skySpec[:, 0], skySpec[:, 1]]).T, names=('WAVELENGTH', 'FLUX'))
sdp = SpecDisperser(orig_img=skyImg, xcenter=skyImg.center.x, ycenter=skyImg.center.y, origin=[1, 1],
tar_spec=spec,
band_start=tbstart, band_end=tbend,
conf=conf)
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
fImg[bounds] = fImg[bounds] + ssImg[bounds]
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/Straylight/Straylight.py deleted 100644 → 0
View file @ 4afd1181
import ctypes
import numpy as np
import astropy.constants as cons
from scipy import interpolate
import math
from astropy.table import Table
import astropy.coordinates as coord
from astropy import units as u
import sys
try:
import importlib.resources as pkg_resources
except ImportError:
# Try backported to PY<37 'importlib_resources'
import importlib_resources as pkg_resources
filterPivotWave = {'nuv':2875.5,'u':3629.6,'g':4808.4,'r':6178.2, 'i':7609.0, 'z':9012.9,'y':9627.9}
filterIndex = {'nuv':0,'u':1,'g':2,'r':3, 'i':4, 'z':5,'y':6}
filterCCD = {'nuv':'UV0','u':'UV0','g':'Astro_MB','r':'Astro_MB', 'i':'Basic_NIR', 'z':'Basic_NIR','y':'Basic_NIR'}
bandRange = {'nuv':[2504.0,3230.0],'u':[3190.0,4039.0],'g':[3989.0,5498.0],'r':[5438.0,6956.0], 'i':[6886.0,8469.0], 'z':[8379.0,10855.0],'y':[9217.0, 10900.0], 'GU':[2550, 4000],'GV':[4000, 6200],'GI':[6200,10000]}
# Instrument_dir = '/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/straylight/straylight/Instrument/'
SpecOrder = ['-2','-1','0','1','2']
filterMirrorEff = {'nuv':0.54,'u':0.68,'g':0.8,'r':0.8, 'i':0.8, 'z':0.8,'y':0.8}
def transRaDec2D(ra, dec):
x1 = np.cos(dec / 57.2957795) * np.cos(ra / 57.2957795);
y1 = np.cos(dec / 57.2957795) * np.sin(ra / 57.2957795);
z1 = np.sin(dec / 57.2957795);
return np.array([x1, y1, z1])
def getAngle132(x1 = 0, y1 = 0, z1 = 0, x2 = 0, y2 = 0, z2 = 0, x3 = 0, y3 = 0, z3 = 0):
cosValue = 0;
angle = 0;
x11 = x1-x3;
y11 = y1-y3;
z11 = z1-z3;
x22 = x2-x3;
y22 = y2-y3;
z22 = z2-z3;
tt = np.sqrt((x11*x11 + y11*y11 + z11* z11) * (x22*x22 + y22*y22 + z22*z22));
if(tt==0):
return 0;
cosValue = (x11*x22+y11*y22+z11*z22)/tt;
if (cosValue > 1):
cosValue = 1;
if (cosValue < -1):
cosValue = -1;
angle = math.acos(cosValue);
return angle * 360 / (2 * math.pi);
def calculateAnglePwithEarth(sat = np.array([0,0,0]), pointing = np.array([0,0,0]), sun = np.array([0,0,0])):
modSat = np.sqrt(sat[0]*sat[0] + sat[1]*sat[1]+sat[2]*sat[2])
modPoint = np.sqrt(pointing[0]*pointing[0] + pointing[1]*pointing[1] + pointing[2]*pointing[2])
withLocalZenithAngle = (pointing[0] * sat[0] + pointing[1] * sat[1] + pointing[2] * sat[2]) / (modPoint*modSat)
innerM_sat_sun = sat[0] * sun[0] + sat[1] * sun[1] + sat[2] * sun[2]
cosAngle = innerM_sat_sun / (modSat * cons.au.value/1000)
isInSunSide = 1
if (cosAngle < -0.3385737): #cos109.79
isInSunSide = -1;
elif cosAngle >= -0.3385737 and cosAngle <= 0.3385737:
isInSunSide = 0;
return math.acos(withLocalZenithAngle)*180/math.pi,isInSunSide
