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Commit 2c0a9477 authored by Wei Chengliang's avatar Wei Chengliang
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update codestyle-PEP8

parent b8b5bed9
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observation_sim/instruments/chip/effects.py
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...@@ -3,7 +3,8 @@ from matplotlib.pyplot import flag ...@@ -3,7 +3,8 @@ from matplotlib.pyplot import flag
import numpy as np import numpy as np
from numpy.core.fromnumeric import mean, size from numpy.core.fromnumeric import mean, size
from numpy.random import Generator, PCG64 from numpy.random import Generator, PCG64
import math,copy import math
import copy
from numba import jit from numba import jit
from astropy import stats from astropy import stats
...@@ -51,10 +52,10 @@ def DefectivePixels(GSImage, IfHotPix=True, IfDeadPix=True, fraction=1E-4, seed= ...@@ -51,10 +52,10 @@ def DefectivePixels(GSImage, IfHotPix=True, IfDeadPix=True, fraction=1E-4, seed=
NPixHot = int(NPix*fraction*HotFraction) NPixHot = int(NPix*fraction*HotFraction)
NPixDead = NPixBad-NPixHot NPixDead = NPixBad-NPixHot
NPix_y,NPix_x = GSImage.array.shape NPix_y, NPix_x = GSImage.array.shape
mean = np.mean(GSImage.array) mean = np.mean(GSImage.array)
rgp = Generator(PCG64(int(seed))) rgp = Generator(PCG64(int(seed)))
yxposfrac = rgp.random((NPixBad,2)) yxposfrac = rgp.random((NPixBad, 2))
YPositHot = np.array(NPix_y*yxposfrac[0:NPixHot, 0]).astype(np.int32) YPositHot = np.array(NPix_y*yxposfrac[0:NPixHot, 0]).astype(np.int32)
XPositHot = np.array(NPix_x*yxposfrac[0:NPixHot, 1]).astype(np.int32) XPositHot = np.array(NPix_x*yxposfrac[0:NPixHot, 1]).astype(np.int32)
YPositDead = np.array(NPix_y*yxposfrac[NPixHot:, 0]).astype(np.int32) YPositDead = np.array(NPix_y*yxposfrac[NPixHot:, 0]).astype(np.int32)
...@@ -108,7 +109,7 @@ def AddBiasNonUniform16(GSImage, bias_level=500, nsecy=2, nsecx=8, seed=202102, ...@@ -108,7 +109,7 @@ def AddBiasNonUniform16(GSImage, bias_level=500, nsecy=2, nsecx=8, seed=202102,
if int(bias_level) == 0: if int(bias_level) == 0:
BiasLevel = np.zeros((nsecy, nsecx)) BiasLevel = np.zeros((nsecy, nsecx))
elif bias_level > 0: elif bias_level > 0:
BiasLevel = Random16.reshape((nsecy,nsecx)) + bias_level BiasLevel = Random16.reshape((nsecy, nsecx)) + bias_level
if logger is not None: if logger is not None:
msg = str(" Biases of 16 channels: " + str(BiasLevel)) msg = str(" Biases of 16 channels: " + str(BiasLevel))
logger.info(msg) logger.info(msg)
...@@ -129,7 +130,7 @@ def MakeBiasNcomb(npix_x, npix_y, bias_level=500, ncombine=1, read_noise=5, gain ...@@ -129,7 +130,7 @@ def MakeBiasNcomb(npix_x, npix_y, bias_level=500, ncombine=1, read_noise=5, gain
