Pyewacket 0.0.1b3

Drop-in Replacement for the Python Random Library.

Pyewacket

Pyewacket is a lightweight drop-in replacement for the Python random module. Pyewacket is based on the RNG Storm Engine, configured for speed.

While Storm is a high quality engine, Pyewacket is not appropriate for cryptography of any kind. Pyewacket is meant for games, data science, A.I. and experimental programming, not security.

Recommended Installation: $ pip install Pyewacket

While there are some optimisasions to be made, Pyewacket is functional and passing all tests for everything implemented so far.

ToDo:

• seed()
• getrandbits()

Development Log

Pyewacket v0.0.1b3

• quick_test()
• Extended Functionality
  • sample()
  • expovariate()
  • gammavariate()
  • weibullvariate()
  • betavariate()
  • paretovariate()
  • gauss()
  • normalvariate()
  • lognormvariate()
  • vonmisesvariate()
  • triangular()

Pyewacket v0.0.1b2

• Basic Functionality
  • random()
  • uniform()
  • randbelow()
  • randint()
  • randrange()
  • choice()
  • choices()
  • shuffle()

Pyewacket v0.0.1b1

• Initial Design & Planning

Pywacket Distribution and Performance Test Suite

Output Distribution: Random.random()
Approximate Single Execution Time: Min: 31ns, Mid: 62ns, Max: 156ns
Raw Samples: 0.09583697775679978, 0.7481848462789238, 0.6871638418565119, 0.04862872396959628, 0.9386451928566252
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.00011202652975261795
 Median: (0.5001110713473089, 0.5001642093623144)
 Maximum: 0.9997068844763999
 Mean: 0.49802520478413886
 Std Deviation: 0.2896050587397882
Post-processor Distribution using lambda1 method:
 0: 10.5%
 1: 9.95%
 2: 9.96%
 3: 9.39%
 4: 10.18%
 5: 10.02%
 6: 10.03%
 7: 10.1%
 8: 10.24%
 9: 9.63%

Output Distribution: random()
Approximate Single Execution Time: Min: 31ns, Mid: 62ns, Max: 531ns
Raw Samples: 0.5514715832535501, 0.5482299292615557, 0.05471032790293082, 0.5251638815931967, 0.038520347592466794
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 1.9350539498879987e-05
 Median: (0.4976510948606806, 0.4978419227896529)
 Maximum: 0.9999961233786222
 Mean: 0.4995828967661423
 Std Deviation: 0.29142596740871246
Post-processor Distribution using lambda2 method:
 0: 10.42%
 1: 9.75%
 2: 10.24%
 3: 10.21%
 4: 9.61%
 5: 9.86%
 6: 9.66%
 7: 9.39%
 8: 10.61%
 9: 10.25%

Output Distribution: Random.uniform(0.0, 10.0)
Approximate Single Execution Time: Min: 218ns, Mid: 250ns, Max: 312ns
Raw Samples: 9.72138404861445, 1.539839756791942, 6.6431389560560525, 3.947938769466818, 8.070107038637088
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.00029655047924737055
 Median: (4.999131041294197, 4.999236871838832)
 Maximum: 9.999134476427438
 Mean: 5.003018012069332
 Std Deviation: 2.899660971736388
Post-processor Distribution using floor method:
 0: 10.11%
 1: 9.86%
 2: 10.0%
 3: 10.27%
 4: 9.78%
 5: 10.18%
 6: 9.93%
 7: 9.58%
 8: 9.57%
 9: 10.72%

Output Distribution: uniform(0.0, 10.0)
Approximate Single Execution Time: Min: 31ns, Mid: 62ns, Max: 93ns
Raw Samples: 0.3847631175775124, 4.745952326603827, 5.556725999795969, 6.087928344328328, 6.498634909988075
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.0017558423742254662
 Median: (4.957270936532334, 4.960170524408329)
 Maximum: 9.999471325225604
 Mean: 4.98391286262782
 Std Deviation: 2.9052098983546495
Post-processor Distribution using floor method:
 0: 10.11%
 1: 10.34%
 2: 9.97%
 3: 9.65%
 4: 10.28%
 5: 10.13%
 6: 9.61%
 7: 9.48%
 8: 10.18%
 9: 10.25%

