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Commit fd6c3108 authored by Fang Yuedong's avatar Fang Yuedong Committed by Zhang Xin
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Release v2.0

parent ca7fb5db
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ObservationSim/Instrument/data/ccd/chip_definition.json 0 → 100644
View file @ fd6c3108
{
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}
}
\ No newline at end of file
ObservationSim/Instrument/data/filters/fgs_sub.list 0 → 100644
View file @ fd6c3108
3000
4500
4750
5000
6000
6500
7500
8500
11000
\ No newline at end of file
ObservationSim/Instrument/data/throughputs/fgs_throughput.txt 0 → 100644
View file @ fd6c3108
# fgs_cssc
# lambda_Angst throughput
2000.00 0.00000
2010.00 0.00000
2020.00 0.00000
2030.00 0.00000
2040.00 0.00000
2050.00 0.00000
2060.00 0.00000
2070.00 0.00000
2080.00 0.00000
2090.00 0.00000
2100.00 0.00000
2110.00 0.00000
2120.00 0.00000
2130.00 0.00000
2140.00 0.00000
2150.00 0.00001
2160.00 0.00001
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ObservationSim/Instrument/data/throughputs/g_throughput.txt
View file @ fd6c3108
# g_css
# g_cssc
# lambda_Angst throughput
2000.00 0.00000
2010.00 0.00000
2020.00 0.00000
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8480.00 0.00001
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8540.00 0.00001
8550.00 0.00001
8560.00 0.00002
8570.00 0.00001
8580.00 0.00001
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8610.00 0.00001
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8760.00 0.00001
8770.00 0.00001
8780.00 0.00001
8790.00 0.00001
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8970.00 0.00001
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9110.00 0.00000
......
ObservationSim/Instrument/data/throughputs/i_throughput.txt
View file @ fd6c3108
# i_css
# i_cssc
# lambda_Angst throughput
2000.00 0.00000
2010.00 0.00000
2020.00 0.00000
......@@ -458,227 +459,227 @@
6560.00 0.00000
6570.00 0.00000
6580.00 0.00000
6590.00 0.00000
6600.00 0.00000
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6850.00 0.00000
6860.00 0.04595
6870.00 0.13800
6880.00 0.23026
6890.00 0.32274
6900.00 0.41542
6910.00 0.50826
6920.00 0.60128
6930.00 0.64820
6940.00 0.64886
6950.00 0.64952
6960.00 0.65018
6970.00 0.65084
6980.00 0.65151
6990.00 0.65217
7000.00 0.65283
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7020.00 0.65386
7030.00 0.65438
7040.00 0.65489
7050.00 0.65541
7060.00 0.65592
7070.00 0.65644
7080.00 0.65695
7090.00 0.65747
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7110.00 0.65843
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7160.00 0.66063
7170.00 0.66108
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7330.00 0.66527
7340.00 0.66549
7350.00 0.66571
7360.00 0.66593
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7380.00 0.66637
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7870.00 0.66225
7880.00 0.66181
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7910.00 0.66027
7920.00 0.65960
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7940.00 0.65828
7950.00 0.65762
7960.00 0.65695
7970.00 0.65629
7980.00 0.65563
7990.00 0.65497
8000.00 0.65430
8010.00 0.65364
8020.00 0.65298
8030.00 0.65232
8040.00 0.65165
8050.00 0.65099
8060.00 0.65033
8070.00 0.64967
8080.00 0.64900
8090.00 0.64834
8100.00 0.64768
8110.00 0.64665
8120.00 0.64562
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8170.00 0.64047
8180.00 0.63944
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8200.00 0.63738
8210.00 0.63605
8220.00 0.63473
8230.00 0.63340
8240.00 0.63208
8250.00 0.63075
8260.00 0.62943
8270.00 0.62810
8280.00 0.62678
8290.00 0.62545
8300.00 0.62413
8310.00 0.62251
8320.00 0.58640
8330.00 0.51606
8340.00 0.44608
8350.00 0.37646
8360.00 0.30721
8370.00 0.23831
8380.00 0.16977
