6.1. Random Generator

  • Since numpy v1.17: BitGenerator for the PCG-64 (Parallel Congruent Generator 64 bit) pseudo-random number generator

  • Before numpy v1.17: Mersenne Twister algorithm for pseudorandom number generation

6.1.1. Pseudorandom Generator

>>> from time import time
>>>
>>>
>>> def randint(maximum=10):
...     return int(time()) % maximum
>>>
>>>
>>> randint()  
3
>>> randint()  
4
>>> randint()  
5
>>> randint()  
6
>>> from time import time
>>>
>>>
>>> def randint(maximum=10):
...     cpu_temperature = 52.4123123
...     return int(time() * cpu_temperature) % maximum
>>>
>>>
>>> randint()  
7
>>> randint()  
2
>>> randint()  
5
>>> randint()  
1
>>> from time import time
>>>
>>>
>>> def randint(maximum=10):
...     cpu_temperature = 52.4123123
...     fan_speed = 1200
...     ram_voltage = 1.42321321
...     network_crc = 9876
...     return int(time() * cpu_temperature * fan_speed * ram_voltage * network_crc) % maximum
>>>
>>>
>>> randint()  
3
>>> randint()  
0
>>> randint()  
2
>>> randint()  
8

6.1.2. Seed

  • Seed the generator

  • Using setting seed to the same value will always generate the same pseudorandom values

>>> import numpy as np
>>>
>>>
>>> np.random.seed(0)

6.1.3. Assignments

Code 6.61. Solution
"""
* Assignment: Numpy Random Float
* Complexity: medium
* Lines of code: 1 lines
* Time: 3 min

English:
    1. Set random seed to zero
    2. Define `result: np.ndarray` of 10 random floats
    3. Run doctests - all must succeed

Polish:
    1. Ustaw ziarno losowości na zero
    2. Zdefiniuj `result: np.ndarray` z 10 losowymi liczbami zmiennoprzecinkowymi
    3. Uruchom doctesty - wszystkie muszą się powieść

Tests:
    >>> import sys; sys.tracebacklimit = 0

    >>> assert result is not Ellipsis, \
    'Assign result to variable: `result`'
    >>> assert type(result) is np.ndarray, \
    'Variable `result` has invalid type, expected: np.ndarray'

    >>> result
    array([0.5488135 , 0.71518937, 0.60276338, 0.54488318, 0.4236548 ,
           0.64589411, 0.43758721, 0.891773  , 0.96366276, 0.38344152])
"""

import numpy as np
np.random.seed(0)


result = ...


Code 6.62. Solution
"""
* Assignment: Numpy Random Int
* Complexity: easy
* Lines of code: 1 lines
* Time: 3 min

English:
    1. Set random seed to zero
    2. Define `result: np.ndarray` of size 16x16 with random integers `[0;9]` (inclusive)
    3. Run doctests - all must succeed

Polish:
    1. Ustaw ziarno losowości na zero
    2. Zdefiniuj `result: np.ndarray` o rozmiarze 16x16 z losowymi liczbami całkowitymi `<0,9>` (włącznie)
    3. Uruchom doctesty - wszystkie muszą się powieść

Tests:
    >>> import sys; sys.tracebacklimit = 0

    >>> assert result is not Ellipsis, \
    'Assign result to variable: `result`'
    >>> assert type(result) is np.ndarray, \
    'Variable `result` has invalid type, expected: np.ndarray'

    >>> result
    array([[5, 0, 3, 3, 7, 9, 3, 5, 2, 4, 7, 6, 8, 8, 1, 6],
           [7, 7, 8, 1, 5, 9, 8, 9, 4, 3, 0, 3, 5, 0, 2, 3],
           [8, 1, 3, 3, 3, 7, 0, 1, 9, 9, 0, 4, 7, 3, 2, 7],
           [2, 0, 0, 4, 5, 5, 6, 8, 4, 1, 4, 9, 8, 1, 1, 7],
           [9, 9, 3, 6, 7, 2, 0, 3, 5, 9, 4, 4, 6, 4, 4, 3],
           [4, 4, 8, 4, 3, 7, 5, 5, 0, 1, 5, 9, 3, 0, 5, 0],
           [1, 2, 4, 2, 0, 3, 2, 0, 7, 5, 9, 0, 2, 7, 2, 9],
           [2, 3, 3, 2, 3, 4, 1, 2, 9, 1, 4, 6, 8, 2, 3, 0],
           [0, 6, 0, 6, 3, 3, 8, 8, 8, 2, 3, 2, 0, 8, 8, 3],
           [8, 2, 8, 4, 3, 0, 4, 3, 6, 9, 8, 0, 8, 5, 9, 0],
           [9, 6, 5, 3, 1, 8, 0, 4, 9, 6, 5, 7, 8, 8, 9, 2],
           [8, 6, 6, 9, 1, 6, 8, 8, 3, 2, 3, 6, 3, 6, 5, 7],
           [0, 8, 4, 6, 5, 8, 2, 3, 9, 7, 5, 3, 4, 5, 3, 3],
           [7, 9, 9, 9, 7, 3, 2, 3, 9, 7, 7, 5, 1, 2, 2, 8],
           [1, 5, 8, 4, 0, 2, 5, 5, 0, 8, 1, 1, 0, 3, 8, 8],
           [4, 4, 0, 9, 3, 7, 3, 2, 1, 1, 2, 1, 4, 2, 5, 5]])
"""

import numpy as np
np.random.seed(0)


result = ...


Code 6.63. Solution
"""
* Assignment: Numpy Random Sample
* Complexity: medium
* Lines of code: 1 lines
* Time: 3 min

English:
    1. Set random seed to zero
    2. Print 6 random integers without repetition in range from 1 to 49
    3. Run doctests - all must succeed

Polish:
    1. Ustaw ziarno losowości na zero
    2. Wyświetl 6 losowych i nie powtarzających się liczb całkowitych z zakresu od 1 do 49.
    3. Uruchom doctesty - wszystkie muszą się powieść

Tests:
    >>> import sys; sys.tracebacklimit = 0

    >>> assert result is not Ellipsis, \
    'Assign result to variable: `result`'
    >>> assert type(result) is np.ndarray, \
    'Variable `result` has invalid type, expected: np.ndarray'

    >>> result
    array([30,  5, 27, 31, 33, 38])
"""

import numpy as np
np.random.seed(0)

result = ...