Output Distribution: Random.triangular(0.0, 10.0, 0.0)
Approximate Single Execution Time: Min: 468ns, Mid: 500ns, Max: 1625ns
Raw Samples: 3.0148022873353924, 8.294454754359723, 1.4440898060144853, 2.15004508614141, 5.315968869548841
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.0006017885517870525
 Median: (2.9559874784791207, 2.956327474563853)
 Maximum: 9.879354985461907
 Mean: 3.339759865490947
 Std Deviation: 2.3487776919252146
Post-processor Distribution using floor method:
 0: 18.82%
 1: 16.73%
 2: 15.02%
 3: 13.29%
 4: 11.39%
 5: 9.1%
 6: 6.65%
 7: 4.91%
 8: 3.0%
 9: 1.09%

Output Distribution: triangular(0.0, 10.0, 0.0)
Approximate Single Execution Time: Min: 31ns, Mid: 62ns, Max: 93ns
Raw Samples: 1.5832287605426298, 7.060749903449856, 3.482319374321574, 1.0013297714344327, 5.341493512516113
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.00023267585398389912
 Median: (2.9568876700222435, 2.9582530617690517)
 Maximum: 9.960931721556184
 Mean: 3.3540947993802996
 Std Deviation: 2.352511126156136
Post-processor Distribution using floor method:
 0: 18.54%
 1: 16.89%
 2: 15.05%
 3: 13.51%
 4: 10.71%
 5: 8.98%
 6: 7.15%
 7: 5.29%
 8: 2.78%
 9: 1.1%

Output Distribution: Random.randint(1, 10)
Approximate Single Execution Time: Min: 1250ns, Mid: 1375ns, Max: 1875ns
Raw Samples: 4, 10, 5, 6, 8
Test Samples: 10000
Sample Statistics:
 Minimum: 1
 Median: 5
 Maximum: 10
 Mean: 5.4499
 Std Deviation: 2.8855021404012553
Sample Distribution:
 1: 10.19%
 2: 10.51%
 3: 10.36%
 4: 9.84%
 5: 10.1%
 6: 9.55%
 7: 9.9%
 8: 9.65%
 9: 9.96%
 10: 9.94%

Output Distribution: randint(1, 10)
Approximate Single Execution Time: Min: 62ns, Mid: 93ns, Max: 875ns
Raw Samples: 3, 8, 4, 10, 8
Test Samples: 10000
Sample Statistics:
 Minimum: 1
 Median: 5
 Maximum: 10
 Mean: 5.4943
 Std Deviation: 2.865866156833373
Sample Distribution:
 1: 9.73%
 2: 9.94%
 3: 10.15%
 4: 10.87%
 5: 9.86%
 6: 9.6%
 7: 9.73%
 8: 10.21%
 9: 9.9%
 10: 10.01%

Output Distribution: Random.choice([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
Approximate Single Execution Time: Min: 1125ns, Mid: 1562ns, Max: 2937ns
Raw Samples: 8, 3, 4, 7, 9
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 9
 Mean: 4.4881
 Std Deviation: 2.8884412230942016
Sample Distribution:
 0: 10.1%
 1: 10.09%
 2: 10.4%
 3: 9.68%
 4: 10.32%
 5: 9.56%
 6: 9.84%
 7: 9.58%
 8: 10.17%
 9: 10.26%

Output Distribution: choice([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
Approximate Single Execution Time: Min: 62ns, Mid: 62ns, Max: 375ns
Raw Samples: 9, 0, 4, 3, 1
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 9
 Mean: 4.4647
 Std Deviation: 2.871023891892713
Sample Distribution:
 0: 10.19%
 1: 10.21%
 2: 10.0%
 3: 9.77%
 4: 10.52%
 5: 9.72%
 6: 10.35%
 7: 9.94%
 8: 9.11%
 9: 10.19%

Output Distribution: Random.randrange(10)
Approximate Single Execution Time: Min: 812ns, Mid: 875ns, Max: 1062ns
Raw Samples: 3, 9, 6, 0, 8
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 9
 Mean: 4.4773
 Std Deviation: 2.873797240770146
Sample Distribution:
 0: 10.35%
 1: 9.85%
 2: 10.05%
 3: 10.09%
 4: 9.73%
 5: 10.33%
 6: 9.82%
 7: 9.96%
 8: 10.08%
 9: 9.74%

