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Commit 883b7a77 authored by Fang Yuedong's avatar Fang Yuedong
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bug fixed

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with 5 additions and 1844 deletions
+5 -1844
ObservationSim/Config/Config.py
+ 1
- 0
View file @ 883b7a77
......@@ -23,6 +23,7 @@ def ConfigDir(config, work_dir=None, data_dir=None):
path_dict["cat_dir"] = os.path.join(path_dict["data_dir"], config["input_path"]["cat_dir"])
# PSF data directory
path_dict["psf_dir"] = os.path.join(path_dict["data_dir"], config["psf_setting"]["psf_dir"])
path_dict["fd_path"] = os.path.join(path_dict["data_dir"], config["psf_setting"]["fd_path"])
# SED catalog directory
# TODO: SED_dir is deprecated
path_dict["SED_dir"] = os.path.join(path_dict["data_dir"], "imageSims/Catalog/SEDObject")
......
ObservationSim/Instrument/Chip/Chip.py
+ 1
- 1
View file @ 883b7a77
......@@ -65,7 +65,7 @@ class Chip(FocalPlane):
self._getCRdata()
# Define the sensor
if config["ins_effects"]["bright_fatter"] == True:
if config["ins_effects"]["bright_fatter"] == True and self.survey_type == "photometric":
self.sensor = galsim.SiliconSensor(strength=config["ins_effects"]["df_strength"], treering_func=treering_func)
else:
self.sensor = galsim.Sensor()
......
ObservationSim/ObservationSim.py
+ 3
- 3
View file @ 883b7a77
......@@ -26,7 +26,7 @@ class Observation(object):
# if we want to apply field distortion?
if self.config["ins_effects"]["field_dist"] == True:
self.fd_model = FieldDistortion()
self.fd_model = FieldDistortion(fdModel_path=self.path_dict["fd_path"])
else:
self.fd_model = None
......@@ -59,7 +59,7 @@ class Observation(object):
if self.config["psf_setting"]["psf_model"] == "Gauss":
psf_model = PSFGauss(chip=chip)
elif self.config["psf_setting"]["psf_model"] == "Interp":
psf_model = PSFInterp(chip=chip)
psf_model = PSFInterp(chip=chip, PSF_data_file=self.path_dict["psf_dir"])
else:
print("unrecognized PSF model type!!", flush=True)
......@@ -78,7 +78,7 @@ class Observation(object):
if chip.survey_type == "photometric":
sky_map = None
elif chip.survey_type == "spectroscopic":
sky_map = calculateSkyMap_split_g(xLen=chip.npix_x, yLen=chip.npix_y, blueLimit=filt.blue_limit, redLimit=filt.red_limit, skyfn=path_dict["sky_file"], conf=chip.sls_conf, pixelSize=chip.pix_scale, isAlongY=0)
sky_map = calculateSkyMap_split_g(xLen=chip.npix_x, yLen=chip.npix_y, blueLimit=filt.blue_limit, redLimit=filt.red_limit, skyfn=self.path_dict["sky_file"], conf=chip.sls_conf, pixelSize=chip.pix_scale, isAlongY=0)
if pointing_type == 'MS':
# Load catalogues and templates
......
ObservationSim/PSF/PSFInterp_deprecated/PSFInterp.py deleted 100644 → 0
+ 0
- 263
View file @ e82a5dcc
import galsim
import numpy as np
import os
import time
import copy
# import psfConfig as mypy
import PSF.PSFInterp.psfConfig as mypy
npsf = 900 #***# 30*30
LOG_DEBUG = False #***#
class PSFInterp(object):
# def __init__(self, PSF_data=None, params=None, PSF_data_file=None):
def __init__(self, chip, PSF_data=None, PSF_data_file=None, sigSpin=0., psfRa=0.15):
"""
The PSF data matrix is either given by a object parameter or read in from a file.
Parameters:
PSF_data: The PSF data matrix object
params: Other parameters?
PSF_data_file: The file for PSF data matrix (optional).
"""
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 # 80% light radius
# iccd = 1 #***#
# iccd = chip.chipID
iccd = int(chip.getChipLabel(chipID=chip.chipID))
if PSF_data_file == None:
PSF_data_file = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp_30X30'
self.nwave = self._getPSFwave(iccd, PSF_data_file)
if LOG_DEBUG:
print('nwave-{:} on ccd-{:}::'.format(self.nwave, iccd), flush=True)
self.PSF_data = self._loadPSF(iccd, PSF_data_file)
self.itpPSF_data = self._preprocessPSF()
if LOG_DEBUG:
print('self.PSF_data & self.itpPSF_data ... ok', flush=True)
if LOG_DEBUG:
print('Preparing self.[psfMat,cen_col,cen_row] for psfMaker ... ', end='', flush=True)
ngy, ngx = self.itpPSF_data[0][0]['psfMat'].shape
self.psfMat = np.zeros([self.nwave, npsf, ngy, ngx])
self.cen_col= np.zeros([self.nwave, npsf])
self.cen_row= np.zeros([self.nwave, npsf])
for iwave in range(self.nwave):
for ipsf in range(npsf):
self.psfMat[iwave, ipsf, :, :] = self.itpPSF_data[iwave][ipsf]['psfMat']
self.cen_col[iwave, ipsf] = self.itpPSF_data[iwave][ipsf]['imgMaxPosx_ccd']
self.cen_row[iwave, ipsf] = self.itpPSF_data[iwave][ipsf]['imgMaxPosy_ccd']
if LOG_DEBUG:
print('ok', flush=True)
def _getPSFwave(self, iccd, PSF_data_file):
"""
Get # of sampling waves on iccd
Parameters:
iccd: The chip of i-th ccd
PSF_data_file: The file for PSF data matrix
Returns:
nwave: The number of the sampling waves
"""
strs = os.listdir(PSF_data_file + '/ccd{:}'.format(iccd))
nwave = 0
for _ in strs:
if 'wave_' in _:
nwave += 1
return nwave
def _loadPSF(self, iccd, PSF_data_file):
"""
load psf-matrix on iccd
Parameters:
iccd: The chip of i-th ccd
PSF_data_file: The file for PSF data matrix
Returns:
psfSet: The matrix of the csst-psf
"""
psfSet = []
for ii in range(self.nwave):
iwave = ii+1
if LOG_DEBUG:
print('self._loadPSF: iwave::', iwave, flush=True)
psfWave = []
for jj in range(npsf):
ipsf = jj+1
psfInfo = mypy.LoadPSF(iccd, iwave, ipsf, PSF_data_file, CalcPSFsize=False, InputMaxPixelPos=True)
psfWave.append(psfInfo)
psfSet.append(psfWave)
if LOG_DEBUG:
print('psfSet has been loaded:', flush=True)
print('psfSet[iwave][ipsf][keys]:', psfSet[0][0].keys(), flush=True)
return psfSet
def _preprocessPSF(self):
"""
Preprocessing psf-matrix
Parameters:
Returns:
itpPSF_data: The matrix of the preprocessed csst-psf
"""
itpPSF_data = copy.deepcopy(self.PSF_data)
for iwave in range(self.nwave):
for ipsf in range(npsf):
psfMat = self.PSF_data[iwave][ipsf]['psfMat']
psfMatX= mypy.psfCentering(psfMat, CenteringMode=1)
itpPSF_data[iwave][ipsf]['psfMat'] = psfMatX
return itpPSF_data
def _findWave(self, bandpass):
for iwave in range(self.nwave):
bandwave = self.PSF_data[iwave][0]['wavelength']
if bandpass.blue_limit < bandwave and bandwave < bandpass.red_limit:
return iwave
return -1
def get_PSF(self, chip, pos_img, bandpass, pixSize=0.037, galsimGSObject=True):
"""
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
Returns:
PSF: A 'galsim.GSObject'.
