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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
import numpy as np
from numpy.core.fromnumeric import mean, size
from numpy.random import Generator, PCG64
import math,copy
import math
import copy
from numba import jit
from astropy import stats
......@@ -51,10 +52,10 @@ def DefectivePixels(GSImage, IfHotPix=True, IfDeadPix=True, fraction=1E-4, seed=
NPixHot = int(NPix*fraction*HotFraction)
NPixDead = NPixBad-NPixHot
NPix_y,NPix_x = GSImage.array.shape
NPix_y, NPix_x = GSImage.array.shape
mean = np.mean(GSImage.array)
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)
XPositHot = np.array(NPix_x*yxposfrac[0:NPixHot, 1]).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,
if int(bias_level) == 0:
BiasLevel = np.zeros((nsecy, nsecx))
elif bias_level > 0:
BiasLevel = Random16.reshape((nsecy,nsecx)) + bias_level
BiasLevel = Random16.reshape((nsecy, nsecx)) + bias_level
if logger is not None:
msg = str(" Biases of 16 channels: " + str(BiasLevel))
logger.info(msg)
......@@ -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)
BiasSngImg = AddBiasNonUniform16(BiasSngImg0,
bias_level=bias_level,
nsecy = 2, nsecx=8,
nsecy=2, nsecx=8,
seed=int(seed),
logger=logger)
BiasCombImg = BiasSngImg*ncombine
......@@ -198,7 +199,7 @@ def MakeFlatSmooth(GSBounds, seed):
xmin, xmax, ymin, ymax = GSBounds.getXMin(), GSBounds.getXMax(), GSBounds.getYMin(), GSBounds.getYMax()
Flty, Fltx = np.mgrid[ymin:(ymax+1), xmin:(xmax+1)]
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
FlatImg = galsim.ImageF(Fltz)
return FlatImg
......@@ -245,7 +246,7 @@ def MakeDarkNcomb(npix_x, npix_y, overscan=500, bias_level=500, seed_bias=202102
DarkCombImg = AddBiasNonUniform16(
DarkCombImg,
bias_level=bias_level,
nsecy = 2, nsecx=8,
nsecy=2, nsecx=8,
seed=int(seed_bias),
logger=logger)
if ncombine == 1:
......@@ -272,7 +273,7 @@ def NonLinearity(GSImage, beta1=5E-7, beta2=0):
return GSImage
#Saturation & Bleeding Start#
# Saturation & Bleeding Start#
def BleedingTrail(aa, yy):
if aa < 0.2:
aa = 0.2
......@@ -280,7 +281,7 @@ def BleedingTrail(aa, yy):
pass
try:
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)
except Exception as e:
print(e)
......@@ -306,14 +307,14 @@ def MakeTrail(imgarr, satuyxtuple, charge, fullwell=9e4, direction='up', trailcu
if direction == 'up':
if imgarr[yi-1, xi] >= fullwell:
imgarr[yi, xi] = fullwell
yi-=1
yi -= 1
continue
elif direction == 'down':
if imgarr[yi+1, xi] >= fullwell:
imgarr[yi, xi] = fullwell
yi += 1
continue
if aa<=1:
if aa <= 1:
while imgarr[yi, xi] >= fullwell:
imgarr[yi, xi] = fullwell
if direction == 'up':
......@@ -359,9 +360,9 @@ def MakeTrail(imgarr, satuyxtuple, charge, fullwell=9e4, direction='up', trailcu
def ChargeFlow(imgarr, fullwell=9E4):
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
return imgarr
elif satupos_y.shape[0]/imgarr.size > 0.5:
......@@ -383,16 +384,16 @@ def ChargeFlow(imgarr, fullwell=9E4):
try:
# 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)
# Charge Clump moves down
imgarr = MakeTrail(imgarr, (yi, xi), chargedn, fullwell=9e4, direction='down', trailcutfrac=0.9)
except Exception as e:
print(e,'@pix ',(yi+1, xi+1))
print(e, '@pix ', (yi+1, xi+1))
return imgarr
return imgarr
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.
......@@ -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 = subbounds.shift(galsim.PositionI(GSImage.bounds.getXMin()-1, GSImage.bounds.getYMin()-1))
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:
print("\n\033[31mError: "+"Wrong rowi or coli assignment. Permitted: 0<=rowi<=7, 0<=coli<=1."+"\033[0m\n")
return OutputSubimg
......@@ -469,19 +470,19 @@ def CTE_Effect(GSImage, threshold=27, direction='column'):
imgarr = GSImage.array
if direction == 'column':
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':
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[:, 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)
return GSImage
@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 = trail_a * (pixel flux)^1/2 + trail_b
#trail pixel flux = pow(0.5,x)/0.5, normalize to 1
# total trail flux vs (pixel flux)^1/2 is approximately linear
# total trail flux = trail_a * (pixel flux)^1/2 + trail_b
# trail pixel flux = pow(0.5,x)/0.5, normalize to 1
trail_a = 5.651803799619966
trail_b = -2.671933068990729
......@@ -491,7 +492,7 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27
idx = np.where(img < threshold)
if len(idx[0]) == 0:
pass
elif len(idx[0])>0:
elif len(idx[0]) > 0:
n_img[idx] = img[idx]
yidx, xidx = np.where(img >= threshold)
......@@ -530,12 +531,8 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27
all_trail_pix += t_pow
all_trail[m] = t_pow
trail_pix_eff = trail_f/all_trail_pix
all_trail = trail_pix_eff*all_trail
all_trail[0] = f - trail_f
for m in np.arange(0, xy_num, 1):
......@@ -559,10 +556,8 @@ def CTEModelColRow(img, trail_direction = 'up', direction='column', threshold=27
return n_img
#---------- For Cosmic-Ray Simulation ------------
#---------- Zhang Xin ----------------------------
# ---------- For Cosmic-Ray Simulation ------------
# ---------- Zhang Xin ----------------------------
def getYValue(collection, x):
index = 0;
if (collection.shape[1] == 2):
......
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