Fixed bugs in geometric and harmonic means, added some tests.

[cipher-tools.git] / caesar_break_parameter_trials.csv

diff --git a/caesar_break_parameter_trials.csv b/caesar_break_parameter_trials.csv
index df9b836ebdfec843d0f42cb319729dfd1a45836c..ba7ee273a0682301beab9d4da6d0db1cba45f0ec 100644 (file)
--- a/caesar_break_parameter_trials.csv
+++ b/caesar_break_parameter_trials.csv
@@ -1,144 +1,168 @@
-l1, normalised_english_counts, normalise, 3000, 0.9616
-l1, normalised_english_counts, normalise, 1000, 0.9562
-l1, normalised_english_counts, normalise, 300, 0.9598
-l1, normalised_english_counts, normalise, 100, 0.9622
-l1, normalised_english_counts, normalise, 50, 0.9584
-l1, normalised_english_counts, normalise, 30, 0.953
-l1, normalised_english_counts, normalise, 20, 0.917
-l1, normalised_english_counts, normalise, 10, 0.7328
-l1, normalised_english_counts, normalise, 5, 0.4394
-l1, normalised_english_counts, scale, 3000, 0.9618
-l1, normalised_english_counts, scale, 1000, 0.9574
-l1, normalised_english_counts, scale, 300, 0.9624
-l1, normalised_english_counts, scale, 100, 0.9566
-l1, normalised_english_counts, scale, 50, 0.959
-l1, normalised_english_counts, scale, 30, 0.9476
-l1, normalised_english_counts, scale, 20, 0.8968
-l1, normalised_english_counts, scale, 10, 0.6844
-l1, normalised_english_counts, scale, 5, 0.4298
-l1, scaled_english_counts, normalise, 3000, 0.957
-l1, scaled_english_counts, normalise, 1000, 0.9662
-l1, scaled_english_counts, normalise, 300, 0.9604
-l1, scaled_english_counts, normalise, 100, 0.9602
-l1, scaled_english_counts, normalise, 50, 0.9578
-l1, scaled_english_counts, normalise, 30, 0.9504
-l1, scaled_english_counts, normalise, 20, 0.9174
-l1, scaled_english_counts, normalise, 10, 0.7204
-l1, scaled_english_counts, normalise, 5, 0.4506
-l1, scaled_english_counts, scale, 3000, 0.9584
-l1, scaled_english_counts, scale, 1000, 0.9586
-l1, scaled_english_counts, scale, 300, 0.964
-l1, scaled_english_counts, scale, 100, 0.9582
-l1, scaled_english_counts, scale, 50, 0.9606
-l1, scaled_english_counts, scale, 30, 0.944
-l1, scaled_english_counts, scale, 20, 0.915
-l1, scaled_english_counts, scale, 10, 0.7324
-l1, scaled_english_counts, scale, 5, 0.4446
-l2, normalised_english_counts, normalise, 3000, 0.953
-l2, normalised_english_counts, normalise, 1000, 0.962
-l2, normalised_english_counts, normalise, 300, 0.9638
-l2, normalised_english_counts, normalise, 100, 0.9632
-l2, normalised_english_counts, normalise, 50, 0.9604
-l2, normalised_english_counts, normalise, 30, 0.95
-l2, normalised_english_counts, normalise, 20, 0.892
-l2, normalised_english_counts, normalise, 10, 0.7124
-l2, normalised_english_counts, normalise, 5, 0.4406
-l2, normalised_english_counts, scale, 3000, 0.9626
-l2, normalised_english_counts, scale, 1000, 0.956
-l2, normalised_english_counts, scale, 300, 0.962
-l2, normalised_english_counts, scale, 100, 0.9572
-l2, normalised_english_counts, scale, 50, 0.9526
-l2, normalised_english_counts, scale, 30, 0.9478
-l2, normalised_english_counts, scale, 20, 0.9046
-l2, normalised_english_counts, scale, 10, 0.6896
-l2, normalised_english_counts, scale, 5, 0.4308
-l2, scaled_english_counts, normalise, 3000, 0.9574
-l2, scaled_english_counts, normalise, 1000, 0.9568
-l2, scaled_english_counts, normalise, 300, 0.9536
-l2, scaled_english_counts, normalise, 100, 0.9624
-l2, scaled_english_counts, normalise, 50, 0.9606
-l2, scaled_english_counts, normalise, 30, 0.9384
-l2, scaled_english_counts, normalise, 20, 0.8914
-l2, scaled_english_counts, normalise, 10, 0.6892
-l2, scaled_english_counts, normalise, 5, 0.4196
-l2, scaled_english_counts, scale, 3000, 0.9532
-l2, scaled_english_counts, scale, 1000, 0.9588
-l2, scaled_english_counts, scale, 300, 0.9644
-l2, scaled_english_counts, scale, 100, 0.9572
-l2, scaled_english_counts, scale, 50, 0.9586
-l2, scaled_english_counts, scale, 30, 0.9436
