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numpy.random.randint(low, high=None, size=None, dtype='l') -
Return random integers from
low(inclusive) tohigh(exclusive).Return random integers from the ?discrete uniform? distribution of the specified dtype in the ?half-open? interval [
low,high). Ifhighis None (the default), then results are from [0,low).Parameters: low : int
Lowest (signed) integer to be drawn from the distribution (unless
high=None, in which case this parameter is the highest such integer).high : int, optional
If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if
high=None).size : int or tuple of ints, optional
Output shape. If the given shape is, e.g.,
(m, n, k), thenm * n * ksamples are drawn. Default is None, in which case a single value is returned.dtype : dtype, 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. The default value is ?np.int?.
New in version 1.11.0.
Returns: out : int or ndarray of ints
size-shaped array of random integers from the appropriate distribution, or a single such random int ifsizenot provided.See also
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random.random_integers - similar to
randint, only for the closed interval [low,high], and 1 is the lowest value ifhighis omitted. In particular, this other one is the one to use to generate uniformly distributed discrete non-integers.
Examples
1234>>> np.random.randint(2, size=10)array([1,0,0,0,1,1,0,0,1,0])>>> np.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:
123>>> np.random.randint(5, size=(2,4))array([[4,0,2,1],[3,2,2,0]]) -
numpy.random.randint()
2025-01-10 15:47:30
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