# /**
# * *eCoor = ra, *eCoor+1 = dec
# */
def Cartesian2Equatorial(carCoor = np.array([0,0,0])):
eCoor = np.zeros(2)
if (carCoor[0] > 0 and carCoor[1] >= 0):
eCoor[0] = math.atan(carCoor[1] / carCoor[0]) * 360 / (2 * math.pi)
elif (carCoor[0] < 0):
eCoor[0] = (math.atan(carCoor[1] / carCoor[0]) + math.pi) * 360 / (2 * math.pi)
elif (carCoor[0] > 0 and carCoor[1] < 0):
eCoor[0] = (math.atan(carCoor[1] / carCoor[0]) + 2 * math.pi) * 360 / (2 * math.pi)
elif (carCoor[0] == 0 and carCoor[1] < 0):
eCoor[0] = 270
elif (carCoor[0] == 0 and carCoor[1] > 0):
eCoor[0] = 90
eCoor[1] = math.atan(carCoor[2] / np.sqrt(carCoor[0] * carCoor[0] + carCoor[1] * carCoor[1])) * 360 / (2 * math.pi)
return eCoor
class Straylight(object):
def __init__(self, jtime = 2460843., sat_pos = np.array([0,0,0]), pointing_radec = np.array([0,0]), sun_pos = np.array([0,0,0])):
self.jtime = jtime
self.sat = sat_pos
self.sun_pos = sun_pos
self.equator = coord.SkyCoord(pointing_radec[0]*u.degree, pointing_radec[1]*u.degree,frame='icrs')
self.ecliptic = self.equator.transform_to('barycentrictrueecliptic')
self.pointing = transRaDec2D(pointing_radec[0], pointing_radec[1])
platForm = sys.platform
if platForm == 'darwin':
try:
with pkg_resources.files('ObservationSim.Straylight.lib').joinpath('libstraylight.dylib') as dllFn:
self.slcdll = ctypes.CDLL(dllFn)
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.lib', 'libstraylight.dylib') as dllFn:
self.slcdll = ctypes.CDLL(dllFn)
elif platForm == 'linux':
try:
with pkg_resources.files('ObservationSim.Straylight.lib').joinpath('libstraylight.so') as dllFn:
self.slcdll = ctypes.CDLL(dllFn)
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.lib', 'libstraylight.so') as dllFn:
self.slcdll = ctypes.CDLL(dllFn)
# self.slcdll=ctypes.CDLL('./libstraylight.dylib')
self.slcdll.Calculate.argtypes = [ctypes.c_double, ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double), ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double), ctypes.c_char_p]
self.slcdll.PointSource.argtypes = [ctypes.c_double, ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double), ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double), ctypes.c_char_p]
self.slcdll.EarthShine.argtypes = [ctypes.c_double, ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double), ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double)]
self.slcdll.Zodiacal.argtypes = [ctypes.c_double, ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double)]
self.slcdll.ComposeY.argtypes = [ctypes.POINTER(ctypes.c_double), ctypes.POINTER(ctypes.c_double),
ctypes.POINTER(ctypes.c_double)]
self.slcdll.Init.argtypes = [ctypes.c_char_p, ctypes.c_char_p, ctypes.c_char_p, ctypes.c_char_p]
try:
with pkg_resources.files('ObservationSim.Straylight.lib').joinpath('DE405') as tFn:
self.deFn = tFn.as_uri()[7:]
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.lib', 'DE405') as tFn:
self.deFn = tFn.as_uri()[7:]
try:
with pkg_resources.files('ObservationSim.Straylight.lib').joinpath('PST') as tFn:
self.PSTFn = tFn.as_uri()[7:]
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.lib', 'PST') as tFn:
self.PSTFn = tFn.as_uri()[7:]
try:
with pkg_resources.files('ObservationSim.Straylight.lib').joinpath('R') as tFn:
self.RFn = tFn.as_uri()[7:]
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.lib', 'R') as tFn:
self.RFn = tFn.as_uri()[7:]
try:
with pkg_resources.files('ObservationSim.Straylight.lib').joinpath('Zodiacal') as tFn:
self.ZolFn = tFn.as_uri()[7:]
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.lib', 'Zodiacal') as tFn:
self.ZolFn = tFn.as_uri()[7:]
try:
with pkg_resources.files('ObservationSim.Straylight.lib').joinpath('BrightGaia_with_csst_mag') as tFn:
self.brightStarTabFn = tFn.as_uri()[7:]
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.lib', 'BrightGaia_with_csst_mag') as tFn:
self.brightStarTabFn = tFn.as_uri()[7:]
print(self.deFn)
self.slcdll.Init(str.encode(self.deFn), str.encode(self.PSTFn), str.encode(self.RFn), str.encode(self.ZolFn))
def getFilterAndCCD_Q(self, filter = 'i'):
try:
with pkg_resources.files('ObservationSim.Instrument.data.ccd').joinpath(filterCCD[filter] + '.txt') as ccd_fn:
q_ccd_f = np.loadtxt(ccd_fn)
except AttributeError:
with pkg_resources.path('ObservationSim.Instrument.data.ccd', filterCCD[filter] + '.txt') as ccd_fn:
q_ccd_f = np.loadtxt(ccd_fn)
try:
with pkg_resources.files('ObservationSim.Instrument.data.filters').joinpath(filter + '.txt') as filter_fn:
q_fil_f = np.loadtxt(filter_fn)
except AttributeError:
with pkg_resources.path('ObservationSim.Instrument.data.filters', filter + '.txt') as filter_fn:
q_fil_f = np.loadtxt(filter_fn)
band_s = 2000
band_e = 11000
q_ccd_f[:,0] = q_ccd_f[:,0]*10
q_ccd = np.zeros([q_ccd_f.shape[0]+2,q_ccd_f.shape[1]])
q_ccd[1:-1,:] = q_ccd_f
q_ccd[0] = [band_s,0]
q_ccd[-1] = [band_e,0]
q_fil = np.zeros([q_fil_f.shape[0]+2,q_fil_f.shape[1]])
q_fil[1:-1,:] = q_fil_f
q_fil[0] = [band_s,0]
q_fil[-1] = [band_e,0]
q_fil_i = interpolate.interp1d(q_fil[:,0], q_fil[:,1])
q_ccd_i = interpolate.interp1d(q_ccd[:,0], q_ccd[:,1])
bands = np.arange(bandRange[filter][0], bandRange[filter][1],0.5)
q_ccd_fil = q_fil_i(bands)*q_ccd_i(bands)
return np.trapz(q_ccd_fil, bands)/(bandRange[filter][1]-bandRange[filter][0])
def calculateEarthShineFilter(self, filter = 'i', pixel_size_phy = 10 ):
sat = (ctypes.c_double*3)()
sat[:] = self.sat
ob = (ctypes.c_double*3)()
ob[:]=self.pointing
py1 = (ctypes.c_double*3)()
py2 = (ctypes.c_double*3)()
self.slcdll.ComposeY(ob,py1,py2)
earth_e1 = (ctypes.c_double*7)()
self.slcdll.EarthShine(self.jtime,sat,ob,py1,earth_e1)
earth_e2 = (ctypes.c_double*7)()
self.slcdll.EarthShine(self.jtime,sat,ob,py2,earth_e2)
band_earth_e1 = earth_e1[:][filterIndex[filter]]
band_earth_e2 = earth_e2[:][filterIndex[filter]]
q=self.getFilterAndCCD_Q(filter=filter)
p_lambda = filterPivotWave[filter]
c = cons.c.value
h = cons.h.value
pix_earth_e1 = band_earth_e1/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
