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Commit 62c408f8 authored by Yan Zhaojun's avatar Yan Zhaojun
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update

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csst_ifs_sim/csst_ifs_sim.py
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......@@ -356,7 +356,7 @@ class cosmicrays():
exposure time.
"""
def __init__(self, log, image, exposuretime,crInfo=None, information=None):
def __init__(self, log, image, exposuretime, crInfo=None, information=None):
"""
Cosmic ray generation class. Can either draw events from distributions or
set the energy of the events to a constant.
......@@ -376,7 +376,7 @@ class cosmicrays():
# set up the information dictionary, first with defaults and then overwrite with inputs if given
self.information = (dict(cosmicraylengths='/home/yan/csst-master/data/cdf_cr_length.dat',
cosmicraydistance='/home/yan/csst-master/data/cdf_cr_total.dat',exptime=exposuretime))
cosmicraydistance='/home/yan/csst-master/data/cdf_cr_total.dat', exptime=exposuretime))
if information is not None:
self.information.update(information)
......@@ -2157,76 +2157,76 @@ class IFSsimulator():
return FlatMat
####################################################################
def getFrameTransferImg(self):
"""
Returns
-------
None.
"""
"""
get frame transfer image from original image of self.image_b and self.image_r
"""
overscan=320
self.frame_b_4 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_b_3 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_b_2 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_b_1 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_r_4 = np.zeros((1536+overscan, 3072), dtype=float)
self.frame_r_3 = np.zeros((1536+overscan, 3072), dtype=float)
self.frame_r_2 = np.zeros((1536+overscan, 3072), dtype=float)
self.frame_r_1 = np.zeros((1536+overscan, 3072), dtype=float)
# OSH, part2 ,no change
b_2 = np.sum(self.image_b[0:1024, 0:2048], axis=0)
# flip right to left of part1
temp_b_1 = np.fliplr(self.image_b[0:1024, 2048:4096]) # left to right
b_1 = np.sum(temp_b_1, axis=0)
# part 4, left to right and up to down
temp_b_4 = np.fliplr(
self.image_b[1024:1024+1024, 2048:2048+2048]) # left to right
b_4 = np.sum(temp_b_4, axis=0)
# part 3,OSE, up to dwon
b_3 = np.sum(self.image_b[1024:1024+1024, 0:2048], axis=0)
####
for k in range(1024+overscan):
# part
self.frame_b_4[k, :] += b_4*0.09216/self.information['exptime']
self.frame_b_3[k, :] += b_3*0.09216/self.information['exptime']
self.frame_b_2[k, :] += b_2*0.09216/self.information['exptime']
self.frame_b_1[k, :] += b_1*0.09216/self.information['exptime']
###################
# red channle
# OSH, part2 ,no change
r_2 = np.sum(self.image_r[0:1536, 0:3072], axis=0)
# # flip right to left of part1
temp_r_1 = np.fliplr(self.image_r[0:1536, 3072:6144]) # left to right
r_1 = np.sum(temp_r_1, axis=0)
# part 4, left to right and up to down
temp_r_4 = np.fliplr(
self.image_r[1536:1536+1536, 3072:6144]) # left to right
r_4 = np.sum(temp_r_4, axis=0)
# part 3,OSE, up to dwon
r_3 = np.sum(self.image_r[1536:1536+1536, 0:3072], axis=0)
for k in range(1536+overscan):
# part 4, OSH zone;
self.frame_r_4[k, :] += r_4*0.13824/self.information['exptime']
self.frame_r_3[k, :] += r_3*0.13824/self.information['exptime']
self.frame_r_2[k, :] += r_2*0.13824/self.information['exptime']
self.frame_r_1[k, :] += r_1*0.13824/self.information['exptime']
# end
def getFrameTransferImg(self):
"""
Returns
-------
None.
"""
"""
get frame transfer image from original image of self.image_b and self.image_r
"""
overscan=320
self.frame_b_4 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_b_3 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_b_2 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_b_1 = np.zeros((1024+overscan, 2048), dtype=float)
self.frame_r_4 = np.zeros((1536+overscan, 3072), dtype=float)
self.frame_r_3 = np.zeros((1536+overscan, 3072), dtype=float)
self.frame_r_2 = np.zeros((1536+overscan, 3072), dtype=float)
self.frame_r_1 = np.zeros((1536+overscan, 3072), dtype=float)
# OSH, part2 ,no change
b_2 = np.sum(self.image_b[0:1024, 0:2048], axis=0)
# flip right to left of part1
temp_b_1 = np.fliplr(self.image_b[0:1024, 2048:4096]) # left to right
b_1 = np.sum(temp_b_1, axis=0)
# part 4, left to right and up to down
temp_b_4 = np.fliplr(
self.image_b[1024:1024+1024, 2048:2048+2048]) # left to right
b_4 = np.sum(temp_b_4, axis=0)
# part 3,OSE, up to dwon
b_3 = np.sum(self.image_b[1024:1024+1024, 0:2048], axis=0)
####
for k in range(1024+overscan):
# part
self.frame_b_4[k, :] += b_4*0.09216/self.information['exptime']
self.frame_b_3[k, :] += b_3*0.09216/self.information['exptime']
self.frame_b_2[k, :] += b_2*0.09216/self.information['exptime']
self.frame_b_1[k, :] += b_1*0.09216/self.information['exptime']
###################
# red channle
# OSH, part2 ,no change
r_2 = np.sum(self.image_r[0:1536, 0:3072], axis=0)
# # flip right to left of part1
temp_r_1 = np.fliplr(self.image_r[0:1536, 3072:6144]) # left to right
r_1 = np.sum(temp_r_1, axis=0)
# part 4, left to right and up to down
temp_r_4 = np.fliplr(
self.image_r[1536:1536+1536, 3072:6144]) # left to right
r_4 = np.sum(temp_r_4, axis=0)
# part 3,OSE, up to dwon
r_3 = np.sum(self.image_r[1536:1536+1536, 0:3072], axis=0)
for k in range(1536+overscan):
# part 4, OSH zone;
self.frame_r_4[k, :] += r_4*0.13824/self.information['exptime']
self.frame_r_3[k, :] += r_3*0.13824/self.information['exptime']
self.frame_r_2[k, :] += r_2*0.13824/self.information['exptime']
self.frame_r_1[k, :] += r_1*0.13824/self.information['exptime']
# end
###############################################################################
def applyflatfield(self, simnumber):
......
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