# numpy.arctanh in Python ()

numpy.arctanh (): this math function helps the user to compute the inverse hyperbolic tangent element-wise for all samples

Syntax: numpy.arctanh (arr, /, out = None, *, where = True, casting = `same_kind`, order = `K`, dtype = None, ufunc `arctanh`)
Parameters:

arr: array_like
Input array.
out: [ndarray, optional] A location into which the result is stored.
– & gt; If provided, it must have a shape that the inputs broadcast to.
– & gt; If not provided or None, a freshly-allocated array is returned.
where: array_like, optional
Values ​​of True indicate to calculate the ufunc at that position, values ​​of False indicate to leave the value in the output alone.
** kwargs: Allows to pass keyword variable length of argument to a function. Used when we want to handle named argument in a function.

Return: An array with inverse hyperbolic tangent of arr
for all arr ie array elements.

Note:

The convention is to return the angle of arr whose imaginary part lies in [-pi / 2, pi / 2].

Code # 1: Work

` `

``` # Python program explaining # arctanh () function   import numpy as np   in_array = [ 0.2 , 0.11  , 0.5 , 0.99 ] print ( " Input array: " , in_array)    arctanh_Values ​​ = np.arctanh (in_array) print ( "Inverse hyperbolic tangent values ​​of input array:" , arctanh_Values) ```

Output:

` Input array: [0.2, 0.11, 0.5, 0.99] Inverse hyperbolic tangent values ​​of input array: [0.20273255 0.11044692 0.54930614 2.64665241] `

Code # 2: Graphical representation

 ` # Show Python program ` ` # Graphical representation ` ` Number of arctanh () functions% matplotlib inline ` ` import ` ` numpy as np ` ` import ` ` matplotlib.pyplot as plt ` ` in_array ` ` = ` ` np.linspace (` ` 0.1 ` `, ` ` 0.99 ` ` , ` ` 25 ` `) ` ` out_array1 = np.tan (in_array) ```` out_array2 = np.arctanh (in_array)    print ( "in_array:" , in_array) print ( "out_array with tan:" , out_array1) print ( "out_array with arctanh:" , out_array2) # blue for numpy.tanh () # red for numpy.arctanh () plt.plot (in_array, out_array1, color = `blue` , marker = "." )    plt.plot (in_array, out_array2, color = `red` , marker = " + " )    plt.title ( " blue: numpy.tan () red: numpy.arctanh () " ) plt.xlabel ( "X" ) plt.ylabel ( " Y " ) ```

Output:

``` in_array: [0.1 0.13708333 0.17416667 0.21125 0.24833333 0.28541667 0.3225 0.35958333 0.39666667 0.43375 0.47083333 0.50791667 0.545 0.58208333 0.6191633667336 75 0.80458333 0.84166667 0.87875 0.91583333 0.95291667 0.99] out_array with tan: [0.10033467 0.13794852 0.17594936 0.21444958 0.25356734 0.29342809 0.33416626 0.37592723 0.41886955 0.46316761 0.5090147 0.55662672 0.60624669 0.65815012 0.7126517 0.77011355 0.83095552 0.89566817 0.96482941 1.03912577 1.11938038 1.20658966 1.30197266 1.40703805 1.52367674] out_array with arctanh: [0.10033535 0.13795183 0.17596049 0.21447937 0.25363582 0.29356929 0.33443481 0.37640728 0.41968694 0.4645065 0.51114049 0.5599181 0.61124089 0.66560789 0.72365253 0.78619832 0.85434644 0.92961997 1.01421559 1.11147549 1.22686186 1.37025371 1.5625545 1.86258009 2.64665241 p>

```