numpy.tanh() in Python Last Updated : 08 Mar, 2024 Comments Improve Suggest changes Like Article Like Report The numpy.tanh()is a mathematical function that helps user to calculate hyperbolic tangent for all x(being the array elements). Equivalent to np.sinh(x) / np.cosh(x) or -1j * np.tan(1j*x). Syntax : numpy.tanh(x[, out]) = ufunc 'tanh') Parameters : array : [array_like] elements are in radians. 2pi Radians = 36o degrees Return : An array with hyperbolic tangent of x for all x i.e. array elements Code #1 : Working Python3 # Python3 program explaining # tanh() function import numpy as np import math in_array = [0, math.pi / 2, np.pi / 3, np.pi] print ("Input array : \n", in_array) tanh_Values = np.tanh(in_array) print ("\nTangent Hyperbolic values : \n", tanh_Values) Output : Input array : [0, 1.5707963267948966, 1.0471975511965976, 3.141592653589793] Tangent Hyperbolic values : [ 0. 0.91715234 0.78071444 0.99627208] Code #2 : Graphical representation Python3 # Python program showing Graphical # representation of tanh() function import numpy as np import matplotlib.pyplot as plt in_array = np.linspace(-np.pi, np.pi, 12) out_array = np.tanh(in_array) print("in_array : ", in_array) print("\nout_array : ", out_array) # red for numpy.tanh() plt.plot(in_array, out_array, color = 'red', marker = "o") plt.title("numpy.tanh()") 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 : [-0.99627208 -0.98836197 -0.96397069 -0.89125532 -0.69460424 -0.27807943 0.27807943 0.69460424 0.89125532 0.96397069 0.98836197 0.99627208] Comment More infoAdvertise with us Next Article numpy.tanh() in Python mohit gupta_omg :) Follow Improve Article Tags : Python Python-numpy Python numpy-Mathematical Function Practice Tags : python Similar Reads numpy.tan() in Python numpy.tan(array[, out]) = ufunc 'tan') : This mathematical function helps user to calculate trigonometric tangent for all x(being the array elements). 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