Commit 81e2570f authored by Zhang Xin's avatar Zhang Xin
Browse files

fix unittest for ccd Effect model

parent 042e5887
...@@ -6,18 +6,28 @@ import matplotlib.pyplot as plt ...@@ -6,18 +6,28 @@ import matplotlib.pyplot as plt
import os,sys,math,copy import os,sys,math,copy
from numpy.random import Generator, PCG64 from numpy.random import Generator, PCG64
import warnings import warnings
from astropy.io import fits
warnings.filterwarnings("ignore", '.*Numba.*',) warnings.filterwarnings("ignore", '.*Numba.*',)
width = 9216 width = 9216
height = 9232 height = 9232
if os.path.isdir('./output/'):
pass
else:
os.mkdir('./output/')
class DetTest(unittest.TestCase): class DetTest(unittest.TestCase):
def __init__(self, methodName='runTest'):
super(DetTest,self).__init__(methodName)
self.filePath('csst_fz_gc0')
def filePath(self, file_name):
self.datafn = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), file_name)
self.outDataFn = os.path.join(self.datafn,'output')
if os.path.isdir(self.outDataFn):
pass
else:
os.mkdir(self.outDataFn)
def test_prnu(self): def test_prnu(self):
''' '''
Unit test for PRNU. Expected result: a randomized GS image contains PRNU with sigma=0.01, mean=1. Unit test for PRNU. Expected result: a randomized GS image contains PRNU with sigma=0.01, mean=1.
...@@ -64,12 +74,12 @@ class DetTest(unittest.TestCase): ...@@ -64,12 +74,12 @@ class DetTest(unittest.TestCase):
img.addNoise(galsim.GaussianNoise(sigma=7)) img.addNoise(galsim.GaussianNoise(sigma=7))
# plt.imshow(img.array) # plt.imshow(img.array)
# plt.show() # plt.show()
filename1 = os.path.join('output','test_satu_initimg.fits') filename1 = os.path.join(self.outDataFn,'test_satu_initimg.fits')
img.write(filename1) img.write(filename1)
newimg = Effects.SaturBloom(img, fullwell=9e4) newimg = Effects.SaturBloom(img, fullwell=9e4)
# plt.imshow(newimg.array) # plt.imshow(newimg.array)
# plt.show() # plt.show()
filename2 = os.path.join('output','test_satu_bleedimg.fits') filename2 = os.path.join(self.outDataFn,'test_satu_bleedimg.fits')
newimg.write(filename2) newimg.write(filename2)
del img,newimg, star del img,newimg, star
...@@ -79,16 +89,16 @@ class DetTest(unittest.TestCase): ...@@ -79,16 +89,16 @@ class DetTest(unittest.TestCase):
''' '''
imgarr = np.arange(1,9e4,4).reshape((150,150)) imgarr = np.arange(1,9e4,4).reshape((150,150))
img = galsim.Image(copy.deepcopy(imgarr)) img = galsim.Image(copy.deepcopy(imgarr))
filename1 = os.path.join('output','test_nonlinear_initimg.fits') filename1 = os.path.join(self.outDataFn,'test_nonlinear_initimg.fits')
img.write(filename1) img.write(filename1)
newimg = Effects.NonLinearity(img, beta1=5E-7, beta2=0) newimg = Effects.NonLinearity(img, beta1=5E-7, beta2=0)
filename2 = os.path.join('output','test_nonlinear_finalimg.fits') filename2 = os.path.join(self.outDataFn,'test_nonlinear_finalimg.fits')
newimg.write(filename2) newimg.write(filename2)
plt.scatter(imgarr.flatten(), newimg.array.flatten(), s=2, alpha=0.5) plt.scatter(imgarr.flatten(), newimg.array.flatten(), s=2, alpha=0.5)
plt.plot([-1e3,9e4],[-1e3,9e4],color='black', lw=1, ls='--') plt.plot([-1e3,9e4],[-1e3,9e4],color='black', lw=1, ls='--')
plt.xlabel('input (e-)') plt.xlabel('input (e-)')
plt.ylabel('output (e-)') plt.ylabel('output (e-)')
plt.savefig('./output/test_nonlinearity.png', dpi=200) plt.savefig(os.path.join(self.outDataFn,'test_nonlinearity.png'), dpi=200)
plt.show() plt.show()
del img,newimg,imgarr del img,newimg,imgarr
...@@ -97,35 +107,35 @@ class DetTest(unittest.TestCase): ...@@ -97,35 +107,35 @@ class DetTest(unittest.TestCase):
rgbadpix = Generator(PCG64(20210911)) rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7) badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
img = Effects.DefectivePixels(img, IfHotPix=True, IfDeadPix=True, fraction=badfraction, seed=20210911, biaslevel=0) img = Effects.DefectivePixels(img, IfHotPix=True, IfDeadPix=True, fraction=badfraction, seed=20210911, biaslevel=0)
img.write('./output/test_badpixel_HtrDtr.fits') img.write(os.path.join(self.outDataFn,'test_badpixel_HtrDtr.fits'))
