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    returnType: N/A
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  - BBCount: 82
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    returnType: N/A
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    linkageType: pythonLinkage
    raised:
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    returnType: N/A
  - BBCount: 15
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    - N/A
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    linkageType: pythonLinkage
    raised:
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    returnType: N/A
  - BBCount: 8
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    ICount: 2
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    functionsReached:
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  Function list name: All functions
Function coverage:
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  - 110
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  - 67
  - 68
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  - 26
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  - 30
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  numpy.__config__.show:
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  - 962
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  - 980
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  - 234
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  - 293
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  numpy.f2py.crackfortran.analyzevars.compute_deps:
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  numpy.f2py.crackfortran.appenddecl:
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  numpy.f2py.crackfortran.appendmultiline:
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  numpy.f2py.crackfortran.buildimplicitrules:
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  numpy.f2py.crackfortran.character_backward_compatibility_hook:
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  numpy.f2py.crackfortran.character_backward_compatibility_hook.fix_usage:
  - 3428
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  numpy.f2py.crackfortran.common2fortran:
  - 3120
  - 3121
  - 3122
  - 3124
  numpy.f2py.crackfortran.crack2fortran:
  - 3325
  numpy.f2py.crackfortran.crack2fortrangen:
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  - 3085
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  numpy.f2py.crackfortran.crackfortran:
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  - 3310
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  - 3313
  - 3314
  - 3315
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  - 3317
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  numpy.f2py.crackfortran.crackline:
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  numpy.f2py.crackfortran.cracktypespec:
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  numpy.f2py.crackfortran.cracktypespec0:
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  - 1575
  - 1576
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  - 1580
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  numpy.f2py.crackfortran.determineexprtype:
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  - 3001
  - 3002
  - 3004
  - 3005
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  - 3007
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  - 3028
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  - 3031
  - 3032
  - 3033
  - 3035
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  numpy.f2py.crackfortran.expr2name:
  - 2947
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  - 2917
  - 2918
  - 2919
  - 2920
  - 2922
  - 2923
  - 2924
  - 2927
  - 2934
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  numpy.f2py.crackfortran.get_parameters:
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  numpy.f2py.crackfortran.get_sorted_names:
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  numpy.f2py.crackfortran.get_usedict:
  - 1940
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  - 1942
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  numpy.f2py.crackfortran.get_useparameters:
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  numpy.f2py.crackfortran.getblockname:
  - 1922
  numpy.f2py.crackfortran.getextension:
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  numpy.f2py.crackfortran.getlincoef:
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  numpy.f2py.crackfortran.is_free_format:
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  numpy.f2py.crackfortran.markinnerspaces:
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  numpy.f2py.crackfortran.markoutercomma:
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  numpy.f2py.crackfortran.markouterparen:
  - 866
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  numpy.f2py.crackfortran.myeval:
  - 2237
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  numpy.f2py.crackfortran.openhook:
  - 320
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  - 325
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  numpy.lib.recfunctions.flatten_descr:
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  - 7781
  - 7782
  - 7783
  - 7784
  - 7785
  - 7786
  - 7787
  - 7788
  - 7789
  - 7790
  numpy.ma.core.power:
  - 6941
  - 6944
  - 6945
  - 6946
  - 6948
  - 6949
  - 6951
  - 6952
  - 6956
  - 6957
  - 6958
  - 6960
  - 6962
  - 6963
  - 6965
  - 6967
  - 6968
  - 6970
  - 6899
  numpy.ma.core.ptp:
  - 6811
  - 6807
  numpy.ma.core.put:
  - 7168
  - 7170
  - 7155
  numpy.ma.core.putmask:
  - 7200
  - 7201
  - 7202
  - 7205
  - 7174
  - 7206
  - 7207
  - 7208
  - 7191
  - 7192
  - 7193
  - 7194
  - 7195
  - 7197
  - 7198
  - 7199
  numpy.ma.core.reshape:
  - 7265
  - 7266