"""
# iccd = 1 #***# #chip.chipID
# iccd = chip.chipID
iccd = int(chip.getChipLabel(chipID=chip.chipID))
# iwave = 1 #***# #self.findWave(bandpass)
iwave = self._findWave(bandpass)
if iwave == -1:
print("!!!PSF bandpass does not match.")
exit()
PSFMat = self.psfMat[iwave]
cen_col= self.cen_col[iwave]
cen_row= self.cen_row[iwave]
# print('shape:', cen_col.shape)
# px = pos_img[0]
# py = pos_img[1]
px = pos_img.x
py = pos_img.y
imPSF = mypy.psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True)
if galsimGSObject:
img = galsim.ImageF(imPSF, scale=pixSize)
self.psf = galsim.InterpolatedImage(img)
dx = px - chip.cen_pix_x
dy = py - chip.cen_pix_y
return self.PSFspin(x=dx, y=dy)
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)
#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
if __name__ == '__main__':
psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp_30X30'
#psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp'
psfCSST = PSFInterp(PSF_data_file = psfPath)
iwave= 1
ipsf = 665
pos_img = [psfCSST.cen_col[iwave, ipsf], psfCSST.cen_row[iwave, ipsf]]
img = psfCSST.get_PSF(1, pos_img, iwave, galsimGSObject=False)
#plot check-1
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(18,5))
ax = plt.subplot(1,3,1)
plt.imshow(img)
plt.colorbar()
ax = plt.subplot(1,3,2)
imgx = psfCSST.itpPSF_data[iwave][ipsf]['psfMat']
imgx/= np.sum(imgx)
plt.imshow(imgx)
plt.colorbar()
ax = plt.subplot(1,3,3)
plt.imshow(img - imgx)
plt.colorbar()
plt.savefig('test/figs/test.jpg')
#plot check-2: 注意图像坐标和全局坐标
fig = plt.figure(figsize=(8,8), dpi = 200)
img = psfCSST.PSF_data[iwave][ipsf]['psfMat']
npix = img.shape[0]
dng = 105
imgg = img[dng:-dng, dng:-dng]
plt.imshow(imgg)
imgX = psfCSST.PSF_data[iwave][ipsf]['image_x'] #in mm
imgY = psfCSST.PSF_data[iwave][ipsf]['image_y'] #in mm
deltX= psfCSST.PSF_data[iwave][ipsf]['centroid_x'] #in mm
deltY= psfCSST.PSF_data[iwave][ipsf]['centroid_y'] #in mm
maxX = psfCSST.PSF_data[iwave][ipsf]['max_x']
maxY = psfCSST.PSF_data[iwave][ipsf]['max_y']
cenPix_X = npix/2 + deltX/0.005
cenPix_Y = npix/2 - deltY/0.005
maxPix_X = npix/2 + maxX/0.005-1
maxPix_Y = npix/2 - maxY/0.005-1
plt.plot([cenPix_X-dng],[cenPix_Y-dng], 'rx', ms = 20)
plt.plot([maxPix_X-dng],[maxPix_Y-dng], 'b+', ms=20)
from scipy import ndimage
y, x = ndimage.center_of_mass(img)
plt.plot([x-dng],[y-dng], 'rx', ms = 10, mew=2)
x, y = mypy.findMaxPix(img)
plt.plot([x-dng],[y-dng], 'b+', ms = 10, mew=2)
plt.savefig('test/figs/test.jpg')
ObservationSim/PSF/PSFInterp_deprecated/PSFInterp_v2/PSFConfig.py deleted 100644 → 0
+ 0
- 236
View file @ e82a5dcc
import sys
from itertools import islice
import numpy as np
import matplotlib.pyplot as plt
import scipy.io
#from scipy.io import loadmat
from scipy import ndimage
import ctypes
import galsim
from PSF.PSFInterp.PSFUtil import *
###加载PSF信息###
def LoadPSF(iccd, iwave, ipsf, psfPath, psfSampleSize=5, InputMaxPixelPos=False, PSFCentroidWgt=False):
"""
load psf informations from psf matrix.
Parameters:
iccd (int): ccd number [1,30].
iwave(int): wave-index [1,4].
ipsf (int): psf number [1, 100].
psfPath (int): path to psf matrix
psfSampleSize (float-optional): psf size in microns.
InputMaxPixelPos(bool-optional): only True for 30*30 psf-matrix
Returns:
psfInfo (dirctionary)
"""
if iccd not in np.linspace(1, 30, 30, dtype='int'):
print('Error - iccd should be in [1, 30].')
sys.exit()
if iwave not in np.linspace(1, 4, 4, dtype='int'):
print('Error - iwave should be in [1, 4].')
sys.exit()
if ipsf not in np.linspace(1, 900, 900, dtype='int'):
print('Error - ipsf should be in [1, 900].')
sys.exit()
psfInfo = {}
fpath = psfPath +'/' +'ccd{:}'.format(iccd) +'/' + 'wave_{:}'.format(iwave)
#获取ipsf矩阵
if not PSFCentroidWgt:
##读取PSF原数据
fpathMat = fpath +'/' +'5_psf_array' +'/' +'psf_{:}.mat'.format(ipsf)
data = scipy.io.loadmat(fpathMat)
psfInfo['psfMat'] = data['psf']
if PSFCentroidWgt:
##读取PSFCentroidWgt
ffpath = psfPath +'_proc/' +'ccd{:}'.format(iccd) +'/' + 'wave_{:}'.format(iwave)
ffpathMat = ffpath +'/' +'5_psf_array' +'/' +'psf_{:}_centroidWgt.mat'.format(ipsf)
data = scipy.io.loadmat(ffpathMat)
psfInfo['psfMat'] = data['psf']
#获取ipsf波长
fpathWave = fpath +'/' +'1_wavelength.txt'
f = open(fpathWave, 'r')
wavelength = np.float(f.readline())
f.close()
psfInfo['wavelength'] = wavelength
#获取ipsf位置
fpathCoordinate = fpath +'/' +'4_PSF_coordinate.txt'
f = open(fpathCoordinate, 'r')
header = f.readline()
for line in islice(f, ipsf-1, ipsf):
line = line.strip()
columns = line.split()
f.close()
icol = 0
psfInfo['field_x'] = float(columns[icol]) #deg, 视场采样位置
icol+= 1
psfInfo['field_y'] = float(columns[icol]) #deg
icol+= 1
psfInfo['centroid_x'] = float(columns[icol]) #mm, psf质心相对主光线的偏移量
icol+= 1
psfInfo['centroid_y'] = float(columns[icol]) #mm
icol+= 1
if InputMaxPixelPos == True:
psfInfo['max_x'] = float(columns[icol]) #mm, max pixel postion
icol+= 1
psfInfo['max_y'] = float(columns[icol]) #mm
icol+= 1
psfInfo['image_x'] = float(columns[icol]) #mm, 主光线位置
icol+= 1
psfInfo['image_y'] = float(columns[icol]) #mm
nrows, ncols = psfInfo['psfMat'].shape
psfPos = psfPixelLayout(nrows, ncols, psfInfo['image_y'], psfInfo['image_x'], pixSizeInMicrons=5.0)
imgMaxPix_x, imgMaxPix_y = findMaxPix(psfInfo['psfMat'])
psfInfo['imgMaxPosx_ccd'] = psfPos[0, imgMaxPix_y, imgMaxPix_x] #cx, psf最大值位置, in mm
psfInfo['imgMaxPosy_ccd'] = psfPos[1, imgMaxPix_y, imgMaxPix_x] #cy
if PSFCentroidWgt:
#if ipsf == 1:
#print('Check:', psfInfo['centroid_x'], psfInfo['centroid_y'], data['cx'][0][0], data['cy'][0][0])
psfInfo['centroid_x'] = data['cx'][0][0] #mm, psfCentroidWgt质心相对主光线的偏移量
psfInfo['centroid_y'] = data['cy'][0][0] #mm
return psfInfo
###加载PSF矩阵信息###
def LoadPSFset(iccd, iwave, npsf, psfPath, psfSampleSize=5, InputMaxPixelPos=False, PSFCentroidWgt=False):
"""
load psfSet for interpolation
Parameters:
iccd, iwave, psfPath: # of ccd/wave and path for psfs
npsf: 100 or 900 for different psf matrixes
Returns:
PSFMat (numpy.array): images
