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')