  - 7251
  - 7263
  numpy.ma.core.resize:
  - 7328
  - 7270
  - 7324
  - 7325
  - 7326
  - 7327
  numpy.ma.core.right_shift:
  - 7145
  - 7146
  - 7147
  - 7148
  - 7150
  - 7151
  - 7134
  numpy.ma.core.round_:
  - 7527
  - 7572
  - 7573
  - 7575
  - 7576
  - 7577
  numpy.ma.core.set_fill_value:
  - 537
  - 538
  - 478
  numpy.ma.core.shape:
  - 7344
  - 7345
  numpy.ma.core.size:
  - 7350
  - 7351
  numpy.ma.core.sort:
  - 7008
  - 7011
  - 7012
  - 7015
  - 6994
  - 7006
  - 7007
  numpy.ma.core.take:
  - 6892
  - 6894
  - 6895
  numpy.ma.core.transpose:
  - 7245
  - 7213
  - 7247
  numpy.ma.core.where:
  - 7424
  - 7425
  - 7428
  - 7429
  - 7430
  - 7434
  - 7435
  - 7436
  - 7437
  - 7438
  - 7439
  - 7441
  - 7442
  - 7443
  - 7446
  - 7448
  - 7361
  - 7416
  - 7417
  - 7419
  - 7420
  - 7423
  numpy.ma.extras:
  - 480
  - 1
  - 353
  - 355
  - 481
  - 1570
  - 479
  - 2045
  - 2008
  - 343
  - 344
  - 345
  - 347
  - 348
  - 349
  - 350
  - 351
  numpy.ma.extras.MAxisConcatenator:
  - 1520
  - 1530
  numpy.ma.extras.MAxisConcatenator.__getitem__:
  - 1546
  - 1543
  numpy.ma.extras.MAxisConcatenator.makemat:
  - 1538
  - 1539
  numpy.ma.extras._covhelper:
  - 1314
  - 1319
  - 1320
  - 1322
  - 1325
  - 1328
  - 1330
  - 1331
  - 1333
  - 1335
  - 1336
  - 1338
  - 1339
  - 1340
  - 1342
  - 1343
  - 1345
  - 1346
  - 1350
  - 1351
  - 1352
  numpy.ma.extras._ezclump:
  - 1891
  - 1892
  - 1893
  - 1896
  - 1897
  - 1898
  - 1900
  - 1901
  - 1902
  - 1904
  - 1907
  - 1909
  - 1910
  - 1886
  numpy.ma.extras._fromnxfunction:
  - 215
  numpy.ma.extras._fromnxfunction.__init__:
  - 236
  numpy.ma.extras._fromnxfunction.getdoc:
  - 257
  - 239
  - 251
  - 252
  - 253
  - 254
  - 255
  numpy.ma.extras._fromnxfunction_allargs:
  - 321
  numpy.ma.extras._fromnxfunction_allargs.__call__:
  - 332
  - 334
  - 335
  - 336
  - 337
  - 338
  numpy.ma.extras._fromnxfunction_args:
  - 296
  numpy.ma.extras._fromnxfunction_args.__call__:
  - 305
  - 307
  - 308
  - 309
  - 311
  - 312
  - 313
  - 314
  - 315
  numpy.ma.extras._fromnxfunction_seq:
  - 283
  numpy.ma.extras._fromnxfunction_seq.__call__:
  - 289
  - 290
  - 291
  - 292
  numpy.ma.extras._fromnxfunction_single:
  - 265
  numpy.ma.extras._fromnxfunction_single.__call__:
  - 271
  - 272
  - 273
  - 274
  - 275
  - 277
  - 278
  - 279
  numpy.ma.extras._median:
  - 769
  - 770
  - 772
  - 774
  - 775
  - 776
  - 777
  - 779
  - 784
  - 785
  - 788
  - 793
  - 795
  - 798
  - 810
  - 812
  - 814
  - 815
  - 817
  - 819
  - 742
  - 746
  - 747
  - 748
  - 749
  - 751
  - 754
  - 756
  - 759
  - 761
  - 764
  - 765
  - 766
  - 767
  numpy.ma.extras._median.replace_masked:
  - 805
  - 806
  - 807
  numpy.ma.extras.apply_along_axis:
  - 384
  - 385
  - 387
  - 388
  - 390
  - 397
  - 398
  - 399
  - 400
  - 401
  - 411
  - 412
  - 413
  - 414
  - 417
  - 418
  - 419
  - 420
  - 421
  - 423
  - 425
  - 426
  - 427
  - 428
  - 438
  - 439
  - 440
  - 441
  - 442
  - 444
  - 445
  - 446
  - 448
  - 449
  - 372
  - 375
  - 377
  - 379
  - 380
  - 381
  - 382
  - 383
  numpy.ma.extras.apply_over_axes:
  - 455
  - 458
  - 460
  - 462
  - 463
  - 466
  - 467
  - 470
  - 471
  numpy.ma.extras.average:
  - 641
  - 642
  - 644
  - 648
  - 649
  - 652
  - 653
  - 654
  - 530
  - 605
  - 606
  - 610
  - 616
  - 617
  - 618
  - 620
  - 622
  - 623
  - 625
  - 628
  - 629
  - 633
  - 636
  numpy.ma.extras.clump_masked:
  - 1986
  - 1954
  - 1987
  - 1989
  numpy.ma.extras.clump_unmasked:
  - 1947
  - 1915
  - 1948
  - 1949
  - 1950
  numpy.ma.extras.compress_cols:
  - 952
  - 953
  - 955
  - 941
  numpy.ma.extras.compress_nd:
  - 845
  - 846
  - 848
  - 849
  - 851
  - 854
  - 857
  - 825
  - 858
  - 861
  - 862
  - 863
  numpy.ma.extras.compress_rowcols:
  - 868
  - 917
  - 919
  numpy.ma.extras.compress_rows:
  - 937
  - 923
  - 934
  - 935
  numpy.ma.extras.corrcoef:
  - 1431
  - 1478
  - 1480
  - 1482
  - 1484
  - 1485
  - 1486
  - 1488
  - 1489
  - 1492
  - 1496
  - 1497
  - 1499
  - 1502
  - 1503
  - 1504
  - 1505
  - 1506
  - 1508
  - 1509
  - 1510
  - 1511
  - 1512
  numpy.ma.extras.count_masked:
  - 51
  - 100
  - 101
  numpy.ma.extras.cov:
  - 1410
  - 1413
  - 1414
  - 1419
  - 1420
  - 1357
  - 1421
  - 1422
  - 1424
  - 1425
  numpy.ma.extras.ediff1d:
  - 1064
  - 1075
  - 1079
  - 1080
  - 1081
  - 1082
  - 1084
  - 1087
  numpy.ma.extras.flatnotmasked_contiguous:
  - 1795
  - 1796
  - 1797
  - 1800
  - 1801
  - 1802
  - 1803
  - 1752
  numpy.ma.extras.flatnotmasked_edges:
  - 1646
  - 1690
  - 1691
  - 1692
  - 1693
  - 1694
  numpy.ma.extras.flatten_inplace:
  - 362
  - 364
  - 365
  numpy.ma.extras.in1d:
  - 1220
  - 1221
  - 1222
  - 1224
  - 1228
  - 1230
  - 1202
  - 1234
  - 1235
  - 1237
  numpy.ma.extras.intersect1d:
  - 1165
  - 1166
  - 1169
  - 1170
  - 1143
  numpy.ma.extras.isin:
  - 1244
  - 1261
  - 1262
  numpy.ma.extras.issequence:
  - 43
  - 47
  numpy.ma.extras.mask_cols:
  - 1056
  - 1010
  - 1050
  - 1053
  numpy.ma.extras.mask_rows:
  - 1000
  - 1003
  - 1006
  - 959
  numpy.ma.extras.masked_all:
  - 152
  - 105
  - 151
  numpy.ma.extras.masked_all_like:
  - 157
  - 206
  - 207
  numpy.ma.extras.median:
  - 661
  - 726
  - 727
  - 730
  - 731
  - 735
  numpy.ma.extras.mr_class:
  - 1550
  numpy.ma.extras.mr_class.__init__:
  - 1568
  numpy.ma.extras.ndenumerate:
  - 1638
  - 1639
  - 1640
  - 1641
  - 1578
  - 1642
  numpy.ma.extras.notmasked_contiguous:
  - 1866
  - 1868
  - 1870
  - 1871
  - 1809
  - 1877
  - 1879
  - 1881
  numpy.ma.extras.notmasked_edges:
  - 1701
  - 1742
  - 1743
  - 1744
  - 1745
  - 1746
  numpy.ma.extras.polyfit:
  - 2012
  - 2016
  - 2017
  - 2019
  - 2020
  - 2021
  - 2022
  - 2023
  - 2024
  - 2025
  - 2029
  - 2030
  - 2031
  - 2033
  - 2035
  - 2037
  - 2039
  - 2041
  - 2043