BiasSngImg0 = galsim.Image(npix_x, npix_y, init_value=0) BiasSngImg0 = galsim.Image(npix_x, npix_y, init_value=0)
BiasSngImg = AddBiasNonUniform16(BiasSngImg0, BiasSngImg = AddBiasNonUniform16(BiasSngImg0,
bias_level=bias_level, bias_level=bias_level,
nsecy = 2, nsecx=8, nsecy=2, nsecx=8,
seed=int(seed), seed=int(seed),
logger=logger) logger=logger)
BiasCombImg = BiasSngImg*ncombine BiasCombImg = BiasSngImg*ncombine
...@@ -198,7 +199,7 @@ def MakeFlatSmooth(GSBounds, seed): ...@@ -198,7 +199,7 @@ def MakeFlatSmooth(GSBounds, seed):
xmin, xmax, ymin, ymax = GSBounds.getXMin(), GSBounds.getXMax(), GSBounds.getYMin(), GSBounds.getYMax() xmin, xmax, ymin, ymax = GSBounds.getXMin(), GSBounds.getXMax(), GSBounds.getYMin(), GSBounds.getYMax()
Flty, Fltx = np.mgrid[ymin:(ymax+1), xmin:(xmax+1)] Flty, Fltx = np.mgrid[ymin:(ymax+1), xmin:(xmax+1)]
rg = Generator(PCG64(int(seed))) rg = Generator(PCG64(int(seed)))
p1, p2, bg=rg.poisson(1000, 3) p1, p2, bg = rg.poisson(1000, 3)
Fltz = 0.6*1e-7*(a1 * (Fltx-p1) ** 2 + a2 * (Flty-p2) ** 2 - a3*Fltx - a4*Flty) + bg*20 Fltz = 0.6*1e-7*(a1 * (Fltx-p1) ** 2 + a2 * (Flty-p2) ** 2 - a3*Fltx - a4*Flty) + bg*20
FlatImg = galsim.ImageF(Fltz) FlatImg = galsim.ImageF(Fltz)
return FlatImg return FlatImg
...@@ -245,7 +246,7 @@ def MakeDarkNcomb(npix_x, npix_y, overscan=500, bias_level=500, seed_bias=202102 ...@@ -245,7 +246,7 @@ def MakeDarkNcomb(npix_x, npix_y, overscan=500, bias_level=500, seed_bias=202102
DarkCombImg = AddBiasNonUniform16( DarkCombImg = AddBiasNonUniform16(
DarkCombImg, DarkCombImg,
bias_level=bias_level, bias_level=bias_level,
nsecy = 2, nsecx=8, nsecy=2, nsecx=8,
seed=int(seed_bias), seed=int(seed_bias),
logger=logger) logger=logger)
if ncombine == 1: if ncombine == 1:
...@@ -272,7 +273,7 @@ def NonLinearity(GSImage, beta1=5E-7, beta2=0): ...@@ -272,7 +273,7 @@ def NonLinearity(GSImage, beta1=5E-7, beta2=0):
return GSImage return GSImage
#Saturation & Bleeding Start# # Saturation & Bleeding Start#
def BleedingTrail(aa, yy): def BleedingTrail(aa, yy):
if aa < 0.2: if aa < 0.2:
aa = 0.2 aa = 0.2
...@@ -280,7 +281,7 @@ def BleedingTrail(aa, yy): ...@@ -280,7 +281,7 @@ def BleedingTrail(aa, yy):
pass pass
try: try:
fy = 0.5*(math.exp(math.log(yy+1)**3/aa)+np.exp(-1*math.log(yy+1)**3/aa)) fy = 0.5*(math.exp(math.log(yy+1)**3/aa)+np.exp(-1*math.log(yy+1)**3/aa))
faa= 0.5*(math.e+1/math.e) faa = 0.5*(math.e+1/math.e)
trail_frac = 1-0.1*(fy-1)/(faa-1) trail_frac = 1-0.1*(fy-1)/(faa-1)
except Exception as e: except Exception as e:
print(e) print(e)
...@@ -306,14 +307,14 @@ def MakeTrail(imgarr, satuyxtuple, charge, fullwell=9e4, direction='up', trailcu ...@@ -306,14 +307,14 @@ def MakeTrail(imgarr, satuyxtuple, charge, fullwell=9e4, direction='up', trailcu