pix_earth_e2 = band_earth_e2/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
if pix_earth_e1< pix_earth_e2:
return pix_earth_e1, py1[:]
else:
return pix_earth_e2, py2[:]
"""
calculate zodiacal call c++ program, seems to have some problem
"""
def calculateZodiacalFilter1(self, filter = 'i', pixel_size_phy = 10 ):
sat = (ctypes.c_double*3)()
sat[:] = self.sat
ob = (ctypes.c_double*3)()
ob[:]=self.pointing
zodical_e = (ctypes.c_double*7)()
self.slcdll.Zodiacal(self.jtime,ob,zodical_e)
ob1 = (ctypes.c_double*2)()
ob1[:] = np.array([self.ecliptic.lon.value, self.ecliptic.lat.value])
zodical_e1 = (ctypes.c_double*7)()
self.slcdll.Zodiacal1(ob1,zodical_e1)
band_zodical_e = zodical_e[:][filterIndex[filter]]
q=self.getFilterAndCCD_Q(filter=filter)
p_lambda = filterPivotWave[filter]
c = cons.c.value
h = cons.h.value
pix_zodical_e = band_zodical_e/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
return pix_zodical_e, band_zodical_e
"""
calculate zodiacal use python
"""
def calculateZodiacalFilter2(self,filter = 'i', aper = 2, pixelsize = 0.074, sun_pos = np.array([0,0,0])):
spec, v_mag = self.calculateZodicalSpec(longitude = self.ecliptic.lon.value, latitude = self.ecliptic.lat.value, sun_pos = sun_pos)
# spec = self.calculateZodicalSpec(longitude = lon, latitude = lat)
try:
with pkg_resources.files('ObservationSim.Instrument.data.throughputs').joinpath(filter + '_throughput.txt') as throughputFn:
throughput = np.loadtxt(throughputFn)
except AttributeError:
with pkg_resources.path('ObservationSim.Instrument.data.throughputs', filter + '_throughput.txt') as throughputFn:
throughput = np.loadtxt(throughputFn)
deltL = 0.5
lamb = np.arange(bandRange[filter][0], bandRange[filter][1], deltL)
speci = interpolate.interp1d(spec['WAVELENGTH'], spec['FLUX'])
y = speci(lamb)
# erg/s/cm2/A --> photo/s/m2/A
flux = y * lamb / (cons.h.value * cons.c.value) * 1e-13
throughput_i = interpolate.interp1d(throughput[:, 0], throughput[:, 1])
throughput_ = throughput_i(lamb)
sky_pix = np.trapz(flux*throughput_, lamb) * math.pi * aper*aper/4 * pixelsize * pixelsize
# sky_pix_e = np.trapz(y, lamb) * math.pi * aper*aper/4 * pixelsize * pixelsize/(10*10*1e-6*1e-6)*1e-7*1e4
return sky_pix, v_mag#, sky_pix_e
def calculateStarLightFilter(self, filter = 'i', pointYaxis = np.array([1,1,1]), pixel_size_phy = 10 ):
sat = (ctypes.c_double*3)()
sat[:] = self.sat
ob = (ctypes.c_double*3)()
ob[:]=self.pointing
py = (ctypes.c_double*3)()
py[:] = pointYaxis
q=self.getFilterAndCCD_Q(filter=filter)
p_lambda = filterPivotWave[filter]
c = cons.c.value
h = cons.h.value
star_e1 = (ctypes.c_double*7)()
self.slcdll.PointSource(self.jtime,sat,ob,py,star_e1, str.encode(self.brightStarTabFn))
band_star_e1 = star_e1[:][filterIndex[filter]]
pix_star_e1 = band_star_e1/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
return pix_star_e1
def calculateEarthshineGrating(self, grating = 'GU', pixel_size_phy = 10, normFilter = 'g', aper = 2, pixelsize = 0.074):
