dpnp.random.RandomState.uniform
method
- RandomState.uniform(low=0.0, high=1.0, size=None, dtype=None, usm_type='device')[source]
Draw samples from a uniform distribution.
Samples are uniformly distributed over the half-open interval [low, high) (includes low, but excludes high). In other words, any value within the given interval is equally likely to be drawn by uniform.
For full documentation refer to
numpy.random.RandomState.uniform.- Parameters:
usm_type ({"device", "shared", "host"}, optional) -- The type of SYCL USM allocation for the output array.
- Returns:
out -- Drawn samples from the parameterized uniform distribution. Output array data type is the same as input dtype. If dtype is
None(the default),dpnp.float64type will be used if device supports it, ordpnp.float32otherwise.- Return type:
dpnp.ndarray
Limitations
Parameters low and high are supported as a scalar. Otherwise,
numpy.random.RandomState.uniform(low, high, size)samples are drawn. Parameter dtype is supported only asdpnp.int32,dpnp.float32,dpnp.float64orNone.Examples
>>> low, high = 1.23, 10.54 # low and high >>> s = dpnp.random.RandomState().uniform(low, high, 5) >>> print(s) [2.48093112 6.52928804 9.1196081 8.6990877 8.34074171]
See also
dpnp.random.RandomState.randintDiscrete uniform distribution, yielding integers.
dpnp.random.RandomState.random_integersDiscrete uniform distribution over the closed interval
[low, high].dpnp.random.RandomState.random_sampleFloats uniformly distributed over
[0, 1).dpnp.random.RandomState.randomAlias for
dpnp.random.RandomState.random_sample.dpnp.random.RandomState.randConvenience function that accepts dimensions as input, e.g.,
rand(2, 2)would generate a 2-by-2 array of floats, uniformly distributed over[0, 1).