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Commit edd720e6 authored by Fang Yuedong's avatar Fang Yuedong
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Merge branch 'develop'

parents 959f0ebc 8df06b27
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tests/det_effect_unit_test.py
View file @ edd720e6
......@@ -6,18 +6,28 @@ import matplotlib.pyplot as plt
import os,sys,math,copy
from numpy.random import Generator, PCG64
import warnings
from astropy.io import fits
warnings.filterwarnings("ignore", '.*Numba.*',)
width = 9216
height = 9232
if os.path.isdir('./output/'):
pass
else:
os.mkdir('./output/')
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):
'''
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):
img.addNoise(galsim.GaussianNoise(sigma=7))
# plt.imshow(img.array)
# plt.show()
filename1 = os.path.join('output','test_satu_initimg.fits')
filename1 = os.path.join(self.outDataFn,'test_satu_initimg.fits')
img.write(filename1)
newimg = Effects.SaturBloom(img, fullwell=9e4)
# plt.imshow(newimg.array)
# plt.show()
filename2 = os.path.join('output','test_satu_bleedimg.fits')
filename2 = os.path.join(self.outDataFn,'test_satu_bleedimg.fits')
newimg.write(filename2)
del img,newimg, star
......@@ -79,16 +89,16 @@ class DetTest(unittest.TestCase):
'''
imgarr = np.arange(1,9e4,4).reshape((150,150))
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)
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)
plt.scatter(imgarr.flatten(), newimg.array.flatten(), s=2, alpha=0.5)
plt.plot([-1e3,9e4],[-1e3,9e4],color='black', lw=1, ls='--')
plt.xlabel('input (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()
del img,newimg,imgarr
......@@ -97,35 +107,35 @@ class DetTest(unittest.TestCase):
rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
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
def test_badpixel_HfsDtr(self):
img = galsim.Image(500,500,init_value=1000)
rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
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
def test_badpixel_HtrDfs(self):
img = galsim.Image(500,500,init_value=1000)
rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
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
def test_badpixel_HfsDfs(self):
img = galsim.Image(500,500,init_value=1000)
rgbadpix = Generator(PCG64(20210911))
badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
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
def test_badlines(self):
img = galsim.Image(500,500,init_value=-1000)
img.addNoise(galsim.GaussianNoise(sigma=7))
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
def test_cte(self):
......@@ -134,8 +144,8 @@ class DetTest(unittest.TestCase):
img.array[150,150] = 3e4
newimgcol = Effects.CTE_Effect(copy.deepcopy(img),direction='column')
newimgrow = Effects.CTE_Effect(copy.deepcopy(img),direction='row')
newimgcol.write('./output/test_ctecol.fits')
newimgrow.write('./output/test_cterow.fits')
newimgcol.write(os.path.join(self.outDataFn,'test_ctecol.fits'))
newimgrow.write(os.path.join(self.outDataFn,'test_cterow.fits'))
del img,newimgcol,newimgrow
def test_readnoise(self):
......@@ -144,7 +154,7 @@ class DetTest(unittest.TestCase):
rng_readout = galsim.BaseDeviate(seed)
readout_noise = galsim.GaussianNoise(rng=rng_readout, sigma=5)
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)
self.assertTrue(np.abs(stdval-5)<0.01*5)
print('\nUnit test for readout noise has been passed.')
......@@ -158,8 +168,8 @@ class DetTest(unittest.TestCase):
def test_apply16gains(self):
img = galsim.Image(500,500,init_value=100)
img = Effects.ApplyGainNonUniform16(img, gain=1.5, nsecy=2, nsecx=8, seed=202102)
img.write("./output/test_apply16gains.fits")
img,_ = Effects.ApplyGainNonUniform16(img, gain=1.5, nsecy=2, nsecx=8, seed=202102)
img.write(os.path.join(self.outDataFn,'test_apply16gains.fits'))
rightedge = int(500/8)*8
print('gain=%6.2f' % 1.5)
meanimg = np.mean(img.array[:,:rightedge])
......@@ -172,20 +182,20 @@ class DetTest(unittest.TestCase):
def test_cosmicray(self):
attachedSizes = np.loadtxt('../ObservationSim/Instrument/Chip/wfc-cr-attachpixel.dat')
cr_map = Effects.produceCR_Map(
attachedSizes = np.loadtxt(os.path.join(self.datafn,'wfc-cr-attachpixel.dat'))
cr_map,_ = Effects.produceCR_Map(
xLen=500, yLen=500, exTime=150+0.5*40,
cr_pixelRatio=0.003*(1+0.5*40/150),
gain=1, attachedSizes=attachedSizes, seed=20210911)
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
def test_shutter(self):
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
img *= shuttimg
img.write('./output/test_shutter.fits')
img.write(os.path.join(self.outDataFn,'test_shutter.fits'))
del img
def test_vignette(self):
......@@ -195,7 +205,7 @@ class DetTest(unittest.TestCase):
img.setOrigin(10000,10000)
flat_img = Effects.MakeFlatSmooth(img.bounds,20210911)
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
......
tests/testData/csst_fz_gc0/CSST_GI2.conf 0 → 100644
View file @ edd720e6
INSTRUMETN CSSTSLS
GRATING GI
WAVELENGTH 6200 10000
# 1 order (BEAM A) *******************
BEAMA 505 1238
MMAG_EXTRACT_A 30
MMAG_MARK_A 30
#
# Trace description
#
DYDX_ORDER_A 1
DYDX_A_0 1.6521968560197104 -0.00023636575255565063 0.00014657966669906052 5.5353251643711546e-08 -6.875491197053945e-09 1.898528225132234e-09
DYDX_A_1 -0.00823033845070988 8.828905689160072e-08 -4.959096708134394e-07 -1.9481266745599912e-11 1.1236282464271542e-11 -7.748796599795913e-12
#
# X and Y Offsets
#
XOFF_A 0.0
YOFF_A 0.0
#
# Dispersion solution
#
DISP_ORDER_A 1
DLDP_A_0 368.406778602958 0.003046565833724366 0.0008085615398225785 -2.139787644130709e-07 -1.1201107471275321e-07 -3.4449662405229706e-08
DLDP_A_1 8.461359683949652 0.00022163929626988009 -6.114607283280979e-07 7.123049245778616e-09 1.99766396430199e-11 2.5539201322842942e-11
#
SENSITIVITY_A GI.Throughput.1st.fits
#
# 0 order (BEAM B) *******************
BEAMB -121 80
MMAG_EXTRACT_B 30
MMAG_MARK_B 30
#
# Trace description
#
DYDX_ORDER_B 0
DYDX_B_0 -0.15118122059806027 -0.00014883011863745443 7.638889641475754e-05 3.208928684076908e-08 -2.743527540058062e-16 -5.917502574749109e-09
#
# X and Y Offsets
#
XOFF_B 0.0
YOFF_B 0.0
#
# Dispersion solution
#
DISP_ORDER_B 1
DLDP_B_0 -69799.9181918991 7.954241458130043e-08 -4.318951729587184e-08 2.591993568563933e-12 -5.884436166492418e-12 3.83253047082687e-12
DLDP_B_1 -3799.99600104444 7.250278281031939e-09 -3.3418691029874735e-09 -1.6236581010798935e-12 -4.3502364485117337e-13 4.507009220450333e-13
#
SENSITIVITY_B GI.Throughput.0st.fits
#
# -1 order (BEAM C) *******************
BEAMC -1251 -537
MMAG_EXTRACT_C 30
MMAG_MARK_C 30
#
# Trace description
#
DYDX_ORDER_C 1
DYDX_C_0 1.6274259827507076 -0.00034821339283356466 0.0002392999867887435 1.5635809977657976e-07 -7.514174027001749e-09 -6.566395011125117e-09
DYDX_C_1 -5.3689415286860876e-05 -1.912489940030657e-07 -1.070383333548475e-08 1.53386647062175e-10 -1.1208241918489809e-11 3.406912464353884e-12
#
# X and Y Offsets
#
XOFF_C 0.0
YOFF_C 0.0
#
# Dispersion solution
#
DISP_ORDER_C 1
DLDP_C_0 -132.55108204545758 -0.002194041658487836 -0.0011882168059149318 4.510589778063266e-08 5.420547634024377e-08 9.930897689686617e-08
DLDP_C_1 -8.799340620412947 -0.00021774440141256442 -9.53499834632785e-07 -6.889561983057868e-09 -1.6142159956150814e-10 1.0347079457327646e-10
#
SENSITIVITY_C GI.Throughput.-1st.fits
#
# 2 order (BEAM D) *******************
BEAMD 1154 2507
MMAG_EXTRACT_D 30
MMAG_MARK_D 30
#
# Trace description
#
DYDX_ORDER_D 1
DYDX_D_0 6.882799280484086 -0.00027753891131284954 0.0004922039820404395 3.082997123523641e-08 -9.49966186877231e-09 -2.3656818322711693e-09
DYDX_D_1 -0.011947813534498112 4.093696016714032e-08 -7.435107573317389e-07 2.5528541317977112e-12 3.192792142602198e-12 -2.453919520892182e-12
#
# X and Y Offsets
#
XOFF_D 0.0
YOFF_D 0.0
#
# Dispersion solution
#
DISP_ORDER_D 1
DLDP_D_0 681.5215546431494 -0.003828618628269481 0.00025066858071110036 8.289914582311179e-08 -8.404758131147936e-08 2.9680890659588283e-08
DLDP_D_1 3.8798704838712443 0.0001054229718827677 -6.676804799370928e-08 3.250115236230527e-09 1.9094002846781994e-11 -2.387851784113332e-11
#
SENSITIVITY_D GI.Throughput.2st.fits
#
# -2 order (BEAM E) *******************
BEAME -2429 -1162
MMAG_EXTRACT_E 30
MMAG_MARK_E 30
#
# Trace description
#
DYDX_ORDER_E 1
DYDX_E_0 7.677233822131253 -0.00048041060058740204 0.0004956385735024366 6.868585247565035e-08 -9.175237278696478e-09 1.2566962458208905e-09
DYDX_E_1 0.003983370254635055 -1.232787560255339e-08 2.1234388976109016e-07 1.6204618268328708e-11 3.983819645370279e-12 4.263520014579825e-12
#
# X and Y Offsets
#
XOFF_E 0.0
YOFF_E 0.0
#
# Dispersion solution
#
DISP_ORDER_E 1
DLDP_E_0 225.51253672373838 0.004993681854364764 -0.0005008288340946528 -3.699489889412266e-07 9.185967746730138e-10 3.449301385107925e-08
DLDP_E_1 -4.201429796832916 -0.0001002659886793457 -1.5067099385104427e-07 -3.422412459135902e-09 -4.7864621219451994e-11 1.2110924433274547e-11
#
SENSITIVITY_E GI.Throughput.-2st.fits
#
tests/testData/csst_fz_gc0/Straylight_test.dat 0 → 100644
View file @ edd720e6
# ra dec lon(ecliptic) lat(ecliptic) pos_angle time(julian) sat_x sat_y sat_z sun_x sun_y sun_z moon_x moon_y moon_z sat_vx sat_vy sat_vz exp_time isDeep
244.972773 39.895901 229.6933 59.8819 109.59452000342756 2460539.75361268 -2218.3663 -5817.8559 2597.9467 -123291049.6698 80698075.2698 34981832.8099 129217.8762 -306193.0456 -168270.0801 5.058199026407237 -3.85818799871231 -4.322908628205369 150.0 -1.0
