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numpy.cosh() in Python
• Last Updated : 04 Dec, 2020

The numpy.cosh() is a mathematical function that helps user to calculate hyperbolic cosine for all x(being the array elements).

Equivalent to `1/2 * (np.exp(x) - np.exp(-x))` and `np.cos(1j*x)`.

Syntax : numpy.cosh(x[, out]) = ufunc ‘cos’)
Parameters :

array : [array_like] elements are in radians.

Return : An array with hyperbolic cosine of x for all x i.e. array elements

Code #1 : Working

 `# Python3 program explaining``# cosh() function`` ` `import` `numpy as np``import` `math`` ` `in_array ``=` `[``0``, math.pi ``/` `2``, np.pi ``/` `3``, np.pi]``print` `(``"Input array : \n"``, in_array)`` ` `cosh_Values ``=` `np.cosh(in_array)``print` `(``"\ncosine Hyperbolic values : \n"``, cosh_Values)`

Output :

```Input array :
[0, 1.5707963267948966, 1.0471975511965976, 3.141592653589793]

cosine Hyperbolic values :
[  1.           2.50917848   1.60028686  11.59195328]
```

Code #2 : Graphical representation

 `# Python program showing Graphical``# representation of cosh() function``import` `numpy as np``import` `matplotlib.pyplot as plt`` ` `in_array ``=` `np.linspace(``-``np.pi, np.pi, ``12``)``out_array ``=` `np.cosh(in_array)`` ` `print``(``"in_array : "``, in_array)``print``(``"\nout_array : "``, out_array)`` ` `# red for numpy.cosh()``plt.plot(in_array, out_array, color ``=` `'red'``, marker ``=` `"o"``)``plt.title(``"numpy.cosh()"``)``plt.xlabel(``"X"``)``plt.ylabel(``"Y"``)``plt.show()`

Output :

```in_array :  [-3.14159265 -2.57039399 -1.99919533 -1.42799666 -0.856798   -0.28559933
0.28559933  0.856798    1.42799666  1.99919533  2.57039399  3.14159265]

out_array :  [ 11.59195328   6.57373932   3.75927846   2.20506252   1.39006258
1.04106146   1.04106146   1.39006258   2.20506252   3.75927846
6.57373932  11.59195328]```

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