numpy.arctanh in Python() (original) (raw)

Last Updated : 29 Nov, 2018

numpy.arctanh() : This mathematical function helps user to calculate inverse hyperbolic tangent, element-wise for all arr.

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. -> If provided, it must have a shape that the inputs broadcast to. -> 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 i.e. array elements. Note : 2pi Radians = 360 degrees The convention is to return the angle of arr whose imaginary part lies in [-pi/2, pi/2].

Code #1 : Working

Python `

Python program explaining

arctanh() function

import numpy as np

in_array = [0.2, 0.11, 0.5, 0.99] print ("Input array : \n", in_array)

arctanh_Values = np.arctanh(in_array) print ("\nInverse hyperbolic tangent values of input array : \n", 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

Python `

Python program showing

Graphical representation

of arctanh() function % 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("\nout_array with tan : ", out_array1) print("\nout_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() \nred : 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 0.61916667 0.65625 0.69333333 0.73041667 0.7675 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]