CMSIS-DSP: Adedd f16 test patterns for Bayes classifier

Testing/PatternGeneration/Bayes.py

@@ -147,8 +147,10 @@ def generatePatterns():
     PARAMDIR = os.path.join("Parameters","DSP","Bayes","Bayes")
     
     configf32=Tools.Config(PATTERNDIR,PARAMDIR,"f32")
+    configf16=Tools.Config(PATTERNDIR,PARAMDIR,"f16")
     
     writeTests(configf32)
+    writeTests(configf16)
 
 if __name__ == '__main__':
   generatePatterns()

Testing/Patterns/DSP/Bayes/BayesF16/Dims1_s16.txt

@@ -0,0 +1,8 @@
+H
+3
+// 10
+0x000A
+// 5
+0x0005
+// 14
+0x000E

Testing/Patterns/DSP/Bayes/BayesF16/Inputs1_f16.txt

@@ -0,0 +1,282 @@
+H
+140
+// 1.028835
+0x3c1e
+// -0.042027
+0xa961
+// -0.017991
+0xa49b
+// 0.012097
+0x2232
+// -0.016666
+0xa444
+// 0.037305
+0x28c6
+// 0.053519
+0x2ada
+// 0.031651
+0x280d
+// -0.017348
+0xa471
+// 0.025363
+0x267e
+// -0.001110
+0x948c
+// 0.035606
+0x288f
+// 0.084181
+0x2d63
+// 0.001424
+0x15d6
+// 0.987903
+0x3be7
+// -0.006092
+0x9e3d
+// -0.010564
+0xa169
+// 0.119496
+0x2fa6
+// 0.082546
+0x2d48
+// -0.027146
+0xa6f3
+// 0.047280
+0x2a0d
+// -0.034102
+0xa85d
+// 0.033022
+0x283a
+// 0.006842
+0x1f02
+// -0.015701
+0xa405
+// -0.027163
+0xa6f4
+// 0.058441
+0x2b7b
+// 0.004949
+0x1d11
+// 0.033348
+0x2845
+// 0.987079
+0x3be6
+// -0.039755
+0xa917
+// -0.012859
+0xa295
+// 0.006069
+0x1e37
+// 0.026571
+0x26cd
+// -0.018924
+0xa4d8
+// 0.117784
+0x2f8a
+// 0.000870
+0x1320
+// -0.004415
+0x9c85
+// 0.099766
+0x2e63
+// 0.009949
+0x2118
+// -0.042644
+0xa975
+// -0.052297
+0xaab2
+// 1.076490
+0x3c4e
+// -0.030186
+0xa7ba
+// 0.036638
+0x28b1
+// -0.026078
+0xa6ad
+// 0.079691
+0x2d1a
+// -0.028333
+0xa741
+// 0.007583
+0x1fc4
+// 0.006078
+0x1e39
+// 0.036232
+0x28a3
+// 0.090921
+0x2dd2
+// -0.051063
+0xaa89
+// 0.069871
+0x2c79
+// 0.079901
+0x2d1d
+// 0.026329
+0x26bd
+// 0.996467
+0x3bf9
+// -0.038444
+0xa8ec
+// -0.041346
+0xa94b
+// -0.033736
+0xa851
+// 0.017099
+0x2461
+// 0.029067
+0x2771
+// -0.082109
+0xad41
+// -0.043751
+0xa99a
+// -0.006711
+0x9edf
+// 0.066126
+0x2c3b
+// 0.044409
+0x29af
+// 0.084120
+0x2d62
+// 0.079225
+0x2d12
+// -0.012100
+0xa232
+// 1.034189
+0x3c23
+// -0.012637
+0xa278
+// -0.040045
+0xa920
+// 0.041149
+0x2944
+// 0.000403
+0xe9a
+// -0.136979
+0xb062
+// -0.072108
+0xac9d
+// -0.031713
+0xa80f
+// -0.031772
+0xa811
+// 0.027767
+0x271c
+// 0.084030
+0x2d61
+// 0.005517
+0x1da6
+// 0.037478
+0x28cc
+// -0.011741
+0xa203
+// 0.037325
+0x28c7
+// -0.017050
+0xa45d
+// -0.042338
+0xa96b
+// 1.024059
+0x3c19
+// 0.010990
+0x21a0
+// 0.017628
+0x2483
+// -0.048205
+0xaa2c
+// 0.017970
+0x249a
+// -0.001856
+0x979b
+// -0.003545
+0x9b43
+// -0.000281
+0x8c99
+// 0.020429
+0x253b
+// -0.037361
+0xa8c8
+// -0.057079
+0xab4e
+// -0.022293
+0xa5b5
+// 0.043349
+0x298c
+// -0.025649
+0xa691
+// 0.977804
+0x3bd3
+// -0.003158
+0x9a78
+// -0.018731
+0xa4cc
+// -0.026258
+0xa6b9
+// 0.006828
+0x1efe
+// 0.050003
+0x2a66
+// 0.065784
+0x2c36
+// -0.017025
+0xa45c
+// 0.050342
+0x2a72
+// 0.009677
+0x20f4
+// 0.023758
+0x2615
+// 0.012159
+0x223a
+// 0.029271
+0x277e
+// -0.031576
+0xa80b
+// -0.022977
+0xa5e2
+// 1.041686
+0x3c2b
+// -0.004790
+0x9ce8
+// -0.011319
+0xa1cc
+// 0.000580
+0x10c1
+// 0.029053
+0x2770
+// -0.020379
+0xa538
+// -0.071286
+0xac90
+// 0.010488
+0x215f
+// -0.038917
+0xa8fb
+// 0.064071
+0x2c1a
+// 1.012504
+0x3c0d
+// -0.007826
+0xa002
+// 0.022324
+0x25b7
+// -0.021164
+0xa56b
+// -0.039090
+0xa901
+// -0.030557
+0xa7d3
+// 0.016082
+0x241e
+// -0.042785
+0xa97a
+// 0.034331
+0x2865
+// -0.003370
+0x9ae7
+// 0.055286
+0x2b14
+// 0.082477
+0x2d47
+// -0.009091
+0xa0a8
+// -0.015729
+0xa407