245.19954 39.834237 230.0613 59.8819 109.42155570115811 2460539.75590434 -1169.3163 -6427.7801 1683.3766 -123294376.7625 80693691.118 34979932.4325 129409.3308 -306117.8806 -168231.5896 5.495628791263698 -2.2766122251687193 -4.877784128846088 150.0 -1.0
245.376849 40.538238 229.8433 60.5906 109.72521611662427 2460543.53323198 -4088.9785 -4865.03 2348.6771 -128524732.1114 73309196.4688 31779164.5982 349033.2322 -76382.1208 -45844.3874 3.513272716954816 -5.1280401490294025 -4.4997767748736806 150.0 -1.0
245.939689 40.198882 230.894 60.4134 109.17526390397103 2460543.53552584 -3296.1182 -5750.7175 1405.5287 -128527752.3153 73304618.787 31777180.4968 349086.0107 -76197.4206 -45744.3873 4.456135176128555 -3.773136335412346 -4.9799999694710095 150.0 -1.0
246.809804 39.784988 232.438 60.2362 108.39295915033918 2460543.53783608 -2330.5509 -6351.0086 384.2962 -128530793.8798 73300008.3241 31775182.1872 349139.047 -76011.3767 -45643.6581 5.179717934292967 -2.216473482430956 -5.210878017528557 150.0 -1.0
247.037801 39.727005 232.8099 60.2362 108.21592927146807 2460543.54012774 -1255.3999 -6627.1633 -648.2573 -128533810.807 73295434.8053 31773199.8903 349191.5393 -75826.8029 -45543.7232 5.637231322125444 -0.5605653312886716 -5.176883766496303 150.0 -1.0
247.26584 39.669564 233.1818 60.2362 108.038749009507 2460543.54241941 -117.3694 -6571.3891 -1648.2421 -128536827.5433 73290861.1758 31771217.5454 349243.9141 -75642.204 -45443.7731 5.812145421308514 1.122583740434493 -4.883329814897479 150.0 -1.0
245.254413 40.383388 229.7713 60.4134 109.70843030522704 2460543.59745489 -4101.478 -4866.9578 2323.1349 -128609218.3748 73180990.3315 31723596.3195 350466.4112 -71201.6169 -43038.9593 3.509223042501617 -5.1159759164056595 -4.516449863272101 150.0 -1.0
245.898224 40.022321 230.9504 60.2362 109.09954624314884 2460543.599753 -3307.4819 -5751.6002 1375.5044 -128612238.7884 73176401.0903 31721607.2092 350515.9823 -71015.8914 -42938.3589 4.456793269669106 -3.758275091286123 -4.990470905338498 150.0 -1.0
246.912851 39.57222 232.7235 60.0591 108.21113555960895 2460543.60207086 -2338.0901 -6350.3531 349.5009 -128615284.9693 73171772.2898 31719600.9527 350565.8595 -70828.5455 -42836.8793 5.185149246981382 -2.196511614110932 -5.213861687802819 150.0 -1.0
247.140446 39.514777 233.0935 60.0591 108.03541662103602 2460543.60436253 -1261.6936 -6622.571 -682.7541 -128618296.5268 73167195.698 31717617.3251 350615.0543 -70643.2938 -42736.5323 5.644314272476549 -0.5413230985595874 -5.171075108238483 150.0 -1.0
246.685297 39.630202 232.3535 60.0591 108.38670333146824 2460543.6066542 -122.112 -6563.1261 -1680.7261 -128621307.8934 73162618.9958 31715633.6496 350664.1312 -70458.0187 -42636.1712 5.820605356021247 1.1401236903839163 -4.869028668063038 150.0 -1.0
246.561326 39.475239 232.2699 59.8819 108.38013823250273 2460543.60894586 1023.5967 -6175.0802 -2594.3 -128624319.0682 73158042.184 31713649.9267 350713.0903 -70272.7204 -42535.7958 5.7056975349860295 2.764332291953906 -4.322172590177615 150.0 -1.0
245.623258 40.847614 229.9894 60.9449 109.75838193462751 2460543.6682487 -1437.2044 -6598.2001 -561.399 -128702174.3868 73039567.2025 31662299.4501 351938.9714 -65469.7753 -39933.5032 5.599335756251094 -0.7771821850383276 -5.189864591059177 150.0 -1.0
245.499769 40.692917 229.916 60.7677 109.74184789995181 2460543.67054037 -302.0605 -6585.6621 -1566.1018 -128705180.4091 73034987.4487 31660314.4531 351984.7548 -65283.8767 -39832.7597 5.820956241348654 0.9040687362721656 -4.91795858765272 150.0 -1.0
245.605624 40.476178 230.2194 60.5906 109.54618182037997 2460543.85286552 -4551.9642 -4177.9517 2779.7576 -128943724.7839 72670271.9443 31502236.3919 355246.6721 -50430.2867 -31778.0894 2.7806315862835618 -5.809120183557752 -4.171875803399416 150.0 -1.0
246.168179 40.138468 231.2682 60.4134 108.9972405764492 2460543.85515932 -3891.5017 -5214.6838 1890.235 -128946718.1231 72665679.1318 31500245.7379 355282.9058 -50242.6873 -31676.2957 3.858369242079789 -4.610655120031879 -4.76915223102651 150.0 -1.0
246.581847 39.843512 232.0661 60.2362 108.5698372158382 2460543.85745099 -3036.7067 -5989.2387 906.5607 -128949708.4894 72661090.477 31498256.886 355318.9862 -50055.2459 -31574.5862 4.741932037004517 -3.1813221279298887 -5.127064128400889 150.1976 -1.0
247.368081 39.457872 233.4635 60.0591 107.85954794587214 2460543.85975863 -2022.3883 -6466.0294 -129.8582 -128952719.5082 72656469.7232 31496254.1216 355355.1975 -49866.4812 -31472.1571 5.39186183170159 -1.5809240736052743 -5.2270457437822415 150.0 -1.0
247.49392 39.612666 233.5537 60.2362 107.86141979573472 2460543.8620503 -913.3254 -6614.5703 -1152.6821 -128955709.4883 72651880.8508 31494265.1755 355391.0381 -49679.0071 -31370.4268 5.766144793522017 0.08734229075344047 -5.06308085288083 150.0 -1.0
247.540067 39.78741 233.5135 60.4134 107.92582448507959 2460543.86434196 241.4815 -6431.8631 -2117.6161 -128958699.2767 72647291.8685 31492276.1817 355426.7591 -49491.5168 -31268.686 5.851879255174026 1.7513616764153994 -4.644633372004137 150.0 -1.0
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245.74134 39.127451 231.2991 59.3504 108.69823302047337 2461960.00055384 -3300.4563 -5086.409 -2987.8676 -40633313.0207 134471153.7064 58290177.3322 161432.4836 -332492.176 -143257.2799 4.231211532414818 -5.053713887618869 3.9430983798229136 150.0 -1.0
246.48139 40.993533 231.1538 61.2992 109.30085507920921 2461960.95975612 -3523.6076 -5095.2176 -2703.9332 -42965876.3823 133857406.8935 58024247.5324 233636.1292 -300335.9563 -121117.3797 4.033294810187726 -5.0098050846190745 4.200978689682415 150.0 -1.0
245.967004 39.068467 231.6616 59.3504 108.52868870359053 2461961.67202793 258.8961 -6610.7974 1352.8773 -44690869.4311 133379313.9965 57817088.0375 280862.7683 -268027.3523 -101259.1454 5.728600171161133 1.2516035100816225 4.973460048538527 150.0 -1.0
245.862775 39.282674 231.3765 59.5276 108.70834345657407 2461961.7912584 -3647.0213 -5181.3371 -2353.0098 -44979014.3428 133297427.7404 57781605.7093 288146.7023 -261984.5661 -97691.0248 3.9793171426299523 -4.819855744763117 4.464712687431529 150.0 -1.0
246.125044 40.900398 230.6908 61.122 109.47309187166248 2461961.85241015 -4471.1884 -3840.08 -3311.1891 -45126731.1923 133255223.1018 57763317.8338 291808.8972 -258818.8098 -95836.2207 2.6955617094972695 -6.22762067304393 3.592697494409549 150.0 -1.0
246.355484 40.839096 231.0733 61.122 109.28894225224086 2461961.91644618 -4462.0903 -3889.8199 -3264.8553 -45281364.985 133210877.9948 57744102.4012 295589.4648 -255456.2655 -93876.422 2.727971425420037 -6.181705520612013 3.6470232867532104 150.0 -1.0
246.586032 40.77834 231.4559 61.122 109.10458959046838 2461962.04413763 -4532.6483 -3784.651 -3291.1572 -45589559.2301 133121993.9205 57705587.3414 302959.5246 -248608.9116 -89916.5412 2.603103836063383 -6.2531402451168105 3.6164912330968946 150.0 -1.0
246.126057 39.96218 231.3223 60.2362 108.92313219026747 2461962.63277483 825.5874 -6272.9571 2354.5096 -47007593.4731 132704382.8536 57524625.4811 333900.029 -214742.734 -70851.0952 5.767102121208154 2.4436210540716274 4.462294250715786 150.0 -1.0
246.396711 40.078597 231.6424 60.4134 108.81906113254608 2461963.84700222 259.3175 -6254.4347 2527.4227 -49918245.567 131802204.2046 57133667.1355 380528.931 -134966.7945 -28416.3176 6.021747071869754 2.0131588530057343 4.337991907159449 150.0 -1.0
246.943449 40.872554 231.9231 61.2992 108.92880040922387 2461968.12876195 -1172.0599 -5757.6869 3320.5816 -60011189.3534 128187092.6554 55566782.5454 336032.0637 176515.8169 115887.5462 6.769633364535821 0.6982789318408322 3.5808791901808945 150.0 -1.0
246.853963 39.960473 232.3909 60.4134 108.4621919061398 2461968.26853717 5044.9604 -1666.7097 4156.14 -60335789.4756 128057798.9753 55510735.8064 329119.236 185513.9505 119524.896 3.868107778707781 6.286005516581099 -2.1698325132274476 150.0 -1.0
247.232254 40.424316 232.6505 60.9449 108.47998131476675 2461968.77999749 5142.2287 -1639.4297 4046.1101 -61520740.8474 127578668.63 55303036.6762 301192.8988 216874.6788 131840.0113 3.883848272062096 6.181727858333943 -2.427029845607649 150.0 -1.0
246.542392 40.602397 231.51 60.9449 109.02880522590246 2461969.27889607 -1492.8636 -5570.7808 3504.9733 -62672265.6826 127102211.2637 55096490.6547 270181.6233 244779.0986 142215.9977 6.918143732200406 0.26348434721512604 3.347216960219157 150.0 -1.0
246.607899 41.14788 231.2352 61.4764 109.31251081523813 2461969.48250457 5022.6411 -1991.7825 4038.4218 -63140974.777 126905187.0903 55011078.4229 256526.7943 255312.1384 145948.5925 4.305012264512698 5.888079023263799 -2.4457485425227787 150.0 -1.0
246.521339 40.23334 231.7241 60.5906 108.82832024886652 2461969.93014068 5161.1423 -1913.186 3898.9906 -64168859.123 126466792.8951 54821026.5437 224628.8476 276553.312 153064.0931 4.221967064113414 5.825841918933747 -2.7252320431307453 150.0 -1.0
246.839349 41.087095 231.6219 61.4764 109.12495090482 2461970.95235458 5137.4841 -2208.3083 3772.0061 -66502536.0965 125438807.8162 54375362.0164 143490.4488 313978.6068 163247.0488 4.525264345111282 5.477807081865649 -2.951414127633143 150.0 -1.0
245.845688 38.913179 231.5832 59.1732 108.5197426516053 2461971.07986267 5027.2302 -2369.9718 3822.323 -66792280.2661 125307967.0929 54318637.1196 132703.8129 317462.3049 163889.6588 4.711795763932969 5.364353510867659 -2.866017980441029 150.0 -1.0
246.772321 40.542473 231.8902 60.9449 108.8459995436438 2462030.29402331 5197.0175 -1859.6237 3901.7679 -149308342.7923 16681434.4854 7231824.4281 -239574.8431 255964.5898 98753.9761 4.144312310500027 5.861287509551403 -2.7351865145055854 150.0 -1.0
