flopscope.

flopscope.numpy.frexp

fnp.frexp(*args, **kwargs)[flopscope source][numpy source]

Decompose the elements of x into mantissa and twos exponent.

Adapted from NumPy docs np.frexp

Areacore
Typecounted
NumPy Refnp.frexp
Cost
numel(output)\text{numel}(\text{output})
Flopscope Context

Decompose x into mantissa and exponent element-wise.

Returns (mantissa, exponent), where x = mantissa * 2**exponent. The mantissa lies in the open interval(-1, 1), while the twos exponent is a signed integer.

Parameters

x:array_like

Array of numbers to be decomposed.

out1:ndarray, optional

Output array for the mantissa. Must have the same shape as x.

out2:ndarray, optional

Output array for the exponent. Must have the same shape as x.

out:ndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

where:array_like, optional

This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.

**kwargs

For other keyword-only arguments, see the ufunc docs.

Returns

mantissa:ndarray

Floating values between -1 and 1. This is a scalar if x is a scalar.

exponent:ndarray

Integer exponents of 2. This is a scalar if x is a scalar.

See also

Notes

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

Examples

>>> import flopscope.numpy as fnp
>>> x = flops.arange(9)
>>> y1, y2 = flops.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.])