8390.00 0.10159
8400.00 0.03377
8410.00 0.00000
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6590.00 0.00001
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6620.00 0.00002
6630.00 0.00003
6640.00 0.00004
6650.00 0.00007
6660.00 0.00008
6670.00 0.00009
6680.00 0.00014
6690.00 0.00018
6700.00 0.00025
6710.00 0.00035
6720.00 0.00049
6730.00 0.00068
6740.00 0.00095
6750.00 0.00136
6760.00 0.00199
6770.00 0.00294
6780.00 0.00445
6790.00 0.00684
6800.00 0.01071
6810.00 0.01708
6820.00 0.02711
6830.00 0.04282
6840.00 0.06652
6850.00 0.09888
6860.00 0.14166
6870.00 0.19419
6880.00 0.25385
6890.00 0.31733
6900.00 0.37981
6910.00 0.43796
6920.00 0.48951
6930.00 0.53083
6940.00 0.56324
6950.00 0.58455
6960.00 0.59682
6970.00 0.60561
6980.00 0.60940
6990.00 0.60835
7000.00 0.60618
7010.00 0.60527
7020.00 0.60577
7030.00 0.60793
7040.00 0.61200
7050.00 0.61709
7060.00 0.62322
7070.00 0.63095
7080.00 0.63821
7090.00 0.64292
7100.00 0.64626
7110.00 0.64878
7120.00 0.64997
7130.00 0.65232
7140.00 0.65406
7150.00 0.65226
7160.00 0.65081
7170.00 0.65292
7180.00 0.65541
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7210.00 0.65967
7220.00 0.66207
7230.00 0.66313
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7250.00 0.66539
7260.00 0.66680
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7280.00 0.66702
7290.00 0.66646
7300.00 0.66629
7310.00 0.66932
7320.00 0.67278
7330.00 0.67504
7340.00 0.67726
7350.00 0.67778
7360.00 0.67831
7370.00 0.68199
7380.00 0.68577
7390.00 0.68984
7400.00 0.69362
7410.00 0.69332
7420.00 0.69276
7430.00 0.69385
7440.00 0.69474
7450.00 0.69416
7460.00 0.69332
7470.00 0.69433
7480.00 0.69497
7490.00 0.69420
7500.00 0.69362
7510.00 0.69276
7520.00 0.69222
7530.00 0.69099
7540.00 0.69025
7550.00 0.69202
7560.00 0.69383
7570.00 0.69339
7580.00 0.69343
7590.00 0.69509
7600.00 0.69705
7610.00 0.69930
7620.00 0.70161
7630.00 0.70368
7640.00 0.70584
7650.00 0.70841
7660.00 0.71096
7670.00 0.71507
7680.00 0.71902
7690.00 0.71999
7700.00 0.72073
7710.00 0.72065
7720.00 0.72011
7730.00 0.71996
7740.00 0.71957
7750.00 0.71536
7760.00 0.71111
7770.00 0.71377
7780.00 0.71623
7790.00 0.71655
7800.00 0.71724
7810.00 0.71336
7820.00 0.70964
7830.00 0.70962
7840.00 0.70961
7850.00 0.71095
7860.00 0.71248
7870.00 0.71171
7880.00 0.71055
7890.00 0.70995
7900.00 0.70901
7910.00 0.70812
7920.00 0.70705
7930.00 0.70299
7940.00 0.69865
7950.00 0.69705
7960.00 0.69556
7970.00 0.69552
7980.00 0.69573
7990.00 0.69293
8000.00 0.69054
8010.00 0.68913
8020.00 0.68773
8030.00 0.68869
8040.00 0.68958
8050.00 0.68922
8060.00 0.68897
8070.00 0.69058
8080.00 0.69198
8090.00 0.69425
8100.00 0.69658
8110.00 0.69466
8120.00 0.69258
8130.00 0.69134
8140.00 0.69023
8150.00 0.68944
8160.00 0.68843
8170.00 0.68879
8180.00 0.68882
8190.00 0.68806
8200.00 0.68653
8210.00 0.68482
8220.00 0.68292
8230.00 0.67639
8240.00 0.67012
8250.00 0.67081
8260.00 0.67174
8270.00 0.66608
8280.00 0.66080
8290.00 0.66262
8300.00 0.66391
8310.00 0.65922
8320.00 0.65126
8330.00 0.64064
8340.00 0.62381
8350.00 0.59850
8360.00 0.56510
8370.00 0.52167
8380.00 0.46983
8390.00 0.41697
8400.00 0.36189
8410.00 0.30067
8420.00 0.24099
8430.00 0.18838
8440.00 0.13948
8450.00 0.09907
8460.00 0.06956
8470.00 0.04814
8480.00 0.03312
8490.00 0.02220
8500.00 0.01492
8510.00 0.01022
8520.00 0.00717
8530.00 0.00507
8540.00 0.00360
8550.00 0.00259
8560.00 0.00188
8570.00 0.00137
8580.00 0.00101
8590.00 0.00078
8600.00 0.00058
8610.00 0.00046
8620.00 0.00036
8630.00 0.00028
8640.00 0.00021
8650.00 0.00017
8660.00 0.00012
8670.00 0.00011
8680.00 0.00008
8690.00 0.00006
8700.00 0.00005
8710.00 0.00004
8720.00 0.00002
8730.00 0.00003
8740.00 0.00002
8750.00 0.00002
8760.00 0.00001
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8780.00 0.00001
8790.00 0.00001
8800.00 0.00000
8810.00 0.00000
8820.00 0.00000
......
