Last Updated : 04 Dec, 2020
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 Radians = 36o degrees Return : An array with hyperbolic sine of x for all x i.e. array elementsCode #1 : Working Python3
# Python3 program explaining
# sinh() function
import numpy as np
import math
in_array = [0, math.pi / 2, np.pi / 3, np.pi]
print ("Input array : \n", in_array)
Sinh_Values = np.sinh(in_array)
print ("\nSine Hyperbolic values : \n", Sinh_Values)
Output :
Input array : [0, 1.5707963267948966, 1.0471975511965976, 3.141592653589793] Sine Hyperbolic values : [ 0. 2.3012989 1.24936705 11.54873936]Code #2 : Graphical representation Python3
# Python program showing Graphical
# representation of sinh() function
import numpy as np
import matplotlib.pyplot as plt
in_array = np.linspace(-np.pi, np.pi, 12)
out_array = np.sinh(in_array)
print("in_array : ", in_array)
print("\nout_array : ", out_array)
# red for numpy.sinh()
plt.plot(in_array, out_array, color = 'red', marker = "o")
plt.title("numpy.sinh()")
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 : [-11.54873936 -6.49723393 -3.62383424 -1.9652737 -0.96554336 -0.28949778 0.28949778 0.96554336 1.9652737 3.62383424 6.49723393 11.54873936]References : https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.sinh.html#numpy.sinh
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