del img del img
def test_badpixel_HfsDtr(self): def test_badpixel_HfsDtr(self):
img = galsim.Image(500,500,init_value=1000) img = galsim.Image(500,500,init_value=1000)
rgbadpix = Generator(PCG64(20210911)) rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7) badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
img = Effects.DefectivePixels(img, IfHotPix=False, IfDeadPix=True, fraction=badfraction, seed=20210911, biaslevel=0) img = Effects.DefectivePixels(img, IfHotPix=False, IfDeadPix=True, fraction=badfraction, seed=20210911, biaslevel=0)
img.write('./output/test_badpixel_HfsDtr.fits') img.write(os.path.join(self.outDataFn,'test_badpixel_HfsDtr.fits'))
del img del img
def test_badpixel_HtrDfs(self): def test_badpixel_HtrDfs(self):
img = galsim.Image(500,500,init_value=1000) img = galsim.Image(500,500,init_value=1000)
rgbadpix = Generator(PCG64(20210911)) rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7) badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
img = Effects.DefectivePixels(img, IfHotPix=True, IfDeadPix=False, fraction=badfraction, seed=20210911, biaslevel=0) img = Effects.DefectivePixels(img, IfHotPix=True, IfDeadPix=False, fraction=badfraction, seed=20210911, biaslevel=0)
img.write('./output/test_badpixel_HtrDfs.fits') img.write(os.path.join(self.outDataFn,'test_badpixel_HtrDfs.fits'))
del img del img
def test_badpixel_HfsDfs(self): def test_badpixel_HfsDfs(self):
img = galsim.Image(500,500,init_value=1000) img = galsim.Image(500,500,init_value=1000)
rgbadpix = Generator(PCG64(20210911)) rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7) badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
img = Effects.DefectivePixels(img, IfHotPix=False, IfDeadPix=False, fraction=badfraction, seed=20210911, biaslevel=0) img = Effects.DefectivePixels(img, IfHotPix=False, IfDeadPix=False, fraction=badfraction, seed=20210911, biaslevel=0)
img.write('./output/test_badpixel_HfsDfs.fits') img.write(os.path.join(self.outDataFn,'test_badpixel_HfsDfs.fits'))
del img del img
def test_badlines(self): def test_badlines(self):
img = galsim.Image(500,500,init_value=-1000) img = galsim.Image(500,500,init_value=-1000)
img.addNoise(galsim.GaussianNoise(sigma=7)) img.addNoise(galsim.GaussianNoise(sigma=7))
newimg = Effects.BadColumns(copy.deepcopy(img), seed=20210911) newimg = Effects.BadColumns(copy.deepcopy(img), seed=20210911)
newimg.write('./output/test_badlines.fits') newimg.write(os.path.join(self.outDataFn,'test_badlines.fits'))
del newimg,img del newimg,img
def test_cte(self): def test_cte(self):
...@@ -134,8 +144,8 @@ class DetTest(unittest.TestCase): ...@@ -134,8 +144,8 @@ class DetTest(unittest.TestCase):
img.array[150,150] = 3e4 img.array[150,150] = 3e4
newimgcol = Effects.CTE_Effect(copy.deepcopy(img),direction='column') newimgcol = Effects.CTE_Effect(copy.deepcopy(img),direction='column')
newimgrow = Effects.CTE_Effect(copy.deepcopy(img),direction='row') newimgrow = Effects.CTE_Effect(copy.deepcopy(img),direction='row')
newimgcol.write('./output/test_ctecol.fits') newimgcol.write(os.path.join(self.outDataFn,'test_ctecol.fits'))
newimgrow.write('./output/test_cterow.fits') newimgrow.write(os.path.join(self.outDataFn,'test_cterow.fits'))
del img,newimgcol,newimgrow del img,newimgcol,newimgrow
def test_readnoise(self): def test_readnoise(self):
...@@ -144,7 +154,7 @@ class DetTest(unittest.TestCase): ...@@ -144,7 +154,7 @@ class DetTest(unittest.TestCase):
rng_readout = galsim.BaseDeviate(seed) rng_readout = galsim.BaseDeviate(seed)
readout_noise = galsim.GaussianNoise(rng=rng_readout, sigma=5) readout_noise = galsim.GaussianNoise(rng=rng_readout, sigma=5)
img.addNoise(readout_noise) img.addNoise(readout_noise)
img.write('./output/test_readnoise.fits') img.write(os.path.join(self.outDataFn,'test_readnoise.fits'))
stdval = np.std(img.array) stdval = np.std(img.array)
self.assertTrue(np.abs(stdval-5)<0.01*5) self.assertTrue(np.abs(stdval-5)<0.01*5)
print('\nUnit test for readout noise has been passed.') print('\nUnit test for readout noise has been passed.')
