From b4201fbceb551a52db3a9b280646e2e68e3eaf37 Mon Sep 17 00:00:00 2001 From: "zhaojunyan@shao.ac.cn" Date: Sat, 13 Apr 2024 17:14:21 +0800 Subject: [PATCH] more case test --- csst_ifs_sim/csst_ifs_sim.py | 460 +++++++++++++++++------------------ 1 file changed, 230 insertions(+), 230 deletions(-) diff --git a/csst_ifs_sim/csst_ifs_sim.py b/csst_ifs_sim/csst_ifs_sim.py index 7389014..ff0873d 100644 --- a/csst_ifs_sim/csst_ifs_sim.py +++ b/csst_ifs_sim/csst_ifs_sim.py @@ -117,50 +117,50 @@ def transRaDec2D(ra, dec): ############################################################################### -def flux2ill(wave, flux): - """ +# def flux2ill(wave, flux): +# """ - Parameters - ---------- - wave : TYPE - DESCRIPTION. - flux : TYPE - DESCRIPTION. +# Parameters +# ---------- +# wave : TYPE +# DESCRIPTION. +# flux : TYPE +# DESCRIPTION. - Returns - ------- - E : TYPE - DESCRIPTION. +# Returns +# ------- +# E : TYPE +# DESCRIPTION. - """ +# """ - # erg/s/cm^2/A/arcsec^2 to W/m^2 +# # erg/s/cm^2/A/arcsec^2 to W/m^2 - # 1 W/m^2/sr/μm = 0.10 erg/cm^2/s/sr/A - # 1 sr = 1 rad^2 = 4.25452e10 arcsec^2 - # 1 J/s = 1 W - # 1 J = 10^7 erg +# # 1 W/m^2/sr/μm = 0.10 erg/cm^2/s/sr/A +# # 1 sr = 1 rad^2 = 4.25452e10 arcsec^2 +# # 1 J/s = 1 W +# # 1 J = 10^7 erg - # convert erg/s/cm^2/A/arcsec^2 to erg/s/cm^2/A/sr - flux1 = flux / (1/4.25452e10) - # convert erg/s/cm^2/A/sr to W/m^2/sr/um - flux2 = flux1 * 10 +# # convert erg/s/cm^2/A/arcsec^2 to erg/s/cm^2/A/sr +# flux1 = flux / (1/4.25452e10) +# # convert erg/s/cm^2/A/sr to W/m^2/sr/um +# flux2 = flux1 * 10 - # 对接收面积积分，输出单位 W/m^2/nm - D = 2 # meter - f = 28 # meter - flux3 = flux2 * np.pi * D**2 / 4 / f**2 / 10**3 +# # 对接收面积积分，输出单位 W/m^2/nm +# D = 2 # meter +# f = 28 # meter +# flux3 = flux2 * np.pi * D**2 / 4 / f**2 / 10**3 - # 对波长积分 - f = interp1d(wave, flux3) - wave_interp = np.arange(3800, 7800) - flux3_interp = f(wave_interp) - # 输出单位 W/m^2 - delta_lamba = 0.1 # nm - E = np.sum(flux3_interp * delta_lamba) +# # 对波长积分 +# f = interp1d(wave, flux3) +# wave_interp = np.arange(3800, 7800) +# flux3_interp = f(wave_interp) +# # 输出单位 W/m^2 +# delta_lamba = 0.1 # nm +# E = np.sum(flux3_interp * delta_lamba) - return E +# return E ################################################################ @@ -391,25 +391,25 @@ class StrayLight(object): ############################################################################### -def str2time(strTime): - """ +# def str2time(strTime): +# """ - Parameters - ---------- - strTime : TYPE - DESCRIPTION. +# Parameters +# ---------- +# strTime : TYPE +# DESCRIPTION. - Returns - ------- - TYPE - DESCRIPTION. +# Returns +# ------- +# TYPE +# DESCRIPTION. - """ - if len(strTime) > 20: # 暂时未用到 - msec = int(float('0.'+strTime[20:])*1000000) # 微秒 - str2 = strTime[0:19]+' '+str(msec) - return datetime.strptime(str2, '%Y %m %d %H %M %S %f') +# """ +# if len(strTime) > 20: # 暂时未用到 +# msec = int(float('0.'+strTime[20:])*1000000) # 微秒 +# str2 = strTime[0:19]+' '+str(msec) +# return datetime.strptime(str2, '%Y %m %d %H %M %S %f') # datetime类转mjd ########################################################################## @@ -822,40 +822,40 @@ def centroid(data): return float(cx), float(cy) ############################################################################### -def centroidN(data): - """ +# def centroidN(data): +# """ - Parameters - ---------- - data : TYPE - DESCRIPTION. +# Parameters +# ---------- +# data : TYPE +# DESCRIPTION. - Returns - ------- - cx : TYPE - DESCRIPTION. - cy : TYPE - DESCRIPTION. +# Returns +# ------- +# cx : TYPE +# DESCRIPTION. +# cy : TYPE +# DESCRIPTION. - """ - ''' - calculate the centroid of the input two-dimentional image data +# """ +# ''' +# calculate the centroid of the input two-dimentional image data - Parameters - ---------- - data : input image. +# Parameters +# ---------- +# data : input image. - Returns - ------- - cx: the centroid column number, in horizontal direction