cen_col, cen_row (numpy.array, numpy.array): position of psf center in the view field
"""
psfSet = []
for ipsf in range(1, npsf+1):
psfInfo = LoadPSF(iccd, iwave, ipsf, psfPath, InputMaxPixelPos=InputMaxPixelPos, PSFCentroidWgt=PSFCentroidWgt)
psfSet.append(psfInfo)
ngy, ngx = psfSet[0]['psfMat'].shape
PSFMat = np.zeros([npsf, ngy, ngx])
cen_col= np.zeros(npsf)
cen_row= np.zeros(npsf)
FieldPos = False
for ipsf in range(npsf):
iPSFMat = psfSet[ipsf]['psfMat']
PSFMat[ipsf, :, :] = psfTailor(iPSFMat, apSizeInArcsec=2.5)
if FieldPos == True:
cen_col[ipsf] = psfSet[ipsf]['field_x'] #cx
cen_row[ipsf] = psfSet[ipsf]['field_y'] #cy
if FieldPos == False:
cen_col[ipsf] = psfSet[ipsf]['image_x'] + psfSet[ipsf]['centroid_x'] #cx
cen_row[ipsf] = psfSet[ipsf]['image_y'] + psfSet[ipsf]['centroid_y'] #cy
#cen_col[ipsf] = psfSet[ipsf]['imgMaxPosx_ccd'] #cx --- to be updated
#cen_row[ipsf] = psfSet[ipsf]['imgMaxPosy_ccd'] #cy
#cen_col[ipsf] = psfSet[ipsf]['image_x']
#cen_row[ipsf] = psfSet[ipsf]['image_y']
return psfSet, PSFMat, cen_col, cen_row
###插值PSF图像-IDW方法###
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:
#hoc,hoclist = findNeighbors_hoclist(cen_col, cen_row)
neigh = findNeighbors_hoclist(cen_col, cen_row, tx=px,ty=py, dn=4, hoc=hoc, hoclist=hoclist)
#print("neigh:", neigh)
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='float64')
for ipsf in range(npsf):
if OnlyNeighbors == True:
if neighFlag[ipsf] != 1:
continue
iPSFMat = PSFMat[ipsf, :, :].copy()
#if not PSFCentroidWgt:
# iPSFMat = psfCentering(iPSFMat, CenteringMode=2)
#iPSFMat = psfCentering_FFT(iPSFMat)
#if PSFCentroidWgt:
ipsfWeight = psfWeight[ipsf]
psfMaker += iPSFMat * ipsfWeight
#print("ipsf, ipsfWeight:", ipsf, ipsfWeight)
psfMaker /= np.nansum(psfMaker)
return psfMaker
###TEST###
if __name__ == '__main__':
iccd = 1
iwave= 1
ipsf = 1
npsf = 100
psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp'
a, b, c, d = LoadPSFset(iccd, iwave, npsf, psfPath, InputMaxPixelPos=False)
psfSet = a
print('psfSet has been loaded.')
print('Usage: psfSet[i][keys]')
print('psfSet.keys:', psfSet[0].keys())
print(c[0:10])
print(d[0:10])
ObservationSim/PSF/PSFInterp_deprecated/PSFInterp_v2/PSFInterp.py deleted 100644 → 0
+ 0
- 377
View file @ e82a5dcc
'''
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 galsim
import numpy as np
import os
import time
import copy
import PSF.PSFInterp.PSFConfig as myConfig
import PSF.PSFInterp.PSFUtil as myUtil
from PSF.PSFModel import PSFModel
LOG_DEBUG = False #***#
NPSF = 900 #***# 30*30
iccdTest = 1 #***#
class PSFInterp(PSFModel):
# def __init__(self, PSF_data=None, params=None, PSF_data_file=None):
def __init__(self, chip, PSF_data=None, PSF_data_file=None, sigSpin=0., psfRa=0.15):
"""
The PSF data matrix is either given by a object parameter or read in from a file.
Parameters:
PSF_data: The PSF data matrix object
params: Other parameters?
PSF_data_file: The file for PSF data matrix (optional).
"""
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 # 80% light radius
self.iccd = int(chip.getChipLabel(chipID=chip.chipID))
if PSF_data_file == None:
PSF_data_file = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp_30X30'
self.nwave= self._getPSFwave(self.iccd, PSF_data_file)
self.PSF_data = self._loadPSF(self.iccd, PSF_data_file)
if 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, NPSF, ngy, ngx])
self.cen_col= np.zeros([self.nwave, NPSF])
self.cen_row= np.zeros([self.nwave, NPSF])
self.hoc =[]
self.hoclist=[]
for twave in range(self.nwave):
for tpsf in range(NPSF):
#psfMatX = myUtil.psfTailor(self.PSF_data[twave][tpsf]['psfMat'], apSizeInArcsec=2.5)
self.psfMat[twave, tpsf, :, :] = self.PSF_data[twave][tpsf]['psfMat']
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']
#hoclist on twave for neighborsFinding
hoc,hoclist = myUtil.findNeighbors_hoclist(self.cen_col[twave], self.cen_row[twave])
self.hoc.append(hoc)
self.hoclist.append(hoclist)
if LOG_DEBUG:
print('ok', flush=True)
def _getPSFwave(self, iccd, PSF_data_file):
"""
Get # of sampling waves on iccd
Parameters:
iccd: The chip of i-th ccd
PSF_data_file: The file for PSF data matrix
Returns:
nwave: The number of the sampling waves
"""
strs = os.listdir(PSF_data_file + '/ccd{:}'.format(iccd))
nwave = 0
for _ in strs:
if 'wave_' in _:
nwave += 1
return nwave
def _loadPSF(self, iccd, PSF_data_file):
"""
load psf-matrix on iccd
Parameters:
iccd: The chip of i-th ccd
PSF_data_file: The file for PSF data matrix
Returns:
psfSet: The matrix of the csst-psf
"""
psfSet = []
for ii in range(self.nwave):
iwave = ii+1
if LOG_DEBUG:
print('self._loadPSF: iwave::', iwave, flush=True)
psfWave = []
for jj in range(NPSF):
ipsf = jj+1
psfInfo = myConfig.LoadPSF(iccd, iwave, ipsf, PSF_data_file, InputMaxPixelPos=True, PSFCentroidWgt=True)
psfWave.append(psfInfo)
psfSet.append(psfWave)
if LOG_DEBUG:
print('psfSet has been loaded:', flush=True)
print('psfSet[iwave][ipsf][keys]:', psfSet[0][0].keys(), flush=True)
return psfSet
def _preprocessPSF(self):
"""
Preprocessing psf-matrix
Parameters:
Returns:
itpPSF_data: The matrix of the preprocessed csst-psf
"""
'''
#old version (discarded)
itpPSF_data = copy.deepcopy(self.PSF_data)
for twave in range(self.nwave):
for tpsf in range(NPSF):
psfMat = self.PSF_data[twave][tpsf]['psfMat']
psf_image_x = self.PSF_data[twave][tpsf]['image_x']
psf_image_y = self.PSF_data[twave][tpsf]['image_y']
#psfMatX= myUtil.psfCentering(psfMat, CenteringMode=1)
#itpPSF_data[twave][tpsf]['psfMat'] = psfMatX
#img, cxt, cyt = myUtil.psfCentering_wgt(psfMat, psf_image_x, psf_image_y)
#itpPSF_data[twave][tpsf]['psfMat'] = img
#itpPSF_data[twave][tpsf]['centroid_x'] = cxt
#itpPSF_data[twave][tpsf]['centroid_y'] = cyt
return itpPSF_data
'''
pass
def _findWave(self, bandpass):
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, pixSize=0.037, galsimGSObject=True, folding_threshold=5.e-3):
"""
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
Returns:
PSF: A 'galsim.GSObject'.