Testing/Patterns/DSP/Bayes/BayesF16/Params1_f16.txt

@@ -0,0 +1,294 @@
+H
+146
+// 0.985004
+0x3be1
+// -0.052907
+0xaac6
+// 0.021975
+0x25a0
+// -0.028403
+0xa745
+// 0.026223
+0x26b7
+// -0.009725
+0xa0fb
+// 0.019631
+0x2507
+// -0.090183
+0xadc6
+// -0.017914
+0xa496
+// -0.008963
+0xa097
+// -0.014395
+0xa35f
+// -0.059904
+0xabab
+// -0.033813
+0xa854
+// -0.033741
+0xa852
+// 0.016201
+0x2426
+// 0.935671
+0x3b7c
+// 0.003785
+0x1bc0
+// 0.056037
+0x2b2c
+// 0.006074
+0x1e38
+// -0.019560
+0xa502
+// -0.063085
+0xac0a
+// 0.019081
+0x24e3
+// -0.020623
+0xa548
+// -0.003726
+0x9ba1
+// 0.018599
+0x24c3
+// -0.014125
+0xa33b
+// 0.011388
+0x21d5
+// 0.024971
+0x2665
+// -0.008454
+0xa054
+// 0.015232
+0x23cd
+// 1.015898
+0x3c10
+// -0.104879
+0xaeb6
+// -0.038666
+0xa8f3
+// -0.023323
+0xa5f8
+// -0.017601
+0xa482
+// 0.001072
+0x1464
+// -0.034200
+0xa861
+// 0.081688
+0x2d3a
+// -0.020961
+0xa55e
+// -0.005916
+0x9e0f
+// 0.013055
+0x22af
+// -0.015015
+0xa3b0
+// 0.052016
+0x2aa8
+// 0.026128
+0x26b0
+// 0.071894
+0x2c9a
+// 0.966634
+0x3bbc
+// -0.025381
+0xa67f
+// -0.010172
+0xa135
+// -0.082984
+0xad50
+// 0.049836
+0x2a61
+// -0.043709
+0xa998
+// 0.017144
+0x2464
+// -0.019426
+0xa4f9
+// -0.043475
+0xa991
+// 0.009035
+0x20a0
+// -0.007580
+0x9fc3
+// -0.011892
+0xa217
+// -0.041841
+0xa95b
+// -0.029643
+0xa797
+// -0.006494
+0x9ea6
+// 0.990770
+0x3bed
+// -0.035150
+0xa880
+// 0.002528
+0x192e
+// -0.013445
+0xa2e2
+// -0.036651
+0xa8b1
+// 0.035736
+0x2893
+// 0.017172
+0x2465
+// 0.004941
+0x1d0f
+// -0.071531
+0xac94
+// -0.002282
+0x98ac
+// 0.010836
+0x218c
+// 0.003472
+0x1b1c
+// 0.008943
+0x2094
+// 0.008475
+0x2057
+// 0.007423
+0x1f9a
+// 0.006206
+0x1e5b
+// 0.002284
+0x18ae
+// 0.006758
+0x1eec
+// 0.001684
+0x16e6
+// 0.004819
+0x1cef
+// 0.002814
+0x19c4
+// 0.006132
+0x1e47
+// 0.017119
+0x2462
+// 0.001992
+0x1814
+// 0.004512
+0x1c9f
+// 0.007858
+0x2006
+// 0.007998
+0x2018
+// 0.005287
+0x1d6a
+// 0.003773
+0x1bba
+// 0.004738
+0x1cda
+// 0.004638
+0x1cc0
+// 0.009202
+0x20b6
+// 0.004985
+0x1d1b
+// 0.007869
+0x2007
+// 0.009183
+0x20b4
+// 0.006448
+0x1e9a
+// 0.005037
+0x1d28
+// 0.009728
+0x20fb
+// 0.002407
+0x18ee
+// 0.005078
+0x1d33
+// 0.003920
+0x1c04
+// 0.005693
+0x1dd4
+// 0.018680
+0x24c8
+// 0.009490
+0x20dc
+// 0.002011
+0x181e
+// 0.006577
+0x1ebc
+// 0.013889
+0x231c
+// 0.005805
+0x1df2
+// 0.008577
+0x2064
+// 0.005699
+0x1dd6
+// 0.000617
+0x110d
+// 0.004139
+0x1c3d
+// 0.020146
+0x2528
+// 0.003045
+0x1a3c
+// 0.010782
+0x2185
+// 0.005398
+0x1d87
+// 0.005078
+0x1d33
+// 0.005103
+0x1d3a
+// 0.007296
+0x1f79
+// 0.014107
+0x2339
+// 0.001909
+0x17d2
+// 0.004052
+0x1c26
+// 0.012092
+0x2231
+// 0.003773
+0x1bba
+// 0.003972
+0x1c11
+// 0.005734
+0x1ddf
+// 0.002210
+0x1886
+// 0.004318
+0x1c6c
+// 0.003743
+0x1bab
+// 0.000974
+0x13fa
+// 0.005820
+0x1df6
+// 0.004014
+0x1c1c
+// 0.003926
+0x1c05
+// 0.004715
+0x1cd4
+// 0.003413
+0x1afe
+// 0.008347
+0x2046
+// 0.005377
+0x1d82
+// 0.001483
+0x1613
+// 0.008437
+0x2052
+// 0.005223
+0x1d59
+// 0.166667
+0x3155
+// 0.300000
+0x34cd
+// 0.166667
+0x3155
+// 0.166667
+0x3155
+// 0.200000
+0x3266
+// 0.000000
+0x0