Output Distribution: randrange(10)
Approximate Single Execution Time: Min: 62ns, Mid: 93ns, Max: 375ns
Raw Samples: 4, 2, 2, 5, 4
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 5
 Maximum: 9
 Mean: 4.4979
 Std Deviation: 2.8800390713504656
Sample Distribution:
 0: 10.13%
 1: 10.04%
 2: 9.9%
 3: 10.26%
 4: 9.65%
 5: 9.89%
 6: 9.73%
 7: 10.4%
 8: 10.06%
 9: 9.94%

Output Distribution: Random.randrange(0, 10)
Approximate Single Execution Time: Min: 1250ns, Mid: 1312ns, Max: 1625ns
Raw Samples: 9, 7, 4, 2, 5
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 9
 Mean: 4.466
 Std Deviation: 2.871736179886427
Sample Distribution:
 0: 9.92%
 1: 10.51%
 2: 10.05%
 3: 10.17%
 4: 9.74%
 5: 10.38%
 6: 9.6%
 7: 9.98%
 8: 9.69%
 9: 9.96%

Output Distribution: randrange(0, 10)
Approximate Single Execution Time: Min: 62ns, Mid: 93ns, Max: 500ns
Raw Samples: 4, 7, 6, 9, 6
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 9
 Mean: 4.4905
 Std Deviation: 2.863132812663481
Sample Distribution:
 0: 10.15%
 1: 9.73%
 2: 9.67%
 3: 10.5%
 4: 10.36%
 5: 10.11%
 6: 9.39%
 7: 10.3%
 8: 10.06%
 9: 9.73%

Output Distribution: Random.randrange(0, 10, 2)
Approximate Single Execution Time: Min: 1406ns, Mid: 1437ns, Max: 1968ns
Raw Samples: 0, 6, 4, 8, 4
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 8
 Mean: 3.9998
 Std Deviation: 2.840494112065728
Sample Distribution:
 0: 20.09%
 2: 20.32%
 4: 19.36%
 6: 19.97%
 8: 20.26%

Output Distribution: randrange(0, 10, 2)
Approximate Single Execution Time: Min: 62ns, Mid: 93ns, Max: 125ns
Raw Samples: 4, 8, 4, 4, 8
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 8
 Mean: 4.036
 Std Deviation: 2.824942836625729
Sample Distribution:
 0: 19.54%
 2: 19.98%
 4: 19.88%
 6: 20.34%
 8: 20.26%

Output Distribution: Random.sample([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], k=10)
Approximate Single Execution Time: Min: 11718ns, Mid: 21156ns, Max: 38281ns
Raw Samples: [8, 1, 2, 5, 9, 6, 0, 3, 7, 4], [9, 4, 3, 7, 1, 6, 5, 0, 8, 2], [2, 0, 5, 6, 9, 1, 3, 7, 8, 4], [4, 2, 0, 8, 7, 3, 1, 5, 9, 6], [5, 9, 0, 8, 3, 7, 4, 1, 2, 6]
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 9
 Mean: 4.4699
 Std Deviation: 2.8788057840490433
Sample Distribution:
 0: 10.26%
 1: 10.23%
 2: 10.17%
 3: 9.58%
 4: 10.23%
 5: 9.52%
 6: 10.56%
 7: 9.75%
 8: 9.75%
 9: 9.95%

Output Distribution: sample([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], k=10)
Approximate Single Execution Time: Min: 468ns, Mid: 500ns, Max: 812ns
Raw Samples: [8, 5, 6, 2, 0, 1, 7, 4, 3, 9], [8, 9, 4, 1, 5, 0, 7, 6, 2, 3], [3, 1, 5, 9, 0, 7, 2, 6, 4, 8], [0, 1, 8, 4, 7, 5, 2, 3, 9, 6], [6, 2, 7, 4, 9, 3, 8, 1, 5, 0]
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 4
 Maximum: 9
 Mean: 4.4779
 Std Deviation: 2.8721658245394477
Sample Distribution:
 0: 10.27%
 1: 9.65%
 2: 10.31%
 3: 10.14%
 4: 10.03%
 5: 9.97%
 6: 10.26%
 7: 9.36%
 8: 10.04%
 9: 9.97%

Timer only: py_random.shuffle(some_list) of size 10:
Approximate Single Execution Time: Min: 8468ns, Mid: 11859ns, Max: 22375ns