"""
assert self.iccd == int(chip.getChipLabel(chipID=chip.chipID)), 'ERROR: self.iccd != chip.label'
# twave = bandpass-1 #***# ??? #self.findWave(bandpass) ###twave=iwave-1 as that in NOTE
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[0]
# py = pos_img[1]
px = (pos_img.x - chip.cen_pix_x)*0.01
py = (pos_img.y - chip.cen_pix_y)*0.01
imPSF = myConfig.psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, hoc=self.hoc[twave], hoclist=self.hoclist[twave], PSFCentroidWgt=True)
#imPSF = myConfig.psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, PSFCentroidWgt=True)
if galsimGSObject:
img = galsim.ImageF(imPSF, scale=pixSize)
gsp = galsim.GSParams(folding_threshold=folding_threshold)
self.psf = galsim.InterpolatedImage(img, gsparams=gsp)
# dx = px - chip.cen_pix_x
# dy = py - chip.cen_pix_y
return self.PSFspin(x=px/0.01, y=py/0.01)
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
def testPSFInterp():
import time
import matplotlib.pyplot as plt
iccd = iccdTest #[1, 30] for test
iwave= 1 #[1, 4] for test
npsfB = 900
psfPathB = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp_30X30'
psfCSST = PSFInterp(PSF_data_file = psfPathB) ### define PSF_data from 30*30
npsfA = 100
psfPathA = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp'
psfSetA, PSFMatA, cen_colA, cen_rowA = myConfig.LoadPSFset(iccd, iwave, npsfA, psfPathA, InputMaxPixelPos=False, PSFCentroidWgt=True) ###load test_data from 10*10
psf_sz = np.zeros(npsfA)
psf_e1 = np.zeros(npsfA)
psf_e2 = np.zeros(npsfA)
psfMaker_sz = np.zeros(npsfA)
psfMaker_e1 = np.zeros(npsfA)
psfMaker_e2 = np.zeros(npsfA)
runtimeInterp = 0
starttime = time.time()
for ipsf in range(npsfA):
print('IDW-ipsf: {:4}/100'.format(ipsf), end='\r', flush=True)
starttimeInterp = time.time()
px = cen_colA[ipsf]
py = cen_rowA[ipsf]
pos_img = [px, py]
img = psfCSST.get_PSF(iccd, pos_img, iwave, galsimGSObject=False) ###interpolate PSF at[px,py]
endtimeInterp = time.time()
runtimeInterp = runtimeInterp + (endtimeInterp - starttimeInterp)
imx = psfSetA[ipsf]['psfMat']
imy = img
cenX, cenY, sz, e1, e2, REE80 = myUtil.psfSizeCalculator(imx, CalcPSFcenter=True, SigRange=True, TailorScheme=2)
psf_sz[ipsf] = sz
psf_e1[ipsf] = e1
psf_e2[ipsf] = e2
cenX, cenY, sz, e1, e2, REE80 = myUtil.psfSizeCalculator(imy, CalcPSFcenter=True, SigRange=True, TailorScheme=2)
psfMaker_sz[ipsf] = sz
psfMaker_e1[ipsf] = e1
psfMaker_e2[ipsf] = e2
endtime = time.time()
print('run time::', endtime - starttime, runtimeInterp)
if True:
ell_iccd = np.zeros(npsfA)
ell_iccd_psfMaker = np.zeros(npsfA)
fig = plt.figure(figsize=(18, 5))
plt.subplots_adjust(wspace=0.1, hspace=0.1)
ax = plt.subplot(1, 3, 1)
for ipsf in range(npsfA):
imx = cen_colA[ipsf]
imy = cen_rowA[ipsf]
plt.plot(imx, imy, 'b.')
ang = np.arctan2(psf_e2[ipsf], psf_e1[ipsf])/2
ell = np.sqrt(psf_e1[ipsf]**2 + psf_e2[ipsf]**2)
ell_iccd[ipsf] = ell
ell *= 50
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
plt.plot([imx-lcos, imx+lcos],[imy-lsin, imy+lsin],'b', lw=2)
###########
ang = np.arctan2(psfMaker_e2[ipsf], psfMaker_e1[ipsf])/2
ell = np.sqrt(psfMaker_e1[ipsf]**2 + psfMaker_e2[ipsf]**2)
ell_iccd_psfMaker[ipsf] = ell
ell *= 50
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
plt.plot([imx-lcos, imx+lcos],[imy-lsin, imy+lsin],'r', lw=1)
###########
plt.gca().set_aspect(1)
ax = plt.subplot(1, 3, 2)
tmp = plt.hist(ell_iccd, bins = 8, color='b', alpha=0.5)
tmp = plt.hist(ell_iccd_psfMaker, bins = 8, color='r', alpha=0.5)
plt.annotate('iccd-{:} iwave-{:}'.format(iccd, iwave), (0.55, 0.85), xycoords='axes fraction',fontsize=15)
plt.xlabel('ell')
plt.ylabel('PDF')
ax = plt.subplot(1, 3, 3)
dsz = (psfMaker_sz - psf_sz)/psf_sz
dsz_hist= plt.hist(dsz)
plt.xlabel('dsz')
plt.savefig('test/figs/testPSFInterp_30t10_iccd{:}_iwave{:}.pdf'.format(iccd, iwave))
if __name__ == '__main__':
if False:
psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp_30X30'
#psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp'
psfCSST = PSFInterp(PSF_data_file = psfPath)
iwave= 1
ipsf = 665
pos_img = [psfCSST.cen_col[iwave, ipsf], psfCSST.cen_row[iwave, ipsf]]
img = psfCSST.get_PSF(1, pos_img, iwave, galsimGSObject=False)
print('haha')
if True:
testPSFInterp()
if False:
#old version (discarded)
#plot check-1
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(18,5))
ax = plt.subplot(1,3,1)
plt.imshow(img)
plt.colorbar()
ax = plt.subplot(1,3,2)
imgx = psfCSST.itpPSF_data[iwave][ipsf]['psfMat']
imgx/= np.sum(imgx)
plt.imshow(imgx)
plt.colorbar()
ax = plt.subplot(1,3,3)
plt.imshow(img - imgx)
plt.colorbar()
plt.savefig('test/figs/test1.jpg')
if False:
#old version (discarded)
#plot check-2: 注意图像坐标和全局坐标
fig = plt.figure(figsize=(8,8), dpi = 200)
img = psfCSST.PSF_data[iwave][ipsf]['psfMat']
npix = img.shape[0]
dng = 105
imgg = img[dng:-dng, dng:-dng]
plt.imshow(imgg)
imgX = psfCSST.PSF_data[iwave][ipsf]['image_x'] #in mm
imgY = psfCSST.PSF_data[iwave][ipsf]['image_y'] #in mm
deltX= psfCSST.PSF_data[iwave][ipsf]['centroid_x'] #in mm
deltY= psfCSST.PSF_data[iwave][ipsf]['centroid_y'] #in mm
maxX = psfCSST.PSF_data[iwave][ipsf]['max_x']
maxY = psfCSST.PSF_data[iwave][ipsf]['max_y']
cenPix_X = npix/2 + deltX/0.005
