Last Updated : 08 Mar, 2024
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 Radians = 36o degrees Return : An array with hyperbolic cosine of x for all x i.e. array elementsCode #1 : Working Python3
# Python3 program explaining
# cosh() function
import numpy as np
import 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 Python3
# Python program showing Graphical
# representation of cosh() function
import numpy as np
import 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]
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