  numpy.ma.extras.setdiff1d:
  - 1281
  - 1300
  - 1301
  - 1303
  - 1304
  - 1305
  numpy.ma.extras.setxor1d:
  - 1185
  - 1186
  - 1187
  - 1189
  - 1190
  - 1192
  - 1193
  - 1195
  - 1175
  numpy.ma.extras.union1d:
  - 1267
  - 1277
  numpy.ma.extras.unique:
  - 1093
  - 1130
  - 1133
  - 1134
  - 1135
  - 1136
  - 1138
  numpy.ma.extras.vander:
  - 2002
  - 2003
  - 2004
  - 1998
  numpy.ma.mrecords:
  - 1
  numpy.ma.mrecords.MaskedRecords:
  - 87
  numpy.ma.mrecords.MaskedRecords.__array_finalize__:
  - 160
  - 146
  - 147
  - 148
  - 149
  - 150
  - 151
  - 153
  - 154
  - 158
  - 159
  numpy.ma.mrecords.MaskedRecords.__getattribute__:
  - 193
  - 228
  - 197
  - 229
  - 235
  - 204
  - 205
  - 206
  - 207
  - 213
  - 214
  - 220
  - 221
  - 222
  - 223
  numpy.ma.mrecords.MaskedRecords.__getitem__:
  - 322
  - 323
  - 295
  - 302
  - 303
  - 305
  - 310
  - 314
  - 317
  numpy.ma.mrecords.MaskedRecords.__getstate__:
  - 442
  - 451
  - 452
  numpy.ma.mrecords.MaskedRecords.__len__:
  - 186
  - 187
  - 181
  - 189
  numpy.ma.mrecords.MaskedRecords.__new__:
  - 132
  - 133
  - 136
  - 139
  - 111
  - 116
  - 117
  - 118
  - 119
  - 121
  - 122
  - 124
  - 125
  - 126
  - 127
  numpy.ma.mrecords.MaskedRecords.__reduce__:
  - 484
  - 478
  numpy.ma.mrecords.MaskedRecords.__repr__:
  - 355
  - 356
  - 357
  - 358
  - 360
  - 350
  numpy.ma.mrecords.MaskedRecords.__setattr__:
  - 256
  - 257
  - 258
  - 280
  - 288
  - 289
  - 262
  - 290
  - 264
  - 291
  - 266
  - 270
  - 239
  - 244
  - 245
  - 248
  - 282
  - 253
  numpy.ma.mrecords.MaskedRecords.__setitem__:
  - 331
  - 332
  - 333
  - 327
  numpy.ma.mrecords.MaskedRecords.__setstate__:
  - 472
  - 473
  - 458
  - 474
  numpy.ma.mrecords.MaskedRecords.__str__:
  - 336
  - 340
  - 341
  - 342
  - 343
  - 345
  - 346
  - 347
  numpy.ma.mrecords.MaskedRecords._data:
  - 170
  - 166
  numpy.ma.mrecords.MaskedRecords._fieldmask:
  - 174
  numpy.ma.mrecords.MaskedRecords.copy:
  - 417
  - 421
  - 422
  numpy.ma.mrecords.MaskedRecords.harden_mask:
  - 403
  numpy.ma.mrecords.MaskedRecords.soften_mask:
  - 410
  numpy.ma.mrecords.MaskedRecords.tolist:
  - 426
  - 434
  - 435
  - 436
  - 437
  - 439
  numpy.ma.mrecords.MaskedRecords.view:
  - 386
  - 388
  - 389
  - 391
  - 394
  - 363
  - 396
  - 397
  - 398
  - 368
  - 369
  - 370
  - 372
  - 374
  - 376
  - 377
  - 379
  - 382
  numpy.ma.mrecords._checknames:
  - 64
  - 65
  - 68
  - 69
  - 70
  - 71
  - 73
  - 75
  - 76
  - 46
  - 53
  - 54
  - 55
  - 58
  - 60
  - 61
  numpy.ma.mrecords._get_fieldmask:
  - 81
  - 82
  numpy.ma.mrecords._guessvartypes:
  - 641
  - 643
  - 613
  - 645
  - 623
  - 624
  - 626
  - 629
  - 631
  - 634
  - 637
  - 639
  numpy.ma.mrecords._mrreconstruct:
  - 488
  - 492
  - 493
  - 494
  numpy.ma.mrecords.addfield:
  - 768
  - 770
  - 771
  - 774
  - 775
  - 777
  - 778
  - 780
  - 750
  - 759
  - 760
  - 761
  - 764
  - 765
  - 767
  numpy.ma.mrecords.fromarrays:
  - 535
  - 536
  - 537
  - 507
  - 541
  - 542
  numpy.ma.mrecords.fromrecords:
  - 581
  - 550
  - 583
  - 585
  - 586
  - 588
  - 590
  - 591
  - 595
  - 598
  - 599
  - 600
  - 601
  - 603
  - 604
  - 606
  - 607
  numpy.ma.mrecords.fromtextfile:
  - 672
  - 695
  - 696
  - 700
  - 707
  - 711
  - 712
  - 713
  - 714
  - 716
  - 720
  - 721
  - 723
  - 726
  - 727
  - 729
  - 730
  - 733
  - 734
  - 737
  - 738
  - 743
  - 744
  - 746
  numpy.ma.mrecords.openfile:
  - 650
  - 655
  - 659
  - 662
  - 663
  - 665
  numpy.ma.setup:
  - 9
  - 11
  - 12
  numpy.ma.setup.configuration:
  - 4
  - 5
  - 6
  numpy.ma.testutils:
  - 1
  numpy.ma.testutils._assert_equal_on_sequences:
  - 88
  - 89
  - 83
  - 87
  numpy.ma.testutils.almost:
  - 64
  - 71
  - 72
  - 73
  - 74
  - 75
  - 76
  - 77
  - 78
  - 79
  numpy.ma.testutils.approx:
  - 42
  - 52
  - 53
  - 54
  - 55
  - 56
  - 57
  - 58
  - 59
  - 60
  numpy.ma.testutils.assert_almost_equal:
  - 177
  - 183
  - 184
  - 186
  - 188
  numpy.ma.testutils.assert_array_almost_equal:
  - 256
  - 265
  numpy.ma.testutils.assert_array_almost_equal.compare:
  - 264
  - 263
  numpy.ma.testutils.assert_array_approx_equal:
  - 242
  - 251
  numpy.ma.testutils.assert_array_approx_equal.compare:
  - 249
  - 250
  numpy.ma.testutils.assert_array_compare:
  - 197
  - 204
  - 205
  - 206
  - 207
  - 209
  - 213
  - 214
  - 215
  numpy.ma.testutils.assert_array_equal:
  - 225
  - 221
  numpy.ma.testutils.assert_array_less:
  - 274
  - 270
  numpy.ma.testutils.assert_equal:
  - 128
  - 132
  - 134
  - 137
  - 138
  - 140
  - 141
  - 142
  - 144
  - 109
  - 114
  - 115
  - 117
  - 118
  - 119
  - 121
  - 124
  - 125
  - 126
  - 127
  numpy.ma.testutils.assert_equal_records:
  - 100
  - 101
  - 102
  - 103
  - 104
  - 94
  numpy.ma.testutils.assert_mask_equal:
  - 288
  - 280
  - 284
  - 285
  - 286
  - 287
  numpy.ma.testutils.fail_if_array_equal:
  - 237
  - 231
  numpy.ma.testutils.fail_if_array_equal.compare:
  - 236
  numpy.ma.testutils.fail_if_equal:
  - 161
  - 162
  - 163
  - 164
  - 166
  - 167
  - 168
  - 169
  - 148
  - 152
  - 153
  - 155
  - 156
  - 157
  - 159
  numpy.ma.timer_comparison:
  - 430
  - 437
  - 439
  - 440
  - 441
  - 442
  - 443
  numpy.ma.timer_comparison.ModuleTester:
  - 193
  - 290
  - 423
  - 237
  - 111
  - 213
  - 150
  - 342
  - 377
  - 122
  numpy.ma.timer_comparison.ModuleTester.assert_array_compare:
  - 50
  - 54
  - 55
  - 56
  - 58
  - 59
  - 60
  - 61
  - 62
  - 63
  - 64
  - 66
  - 67
  - 68
  - 69
  - 70
  - 74
  - 75
  - 81
  - 82
  - 83
  - 84
  - 88
  - 89
  - 90
  - 91
  - 92
  - 93
  - 100
  numpy.ma.timer_comparison.ModuleTester.assert_array_equal:
  - 104
  - 108
  numpy.ma.timer_comparison.ModuleTester.test_0:
  - 120
  - 113
  - 117
  - 119
  numpy.ma.timer_comparison.ModuleTester.test_1:
  - 128
  - 129
  - 132
  - 133
  - 134
