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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 Radians = 36o degreesReturn : An array with hyperbolic sine of x for all x i.e. array elements
Code #1 : Working
# Python3 program explaining# sinh() function import numpy as npimport 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
# Python program showing Graphical# representation of sinh() functionimport numpy as npimport 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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