definet in python image show - cy: the centroid row number , in vertical direction +# Returns +# ------- +# cx: the centroid column number, in horizontal direction definet in python image show +# cy: the centroid row number , in vertical direction - ''' - ### - from scipy import ndimage - cy, cx = ndimage.center_of_mass(data) - return cx, cy +# ''' +# ### +# from scipy import ndimage +# cy, cx = ndimage.center_of_mass(data) +# return cx, cy #################################################################### @@ -1494,42 +1494,42 @@ class IFSsimulator(): return wave_A, spec_erg2 ########################################################################## - def smoothingWithChargeDiffusion(self, image, sigma=(0.32, 0.32)): - """ + # def smoothingWithChargeDiffusion(self, image, sigma=(0.32, 0.32)): + # """ - Parameters - ---------- - image : TYPE - DESCRIPTION. - sigma : TYPE, optional - DESCRIPTION. The default is (0.32, 0.32). + # Parameters + # ---------- + # image : TYPE + # DESCRIPTION. + # sigma : TYPE, optional + # DESCRIPTION. The default is (0.32, 0.32). - Returns - ------- - TYPE - DESCRIPTION. + # Returns + # ------- + # TYPE + # DESCRIPTION. - """ - """ - Smooths a given image with a gaussian kernel with widths given as sigmas. - This smoothing can be used to mimic charge diffusion within the CCD. + # """ + # """ + # Smooths a given image with a gaussian kernel with widths given as sigmas. + # This smoothing can be used to mimic charge diffusion within the CCD. - The default values are from Table 8-2 of CCD_273_Euclid_secification_1.0.130812.pdf converted - to sigmas (FWHM / (2sqrt(2ln2)) and rounded up to the second decimal. + # The default values are from Table 8-2 of CCD_273_Euclid_secification_1.0.130812.pdf converted + # to sigmas (FWHM / (2sqrt(2ln2)) and rounded up to the second decimal. - .. Note:: This method should not be called for the full image if the charge spreading - has already been taken into account in the system PSF to avoid double counting. + # .. Note:: This method should not be called for the full image if the charge spreading + # has already been taken into account in the system PSF to avoid double counting. - :param image: image array which is smoothed with the kernel - :type image: ndarray - :param sigma: widths of the gaussian kernel that approximates the charge diffusion [0.32, 0.32]. - :param sigma: tuple + # :param image: image array which is smoothed with the kernel + # :type image: ndarray + # :param sigma: widths of the gaussian kernel that approximates the charge diffusion [0.32, 0.32]. + # :param sigma: tuple - :return: smoothed image array - :rtype: ndarray - """ - return ndimage.filters.gaussian_filter(image, sigma) + # :return: smoothed image array + # :rtype: ndarray + # """ + # return ndimage.filters.gaussian_filter(image, sigma) ############################################################################### def readCosmicRayInformation(self): @@ -1835,88 +1835,88 @@ class IFSsimulator(): ###################################################################### ############################################################################## - def generateflat(self, ave=1.0, sigma=0.01): - """ + # def generateflat(self, ave=1.0, sigma=0.01): + # """ - Parameters - ---------- - ave : TYPE, optional - DESCRIPTION. The default is 1.0. - sigma : TYPE, optional - DESCRIPTION. The default is 0.01. + # Parameters + # ---------- + # ave : TYPE, optional + # DESCRIPTION. The default is 1.0. + # sigma : TYPE, optional + # DESCRIPTION. The default is 0.01. - Returns - ------- - TYPE - DESCRIPTION. - TYPE - DESCRIPTION. + # Returns + # ------- + # TYPE + # DESCRIPTION. + # TYPE + # DESCRIPTION. - """ - """ - Creates a flat field image with given properties. + # """ + # """ + # Creates a flat field image with given properties. - :return: flat field image - :rtype: ndarray - """ - self.log.info('Generating a flat field...') - self.log.info('The