sat = (ctypes.c_double*3)()
sat[:] = self.sat
ob = (ctypes.c_double*3)()
ob[:]=self.pointing
py1 = (ctypes.c_double*3)()
py2 = (ctypes.c_double*3)()
self.slcdll.ComposeY(ob,py1,py2)
earth_e1 = (ctypes.c_double*7)()
self.slcdll.EarthShine(self.jtime,sat,ob,py1,earth_e1)
earth_e2 = (ctypes.c_double*7)()
self.slcdll.EarthShine(self.jtime,sat,ob,py2,earth_e2)
# zodical_e = (ctypes.c_double*7)()
# self.slcdll.Zodiacal(self.jtime,ob,zodical_e)
band_earth_e1 = earth_e1[:][filterIndex[normFilter]]
band_earth_e2 = earth_e2[:][filterIndex[normFilter]]
band_earth_e = band_earth_e2
py = py2[:]
if band_earth_e1<band_earth_e2:
band_earth_e = band_earth_e1
py = py1[:]
# band_earth_e = np.min([band_earth_e1, band_earth_e2])
# band_earth_e1 = 0
# band_earth_e2 = 0
# band_zodical_e = zodical_e[:][filterIndex[normFilter]]
q=self.getFilterAndCCD_Q(filter=normFilter)
p_lambda = filterPivotWave[normFilter]
c = cons.c.value
h = cons.h.value
pix_earth_e = band_earth_e/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
# pix_earth_e2 = band_earth_e2/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
# pix_zodical_e = band_zodical_e/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
# pix_earth_e = np.min([pix_earth_e1, pix_earth_e2])
earthshine_v, earthshine_spec = self.calculatEarthshineByHSTSpec(filter = normFilter, aper = aper, pixelsize = pixelsize)
lamb_earth = earthshine_spec['WAVELENGTH']
flux_earth = earthshine_spec['FLUX']*pix_earth_e/earthshine_v
# print(pix_earth_e,earthshine_v)
earth_v_grating = 0
for s_order in SpecOrder:
try:
with pkg_resources.files('ObservationSim.Instrument.data.sls_conf').joinpath(
grating + '.Throughput.' + s_order + 'st.fits') as thpFn:
thp_ = Table.read(thpFn)
except AttributeError:
with pkg_resources.path('ObservationSim.Instrument.data.sls_conf',
grating + '.Throughput.' + s_order + 'st.fits') as thpFn:
thp_ = Table.read(thpFn)
thpFn_i = interpolate.interp1d(thp_['WAVELENGTH'], thp_['SENSITIVITY'])
thp = thpFn_i(lamb_earth)
beamsEarth = np.trapz(flux_earth*thp,lamb_earth)* math.pi*aper*aper/4 * pixelsize * pixelsize
earth_v_grating = earth_v_grating + beamsEarth
# print(beamsEarth)
# print(earthshine_v, pix_earth_e, earth_v_grating)
return earth_v_grating, py
def calculateStarLightGrating(self, grating = 'GU', pointYaxis = np.array([1,1,1]), pixel_size_phy = 10 ):
sat = (ctypes.c_double*3)()
sat[:] = self.sat
ob = (ctypes.c_double*3)()
ob[:]=self.pointing
py = (ctypes.c_double*3)()
py[:] = pointYaxis
# q=self.getFilterAndCCD_Q(filter=filter)
# p_lambda = filterPivotWave[filter]
c = cons.c.value
h = cons.h.value
star_e1 = (ctypes.c_double*7)()
self.slcdll.PointSource(self.jtime,sat,ob,py,star_e1, str.encode(self.brightStarTabFn))
filterPivotWaveList = np.zeros(7)
bandRangeList = np.zeros(7)
filterMirrorEffList = np.zeros(7)
filterNameList = list(filterPivotWave.keys())
for i in np.arange(7):
filterPivotWaveList[i] = filterPivotWave[filterNameList[i]]
filterMirrorEffList[i] = filterMirrorEff[filterNameList[i]]