...@@ -158,8 +168,8 @@ class DetTest(unittest.TestCase): ...@@ -158,8 +168,8 @@ class DetTest(unittest.TestCase):
def test_apply16gains(self): def test_apply16gains(self):
img = galsim.Image(500,500,init_value=100) img = galsim.Image(500,500,init_value=100)
img = Effects.ApplyGainNonUniform16(img, gain=1.5, nsecy=2, nsecx=8, seed=202102) img,_ = Effects.ApplyGainNonUniform16(img, gain=1.5, nsecy=2, nsecx=8, seed=202102)
img.write("./output/test_apply16gains.fits") img.write(os.path.join(self.outDataFn,'test_apply16gains.fits'))
rightedge = int(500/8)*8 rightedge = int(500/8)*8
print('gain=%6.2f' % 1.5) print('gain=%6.2f' % 1.5)
meanimg = np.mean(img.array[:,:rightedge]) meanimg = np.mean(img.array[:,:rightedge])
...@@ -172,20 +182,20 @@ class DetTest(unittest.TestCase): ...@@ -172,20 +182,20 @@ class DetTest(unittest.TestCase):
def test_cosmicray(self): def test_cosmicray(self):
attachedSizes = np.loadtxt('../ObservationSim/Instrument/Chip/wfc-cr-attachpixel.dat') attachedSizes = np.loadtxt(os.path.join(self.datafn,'wfc-cr-attachpixel.dat'))
cr_map = Effects.produceCR_Map( cr_map,_ = Effects.produceCR_Map(
xLen=500, yLen=500, exTime=150+0.5*40, xLen=500, yLen=500, exTime=150+0.5*40,
cr_pixelRatio=0.003*(1+0.5*40/150), cr_pixelRatio=0.003*(1+0.5*40/150),
gain=1, attachedSizes=attachedSizes, seed=20210911) gain=1, attachedSizes=attachedSizes, seed=20210911)
crimg = galsim.Image(cr_map) crimg = galsim.Image(cr_map)
crimg.write('./output/test_cosmicray.fits') crimg.write(os.path.join(self.outDataFn,'test_cosmicray.fits'))
del cr_map,crimg del cr_map,crimg
def test_shutter(self): def test_shutter(self):
img = galsim.Image(5000,5000,init_value=1000) img = galsim.Image(5000,5000,init_value=1000)
shuttimg = Effects.ShutterEffectArr(img, t_exp=150, t_shutter=1.3, dist_bearing=735, dt=1E-3) # shutter effect normalized image for this chip shuttimg = Effects.ShutterEffectArr(img, t_exp=150, t_shutter=1.3, dist_bearing=735, dt=1E-3) # shutter effect normalized image for this chip
img *= shuttimg img *= shuttimg
img.write('./output/test_shutter.fits') img.write(os.path.join(self.outDataFn,'test_shutter.fits'))
del img del img
def test_vignette(self): def test_vignette(self):
...@@ -195,7 +205,7 @@ class DetTest(unittest.TestCase): ...@@ -195,7 +205,7 @@ class DetTest(unittest.TestCase):
img.setOrigin(10000,10000) img.setOrigin(10000,10000)
flat_img = Effects.MakeFlatSmooth(img.bounds,20210911) flat_img = Effects.MakeFlatSmooth(img.bounds,20210911)
flat_normal = flat_img / np.mean(flat_img.array) flat_normal = flat_img / np.mean(flat_img.array)
flat_normal.write('./output/test_vignette.fits') flat_normal.write(os.path.join(self.outDataFn,'test_vignette.fits'))
del flat_img,img,flat_normal del flat_img,img,flat_normal
......
# Graph from wfc-cr-attach, page 1
0.00000 0.004684
0.5031 0.004684
0.5283 0.01873
1.509 0.01873
1.534 0.09327
2.490 0.09327
2.515 0.1034
3.496 0.1034
3.522 0.2440
4.503 0.2440
4.528 0.1107
5.509 0.1107
5.534 0.1013
6.490 0.1013
6.515 0.06090
7.496 0.06090
7.522 0.05834
8.503 0.05834
8.528 0.03875
9.509 0.03875
9.534 0.03066
10.49 0.03066
10.51 0.01788
11.47 0.01788
11.49 0.01831
13.50 0.01831
13.53 0.01235
13.53 0.01235
14.49 0.01235
14.51 0.01064
15.49 0.01064
15.52 0.008091
16.50 0.008091
16.52 0.004684
17.48 0.004684
17.53 0.003833
18.49 0.003833
18.51 0.005536
19.47 0.005536
19.52 0.004684
20.00 0.004684
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