247.047209 40.658529 232.221 61.122 108.7354735308835 2462030.80624205 5244.0496 -1932.1058 3801.9893 -149440899.2725 15484219.5773 6712812.6574 -271639.5091 225034.1095 81226.8271 4.215009001491126 5.724789276980573 -2.9124319807897336 150.0 -1.0
247.997741 39.674763 234.262 60.4134 107.56745835107756 2462031.31842367 5283.7344 -2020.1733 3700.7797 -149561972.8395 14285862.8381 6193309.1777 -299228.7445 190353.9128 62347.4756 4.285410045258686 5.58392762352014 -3.078362375213146 150.0 -1.0
246.876034 40.328544 232.1849 60.7677 108.6558758373069 2462031.57440339 5262.7436 -2116.4254 3676.4321 -149618177.0556 13686514.344 5933485.1844 -311170.9682 171777.2025 52496.7593 4.378710896353368 5.489230202088038 -3.116244377106341 150.0 -1.0
247.311323 39.84455 233.1393 60.4134 108.1047630499479 2462174.23879932 -2869.0819 -6069.0656 793.1017 109331229.9378 -90894868.4058 -39401578.0123 -197069.4369 -283994.9471 -149367.3448 4.8587505300793055 -2.982423282956006 -5.159325211233181 150.2773 -1.0
246.192767 39.009986 232.0242 59.3504 108.35894074841596 2462174.43108379 -2909.3605 -6060.341 707.8512 109671118.7476 -90556277.7514 -39254795.3362 -182616.9995 -293032.3995 -152098.5356 4.860413613728269 -2.9492565987311536 -5.174892646189164 150.2637 -1.0
247.896243 39.885553 233.9812 60.5906 107.74691651250163 2462174.87915376 -3244.1133 -5879.3537 770.1803 110458300.8197 -89763249.2637 -38911006.7054 -147509.7388 -311705.2917 -157230.4518 4.6679840427714225 -3.263689292152776 -5.162518025827012 150.3422 -1.0
247.070849 41.026882 232.0086 61.4764 108.93723946870263 2462175.19888911 -3594.9744 -5643.6638 951.1984 111015855.1645 -89193930.9172 -38664197.7124 -121415.9716 -322919.3201 -159824.4286 4.39793623730111 -3.6765481198744965 -5.123315670992952 150.3534 -1.0
247.768852 39.730819 233.8877 60.4134 107.74673841160009 2462253.15152102 -1211.1436 -5049.711 -4336.9329 121362268.2401 81736272.7992 35429318.4281 -351193.0197 -48435.5681 -55431.467 6.823528124857603 -3.08510699512226 1.6831110300699947 150.0 -1.0
247.118021 39.147872 233.2859 59.7047 107.85477794891013 2462262.69777181 -347.402 -6744.0498 276.7957 105695760.4421 98834877.4684 42841973.2401 322897.4677 -221860.0347 -66968.7278 5.6633989486050496 -0.07635456612661073 5.195740062693517 150.0 -1.0
247.208626 40.056956 232.8527 60.5906 108.28826749754191 2462319.10684862 247.406 -6564.4141 -1642.4043 -25441545.0952 137577555.6066 59636758.8963 384901.2544 -102871.5324 -6666.4917 5.861530949557903 -0.9786556003473379 4.855618813403453 150.0 -1.0
246.979487 40.1152 232.4765 60.5906 108.4684365812141 2462319.74841245 190.256 -6638.4103 -1318.2807 -27040967.7247 137322355.3345 59526164.8031 396522.101 -54823.6005 15723.717 5.783374763091729 -0.8079256480596086 4.980751912410142 150.0 -1.0
247.105538 40.269756 232.563 60.7677 108.47436563632616 2462319.812486 142.5629 -6639.2931 -1321.0232 -27200539.4907 137295994.4829 59514740.4065 397261.822 -49952.9422 17949.2628 5.780481847124008 -0.8511806083515694 4.9824665871574325 150.0 -1.0
246.625286 40.01927 232.0166 60.4134 108.64072700435482 2462319.8788307 1216.2664 -6650.1126 -321.9542 -27365735.2681 137268532.1085 59502838.5136 397946.943 -44899.8399 20249.8788 5.60570354570018 0.7905537790156814 5.188217678746696 150.0 -1.0
247.69237 40.308398 233.4108 60.9449 108.11336607869262 2462319.94056896 16.6658 -6634.6282 -1353.4861 -27519431.6071 137242823.7723 59491696.6991 398510.6085 -40189.534 22386.8685 5.767847519702585 -0.9835783188282221 4.970527282287094 150.0 -1.0
247.002234 40.483123 232.2703 60.9449 108.66308984313291 2462320.0068373 1054.6122 -6674.3801 -389.5385 -27684373.5998 137215065.2539 59479666.2403 399036.3599 -35125.9511 24676.0543 5.633374143335459 0.6039831150883401 5.181799366346809 150.0 -1.0
247.469964 39.246542 233.7423 59.8819 107.68277420634686 2462320.32672669 586.267 -6715.7512 -613.3686 -28480107.5414 137078684.9983 59420557.8573 400420.277 -10604.437 35644.8427 5.692243830799271 0.04264450862137892 5.155318912658231 150.0 -1.0
246.353932 39.902577 231.6942 60.2362 108.74656203862885 2462320.39207401 1159.9081 -6667.0986 -44.6746 -28642563.4754 137050339.2478 59408272.2453 400468.0681 -5585.8416 37866.0031 5.5718285265538725 0.9513103997051076 5.20181847474241 150.0 -1.0
246.816627 40.718145 231.8385 61.122 108.92008344366282 2462320.45908824 2465.0624 -6171.1226 1258.582 -28809128.6764 137021099.2945 59395598.9577 400434.4571 -438.307 40135.9054 4.987255645787627 3.029769582044537 5.000514050686888 150.0 -1.0
246.750391 40.173995 232.1003 60.5906 108.6484546432903 2462320.71351922 1445.7857 -6595.7929 432.9487 -29441197.5337 136908507.2897 59346797.9085 399546.8932 19095.1647 48672.9892 5.457516486480927 1.5529534998040617 5.177141500764151 150.0 -1.0
247.17452 40.812923 232.3077 61.2992 108.74256993242068 2462320.77651841 885.6544 -6709.5277 -50.4945 -29597622.7349 136880242.9655 59334546.9846 399141.8506 23924.8786 50765.1144 5.607114462145546 0.7176541563603678 5.201735673724102 150.0 -1.0
247.277898 40.599462 232.6036 61.122 108.55066476038463 2462320.84177882 1407.5329 -6600.9668 480.4151 -29759628.5206 136850802.7953 59321786.3003 398644.9898 28923.1824 52922.4441 5.463236461835095 1.5585713168184157 5.173147883371598 150.0 -1.0
247.405641 40.75386 232.6923 61.2992 108.55618983272879 2462320.90477846 848.2342 -6714.6948 -2.1897 -29915989.122 136822226.7464 59309400.0684 398090.8867 33742.8437 54995.1144 5.604772019247548 0.7230969162446854 5.201014303481483 150.0 -1.0
247.462259 40.366084 233.0306 60.9449 108.29677171487835 2462321.09496945 -280.8852 -6703.5008 -910.3315 -30387831.3563 136735029.925 59271604.2093 395976.0197 48251.4717 61189.4642 5.667605424368389 -0.9135896564293944 5.097389409246489 150.0 -1.0
247.636809 40.695368 233.0769 61.2992 108.36966154651509 2462321.61011072 604.6131 -6736.6975 228.7071 -31664309.9512 136491855.5275 59166194.9395 386948.344 87075.9225 77426.019 5.6153257755443065 0.6971241051178367 5.194694090523342 150.0 -1.0
247.794435 40.096696 233.6975 60.7677 107.92884388133275 2462321.67232451 -346.8075 -6734.353 -604.226 -31818316.3696 136461795.9207 59153164.5428 385536.0825 91702.4384 79326.9631 5.642762956610454 -0.7369361795463192 5.156186184104854 150.0 -1.0
246.070956 38.854726 231.9439 59.1732 108.35141276177265 2462321.86668987 563.741 -6734.8087 357.5065 -32299237.0127 136366925.8837 59112039.2409 380683.7584 106048.357 85173.7723 5.616744443631205 0.7625317362453643 5.185346321812858 150.0 -1.0
247.508634 40.54096 232.9862 61.122 108.36570681440722 2462322.05884512 399.7833 -6748.0594 330.1177 -32774359.3007 136271706.5252 59070761.7239 375237.778 120051.9093 90809.6151 5.632439604359547 0.6044181975539686 5.186737518226323 150.0 -1.0
247.739417 40.483024 233.3688 61.122 108.18060113241472 2462322.44440913 681.9843 -6679.9477 835.7351 -33726693.5119 136076366.639 58986079.7494 362403.0578 147519.2174 101647.3405 5.601859946459626 1.2289689967838058 5.113525943238528 150.0 -1.0
247.595755 39.401506 233.8335 60.0591 107.68353096519836 2462329.04609969 -1988.4399 -6046.3309 2299.6134 -49783826.9801 131852391.0206 57154628.4732 -116549.6763 338574.4681 137859.8862 6.218106696430823 -0.31583298971781915 4.495656837843853 150.0 -1.0
247.922466 40.251288 233.7909 60.9449 107.92986232155825 2462330.26613771 -983.2823 -5771.9076 3387.3469 -52690301.2234 130891957.1828 56738202.8943 -211927.3478 294886.7724 108995.7536 6.775456380065634 0.9177357850330736 3.4974696432527708 150.0 -1.0
248.024116 40.040135 234.0756 60.7677 107.74674181521529 2462330.32825689 -2125.929 -5806.9612 2748.2083 -52837701.0734 130841576.1569 56716359.2306 -216387.3897 291993.5791 107270.7851 6.444069641288479 -0.3713079646695405 4.159348266816778 150.0 -1.0
246.870149 38.837697 233.1118 59.3504 107.84886369049836 2462330.52405023 -108.9998 -5551.7283 3859.5644 -53301910.1884 130681845.0956 56647105.1776 -230138.9105 282473.5668 101687.6712 6.918374020225571 1.8269670143308758 2.7960470906509727 150.0 -1.0
config/config_NGP.yaml → tests/testData/csst_fz_gc0/config_C6.yaml
View file @ edd720e6
......@@ -2,7 +2,7 @@
###############################################
#
# Configuration file for CSST simulation
# CSST-Sim Group, 2023/04/25
# CSST-Sim Group, 2021/10/07
#
###############################################
......@@ -10,8 +10,17 @@
# Can add some of the command-line arguments here as well;
# OK to pass either way or both, as long as they are consistent
work_dir: "/share/home/fangyuedong/test_psf_rot/csst-simulation/workplace/"
# work_dir: "/share/"
data_dir: "/share/simudata/CSSOSDataProductsSims/data/"
run_name: "NGP_C3"
run_name: "C6_photometry"
# (Optional) a file of point list
# if you just want to run default pointing:
# - pointing_dir: null
# - pointing_file: null
pointing_dir: "/share/simudata/CSSOSDataProductsSims/data/"
# pointing_dir: "/share/home/fangyuedong/test_psf_rot/csst-simulation/workplace/"
pointing_file: "pointing_radec_246.5_40.dat"
# Whether to use MPI
run_option:
......@@ -25,32 +34,12 @@ run_option:
# If yes, no imaging simulation will run
out_cat_only: NO
###############################################
# Catalog setting
###############################################
# Configure your catalog: options to be implemented
# in the corresponding (user defined) 'Catalog' class
catalog_options:
input_path:
cat_dir: "OnOrbitCalibration/CTargets20211231"
star_cat: "CT-NGP_r1.8_G28.hdf5"
galaxy_cat: "galaxyCats_r_3.0_healpix_shift_192.859500_27.128300.hdf5"
SED_templates_path:
star_SED: "Catalog_20210126/SpecLib.hdf5"
galaxy_SED: "Templates/Galaxy/"