brange = bandRange[filterNameList[i]]
bandRangeList[i] = brange[1] - brange[0]
filterFlux_lamb = star_e1[:]/bandRangeList/filterMirrorEffList/(h*c/(filterPivotWaveList*1e-10))
filterFlux_lambi = interpolate.interp1d(filterPivotWaveList,filterFlux_lamb,fill_value="extrapolate")
lamb_g = np.arange(bandRange[grating][0], bandRange[grating][1],1)
flux_g = filterFlux_lambi(lamb_g)
# flux_total_g = np.trapz(flux_g,lamb_g)
starLight_grating = 0
for s_order in SpecOrder:
try:
with pkg_resources.files('ObservationSim.Instrument.data.sls_conf').joinpath(
grating + '.Throughput.' + s_order + 'st.fits') as thpFn:
thp_ = Table.read(thpFn)
except AttributeError:
with pkg_resources.path('ObservationSim.Instrument.data.sls_conf',
grating + '.Throughput.' + s_order + 'st.fits') as thpFn:
thp_ = Table.read(thpFn)
thpFn_i = interpolate.interp1d(thp_['WAVELENGTH'], thp_['SENSITIVITY'])
thp = thpFn_i(lamb_g)
beamsZol = np.trapz(flux_g*thp,lamb_g)*pixel_size_phy*1e-6*pixel_size_phy*1e-6
starLight_grating = starLight_grating + beamsZol
# print(beamsZol)
# band_star_e1 = star_e1[:][filterIndex[filter]]
# pix_star_e1 = band_star_e1/(h*c/(p_lambda*1e-10))*pixel_size_phy*1e-6*pixel_size_phy*1e-6*q
return starLight_grating
def calculatEarthshineByHSTSpec(self, filter = 'g', aper = 2, pixelsize = 0.074, s = 2000, e = 11000):
try:
with pkg_resources.files('ObservationSim.Straylight.data.sky').joinpath('earthShine.dat') as specFn:
spec = np.loadtxt(specFn)
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.data.sky',
'earthShine.dat') as specFn:
spec = np.loadtxt(specFn)
try:
with pkg_resources.files('ObservationSim.Instrument.data.throughputs').joinpath(filter + '_throughput.txt') as throughputFn:
throughput = np.loadtxt(throughputFn)
except AttributeError:
with pkg_resources.path('ObservationSim.Instrument.data.throughputs', filter + '_throughput.txt') as throughputFn:
throughput = np.loadtxt(throughputFn)
deltL = 0.5
lamb = np.arange(bandRange[filter][0], bandRange[filter][1], deltL)
speci = interpolate.interp1d(spec[:, 0], spec[:, 1])
y = speci(lamb)
# erg/s/cm2/A --> photo/s/m2/A
flux = y * lamb / (cons.h.value * cons.c.value) * 1e-13
throughput_i = interpolate.interp1d(throughput[:, 0], throughput[:, 1])
throughput_ = throughput_i(lamb)
sky_pix = np.trapz(flux*throughput_, lamb) * math.pi * aper*aper/4 * pixelsize * pixelsize
lamb = np.arange(s, e, deltL)
speci = interpolate.interp1d(spec[:, 0], spec[:, 1])
y = speci(lamb)
# erg/s/cm2/A --> photo/s/m2/A
flux = y * lamb / (cons.h.value * cons.c.value) * 1e-13
return sky_pix, Table(np.array([lamb, flux]).T,names=('WAVELENGTH', 'FLUX'))
def calculateZodicalSpec(self,longitude = 50, latitude = 60, sun_pos = np.array([0,0,0])):
from scipy.interpolate import interp2d
from scipy.interpolate import griddata
try:
with pkg_resources.files('ObservationSim.Straylight.data').joinpath('Zodiacal_map1.dat') as z_map_fn:
ZL = np.loadtxt(z_map_fn)
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.data',
