6.4. Random Draw¶
6.4.1. SetUp¶
>>> import numpy as np
6.4.2. Random Choice (Draw)¶
>>> np.random.seed(0)
Choice:
>>> np.random.choice([1, 2, 3])
1
>>> np.random.choice([1, 2, 3], size=2)
array([2, 1])
>>> np.random.choice([1, 2, 3], size=2)
array([2, 2])
>>> np.random.choice([1, 2, 3], 2, replace=False)
array([2, 1])
6.4.3. Random Sample¶
Compatible with Python built-in
random.random
>>> np.random.seed(0)
Sample:
>>> np.random.sample(size=5)
array([0.5488135 , 0.71518937, 0.60276338, 0.54488318, 0.4236548 ])
>>> np.random.sample(size=(2,3))
array([[0.64589411, 0.43758721, 0.891773 ],
[0.96366276, 0.38344152, 0.79172504]])
>>> np.random.sample(size=(3,2))
array([[0.52889492, 0.56804456],
[0.92559664, 0.07103606],
[0.0871293 , 0.0202184 ]])
6.4.4. Shuffle¶
Modify sequence in-place (!!)
Multi-dimensional arrays are only shuffled along the first axis
>>> np.random.seed(0)
1-dimensional Array:
>>> a = np.array([1, 2, 3])
>>>
>>> np.random.shuffle(a)
>>> a
array([3, 2, 1])
2-dimensional Array:
>>> a = np.array([[1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]])
>>>
>>> np.random.shuffle(a)
>>> a
array([[7, 8, 9],
[1, 2, 3],
[4, 5, 6]])
6.4.5. Assignments¶
"""
* 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 = ...
"""
* 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 = ...
"""
* 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 = ...