# Only simulate stars?
star_only: NO
# Only simulate galaxies?
galaxy_only: NO
# rotate galaxy ellipticity
rotateEll: 0. # [degree]
seed_Av: 121212 # Seed for generating random intrinsic extinction
###############################################
# Observation setting
###############################################
......@@ -59,14 +48,14 @@ obs_setting:
# Options for survey types:
# "Photometric": simulate photometric chips only
# "Spectroscopic": simulate slitless spectroscopic chips only
# "FGS": simulate FGS chips only (31-42)
# "All": simulate full focal plane
survey_type: "Photometric"
survey_type: "Spectroscopic"
# Exposure time [seconds]
exp_time: 150.
# Observation starting date & time
# (Subject to change)
date_obs: "210525" # [yymmdd]
time_obs: "120000" # [hhmmss]
......@@ -74,16 +63,10 @@ obs_setting:
# Note: NOT valid when a pointing list file is specified
ra_center: 192.8595
dec_center: 27.1283
# Image rotation [degree]
image_rot: -113.4333
# (Optional) a file of point list
# if you just want to run default pointing:
# - pointing_dir: null
# - pointing_file: null
pointing_dir: "/share/simudata/CSSOSDataProductsSims/data/"
pointing_file: "pointing_test_NGP_2.17.dat"
# Number of calibration pointings
np_cal: 0
......@@ -91,7 +74,7 @@ obs_setting:
# - give a list of indexes of pointings: [ip_1, ip_2...]
# - run all pointings: null
# Note: only valid when a pointing list is specified
run_pointings: [0, 1, 2]
run_pointings: null
# Run specific chip(s):
# - give a list of indexes of chips: [ip_1, ip_2...]
......@@ -100,6 +83,7 @@ obs_setting:
run_chips: null
# Whether to enable astrometric modeling
# astrometric_lib: "libshao.so"
enable_astrometric_model: True
# Cut by saturation magnitude in which band?
......@@ -111,6 +95,20 @@ obs_setting:
# limiting magnitude margin
mag_lim_margin: +1.0
###############################################
# Input path setting
###############################################
# Default path settings for WIDE survey simulation
input_path:
cat_dir: "Catalog_C6_20221212"
star_cat: "C6_MMW_GGC_Astrometry_healpix.hdf5"
galaxy_cat: "cat2CSSTSim_bundle/"
SED_templates_path:
star_SED: "Catalog_20210126/SpecLib.hdf5"
galaxy_SED: "Catalog_C6_20221212/sedlibs/"
###############################################
# PSF setting
###############################################
......@@ -130,6 +128,12 @@ psf_setting:
# NOTE: only valid for "Interp" PSF
psf_dir: "/share/simudata/CSSOSDataProductsSims/data/psfCube"
# path to field-distortion model
# Note: only valid when ins_effects: field_dist is "ON"
fd_path: "FieldDistModelGlobal_v1.0.pickle"
# sigma_spin: 0.0 # psf spin?
###############################################
# Shear setting
###############################################
......@@ -138,19 +142,28 @@ shear_setting:
# Options to generate mock shear field:
# "constant": all galaxies are assigned a constant reduced shear
# "catalog": from catalog
shear_type: "constant"
# "extra": from seprate file
shear_type: "catalog"
# For constant shear filed
reduced_g1: 0.026
reduced_g2: 0.015
reduced_g1: 0.
reduced_g2: 0.
# Representation of the shear vector?
reShear: "E"
# rotate galaxy ellipticity
rotateEll: 0. # [degree]
# Extra shear catalog
# (currently not used)
# shear_cat: "mockShear.cat"
###############################################
# Instrumental effects setting
###############################################
ins_effects:
# switches
# Note: bias_16channel, gain_16channel, and shutter_effect
# is currently not applicable to "FGS" observations
field_dist: ON # Whether to add field distortions
add_back: ON # Whether to add sky background
add_dark: ON # Whether to add dark noise
......@@ -171,20 +184,20 @@ ins_effects:
add_deadpixels: ON # Whether to add dead(dark) pixels
bright_fatter: ON # Whether to simulate Brighter-Fatter (also diffusion) effect
# Values:
# default values have been defined individually for each chip in:
# ObservationSim/Instrument/data/ccd/chip_definition.json
# Set them here will override the default values
# dark_exptime: 300 # Exposure time for dark current frames [seconds]
# flat_exptime: 150 # Exposure time for flat-fielding frames [seconds]
# readout_time: 40 # The read-out time for each channel [seconds]
# df_strength: 2.3 # Sillicon sensor diffusion strength
# bias_level: 500 # bias level [e-/pixel]
# gain: 1.1 # Gain
# full_well: 90000 # Full well depth [e-]
# values
dark_exptime: 300 # Exposure time for dark current frames [seconds]
flat_exptime: 150 # Exposure time for flat-fielding frames [seconds]
readout_time: 40 # The read-out time for each channel [seconds]
df_strength: 2.3 # Sillicon sensor diffusion strength
bias_level: 500 # bias level [e-/pixel]
gain: 1.1 # Gain
full_well: 90000 # Full well depth [e-]
NBias: 1 # Number of bias frames to be exported for each exposure
NDark: 1 # Number of dark frames to be exported for each exposure
NFlat: 1 # Number of flat frames to be exported for each exposure
###############################################
# Output options (for calibration pointings only)
# Output options
###############################################
output_setting:
readout16: OFF # Whether to export as 16 channels (subimages) with pre- and over-scan
......@@ -193,14 +206,12 @@ output_setting:
dark_output: ON # Whether to export the combined dark current files
flat_output: ON # Whether to export the combined flat-fielding files
prnu_output: OFF # Whether to export the PRNU (pixel-to-pixel flat-fielding) files
NBias: 1 # Number of bias frames to be exported for each exposure
NDark: 1 # Number of dark frames to be exported for each exposure
NFlat: 1 # Number of flat frames to be exported for each exposure
###############################################
# Random seeds
###############################################
random_seeds:
seed_Av: 121212 # Seed for generating random intrinsic extinction
seed_poisson: 20210601 # Seed for Poisson noise
seed_CR: 20210317 # Seed for generating random cosmic ray maps
seed_flat: 20210101 # Seed for generating random flat fields
......
tests/testData/csst_fz_gc0/wfc-cr-attachpixel.dat 0 → 100755
View file @ edd720e6
# 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
tests/test_BF_CTE.py 0 → 100644
View file @ edd720e6
import unittest
import sys,os,math
from itertools import islice
import numpy as np
import copy
import ctypes
import galsim
import yaml
from astropy.io import fits
from ObservationSim.Instrument import Chip, Filter, FilterParam, FocalPlane
from ObservationSim.Instrument.Chip import ChipUtils as chip_utils
#from ObservationSim.sim_steps import add_brighter_fatter_CTE
from ObservationSim.Instrument.Chip.libCTI.CTI_modeling import CTI_sim
try:
import importlib.resources as pkg_resources
except ImportError:
# Try backported to PY<37 'importlib_resources'
import importlib_resources as pkg_resources
### test FUNCTION --- START ###
def add_brighter_fatter(img):
#Inital dynamic lib
try:
with pkg_resources.files('ObservationSim.Instrument.Chip.libBF').joinpath("libmoduleBF.so") as lib_path:
lib_bf = ctypes.CDLL(lib_path)
except AttributeError:
with pkg_resources.path('ObservationSim.Instrument.Chip.libBF', "libmoduleBF.so") as lib_path:
lib_bf = ctypes.CDLL(lib_path)
lib_bf.addEffects.argtypes = [ctypes.c_int, ctypes.c_int, ctypes.POINTER(ctypes.c_float), ctypes.POINTER(ctypes.c_float), ctypes.c_int]
# Set bit flag
bit_flag = 1
bit_flag = bit_flag | (1 << 2)
nx, ny = img.array.shape
nn = nx * ny
arr_ima= (ctypes.c_float*nn)()
arr_imc= (ctypes.c_float*nn)()
arr_ima[:]= img.array.reshape(nn)
arr_imc[:]= np.zeros(nn)
lib_bf.addEffects(nx, ny, arr_ima, arr_imc, bit_flag)
img.array[:, :] = np.reshape(arr_imc, [nx, ny])
del arr_ima, arr_imc
return img
### test FUNCTION --- END ###
def defineCCD(iccd, config_file):
with open(config_file, "r") as stream:
try:
config = yaml.safe_load(stream)
#for key, value in config.items():
# print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
chip = Chip(chipID=iccd, config=config)
chip.img = galsim.ImageF(400, 200) #galsim.ImageF(chip.npix_x, chip.npix_y)
focal_plane = FocalPlane(chip_list=[iccd])
chip.img.wcs= focal_plane.getTanWCS(192.8595, 27.1283, -113.4333*galsim.degrees, chip.pix_scale)
return chip
def defineFilt(chip):
filter_param = FilterParam()
filter_id, filter_type = chip.getChipFilter()
filt = Filter(
filter_id=filter_id,
filter_type=filter_type,
filter_param=filter_param,
ccd_bandpass=chip.effCurve)
bandpass_list = filt.bandpass_sub_list
return filt
class detModule_coverage(unittest.TestCase):
def __init__(self, methodName='runTest'):
super(detModule_coverage, self).__init__(methodName)
##self.dataPath = "/public/home/chengliang/CSSOSDataProductsSims/csst-simulation/tests/UNIT_TEST_DATA" ##os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), 'csst_fz_gc1')
self.dataPath = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), 'csst_fz_msc')
self.iccd = 1
def test_add_brighter_fatter(self):
config_file = os.path.join(self.dataPath, 'config_test.yaml')
chip = defineCCD(self.iccd, config_file)
filt = defineFilt(chip)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
#objA-lowSFB
obj = galsim.Gaussian(sigma=0.2, flux=1000)
arr = obj.drawImage(nx=64, ny=64, scale=0.074).array
chip.img.array[(100-32):(100+32),(200-32):(200+32)] = arr[:,:]
img_old = copy.deepcopy(chip.img)
img_new = add_brighter_fatter(img=chip.img)
arr1= img_old.array
arr2= img_new.array
deltaA_max = np.max(np.abs(arr2-arr1))
print('deltaA-max:', np.max(np.abs(arr2-arr1)))
print('deltaA-min:', np.min(np.abs(arr2-arr1)))
#objB-highSFB
obj = galsim.Gaussian(sigma=0.2, flux=10000)
arr = obj.drawImage(nx=64, ny=64, scale=0.074).array
chip.img.array[(100-32):(100+32),(200-32):(200+32)] = arr[:,:]
img_old = copy.deepcopy(chip.img)
img_new = add_brighter_fatter(img=chip.img)
arr3= img_old.array
arr4= img_new.array
deltaB_max = np.max(np.abs(arr4-arr3))
print('deltaB-max:', np.max(np.abs(arr4-arr3)))
print('deltaB-min:', np.min(np.abs(arr4-arr3)))
self.assertTrue( deltaB_max > deltaA_max )
def test_apply_CTE(self):
config_file = os.path.join(self.dataPath, 'config_test.yaml')
chip = defineCCD(self.iccd, config_file)
filt = defineFilt(chip)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
print(" Apply CTE Effect")
nx,ny,noverscan,nsp,nmax = 4608,4616,84,3,10
ntotal = 4700
beta,w,c = 0.478,84700,0
t = np.array([0.74,7.7,37],dtype=np.float32)
rho_trap = np.array([0.6,1.6,1.4],dtype=np.float32)
trap_seeds = np.array([0,100,1000],dtype=np.int32)
release_seed = 500
image = fits.getdata(os.path.join(self.dataPath, "testCTE_image_before.fits")).astype(np.int32)
#get_trap_map(trap_seeds,nx,ny,nmax,rho_trap,beta,c,".")
