Metadata-Version: 2.1
Name: Pyewacket
Version: 0.0.1b3
Summary: Drop-in Replacement for the Python Random Library.
Home-page: https://sharpdesigndigital.com
Author: Broken aka Robert Sharp
Author-email: webmaster@sharpdesigndigital.com
License: Free for non-commercial use
Description: # 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%
        
        
        ```
        
Keywords: Pyewacket
Platform: Darwin
Platform: Linux
Classifier: Development Status :: 1 - Planning
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Cython
Classifier: Programming Language :: C++
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires: Cython
Requires-Python: >=3.7
Description-Content-Type: text/markdown