  - 135
  - 137
  - 139
  - 140
  - 142
  - 148
  - 124
  numpy.ma.timer_comparison.ModuleTester.test_2:
  - 152
  - 156
  - 157
  - 158
  - 159
  - 161
  - 162
  - 164
  - 168
  - 175
  - 176
  - 177
  - 178
  - 179
  - 180
  - 182
  - 183
  - 187
  - 188
  - 190
  numpy.ma.timer_comparison.ModuleTester.test_3:
  - 195
  - 199
  - 201
  - 202
  - 203
  - 204
  - 205
  - 206
  - 207
  - 208
  - 209
  - 210
  - 211
  numpy.ma.timer_comparison.ModuleTester.test_4:
  - 224
  - 225
  - 226
  - 227
  - 228
  - 229
  - 230
  - 232
  - 215
  - 219
  - 220
  - 222
  - 223
  numpy.ma.timer_comparison.ModuleTester.test_5:
  - 256
  - 258
  - 260
  - 261
  - 264
  - 266
  - 268
  - 269
  - 272
  - 274
  - 276
  - 277
  - 280
  - 281
  - 282
  - 284
  - 285
  - 288
  - 239
  - 243
  - 244
  - 245
  - 248
  - 250
  - 252
  - 253
  numpy.ma.timer_comparison.ModuleTester.test_6:
  - 292
  - 296
  - 297
  - 298
  - 301
  - 305
  - 306
  - 307
  - 309
  - 310
  - 313
  - 317
  - 318
  - 319
  - 321
  - 322
  - 325
  - 329
  - 330
  - 331
  - 333
  - 334
  - 337
  numpy.ma.timer_comparison.ModuleTester.test_7:
  - 367
  - 369
  - 370
  - 372
  - 373
  - 374
  - 375
  - 344
  - 345
  - 346
  - 347
  numpy.ma.timer_comparison.ModuleTester.test_99:
  - 384
  - 387
  - 388
  - 389
  - 391
  - 392
  - 393
  - 394
  - 395
  - 398
  - 399
  - 400
  - 401
  - 402
  - 403
  - 404
  - 405
  - 406
  - 407
  - 408
  - 411
  - 413
  - 414
  - 415
  - 416
  - 417
  - 418
  - 419
  - 420
  - 421
  - 380
  - 381
  - 382
  - 383
  numpy.ma.timer_comparison.ModuleTester.test_A:
  - 425
  - 427
  numpy.matlib:
  - 5
  numpy.matlib.empty:
  - 25
  - 60
  numpy.matlib.eye:
  - 188
  - 229
  numpy.matlib.identity:
  - 152
  - 182
  - 183
  numpy.matlib.ones:
  - 104
  - 103
  - 63
  numpy.matlib.rand:
  - 232
  - 273
  - 275
  numpy.matlib.randn:
  - 328
  - 326
  - 278
  numpy.matlib.repmat:
  - 331
  - 367
  - 369
  - 371
  - 377
  - 378
  numpy.matlib.zeros:
  - 148
  - 147
  - 108
  numpy.matrixlib:
  - 1
  - 10
  numpy.matrixlib.defmatrix:
  - 1035
  - 36
  numpy.matrixlib.defmatrix._convert_from_string:
  - 32
  - 15
  - 16
  - 18
  - 21
  - 22
  - 24
  - 25
  - 26
  - 27
  - 28
  - 29
  numpy.matrixlib.defmatrix._from_string:
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  - 1031
  - 1032
  - 1011
  - 1013
  - 1014
  - 1016
  - 1017
  - 1020
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  numpy.matrixlib.defmatrix.asmatrix:
  - 69
  - 38
  numpy.matrixlib.defmatrix.bmat:
  - 1089
  - 1090
  - 1092
  - 1099
  - 1037
  - 1101
  - 1104
  - 1105
  - 1106
  - 1108
  - 1109
  - 1110
  - 1111
  numpy.matrixlib.defmatrix.matrix:
  - 74
  numpy.matrixlib.defmatrix.matrix.A:
  - 865
  - 839
  numpy.matrixlib.defmatrix.matrix.A1:
  - 869
  - 894
  numpy.matrixlib.defmatrix.matrix.H:
  - 1001
  - 970
  - 998
  - 999
  numpy.matrixlib.defmatrix.matrix.I:
  - 794
  - 835
  - 831
  numpy.matrixlib.defmatrix.matrix.T:
  - 937
  - 966
  numpy.matrixlib.defmatrix.matrix.__array_finalize__:
  - 169
  - 171
  - 173
  - 174
  - 175
  - 176
  - 179
  - 183
  - 185
  numpy.matrixlib.defmatrix.matrix.__getitem__:
  - 193
  - 197
  - 200
  - 202
  - 206
  - 209
  numpy.matrixlib.defmatrix.matrix.__mul__:
  - 216
  - 218
  - 219
  - 220
  numpy.matrixlib.defmatrix.matrix.__new__:
  - 128
  - 130
  - 131
  - 134
  - 135
  - 136
  - 137
  - 138
  - 141
  - 142
  - 145
  - 148
  - 150
  - 152
  - 156
  - 159
  - 160
  - 162
  - 116
  - 122
  - 124
  - 126
  numpy.matrixlib.defmatrix.matrix.__pow__:
  - 231
  numpy.matrixlib.defmatrix.matrix.__rmul__:
  - 224
  numpy.matrixlib.defmatrix.matrix._align:
  - 241
  - 244
  - 246
  - 248
  - 249
  numpy.matrixlib.defmatrix.matrix._collapse:
  - 257
  - 254
  numpy.matrixlib.defmatrix.matrix.all:
  - 609
  - 572
  numpy.matrixlib.defmatrix.matrix.any:
  - 569
  - 549
  numpy.matrixlib.defmatrix.matrix.argmax:
  - 683
  - 647
  numpy.matrixlib.defmatrix.matrix.argmin:
  - 721
  - 757
  numpy.matrixlib.defmatrix.matrix.flatten:
  - 377
  - 411
  numpy.matrixlib.defmatrix.matrix.max:
  - 644
  - 612
  numpy.matrixlib.defmatrix.matrix.mean:
  - 445
  - 414
  numpy.matrixlib.defmatrix.matrix.min:
  - 718
  - 686
  numpy.matrixlib.defmatrix.matrix.prod:
  - 546
  - 516
  numpy.matrixlib.defmatrix.matrix.ptp:
  - 760
  - 790
  numpy.matrixlib.defmatrix.matrix.ravel:
  - 898
  - 933
  numpy.matrixlib.defmatrix.matrix.squeeze:
  - 372
  - 324
  numpy.matrixlib.defmatrix.matrix.std:
  - 448
  - 479
  numpy.matrixlib.defmatrix.matrix.sum:
  - 288
  - 319
  numpy.matrixlib.defmatrix.matrix.tolist:
  - 265
  - 284
  numpy.matrixlib.defmatrix.matrix.var:
  - 513
  - 482
  numpy.matrixlib.setup:
  - 9
  - 11
  - 12
  numpy.matrixlib.setup.configuration:
  - 4
  - 5
  - 6
  numpy.polynomial:
  - 184
  - 1
  numpy.polynomial._polybase:
  - 1
  numpy.polynomial._polybase.ABCPolyBase:
  - 80
  - 19
  - 92
  numpy.polynomial._polybase.ABCPolyBase.__add__:
  - 537
  - 532
  - 534
  numpy.polynomial._polybase.ABCPolyBase.__call__:
  - 513
  - 511
  numpy.polynomial._polybase.ABCPolyBase.__divmod__:
  - 587
  - 586
  - 579
  - 581
  numpy.polynomial._polybase.ABCPolyBase.__eq__:
  - 649
  - 650
  - 651
  - 653
  numpy.polynomial._polybase.ABCPolyBase.__floordiv__:
  - 568
  - 567
  numpy.polynomial._polybase.ABCPolyBase.__format__:
  - 352
  - 353
  - 343
  - 344
  - 345
  - 351
  numpy.polynomial._polybase.ABCPolyBase.__getstate__:
  - 498
  - 499
  - 500
  - 501
  numpy.polynomial._polybase.ABCPolyBase.__init__:
  - 322
  - 305
  - 308
  - 309
  - 310
  - 314
  - 315
  - 316
  numpy.polynomial._polybase.ABCPolyBase.__iter__:
  - 516
  numpy.polynomial._polybase.ABCPolyBase.__len__:
  - 519
  numpy.polynomial._polybase.ABCPolyBase.__mod__:
  - 573
  - 574
  numpy.polynomial._polybase.ABCPolyBase.__mul__:
  - 553