Timer only: shuffle(some_list) of size 10:
Approximate Single Execution Time: Min: 468ns, Mid: 625ns, Max: 3750ns

Output Distribution: Random.choices([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [10, 9, 8, 7, 6, 5, 4, 3, 2, 1], k=3)
Approximate Single Execution Time: Min: 3718ns, Mid: 3781ns, Max: 7031ns
Raw Samples: [3, 3, 0], [1, 6, 5], [2, 9, 2], [5, 2, 3], [5, 2, 5]
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 3
 Maximum: 9
 Mean: 3.0032
 Std Deviation: 2.440734618623634
Sample Distribution:
 0: 17.89%
 1: 16.58%
 2: 14.39%
 3: 12.8%
 4: 11.11%
 5: 9.22%
 6: 7.28%
 7: 5.34%
 8: 3.55%
 9: 1.84%

Output Distribution: choices([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [10, 9, 8, 7, 6, 5, 4, 3, 2, 1], k=3)
Approximate Single Execution Time: Min: 1937ns, Mid: 1968ns, Max: 2625ns
Raw Samples: [0, 0, 0], [3, 6, 1], [6, 5, 3], [5, 1, 0], [2, 1, 4]
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 3
 Maximum: 9
 Mean: 3.033
 Std Deviation: 2.4537548963393085
Sample Distribution:
 0: 17.99%
 1: 16.07%
 2: 14.28%
 3: 12.82%
 4: 10.72%
 5: 9.83%
 6: 7.06%
 7: 5.78%
 8: 3.69%
 9: 1.76%

Output Distribution: Random.choices([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], cum_weights=[10, 19, 27, 34, 40, 45, 49, 52, 54, 55], k=3)
Approximate Single Execution Time: Min: 3000ns, Mid: 3968ns, Max: 9875ns
Raw Samples: [0, 5, 3], [5, 7, 5], [6, 7, 8], [0, 0, 1], [2, 4, 3]
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 3
 Maximum: 9
 Mean: 3.005
 Std Deviation: 2.444784795696694
Sample Distribution:
 0: 18.14%
 1: 16.07%
 2: 14.71%
 3: 12.8%
 4: 11.03%
 5: 9.09%
 6: 7.33%
 7: 5.33%
 8: 3.75%
 9: 1.75%

Output Distribution: choices([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], cum_weights=[10, 19, 27, 34, 40, 45, 49, 52, 54, 55], k=3)
Approximate Single Execution Time: Min: 1781ns, Mid: 1906ns, Max: 3281ns
Raw Samples: [5, 3, 0], [2, 5, 1], [1, 2, 0], [2, 1, 6], [2, 1, 9]
Test Samples: 10000
Sample Statistics:
 Minimum: 0
 Median: 3
 Maximum: 9
 Mean: 2.9671
 Std Deviation: 2.434421950078314
Sample Distribution:
 0: 18.4%
 1: 16.19%
 2: 14.96%
 3: 13.15%
 4: 10.86%
 5: 8.67%
 6: 7.23%
 7: 5.0%
 8: 3.88%
 9: 1.66%

Output Distribution: Random.normalvariate(0.0, 2.8)
Approximate Single Execution Time: Min: 656ns, Mid: 750ns, Max: 906ns
Raw Samples: 1.0945889894404213, 1.851126536737369, -2.9618921213612577, -2.937221656311652, -0.16192472793860538
Test Samples: 10000
Pre-processor Statistics:
 Minimum: -11.708225641563802
 Median: (-0.015889527887160065, -0.014926224611675061)
 Maximum: 9.94312914939947
 Mean: -0.018837119177641474
 Std Deviation: 2.7885740523556533
Post-processor Distribution using round method:
 -12: 0.01%
 -10: 0.01%
 -9: 0.1%
 -8: 0.3%
 -7: 0.63%
 -6: 1.44%
 -5: 2.86%
 -4: 5.18%
 -3: 8.04%
 -2: 11.12%
 -1: 13.63%
 0: 14.06%
 1: 13.06%
 2: 11.28%
 3: 7.95%
 4: 4.98%
 5: 2.95%
 6: 1.48%
 7: 0.57%
 8: 0.29%
 9: 0.04%
 10: 0.02%