#bin2fits("trap.bin",".",nsp,nx,ny,nmax)
image_cti = CTI_sim(image,nx,ny,noverscan,nsp,nmax,beta,w,c,t,rho_trap,trap_seeds,release_seed)
fits.writeto(os.path.join(self.dataPath, "testCTE_image_after.fits"),data=image_cti,overwrite=True)
if __name__ == '__main__':
unittest.main()
tests/test_PSFmodule.py 0 → 100644
View file @ edd720e6
import unittest
import sys,os,math
from itertools import islice
import numpy as np
import galsim
import yaml
from ObservationSim.Instrument import Chip, Filter, FilterParam, FocalPlane
from ObservationSim.PSF.PSFInterp import PSFInterp
def defineCCD(iccd, config_file):
with open(config_file, "r") as stream:
try:
config = yaml.safe_load(stream)
#for key, value in config.items():
# print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
chip = Chip(chipID=iccd, config=config)
chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
focal_plane = FocalPlane(chip_list=[iccd])
chip.img.wcs= focal_plane.getTanWCS(192.8595, 27.1283, -113.4333*galsim.degrees, chip.pix_scale)
return chip
def defineFilt(chip):
filter_param = FilterParam()
filter_id, filter_type = chip.getChipFilter()
filt = Filter(
filter_id=filter_id,
filter_type=filter_type,
filter_param=filter_param,
ccd_bandpass=chip.effCurve)
bandpass_list = filt.bandpass_sub_list
return bandpass_list
class PSFInterpModule_coverage(unittest.TestCase):
def __init__(self, methodName='runTest'):
super(PSFInterpModule_coverage, self).__init__(methodName)
self.dataPath = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), 'csst_fz_msc')
self.iccd = 8
def test_loadPSFSet(self):
config_file = os.path.join(self.dataPath, 'config_test.yaml')
chip = defineCCD(self.iccd, config_file)
bandpass = defineFilt(chip)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
pathTemp = self.dataPath #"/public/share/yangxuliu/CSSOSDataProductsSims/psfCube/set1_dynamic/"
psfModel= PSFInterp(chip, npsf=900, PSF_data_file=pathTemp, PSF_data_prefix="", HocBuild=True, LOG_DEBUG=True)
x, y = 4096, 4096 #imgPos[iobj, :] # try get the PSF at some location (1234, 1234) on the chip
x = x+chip.bound.xmin
y = y+chip.bound.ymin
pos_img = galsim.PositionD(x, y)
psf,_ = psfModel.get_PSF(chip=chip, pos_img=pos_img, bandpass=0, galsimGSObject=True)
psfA = psfModel.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass[0], galsimGSObject=False)
psfB = psfModel.get_PSF(chip=chip, pos_img=pos_img, findNeighMode='hoclistFind', bandpass=bandpass[0], galsimGSObject=False)
self.assertTrue( psf != None )
self.assertTrue( np.max(np.abs(psfA-psfB))<1e-6 )
if __name__ == '__main__':
unittest.main()
tests/TestSpecDisperse.py → tests/test_SpecDisperse.py
View file @ edd720e6
#
#need add environment parameter UNIT_TEST_DATA_ROOT, link to "testData/"
#linx and mac can run as follow, need modify the name of file directory
#export UNIT_TEST_DATA_ROOT=/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_develop/csst-simulation/tests/testData
#
import unittest
from ObservationSim.MockObject.SpecDisperser import rotate90, SpecDisperser
from ObservationSim.Config import ChipOutput, Config
from ObservationSim.Config import ChipOutput
from ObservationSim.Instrument import Telescope, Chip, FilterParam, Filter, FocalPlane
from ObservationSim.MockObject import MockObject, Star
from ObservationSim.PSF import PSFGauss
......@@ -18,6 +23,7 @@ from lmfit.models import LinearModel, GaussianModel
from ObservationSim.Config.Header import generateExtensionHeader
import math
import yaml
import os
def getAngle132(x1=0, y1=0, z1=0, x2=0, y2=0, z2=0, x3=0, y3=0, z3=0):
......@@ -85,13 +91,11 @@ def fit_SingleGauss(xX, yX, contmX, iHa0):
return sigmaX, err_sigmaX, fwhmX, err_fwhmX, centerX, err_centerX
def produceObj(x,y,chip, ra, dec, pa):
pos_img = galsim.PositionD(chip.bound.xmin + x, chip.bound.ymin + y)
pos_img = galsim.PositionD(x, y)
param = {}
param["star"] = 1
param["id"] = 1
param["ra"] = chip.img.wcs.posToWorld(pos_img).ra.deg
param["dec"] = chip.img.wcs.posToWorld(pos_img).dec.deg
param["z"] = 0
param["sed_type"] = 1
param["model_tag"] = 1
......@@ -99,7 +103,7 @@ def produceObj(x,y,chip, ra, dec, pa):
obj = Star(param)
header_wcs = generateExtensionHeader(
header_wcs = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -109,12 +113,21 @@ def produceObj(x,y,chip, ra, dec, pa):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw')
pos_img, offset, local_wcs, _ = obj.getPosImg_Offset_WCS(img=chip.img, chip=chip, img_header=header_wcs)
pixel_scale=chip.pix_scale,
pixel_size=chip.pix_size,
xcen=chip.x_cen,
ycen=chip.y_cen,
extName='SCI')
chip_wcs = galsim.FitsWCS(header=header_wcs)
param["ra"] = chip_wcs.posToWorld(pos_img).ra.deg
param["dec"] = chip_wcs.posToWorld(pos_img).dec.deg
# pos_img, offset, local_wcs, _, _ = obj.getPosImg_Offset_WCS(img=chip.img, chip=chip, img_header=header_wcs)
pos_img, offset, local_wcs, real_wcs, fd_shear = obj.getPosImg_Offset_WCS(img=chip.img,
chip=chip, verbose=False,
chip_wcs=chip_wcs, img_header=header_wcs)
wave = np.arange(2500, 11000.5, 0.5)
# sedLen = wave.shape[0]
flux = pow(wave, -2) * 1e8
......@@ -129,10 +142,19 @@ def produceObj(x,y,chip, ra, dec, pa):
class TestSpecDisperse(unittest.TestCase):
def __init__(self, methodName='runTest',conff = '', throughputf = ''):
def __init__(self, methodName='runTest'):
super(TestSpecDisperse,self).__init__(methodName)
self.conff = conff
self.throughputf = throughputf
self.filePath('csst_fz_gc0')
# self.conff = conff
# self.throughputf = throughputf
def filePath(self, file_name):
fn = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), file_name)
self.conff= os.path.join(fn, 'CSST_GI2.conf')
self.throughputf= os.path.join(fn, 'GI.Throughput.1st.fits')
self.testDir = fn
def test_rotate901(self):
m = np.array([[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15],[16,17,18,19,20],[21,22,23,24,25]])
......@@ -160,6 +182,7 @@ class TestSpecDisperse(unittest.TestCase):
def test_Specdistperse1(self):
star = galsim.Gaussian(fwhm=0.39)
g_img = galsim.Image(100, 100, scale=0.074)
starImg = star.drawImage(image=g_img)
......@@ -276,8 +299,8 @@ class TestSpecDisperse(unittest.TestCase):
print('Emission line position and shape test')
self.assertTrue(input_em_lam-center < deltLamda_pix)
self.assertTrue(fwhmx/deltLamda_pix*pix_scale - psf_fwhm < np.abs(0.01))
# print(fwhmx/deltLamda_pix*pix_scale - psf_fwhm)
self.assertTrue(fwhmx/deltLamda_pix*pix_scale - psf_fwhm < np.abs(0.02))
# print('error is ',np.mean((wave_flux[ids][ids1] - sed_i(wave_pix[ids][ids1]))/sed_i(wave_pix[ids][ids1])))
# self.assertTrue(np.mean((wave_flux[ids][ids1] - sed_i(wave_pix[ids][ids1]))/sed_i(wave_pix[ids][ids1]))<0.004)
plt.figure()
......@@ -388,11 +411,11 @@ class TestSpecDisperse(unittest.TestCase):
def test_double_disperse(self):
work_dir = "/public/home/fangyuedong/CSST_unittest/CSST/test/"
# work_dir = "/public/home/fangyuedong/CSST_unittest/CSST/test/"
# data_dir = "/Volumes/Extreme SSD/SimData/"
data_dir = "/data/simudata/CSSOSDataProductsSims/data/"
configFn = '/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/config/config_C6.yaml'
normFilterFn = "/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/Catalog/data/SLOAN_SDSS.g.fits"
# data_dir = "/data/simudata/CSSOSDataProductsSims/data/"
configFn = os.path.join(self.testDir, 'config_C6.yaml')
normFilterFn = os.path.join(self.testDir, 'SLOAN_SDSS.g.fits')
norm_star = Table.read(normFilterFn)
with open(configFn, "r") as stream:
try:
......@@ -401,8 +424,6 @@ class TestSpecDisperse(unittest.TestCase):
print(key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
# config = Config.read_config(configFn)
# path_dict = Config.config_dir(config,work_dir=work_dir, data_dir=data_dir)
filter_param = FilterParam()
......@@ -422,6 +443,7 @@ class TestSpecDisperse(unittest.TestCase):
chip.img.wcs = wcs_fp
obj, pos_img = produceObj(2000,4500, chip,float(config["obs_setting"]["ra_center"]), float(config["obs_setting"]["dec_center"]), float(config["obs_setting"]["image_rot"]))
# print(pos_img,chip.pix_scale)
obj.drawObj_slitless(
tel=tel,
pos_img=pos_img,
......@@ -470,7 +492,7 @@ class TestSpecDisperse(unittest.TestCase):
def test_SLSImage_rotation(self):
from astropy.wcs import WCS
configFn = '/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/config/config_C6.yaml'
configFn = os.path.join(self.testDir,'config_C6.yaml')
with open(configFn, "r") as stream:
try:
......@@ -485,7 +507,8 @@ class TestSpecDisperse(unittest.TestCase):
dec=float(config["obs_setting"]["dec_center"])
pa=float(config["obs_setting"]["image_rot"])
header_wcs1 = generateExtensionHeader(
chip.rotate_angle = 0
header_wcs1 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -495,18 +518,19 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=0)
extName='raw')
center = np.array([chip.npix_x / 2, chip.npix_y / 2])
h_wcs1 = WCS(header_wcs1)
x1, y1 = center + [100,0]
sky_1 = h_wcs1.pixel_to_world(x1,y1)
chip = Chip(1, config=config)
rot_angle = 1