cenPix_Y = npix/2 - deltY/0.005
maxPix_X = npix/2 + maxX/0.005-1
maxPix_Y = npix/2 - maxY/0.005-1
plt.plot([cenPix_X-dng],[cenPix_Y-dng], 'rx', ms = 20)
plt.plot([maxPix_X-dng],[maxPix_Y-dng], 'b+', ms=20)
from scipy import ndimage
y, x = ndimage.center_of_mass(img)
plt.plot([x-dng],[y-dng], 'rx', ms = 10, mew=4)
x, y = myUtil.findMaxPix(img)
plt.plot([x-dng],[y-dng], 'b+', ms = 10, mew=4)
plt.savefig('test/figs/test2.jpg')
ObservationSim/PSF/PSFInterp_deprecated/PSFInterp_v2/PSFProcess.py deleted 100644 → 0
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- 85
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import os, sys
import numpy as np
import scipy.io
import mpi4py.MPI as MPI
sys.path.append("/public/home/weichengliang/lnData/CSST_new_framwork/csstPSF")
import PSFConfig as myConfig
import PSFUtil as myUtil
def mkdir(path):
isExists = os.path.exists(path)
if not isExists:
os.mkdir(path)
############################################
comm = MPI.COMM_WORLD
ThisTask = comm.Get_rank()
NTasks = comm.Get_size()
npsf = 900
psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp_30X30'
#npsf = 100
#psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_ciomp'
npsfPerTasks = int(npsf/NTasks)
iStart= 0 + npsfPerTasks*ThisTask
iEnd = npsfPerTasks + npsfPerTasks*ThisTask
if ThisTask == NTasks:
iEnd = npsf
for iccd in range(1, 31):
iccdPath = psfPath + '_proc/ccd{:}'.format(iccd)
if ThisTask == 0:
mkdir(iccdPath)
comm.barrier()
for iwave in range(1, 5):
iwavePath = iccdPath + '/wave_{:}'.format(iwave)
if ThisTask == 0:
mkdir(iwavePath)
comm.barrier()
psfMatPath = iwavePath + '/5_psf_array'
if ThisTask == 0:
mkdir(psfMatPath)
comm.barrier()
for ii in range(iStart, iEnd):
ipsf = ii+1
if ThisTask ==0:
print('iccd-iwave-ipsf: {:4}{:4}{:4}'.format(iccd, iwave, ipsf), end='\r',flush=True)
#if iccd != 1 or iwave !=1 or ipsf != 1:
# continue
ipsfOutput = psfMatPath + '/psf_{:}_centroidWgt.mat'.format(ipsf)
#ipsfOutput = './psf_{:}_centroidWgt.mat'.format(ipsf)
psfInfo = myConfig.LoadPSF(iccd, iwave, ipsf, psfPath, InputMaxPixelPos=True)
ipsfMat = psfInfo['psfMat']
npix_y, npix_x = ipsfMat.shape
if npsf == 100:
ncut = 160
if npsf == 900:
ncut = 200
img, cx, cy = myUtil.centroidWgt(ipsfMat, nt=ncut)
dcx = cx - npix_x/2 #pixel coords -> global coords
dcy =-(cy - npix_y/2) #pixel coords -> global coords
dcx*= 5e-3 #pixels -> mm
dcy*= 5e-3 #pixels -> mm
nn = 256
dn = int((nn - ncut)/2)
imgt = np.zeros([nn, nn], dtype=np.float32)
imgt[dn:-dn, dn:-dn] = img
scipy.io.savemat(ipsfOutput, {'cx':dcx, 'cy':dcy, 'psf':imgt})
if iccd != 1 or iwave !=1 or ipsf != 1:
if ThisTask == 0:
print('CHECK::', dcx, dcy, psfInfo['centroid_x'],psfInfo['centroid_y'])
ObservationSim/PSF/PSFInterp_deprecated/PSFInterp_v2/PSFUtil.py deleted 100644 → 0
+ 0
- 531
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import sys
from itertools import islice
import numpy as np
#import matplotlib.pyplot as plt
import scipy.io
#from scipy.io import loadmat
#import xlrd
from scipy import ndimage
#from scipy.interpolate import RectBivariateSpline
import scipy.spatial as spatial
#from astropy.modeling.models import Ellipse2D
#from astropy.coordinates import Angle
#import matplotlib.patches as mpatches
import ctypes
#import galsim
###定义PSF像素的全局坐标###
def psfPixelLayout(nrows, ncols, cenPosRow, cenPosCol, pixSizeInMicrons=5.0):
"""
convert psf pixels to physical position
Parameters:
nrows, ncols (int, int): psf sampling with [nrows, ncols].
cenPosRow, cenPosCol (float, float): A physical position of the chief ray for a given psf.
pixSizeInMicrons (float-optional): The pixel size in microns from the psf sampling.
Returns:
psfPixelPos (numpy.array-float): [posx, posy] in mm for [irow, icol]
Notes:
1. show positions on ccd, but not position on image only [+/- dy]
"""
psfPixelPos = np.zeros([2, nrows, ncols])
if nrows % 2 != 0:
sys.exit()
if ncols % 2 != 0:
sys.exit()
cenPix_row = nrows/2 + 1 #中心主光线对应pixle [由长光定义]
cenPix_col = ncols/2 + 1
for irow in range(nrows):
for icol in range(ncols):
delta_row = ((irow + 1) - cenPix_row)*pixSizeInMicrons*1e-3
delta_col = ((icol + 1) - cenPix_col)*pixSizeInMicrons*1e-3
psfPixelPos[0, irow, icol] = cenPosCol + delta_col
psfPixelPos[1, irow, icol] = cenPosRow - delta_row #note-1:in CCD全局坐标
return psfPixelPos
###查找最大pixel位置###
def findMaxPix(img):
"""
get the pixel position of the maximum-value
Parameters:
img (numpy.array-float): image
Returns:
imgMaxPix_x, imgMaxPix_y (int, int): pixel position in columns & rows
"""
maxIndx = np.argmax(img)
maxIndx = np.unravel_index(maxIndx, np.array(img).shape)
imgMaxPix_x = maxIndx[1]
imgMaxPix_y = maxIndx[0]
return imgMaxPix_x, imgMaxPix_y
###查找neighbors位置###
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
###查找neighbors位置-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中心对齐###
def psfCentering(img, apSizeInArcsec=0.5, psfSampleSizeInMicrons=5, focalLengthInMeters=28, CenteringMode=1):
"""
centering psf within an aperture
Parameters:
img (numpy.array): image
apSizeInArcsec (float-optional): aperture size in arcseconds.
psfSampleSizeInMicrons (float-optional): psf pixel size in microns.
focalLengthInMeters (float-optional): csst focal length im meters.