Output Distribution: normalvariate(0.0, 2.8)
Approximate Single Execution Time: Min: 62ns, Mid: 93ns, Max: 1312ns
Raw Samples: -1.9004926275572116, 3.1818195555886923, -0.63228718194078, 2.3442972091954863, -3.5407806815612317
Test Samples: 10000
Pre-processor Statistics:
 Minimum: -9.557063001320403
 Median: (0.04414526876059948, 0.04495239746866559)
 Maximum: 10.544166423515879
 Mean: 0.060653915630701646
 Std Deviation: 2.8071867564787185
Post-processor Distribution using round method:
 -10: 0.01%
 -9: 0.09%
 -8: 0.23%
 -7: 0.65%
 -6: 1.34%
 -5: 2.48%
 -4: 4.99%
 -3: 8.43%
 -2: 11.36%
 -1: 13.31%
 0: 13.47%
 1: 13.17%
 2: 11.1%
 3: 8.12%
 4: 5.55%
 5: 2.86%
 6: 1.82%
 7: 0.63%
 8: 0.31%
 9: 0.07%
 11: 0.01%

Output Distribution: Random.gauss(1.0, 1.0)
Approximate Single Execution Time: Min: 687ns, Mid: 718ns, Max: 2406ns
Raw Samples: -0.04856580920708087, 1.6611206339937667, 0.39465785891152927, -1.2789484378143747, 0.8425891614414973
Test Samples: 10000
Pre-processor Statistics:
 Minimum: -2.6770864666831686
 Median: (0.9946288295639921, 0.9949593013459612)
 Maximum: 4.816340048962607
 Mean: 1.0083207211114693
 Std Deviation: 1.001970304972284
Post-processor Distribution using round method:
 -3: 0.01%
 -2: 0.56%
 -1: 5.92%
 0: 24.5%
 1: 38.12%
 2: 23.88%
 3: 6.37%
 4: 0.62%
 5: 0.02%

Output Distribution: gauss(1.0, 1.0)
Approximate Single Execution Time: Min: 93ns, Mid: 109ns, Max: 406ns
Raw Samples: 0.8810998602455568, 1.902120592501416, 0.41509387629061834, 2.021688064088669, 1.932948388265123
Test Samples: 10000
Pre-processor Statistics:
 Minimum: -3.2586270844715086
 Median: (0.9958965765397435, 0.9959226467543415)
 Maximum: 4.724616651607568
 Mean: 0.9948751638625993
 Std Deviation: 1.0008566742162837
Post-processor Distribution using round method:
 -3: 0.04%
 -2: 0.58%
 -1: 6.24%
 0: 24.42%
 1: 37.7%
 2: 24.34%
 3: 6.15%
 4: 0.52%
 5: 0.01%

Output Distribution: Random.lognormvariate(0.0, 0.5)
Approximate Single Execution Time: Min: 812ns, Mid: 906ns, Max: 1156ns
Raw Samples: 2.246833572600596, 0.9645111839279291, 0.6636826849378116, 1.3839978131643655, 1.5706954151764843
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.15981420953686484
 Median: (1.0055654114426444, 1.005702998417229)
 Maximum: 5.456017436839273
 Mean: 1.1398101416430748
 Std Deviation: 0.6078083453404712
Post-processor Distribution using round method:
 0: 8.49%
 1: 70.05%
 2: 17.78%
 3: 3.03%
 4: 0.55%
 5: 0.1%

Output Distribution: lognormvariate(0.0, 0.5)
Approximate Single Execution Time: Min: 125ns, Mid: 156ns, Max: 1250ns
Raw Samples: 0.6066965782367475, 1.4271907881912627, 1.1825844581178435, 1.0489078657589839, 1.0910982138156802
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.14300163818926936
 Median: (0.9973151890283786, 0.997319527185987)
 Maximum: 7.567457042916076
 Mean: 1.1332803435012233
 Std Deviation: 0.6066865380411258
Post-processor Distribution using round method:
 0: 8.18%
 1: 71.25%
 2: 17.33%
 3: 2.65%
 4: 0.42%
 5: 0.1%
 6: 0.04%
 7: 0.02%
 8: 0.01%

