flopscope.

flopscope.numpy.random.RandomState.randint

fnp.random.RandomState.randint(self, low, high=None, size=None, dtype=<class 'int'>)

Return random integers from `low` (inclusive) to `high` (exclusive).

Adapted from NumPy docs np.random.RandomState.randint

Arearandom
Typecounted
NumPy Refnp.random.RandomState.randint
Cost
numel(output)\text{numel}(\text{output})
Flopscope Context

Legacy integer sampler; cost = numel(output).

Return random integers from low (inclusive) to high (exclusive).

Return random integers from the "discrete uniform" distribution of the specified dtype in the "half-open" interval [low, high). If high is None (the default), then results are from [0, low).

Note.

New code should use the integers method of a Generator instance instead; please see the random-quick-start.

Parameters

low:int or array-like of ints

Lowest (signed) integers to be drawn from the distribution (unless high=None, in which case this parameter is one above the highest such integer).

high:int or array-like of ints, optional

If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if high=None). If array-like, must contain integer values

size:int 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.

dtype:dtype, optional

Desired dtype of the result. Byteorder must be native. The default value is long.

Warning.

This function defaults to the C-long dtype, which is 32bit on windows and otherwise 64bit on 64bit platforms (and 32bit on 32bit ones). Since NumPy 2.0, NumPy's default integer is 32bit on 32bit platforms and 64bit on 64bit platforms. Which corresponds to flops.intp. (dtype=int is not the same as in most NumPy functions.)

Returns

out:int or ndarray of ints

size-shaped array of random integers from the appropriate distribution, or a single such random int if size not provided.

See also

Examples

>>> flops.random.randint(2, size=10)
array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0]) # random
>>> flops.random.randint(1, size=10)
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

Generate a 2 x 4 array of ints between 0 and 4, inclusive:

>>> flops.random.randint(5, size=(2, 4))
array([[4, 0, 2, 1], # random
       [3, 2, 2, 0]])

Generate a 1 x 3 array with 3 different upper bounds

>>> flops.random.randint(1, [3, 5, 10])
array([2, 2, 9]) # random

Generate a 1 by 3 array with 3 different lower bounds

>>> flops.random.randint([1, 5, 7], 10)
array([9, 8, 7]) # random

Generate a 2 by 4 array using broadcasting with dtype of uint8

>>> flops.random.randint([1, 3, 5, 7], [[10], [20]], dtype=flops.uint8)
array([[ 8,  6,  9,  7], # random
       [ 1, 16,  9, 12]], dtype=uint8)