-l2, scaled_english_counts, scale, 20, 0.9036
-l2, scaled_english_counts, scale, 10, 0.693
-l2, scaled_english_counts, scale, 5, 0.4376
-l3, normalised_english_counts, normalise, 3000, 0.9626
-l3, normalised_english_counts, normalise, 1000, 0.9582
-l3, normalised_english_counts, normalise, 300, 0.9542
-l3, normalised_english_counts, normalise, 100, 0.9606
-l3, normalised_english_counts, normalise, 50, 0.953
-l3, normalised_english_counts, normalise, 30, 0.9248
-l3, normalised_english_counts, normalise, 20, 0.8684
-l3, normalised_english_counts, normalise, 10, 0.6106
-l3, normalised_english_counts, normalise, 5, 0.4064
-l3, normalised_english_counts, scale, 3000, 0.961
-l3, normalised_english_counts, scale, 1000, 0.9568
-l3, normalised_english_counts, scale, 300, 0.9566
-l3, normalised_english_counts, scale, 100, 0.9554
-l3, normalised_english_counts, scale, 50, 0.9436
-l3, normalised_english_counts, scale, 30, 0.8936
-l3, normalised_english_counts, scale, 20, 0.8016
-l3, normalised_english_counts, scale, 10, 0.579
+l1, normalised_english_counts, normalise, 300, 0.9992
+l1, normalised_english_counts, normalise, 100, 0.9996
+l1, normalised_english_counts, normalise, 50, 0.9992
+l1, normalised_english_counts, normalise, 30, 0.9914
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+l1, normalised_english_counts, normalise, 10, 0.7442
+l1, normalised_english_counts, normalise, 5, 0.4358
+l1, normalised_english_counts, scale, 300, 1.0
+l1, normalised_english_counts, scale, 100, 0.999
+l1, normalised_english_counts, scale, 50, 0.9988
+l1, normalised_english_counts, scale, 30, 0.9848
+l1, normalised_english_counts, scale, 20, 0.9316
+l1, normalised_english_counts, scale, 10, 0.715
+l1, normalised_english_counts, scale, 5, 0.436
+l1, scaled_english_counts, normalise, 300, 0.9994
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+l1, scaled_english_counts, normalise, 50, 0.999
+l1, scaled_english_counts, normalise, 30, 0.9868
+l1, scaled_english_counts, normalise, 20, 0.9482
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+l1, scaled_english_counts, scale, 300, 0.9996
+l1, scaled_english_counts, scale, 100, 1.0
+l1, scaled_english_counts, scale, 50, 0.9988
+l1, scaled_english_counts, scale, 30, 0.9874
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+l1, scaled_english_counts, scale, 10, 0.745
+l1, scaled_english_counts, scale, 5, 0.4548
+l2, normalised_english_counts, normalise, 300, 0.9994
+l2, normalised_english_counts, normalise, 100, 0.9992
+l2, normalised_english_counts, normalise, 50, 0.9978
+l2, normalised_english_counts, normalise, 30, 0.9836
+l2, normalised_english_counts, normalise, 20, 0.9318
+l2, normalised_english_counts, normalise, 10, 0.7072
+l2, normalised_english_counts, normalise, 5, 0.4294
+l2, normalised_english_counts, scale, 300, 0.9988
+l2, normalised_english_counts, scale, 100, 0.9998
+l2, normalised_english_counts, scale, 50, 0.9978
+l2, normalised_english_counts, scale, 30, 0.9868
+l2, normalised_english_counts, scale, 20, 0.9364
+l2, normalised_english_counts, scale, 10, 0.7136
+l2, normalised_english_counts, scale, 5, 0.446
+l2, scaled_english_counts, normalise, 300, 0.9992
+l2, scaled_english_counts, normalise, 100, 0.9996
+l2, scaled_english_counts, normalise, 50, 0.9984
+l2, scaled_english_counts, normalise, 30, 0.9854
+l2, scaled_english_counts, normalise, 20, 0.9328
+l2, scaled_english_counts, normalise, 10, 0.7122
+l2, scaled_english_counts, normalise, 5, 0.4328
+l2, scaled_english_counts, scale, 300, 1.0
+l2, scaled_english_counts, scale, 100, 0.9998
+l2, scaled_english_counts, scale, 50, 0.9972
+l2, scaled_english_counts, scale, 30, 0.9842
+l2, scaled_english_counts, scale, 20, 0.9356
+l2, scaled_english_counts, scale, 10, 0.7126
+l2, scaled_english_counts, scale, 5, 0.4318
+l3, normalised_english_counts, normalise, 300, 0.9996
+l3, normalised_english_counts, normalise, 100, 0.999
+l3, normalised_english_counts, normalise, 50, 0.994