'Zodiacal_map1.dat') as z_map_fn:
ZL = np.loadtxt(z_map_fn)
# zl_sh = ZL.shape
# x = np.arange(0,zl_sh[1],1)
# y = np.arange(0,zl_sh[0],1)
x = ZL[0,1:]
y = ZL[1:,0]
X,Y = np.meshgrid(x,y)
# f_sur = interp2d(X,Y,ZL,kind='linear')
sun_radec = Cartesian2Equatorial(sun_pos)
sun_eclip = coord.SkyCoord(sun_radec[0]*u.degree, sun_radec[1]*u.degree,frame='icrs')
sun_equtor = sun_eclip.transform_to('barycentrictrueecliptic')
longitude = longitude - (sun_equtor.lon*u.degree).value
longitude = np.abs(longitude)
# print((sun_equtor.lon*u.degree).value)
if (longitude > 180):
longitude = 360 - longitude
latitude = np.abs(latitude)
lo = longitude
la = latitude
zl = griddata((X.flatten(),Y.flatten()),ZL[1:,1:].flatten(),(la,lo), method='cubic').min()
zl = zl*(math.pi*math.pi)/(180*180)/(3600*3600)*1e-4*1e7*1e-8*1e-4
# print(zl , '\n')
try:
with pkg_resources.files('ObservationSim.Straylight.data.sky').joinpath('zodiacal.dat') as zodical_fn:
spec = np.loadtxt(zodical_fn)
except AttributeError:
with pkg_resources.path('ObservationSim.Straylight.data.sky',
'zodiacal.dat') as zodical_fn:
spec = np.loadtxt(zodical_fn)
speci = interpolate.interp1d(spec[:, 0], spec[:, 1])
flux5000 = speci(5000)
f_ration = zl/flux5000
v_mag = np.log10(f_ration)*(-2.5)+22.1
# print("factor:", v_mag, lo, la)
return Table(np.array([spec[:,0], spec[:,1]*f_ration]).T,names=('WAVELENGTH', 'FLUX')), v_mag
def calculateStrayLightFilter(self, filter = 'i', pixel_size_phy = 10, pixel_scale = 0.074):
e1,py = self.calculateEarthShineFilter(filter = filter, pixel_size_phy = pixel_size_phy)
e2, _ = self.calculateZodiacalFilter2(filter = filter, sun_pos=self.sun_pos, pixelsize = pixel_scale)
e3 = self.calculateStarLightFilter(filter = filter,pointYaxis = py, pixel_size_phy = pixel_size_phy)
return e1+e2+e3
def calculateStrayLightGrating(self, grating = 'GI', pixel_size_phy = 10, normFilter_es = 'g'):
e1,py = self.calculateEarthshineGrating(grating = grating, pixel_size_phy = pixel_size_phy, normFilter = normFilter_es)
e2 = self.calculateStarLightGrating(grating = grating, pointYaxis = py)
spec, _ = self.calculateZodicalSpec(longitude = self.ecliptic.lon.value, latitude = self.ecliptic.lat.value, sun_pos = self.sun_pos)
return e1+e2, spec
def testZodiacal(lon = 285.04312526255366, lat = 30.):
c_eclip = coord.SkyCoord(lon*u.degree, lat*u.degree,frame='barycentrictrueecliptic')
c_equtor = c_eclip.transform_to('icrs')
sl = Straylight(jtime = 2459767.00354975, sat = np.array([]), radec = np.array([(c_equtor.ra*u.degree).value, (c_equtor.dec*u.degree).value]))
e_zol, v_mag = sl.calculateZodiacalFilter2(filter = 'i', sun_pos=np.array([-3.70939436e+07, 1.35334903e+08, 5.86673104e+07]))
print(e_zol)
