flopscope.

flopscope.numpy.random.RandomState.tomaxint

fnp.random.RandomState.tomaxint(self, size=None)

Return a sample of uniformly distributed random integers in the interval [0, ``flops.iinfo("long").max``].

Adapted from NumPy docs np.random.RandomState.tomaxint

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

Legacy max-int sampler; cost = numel(output).

Return a sample of uniformly distributed random integers in the interval [0, flops.iinfo("long").max].

Warning.

This function uses 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.

Parameters

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.

Returns

out:ndarray

Drawn samples, with shape size.

See also

  • randint Uniform sampling over a given half-open interval of integers.
  • random_integers Uniform sampling over a given closed interval of integers.

Examples

>>> rs = flops.random.RandomState() # need a RandomState object
>>> rs.tomaxint((2,2,2))
array([[[1170048599, 1600360186], # random
        [ 739731006, 1947757578]],
       [[1871712945,  752307660],
        [1601631370, 1479324245]]])
>>> rs.tomaxint((2,2,2)) < flops.iinfo(flops.int_).max
array([[[ True,  True],
        [ True,  True]],
       [[ True,  True],
        [ True,  True]]])