numpy.ldexp#

numpy.ldexp(x1,x2,/,out=None,*,where=True,casting='same_kind',order='K',dtype=None,subok=True[,signature])=<ufunc'ldexp'>#

Returns x1 * 2**x2, element-wise.

The mantissasx1 and twos exponentsx2 are used to constructfloating point numbersx1*2**x2.

Parameters:

x1array_like

Array of multipliers.

x2array_like, int

Array of twos exponents.Ifx1.shape!=x2.shape, they must be broadcastable to a commonshape (which becomes the shape of the output).

outndarray, None, or tuple of ndarray and None, optional

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

wherearray_like, optional

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

**kwargs

For other keyword-only arguments, see theufunc docs.

Returns:

yndarray or scalar

The result ofx1*2**x2.This is a scalar if bothx1 andx2 are scalars.

See also

frexp

Return (y1, y2) fromx=y1*2**y2, inverse toldexp.

Notes

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

ldexp is useful as the inverse offrexp, if used by itself it ismore clear to simply use the expressionx1*2**x2.

Examples

Try it in your browser!

>>>importnumpyasnp>>>np.ldexp(5,np.arange(4))array([ 5., 10., 20., 40.], dtype=float16)

>>>x=np.arange(6)>>>np.ldexp(*np.frexp(x))array([ 0.,  1.,  2.,  3.,  4.,  5.])

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