  - 548
  - 550
  numpy.polynomial._polybase.ABCPolyBase.__ne__:
  - 658
  numpy.polynomial._polybase.ABCPolyBase.__neg__:
  - 524
  numpy.polynomial._polybase.ABCPolyBase.__pow__:
  - 592
  - 591
  numpy.polynomial._polybase.ABCPolyBase.__radd__:
  - 600
  - 597
  numpy.polynomial._polybase.ABCPolyBase.__rdiv__:
  - 618
  numpy.polynomial._polybase.ABCPolyBase.__rdivmod__:
  - 644
  - 645
  - 639
  numpy.polynomial._polybase.ABCPolyBase.__repr__:
  - 336
  - 337
  - 335
  numpy.polynomial._polybase.ABCPolyBase.__rfloordiv__:
  - 626
  - 627
  numpy.polynomial._polybase.ABCPolyBase.__rmod__:
  - 632
  - 633
  numpy.polynomial._polybase.ABCPolyBase.__rmul__:
  - 611
  - 614
  numpy.polynomial._polybase.ABCPolyBase.__rsub__:
  - 604
  - 607
  numpy.polynomial._polybase.ABCPolyBase.__str__:
  - 356
  - 357
  - 358
  numpy.polynomial._polybase.ABCPolyBase.__sub__:
  - 545
  - 540
  - 542
  numpy.polynomial._polybase.ABCPolyBase.__truediv__:
  - 564
  - 559
  numpy.polynomial._polybase.ABCPolyBase._generate_string:
  - 385
  - 387
  - 390
  - 361
  - 393
  - 394
  - 366
  - 367
  - 369
  - 370
  - 372
  - 378
  - 379
  - 381
  numpy.polynomial._polybase.ABCPolyBase._get_coefficients:
  - 292
  - 293
  - 295
  - 297
  - 267
  - 299
  numpy.polynomial._polybase.ABCPolyBase._repr_latex_:
  - 442
  - 443
  - 446
  - 447
  - 449
  - 450
  - 454
  - 455
  - 462
  - 464
  - 465
  - 466
  - 467
  - 468
  - 469
  - 471
  - 474
  - 475
  - 480
  - 481
  - 483
  - 485
  - 486
  numpy.polynomial._polybase.ABCPolyBase._repr_latex_scalar:
  - 438
  numpy.polynomial._polybase.ABCPolyBase._repr_latex_term:
  - 427
  numpy.polynomial._polybase.ABCPolyBase._str_term_ascii:
  - 418
  - 414
  numpy.polynomial._polybase.ABCPolyBase._str_term_unicode:
  - 400
  - 409
  - 404
  numpy.polynomial._polybase.ABCPolyBase.basis:
  - 1134
  - 1136
  - 1105
  - 1138
  - 1140
  - 1142
  numpy.polynomial._polybase.ABCPolyBase.cast:
  - 1184
  - 1146
  - 1180
  - 1182
  numpy.polynomial._polybase.ABCPolyBase.convert:
  - 800
  - 798
  - 794
  - 796
  - 766
  numpy.polynomial._polybase.ABCPolyBase.copy:
  - 665
  - 673
  numpy.polynomial._polybase.ABCPolyBase.cutdeg:
  - 689
  - 711
  numpy.polynomial._polybase.ABCPolyBase.degree:
  - 676
  - 686
  numpy.polynomial._polybase.ABCPolyBase.deriv:
  - 865
  - 882
  - 883
  - 884
  numpy.polynomial._polybase.ABCPolyBase.fit:
  - 936
  - 1006
  - 1007
  - 1008
  - 1011
  - 1014
  - 1015
  - 1016
  - 1019
  - 1023
  numpy.polynomial._polybase.ABCPolyBase.fromroots:
  - 1056
  - 1027
  - 1059
  - 1062
  - 1063
  - 1065
  - 1066
  - 1053
  - 1054
  - 1055
  numpy.polynomial._polybase.ABCPolyBase.has_samecoef:
  - 205
  - 190
  - 207
  numpy.polynomial._polybase.ABCPolyBase.has_samedomain:
  - 228
  - 213
  numpy.polynomial._polybase.ABCPolyBase.has_sametype:
  - 264
  - 249
  numpy.polynomial._polybase.ABCPolyBase.has_samewindow:
  - 246
  - 231
  numpy.polynomial._polybase.ABCPolyBase.identity:
  - 1095
  - 1097
  - 1099
  - 1100
  - 1101
  - 1070
  numpy.polynomial._polybase.ABCPolyBase.integ:
  - 832
  - 856
  - 857
  - 861
  - 862
  numpy.polynomial._polybase.ABCPolyBase.linspace:
  - 929
  - 930
  - 902
  - 927
  numpy.polynomial._polybase.ABCPolyBase.mapparms:
  - 803
  - 829
  numpy.polynomial._polybase.ABCPolyBase.roots:
  - 898
  - 899
  - 887
  numpy.polynomial._polybase.ABCPolyBase.trim:
  - 714
  - 733
  - 734
  numpy.polynomial._polybase.ABCPolyBase.truncate:
  - 737
  - 756
  - 757
  - 759
  - 763
  numpy.polynomial.chebyshev:
  - 1
  - 464
  - 467
  - 470
  - 473
  numpy.polynomial.chebyshev.Chebyshev:
  - 2018
  - 2019
  - 2020
  - 2021
  - 2022
  - 2023
  - 2024
  - 2025
  - 2026
  - 2027
  - 1996
  - 2028
  - 2029
  - 2074
  - 2075
  numpy.polynomial.chebyshev.Chebyshev.interpolate:
  - 2033
  - 2067
  - 2069
  - 2070
  - 2071
  numpy.polynomial.chebyshev.Chebyshev.interpolate.<lambda1>:
  - 2069
  numpy.polynomial.chebyshev._cseries_to_zseries:
  - 153
  - 134
  numpy.polynomial.chebyshev._zseries_der:
  - 302
  - 303
  - 304
  - 305
  - 278
  numpy.polynomial.chebyshev._zseries_div:
  - 256
  - 273
  - 211
  - 244
  - 245
  - 246
  - 243
  - 250
  - 247
  numpy.polynomial.chebyshev._zseries_int:
  - 333
  - 334
  - 335
  - 336
  - 310
  numpy.polynomial.chebyshev._zseries_mul:
  - 184
  - 207
  numpy.polynomial.chebyshev._zseries_to_cseries:
  - 178
  - 159
  numpy.polynomial.chebyshev.cheb2poly:
  - 451
  - 453
  - 454
  - 455
  - 398
  - 443
  - 444
  - 445
  numpy.polynomial.chebyshev.chebadd:
  - 608
  - 570
  numpy.polynomial.chebyshev.chebcompanion:
  - 1701
  - 1702
  - 1704
  - 1705
  - 1675
  - 1707
  - 1708
  - 1709
  - 1710
  - 1711
  - 1712
  numpy.polynomial.chebyshev.chebder:
  - 963
  - 935
  - 936
  - 937
  - 938
  - 939
  - 876
  - 940
  - 942
  - 944
  - 947
  - 948
  - 949
  - 952
  - 955
  - 956
  - 959
  numpy.polynomial.chebyshev.chebdiv:
  - 802
  - 803
  - 804
  - 806
  - 809
  - 810
  - 811
  - 812
  - 813
  - 751
  - 797
  - 798
  numpy.polynomial.chebyshev.chebfit:
  - 1548
  - 1671
  numpy.polynomial.chebyshev.chebfromroots:
  - 515
  - 566
  numpy.polynomial.chebyshev.chebgauss:
  - 1848
  - 1882
  - 1883
  - 1886
  - 1887
  numpy.polynomial.chebyshev.chebgrid2d:
  - 1228
  - 1277
  numpy.polynomial.chebyshev.chebgrid3d:
  - 1384
  - 1332
  numpy.polynomial.chebyshev.chebint:
  - 1052
  - 1053
  - 1054
  - 1055
  - 1057
  - 1058
  - 1059
  - 1061
  - 1063
  - 1065
  - 1067
  - 1069
  - 1072
  - 1073
  - 1074
  - 1075
  - 1077
  - 1080
  - 1083
  - 1085
  - 1088
  - 1090
  - 968
  numpy.polynomial.chebyshev.chebinterpolate:
  - 1828
  - 1831
  - 1833
  - 1837
  - 1838
  - 1839
  - 1840
  - 1781
  numpy.polynomial.chebyshev.chebline:
  - 509
  - 508
  - 477
  - 511
  numpy.polynomial.chebyshev.chebmul:
  - 742
  - 743
  - 744
  - 745
  - 746
