numpy.arccosh
-
numpy.arccosh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'arccosh'>
-
Inverse hyperbolic cosine, element-wise.
- Parameters
-
-
xarray_like
-
Input array.
-
outndarray, 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.
-
wherearray_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, 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 will remain uninitialized. - **kwargs
-
For other keyword-only arguments, see the ufunc docs.
-
- Returns
-
-
arccoshndarray
-
Array of the same shape as
x
. This is a scalar ifx
is a scalar.
-
Notes
arccosh
is a multivalued function: for eachx
there are infinitely many numbersz
such thatcosh(z) = x
. The convention is to return thez
whose imaginary part lies in[-pi, pi]
and the real part in[0, inf]
.For real-valued input data types,
arccosh
always returns real output. For each value that cannot be expressed as a real number or infinity, it yieldsnan
and sets theinvalid
floating point error flag.For complex-valued input,
arccosh
is a complex analytical function that has a branch cut[-inf, 1]
and is continuous from above on it.References
-
1
-
M. Abramowitz and I.A. Stegun, “Handbook of Mathematical Functions”, 10th printing, 1964, pp. 86. http://www.math.sfu.ca/~cbm/aands/
-
2
-
Wikipedia, “Inverse hyperbolic function”, https://en.wikipedia.org/wiki/Arccosh
Examples
>>> np.arccosh([np.e, 10.0]) array([ 1.65745445, 2.99322285]) >>> np.arccosh(1) 0.0
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Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.19/reference/generated/numpy.arccosh.html