if direction == 'up': if direction == 'up':
if imgarr[yi-1, xi] >= fullwell: if imgarr[yi-1, xi] >= fullwell:
imgarr[yi, xi] = fullwell imgarr[yi, xi] = fullwell
yi-=1 yi -= 1
continue continue
elif direction == 'down': elif direction == 'down':
if imgarr[yi+1, xi] >= fullwell: if imgarr[yi+1, xi] >= fullwell:
imgarr[yi, xi] = fullwell imgarr[yi, xi] = fullwell
yi += 1 yi += 1
continue continue
if aa<=1: if aa <= 1:
while imgarr[yi, xi] >= fullwell: while imgarr[yi, xi] >= fullwell:
imgarr[yi, xi] = fullwell imgarr[yi, xi] = fullwell
if direction == 'up': if direction == 'up':
...@@ -359,9 +360,9 @@ def MakeTrail(imgarr, satuyxtuple, charge, fullwell=9e4, direction='up', trailcu ...@@ -359,9 +360,9 @@ def MakeTrail(imgarr, satuyxtuple, charge, fullwell=9e4, direction='up', trailcu
def ChargeFlow(imgarr, fullwell=9E4): def ChargeFlow(imgarr, fullwell=9E4):
size_y, size_x = imgarr.shape size_y, size_x = imgarr.shape
satupos_y, satupos_x = np.where(imgarr>fullwell) satupos_y, satupos_x = np.where(imgarr > fullwell)
if satupos_y.shape[0]==0: if satupos_y.shape[0] == 0:
# make no change for the image array # make no change for the image array
return imgarr return imgarr
elif satupos_y.shape[0]/imgarr.size > 0.5: elif satupos_y.shape[0]/imgarr.size > 0.5:
...@@ -383,16 +384,16 @@ def ChargeFlow(imgarr, fullwell=9E4): ...@@ -383,16 +384,16 @@ def ChargeFlow(imgarr, fullwell=9E4):
try: try:
# Charge Clump moves up # Charge Clump moves up
if yi>=0 and yi<imgarr.shape[0]: if yi >= 0 and yi < imgarr.shape[0]:
imgarr = MakeTrail(imgarr, (yi, xi), chargeup, fullwell=9e4, direction='up', trailcutfrac=0.9) imgarr = MakeTrail(imgarr, (yi, xi), chargeup, fullwell=9e4, direction='up', trailcutfrac=0.9)
# Charge Clump moves down # Charge Clump moves down
imgarr = MakeTrail(imgarr, (yi, xi), chargedn, fullwell=9e4, direction='down', trailcutfrac=0.9) imgarr = MakeTrail(imgarr, (yi, xi), chargedn, fullwell=9e4, direction='down', trailcutfrac=0.9)
except Exception as e: except Exception as e:
print(e,'@pix ',(yi+1, xi+1)) print(e, '@pix ', (yi+1, xi+1))
return imgarr return imgarr
return imgarr return imgarr
def SaturBloom(GSImage, nsect_x=1, nsect_y=1, fullwell=9e4): def SaturBloom(GSImage, nsect_x=1, nsect_y=1, fullwell=9e4):
""" """
To simulate digital detector's saturation and blooming effect. The blooming is along the read-out direction, perpendicular to the charge transfer direction. Charge clumpy overflows the pixel well will flow to two oposite directions with nearly same charges. To simulate digital detector's saturation and blooming effect. The blooming is along the read-out direction, perpendicular to the charge transfer direction. Charge clumpy overflows the pixel well will flow to two oposite directions with nearly same charges.