CenteringMode (int-optional): how to center psf images
Returns:
imgT (numpy.array)
"""
if CenteringMode == 1:
imgMaxPix_x, imgMaxPix_y = findMaxPix(img)
if CenteringMode == 2:
y,x = ndimage.center_of_mass(img) #y-rows, x-cols
imgMaxPix_x = int(x)
imgMaxPix_y = int(y)
apSizeInMicrons = np.deg2rad(apSizeInArcsec/3600.)*focalLengthInMeters*1e6
apSizeInPix = apSizeInMicrons/psfSampleSizeInMicrons
apSizeInPix = np.int(np.ceil(apSizeInPix))
imgT = np.zeros_like(img)
ngy, ngx = img.shape
cy = int(ngy/2)
cx = int(ngx/2)
imgT[cy-apSizeInPix:cy+apSizeInPix+1,
cx-apSizeInPix:cx+apSizeInPix+1] = \
img[imgMaxPix_y-apSizeInPix:imgMaxPix_y+apSizeInPix+1,
imgMaxPix_x-apSizeInPix:imgMaxPix_x+apSizeInPix+1]
return imgT
###插值对齐-fft###
def psfCentering_FFT(image):
"""
centering psf within an aperture by FFT
"""
ny, nx = image.shape
py, px = ndimage.center_of_mass(image)
dx = (px - nx/2)
dy = (py - ny/2)
k=np.zeros((nx,ny,2),dtype=float)
fg=np.fft.fft2(image)
ge =np.zeros_like(fg)
inx = int(nx/2)
jny = int(ny/2)
#prepare for the phase multiply matrix
#left bottom
for i in range(inx+1):
for j in range(jny+1):
k[i][j][0]=i;
k[i][j][1]=j;
#top right
for i in range(inx-1):
for j in range(jny-1):
k[i+inx+1][j+jny+1][0]=(-(nx/2-1)+i)
k[i+inx+1][j+jny+1][1]=(-(ny/2-1)+j)
#bottom right
for i in range(inx+1):
for j in range(jny-1):
k[i][j+jny+1][0]=i
k[i][j+jny+1][1]=(-(ny/2-1)+j)
#top left
for i in range(inx-1):
for j in range(int(jny+1)):
k[i+inx+1][j][0]=(-(nx/2-1)+i)
k[i+inx+1][j][1]=j
for i in range(nx):
for j in range(ny):
ge[i][j]=fg[i][j]*np.exp(2.*np.pi*(dx*k[i][j][0]/nx+dy*k[i][j][1]/ny)*1j)
get=np.fft.ifft2(ge).real
return(get)
###图像叠加###
def psfStack(*psfMat):
"""
stacked image from the different psfs
Parameters:
*psfMat (numpy.array): the different psfs for stacking
Returns:
img (numpy.array): image
"""
nn = len(psfMat)
img = np.zeros_like(psfMat[0])
for ii in range(nn):
img += psfMat[ii]/np.sum(psfMat[ii])
img /= np.sum(img)
return img
###计算PSF椭率-接口###
def psfSizeCalculator(psfMat, psfSampleSize=5, CalcPSFcenter=True, SigRange=True, TailorScheme=2):
"""
calculate psf size & ellipticity
Parameters:
psfMat (numpy.array): image
psfSampleSize (float-optional): psf size in microns.
CalcPSFcenter (bool-optional): whether calculate psf center. Default: True
SigRange (bool-optional): whether use psf tailor. Default: False
TailorScheme (int-optional): which method for psf tailor. Default: 1
Returns:
cenX, cenY (float, float): the pixel position of the mass center
sz (float): psf size
e1, e2 (float, float): psf ellipticity
REE80 (float): radius of REE80 in arcseconds
"""
psfSampleSize = psfSampleSize*1e-3 #mm
REE80 = -1.0 ##encircling 80% energy
if SigRange is True:
if TailorScheme == 1:
psfMat = imSigRange(psfMat, fraction=0.80)
psfInfo['psfMat'] = psfMat #set on/off
if TailorScheme == 2:
#img = psfTailor(psfMat, apSizeInArcsec=0.5)
imgX, REE80 = psfEncircle(psfMat)
#psfMat = img
REE80 = REE80[0]
if CalcPSFcenter is True:
img = psfMat/np.sum(psfMat)
y,x = ndimage.center_of_mass(img) #y-rows, x-cols
cenX = x
cenY = y
if CalcPSFcenter is False:
cenPix_X = psfMat.shape[1]/2 #90
cenPix_Y = psfMat.shape[0]/2 #90
cenX = cenPix_X + psfInfo['centroid_x']/psfSampleSize
cenY = cenPix_Y - psfInfo['centroid_y']/psfSampleSize
pixSize = 1
sz, e1, e2 = psfSecondMoments(psfMat, cenX, cenY, pixSize=pixSize)
return cenX, cenY, sz, e1, e2, REE80
###计算PSF椭率###
def psfSecondMoments(psfMat, cenX, cenY, pixSize=1):
"""
estimate the psf ellipticity by the second moment of surface brightness
Parameters:
psfMat (numpy.array-float): image
cenX, cenY (float, float): pixel position of the psf center
pixSize (float-optional): pixel size
Returns:
sz (float): psf size
e1, e2 (float, float): psf ellipticity
"""
apr = 0.5 #arcsec, 0.5角秒内测量
fl = 28. #meters
pxs = 5.0 #microns
apr = np.deg2rad(apr/3600.)*fl*1e6
apr = apr/pxs
apr = np.int(np.ceil(apr))
I = psfMat
ncol = I.shape[1]
nrow = I.shape[0]
w = 0.0
w11 = 0.0
w12 = 0.0
w22 = 0.0
for icol in range(ncol):
for jrow in range(nrow):
x = icol*pixSize - cenX
y = jrow*pixSize - cenY
rr = np.sqrt(x*x + y*y)
wgt= 0.0
if rr <= apr:
wgt = 1.0
w += I[jrow, icol]*wgt
w11 += x*x*I[jrow, icol]*wgt
w12 += x*y*I[jrow, icol]*wgt
w22 += y*y*I[jrow, icol]*wgt
w11 /= w
w12 /= w
w22 /= w
sz = w11 + w22
e1 = (w11 - w22)/sz
e2 = 2.0*w12/sz
return sz, e1, e2
###计算REE80###
def psfEncircle(img, fraction=0.8, psfSampleSizeInMicrons=5, focalLengthInMeters=28):
"""
psf tailor within a given percentage.
Parameters:
img (numpy.array-float): image
fraction (float-optional): a percentage for psf tailor.
psfSampleSizeInMicrons (float-optional): psf pixel size in microns.
focalLengthInMeters (float-optional): csst focal length im meters.
Returns:
img*wgt (numpy.array-float): image
REE80 (float): radius of REE80 in arcseconds.
"""
#imgMaxPix_x, imgMaxPix_y = findMaxPix(img)
y,x = ndimage.center_of_mass(img) #y-rows, x-cols
imgMaxPix_x = int(x)
imgMaxPix_y = int(y)
im1 = img.copy()
im1size = im1.shape
dis = np.zeros_like(img)
for irow in range(im1size[0]):
for icol in range(im1size[1]):
dx = icol - imgMaxPix_x
dy = irow - imgMaxPix_y
dis[irow, icol] = np.hypot(dx, dy)
nn = im1size[1]*im1size[0]
disX = dis.reshape(nn)
disXsortId = np.argsort(disX)
imgX = img.reshape(nn)
imgY = imgX[disXsortId]
psfFrac = np.cumsum(imgY)/np.sum(imgY)
ind = np.where(psfFrac > fraction)[0][0]
wgt = np.ones_like(dis)
wgt[np.where(dis > dis[np.where(img == imgY[ind])])] = 0
REE80 = np.rad2deg(dis[np.where(img == imgY[ind])]*psfSampleSizeInMicrons*1e-6/focalLengthInMeters)*3600
return img*wgt, REE80
###图像能量百分比查找###
def imSigRange(img, fraction=0.80):
"""
extract the image within x-percent (DISCARD)
Parameters:
img (numpy.array-float): image
fraction (float-optional): a percentage
Returns:
im1 (numpy.array-float): image
"""
im1 = img.copy()
im1size = im1.shape
im2 = np.sort(im1.reshape(im1size[0]*im1size[1]))
im2 = im2[::-1]
im3 = np.cumsum(im2)/np.sum(im2)
loc = np.where(im3 > fraction)
#print(im3[loc[0][0]], im2[loc[0][0]])
im1[np.where(im1 <= im2[loc[0][0]])]=0
return im1
###孔径内图像裁剪###
def psfTailor(img, apSizeInArcsec=0.5, psfSampleSizeInMicrons=5, focalLengthInMeters=28):
"""
psf tailor within a given aperture size
Parameters:
img (numpy.array-float): image
apSizeInArcsec (float-optional): aperture size in arcseconds.
psfSampleSizeInMicrons (float-optional): psf pixel size in microns.
focalLengthInMeters (float-optional): csst focal length im meters.
