nlcpy.random.RandomState.randint

RandomState.randint(self, low, high=None, size=None, dtype=int)

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

Returns 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).

Parameters

lowint

array_like of ints is not implemented. Lowest (signed) integers to be drawn from the distribution (unless high=None, in which case this parameter is one above the highest such integer).

highint , optional

array_like of ints is not implemented. If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if high=None).

sizeint or 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.

dtypedtype, optional

Desired dtype of the result. All dtypes are determined by their name, i.e., ‘int64’, ‘int’, etc, so byteorder is not available and a specific precision may have different C types depending on the platform.

Returns

outndarray of ints

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

See also

RandomState.random_integers

Random integers of type nlcpy.int64/nlcpy.int32 between low and high, inclusive.

Examples

>>> import nlcpy as vp
>>> vp.random.randint(2, size=10)   
array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0]) # random
>>> vp.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:

>>> vp.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

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