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# numpy.random.RandomState.choice¶

method

`RandomState.``choice`(a, size=None, replace=True, p=None)

Generates a random sample from a given 1-D array

New in version 1.7.0.

Note

New code should use the `choice` method of a `default_rng()` instance instead; see random-quick-start.

Parameters
a1-D array-like or int

If an ndarray, a random sample is generated from its elements. If an int, the random sample is generated as if a were np.arange(a)

sizeint or tuple of ints, optional

Output shape. If the given shape is, e.g., `(m, n, k)`, then `m * n * k` samples are drawn. Default is None, in which case a single value is returned.

replaceboolean, optional

Whether the sample is with or without replacement

p1-D array-like, optional

The probabilities associated with each entry in a. If not given the sample assumes a uniform distribution over all entries in a.

Returns
samplessingle item or ndarray

The generated random samples

Raises
ValueError

If a is an int and less than zero, if a or p are not 1-dimensional, if a is an array-like of size 0, if p is not a vector of probabilities, if a and p have different lengths, or if replace=False and the sample size is greater than the population size

`Generator.choice`

which should be used in new code

Notes

Sampling random rows from a 2-D array is not possible with this function, but is possible with `Generator.choice` through its `axis` keyword.

Examples

Generate a uniform random sample from np.arange(5) of size 3:

```>>> np.random.choice(5, 3)
array([0, 3, 4]) # random
>>> #This is equivalent to np.random.randint(0,5,3)
```

Generate a non-uniform random sample from np.arange(5) of size 3:

```>>> np.random.choice(5, 3, p=[0.1, 0, 0.3, 0.6, 0])
array([3, 3, 0]) # random
```

Generate a uniform random sample from np.arange(5) of size 3 without replacement:

```>>> np.random.choice(5, 3, replace=False)
array([3,1,0]) # random
>>> #This is equivalent to np.random.permutation(np.arange(5))[:3]
```

Generate a non-uniform random sample from np.arange(5) of size 3 without replacement:

```>>> np.random.choice(5, 3, replace=False, p=[0.1, 0, 0.3, 0.6, 0])
array([2, 3, 0]) # random
```

Any of the above can be repeated with an arbitrary array-like instead of just integers. For instance:

```>>> aa_milne_arr = ['pooh', 'rabbit', 'piglet', 'Christopher']
>>> np.random.choice(aa_milne_arr, 5, p=[0.5, 0.1, 0.1, 0.3])
array(['pooh', 'pooh', 'pooh', 'Christopher', 'piglet'], # random
dtype='<U11')
```