flat field has mean value of 1 and a given fluctuations, usually either 1 or 2 percent defined by sigma= %d...' % sigma) + # :return: flat field image + # :rtype: ndarray + # """ + # self.log.info('Generating a flat field...') + # self.log.info('The flat field has mean value of 1 and a given fluctuations, usually either 1 or 2 percent defined by sigma= %d...' % sigma) - np.random.seed(5*self.simnumber) - self.flat_b = np.random.normal(loc=ave, scale=sigma, size=(2048, 4096)) + # np.random.seed(5*self.simnumber) + # self.flat_b = np.random.normal(loc=ave, scale=sigma, size=(2048, 4096)) - np.random.seed(55*self.simnumber) - self.flat_r = np.random.normal(loc=ave, scale=sigma, size=(3072, 6144)) + # np.random.seed(55*self.simnumber) + # self.flat_r = np.random.normal(loc=ave, scale=sigma, size=(3072, 6144)) - s1 = self.flat_b + # s1 = self.flat_b - hdu1 = fits.PrimaryHDU(s1) + # hdu1 = fits.PrimaryHDU(s1) - hdu1.header.set('sigma', sigma) + # hdu1.header.set('sigma', sigma) - dtime = datetime.utcnow().strftime('%Y -%m -%d %H: %M: %S') - hdu1.header.add_history( - 'flat image of blue channel is generated on :'+dtime) + # dtime = datetime.utcnow().strftime('%Y -%m -%d %H: %M: %S') + # hdu1.header.add_history( + # 'flat image of blue channel is generated on :'+dtime) - f1 = '../flat_Blue_'+str(sigma)+'.fits' - fits.writeto(f1, s1, header=hdu1.header, overwrite=True) + # f1 = '../flat_Blue_'+str(sigma)+'.fits' + # fits.writeto(f1, s1, header=hdu1.header, overwrite=True) - s2 = self.flat_r + # s2 = self.flat_r - hdu1 = fits.PrimaryHDU(s2) + # hdu1 = fits.PrimaryHDU(s2) - hdu1.header.set('sigma', sigma) + # hdu1.header.set('sigma', sigma) - dtime = datetime.utcnow().strftime('%Y -%m -%d %H: %M: %S') - hdu1.header.add_history( - 'flat image of red channel is generated on :'+dtime) + # dtime = datetime.utcnow().strftime('%Y -%m -%d %H: %M: %S') + # hdu1.header.add_history( + # 'flat image of red channel is generated on :'+dtime) - f2 = '../flat_Red_'+str(sigma)+'.fits' - fits.writeto(f2, s2, header=hdu1.header, overwrite=True) + # f2 = '../flat_Red_'+str(sigma)+'.fits' + # fits.writeto(f2, s2, header=hdu1.header, overwrite=True) - return self.flat_b, self.flat_r + # return self.flat_b, self.flat_r ########################################################################## - def addLampFlux(self): - """ + # def addLampFlux(self): + # """ - Returns - ------- - None. + # Returns + # ------- + # None. - """ - """ - Include flux from the calibration source. - """ + # """ + # """ + # Include flux from the calibration source. + # """ - self.image_b += fits.getdata(self.information['flatflux']) - self.image_r += fits.getdata(self.information['flatflux']) + # self.image_b += fits.getdata(self.information['flatflux']) + # self.image_r += fits.getdata(self.information['flatflux']) - self.log.info('Flux from the calibration unit included (%s)' % - self.information['flatflux']) + # self.log.info('Flux from the calibration unit included (%s)' % + # self.information['flatflux']) ############################################################################# def MakeFlatMatrix(self, img, seed): @@ -2111,69 +2111,69 @@ class IFSsimulator(): ########################################################## ######################################################################### - def addReadoutTrails(self): - """ + # def addReadoutTrails(self): + # """ - Returns - ------- - None. + # Returns + # ------- + # None. - """ - """ - Add readout trails resulting from reading out the shutter open. + # """ + # """ + # Add readout trails resulting from reading out the shutter open. - Quadrants assumed to be numbered: - 2 3 - 0 1 - """ - flux_ratio = self.information['readouttime'] / float( - self.information['bluesize']) / self.information['exptime'] - - # make a copy, this will be updated - data = self.image_b.copy() - # Amplifier at different positions depending on the quadrant number ! - # left side is 0, 2 and right side is 1, 3 starting from bottom i.e. - # going clock wise from lower left we have 0, 2, 3, and 1 quadrants. - if self.information['quadrant'] in (2, 3): - data = data[::-1, :] - - data_shift = data.copy() * flux_ratio - size1, size2 = data.shape - - for i in range(1, size2, 1): - data_shift2 = np.roll(data_shift, i, axis=0) - data_shift2[:i, :] = 0.0 - data += data_shift2 - - if self.information['quadrant'] in (2, 3): - self.image_b = data[::-1, :] - else: - self.image_b = data + # Quadrants assumed to be numbered: + # 2 3 + # 0 1 + # """ + # flux_ratio = self.information['readouttime'] / float( + # self.information['bluesize']) / self.information['exptime'] + + # # make a copy, this will be updated + # data = self.image_b.copy() + # # Amplifier at different positions depending on the quadrant number ! + # # left side is 0, 2 and right side is 1, 3 starting from bottom i.e. + # # going clock wise from lower left we have 0, 2, 3, and 1 quadrants. + # if self.information['quadrant'] in (2, 3): + # data = data[::-1, :] + + # data_shift = data.copy() * flux_ratio + # size1, size2 = data.shape + + # for i in range(1, size2, 1): + # data_shift2 = np.roll(data_shift, i, axis=0) + # data_shift2[:i, :] = 0.0 + # data += data_shift2 + + # if self.information['quadrant'] in (2, 3): + # self.image_b = data[::-1, :] + # else: + # self.image_b = data - flux_ratio = self.information['readouttime'] / float( - self.information['redsize']) / self.information['exptime'] - # make a copy, this will be updated - data = self.image_r.copy() - # Amplifier at different positions depending on the quadrant number ! - # left side is 0, 2 and right side is 1, 3 starting from bottom i.e. - # going clock wise from lower left we have 0, 2, 3, and 1 quadrants. - if self.information['quadrant'] in (2, 3): - data = data[::-1, :] - - data_shift = data.copy() * flux_ratio - size1, size2 = data.shape - - for i in range(1, size2, 1): - data_shift2 = np.roll(data_shift, i, axis=0) - data_shift2[:i, :] = 0.0 - data += data_shift2 - - if self.information['quadrant'] in (2, 3): - self.image_r = data[::-1, :] - else: - self.image_r = data + # flux_ratio = self.information['readouttime'] / float( + # self.information['redsize']) / self.information['exptime'] + # # make a copy, this will be updated + # data = self.image_r.copy() + # # Amplifier at different positions depending on the quadrant number ! + # # left side is 0, 2 and right side is 1, 3 starting from bottom i.e. + # # going clock wise from lower left we have 0, 2, 3, and 1 quadrants. + # if self.information['quadrant'] in (2, 3): + # data = data[::-1, :] + + # data_shift = data.copy() * flux_ratio + # size1, size2 = data.shape + + # for i in range(1, size2, 1): + # data_shift2 = np.roll(data_shift, i, axis=0) + # data_shift2[:i, :] = 0.0 + # data += data_shift2 + + # if self.information['quadrant'] in (2, 3): + # self.image_r = data[::-1, :] + # else: + # self.image_r = data ############################################################################## @@ -2259,24 +2259,24 @@ class IFSsimulator(): ########################################################################## - def applyScatteredLight(self): - """ + # def applyScatteredLight(self): + # """ - Returns - ------- - None. + # Returns + # ------- + # None. - """ - """ - Adds spatially uniform scattered light to the image. - """ - sl = self.information['exptime'] * self.information['scattered_light'] + # """ + # """ + # Adds spatially uniform scattered light to the image. + # """ + # sl = self.information['exptime'] * self.information['scattered_light'] - self.image_b += sl - self.image_r += sl + # self.image_b += sl + # self.image_r += sl - self.log.info('Added scattered light = %f' % sl) + # self.log.info('Added scattered light = %f' % sl) ############################################################################## def applyPoissonNoise(self): -- GitLab