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Commit b4201fbc authored by Yan Zhaojun's avatar Yan Zhaojun
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more case test

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csst_ifs_sim/csst_ifs_sim.py
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...@@ -117,50 +117,50 @@ def transRaDec2D(ra, dec): ...@@ -117,50 +117,50 @@ def transRaDec2D(ra, dec):
############################################################################### ###############################################################################
def flux2ill(wave, flux): # def flux2ill(wave, flux):
""" # """
Parameters # Parameters
---------- # ----------
wave : TYPE # wave : TYPE
DESCRIPTION. # DESCRIPTION.
flux : TYPE # flux : TYPE
DESCRIPTION. # DESCRIPTION.
Returns # Returns
------- # -------
E : TYPE # E : TYPE
DESCRIPTION. # 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 W/m^2/sr/μm = 0.10 erg/cm^2/s/sr/A
# 1 sr = 1 rad^2 = 4.25452e10 arcsec^2 # # 1 sr = 1 rad^2 = 4.25452e10 arcsec^2
# 1 J/s = 1 W # # 1 J/s = 1 W
# 1 J = 10^7 erg # # 1 J = 10^7 erg
# convert erg/s/cm^2/A/arcsec^2 to erg/s/cm^2/A/sr # # convert erg/s/cm^2/A/arcsec^2 to erg/s/cm^2/A/sr
flux1 = flux / (1/4.25452e10) # flux1 = flux / (1/4.25452e10)
# convert erg/s/cm^2/A/sr to W/m^2/sr/um # # convert erg/s/cm^2/A/sr to W/m^2/sr/um
flux2 = flux1 * 10 # flux2 = flux1 * 10
# 对接收面积积分，输出单位 W/m^2/nm # # 对接收面积积分，输出单位 W/m^2/nm
D = 2 # meter # D = 2 # meter
f = 28 # meter # f = 28 # meter
flux3 = flux2 * np.pi * D**2 / 4 / f**2 / 10**3 # flux3 = flux2 * np.pi * D**2 / 4 / f**2 / 10**3
# 对波长积分 # # 对波长积分
f = interp1d(wave, flux3) # f = interp1d(wave, flux3)
wave_interp = np.arange(3800, 7800) # wave_interp = np.arange(3800, 7800)
flux3_interp = f(wave_interp) # flux3_interp = f(wave_interp)
# 输出单位 W/m^2 # # 输出单位 W/m^2
delta_lamba = 0.1 # nm # delta_lamba = 0.1 # nm
E = np.sum(flux3_interp * delta_lamba) # E = np.sum(flux3_interp * delta_lamba)
return E # return E
################################################################ ################################################################
...@@ -391,25 +391,25 @@ class StrayLight(object): ...@@ -391,25 +391,25 @@ class StrayLight(object):
############################################################################### ###############################################################################
def str2time(strTime): # def str2time(strTime):
""" # """
Parameters # Parameters
---------- # ----------
strTime : TYPE # strTime : TYPE
DESCRIPTION. # DESCRIPTION.
Returns # Returns
------- # -------
TYPE # TYPE
DESCRIPTION. # DESCRIPTION.
""" # """
if len(strTime) > 20: # 暂时未用到 # if len(strTime) > 20: # 暂时未用到
msec = int(float('0.'+strTime[20:])*1000000) # 微秒 # msec = int(float('0.'+strTime[20:])*1000000) # 微秒
str2 = strTime[0:19]+' '+str(msec) # str2 = strTime[0:19]+' '+str(msec)
return datetime.strptime(str2, '%Y %m %d %H %M %S %f') # return datetime.strptime(str2, '%Y %m %d %H %M %S %f')
# datetime类转mjd # datetime类转mjd
########################################################################## ##########################################################################
...@@ -822,40 +822,40 @@ def centroid(data): ...@@ -822,40 +822,40 @@ def centroid(data):
return float(cx), float(cy) return float(cx), float(cy)
############################################################################### ###############################################################################
def centroidN(data): # def centroidN(data):
""" # """
Parameters # Parameters
---------- # ----------
data : TYPE # data : TYPE
DESCRIPTION. # DESCRIPTION.
Returns # Returns
------- # -------
cx : TYPE # cx : TYPE
DESCRIPTION. # DESCRIPTION.
cy : TYPE # cy : TYPE
DESCRIPTION. # DESCRIPTION.
""" # """
''' # '''
calculate the centroid of the input two-dimentional image data # calculate the centroid of the input two-dimentional image data
Parameters # Parameters
---------- # ----------
data : input image. # data : input image.