# ju=2.4608437604166665e+06
# sat = (ctypes.c_double*3)()
# sat[:] = np.array([5873.752, -1642.066, 2896.744])
# ob = (ctypes.c_double*3)()
# ob[:]=np.array([0.445256,0.76061,-0.47246])
# sl = StrayLight(jtime = ju, sat = np.array([5873.752, -1642.066, 2896.744]), pointing = np.array([-0.445256,-0.76061,0.47246]))
# fn = '/Users/zhangxin/Work/SurveyPlan/point/csst_survey_sim_20211028/E17.5_b17.5_beta_11.6_opt_transtime_1_CMG_1_dp_2_0.25_da_10_Texp_1.5_DEC60_500_0.1_800_1000_+5deg.dat'
#
# surveylist = np.loadtxt(fn)
# sky_pix = np.zeros([surveylist.shape[0],7])
#
#
# i = 693438
# c_eclip = coord.SkyCoord(surveylist[:,2]*u.degree, surveylist[:,1]*u.degree,frame='barycentrictrueecliptic')
# c_equtor = c_eclip.transform_to('icrs')
#
#
# # pointing = transRaDec2D((c_equtor[i].ra*u.degree).value, (c_equtor[i].dec*u.degree).value)
# # # print(ju, pointing, surveylist[i,3:9])
# # ju = surveylist[i,0]
# # sl = StrayLight(jtime = ju, sat = surveylist[i,3:6], pointing = pointing)
# # sl.caculateStrayLightGrating(grating = 'GI', pixel_size_phy = 10, normFilter = 'g')
#
# for i in np.arange(surveylist.shape[0]):
# print(i)
# if i > 300:
# break
# # if i != 300:
# # continue
# # if i != 693438:
# # continue
# ju = surveylist[i,0]
# pointing = transRaDec2D((c_equtor[i].ra*u.degree).value, (c_equtor[i].dec*u.degree).value)
# # print(ju, pointing, surveylist[i,3:9])
# sl = StrayLight(jtime = ju, sat = surveylist[i,3:6], radec = np.array([(c_equtor[i].ra*u.degree).value, (c_equtor[i].dec*u.degree).value]))
# # strayl_i,s_zoldical ,s_earth, s_earth1 = sl.caculateStrayLightFilter(filter = 'i')
# # print(i,strayl_i,s_zoldical,s_earth, s_earth1)
# p_cart= transRaDec2D((c_equtor[i].ra*u.degree).value, (c_equtor[i].dec*u.degree).value)
# sky_pix[i,6] = getAngle132(x1 = surveylist[i,6], y1 = surveylist[i,7], z1 = surveylist[i,8], x2 = p_cart[0], y2 = p_cart[1], z2 = p_cart[2], x3 = 0, y3 = 0, z3 = 0)
#
# earthZenithAngle,isInSunSide = calculateAnglePwithEarth(sat = surveylist[i,3:6], pointing = pointing, sun = surveylist[i,6:9])
# sky_pix[i,4] = earthZenithAngle
# sky_pix[i,5] = isInSunSide
#
# e1_,py = sl.caculateEarthShineFilter(filter = 'i')
# # e2, e2_ = sl.calculateZodiacalFilter1(filter = 'i')
# e3, v_mag = sl.calculateZodiacalFilter2(filter = 'i', sun_pos=surveylist[i,6:9])
# # e4 = sl.caculateStarLightFilter(filter = 'i',pointYaxis = py)
# # e4 = 0
#
# e1,py = sl.caculateEarthshineGrating(grating = 'GI', pixel_size_phy = 10, normFilter = 'g')
#
# # e2 = sl.caculateStarLightGrating(grating = 'GV', pointYaxis = py)
# e2 = sl.caculateStarLightGrating(grating = 'GI', pointYaxis = py)
# e4 = sl.caculateStarLightFilter(filter = 'i',pointYaxis = py)
#
# e5=sl.caculateStrayLightFilter(filter = 'i', pixel_size_phy = 10, pixel_scale = 0.074, sun_pos = surveylist[i,6:9])
# e6,_=sl.caculateStrayLightGrating(grating = 'GI', normFilter_es = 'g', sun_pos = surveylist[i,6:9])
#
# sky_pix[i,0] = e1
# sky_pix[i,1] = e2
# sky_pix[i,2] = e3
# sky_pix[i,3] = e4
# print(e1+e2,e1_+e3+e4,e5,e6)
#
# # print(e1,e2,e3,e4)
ObservationSim/Straylight/__init__.py deleted 100755 → 0
View file @ 4afd1181
from .Straylight import Straylight
from .SkybackgroundMap import *
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