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).
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Syntax : numpy.cosh(x[, out]) = ufunc ‘cos’)
Parameters :array : [array_like] elements are in radians.
2pi Radians = 36o degreesReturn : An array with hyperbolic cosine of x for all x i.e. array elements
Code #1 : Working
# Python3 program explaining# cosh() function import numpy as npimport math in_array = [0, math.pi / 2, np.pi / 3, np.pi]print ("Input array : \n", in_array) cosh_Values = np.cosh(in_array)print ("\ncosine Hyperbolic values : \n", cosh_Values) |
Output :
Input array : [0, 1.5707963267948966, 1.0471975511965976, 3.141592653589793] cosine Hyperbolic values : [ 1. 2.50917848 1.60028686 11.59195328]
Code #2 : Graphical representation
# Python program showing Graphical# representation of cosh() functionimport numpy as npimport matplotlib.pyplot as plt in_array = np.linspace(-np.pi, np.pi, 12)out_array = np.cosh(in_array) print("in_array : ", in_array)print("\nout_array : ", out_array) # red for numpy.cosh()plt.plot(in_array, out_array, color = 'red', marker = "o")plt.title("numpy.cosh()")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 : [ 11.59195328 6.57373932 3.75927846 2.20506252 1.39006258 1.04106146 1.04106146 1.39006258 2.20506252 3.75927846 6.57373932 11.59195328]
References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.cosh.html#numpy.cosh
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