Returns # Returns
------- # -------
cx: the centroid column number, in horizontal direction definet in python image show # cx: the centroid column number, in horizontal direction definet in python image show
cy: the centroid row number , in vertical direction # cy: the centroid row number , in vertical direction
''' # '''
### # ###
from scipy import ndimage # from scipy import ndimage
cy, cx = ndimage.center_of_mass(data) # cy, cx = ndimage.center_of_mass(data)
return cx, cy # return cx, cy
#################################################################### ####################################################################
...@@ -1494,42 +1494,42 @@ class IFSsimulator(): ...@@ -1494,42 +1494,42 @@ class IFSsimulator():
return wave_A, spec_erg2 return wave_A, spec_erg2
########################################################################## ##########################################################################
def smoothingWithChargeDiffusion(self, image, sigma=(0.32, 0.32)): # def smoothingWithChargeDiffusion(self, image, sigma=(0.32, 0.32)):
""" # """
Parameters # Parameters
---------- # ----------
image : TYPE # image : TYPE
DESCRIPTION. # DESCRIPTION.
sigma : TYPE, optional # sigma : TYPE, optional
DESCRIPTION. The default is (0.32, 0.32). # DESCRIPTION. The default is (0.32, 0.32).
Returns # Returns
------- # -------
TYPE # TYPE
DESCRIPTION. # DESCRIPTION.
""" # """
""" # """
Smooths a given image with a gaussian kernel with widths given as sigmas. # 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. # 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 # 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. # 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 # .. 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. # has already been taken into account in the system PSF to avoid double counting.
:param image: image array which is smoothed with the kernel # :param image: image array which is smoothed with the kernel
:type image: ndarray # :type image: ndarray
:param sigma: widths of the gaussian kernel that approximates the charge diffusion [0.32, 0.32]. # :param sigma: widths of the gaussian kernel that approximates the charge diffusion [0.32, 0.32].
:param sigma: tuple # :param sigma: tuple
:return: smoothed image array # :return: smoothed image array
:rtype: ndarray # :rtype: ndarray
""" # """
return ndimage.filters.gaussian_filter(image, sigma) # return ndimage.filters.gaussian_filter(image, sigma)
############################################################################### ###############################################################################
def readCosmicRayInformation(self): def readCosmicRayInformation(self):
...@@ -1835,88 +1835,88 @@ class IFSsimulator(): ...@@ -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 # Parameters
---------- # ----------
ave : TYPE, optional # ave : TYPE, optional
DESCRIPTION. The default is 1.0. # DESCRIPTION. The default is 1.0.
sigma : TYPE, optional # sigma : TYPE, optional
DESCRIPTION. The default is 0.01. # DESCRIPTION. The default is 0.01.
Returns # Returns
------- # -------
TYPE # TYPE
DESCRIPTION. # DESCRIPTION.
TYPE # TYPE
DESCRIPTION. # DESCRIPTION.
""" # """
""" # """
Creates a flat field image with given properties. # Creates a flat field image with given properties.
:return: flat field image # :return: flat field image
:rtype: ndarray # :rtype: ndarray
""" # """
self.log.info('Generating a flat field...') # 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) # 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) # np.random.seed(5*self.simnumber)
self.flat_b = np.random.normal(loc=ave, scale=sigma, size=(2048, 4096)) # self.flat_b = np.random.normal(loc=ave, scale=sigma, size=(2048, 4096))
np.random.seed(55*self.simnumber) # np.random.seed(55*self.simnumber)
self.flat_r = np.random.normal(loc=ave, scale=sigma, size=(3072, 6144)) # 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') # dtime = datetime.utcnow().strftime('%Y -%m -%d %H: %M: %S')
hdu1.header.add_history( # hdu1.header.add_history(
'flat image of blue channel is generated on :'+dtime) # 'flat image of blue channel is generated on :'+dtime)
f1 = '../flat_Blue_'+str(sigma)+'.fits' # f1 = '../flat_Blue_'+str(sigma)+'.fits'
fits.writeto(f1, s1, header=hdu1.header, overwrite=True) # 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') # dtime = datetime.utcnow().strftime('%Y -%m -%d %H: %M: %S')
hdu1.header.add_history( # hdu1.header.add_history(
'flat image of red channel is generated on :'+dtime) # 'flat image of red channel is generated on :'+dtime)
f2 = '../flat_Red_'+str(sigma)+'.fits' # f2 = '../flat_Red_'+str(sigma)+'.fits'
fits.writeto(f2, s2, header=hdu1.header, overwrite=True) # 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 # Returns
------- # -------
None. # None.
""" # """
""" # """
Include flux from the calibration source. # Include flux from the calibration source.
