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.

outtuple of None, dpnp.ndarray, or usm_ndarray, optional

A location into which the result is stored. If provided, it must be a tuple and have length equal to the number of outputs. Each provided array must have the same shape as x and the expected data type. It is prohibited to pass output arrays through out keyword when either out1 or out2 is passed.

Default: (None, None).

order{None, "C", "F", "A", "K"}, optional

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

Default: "K".

Returns:

mantissadpnp.ndarray: Floating values between -1 and 1.
exponentdpnp.ndarray: Integer exponents of 2.

Limitations

Parameters where, dtype 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.])