...@@ -453,7 +454,7 @@ def readout16(GSImage, rowi=0, coli=0, overscan_value=0): ...@@ -453,7 +454,7 @@ def readout16(GSImage, rowi=0, coli=0, overscan_value=0):
subbounds = galsim.BoundsI(npix_x/2+1, npix_x, npix_y/8*rowi+1, npix_y/8*(rowi+1)) subbounds = galsim.BoundsI(npix_x/2+1, npix_x, npix_y/8*rowi+1, npix_y/8*(rowi+1))
subbounds = subbounds.shift(galsim.PositionI(GSImage.bounds.getXMin()-1, GSImage.bounds.getYMin()-1)) subbounds = subbounds.shift(galsim.PositionI(GSImage.bounds.getXMin()-1, GSImage.bounds.getYMin()-1))
subimg = GSImage[subbounds] subimg = GSImage[subbounds]
OutputSubimg.array[16 :int(npix_y/8)+16, 8:int(npix_x/2)+8] = subimg.array OutputSubimg.array[16:int(npix_y/8)+16, 8:int(npix_x/2)+8] = subimg.array
else: else:
print("\n\033[31mError: "+"Wrong rowi or coli assignment. Permitted: 0<=rowi<=7, 0<=coli<=1."+"\033[0m\n") print("\n\033[31mError: "+"Wrong rowi or coli assignment. Permitted: 0<=rowi<=7, 0<=coli<=1."+"\033[0m\n")
return OutputSubimg return OutputSubimg
...@@ -469,19 +470,19 @@ def CTE_Effect(GSImage, threshold=27, direction='column'): ...@@ -469,19 +470,19 @@ def CTE_Effect(GSImage, threshold=27, direction='column'):
imgarr = GSImage.array imgarr = GSImage.array
if direction == 'column': if direction == 'column':
imgarr[0:size_sect_y, :] = CTEModelColRow(imgarr[0:size_sect_y, :], trail_direction='down', direction='column', threshold=threshold) imgarr[0:size_sect_y, :] = CTEModelColRow(imgarr[0:size_sect_y, :], trail_direction='down', direction='column', threshold=threshold)
imgarr[size_sect_y:size_y, :] = CTEModelColRow(imgarr[size_sect_y:size_y,:], trail_direction='up', direction='column', threshold=threshold) imgarr[size_sect_y:size_y, :] = CTEModelColRow(imgarr[size_sect_y:size_y, :], trail_direction='up', direction='column', threshold=threshold)
elif direction == 'row': elif direction == 'row':
imgarr[:,0:size_sect_x] = CTEModelColRow(imgarr[:,0:size_sect_x], trail_direction='right', direction='row', threshold=threshold) imgarr[:, 0:size_sect_x] = CTEModelColRow(imgarr[:, 0:size_sect_x], trail_direction='right', direction='row', threshold=threshold)
imgarr[:,size_sect_x:size_x] = CTEModelColRow(imgarr[:,size_sect_x:size_x], trail_direction='left', direction='row', threshold=threshold) imgarr[:, size_sect_x:size_x] = CTEModelColRow(imgarr[:, size_sect_x:size_x], trail_direction='left', direction='row', threshold=threshold)
return GSImage return GSImage
@jit() @jit()
def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27): def CTEModelColRow(img, trail_direction='up', direction='column', threshold=27):
#total trail flux vs (pixel flux)^1/2 is approximately linear # total trail flux vs (pixel flux)^1/2 is approximately linear
#total trail flux = trail_a * (pixel flux)^1/2 + trail_b # total trail flux = trail_a * (pixel flux)^1/2 + trail_b
#trail pixel flux = pow(0.5,x)/0.5, normalize to 1 # trail pixel flux = pow(0.5,x)/0.5, normalize to 1
trail_a = 5.651803799619966 trail_a = 5.651803799619966
trail_b = -2.671933068990729 trail_b = -2.671933068990729
...@@ -491,7 +492,7 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27 ...@@ -491,7 +492,7 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27
idx = np.where(img < threshold) idx = np.where(img < threshold)
if len(idx[0]) == 0: if len(idx[0]) == 0:
pass pass
elif len(idx[0])>0: elif len(idx[0]) > 0:
n_img[idx] = img[idx] n_img[idx] = img[idx]
yidx, xidx = np.where(img >= threshold) yidx, xidx = np.where(img >= threshold)
...@@ -530,12 +531,8 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27 ...@@ -530,12 +531,8 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27
all_trail_pix += t_pow all_trail_pix += t_pow
all_trail[m] = t_pow all_trail[m] = t_pow
trail_pix_eff = trail_f/all_trail_pix trail_pix_eff = trail_f/all_trail_pix
all_trail = trail_pix_eff*all_trail all_trail = trail_pix_eff*all_trail
all_trail[0] = f - trail_f all_trail[0] = f - trail_f
for m in np.arange(0, xy_num, 1): for m in np.arange(0, xy_num, 1):
...@@ -559,10 +556,8 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27 ...@@ -559,10 +556,8 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27
return n_img return n_img
# ---------- For Cosmic-Ray Simulation ------------
#---------- For Cosmic-Ray Simulation ------------ # ---------- Zhang Xin ----------------------------
#---------- Zhang Xin ----------------------------
def getYValue(collection, x): def getYValue(collection, x):
index = 0; index = 0;
if (collection.shape[1] == 2): if (collection.shape[1] == 2):
......
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