ObservationSim/Instrument/data/throughputs/nuv_throughput.txt
View file @ fd6c3108
# NUV_css
# NUV_cssc
# lambda_Angst throughput
2000.00 0.00000
2010.00 0.00000
2020.00 0.00000
......@@ -49,79 +50,79 @@
2470.00 0.00000
2480.00 0.00000
2490.00 0.00000
2500.00 0.02686
2510.00 0.08110
2520.00 0.13603
2530.00 0.16427
2540.00 0.16530
2550.00 0.16634
2560.00 0.16730
2570.00 0.16827
2580.00 0.16924
2590.00 0.17021
2600.00 0.17118
2610.00 0.17154
2620.00 0.17190
2630.00 0.17225
2640.00 0.17261
2650.00 0.17297
2660.00 0.17347
2670.00 0.17396
2680.00 0.17446
2690.00 0.17496
2700.00 0.17545
2710.00 0.17685
2720.00 0.17826
2730.00 0.17966
2740.00 0.18107
2750.00 0.18247
2760.00 0.18444
2770.00 0.18641
2780.00 0.18838
2790.00 0.19036
2800.00 0.19234
2810.00 0.19411
2820.00 0.19589
2830.00 0.19767
2840.00 0.19945
2850.00 0.20123
2860.00 0.20239
2870.00 0.20387
2880.00 0.20558
2890.00 0.20729
2900.00 0.20902
2910.00 0.20996
2920.00 0.21091
2930.00 0.21185
2940.00 0.21280
2950.00 0.21375
2960.00 0.21448
2970.00 0.21522
2980.00 0.21595
2990.00 0.21669
3000.00 0.21742
3010.00 0.21808
3020.00 0.21874
3030.00 0.21940
3040.00 0.22006
3050.00 0.22071
3060.00 0.22137
3070.00 0.22203
3080.00 0.22268
3090.00 0.22334
3100.00 0.22400
3110.00 0.22473
3120.00 0.22546
3130.00 0.22619
3140.00 0.22692
3150.00 0.22765
3160.00 0.22823
3170.00 0.22880
3180.00 0.22938
3190.00 0.22995
3200.00 0.17289
3210.00 0.11543
3220.00 0.05780
2500.00 0.00000
2510.00 0.02890
2520.00 0.07842
2530.00 0.13705
2540.00 0.16934
2550.00 0.17568
2560.00 0.18201
2570.00 0.17908
2580.00 0.17612
2590.00 0.17743
2600.00 0.17874
2610.00 0.18320
2620.00 0.18767
2630.00 0.18694
2640.00 0.18622
2650.00 0.18415
2660.00 0.18222
2670.00 0.17916
2680.00 0.17609
2690.00 0.17934
2700.00 0.18261
2710.00 0.17972
2720.00 0.17677
2730.00 0.17248
2740.00 0.16810
2750.00 0.17060
2760.00 0.17365
2770.00 0.17828
2780.00 0.18296
2790.00 0.18927
2800.00 0.19566
2810.00 0.20374
2820.00 0.21194
2830.00 0.21147
2840.00 0.21098
2850.00 0.21570
2860.00 0.21978
2870.00 0.22200
2880.00 0.22424
2890.00 0.22634
2900.00 0.22844
2910.00 0.22980
2920.00 0.23116
2930.00 0.22575
2940.00 0.22034
2950.00 0.21453
2960.00 0.20850
2970.00 0.20439
2980.00 0.20027
2990.00 0.20086
3000.00 0.20144
3010.00 0.20298
3020.00 0.20452
3030.00 0.21077
3040.00 0.21701
3050.00 0.21982
3060.00 0.22262
3070.00 0.22042
3080.00 0.21822
3090.00 0.22159
3100.00 0.22495
3110.00 0.22649
3120.00 0.22802
3130.00 0.22460
3140.00 0.22117
3150.00 0.21898
3160.00 0.21664
3170.00 0.22178
3180.00 0.22692
3190.00 0.22901
3200.00 0.17332
3210.00 0.11541
3220.00 0.05763
3230.00 0.00000
3240.00 0.00000
3250.00 0.00000
......
ObservationSim/Instrument/data/throughputs/r_throughput.txt
View file @ fd6c3108
# r_css
# r_cssc
# lambda_Angst throughput
2000.00 0.00000
2010.00 0.00000
2020.00 0.00000
......@@ -311,12 +312,12 @@
5090.00 0.00000
5100.00 0.00000
5110.00 0.00000
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5130.00 0.00000
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5120.00 0.00001
5130.00 0.00001
5140.00 0.00001
5150.00 0.00001
5160.00 0.00001
5170.00 0.00001
5180.00 0.00000
5190.00 0.00000
5200.00 0.00000
......@@ -329,228 +330,228 @@
5270.00 0.00000
5280.00 0.00000
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5340.00 0.00000
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5460.00 0.00000
5470.00 0.11125
5480.00 0.22258
5490.00 0.33397
5500.00 0.44544
5510.00 0.55704
5520.00 0.66874
5530.00 0.66902
5540.00 0.66931
5550.00 0.66960
5560.00 0.66989
5570.00 0.67018
5580.00 0.67046
5590.00 0.67075
5600.00 0.67104
5610.00 0.67104
5620.00 0.67104
5630.00 0.67104
5640.00 0.67104
5650.00 0.67104
5660.00 0.67104
5670.00 0.67104
5680.00 0.67104
5690.00 0.67104
5700.00 0.67104
5710.00 0.67104
5720.00 0.67104
5730.00 0.67104
5740.00 0.67104
5750.00 0.67104
5760.00 0.67104
5770.00 0.67104
5780.00 0.67104
5790.00 0.67104
5800.00 0.67104
5810.00 0.67104
5820.00 0.67104
5830.00 0.67104
5840.00 0.67104
5850.00 0.67104
5860.00 0.67104
5870.00 0.67104
5880.00 0.67104
5890.00 0.67104
5900.00 0.67104
5910.00 0.67082
5920.00 0.67061
5930.00 0.67039
5940.00 0.67018
5950.00 0.66996
5960.00 0.66974
5970.00 0.66953
5980.00 0.66931
5990.00 0.66910
6000.00 0.66888
6010.00 0.66852
6020.00 0.66816
6030.00 0.66780
6040.00 0.66744
6050.00 0.66708
6060.00 0.66672
6070.00 0.66636
6080.00 0.66600
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......