header_wcs2 = generateExtensionHeader(
chip.rotate_angle = rot_angle
header_wcs2 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -516,19 +540,21 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=rot_angle)
extName='raw')
h_wcs2 = WCS(header_wcs2)
x2, y2 = h_wcs2.world_to_pixel(sky_1)
angle = getAngle132(x1,y1,0,x2,y2,0,center[0],center[1],0)
print(angle)
self.assertTrue(rot_angle - angle < np.abs(0.001))
# print("rotation angle:" ,rot_angle ,chip.rotate_angle, angle)
# self.assertTrue(rot_angle - angle < np.abs(0.001))
rot_angle = 10
header_wcs2 = generateExtensionHeader(
chip.rotate_angle = rot_angle
header_wcs2 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -538,19 +564,20 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=rot_angle)
extName='raw')
h_wcs2 = WCS(header_wcs2)
x2, y2 = h_wcs2.world_to_pixel(sky_1)
angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
print(angle)
# print("rotation angle:", rot_angle, chip.rotate_angle, angle)
self.assertTrue(rot_angle - angle < np.abs(0.001))
rot_angle = 50
header_wcs2 = generateExtensionHeader(
chip.rotate_angle = rot_angle
header_wcs2 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -560,15 +587,15 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=rot_angle)
extName='raw')
h_wcs2 = WCS(header_wcs2)
x2, y2 = h_wcs2.world_to_pixel(sky_1)
angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
print(angle)
# print(rot_angle - angle)
self.assertTrue(rot_angle - angle < np.abs(0.001))
......@@ -577,8 +604,8 @@ class TestSpecDisperse(unittest.TestCase):
ra = float(config["obs_setting"]["ra_center"])
dec = float(config["obs_setting"]["dec_center"])
pa = float(config["obs_setting"]["image_rot"])
header_wcs1 = generateExtensionHeader(
chip.rotate_angle = 0
header_wcs1 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -588,10 +615,10 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=0)
extName='raw')
center = np.array([chip.npix_x / 2, chip.npix_y / 2])
h_wcs1 = WCS(header_wcs1)
......@@ -599,7 +626,8 @@ class TestSpecDisperse(unittest.TestCase):
sky_1 = h_wcs1.pixel_to_world(x1, y1)
rot_angle = 1
header_wcs2 = generateExtensionHeader(
chip.rotate_angle = rot_angle
header_wcs2 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -609,19 +637,20 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=rot_angle)
extName='raw')
h_wcs2 = WCS(header_wcs2)
x2, y2 = h_wcs2.world_to_pixel(sky_1)
angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
print(angle)
# print(rot_angle - angle)
self.assertTrue(rot_angle - angle < np.abs(0.001))
rot_angle = 10
header_wcs2 = generateExtensionHeader(
chip.rotate_angle = rot_angle
header_wcs2 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -631,19 +660,20 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=rot_angle)
extName='raw')
h_wcs2 = WCS(header_wcs2)
x2, y2 = h_wcs2.world_to_pixel(sky_1)
angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
print(angle)
# print(rot_angle - angle)
self.assertTrue(rot_angle - angle < np.abs(0.001))
rot_angle = 50
header_wcs2 = generateExtensionHeader(
chip.rotate_angle = rot_angle
header_wcs2 = generateExtensionHeader(chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=ra,
......@@ -653,32 +683,34 @@ class TestSpecDisperse(unittest.TestCase):
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
psize=chip.pix_scale,
pixel_scale=chip.pix_scale,
row_num=chip.rowID,
col_num=chip.colID,
extName='raw', center_rot=rot_angle)
extName='raw')
h_wcs2 = WCS(header_wcs2)
x2, y2 = h_wcs2.world_to_pixel(sky_1)
angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
print(angle)
# print(rot_angle - angle)
self.assertTrue(rot_angle - angle < np.abs(0.001))
if __name__ == '__main__':
conff='/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/ObservationSim/Instrument/data/sls_conf/CSST_GI2.conf'
throughputf='/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/ObservationSim/Instrument/data/sls_conf/GI.Throughput.1st.fits'
os.environ['UNIT_TEST_DATA_ROOT']="/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_develop/csst-simulation/tests/testData"
testDir = os.getenv('UNIT_TEST_DATA_ROOT')
# conff= os.path.join(testDir, 'CSST_GI2.conf')
# throughputf= os.path.join(testDir, 'GI.Throughput.1st.fits')
suit = unittest.TestSuite()
case1 = TestSpecDisperse('test_Specdistperse1',conff,throughputf)
case1 = TestSpecDisperse('test_Specdistperse1')
suit.addTest(case1)
case2 = TestSpecDisperse('test_Specdistperse2', conff, throughputf)
case2 = TestSpecDisperse('test_Specdistperse2')
suit.addTest(case2)
case3 = TestSpecDisperse('test_Specdistperse3', conff, throughputf)
case3 = TestSpecDisperse('test_Specdistperse3')
suit.addTest(case3)
case4 = TestSpecDisperse('test_double_disperse', conff, throughputf)
case4 = TestSpecDisperse('test_double_disperse')
suit.addTest(case4)
case5 = TestSpecDisperse('test_SLSImage_rotation')
suit.addTest(case5)
......
tests/test_Straylight.py 0 → 100644
View file @ edd720e6
#
#need add environment parameter UNIT_TEST_DATA_ROOT, link to "testData/"
#linx and mac can run as follow, need modify the name of file directory
#export UNIT_TEST_DATA_ROOT=/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_develop/csst-simulation/tests/testData
#
import unittest
from ObservationSim.Straylight import Straylight
import numpy as np
import math
import astropy.constants as cons
import galsim
from astropy.table import Table
from scipy import interpolate
import matplotlib.pyplot as plt
import os
hubbleAverZodiacal = {'nuv':0.0035,'u':0.0163,'g':0.1109,'r':0.1471,'i':0.1568,'z':0.0953,'y':0.0283}
hubbleAverEarthShine = {'nuv':0.00024,'u':0.0051,'g':0.0506,'r':0.0591,'i':0.0568,'z':0.0315,'y':0.0090}
def transRaDec2D(ra, dec):
x1 = np.cos(dec / 57.2957795) * np.cos(ra / 57.2957795);
y1 = np.cos(dec / 57.2957795) * np.sin(ra / 57.2957795);
z1 = np.sin(dec / 57.2957795);
return np.array([x1, y1, z1])
def getAngle132(x1=0, y1=0, z1=0, x2=0, y2=0, z2=0, x3=0, y3=0, z3=0):
cosValue = 0;
angle = 0;
x11 = x1 - x3;
y11 = y1 - y3;
z11 = z1 - z3;
x22 = x2 - x3;
y22 = y2 - y3;
z22 = z2 - z3;
tt = np.sqrt((x11 * x11 + y11 * y11 + z11 * z11) * (x22 * x22 + y22 * y22 + z22 * z22));
if (tt == 0):
return 0;
cosValue = (x11 * x22 + y11 * y22 + z11 * z22) / tt;
if (cosValue > 1):
cosValue = 1;
if (cosValue < -1):
cosValue = -1;
angle = math.acos(cosValue);
return angle * 360 / (2 * math.pi);
def calculateAnglePwithEarth(sat = np.array([0,0,0]), pointing = np.array([0,0,0]), sun = np.array([0,0,0])):
modSat = np.sqrt(sat[0]*sat[0] + sat[1]*sat[1]+sat[2]*sat[2])
modPoint = np.sqrt(pointing[0]*pointing[0] + pointing[1]*pointing[1] + pointing[2]*pointing[2])
withLocalZenithAngle = (pointing[0] * sat[0] + pointing[1] * sat[1] + pointing[2] * sat[2]) / (modPoint*modSat)
innerM_sat_sun = sat[0] * sun[0] + sat[1] * sun[1] + sat[2] * sun[2]
cosAngle = innerM_sat_sun / (modSat * cons.au.value/1000)
isInSunSide = 1
if (cosAngle < -0.3385737): #cos109.79
isInSunSide = -1;
elif cosAngle >= -0.3385737 and cosAngle <= 0.3385737:
isInSunSide = 0;
return math.acos(withLocalZenithAngle)*180/math.pi,isInSunSide
class TestStraylight(unittest.TestCase):
def __init__(self,methodName='runTest', filter = 'i', grating = "GI"):
super(TestStraylight,self).__init__(methodName)
# print(file_name)
# fn = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), file_name)
# self.pointingData = np.loadtxt(os.path.join(fn, 'Straylight_test.dat'), dtype=np.double)
self.filePath('csst_fz_gc0')
self.filter = filter
self.grating = grating
def filePath(self, file_name):
fn = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), file_name)
self.pointingData = np.loadtxt(os.path.join(fn, 'Straylight_test.dat'), dtype=np.double)
def test_EarthShineFilter(self):
d_sh = self.pointingData.shape
sl_e_pix = np.zeros([d_sh[0],3],dtype=np.double)
for i in np.arange(d_sh[0]):
# if i > 50:
# continue
ju = self.pointingData[i, 5]
# pointing = transRaDec2D(self.pointingData[i, 0], self.pointingData[i, 1])
# print(ju, pointing, surveylist[i,3:9])
sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
e1, py = sl.calculateEarthShineFilter(filter=self.filter)
earthZenithAngle, isInSunSide = calculateAnglePwithEarth(sat=self.pointingData[i, 6:9], pointing= sl.pointing, sun=self.pointingData[i,9:12])
# e2, _ = sl.calculateZodiacalFilter2(filter='i', sun_pos=sl.sun_pos)
# e3 = sl.calculateStarLightFilter(filter='i', pointYaxis=py)
# e_all = sl.calculateStrayLightFilter(filter='i')
# s_pix, spec = sl.calculateStrayLightGrating(grating='GI')
sl_e_pix[i,0] = e1
sl_e_pix[i, 1] = earthZenithAngle
sl_e_pix[i, 2] = isInSunSide
median = np.median(sl_e_pix[:,0])
print(' average Earthshine %s: %e' % (self.filter, median))
self.assertTrue(median-hubbleAverEarthShine[self.filter] < 0.1)
plt.figure()
ids1 = sl_e_pix[:, 2] == 1
ids2 = sl_e_pix[:, 2] != 1
plt.plot(sl_e_pix[ids1, 0], sl_e_pix[ids1, 1], 'r.')
plt.plot(sl_e_pix[ids2, 0], sl_e_pix[ids2, 1], 'b.')