  - 747
  - 702
  numpy.polynomial.chebyshev.chebmulx:
  - 686
  - 656
  - 688
  - 691
  - 694
  numpy.polynomial.chebyshev.chebpow:
  - 868
  - 870
  - 871
  - 872
  - 818
  - 855
  - 856
  - 857
  - 859
  - 861
  - 862
  - 863
  numpy.polynomial.chebyshev.chebpts1:
  - 1921
  - 1953
  - 1954
  - 1947
  - 1948
  - 1950
  numpy.polynomial.chebyshev.chebpts2:
  - 1984
  - 1987
  - 1988
  - 1958
  - 1981
  - 1982
  numpy.polynomial.chebyshev.chebroots:
  - 1767
  - 1768
  - 1769
  - 1770
  - 1771
  - 1774
  - 1775
  - 1776
  - 1720
  numpy.polynomial.chebyshev.chebsub:
  - 652
  - 612
  numpy.polynomial.chebyshev.chebval:
  - 1153
  - 1154
  - 1155
  - 1156
  - 1157
  - 1158
  - 1095
  - 1159
  - 1161
  - 1164
  - 1171
  numpy.polynomial.chebyshev.chebval2d:
  - 1224
  - 1179
  numpy.polynomial.chebyshev.chebval3d:
  - 1328
  - 1281
  numpy.polynomial.chebyshev.chebvander:
  - 1388
  - 1422
  - 1423
  - 1426
  - 1429
  - 1432
  - 1435
  - 1437
  numpy.polynomial.chebyshev.chebvander2d:
  - 1441
  - 1490
  numpy.polynomial.chebyshev.chebvander3d:
  - 1544
  - 1494
  numpy.polynomial.chebyshev.chebweight:
  - 1916
  - 1893
  numpy.polynomial.chebyshev.poly2cheb:
  - 389
  - 390
  - 392
  - 393
  - 348
  numpy.polynomial.hermite:
  - 1
  - 205
  - 208
  - 211
  - 214
  numpy.polynomial.hermite.Hermite:
  - 1696
  - 1692
  - 1681
  - 1682
  - 1683
  - 1684
  - 1685
  - 1686
  - 1687
  - 1688
  - 1689
  - 1690
  - 1659
  - 1691
  - 1695
  numpy.polynomial.hermite._normed_hermite_n:
  - 1545
  - 1546
  - 1549
  - 1517
  - 1550
  - 1551
  - 1553
  - 1554
  - 1556
  numpy.polynomial.hermite.herm2poly:
  - 193
  - 195
  - 196
  - 197
  - 143
  - 182
  - 183
  - 184
  - 186
  numpy.polynomial.hermite.hermadd:
  - 314
  - 350
  numpy.polynomial.hermite.hermcompanion:
  - 1408
  - 1440
  - 1441
  - 1442
  - 1443
  - 1444
  - 1445
  - 1446
  - 1434
  - 1435
  - 1437
  - 1438
  numpy.polynomial.hermite.hermder:
  - 672
  - 673
  - 676
  - 652
  - 653
  - 654
  - 655
  - 656
  - 657
  - 659
  - 661
  - 598
  - 664
  - 665
  - 666
  - 669
  numpy.polynomial.hermite.hermdiv:
  - 513
  - 557
  numpy.polynomial.hermite.hermfit:
  - 1404
  - 1276
  numpy.polynomial.hermite.hermfromroots:
  - 258
  - 310
  numpy.polynomial.hermite.hermgauss:
  - 1601
  - 1602
  - 1603
  - 1606
  - 1607
  - 1612
  - 1613
  - 1621
  - 1560
  - 1595
  - 1596
  numpy.polynomial.hermite.hermgrid2d:
  - 948
  - 997
  numpy.polynomial.hermite.hermgrid3d:
  - 1104
  - 1052
  numpy.polynomial.hermite.hermint:
  - 768
  - 769
  - 770
  - 772
  - 774
  - 776
  - 778
  - 780
  - 783
  - 784
  - 785
  - 786
  - 788
  - 791
  - 794
  - 796
  - 798
  - 681
  - 763
  - 764
  - 765
  - 766
  numpy.polynomial.hermite.hermline:
  - 218
  - 251
  - 252
  - 254
  numpy.polynomial.hermite.hermmul:
  - 485
  - 487
  - 494
  - 497
  - 501
  - 504
  - 507
  - 508
  - 509
  - 447
  numpy.polynomial.hermite.hermmulx:
  - 394
  - 432
  - 434
  - 437
  - 440
  numpy.polynomial.hermite.hermpow:
  - 561
  - 594
  numpy.polynomial.hermite.hermroots:
  - 1504
  - 1505
  - 1506
  - 1507
  - 1510
  - 1511
  - 1512
  - 1453
  - 1503
  numpy.polynomial.hermite.hermsub:
  - 354
  - 390
  numpy.polynomial.hermite.hermval:
  - 803
  - 871
  - 872
  - 873
  - 874
  - 875
  - 876
  - 877
  - 880
  - 883
  - 887
  - 890
  numpy.polynomial.hermite.hermval2d:
  - 944
  - 899
  numpy.polynomial.hermite.hermval3d:
  - 1048
  - 1001
  numpy.polynomial.hermite.hermvander:
  - 1152
  - 1155
  - 1158
  - 1160
  - 1163
  - 1165
  - 1108
  - 1151
  numpy.polynomial.hermite.hermvander2d:
  - 1169
  - 1218
  numpy.polynomial.hermite.hermvander3d:
  - 1272
  - 1222
  numpy.polynomial.hermite.hermweight:
  - 1650
  - 1627
  numpy.polynomial.hermite.poly2herm:
  - 97
  - 134
  - 135
  - 137
  - 138
  numpy.polynomial.hermite_e:
  - 1
  - 205
  - 208
  - 211
  - 214
  numpy.polynomial.hermite_e.HermiteE:
  - 1673
  - 1674
  - 1675
  - 1676
  - 1677
  - 1678
  - 1679
  - 1680
  - 1681
  - 1682
  - 1651
  - 1683
  - 1684
  - 1687
  - 1688
  numpy.polynomial.hermite_e._normed_hermite_e_n:
  - 1538
  - 1539
  - 1510
  - 1543
  - 1542
  - 1544
  - 1546
  - 1547
  numpy.polynomial.hermite_e.herme2poly:
  - 193
  - 195
  - 196
  - 197
  - 144
  - 183
  - 184
  - 185
  - 187
  numpy.polynomial.hermite_e.hermeadd:
  - 313
  - 349
  numpy.polynomial.hermite_e.hermecompanion:
  - 1427
  - 1428
  - 1430
  - 1431
  - 1400
  - 1433
  - 1434
  - 1435
  - 1436
  - 1437
  - 1438
  - 1439
  numpy.polynomial.hermite_e.hermeder:
  - 645
  - 646
  - 647
  - 648
  - 649
  - 650
  - 652
  - 654
  - 591
  - 657
  - 658
  - 659
  - 662
  - 665
  - 666
  - 669
  numpy.polynomial.hermite_e.hermediv:
  - 508
  - 550
  numpy.polynomial.hermite_e.hermefit:
  - 1267
  - 1396
  numpy.polynomial.hermite_e.hermefromroots:
  - 257
  - 309
  numpy.polynomial.hermite_e.hermegauss:
  - 1600
  - 1605
  - 1606
  - 1614
  - 1553
  - 1588
  - 1589
  - 1594
  - 1595
  - 1596
  - 1599
  numpy.polynomial.hermite_e.hermegrid2d:
  - 940
  - 989
  numpy.polynomial.hermite_e.hermegrid3d:
  - 1096
  - 1044
  numpy.polynomial.hermite_e.hermeint:
  - 769
  - 771
  - 773
  - 776
  - 777
  - 778
  - 779
  - 781
  - 784
  - 787
  - 789
  - 791
  - 674
  - 756
  - 757
  - 758
  - 759
  - 761
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  numpy.polynomial.laguerre.lagint:
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  numpy.polynomial.laguerre.lagline:
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  numpy.polynomial.laguerre.lagmul:
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  numpy.polynomial.laguerre.lagmulx:
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  numpy.polynomial.laguerre.lagpow:
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  numpy.polynomial.laguerre.lagroots:
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  numpy.polynomial.laguerre.lagsub:
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  numpy.polynomial.laguerre.lagval:
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  - 872
  - 873
  - 874
  - 875
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  - 878
  - 881
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  numpy.polynomial.laguerre.lagval3d:
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  numpy.polynomial.laguerre.lagvander3d:
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  numpy.polynomial.laguerre.lagweight:
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  - 902
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  - 1165
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  - 1172
  - 1174
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  numpy.polynomial.legendre.legvander3d:
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  numpy.polynomial.polynomial.polyfit:
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  numpy.polynomial.polynomial.polyline:
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  numpy.polynomial.polynomial.polyroots:
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  - 752
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  - 1107
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  numpy.distutils.system_info.agg2_info:
  - system_info
  numpy.distutils.system_info.amd_info:
  - system_info
  numpy.distutils.system_info.armpl_info:
  - system_info
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  - atlas_3_10_info
  numpy.distutils.system_info.atlas_3_10_blas_threads_info:
  - atlas_3_10_blas_info
  numpy.distutils.system_info.atlas_3_10_info:
  - atlas_info
  numpy.distutils.system_info.atlas_3_10_threads_info:
  - atlas_3_10_info
  numpy.distutils.system_info.atlas_blas_info:
  - atlas_info
  numpy.distutils.system_info.atlas_blas_threads_info:
  - atlas_blas_info
  numpy.distutils.system_info.atlas_info:
  - system_info
  numpy.distutils.system_info.atlas_threads_info:
  - atlas_info
  numpy.distutils.system_info.blas64__opt_info:
  - blas_ilp64_opt_info
  numpy.distutils.system_info.blas_armpl_info:
  - armpl_info
  numpy.distutils.system_info.blas_ilp64_opt_info:
  - _ilp64_opt_info_mixin
  - blas_opt_info
  numpy.distutils.system_info.blas_ilp64_plain_opt_info:
  - blas_ilp64_opt_info
  numpy.distutils.system_info.blas_info:
  - system_info
  numpy.distutils.system_info.blas_mkl_info:
  - mkl_info
  numpy.distutils.system_info.blas_opt_info:
  - system_info
  numpy.distutils.system_info.blas_src_info:
  - system_info
  numpy.distutils.system_info.blis_info:
  - blas_info
  numpy.distutils.system_info.boost_python_info:
  - system_info
  numpy.distutils.system_info.cblas_info:
  - system_info
  numpy.distutils.system_info.dfftw_info:
  - fftw_info
  numpy.distutils.system_info.dfftw_threads_info:
  - fftw_info
  numpy.distutils.system_info.djbfft_info:
  - system_info
  numpy.distutils.system_info.f2py_info:
  - system_info
  numpy.distutils.system_info.fft_opt_info:
  - system_info
  numpy.distutils.system_info.fftw2_info:
  - fftw_info
  numpy.distutils.system_info.fftw3_armpl_info:
  - fftw_info
  numpy.distutils.system_info.fftw3_info:
  - fftw_info
  numpy.distutils.system_info.fftw_info:
  - system_info
  numpy.distutils.system_info.fftw_threads_info:
  - fftw_info
  numpy.distutils.system_info.flame_info:
  - system_info
  numpy.distutils.system_info.freetype2_info:
  - _pkg_config_info
  numpy.distutils.system_info.gdk_2_info:
  - _pkg_config_info
  numpy.distutils.system_info.gdk_info:
  - _pkg_config_info
  numpy.distutils.system_info.gdk_pixbuf_2_info:
  - _pkg_config_info
  numpy.distutils.system_info.gdk_pixbuf_xlib_2_info:
  - _pkg_config_info
  numpy.distutils.system_info.gdk_x11_2_info:
  - _pkg_config_info
  numpy.distutils.system_info.gtkp_2_info:
  - _pkg_config_info
  numpy.distutils.system_info.gtkp_x11_2_info:
  - _pkg_config_info
  numpy.distutils.system_info.lapack64__opt_info:
  - lapack_ilp64_opt_info
  numpy.distutils.system_info.lapack_armpl_info:
  - armpl_info
  numpy.distutils.system_info.lapack_atlas_3_10_info:
  - atlas_3_10_info
  numpy.distutils.system_info.lapack_atlas_3_10_threads_info:
  - atlas_3_10_threads_info
  numpy.distutils.system_info.lapack_atlas_info:
  - atlas_info
  numpy.distutils.system_info.lapack_atlas_threads_info:
  - atlas_threads_info
  numpy.distutils.system_info.lapack_ilp64_opt_info:
  - lapack_opt_info
  - _ilp64_opt_info_mixin
  numpy.distutils.system_info.lapack_ilp64_plain_opt_info:
  - lapack_ilp64_opt_info
  numpy.distutils.system_info.lapack_info:
  - system_info
  numpy.distutils.system_info.lapack_mkl_info:
  - mkl_info
  numpy.distutils.system_info.lapack_opt_info:
  - system_info
  numpy.distutils.system_info.lapack_src_info:
  - system_info
  numpy.distutils.system_info.mkl_info:
  - system_info
  numpy.distutils.system_info.numarray_info:
  - _numpy_info
  numpy.distutils.system_info.numerix_info:
  - system_info
  numpy.distutils.system_info.numpy_info:
  - _numpy_info
  numpy.distutils.system_info.openblas64__info:
  - openblas_ilp64_info
  numpy.distutils.system_info.openblas64__lapack_info:
  - openblas_ilp64_lapack_info
  - openblas64__info
  numpy.distutils.system_info.openblas_clapack_info:
  - openblas_lapack_info
  numpy.distutils.system_info.openblas_ilp64_info:
  - openblas_info
  numpy.distutils.system_info.openblas_ilp64_lapack_info:
  - openblas_ilp64_info
  numpy.distutils.system_info.openblas_info:
  - blas_info
  numpy.distutils.system_info.openblas_lapack_info:
  - openblas_info
  numpy.distutils.system_info.sfftw_info:
  - fftw_info
  numpy.distutils.system_info.sfftw_threads_info:
  - fftw_info
  numpy.distutils.system_info.system_info: []
  numpy.distutils.system_info.umfpack_info:
