''' 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 from ObservationSim.PSF.PSFInterp import PSFConfig as myConfig from ObservationSim.PSF.PSFInterp import PSFUtil as myUtil from ObservationSim.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). """ from . import PSFUtil as myUtil 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.iccd = int(chip.getChipLabel(chipID=chip.chipID)) if PSF_data_file == None: PSF_data_file = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_20210108/CSST_psf_ciomp_2p5um_cycle3_ccr90' 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], dtype=np.float32) self.cen_col= np.zeros([self.nwave, NPSF], dtype=np.float32) self.cen_row= np.zeros([self.nwave, NPSF], dtype=np.float32) self.hoc =[] self.hoclist=[] for twave in range(self.nwave): for tpsf in range(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'] +0.*self.pixsize + self.PSF_data[twave][tpsf]['centroid_x'] self.cen_row[twave, tpsf] = self.PSF_data[twave][tpsf]['image_y'] +0.*self.pixsize + 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 """ from . import PSFConfig as myConfig 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, PSFBinning=True, PSFConvGauss=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): 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=0.0184, galsimGSObject=True, findNeighMode='treeFind', 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 findNeighMode: 'treeFind' or 'hoclistFind' Returns: PSF: A 'galsim.GSObject'. """ from . import PSFConfig as myConfig pixSize = np.rad2deg(self.pixsize*1e-3/28)*3600 #set psf pixsize #***# assert self.iccd == chip.chipID, 'ERROR: self.iccd != chip.chipID' # twave = bandpass-1 #***# ??? #self.findWave(bandpass) ###twave=iwave-1 as that in NOTE 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[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 if findNeighMode == 'treeFind': imPSF = myConfig.psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=2, OnlyNeighbors=True, PSFCentroidWgt=True) if findNeighMode == 'hoclistFind': 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) if galsimGSObject: img = galsim.ImageF(imPSF, scale=pixSize) gsp = galsim.GSParams(folding_threshold=folding_threshold) self.psf = galsim.InterpolatedImage(img, gsparams=gsp) # gaussPSF = galsim.Gaussian(sigma=0.04, gsparams=gsp) # self.psf = galsim.Convolve(gaussPSF, self.psf) 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 if __name__ == '__main__': if True: psfPath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/CSSOS_psf_20210108/CSST_psf_ciomp_2p5um_cycle3_ccr90' 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=True) print('haha') 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) from . import PSFUtil as myUtil x, y = myUtil.findMaxPix(img) plt.plot([x-dng],[y-dng], 'b+', ms = 10, mew=4) plt.savefig('test/figs/test2.jpg')