plt.legend(['In Sun Side', 'In Earths shadow'])
plt.xlabel('straylight-earthshine(e-/pixel/s)')
plt.ylabel('Angle with local zenith(degree)')
plt.show()
def test_ZodiacalFilter(self):
d_sh = self.pointingData.shape
sl_e_pix = np.zeros([d_sh[0],2],dtype=np.double)
for i in np.arange(d_sh[0]):
ju = self.pointingData[i, 5]
sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
e1, _ = sl.calculateZodiacalFilter2(filter=self.filter, sun_pos=sl.sun_pos)
sl_e_pix[i,0] = e1
sl_e_pix[i,1] = getAngle132(x1=self.pointingData[i,9], y1=self.pointingData[i,10], z1=self.pointingData[i,11], x2=sl.pointing[0],
y2=sl.pointing[1], z2=sl.pointing[2], x3=0, y3=0, z3=0)
plt.figure()
plt.plot(sl_e_pix[:, 0], sl_e_pix[:, 1], 'r.')
plt.xlabel('straylight-zodiacal(e-/pixel/s)')
plt.ylabel('Angle between pointing and sun(degree)')
plt.show()
median = np.median(sl_e_pix[:,0])
print(' average Zodiacal %s: %f' % (self.filter, median))
self.assertTrue(median-hubbleAverZodiacal[self.filter] < 0.1)
def test_StarFilter(self):
d_sh = self.pointingData.shape
sl_e_pix = np.zeros(d_sh[0],dtype=np.double)
tnum = 10
for i in np.arange(tnum):
# if i > 50:
# continue
ju = self.pointingData[i, 5]
# pointing = transRaDec2D(self.pointingData[i, 0], self.pointingData[i, 1])
# print(ju, pointing, surveylist[i,3:9])
sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
e1, py = sl.calculateEarthShineFilter(filter=self.filter)
# e2, _ = sl.calculateZodiacalFilter2(filter='i', sun_pos=sl.sun_pos)
e3 = sl.calculateStarLightFilter(filter=self.filter, pointYaxis=py)
# e_all = sl.calculateStrayLightFilter(filter='i')
# s_pix, spec = sl.calculateStrayLightGrating(grating='GI')
sl_e_pix[i] = e3
median = np.median(sl_e_pix[0:tnum])
print(' average Earthshine %s: %e' % (self.filter, median))
self.assertTrue(median-hubbleAverEarthShine[self.filter] < 0.2)
def test_GratingStraylight(self):
d_sh = self.pointingData.shape
sl_e_pix = np.zeros(d_sh[0],dtype=np.double)
tnum = 10
for i in np.arange(tnum):
# if i > 50:
# continue
ju = self.pointingData[i, 5]
# pointing = transRaDec2D(self.pointingData[i, 0], self.pointingData[i, 1])
# print(ju, pointing, surveylist[i,3:9])
sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
# e1, py = sl.calculateEarthShineFilter(filter=self.filter)
# e2, _ = sl.calculateZodiacalFilter2(filter='i', sun_pos=sl.sun_pos)
# e3 = sl.calculateStarLightFilter(filter=self.filter, pointYaxis=py)
# e_all = sl.calculateStrayLightFilter(filter='i')
s_pix, spec = sl.calculateStrayLightGrating(grating=self.grating)
sl_e_pix[i] = s_pix
plt.figure()
plt.plot(spec['WAVELENGTH'], spec['FLUX'], 'r')
plt.xlabel('WAVELENGTH')
plt.ylabel('F$\lambda$(erg/s/cm2/A/arcsec2)')
plt.xlim(2000,10000)
plt.show()
median = np.median(sl_e_pix[0:tnum])
print(' average Earthshine %s: %e' % (self.grating, median))
self.assertTrue(median < 0.8)
if __name__ == '__main__':
os.environ['UNIT_TEST_DATA_ROOT']="/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_develop/csst-simulation/tests/testData"
suit = unittest.TestSuite()
case1 = TestStraylight('test_EarthShineFilter', filter = 'i')
suit.addTest(case1)
case2 = TestStraylight('test_ZodiacalFilter',filter = 'i')
suit.addTest(case2)
case3 = TestStraylight('test_StarFilter', filter='i')
suit.addTest(case3)
case4 = TestStraylight('test_GratingStraylight', grating = 'GI')
suit.addTest(case4)
unittest.TextTestRunner(verbosity=2).run(suit)
\ No newline at end of file
tests/test_darknoise_func.py 0 → 100644
View file @ edd720e6
import unittest
import sys,os,math
from itertools import islice
import numpy as np
import galsim
import yaml
from ObservationSim.Instrument import Chip, Filter, FilterParam, FocalPlane
#from ObservationSim.Instrument.Chip import ChipUtils as chip_utils
### test FUNCTION --- START ###
def get_base_img(img, chip, read_noise, readout_time, dark_noise, exptime=150., InputDark=None):
if InputDark == None:
# base_level = read_noise**2 + dark_noise*(exptime+0.5*readout_time)
## base_level = dark_noise*(exptime+0.5*readout_time)
base_level = dark_noise*(exptime)
base_img1 = base_level * np.ones_like(img.array)
else:
base_img1 = np.zeros_like(img.array)
ny = int(chip.npix_y/2)
nx = chip.npix_x
arr = np.arange(ny).reshape(ny, 1)
arr = np.broadcast_to(arr, (ny, nx))
base_img2 = np.zeros_like(img.array)
base_img2[:ny, :] = arr
base_img2[ny:, :] = arr[::-1,:]
base_img2[:,:] = base_img2[:,:]*(readout_time/ny)*dark_noise
return base_img1+base_img2
### test FUNCTION --- END ###
def defineCCD(iccd, config_file):
with open(config_file, "r") as stream:
try:
config = yaml.safe_load(stream)
#for key, value in config.items():
# print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
chip = Chip(chipID=iccd, config=config)
chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
focal_plane = FocalPlane(chip_list=[iccd])
chip.img.wcs= focal_plane.getTanWCS(192.8595, 27.1283, -113.4333*galsim.degrees, chip.pix_scale)
return chip
def defineFilt(chip):
filter_param = FilterParam()
filter_id, filter_type = chip.getChipFilter()
filt = Filter(
filter_id=filter_id,
filter_type=filter_type,
filter_param=filter_param,
ccd_bandpass=chip.effCurve)
bandpass_list = filt.bandpass_sub_list
return bandpass_list
class detModule_coverage(unittest.TestCase):
def __init__(self, methodName='runTest'):
super(detModule_coverage, self).__init__(methodName)
self.dataPath = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), 'csst_fz_msc')
self.iccd = 1
def test_add_dark(self):
config_file = os.path.join(self.dataPath, 'config_test.yaml')
chip = defineCCD(self.iccd, config_file)
bandpass = defineFilt(chip)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
exptime=150.
base_img = get_base_img(img=chip.img, chip=chip, read_noise=chip.read_noise, readout_time=chip.readout_time, dark_noise=chip.dark_noise, exptime=exptime, InputDark=None)
ny = int(chip.npix_y/2)
self.assertTrue( np.abs(np.max(base_img) - (exptime*chip.dark_noise+(ny-1)*(chip.readout_time/ny)*chip.dark_noise )) < 1e-6 )
self.assertTrue( np.min(base_img) == 3 )
base_img = get_base_img(img=chip.img, chip=chip, read_noise=chip.read_noise, readout_time=chip.readout_time, dark_noise=chip.dark_noise, exptime=150., InputDark="testTag")
self.assertTrue( np.abs(np.max(base_img) - ((ny-1)*(chip.readout_time/ny)*chip.dark_noise )) < 1e-6 )
if __name__ == '__main__':
unittest.main()
tests/test_imaging.py 0 → 100644
View file @ edd720e6
import unittest
from scipy import interpolate
import astropy.constants as cons
from astropy.table import Table
import h5py as h5
import sys,os,math
from itertools import islice
import numpy as np
import galsim
import yaml
import copy
from astropy.cosmology import FlatLambdaCDM
from astropy import constants
from astropy import units as U
from ObservationSim.MockObject._util import getObservedSED
from ObservationSim.Instrument import Chip, Filter, FilterParam, FocalPlane
from ObservationSim.PSF.PSFInterp import PSFInterp
from ObservationSim.MockObject._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getABMAG
def convert_sed(mag, sed, target_filt, norm_filt=None):
bandpass = target_filt.bandpass_full
if norm_filt is not None:
norm_thr_rang_ids = norm_filt['SENSITIVITY'] > 0.001
else:
norm_filt = Table(
np.array(np.array([bandpass.wave_list*10.0, bandpass.func(bandpass.wave_list)])).T, names=(['WAVELENGTH', 'SENSITIVITY'])
)
norm_thr_rang_ids = norm_filt['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=mag,
spectrum=sed,
norm_thr=norm_filt,
sWave=np.floor(norm_filt[norm_thr_rang_ids][0][0]),
eWave=np.ceil(norm_filt[norm_thr_rang_ids][-1][0]))
sed_photon = copy.copy(sed)
sed_photon = np.array([sed_photon['WAVELENGTH'], sed_photon['FLUX']*sedNormFactor]).T
sed_photon = galsim.LookupTable(x=np.array(sed_photon[:, 0]), f=np.array(sed_photon[:, 1]), interpolant='nearest')
# Get magnitude
sed_photon = galsim.SED(sed_photon, wave_type='A', flux_type='1', fast=False)
interFlux = integrate_sed_bandpass(sed=sed_photon, bandpass=bandpass)
mag_csst = getABMAG(
interFlux=interFlux,
bandpass=bandpass
)
if target_filt.survey_type == "photometric":
return sed_photon, mag_csst, interFlux
elif target_filt.survey_type == "spectroscopic":
del sed_photon
return sed, mag_csst, interFlux
def _load_gals(file_path):
gals_cat = h5.File(file_path, 'r')['galaxies']
for ikeys in gals_cat.keys():
gals = gals_cat[ikeys]
param = {}
igals = 9
param['z'] = gals['redshift'][igals]
param['mag_use_normal'] = gals['mag_csst_g'][igals]
print(param['mag_use_normal'] )
param['e1'] = gals['ellipticity_true'][igals][0]
param['e2'] = gals['ellipticity_true'][igals][1]
param['e1_disk'] = param['e1']
param['e2_disk'] = param['e2']
param['e1_bulge'] = param['e1']
param['e2_bulge'] = param['e2']
# Masses
param['bulgemass'] = gals['bulgemass'][igals]
param['diskmass'] = gals['diskmass'][igals]
param['size'] = gals['size'][igals]
# Sersic index
param['disk_sersic_idx'] = 1.
param['bulge_sersic_idx'] = 4.
