dpnp.frexp

dpnp.frexp = <DPNPUnaryTwoOutputsFunc '_frexp'>

Decompose each element \(x_i\) of the input array x into the mantissa and the twos exponent.

For full documentation refer to numpy.frexp.

Parameters:

  • x ({dpnp.ndarray, usm_ndarray}) -- Array of numbers to be decomposed, expected to have a real-valued floating-point data type.

  • out1 ({None, dpnp.ndarray, usm_ndarray}, optional) --

    Output array for the mantissa to populate. Array must have the same shape as x and the expected data type.

    Default: None.

  • out2 ({None, dpnp.ndarray, usm_ndarray}, optional) --

    Output array for the exponent to populate. Array must have the same shape as x and the expected data type.

    Default: None.

  • order ({None, "C", "F", "A", "K"}, optional) --

    Memory layout of the newly output array, if parameter out is None.

    Default: "K".

Returns:

  • mantissa (dpnp.ndarray) -- Floating values between -1 and 1.

  • exponent (dpnp.ndarray) -- Integer exponents of 2.

Limitations

Parameters where and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

See also

dpnp.ldexp

Compute \(y = x1 * 2^{x2}\), inverse to dpnp.frexp.

Notes

Complex dtypes are not supported, they will raise a TypeError.

Examples

>>> import dpnp as np
>>> x = np.arange(9)
>>> y1, y2 = np.frexp(x)
>>> y1
array([0.   , 0.5  , 0.5  , 0.75 , 0.5  , 0.625, 0.75 , 0.875, 0.5  ])
>>> y2
array([0, 1, 2, 2, 3, 3, 3, 3, 4], dtype=int32)
>>> y1 * 2**y2
array([0., 1., 2., 3., 4., 5., 6., 7., 8.])