ObservationSim/Instrument/data/throughputs/u_throughput.txt
View file @ fd6c3108
# u_css
# u_cssc
# lambda_Angst throughput
2000.00 0.00000
2010.00 0.00000
2020.00 0.00000
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3230.00 0.20778
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......
ObservationSim/Instrument/data/throughputs/y_throughput.txt
View file @ fd6c3108
# y_css
# y_cssc
# lambda_Angst throughput
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9070.00 0.00379
9080.00 0.00654
9090.00 0.01016
9100.00 0.01473
9110.00 0.02009
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9180.00 0.04629
9190.00 0.05196
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9210.00 0.06897
9220.00 0.08142
9230.00 0.09667
9240.00 0.11727
9250.00 0.14703
9260.00 0.18512
9270.00 0.22564
9280.00 0.25914
9290.00 0.27504
9300.00 0.27413
9310.00 0.26672
9320.00 0.25628
9330.00 0.25043
9340.00 0.25056
9350.00 0.25780
9360.00 0.26953
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9380.00 0.29300
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ObservationSim/Instrument/data/throughputs/z_throughput.txt
View file @ fd6c3108
# z_css
# z_cssc
# lambda_Angst throughput
2000.00 0.00000
2010.00 0.00000
2020.00 0.00000
......@@ -273,19 +274,19 @@
4710.00 0.00000
4720.00 0.00000
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4850.00 0.00002
4860.00 0.00001
4870.00 0.00000
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4890.00 0.00000
......@@ -349,16 +350,16 @@
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5560.00 0.00002
5570.00 0.00001
5580.00 0.00001
5590.00 0.00001
5600.00 0.00000
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5620.00 0.00000
......@@ -372,20 +373,20 @@
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5840.00 0.00002
5850.00 0.00001
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5870.00 0.00000
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5890.00 0.00000
......@@ -599,304 +600,304 @@
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8350.00 0.37646
8360.00 0.44374
8370.00 0.51066
8380.00 0.57722
8390.00 0.60956
8400.00 0.60794
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10280.00 0.05111
10290.00 0.04861
10300.00 0.04624
10310.00 0.04473
10320.00 0.04323
10330.00 0.04159
10340.00 0.03990
10350.00 0.03836
10360.00 0.03685
10370.00 0.03495
10380.00 0.03347
10390.00 0.03179
10400.00 0.03022
10410.00 0.02922
10420.00 0.02809
10430.00 0.02687
10440.00 0.02562
10450.00 0.02458
10460.00 0.02340
10470.00 0.02243
10480.00 0.02127
10490.00 0.01998
10500.00 0.01877
10510.00 0.01843
10520.00 0.01806
10530.00 0.01774
10540.00 0.01732
10550.00 0.01701
10560.00 0.01671
10570.00 0.01628
10580.00 0.01597
10590.00 0.01558
10600.00 0.01522
10610.00 0.01479
10620.00 0.01442
10630.00 0.01400
10640.00 0.01363
10650.00 0.01319
10660.00 0.01273
10670.00 0.01234
10680.00 0.01193
10690.00 0.01143
10700.00 0.01087
10710.00 0.01034
10720.00 0.00980
10730.00 0.00922
10740.00 0.00860
10750.00 0.00802
10760.00 0.00742
10770.00 0.00671
10780.00 0.00610
10790.00 0.00546
10800.00 0.00478
10810.00 0.00421
10820.00 0.00366
10830.00 0.00314
10840.00 0.00267
10850.00 0.00226
10860.00 0.00189
10870.00 0.00157
10880.00 0.00130
10890.00 0.00106
10900.00 0.00085
10910.00 0.00068
10920.00 0.00054
10930.00 0.00042
10940.00 0.00032
10950.00 0.00024
10960.00 0.00017
10970.00 0.00011
10980.00 0.00007
10990.00 0.00003
11000.00 0.00000
ObservationSim/MockObject/CatalogBase.py
View file @ fd6c3108
......@@ -38,8 +38,8 @@ class CatalogBase(metaclass=ABCMeta):
"mag_use_normal":100.,
"theta":0.,
"kappa":0.,
"gamma1":0.,
"gamma2":0.,
"g1":0.,
"g2":0.,
"bfrac":0.,
"av":0.,
"redden":0.,
......@@ -48,11 +48,24 @@ class CatalogBase(metaclass=ABCMeta):
"ell_bulge":0.,
"ell_disk":0.,
"ell_tot":0.,
"e1_disk":0.,
"e2_disk":0.,
"e1_bulge":0.,
"e2_bulge":0.,
"teff":0.,
"logg":0.,
"feh":0.,
"g1":0.,
"g2":0.,
# C6 galaxies parameters
"e1":0.,
"e2":0.,
"bulgemass":0.,
"diskmass":0.,
"size":0.,
"detA":0.,
"type":0,
"veldisp":0.,
"coeff": np.zeros(20),
# Astrometry related
"pmra":0.,
"pmdec":0.,
"rv":0.,
......