Output Distribution: Random.expovariate(1.0)
Approximate Single Execution Time: Min: 375ns, Mid: 406ns, Max: 1593ns
Raw Samples: 1.2337990761513633, 1.5656435339285415, 1.770694773297028, 0.28004743268476107, 0.8701519551946996
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 7.712397078721108e-05
 Median: (0.6753464213622776, 0.6753556217178839)
 Maximum: 9.267290446836705
 Mean: 0.9810148662264948
 Std Deviation: 0.9873271774761467
Post-processor Distribution using floor method:
 0: 63.78%
 1: 23.11%
 2: 8.4%
 3: 3.0%
 4: 0.98%
 5: 0.51%
 6: 0.16%
 7: 0.03%
 8: 0.02%
 9: 0.01%

Output Distribution: expovariate(1.0)
Approximate Single Execution Time: Min: 62ns, Mid: 62ns, Max: 218ns
Raw Samples: 0.35004896542529634, 0.7521903548598108, 0.6644403202167085, 1.8911031655814987, 0.558048214159425
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 6.644382015650171e-05
 Median: (0.7169369707905694, 0.7170402221064897)
 Maximum: 9.306503530580908
 Mean: 1.013829457246176
 Std Deviation: 1.004048810663322
Post-processor Distribution using floor method:
 0: 62.12%
 1: 24.18%
 2: 8.53%
 3: 3.31%
 4: 1.11%
 5: 0.49%
 6: 0.2%
 7: 0.04%
 8: 0.01%
 9: 0.01%

Output Distribution: Random.vonmisesvariate(0, 0)
Approximate Single Execution Time: Min: 250ns, Mid: 250ns, Max: 406ns
Raw Samples: 1.711873065039154, 1.8155637533557154, 3.488005794231086, 3.673855226384723, 0.12741299711745097
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.00038293266481131174
 Median: (3.0929184882969425, 3.0929605598731063)
 Maximum: 6.283071361639183
 Mean: 3.129118147133524
 Std Deviation: 1.8148072284571526
Post-processor Distribution using floor method:
 0: 15.87%
 1: 16.3%
 2: 16.36%
 3: 15.81%
 4: 15.26%
 5: 15.82%
 6: 4.58%

Output Distribution: vonmisesvariate(0, 0)
Approximate Single Execution Time: Min: 62ns, Mid: 93ns, Max: 156ns
Raw Samples: 2.347787422324325, 2.6585671498632215, 0.8471642169486492, 3.6901718326782373, 0.08759662936635199
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.00017558418882149027
 Median: (3.1241935094422715, 3.1246352372680475)
 Maximum: 6.282724684514234
 Mean: 3.133330549659671
 Std Deviation: 1.806891610737431
Post-processor Distribution using floor method:
 0: 16.09%
 1: 16.04%
 2: 15.59%
 3: 16.0%
 4: 16.01%
 5: 16.1%
 6: 4.17%

Output Distribution: Random.gammavariate(2.0, 1.0)
Approximate Single Execution Time: Min: 1468ns, Mid: 1656ns, Max: 3500ns
Raw Samples: 3.70818189243767, 0.5942649681647911, 1.217723931010412, 3.7362885153937313, 0.5860116040765794
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.010288248066869777
 Median: (1.663342418919281, 1.6641108355728298)
 Maximum: 11.885151723187366
 Mean: 2.0007216926775726
 Std Deviation: 1.4115535772792656
Post-processor Distribution using round method:
 0: 8.79%
 1: 35.36%
 2: 27.11%
 3: 14.72%
 4: 8.01%
 5: 3.38%
 6: 1.57%
 7: 0.62%
 8: 0.27%
 9: 0.1%
 10: 0.04%
 11: 0.02%
 12: 0.01%

Output Distribution: gammavariate(2.0, 1.0)
Approximate Single Execution Time: Min: 125ns, Mid: 187ns, Max: 1187ns
Raw Samples: 0.9668075190803687, 4.364833765600433, 2.2350993424976027, 3.499852592243818, 0.6492622193040826
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.008494152265271726
 Median: (1.68020041442155, 1.6803557131399585)
 Maximum: 13.883282619182093
 Mean: 1.9971439163233273
 Std Deviation: 1.4086252755537527
Post-processor Distribution using round method:
 0: 9.28%
 1: 34.54%
 2: 27.62%
 3: 14.83%
 4: 7.76%
 5: 3.31%
 6: 1.52%
 7: 0.77%
 8: 0.23%
 9: 0.09%
 10: 0.02%
 11: 0.01%
 12: 0.01%
 14: 0.01%

