dpnp.random.Generator.uniform

method

Generator.uniform(low=0.0, high=1.0, size=None, dtype=None, *, usm_type=None)

Draw samples from a uniform distribution over [low, high).

For full documentation refer to numpy.random.Generator.uniform.

Parameters:

low{float, array_like of floats, dpnp.ndarray, usm_ndarray}, optional

The lower bound of the output interval.

Default: 0.0.

high{float, array_like of floats, dpnp.ndarray, usm_ndarray}, optional

The upper bound of the output interval.

Default: 1.0.

size{None, int, tuple of ints}, optional

Output shape. With None, the broadcast shape of low and high.

Default: None.

dtype{None, dtype}, optional

The data type of the output, dpnp.float32 or dpnp.float64.

Default: None, which means the default floating-point type of the device.

usm_type{None, "device", "shared", "host"}, optional

The type of SYCL USM allocation for the output array.

Default: None, which means the USM type of the array parameters, or "device" when there are none.

Returns:

outdpnp.ndarray

The samples.

Limitations

dtype and usm_type are not in NumPy's signature. A high - low range that overflows dtype raises OverflowError, as it does in float64.

Examples

>>> import dpnp as np
>>> rng = np.random.default_rng(42)
>>> x = rng.uniform(-1, 0, 1000)
>>> bool(((-1 <= x) & (x < 0)).all())
True