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). Parameters : array : [array_like]elements are in radians. out : [optional]shape same as array. 2pi Radians = 360 degrees tan(x) = sin(x) / cos(x) Ret 2 min read numpy.sinh() in Python The numpy.sinh() is a mathematical function that 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). Syntax: numpy.sinh(x[, out]) = ufunc 'sin') Parameters : array : [array_like] elements are in radians. 2pi 2 min read numpy.sin() in Python numpy.sin(x[, out]) = ufunc 'sin') : This mathematical function helps user to calculate trigonometric sine for all x(being the array elements). Parameters : array : [array_like]elements are in radians. 2pi Radians = 36o degrees Return : An array with trigonometric sine of x for all x i.e. array elem 1 min read numpy.cos() in Python numpy.cos(x[, out]) = ufunc 'cos') : This mathematical function helps user to calculate trigonometric cosine for all x(being the array elements). Parameters : array : [array_like]elements are in radians. 2pi Radians = 360 degrees Return : An array with trigonometric cosine of x for all x i.e. array 2 min read numpy.cosh() in Python 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. 2pi R 2 min read numpy.angle() in Python numpy.angle() function is used when we want to compute the angle of the complex argument. A complex number is represented by â x + yi " where x and y are real number and i= (-1)^1/2. The angle is calculated by the formula tan-1(x/y). Syntax : numpy.angle(z, deg=0) Parameters : z : [array_like] A com 2 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read numpy.arctan() in Python numpy.arctan(x[, out]) = ufunc 'arctan') : This mathematical function helps user to calculate inverse tangent for all x(being the array elements). Parameters : array : [array_like]elements are in radians. out : [array_like]array of same shape as x. Note : 2pi Radians = 360 degrees The convention is 2 min read Python PyTorch from_numpy() PyTorch is an open-source machine learning library developed by Facebook. It is used for deep neural network and natural language processing purposes. The function torch.from_numpy() provides support for the conversion of a numpy array into a tensor in PyTorch. It expects the input as a numpy array 1 min read numpy.arctanh in Python() 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, o 3 min read Like