Output Distribution: Random.betavariate(3.0, 3.0)
Approximate Single Execution Time: Min: 2531ns, Mid: 2687ns, Max: 3000ns
Raw Samples: 0.5809440127629767, 0.3689167280518387, 0.05290086951440652, 0.41590309091802863, 0.7244821099620002
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.0230146293568755
 Median: (0.5027637818756018, 0.5027651391510145)
 Maximum: 0.9590772173935096
 Mean: 0.501293841629715
 Std Deviation: 0.18855333026430554
Post-processor Distribution using round method:
 0: 49.45%
 1: 50.55%

Output Distribution: betavariate(3.0, 3.0)
Approximate Single Execution Time: Min: 156ns, Mid: 187ns, Max: 218ns
Raw Samples: 0.5195148558676725, 0.29901952381642627, 0.9351617473036777, 0.6204740258891677, 0.4103905177545022
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.026027898867851357
 Median: (0.503049870649383, 0.5031300801833846)
 Maximum: 0.976373375329432
 Mean: 0.5035024300342954
 Std Deviation: 0.18848398338837413
Post-processor Distribution using round method:
 0: 49.43%
 1: 50.57%

Output Distribution: Random.paretovariate(4.0)
Approximate Single Execution Time: Min: 343ns, Mid: 468ns, Max: 1187ns
Raw Samples: 1.6548218778756214, 1.0235199111524522, 1.256346134216108, 1.0423385596705579, 2.2672133974436566
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 1.0000134877377684
 Median: (1.1906883033271822, 1.1907007488491919)
 Maximum: 9.219189527235306
 Mean: 1.3336054431486195
 Std Deviation: 0.45780273399460525
Post-processor Distribution using floor method:
 1: 93.75%
 2: 4.97%
 3: 0.85%
 4: 0.28%
 5: 0.09%
 6: 0.03%
 7: 0.02%
 9: 0.01%

Output Distribution: paretovariate(4.0)
Approximate Single Execution Time: Min: 125ns, Mid: 125ns, Max: 906ns
Raw Samples: 1.0550143670856882, 1.0050815871468337, 5.096213485229597, 1.3552499822938424, 1.2181203297870125
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 1.0000524852335335
 Median: (1.190669453818392, 1.1907657256629907)
 Maximum: 10.32025392131445
 Mean: 1.3364535046358461
 Std Deviation: 0.4788482240084414
Post-processor Distribution using floor method:
 1: 93.77%
 2: 4.87%
 3: 0.9%
 4: 0.33%
 5: 0.02%
 6: 0.05%
 7: 0.01%
 8: 0.02%
 9: 0.01%
 10: 0.02%

Output Distribution: Random.weibullvariate(1.0, 1.0)
Approximate Single Execution Time: Min: 468ns, Mid: 500ns, Max: 875ns
Raw Samples: 0.7109199007437706, 0.04102203536063654, 0.4325449725685951, 0.3737481714553773, 3.5602673588552496
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 0.00024085418653614605
 Median: (0.6911545687152738, 0.6911593764707898)
 Maximum: 9.315446615045776
 Mean: 1.0049374144494887
 Std Deviation: 0.9994000170896726
Post-processor Distribution using floor method:
 0: 62.71%
 1: 23.62%
 2: 8.75%
 3: 3.06%
 4: 1.26%
 5: 0.36%
 6: 0.16%
 7: 0.04%
 8: 0.02%
 9: 0.02%

Output Distribution: weibullvariate(1.0, 1.0)
Approximate Single Execution Time: Min: 93ns, Mid: 93ns, Max: 156ns
Raw Samples: 0.4626531359780423, 0.13366462363073986, 0.4173599247687062, 0.548432697308713, 0.6910796015830221
Test Samples: 10000
Pre-processor Statistics:
 Minimum: 3.6780355233384826e-05
 Median: (0.6835891558049825, 0.683910404754705)
 Maximum: 11.105956344388273
 Mean: 0.9955431658581466
 Std Deviation: 0.9943143982554206
Post-processor Distribution using floor method:
 0: 63.66%
 1: 22.88%
 2: 8.69%
 3: 2.96%
 4: 1.12%
 5: 0.45%
 6: 0.19%
 7: 0.03%
 8: 0.01%
 11: 0.01%