# numpy.sinh() in Python

numpy.sinh(x[, out]) = ufunc ‘sin’) : This mathematical function helps user to calculate hyperbolic sine for all x(being the array elements).

Equivalent to 1/2 * (np.exp(x) – np.exp(-x)) or -1j * np.sin(1j*x).

Parameters :

array : [array_like] elements are in radians.

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

Code #1 : Working

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

Output :

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

Sine Hyperbolic values :
[  0.           2.3012989    1.24936705  11.54873936]
```

Code #2 : Graphical representation

 `# Python program showing Graphical ` `# representation of sinh() function ` `import` `numpy as np ` `import` `matplotlib.pyplot as plt ` ` `  `in_array ``=` `np.linspace(``-``np.pi, np.pi, ``12``) ` `out_array ``=` `np.sinh(in_array) ` ` `  `print``(``"in_array : "``, in_array) ` `print``(``"\nout_array : "``, out_array) ` ` `  `# red for numpy.sinh() ` `plt.plot(in_array, out_array, color ``=` `'red'``, marker ``=` `"o"``) ` `plt.title(``"numpy.sinh()"``) ` `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 :  [-11.54873936  -6.49723393  -3.62383424  -1.9652737   -0.96554336
-0.28949778   0.28949778   0.96554336   1.9652737    3.62383424
6.49723393  11.54873936]```

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