+l3, normalised_english_counts, normalise, 30, 0.9658
+l3, normalised_english_counts, normalise, 20, 0.8926
+l3, normalised_english_counts, normalise, 10, 0.6252
+l3, normalised_english_counts, normalise, 5, 0.3974
+l3, normalised_english_counts, scale, 300, 0.9996
+l3, normalised_english_counts, scale, 100, 0.998
+l3, normalised_english_counts, scale, 50, 0.9828
+l3, normalised_english_counts, scale, 30, 0.9334
+l3, normalised_english_counts, scale, 20, 0.8304
+l3, normalised_english_counts, scale, 10, 0.5968
 l3, normalised_english_counts, scale, 5, 0.4114
-l3, scaled_english_counts, normalise, 3000, 0.9616
-l3, scaled_english_counts, normalise, 1000, 0.9612
-l3, scaled_english_counts, normalise, 300, 0.9624
-l3, scaled_english_counts, normalise, 100, 0.9524
-l3, scaled_english_counts, normalise, 50, 0.9474
-l3, scaled_english_counts, normalise, 30, 0.9066
-l3, scaled_english_counts, normalise, 20, 0.8004
-l3, scaled_english_counts, normalise, 10, 0.5686
-l3, scaled_english_counts, normalise, 5, 0.3404
-l3, scaled_english_counts, scale, 3000, 0.96
-l3, scaled_english_counts, scale, 1000, 0.96
-l3, scaled_english_counts, scale, 300, 0.9596
-l3, scaled_english_counts, scale, 100, 0.96
-l3, scaled_english_counts, scale, 50, 0.954
-l3, scaled_english_counts, scale, 30, 0.9374
-l3, scaled_english_counts, scale, 20, 0.862
-l3, scaled_english_counts, scale, 10, 0.6276
-l3, scaled_english_counts, scale, 5, 0.399
-cosine_distance, normalised_english_counts, normalise, 3000, 0.9618
-cosine_distance, normalised_english_counts, normalise, 1000, 0.96
-cosine_distance, normalised_english_counts, normalise, 300, 0.9604
-cosine_distance, normalised_english_counts, normalise, 100, 0.9538
-cosine_distance, normalised_english_counts, normalise, 50, 0.9608
-cosine_distance, normalised_english_counts, normalise, 30, 0.9426
-cosine_distance, normalised_english_counts, normalise, 20, 0.9012
-cosine_distance, normalised_english_counts, normalise, 10, 0.6916
-cosine_distance, normalised_english_counts, normalise, 5, 0.4286
-cosine_distance, normalised_english_counts, scale, 3000, 0.9606
-cosine_distance, normalised_english_counts, scale, 1000, 0.9572
-cosine_distance, normalised_english_counts, scale, 300, 0.9628
-cosine_distance, normalised_english_counts, scale, 100, 0.959
-cosine_distance, normalised_english_counts, scale, 50, 0.9542
-cosine_distance, normalised_english_counts, scale, 30, 0.951
-cosine_distance, normalised_english_counts, scale, 20, 0.9028
-cosine_distance, normalised_english_counts, scale, 10, 0.7028
-cosine_distance, normalised_english_counts, scale, 5, 0.44
-cosine_distance, scaled_english_counts, normalise, 3000, 0.9582
-cosine_distance, scaled_english_counts, normalise, 1000, 0.9614
-cosine_distance, scaled_english_counts, normalise, 300, 0.9632
-cosine_distance, scaled_english_counts, normalise, 100, 0.9584
-cosine_distance, scaled_english_counts, normalise, 50, 0.9574
-cosine_distance, scaled_english_counts, normalise, 30, 0.9506
-cosine_distance, scaled_english_counts, normalise, 20, 0.8956
-cosine_distance, scaled_english_counts, normalise, 10, 0.6916
-cosine_distance, scaled_english_counts, normalise, 5, 0.4356
-cosine_distance, scaled_english_counts, scale, 3000, 0.9572
-cosine_distance, scaled_english_counts, scale, 1000, 0.961
-cosine_distance, scaled_english_counts, scale, 300, 0.9596
-cosine_distance, scaled_english_counts, scale, 100, 0.9544
-cosine_distance, scaled_english_counts, scale, 50, 0.9598
-cosine_distance, scaled_english_counts, scale, 30, 0.9414
-cosine_distance, scaled_english_counts, scale, 20, 0.9036
-cosine_distance, scaled_english_counts, scale, 10, 0.6928
-cosine_distance, scaled_english_counts, scale, 5, 0.4178
+l3, scaled_english_counts, normalise, 300, 0.9994
+l3, scaled_english_counts, normalise, 100, 0.9984
+l3, scaled_english_counts, normalise, 50, 0.9876
+l3, scaled_english_counts, normalise, 30, 0.9284
