arcsinh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Some inconsistencies with the Dask version may exist.

Inverse hyperbolic sine element-wise.

Notes

arcsinh is a multivalued function: for each x there are infinitely many numbers :None:None:`z` such that :None:None:`sinh(z) = x`. The convention is to return the :None:None:`z` whose imaginary part lies in :None:None:`[-pi/2, pi/2]`.

For real-valued input data types, arcsinh always returns real output. For each value that cannot be expressed as a real number or infinity, it returns nan and sets the :None:None:`invalid` floating point error flag.

For complex-valued input, arccos is a complex analytical function that has branch cuts :None:None:`[1j, infj]` and :None:None:`[-1j, -infj]` and is continuous from the right on the former and from the left on the latter.

The inverse hyperbolic sine is also known as :None:None:`asinh` or sinh^-1 .

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 :None:None:`out` array will be set to the ufunc result. Elsewhere, the :None:None:`out` array will retain its original value. Note that if an uninitialized :None:None:`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 <ufuncs.kwargs> .

Returns

out : ndarray or scalar

Array of the same shape as x. This is a scalar if x is a scalar.

This docstring was copied from numpy.arcsinh.

Examples

This example is valid syntax, but we were not able to check execution

>>> np.arcsinh(np.array([np.e, 10.0]))  # doctest: +SKIP
array([ 1.72538256,  2.99822295])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.ufunc.arccosh dask.array.ufunc.arcsinh

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