ObservationSim/MockObject/Galaxy.py
View file @ fd6c3108
......@@ -9,31 +9,37 @@ from ObservationSim.MockObject._util import eObs, integrate_sed_bandpass, getNor
from ObservationSim.MockObject.SpecDisperser import SpecDisperser
from ObservationSim.MockObject.MockObject import MockObject
# import tracemalloc
class Galaxy(MockObject):
def __init__(self, param, rotation=None, logger=None):
super().__init__(param, logger=logger)
self.thetaR = self.param["theta"]
self.bfrac = self.param["bfrac"]
self.hlr_disk = self.param["hlr_disk"]
self.hlr_bulge = self.param["hlr_bulge"]
# self.thetaR = self.param["theta"]
# self.bfrac = self.param["bfrac"]
# self.hlr_disk = self.param["hlr_disk"]
# self.hlr_bulge = self.param["hlr_bulge"]
# Extract ellipticity components
self.e_disk = galsim.Shear(g=self.param["ell_disk"], beta=self.thetaR*galsim.degrees)
self.e_bulge = galsim.Shear(g=self.param["ell_bulge"], beta=self.thetaR*galsim.degrees)
self.e_total = galsim.Shear(g=self.param["ell_tot"], beta=self.thetaR*galsim.degrees)
self.e1_disk, self.e2_disk = self.e_disk.g1, self.e_disk.g2
self.e1_bulge, self.e2_bulge = self.e_bulge.g1, self.e_bulge.g2
self.e1_total, self.e2_total = self.e_total.g1, self.e_total.g2
# self.e_disk = galsim.Shear(g=self.param["ell_disk"], beta=self.thetaR*galsim.degrees)
# self.e_bulge = galsim.Shear(g=self.param["ell_bulge"], beta=self.thetaR*galsim.degrees)
# self.e_total = galsim.Shear(g=self.param["ell_tot"], beta=self.thetaR*galsim.degrees)
# self.e1_disk, self.e2_disk = self.e_disk.g1, self.e_disk.g2
# self.e1_bulge, self.e2_bulge = self.e_bulge.g1, self.e_bulge.g2
# self.e1_total, self.e2_total = self.e_total.g1, self.e_total.g2
if rotation is not None:
self.rotateEllipticity(rotation)
if not hasattr(self, "disk_sersic_idx"):
self.disk_sersic_idx = 1.
if not hasattr(self, "bulge_sersic_idx"):
self.bulge_sersic_idx = 4.
def unload_SED(self):
"""(Test) free up SED memory
"""
del self.sed
def getGSObj_multiband(self, tel, psf_list, bandpass_list, filt, nphotons_tot=None, g1=0, g2=0, exptime=150.):
def getGSObj_multiband(self, tel, psf_list, bandpass_list, filt, nphotons_tot=None, g1=0, g2=0, exptime=150., fd_shear=None):
if len(psf_list) != len(bandpass_list):
raise ValueError("!!!The number of PSF profiles and the number of bandpasses must be equal.")
objs = []
......@@ -63,10 +69,10 @@ class Galaxy(MockObject):
return -1
psf = psf_list[i]
disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0)
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape)
bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0)
bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0)
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
......@@ -75,11 +81,14 @@ class Galaxy(MockObject):
gal_shear = galsim.Shear(g1=g1, g2=g2)
gal = gal.shear(gal_shear)
gal = galsim.Convolve(psf, gal)
if fd_shear is not None:
gal = gal.shear(fd_shear)
objs.append(gal)
final = galsim.Sum(objs)
return final
def drawObj_multiband(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0, exptime=150.):
def drawObj_multiband(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0, exptime=150., fd_shear=None):
if nphotons_tot == None:
nphotons_tot = self.getElectronFluxFilt(filt, tel, exptime)
# print("nphotons_tot = ", nphotons_tot)
......@@ -89,15 +98,18 @@ class Galaxy(MockObject):
except Exception as e:
print(e)
self.logger.error(e)
return False
return 2, None
nphotons_sum = 0
photons_list = []
xmax, ymax = 0, 0
# # [C6 TEST]
# print('hlr_disk = %.4f, hlr_bulge = %.4f'%(self.hlr_disk, self.hlr_bulge))
# tracemalloc.start()
big_galaxy = False
if self.hlr_disk > 3.0: # Very big galaxy
if self.hlr_disk > 3.0 or self.hlr_bulge > 3.0: # Very big galaxy
big_galaxy = True
# (TEST) Galsim Parameters
......@@ -134,22 +146,23 @@ class Galaxy(MockObject):
if not (ratio == -1 or (ratio != ratio)):
nphotons = ratio * nphotons_tot
else:
# return False
continue
nphotons_sum += nphotons
# # [C6 TEST]
# print("nphotons_sub-band_%d = %.2f"%(i, nphotons))
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape)
bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
# # (TEST) Random knots
# (TEST) Random knots
# knots = galsim.RandomKnots(npoints=100, profile=disk)
# kfrac = np.random.random()*(1.0 - self.bfrac)
# gal = self.bfrac * bulge + (1.0 - self.bfrac - kfrac) * disk + kfrac * knots
......@@ -158,93 +171,82 @@ class Galaxy(MockObject):
gal_shear = galsim.Shear(g1=g1, g2=g2)
gal = gal.shear(gal_shear)
if self.hlr_disk < 10.0: # Not apply PSF for very big galaxy
if not big_galaxy: # Not apply PSF for very big galaxy
gal = galsim.Convolve(psf, gal)
if fd_shear is not None:
gal = gal.shear(fd_shear)
# Use (explicit) stamps to draw
# stamp = gal.drawImage(wcs=self.localWCS, method='phot', offset=self.offset, save_photons=True)
# xmax = max(xmax, stamp.xmax)
# ymax = max(ymax, stamp.ymax)
# photons = stamp.photons
# photons.x += self.x_nominal
# photons.y += self.y_nominal
# photons_list.append(photons)
stamp = gal.drawImage(wcs=real_wcs_local, method='phot', offset=offset, save_photons=True)
xmax = max(xmax, stamp.xmax)
ymax = max(ymax, stamp.ymax)
xmax = max(xmax, stamp.xmax - stamp.xmin)
ymax = max(ymax, stamp.ymax - stamp.ymin)
photons = stamp.photons
photons.x += x_nominal
photons.y += y_nominal
photons_list.append(photons)
del gal