+l3, scaled_english_counts, normalise, 20, 0.8322
+l3, scaled_english_counts, normalise, 10, 0.579
+l3, scaled_english_counts, normalise, 5, 0.3466
+l3, scaled_english_counts, scale, 300, 1.0
+l3, scaled_english_counts, scale, 100, 0.999
+l3, scaled_english_counts, scale, 50, 0.994
+l3, scaled_english_counts, scale, 30, 0.9688
+l3, scaled_english_counts, scale, 20, 0.8952
+l3, scaled_english_counts, scale, 10, 0.6416
+l3, scaled_english_counts, scale, 5, 0.4042
+cosine_distance, normalised_english_counts, normalise, 300, 0.9994
+cosine_distance, normalised_english_counts, normalise, 100, 1.0
+cosine_distance, normalised_english_counts, normalise, 50, 0.9978
+cosine_distance, normalised_english_counts, normalise, 30, 0.9856
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+cosine_distance, normalised_english_counts, normalise, 10, 0.7212
+cosine_distance, normalised_english_counts, normalise, 5, 0.4282
+cosine_distance, normalised_english_counts, scale, 300, 0.9998
+cosine_distance, normalised_english_counts, scale, 100, 0.9994
+cosine_distance, normalised_english_counts, scale, 50, 0.9972
+cosine_distance, normalised_english_counts, scale, 30, 0.9846
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+cosine_distance, normalised_english_counts, scale, 10, 0.7144
+cosine_distance, normalised_english_counts, scale, 5, 0.4284
+cosine_distance, scaled_english_counts, normalise, 300, 0.9994
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+cosine_distance, scaled_english_counts, scale, 100, 0.9988
+cosine_distance, scaled_english_counts, scale, 50, 0.9976
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+harmonic_mean, normalised_english_counts, normalise, 300, 0.4684
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+harmonic_mean, normalised_english_counts, normalise, 30, 0.593
+harmonic_mean, normalised_english_counts, normalise, 20, 0.536
+harmonic_mean, normalised_english_counts, normalise, 10, 0.4284
+harmonic_mean, normalised_english_counts, normalise, 5, 0.3542
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+harmonic_mean, normalised_english_counts, scale, 30, 0.7694
+harmonic_mean, normalised_english_counts, scale, 20, 0.6924
+harmonic_mean, normalised_english_counts, scale, 10, 0.559
+harmonic_mean, normalised_english_counts, scale, 5, 0.39
+harmonic_mean, scaled_english_counts, normalise, 300, 0.1214
+harmonic_mean, scaled_english_counts, normalise, 100, 0.132
+harmonic_mean, scaled_english_counts, normalise, 50, 0.1956
+harmonic_mean, scaled_english_counts, normalise, 30, 0.2686
+harmonic_mean, scaled_english_counts, normalise, 20, 0.258
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+harmonic_mean, scaled_english_counts, scale, 300, 0.7956
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+harmonic_mean, scaled_english_counts, scale, 20, 0.3012
+harmonic_mean, scaled_english_counts, scale, 10, 0.2136
+harmonic_mean, scaled_english_counts, scale, 5, 0.1426
+geometric_mean, normalised_english_counts, normalise, 300, 0.9996
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+geometric_mean, normalised_english_counts, scale, 50, 0.9724
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+geometric_mean, scaled_english_counts, normalise, 300, 0.9556
+geometric_mean, scaled_english_counts, normalise, 100, 0.8724
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+geometric_mean, scaled_english_counts, normalise, 10, 0.3926
+geometric_mean, scaled_english_counts, normalise, 5, 0.319
+geometric_mean, scaled_english_counts, scale, 300, 0.7822
+geometric_mean, scaled_english_counts, scale, 100, 0.5784
+geometric_mean, scaled_english_counts, scale, 50, 0.4318
+geometric_mean, scaled_english_counts, scale, 30, 0.349
+geometric_mean, scaled_english_counts, scale, 20, 0.2932
+geometric_mean, scaled_english_counts, scale, 10, 0.2098
+geometric_mean, scaled_english_counts, scale, 5, 0.1406