""" # """
self.image_b += fits.getdata(self.information['flatflux']) # self.image_b += fits.getdata(self.information['flatflux'])
self.image_r += fits.getdata(self.information['flatflux']) # self.image_r += fits.getdata(self.information['flatflux'])
self.log.info('Flux from the calibration unit included (%s)' % # self.log.info('Flux from the calibration unit included (%s)' %
self.information['flatflux']) # self.information['flatflux'])
############################################################################# #############################################################################
def MakeFlatMatrix(self, img, seed): def MakeFlatMatrix(self, img, seed):
...@@ -2111,69 +2111,69 @@ class IFSsimulator(): ...@@ -2111,69 +2111,69 @@ class IFSsimulator():
########################################################## ##########################################################
######################################################################### #########################################################################
def addReadoutTrails(self): # def addReadoutTrails(self):
""" # """
Returns # Returns
------- # -------
None. # 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: # Quadrants assumed to be numbered:
2 3 # 2 3
0 1 # 0 1
""" # """
flux_ratio = self.information['readouttime'] / float( # flux_ratio = self.information['readouttime'] / float(
self.information['bluesize']) / self.information['exptime'] # self.information['bluesize']) / self.information['exptime']
# make a copy, this will be updated # # make a copy, this will be updated
data = self.image_b.copy() # data = self.image_b.copy()
# Amplifier at different positions depending on the quadrant number ! # # 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. # # 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. # # going clock wise from lower left we have 0, 2, 3, and 1 quadrants.
if self.information['quadrant'] in (2, 3): # if self.information['quadrant'] in (2, 3):
data = data[::-1, :] # data = data[::-1, :]
data_shift = data.copy() * flux_ratio # data_shift = data.copy() * flux_ratio
size1, size2 = data.shape # size1, size2 = data.shape
for i in range(1, size2, 1): # for i in range(1, size2, 1):
data_shift2 = np.roll(data_shift, i, axis=0) # data_shift2 = np.roll(data_shift, i, axis=0)
data_shift2[:i, :] = 0.0 # data_shift2[:i, :] = 0.0
data += data_shift2 # data += data_shift2
if self.information['quadrant'] in (2, 3): # if self.information['quadrant'] in (2, 3):
self.image_b = data[::-1, :] # self.image_b = data[::-1, :]
else: # else:
self.image_b = data # self.image_b = data
flux_ratio = self.information['readouttime'] / float( # flux_ratio = self.information['readouttime'] / float(
self.information['redsize']) / self.information['exptime'] # self.information['redsize']) / self.information['exptime']
# make a copy, this will be updated # # make a copy, this will be updated
data = self.image_r.copy() # data = self.image_r.copy()
# Amplifier at different positions depending on the quadrant number ! # # 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. # # 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. # # going clock wise from lower left we have 0, 2, 3, and 1 quadrants.
if self.information['quadrant'] in (2, 3): # if self.information['quadrant'] in (2, 3):
data = data[::-1, :] # data = data[::-1, :]
data_shift = data.copy() * flux_ratio # data_shift = data.copy() * flux_ratio
size1, size2 = data.shape # size1, size2 = data.shape
for i in range(1, size2, 1): # for i in range(1, size2, 1):
data_shift2 = np.roll(data_shift, i, axis=0) # data_shift2 = np.roll(data_shift, i, axis=0)
data_shift2[:i, :] = 0.0 # data_shift2[:i, :] = 0.0
data += data_shift2 # data += data_shift2
if self.information['quadrant'] in (2, 3): # if self.information['quadrant'] in (2, 3):
self.image_r = data[::-1, :] # self.image_r = data[::-1, :]
else: # else:
self.image_r = data # self.image_r = data
############################################################################## ##############################################################################
...@@ -2259,24 +2259,24 @@ class IFSsimulator(): ...@@ -2259,24 +2259,24 @@ class IFSsimulator():
########################################################################## ##########################################################################
def applyScatteredLight(self): # def applyScatteredLight(self):
""" # """
Returns # Returns
------- # -------
None. # None.
""" # """
""" # """
Adds spatially uniform scattered light to the image. # Adds spatially uniform scattered light to the image.
""" # """
sl = self.information['exptime'] * self.information['scattered_light'] # sl = self.information['exptime'] * self.information['scattered_light']
self.image_b += sl # self.image_b += sl
self.image_r += sl # self.image_r += sl
self.log.info('Added scattered light = %f' % sl) # self.log.info('Added scattered light = %f' % sl)
############################################################################## ##############################################################################
def applyPoissonNoise(self): def applyPoissonNoise(self):
......
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