flopscope.numpy.arctanh
fnp.arctanh(*args, **kwargs)[flopscope source][numpy source]
Inverse hyperbolic tangent element-wise.
Adapted from NumPy docs np.arctanh
Element-wise inverse hyperbolic tangent.
Parameters
- x:array_like
Input array.
- 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
outarray will be set to the ufunc result. Elsewhere, theoutarray will retain its original value. Note that if an uninitializedoutarray is created via the defaultout=None, locations within it where the condition is False will remain uninitialized.- **kwargs
For other keyword-only arguments, see the ufunc docs.
Returns
- out:ndarray or scalar
Array of the same shape as
x. This is a scalar ifxis a scalar.
See also
- emath.arctanh
Notes
arctanh is a multivalued function: for each x there are infinitely
many numbers z such that tanh(z) = x. The convention is to return
the z whose imaginary part lies in [-pi/2, pi/2].
For real-valued input data types, arctanh always returns real output.
For each value that cannot be expressed as a real number or infinity,
it yields nan and sets the invalid floating point error flag.
For complex-valued input, arctanh is a complex analytical function
that has branch cuts [-1, -inf] and [1, inf] and is continuous from
above on the former and from below on the latter.
The inverse hyperbolic tangent is also known as atanh or tanh^-1.
References
1
M. Abramowitz and I.A. Stegun, "Handbook of Mathematical Functions",
10th printing, 1964, pp. 86.
https://personal.math.ubc.ca/~cbm/aands/page_86.htm2
Wikipedia, "Inverse hyperbolic function",
https://en.wikipedia.org/wiki/ArctanhExamples
>>> import flopscope.numpy as fnp
>>> flops.arctanh([0, -0.5])
array([ 0. , -0.54930614])