Returns:
imgT (numpy.array-float): image
"""
#imgMaxPix_x, imgMaxPix_y = findMaxPix(img)
y,x = ndimage.center_of_mass(img) #y-rows, x-cols
imgMaxPix_x = int(x)
imgMaxPix_y = int(y)
apSizeInMicrons = np.deg2rad(apSizeInArcsec/3600.)*focalLengthInMeters*1e6
apSizeInPix = apSizeInMicrons/psfSampleSizeInMicrons
apSizeInPix = np.int(np.ceil(apSizeInPix))
imgT = np.zeros_like(img)
imgT[imgMaxPix_y-apSizeInPix:imgMaxPix_y+apSizeInPix+1,
imgMaxPix_x-apSizeInPix:imgMaxPix_x+apSizeInPix+1] = \
img[imgMaxPix_y-apSizeInPix:imgMaxPix_y+apSizeInPix+1,
imgMaxPix_x-apSizeInPix:imgMaxPix_x+apSizeInPix+1]
return imgT
###centroid with a window###
def centroidWgt(img, nt=160):
#libCentroid = ctypes.CDLL('/public/home/weichengliang/lnData/CSST_new_framwork/csstPSF/libCentroid/libCentroid.so') # CDLL加载库
libCentroid = ctypes.CDLL('./libCentroid/libCentroid.so') # CDLL加载库
libCentroid.centroidWgt.argtypes = [ctypes.POINTER(ctypes.c_float), ctypes.c_int, ctypes.c_int, ctypes.POINTER(ctypes.c_double)]
libCentroid.imSplint.argtypes = [ctypes.POINTER(ctypes.c_float), ctypes.c_int, ctypes.c_int, ctypes.POINTER(ctypes.c_double), ctypes.c_int, ctypes.c_int, ctypes.POINTER(ctypes.c_float)]
imx = img/np.sum(img)
ny, nx = imx.shape
#imx centroid
nn = nx*ny
arr = (ctypes.c_float*nn)()
arr[:] = imx.reshape(nn)
para = (ctypes.c_double*10)()
libCentroid.centroidWgt(arr, ny, nx, para)
imx_cy = para[3] #irow
imx_cx = para[4] #icol
#imx -> imy
nxt=nyt=nt
nn=nxt*nyt
yat = (ctypes.c_float*nn)()
libCentroid.imSplint(arr, ny, nx, para, nxt, nyt, yat)
imy = np.array(yat[:]).reshape([nxt, nyt])
return imy, imx_cx, imx_cy
'''
def psfCentering_wgt(ipsfMat, psf_image_x, psf_image_y, psfSampleSizeInMicrons=5.0):
img, cx, cy = centroidWgt(ipsfMat, nt=160)
nrows, ncols = ipsfMat.shape
cyt = (cy + nrows/2)*psfSampleSizeInMicrons*1e-3 +psf_image_y
cxt = (cx + ncols/2)*psfSampleSizeInMicrons*1e-3 +psf_image_x
return img, cxt, cyt
'''
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from .PSFInterp import PSFInterp
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#OPTS += -D
CC = gcc
OPTIMIZE = -fPIC -g -O3 #-Wall -wd981 #-wd1419 -wd810
#GSLI = -I/home/alex/opt/gsl/include
#GSLL = -L/home/alex/opt/gsl/lib -lgsl -lgslcblas
#FFTWI = -I/home/alex/opt/fftw/include
#FFTWL = -L/home/alex/opt/fftw/lib -lfftw3 -lfftw3f
#HDF5I = -I/home/alex/opt/hdf5/include
#HDF5L = -L/home/alex/opt/hdf5/lib -lhdf5_hl -lhdf5
#FITSI = -I/home/alex/opt/cfitsio/include
#FITSL = -L/home/alex/opt/cfitsio/lib -lcfitsio
#EXTRACFLAGS =
#EXTRACLIB =
CLINK=$(CC)
CFLAGS=$(OPTIMIZE) #$(EXTRACFLAGS) $(OPTS)
CLIB= -shared -lm #$(EXTRACLIB)
OBJS = centroidWgt.o nrutil.o
EXEC = libCentroid.so
all: $(EXEC)
$(EXEC): $(OBJS)
$(CLINK) $(CFLAGS) -o $@ $(OBJS) $(CLIB)
$(OBJS): nrutil.h Makefile
.PHONY : clean
clean:
rm -f *.o $(EXEC)
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#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include "nrutil.h"
//y is the input image, nx and ny are the pixels along x and y axis;
//yt and residu are the required matrix for the function
//para contains the needed parameters: centx=para[3], centy=para[4]
void star_gaus(float **y,int nx,int ny,double *para);
void Interp_bicubic(int nx,int ny,float **a0,int nbound, int nxt,int nyt, float **at,double *xcen);
void splie2(float **ya, int m, int n, float **y2a);
void spline(float y[], int n, float yp1, float ypn, float y2[]);
void splint(float ya[], float y2a[], int n, float x, float *y);
void centroidWgt(float *y, int nx, int ny, double *para)
{
int i, j, k;
float **yy;
double **basef;
double **coff;
double ccol, crow;
yy = matrix(0, nx-1, 0, ny-1);
for(i=0; i<nx; i++)
for(j=0; j<ny; j++)
{
k = j + i*nx;
yy[i][j] = y[k];
}
star_gaus(yy, nx, ny, para);
//ccol = para[4];
//crow = para[3];
}
void imSplint(float *y, int nx, int ny, double *para, int nxt, int nyt, float *yat)
{
int i, j, k;
float **yy;
double **basef;
double **coff;
double ccol, crow;
yy = matrix(0, nx-1, 0, ny-1);
for(i=0; i<nx; i++)
for(j=0; j<ny; j++)
{
k = j + i*nx;
yy[i][j] = y[k];
}
crow = para[3];
ccol = para[4];
int nbound;
float **at;
double xcen[2];
at = matrix(0, nxt-1, 0, nyt-1);
nbound = (int)((nx - nxt)/2);
xcen[0]= crow;
xcen[1]= ccol;
Interp_bicubic(nx, ny, yy, nbound, nxt, nyt, at, xcen);
for(i=0; i<nxt; i++)
for(j=0; j<nyt; j++)
{
k = j + i*nxt;
yat[k] = at[i][j];
}
}
//void star_gaus(float **y,int nx,int ny,float **yt,float **residu,double *para)
void star_gaus(float **y,int nx,int ny,double *para)
{
void gasfit_2D(double **x, double *y,int np,double *para,double bg0, int fbg);
double **xs,*ys,ymax;
int i,j,np,npt,im,jm,**xi,k;
double kc,bgc,sigmac,xc,yc,sigma2v,det;
double bg0=0;
int fbg=0;
np=nx*ny;
xs=dmatrix(0,np-1,0,1);
ys=dvector(0,np-1);
xi=imatrix(0,np-1,0,1);
ymax=y[0][0];
for(i=0;i<nx;i++)for(j=0;j<ny;j++){
if(ymax<y[i][j]){ymax=y[i][j];im=i;jm=j;}
}
int cutPix;
cutPix = 23;
npt=0;
for(i=-cutPix;i<=cutPix;i++){
for(j=-cutPix;j<=cutPix;j++){
xs[npt][0]=xi[npt][0]=i+im;
xs[npt][1]=xi[npt][1]=j+jm;
ys[npt]=y[im+i][jm+j];
npt++;
}
}