  - system_info
  numpy.distutils.system_info.wx_info:
  - _pkg_config_info
  numpy.distutils.system_info.x11_info:
  - system_info
  numpy.distutils.system_info.xft_info:
  - _pkg_config_info
  numpy.f2py.auxfuncs.F2PYError:
  - Exception
  numpy.f2py.auxfuncs.throw_error: []
  numpy.f2py.symbolic.ArithOp:
  - Enum
  numpy.f2py.symbolic.Expr: []
  numpy.f2py.symbolic.ExprWarning:
  - UserWarning
  numpy.f2py.symbolic.Language:
  - Enum
  numpy.f2py.symbolic.Op:
  - Enum
  numpy.f2py.symbolic.OpError:
  - Exception
  numpy.f2py.symbolic.Precedence:
  - Enum
  numpy.f2py.symbolic.RelOp:
  - Enum
  numpy.f2py.symbolic._FromStringWorker: []
  numpy.f2py.symbolic._Pair: []
  numpy.lib._datasource.DataSource: []
  numpy.lib._datasource.Repository:
  - DataSource
  numpy.lib._datasource._FileOpeners: []
  numpy.lib._iotools.ConversionWarning:
  - UserWarning
  numpy.lib._iotools.ConverterError:
  - Exception
  numpy.lib._iotools.ConverterLockError:
  - ConverterError
  numpy.lib._iotools.LineSplitter: []
  numpy.lib._iotools.NameValidator: []
  numpy.lib._iotools.StringConverter: []
  numpy.lib._version.NumpyVersion: []
  numpy.lib.arrayterator.Arrayterator: []
  numpy.lib.function_base.vectorize: []
  numpy.lib.index_tricks.AxisConcatenator: []
  numpy.lib.index_tricks.CClass:
  - AxisConcatenator
  numpy.lib.index_tricks.IndexExpression: []
  numpy.lib.index_tricks.MGridClass:
  - nd_grid
  numpy.lib.index_tricks.OGridClass:
  - nd_grid
  numpy.lib.index_tricks.RClass:
  - AxisConcatenator
  numpy.lib.index_tricks.nd_grid: []
  numpy.lib.index_tricks.ndenumerate: []
  numpy.lib.index_tricks.ndindex: []
  numpy.lib.mixins.NDArrayOperatorsMixin: []
  numpy.lib.npyio.BagObj: []
  numpy.lib.npyio.NpzFile:
  - Mapping
  numpy.lib.npyio.savetxt.WriteWrap: []
  numpy.lib.polynomial.RankWarning:
  - UserWarning
  numpy.lib.polynomial.poly1d: []
  numpy.lib.stride_tricks.DummyArray: []
  numpy.lib.user_array.container: []
  numpy.lib.utils._Deprecate: []
  numpy.linalg.linalg.LinAlgError:
  - Exception
  numpy.linalg.setup.configuration.numpy_linalg_lapack_lite:
  - system_info
  numpy.ma.core.MAError:
  - Exception
  numpy.ma.core.MaskError:
  - MAError
  numpy.ma.core.MaskedArray:
  - ndarray
  numpy.ma.core.MaskedArrayFutureWarning:
  - FutureWarning
  numpy.ma.core.MaskedConstant:
  - MaskedArray
  numpy.ma.core.MaskedIterator: []
  numpy.ma.core._DomainCheckInterval: []
  numpy.ma.core._DomainGreater: []
  numpy.ma.core._DomainGreaterEqual: []
  numpy.ma.core._DomainSafeDivide: []
  numpy.ma.core._DomainTan: []
  numpy.ma.core._DomainedBinaryOperation:
  - _MaskedUFunc
  numpy.ma.core._MaskedBinaryOperation:
  - _MaskedUFunc
  numpy.ma.core._MaskedPrintOption: []
  numpy.ma.core._MaskedUFunc: []
  numpy.ma.core._MaskedUnaryOperation:
  - _MaskedUFunc
  numpy.ma.core._convert2ma: []
  numpy.ma.core._extrema_operation:
  - _MaskedUFunc
  numpy.ma.core._frommethod: []
  numpy.ma.core.mvoid:
  - MaskedArray
  numpy.ma.extras.MAxisConcatenator:
  - AxisConcatenator
  numpy.ma.extras._fromnxfunction: []
  numpy.ma.extras._fromnxfunction_allargs:
  - _fromnxfunction
  numpy.ma.extras._fromnxfunction_args:
  - _fromnxfunction
  numpy.ma.extras._fromnxfunction_seq:
  - _fromnxfunction
  numpy.ma.extras._fromnxfunction_single:
  - _fromnxfunction
  numpy.ma.extras.mr_class:
  - MAxisConcatenator
  numpy.ma.mrecords.MaskedRecords:
  - MaskedArray
  numpy.ma.timer_comparison.ModuleTester: []
  numpy.matrixlib.defmatrix.matrix: []
  numpy.polynomial._polybase.ABCPolyBase: []
  numpy.polynomial.chebyshev.Chebyshev:
  - ABCPolyBase
  numpy.polynomial.hermite.Hermite:
  - ABCPolyBase
  numpy.polynomial.hermite_e.HermiteE:
  - ABCPolyBase
  numpy.polynomial.laguerre.Laguerre:
  - ABCPolyBase
  numpy.polynomial.legendre.Legendre:
  - ABCPolyBase
  numpy.polynomial.polynomial.Polynomial:
  - ABCPolyBase
  numpy.polynomial.polyutils.RankWarning:
  - UserWarning
  numpy.testing._private.noseclasses.FPUModeCheckPlugin:
  - Plugin
  numpy.testing._private.noseclasses.KnownFailurePlugin:
  - ErrorClassPlugin
  numpy.testing._private.noseclasses.NumpyDocTestCase: []
  numpy.testing._private.noseclasses.NumpyDocTestFinder: []
  numpy.testing._private.noseclasses.NumpyDoctest: []
  numpy.testing._private.noseclasses.NumpyOutputChecker: []
  numpy.testing._private.noseclasses.NumpyTestProgram: []
  numpy.testing._private.noseclasses.Unplugger: []
  numpy.testing._private.nosetester.NoseTester: []
  numpy.testing._private.parameterized.param:
  - _param
  numpy.testing._private.parameterized.parameterized: []
  numpy.testing._private.utils.IgnoreException:
  - Exception
  numpy.testing._private.utils.KnownFailureException:
  - Exception
  numpy.testing._private.utils._Dummy: []
  numpy.testing._private.utils.clear_and_catch_warnings: []
  numpy.testing._private.utils.suppress_warnings: []
  numpy.testing.print_coercion_tables.GenericObject: []
  numpy.typing.mypy_plugin._NumpyPlugin:
  - Plugin
  toml.decoder.CommentValue:
  - object
  toml.decoder.InlineTableDict:
  - object
  toml.decoder.TomlDecodeError:
  - ValueError
  toml.decoder.TomlDecoder:
  - object
  toml.decoder.TomlDecoder.get_empty_inline_table.DynamicInlineTableDict:
  - InlineTableDict
  toml.decoder.TomlPreserveCommentDecoder:
  - TomlDecoder
  toml.encoder.TomlArraySeparatorEncoder:
  - TomlEncoder
  toml.encoder.TomlEncoder:
  - object
  toml.encoder.TomlNumpyEncoder:
  - TomlEncoder
  toml.encoder.TomlPathlibEncoder:
  - TomlEncoder
  toml.encoder.TomlPreserveCommentEncoder:
  - TomlEncoder
  toml.encoder.TomlPreserveInlineDictEncoder:
  - TomlEncoder
  toml.ordered.TomlOrderedDecoder:
  - TomlDecoder
  toml.ordered.TomlOrderedEncoder:
  - TomlEncoder
  toml.tz.TomlTz:
  - tzinfo
ep:
  func_name: TestOneInput
  module: '...fuzz_dump'
