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

parent e985dd75
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csst_ifs_sim/csst_ifs_sim.py
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......@@ -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):
"""
Returns
-------
None.
"""
"""
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
# def addReadoutTrails(self):
# """
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
# Returns
# -------
# None.
for i in range(1, size2, 1):
data_shift2 = np.roll(data_shift, i, axis=0)
data_shift2[:i, :] = 0.0
data += data_shift2
# """
# """
# Add readout trails resulting from reading out the shutter open.
if self.information['quadrant'] in (2, 3):
self.image_r = data[::-1, :]
else:
self.image_r = 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
##############################################################################
......@@ -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):
......
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