# # [C6 TEST]
# print('xmax = %d, ymax = %d '%(xmax, ymax))
# # Output memory usage
# snapshot = tracemalloc.take_snapshot()
# top_stats = snapshot.statistics('lineno')
# for stat in top_stats[:10]:
# print(stat)
stamp = galsim.ImageF(int(xmax * 1.1), int(ymax * 1.1))
stamp.wcs = real_wcs_local
stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds]
if not big_galaxy:
for i in range(len(photons_list)):
if i == 0:
chip.sensor.accumulate(photons_list[i], stamp)
else:
chip.sensor.accumulate(photons_list[i], stamp, resume=True)
if bounds.area() > 0:
chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds]
if not big_galaxy:
for i in range(len(photons_list)):
if i == 0:
chip.sensor.accumulate(photons_list[i], stamp)
else:
chip.sensor.accumulate(photons_list[i], stamp, resume=True)
else:
sensor = galsim.Sensor()
for i in range(len(photons_list)):
if i == 0:
sensor.accumulate(photons_list[i], stamp)
else:
sensor.accumulate(photons_list[i], stamp, resume=True)
del sensor
chip.img[bounds] = stamp[bounds]
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
else:
sensor = galsim.Sensor()
for i in range(len(photons_list)):
if i == 0:
sensor.accumulate(photons_list[i], stamp)
else:
sensor.accumulate(photons_list[i], stamp, resume=True)
chip.img[bounds] = stamp[bounds]
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
# stamp = galsim.ImageF(int(xmax*1.1), int(ymax*1.1))
# stamp.wcs = self.localWCS
# stamp.setCenter(self.x_nominal, self.y_nominal)
# bounds = stamp.bounds & chip.img.bounds
# stamp[bounds] = chip.img[bounds]
#
# if not big_galaxy:
# for i in range(len(photons_list)):
# if i == 0:
# chip.sensor.accumulate(photons_list[i], stamp)
# else:
# chip.sensor.accumulate(photons_list[i], stamp, resume=True)
# else:
# sensor = galsim.Sensor()
# for i in range(len(photons_list)):
# if i == 0:
# sensor.accumulate(photons_list[i], stamp)
# else:
# sensor.accumulate(photons_list[i], stamp, resume=True)
#
# # print(stamp.array.sum())
# # chip.img[bounds] += stamp[bounds]
# chip.img[bounds] = stamp[bounds]
# # print("nphotons_sum = ", nphotons_sum)
# Return code 0: object photons missed this detector
print("obj %s missed"%(self.id))
self.logger.info("obj %s missed"%(self.id))
return 0, pos_shear
# # [C6 TEST]
# print("nphotons_sum = ", nphotons_sum)
del photons_list
del stamp
return True, pos_shear
return 1, pos_shear
def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150., normFilter=None, grating_split_pos=3685):
norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
norm_thr=normFilter,
sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]),
eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
if sedNormFactor == 0:
return False
exptime=150., normFilter=None, grating_split_pos=3685, fd_shear=None):
if normFilter is not None:
norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
norm_thr=normFilter,
sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]),
eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
if sedNormFactor == 0:
return 2, None
else:
sedNormFactor = 1.
normalSED = Table(np.array([self.sed['WAVELENGTH'], self.sed['FLUX'] * sedNormFactor]).T,
names=('WAVELENGTH', 'FLUX'))
......@@ -262,7 +264,7 @@ class Galaxy(MockObject):
big_galaxy = False
if self.hlr_disk > 3.0: # Very big galaxy
if self.hlr_disk > 3.0 or self.hlr_bulge > 3.0: # Very big galaxy
big_galaxy = True
if self.getMagFilter(filt) <= 15 and (not big_galaxy):
......@@ -280,10 +282,10 @@ class Galaxy(MockObject):
bandpass = bandpass_list[i]
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape)
bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
......@@ -299,11 +301,16 @@ class Galaxy(MockObject):
gal = gal.shear(gal_shear)
gal = galsim.Convolve(psf, gal)
starImg = gal.drawImage(wcs=real_wcs_local)
if not big_galaxy: # Not apply PSF for very big galaxy
gal = galsim.Convolve(psf, gal)
if fd_shear is not None:
gal = gal.shear(fd_shear)
starImg = gal.drawImage(wcs=real_wcs_local, offset=offset)
origin_star = [y_nominal - (starImg.center.y - starImg.ymin),
x_nominal - (starImg.center.x - starImg.xmin)]
starImg.setOrigin(0, 0)
gal_origin = [origin_star[0], origin_star[1]]
gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1]
......@@ -313,6 +320,7 @@ class Galaxy(MockObject):
subImg_p1 = starImg.array[:, 0:subSlitPos]
star_p1 = galsim.Image(subImg_p1)
star_p1.setOrigin(0, 0)
origin_p1 = origin_star
xcenter_p1 = min(x_nominal,grating_split_pos_chip-1) - 0
ycenter_p1 = y_nominal-0
......@@ -329,6 +337,7 @@ class Galaxy(MockObject):
subImg_p2 = starImg.array[:, subSlitPos+1:starImg.array.shape[1]]
star_p2 = galsim.Image(subImg_p2)
star_p2.setOrigin(0, 0)
origin_p2 = [origin_star[0], grating_split_pos_chip]
xcenter_p2 = max(x_nominal, grating_split_pos_chip - 1) - 0
ycenter_p2 = y_nominal - 0
......@@ -368,16 +377,16 @@ class Galaxy(MockObject):
# print(self.y_nominal, starImg.center.y, starImg.ymin)
del psf
return True, pos_shear
return 1, pos_shear
def getGSObj(self, psf, g1=0, g2=0, flux=None, filt=None, tel=None, exptime=150.):
if flux == None:
flux = self.getElectronFluxFilt(filt, tel, exptime)
disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0)
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape)
bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0)
bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0)
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
......
