mars.tensor.frexp

mars.tensor.frexp(x, out1=None, out2=None, out=None, where=None, **kwargs)[source]

Decompose the elements of x into mantissa and twos exponent.

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

x : array_like
Tensor of numbers to be decomposed.
out1 : Tensor, optional
Output tensor for the mantissa. Must have the same shape as x.
out2 : Tensor, optional
Output tensor for the exponent. Must have the same shape as x.
out : Tensor, None, or tuple of Tensor 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 tensor is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.

**kwargs

(mantissa, exponent) : tuple of tensors, (float, int)
mantissa is a float array with values between -1 and 1. exponent is an int array which represents the exponent of 2.

ldexp : Compute y = x1 * 2**x2, the inverse of frexp.

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

>>> import mars.tensor as mt
>>> from mars.session import new_session
>>> x = mt.arange(9)
>>> y1, y2 = mt.frexp(x)
>>> sess = new_session().as_default()
>>> y1_result, y2_result = sess.run(y1, y2)
>>> y1_result
array([ 0.   ,  0.5  ,  0.5  ,  0.75 ,  0.5  ,  0.625,  0.75 ,  0.875,
        0.5  ])
>>> y2_result
array([0, 1, 2, 2, 3, 3, 3, 3, 4])
>>> (y1 * 2**y2).execute(session=sess)
array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.])