Testing/Patterns/DSP/Bayes/BayesF16/Predicts1_s16.txt

@@ -0,0 +1,22 @@
+H
+10
+// 0
+0x0000
+// 0
+0x0000
+// 1
+0x0001
+// 0
+0x0000
+// 0
+0x0000
+// 0
+0x0000
+// 3
+0x0003
+// 3
+0x0003
+// 4
+0x0004
+// 0
+0x0000

Testing/Patterns/DSP/Bayes/BayesF16/Probas1_f16.txt

@@ -0,0 +1,102 @@
+H
+50
+// 18.642480
+0x4ca9
+// -155.894587
+0xd8df
+// -345.138640
+0xdd65
+// -91.319113
+0xd5b5
+// -311.060822
+0xdcdc
+// 18.388500
+0x4c99
+// -142.840672
+0xd877
+// -326.646008
+0xdd1b
+// -72.032285
+0xd481
+// -283.462321
+0xdc6e
+// -182.139885
+0xd9b1
+// 18.710160
+0x4cad
+// -219.302485
+0xdada
+// -222.657746
+0xdaf5
+// -185.529311
+0xd9cc
+// 15.988660
+0x4bff
+// -166.609104
+0xd935
+// -350.326487
+0xdd79
+// -103.315845
+0xd675
+// -319.995884
+0xdd00
+// 15.967577
+0x4bfc
+// -148.432571
+0xd8a3
+// -336.685663
+0xdd43
+// -99.190971
+0xd633
+// -292.712176
+0xdc93
+// 15.373112
+0x4bb0
+// -152.803638
+0xd8c6
+// -350.559539
+0xdd7a
+// -85.742894
+0xd55c
+// -311.867172
+0xdcdf
+// -87.730568
+0xd57c
+// -125.977689
+0xd7e0
+// -236.344119
+0xdb63
+// 18.067427
+0x4c84
+// -605.617259
+0xe0bb
+// -90.857202
+0xd5ae
+// -111.117756
+0xd6f2
+// -219.838765
+0xdadf
+// 16.342459
+0x4c16
+// -561.457687
+0xe063
+// -96.933962
+0xd60f
+// -174.997703
+0xd978
+// -153.672586
+0xd8cd
+// -185.436485
+0xd9cb
+// 21.182070
+0x4d4c
+// 17.950097
+0x4c7d
+// -148.137651
+0xd8a1
+// -323.389710
+0xdd0e
+// -97.479086
+0xd618
+// -308.072909
+0xdcd0