numpy.cosh#

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

Hyperbolic cosine, element-wise.

Equivalent to1/2*(np.exp(x)+np.exp(-x)) andnp.cos(1j*x).

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 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:

outndarray or scalar

Output array of same shape asx.This is a scalar ifx is a scalar.

Examples

Try it in your browser!

>>>importnumpyasnp>>>np.cosh(0)1.0

The hyperbolic cosine describes the shape of a hanging cable:

>>>importmatplotlib.pyplotasplt>>>x=np.linspace(-4,4,1000)>>>plt.plot(x,np.cosh(x))>>>plt.show()

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