ObservationSim/MockObject/MockObject.py
View file @ fd6c3108
import galsim
import numpy as np
import astropy.constants as cons
from astropy import wcs
from astropy.table import Table
from ObservationSim.MockObject._util import magToFlux, VC_A, convolveGaussXorders
......@@ -12,53 +13,36 @@ from ObservationSim.MockObject.SpecDisperser import SpecDisperser
class MockObject(object):
def __init__(self, param, logger=None):
self.param = param
for key in self.param:
setattr(self, key, self.param[key])
if self.param["star"] == 0:
self.type = "galaxy"
elif self.param["star"] == 1:
self.type = "star"
elif self.param["star"] == 2:
self.type = "quasar"
###mock_stamp_START
elif self.param["star"] == 3:
self.type = "stamp"
###mock_stamp_END
self.id = self.param["id"]
self.ra = self.param["ra"]
self.dec = self.param["dec"]
self.ra_orig = self.param["ra_orig"]
self.dec_orig = self.param["dec_orig"]
self.z = self.param["z"]
self.sed_type = self.param["sed_type"]
self.model_tag = self.param["model_tag"]
self.mag_use_normal = self.param["mag_use_normal"]
self.sed = None
# Place holder for outputs
self.av = self.param["av"]
self.redden = self.param["redden"]
self.pmra = self.param["pmra"]
self.pmdec = self.param["pmdec"]
self.rv = self.param["rv"]
self.parallax = self.param["parallax"]
self.g1 = self.param["g1"]
self.g2 = self.param["g2"]
self.thetaR = self.param["theta"]
self.bfrac = self.param["bfrac"]
self.hlr_disk = self.param["hlr_disk"]
self.hlr_bulge = self.param["hlr_bulge"]
self.e1_disk, self.e2_disk = 0., 0.
self.e1_bulge, self.e2_bulge = 0., 0.
self.additional_output_str = ""
self.fd_shear = None
self.logger = logger
def getMagFilter(self, filt):
if filt.filter_type in ["GI", "GV", "GU"]:
return self.param["mag_use_normal"]
return self.param["mag_%s" % filt.filter_type]
# (TEST) stamp size
# return 13.0
return self.param["mag_%s" % filt.filter_type.lower()]
def getFluxFilter(self, filt):
return self.param["flux_%s" % filt.filter_type]
return self.param["flux_%s" % filt.filter_type.lower()]
def getNumPhotons(self, flux, tel, exptime=150.):
pupil_area = tel.pupil_area * (100.) ** 2 # m^2 to cm^2
......@@ -85,7 +69,7 @@ class MockObject(object):
print("\n")
print("Before field distortion:\n")
print("x = %.2f, y = %.2f\n" % (self.posImg.x, self.posImg.y), flush=True)
self.posImg = fdmodel.get_Distorted(chip=chip, pos_img=self.posImg)
self.posImg, self.fd_shear = fdmodel.get_distorted(chip=chip, pos_img=self.posImg)
if verbose:
print("After field distortion:\n")
print("x = %.2f, y = %.2f\n" % (self.posImg.x, self.posImg.y), flush=True)
......@@ -96,14 +80,12 @@ class MockObject(object):
dy = y - self.y_nominal
self.offset = galsim.PositionD(dx, dy)
from astropy import wcs
if img_header is not None:
self.real_wcs = galsim.FitsWCS(header=img_header)
else:
self.real_wcs = None
return self.posImg, self.offset, self.localWCS, self.real_wcs
return self.posImg, self.offset, self.localWCS, self.real_wcs, self.fd_shear
def getRealPos(self, img, global_x=0., global_y=0., img_real_wcs=None):
img_global_pos = galsim.PositionD(global_x, global_y)
......@@ -141,7 +123,7 @@ class MockObject(object):
return img, stamp, isUpdated
def drawObj_multiband(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150.):
exptime=150., fd_shear=None):
if nphotons_tot == None:
nphotons_tot = self.getElectronFluxFilt(filt, tel, exptime)
# print("nphotons_tot = ", nphotons_tot)
......@@ -151,7 +133,7 @@ class MockObject(object):
except Exception as e:
print(e)
self.logger.error(e)
return False
return 2, None
nphotons_sum = 0
photons_list = []
......@@ -201,14 +183,6 @@ class MockObject(object):
star = star.withFlux(nphotons)
star = galsim.Convolve(psf, star)
# stamp = star.drawImage(wcs=self.localWCS, method='phot', offset=self.offset, save_photons=True)
# xmax = max(xmax, stamp.xmax)
# ymax = max(ymax, stamp.ymax)
# photons = stamp.photons
# photons.x += self.x_nominal
# photons.y += self.y_nominal
# photons_list.append(photons)
stamp = star.drawImage(wcs=real_wcs_local, method='phot', offset=offset, save_photons=True)
xmax = max(xmax, stamp.xmax)
ymax = max(ymax, stamp.ymax)
......@@ -221,37 +195,31 @@ class MockObject(object):
stamp.wcs = real_wcs_local
stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds]
for i in range(len(photons_list)):
if i == 0:
chip.sensor.accumulate(photons_list[i], stamp)
else:
chip.sensor.accumulate(photons_list[i], stamp, resume=True)
chip.img[bounds] = stamp[bounds]
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
# Test stamp size
# print(xmax, ymax)
# stamp = galsim.ImageF(int(xmax*1.1), int(ymax*1.1))
# stamp.wcs = self.localWCS
# stamp.setCenter(self.x_nominal, self.y_nominal)
# bounds = stamp.bounds & chip.img.bounds
# stamp[bounds] = chip.img[bounds]
# for i in range(len(photons_list)):
# if i == 0:
# chip.sensor.accumulate(photons_list[i], stamp)
# else:
# chip.sensor.accumulate(photons_list[i], stamp, resume=True)
#
# chip.img[bounds] = stamp[bounds]
# print(chip.img.array.sum())
# print("nphotons_sum = ", nphotons_sum)
# # (DEBUG)
# print("stamp bounds: ", stamp.bounds)
# print(bounds)
if bounds.area() > 0:
chip.img.setOrigin(0, 0)
stamp[bounds] = chip.img[bounds]
for i in range(len(photons_list)):
if i == 0:
chip.sensor.accumulate(photons_list[i], stamp)
else:
chip.sensor.accumulate(photons_list[i], stamp, resume=True)
chip.img[bounds] = stamp[bounds]
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
else:
# Return code 0: object photons missed this detector
print("obj %s missed"%(self.id))
self.logger.info("obj %s missed"%(self.id))
return 0, pos_shear
del photons_list
del stamp
return True, pos_shear
return 1, pos_shear # Return code 1: draw sucesss
def addSLStoChipImage(self, sdp=None, chip=None, xOrderSigPlus=None, local_wcs=None):
spec_orders = sdp.compute_spec_orders()
......@@ -302,17 +270,18 @@ class MockObject(object):
del spec_orders
def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150., normFilter=None, grating_split_pos=3685):
norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
norm_thr=normFilter,
sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]),
eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
# print(self.x_nominal, self.y_nominal, chip.bound)
if sedNormFactor == 0:
return False
exptime=150., normFilter=None, grating_split_pos=3685, fd_shear=None):
if normFilter is not None:
norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
norm_thr=normFilter,
sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]),
eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
if sedNormFactor == 0:
return 2, None
else:
sedNormFactor = 1.
if self.getMagFilter(filt) <= 15:
folding_threshold = 5.e-4
......@@ -347,11 +316,12 @@ class MockObject(object):
star = galsim.DeltaFunction(gsparams=gsp)
star = star.withFlux(tel.pupil_area * exptime)
star = galsim.Convolve(psf, star)
starImg = star.drawImage(nx=100, ny=100, wcs=real_wcs_local)
starImg = star.drawImage(nx=100, ny=100, wcs=real_wcs_local, offset=offset)
origin_star = [y_nominal - (starImg.center.y - starImg.ymin),
x_nominal - (starImg.center.x - starImg.xmin)]
starImg.setOrigin(0,0)
gal_origin = [origin_star[0], origin_star[1]]
gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1]
......@@ -362,6 +332,7 @@ class MockObject(object):
subImg_p1 = starImg.array[:, 0:subSlitPos]
star_p1 = galsim.Image(subImg_p1)
origin_p1 = origin_star
star_p1.setOrigin(0,0)
xcenter_p1 = min(x_nominal, grating_split_pos_chip - 1) - 0
ycenter_p1 = y_nominal - 0
......@@ -377,6 +348,7 @@ class MockObject(object):
subImg_p2 = starImg.array[:, subSlitPos + 1:starImg.array.shape[1]]
star_p2 = galsim.Image(subImg_p2)
star_p2.setOrigin(0, 0)
origin_p2 = [origin_star[0], grating_split_pos_chip]
xcenter_p2 = max(x_nominal, grating_split_pos_chip - 1) - 0
ycenter_p2 = y_nominal - 0
......@@ -414,7 +386,7 @@ class MockObject(object):
self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=real_wcs_local)
del sdp
del psf
return True, pos_shear
return 1, pos_shear
def SNRestimate(self, img_obj, flux, noise_level=0.0, seed=31415):
img_flux = img_obj.added_flux
......@@ -425,6 +397,3 @@ class MockObject(object):
sig_obj = np.std(stamp.array)
snr_obj = img_flux / sig_obj
return snr_obj
# def getObservedEll(self, g1=0, g2=0):
# return 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
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