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import sys
import numpy as np
import scipy.io
from itertools import islice
# from PSF.PSFInterp.PSFUtil import *
# from PSFUtil import findNeighbors, findNeighbors_hoclist
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###加载PSF信息###
def LoadPSF(iccd, iwave, ipsf, psfPath, InputMaxPixelPos=True, PSFCentroidWgt=False, PixSizeInMicrons=2.5, PSFBinning=False, PSFConvGauss=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
InputMaxPixelPos(bool-optional): only True for 30*30 psf-matrix
PSFCentroidWgt(bool-optional): True for using psfMat with libCentroid.lib
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']
'''
if not PSFCentroidWgt:
ffpath = fpath
ffpathMat = ffpath +'/5_psf_array/psf_{:}.mat'.format(ipsf)
if PSFCentroidWgt:
ffpath = psfPath +'_proc/ccd{:}/wave_{:}'.format(iccd, iwave)
ffpathMat = ffpath +'/5_psf_array/psf_{:}_centroidWgt.mat'.format(ipsf)
if PSFBinning and (not PSFConvGauss):
ffpath = psfPath +'_bin256x256/ccd{:}/wave_{:}'.format(iccd, iwave)
ffpathMat = ffpath +'/5_psf_array/psf_{:}_centroidWgt.mat'.format(ipsf)
if (not PSFBinning) and PSFConvGauss:
ffpath = psfPath +'_convGauss/ccd{:}/wave_{:}'.format(iccd, iwave)
ffpathMat = ffpath +'/5_psf_array/psf_{:}_centroidWgt.mat'.format(ipsf)
if PSFBinning and PSFConvGauss:
ffpath = psfPath +'_convGauss/ccd{:}/wave_{:}'.format(iccd, iwave)
ffpathMat = ffpath +'/5_psf_array/psf_{:}_centroidWgt_BC.mat'.format(ipsf)
data = scipy.io.loadmat(ffpathMat)
psfInfo['psfMat'] = data['psf']
psfInfo['pixsize'] = PixSizeInMicrons #microns
if PSFBinning:
psfInfo['pixsize'] = PixSizeInMicrons*2.0
#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
if PSFCentroidWgt:
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
if PSFBinning:
psfInfo['centroid_x'] = data['cx'][0][0] +0.0025/2 #binning引起的主光线漂移
psfInfo['centroid_y'] = data['cy'][0][0] +0.0025/2
return psfInfo
###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])
from .PSFUtil import findNeighbors, findNeighbors_hoclist
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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
###TEST###
if __name__ == '__main__':
iccd = 1
iwave= 1
ipsf = 1
psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_20210108/CSST_psf_ciomp_2p5um_cycle3_ccr90'
psfInfo = LoadPSF(iccd, iwave, ipsf, psfPath, InputMaxPixelPos=True, PSFCentroidWgt=True)
print('psfInfo.keys:', psfInfo.keys())
print(psfInfo)