gasfit_2D(xs, ys,npt,para,bg0,fbg);
kc=para[0];sigmac=para[1];bgc=para[2];xc=para[3];yc=para[4];
// printf("%e %e %e %e %e\n",kc,sigmac,bgc,xc,yc);
/*
sigma2v=-1./(2.*sigmac*sigmac);
for(i=0;i<nx;i++){
for(j=0;j<ny;j++){
det=DSQR(i-xc)+DSQR(j-yc);
yt[i][j]=kc*exp(det*sigma2v)+bgc;
residu[i][j]=y[i][j]-yt[i][j];
}
}
*/
free_dmatrix(xs,0,np-1,0,1);
free_imatrix(xi,0,np-1,0,1);
free_dvector(ys,0,np-1);
}
void gasfit_2D(double **x, double *y,int np,double *para,double bg0,int fbg)
{
void search_2D(double **x,double *y,int np,double kc,double kd,double sigmac,
double sigmad,double bgc,double bgd,double xc, double xd,
double yc, double yd,double *para,double bg0,int fbg);
int i,j,k,imax=0,isigma;
double ymax,ymin,kc,kd,sigmac,sigmad,bgc,bgd,ysigma,xc,yc,xd,yd;
double det,dett;
ymin=ymax=y[imax];
for(i=1;i<np;i++){
if(ymax<y[i]){imax=i;ymax=y[i];}
if(ymin>y[i])ymin=y[i];
}
kc=ymax;kd=ymax/12.;
det=ysigma=kc*exp(-0.5);
for(i=0;i<np;i++){
dett=fabs(ysigma-y[i]);
if(dett<det && y[i]!=kc){det=dett;isigma=i;}
//if(dett<det){det=dett;isigma=i;}
}
xc=x[imax][0];yc=x[imax][1];
sigmac=sqrt(DSQR(xc-x[isigma][0])+DSQR(yc-x[isigma][1]))*1.;
xd=yd=sigmac*0.25;
sigmad=0.25*sigmac;
bgc=0.;bgd=fabs(ymin);
for(i=0;i<4;i++){
search_2D(x,y,np,kc,kd,sigmac,sigmad,bgc,bgd,xc,xd,yc,yd,para,bg0,fbg);
kd*=0.33;sigmad*=0.33;bgd*=0.33;xd*=0.33;yd*=0.33;
kc=para[0];sigmac=para[1];bgc=para[2];xc=para[3];yc=para[4];
}
if(fbg==0)para[2]=bg0;
}
void search_2D(double **x,double *y,int np,double kc,double kd,double sigmac,
double sigmad,double bgc,double bgd,double xc, double xd,
double yc, double yd,double *para,double bg0,int fbg)
{
double k,sigma,bg,k2,k20,sigma2v,det,xt,yt;
int i,j,l,m,p,q;
sigma2v=-1./(2.*sigmac*sigmac);
bg=bgc;
k20=0;
for(m=0;m<np;m++){
det=DSQR(x[m][0]-xc)+DSQR(x[m][1]-yc);
det=kc*exp(det*sigma2v)+bgc-y[m];
k20+=det*det;
}
for(i=-4;i<=4;i++){
k=kc+i*kd;
if(k>0){
for(j=-4;j<=4;j++){
sigma=sigmac+j*sigmad;
if(sigma>0){
sigma2v=-1./(2.*sigma*sigma);
for(p=-4;p<=4;p++){
xt=xc+p*xd;
for(q=-4;q<=4;q++){
yt=yc+q*yd;
k2=0;
if(fbg==0){
bg=bg0;
for(m=0;m<np;m++){
det=DSQR(x[m][0]-xt)+DSQR(x[m][1]-yt);
det=k*exp(det*sigma2v)+bg-y[m];
k2+=det*det;
}
}
else{
for(l=-4;l<=4;l++){
bg=bgc+l*bgd;
for(m=0;m<np;m++){
det=DSQR(x[m][0]-xt)+DSQR(x[m][1]-yt);
det=k*exp(det*sigma2v)+bg-y[m];
k2+=det*det;
}
}
}
//printf("k20=%e k2=%e\n",k20,k2);
if(k2<=k20){k20=k2;para[5]=k2;
para[0]=k;para[1]=sigma;para[2]=bg;para[3]=xt;para[4]=yt;}
}
}
}
}
}
}
}
/////////////////////////////
//#include <math.h>
//#include <stdio.h>
//#include <stdlib.h>
//#include "nrutil.h"
//nx,ny is the pixels of x and y direction
//a0 is the input image in nx*ny
//nbound is the boundary limit
//nxt,nyt is out put image dimentions
//at is the output image and cen represent the required center
void Interp_bicubic(int nx,int ny,float **a0,int nbound,
int nxt,int nyt, float **at,double *xcen)
{
void splie2(float **ya, int m, int n, float **y2a);
void spline(float y[], int n, float yp1, float ypn, float y2[]);
void splint(float ya[], float y2a[], int n, float x, float *y);
int i,j,m,n,ic,jc;
float *ytmp,*yytmp,**y2a,x1,x2,shift1,shift2;
y2a=matrix(0,nx,0,ny);
ytmp=vector(0,ny);
yytmp=vector(0,ny);
splie2(a0,nx,ny,y2a);
ic=nx*0.5;
jc=ny*0.5;
shift1=xcen[0]-ic;//-0.5;
shift2=xcen[1]-jc;//-0.5;
if(fabs(shift1)>nbound || fabs(shift2)>nbound){
printf("bicubic shifts too much %e %e\n",shift1,shift2);
getchar();
}
for (n=0;n<nyt;n++){
x2=n+nbound+shift2;
for(i=0;i<nx;i++){
splint(a0[i],y2a[i],ny,x2,&yytmp[i]);
spline(yytmp,ny,1.0e30,1.0e30,ytmp);
}
for (m=0;m<nxt;m++){
x1=m+nbound+shift1;
splint(yytmp,ytmp,ny,x1,&at[m][n]);
}
}
free_vector(yytmp,0,ny);
free_vector(ytmp,0,ny);
free_matrix(y2a,0,nx,0,ny);
}
void splie2(float **ya, int m, int n, float **y2a)
{
void spline(float y[], int n, float yp1, float ypn, float y2[]);
int j;
for (j=0;j<m;j++)spline(ya[j],n,1.0e30,1.0e30,y2a[j]);
}
void spline(float y[], int n, float yp1, float ypn, float y2[])
{
int i,k;
float p,qn,sig,un,*u;
u=vector(0,n-1);
if (yp1 > 0.99e30)
y2[0]=u[0]=0.0;
else {
y2[0] = -0.5;
u[0]=3.0*(y[1]-y[0]-yp1);
}
sig=0.5;
for (i=1;i<=n-2;i++) {
p=sig*y2[i-1]+2.0;
y2[i]=(sig-1.0)/p;
u[i]=(y[i+1]-2.*y[i]+y[i-1]);
u[i]=(3.0*u[i]-sig*u[i-1])/p;
}
if (ypn > 0.99e30)
qn=un=0.0;
else {
qn=0.5;
un=3.0*(ypn-y[n-1]+y[n-2]);
}
y2[n-1]=(un-qn*u[n-2])/(qn*y2[n-2]+1.0);
for (k=n-2;k>=0;k--)y2[k]=y2[k]*y2[k+1]+u[k];
free_vector(u,0,n-1);
}
void splint(float ya[], float y2a[], int n, float x, float *y)
{
void nrerror(char error_text[]);
int klo,khi,k;
float h,b,a;
klo=x;
if( klo<0)klo=0;
if(klo==n-1)klo=n-2;
khi=klo+1;
if (klo<0 || khi>=n) printf("error:klo, khi, n: %d %d %d\n", klo, khi, n);
if (klo<0 || khi>=n) nrerror("Bad xa input to routine splint");
a=(khi-x);
b=(x-klo);
*y=a*ya[klo]+b*ya[khi]+((a*a*a-a)*y2a[klo]+(b*b*b-b)*y2a[khi])/6.0;
}
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ObservationSim/PSF/PSFInterp_deprecated/PSFInterp_v2/libCentroid/libCentroid.so deleted 100755 → 0
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