# Sizes
param['bfrac'] = param['bulgemass']/(param['bulgemass'] + param['diskmass'])
if param['bfrac'] >= 0.6:
param['hlr_bulge'] = param['size']
param['hlr_disk'] = param['size'] * (1. - param['bfrac'])
else:
param['hlr_disk'] = param['size']
param['hlr_bulge'] = param['size'] * param['bfrac']
# SED coefficients
param['coeff'] = gals['coeff'][igals]
# TEST no redening and no extinction
param['av'] = 0.0
param['redden'] = 0
pcs = h5.File("/public/share/yangxuliu/CSSOSDataProductsSims/data_50sqDeg/sedlibs/"+"pcs.h5", "r")
lamb = h5.File("/public/share/yangxuliu/CSSOSDataProductsSims/data_50sqDeg/sedlibs/"+"lamb.h5", "r")
lamb_gal = lamb['lamb'][()]
pcs = pcs['pcs'][()]
cosmo = FlatLambdaCDM(H0=67.66, Om0=0.3111)
factor = 10**(-.4 * cosmo.distmod(param['z']).value)
flux = np.matmul(pcs, param['coeff']) * factor
# if np.any(flux < 0):
# raise ValueError("Glaxy %s: negative SED fluxes"%obj.id)
flux[flux < 0] = 0.
sedcat = np.vstack((lamb_gal, flux)).T
sed_data = getObservedSED(
sedCat=sedcat,
redshift=param['z'],
av=param["av"],
redden=param["redden"]
)
wave, flux = sed_data[0], sed_data[1]
speci = interpolate.interp1d(wave, flux)
lamb = np.arange(2000, 11001+0.5, 0.5)
y = speci(lamb)
# erg/s/cm2/A --> photon/s/m2/A
all_sed = y * lamb / (cons.h.value * cons.c.value) * 1e-13
sed = Table(np.array([lamb, all_sed]).T, names=('WAVELENGTH', 'FLUX'))
param["sed"] = sed
del wave
del flux
return param
def defineCCD(iccd, config_file):
with open(config_file, "r") as stream:
try:
config = yaml.safe_load(stream)
#for key, value in config.items():
# print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
chip = Chip(chipID=iccd, config=config)
chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
focal_plane = FocalPlane(chip_list=[iccd])
chip.img.wcs= focal_plane.getTanWCS(192.8595, 27.1283, -113.4333*galsim.degrees, chip.pix_scale)
return chip
def defineFilt(chip):
filter_param = FilterParam()
filter_id, filter_type = chip.getChipFilter()
filt = Filter(
filter_id=filter_id,
filter_type=filter_type,
filter_param=filter_param,
ccd_bandpass=chip.effCurve)
return filt
class imagingModule_coverage(unittest.TestCase):
def __init__(self, methodName='runTest'):
super(imagingModule_coverage, self).__init__(methodName)
self.dataPath = "/public/home/chengliang/CSSOSDataProductsSims/csst-simulation/tests/UNIT_TEST_DATA" ##os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), 'csst_fz_gc1')
self.iccd = 8
def test_imaging(self):
config_file = os.path.join(self.dataPath, 'config_test.yaml')
chip = defineCCD(self.iccd, config_file)
bandpass = defineFilt(chip)
filt = defineFilt(chip)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
obj = _load_gals("UNIT_TEST_DATA/galaxies_C6_bundle000287.h5")
sed_data = obj['sed']
norm_filt = None
obj_sed, obj_mag, obj_flux = convert_sed(
mag=obj["mag_use_normal"],
sed=sed_data,
target_filt=filt,
norm_filt=norm_filt,
)
pupil_area= np.pi * (0.5 * 2.)**2
exptime = 150.
nphotons_tot = obj_flux*pupil_area * exptime #getElectronFluxFilt(filt, tel, exptime)
full = integrate_sed_bandpass(sed=obj_sed, bandpass=filt.bandpass_full)
print(full, nphotons_tot, obj_mag)
for i in range(4):
sub = integrate_sed_bandpass(sed=obj_sed, bandpass=filt.bandpass_sub_list[i])
ratio = sub / full
nphotons = ratio * nphotons_tot
disk = galsim.Sersic(n=obj['disk_sersic_idx'], half_light_radius=obj['hlr_disk'], flux=1.0)
disk_shape = galsim.Shear(g1=obj['e1_disk'], g2=obj['e2_disk'])
disk = disk.shear(disk_shape)
gal_temp = disk
gal_temp = gal_temp.withFlux(nphotons)
psf = galsim.Gaussian(sigma=0.1, flux=1)
gal_temp = galsim.Convolve(psf, gal_temp)
if i == 0:
gal = gal_temp
else:
gal = gal + gal_temp
print(gal)
self.assertTrue( gal != None )
if __name__ == '__main__':
unittest.main()
tests/test_prescan_overscan_func.py 0 → 100644
View file @ edd720e6
import unittest
import sys,os,math
from itertools import islice
import numpy as np
import galsim
import yaml
from ObservationSim.Instrument import Chip, Filter, FilterParam, FocalPlane
#from ObservationSim.Instrument.Chip import ChipUtils as chip_utils
### test FUNCTION --- START ###
def AddPreScan(GSImage, pre1=27, pre2=4, over1=71, over2=80, nsecy = 2, nsecx=8):
img= GSImage.array
ny, nx = img.shape
dx = int(nx/nsecx)
dy = int(ny/nsecy)
imgt=np.zeros([int(nsecy*nsecx), int(ny/nsecy+pre2+over2), int(nx/nsecx+pre1+over1)])
for iy in range(nsecy):
for ix in range(nsecx):
if iy % 2 == 0:
tx = ix
else:
tx = (nsecx-1)-ix
ty = iy
chunkidx = int(tx+ty*nsecx) #chunk1-[1,2,3,4], chunk2-[5,6,7,8], chunk3-[9,10,11,12], chunk4-[13,14,15,16]
imgtemp = np.zeros([int(ny/nsecy+pre2+over2), int(nx/nsecx+pre1+over1)])
if int(chunkidx/4) == 0:
imgtemp[pre2:pre2+dy, pre1:pre1+dx] = img[iy*dy:(iy+1)*dy, ix*dx:(ix+1)*dx]
imgt[chunkidx, :, :] = imgtemp
if int(chunkidx/4) == 1:
imgtemp[pre2:pre2+dy, over1:over1+dx] = img[iy*dy:(iy+1)*dy, ix*dx:(ix+1)*dx]
imgt[chunkidx, :, :] = imgtemp #[:, ::-1]
if int(chunkidx/4) == 2:
imgtemp[over2:over2+dy, over1:over1+dx] = img[iy*dy:(iy+1)*dy, ix*dx:(ix+1)*dx]
imgt[chunkidx, :, :] = imgtemp #[::-1, ::-1]
if int(chunkidx/4) == 3:
imgtemp[over2:over2+dy, pre1:pre1+dx] = img[iy*dy:(iy+1)*dy, ix*dx:(ix+1)*dx]
imgt[chunkidx, :, :] = imgtemp #[::-1, :]
imgtx1 = np.hstack(imgt[:nsecx:, :, :]) #hstack chunk(1,2)-[1,2,3,4,5,6,7,8]
imgtx2 = np.hstack(imgt[:(nsecx-1):-1, :, :]) #hstack chunk(4,3)-[16,15,14,13,12,11,,10,9]
newimg = galsim.Image(int(nx+(pre1+over1)*nsecx), int(ny+(pre2+over2)*nsecy), init_value=0)
newimg.array[:, :] = np.concatenate([imgtx1, imgtx2]) #vstack chunk(1,2) & chunk(4,3)
newimg.wcs = GSImage.wcs
return newimg
### test FUNCTION --- END ###
def defineCCD(iccd, config_file):
with open(config_file, "r") as stream:
try:
config = yaml.safe_load(stream)
#for key, value in config.items():
# print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
chip = Chip(chipID=iccd, config=config)
chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
focal_plane = FocalPlane(chip_list=[iccd])
chip.img.wcs= focal_plane.getTanWCS(192.8595, 27.1283, -113.4333*galsim.degrees, chip.pix_scale)
return chip
def defineFilt(chip):
filter_param = FilterParam()
filter_id, filter_type = chip.getChipFilter()
filt = Filter(
filter_id=filter_id,
filter_type=filter_type,
filter_param=filter_param,
ccd_bandpass=chip.effCurve)
bandpass_list = filt.bandpass_sub_list
return bandpass_list
class detModule_coverage(unittest.TestCase):
def __init__(self, methodName='runTest'):
super(detModule_coverage, self).__init__(methodName)
self.dataPath = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), 'csst_fz_msc')
self.iccd = 1
def test_add_prescan_overscan(self):
config_file = os.path.join(self.dataPath, 'config_test.yaml')
chip = defineCCD(self.iccd, config_file)
bandpass = defineFilt(chip)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
chip.img = AddPreScan(GSImage=chip.img,
pre1=chip.prescan_x,
pre2=chip.prescan_y,
over1=chip.overscan_x,
over2=chip.overscan_y)
self.assertTrue( (chip.prescan_x+chip.overscan_x)*8+chip.npix_x == np.shape(chip.img.array)[1] )
self.assertTrue( (chip.prescan_y+chip.overscan_y)*2+chip.npix_y == np.shape(chip.img.array)[0] )
if __name__ == '__main__':
unittest.main()
tools/getPSF.py 0 → 100644
View file @ edd720e6
import os
import numpy as np
import ObservationSim.PSF.PSFInterp as PSFInterp
from ObservationSim.Instrument import Chip, Filter, FilterParam
import yaml
import galsim
import astropy.io.fits as fitsio
# Setup PATH
SIMPATH = "/share/simudata/CSSOSDataProductsSims/data/CSSTSimImage_C8/testRun_FGS"
config_filename= SIMPATH+"/config_C6_fits.yaml"
cat_filename = SIMPATH+"/MSC_00000000/MSC_10106100000000_chip_40_filt_FGS.cat"
# Read cat file
catFn = open(cat_filename,"r")
line = catFn.readline()
print(cat_filename,'\n',line)
imgPos = []
chipID = -1
for line in catFn:
line = line.strip()
columns = line.split()
if chipID == -1:
chipID = int(columns[1])
else:
assert chipID == int(columns[1])
ximg = float(columns[3])
yimg = float(columns[4])
imgPos.append([ximg, yimg])
imgPos = np.array(imgPos)
nobj = imgPos.shape[0]
print('chipID, nobj::', chipID, nobj)
# Read config file
with open(config_filename, "r") as stream:
try:
config = yaml.safe_load(stream)
for key, value in config.items():
print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
# Setup Chip
chip = Chip(chipID=chipID, config=config)
print('chip.bound::', chip.bound.xmin, chip.bound.xmax, chip.bound.ymin, chip.bound.ymax)
for iobj in range(nobj):
print("\nget psf for iobj-", iobj, '\t', 'bandpass:', end=" ", flush=True)
# Setup Position on focalplane
x, y = imgPos[iobj, :] # try get the PSF at some location (1234, 1234) on the chip
x = x+chip.bound.xmin
y = y+chip.bound.ymin
pos_img = galsim.PositionD(x, y)
# Setup sub-bandpass
# (There are 4 sub-bandpasses for each PSF sample)
filter_param = FilterParam()
filter_id, filter_type = chip.getChipFilter()
filt = Filter(
filter_id=filter_id,
filter_type=filter_type,
filter_param=filter_param,
ccd_bandpass=chip.effCurve)
bandpass_list = filt.bandpass_sub_list
for i in range(len(bandpass_list)):
print(i, end=" ", flush=True)
bandpass = bandpass_list[i] # say you want to access the PSF for the sub-bandpass at the blue end for that chip
# Get corresponding PSF model
psf_model = PSFInterp(chip=chip, npsf=100, PSF_data_file=config["psf_setting"]["psf_dir"])
psf = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, galsimGSObject=False)
if True:
fn = "psf_{:}.{:}.{:}.fits".format(chipID, iobj, i)
if fn != None:
if os.path.exists(fn):
os.remove(fn)
hdu = fitsio.PrimaryHDU()
hdu.data = psf
hdu.header.set('pixScale', 5)
hdu.writeto(fn)
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