numpy.arcsin() in Python

Last Updated : 22 May, 2024

numpy.arcsin(x[, out]) = ufunc 'arcsin') : This mathematical function helps user to calculate inverse sine for all x(being the array elements). Parameters :

 array : [array_like]elements are in radians. out : [array_like]array of same shape as x.

Return :

 An array with inverse sine of x for all x i.e. array elements. The values are in the closed interval [-pi/2, pi/2].

Code #1 : Working

Python3

# Python program explaining # arcsin() function import numpy as np in_array = [0, 1, 0.3, -1] print ("Input array : \n", in_array) arcsin_Values = np.arcsin(in_array) print ("\nInverse Sine values : \n", arcsin_Values)

Output :

 Input array : [0, 1, 0.3, -1] Inverse Sine values : [ 0. 1.57079633 0.30469265 -1.57079633]

Code #2 : Graphical representation

Python3

# Python program showing # Graphical representation of  # arcsin() function import numpy as np import matplotlib.pyplot as plt in_array = np.linspace(-np.pi, np.pi, 12) out_array1 = np.sin(in_array) out_array2 = np.arcsin(in_array) print("in_array : ", in_array) print("\nout_array with sin : ", out_array1) print("\nout_arraywith arcsin : ", out_array1) # red for numpy.arcsin() plt.plot(in_array, out_array1, color = 'blue', marker = "*") plt.plot(in_array, out_array2, color = 'red', marker = "o") plt.title("blue : numpy.sin() \nred : numpy.arcsin()") 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 with sin : [ -1.22464680e-16 -5.40640817e-01 -9.09631995e-01 -9.89821442e-01 -7.55749574e-01 -2.81732557e-01 2.81732557e-01 7.55749574e-01 9.89821442e-01 9.09631995e-01 5.40640817e-01 1.22464680e-16] out_arraywith arcsin : [ -1.22464680e-16 -5.40640817e-01 -9.09631995e-01 -9.89821442e-01 -7.55749574e-01 -2.81732557e-01 2.81732557e-01 7.55749574e-01 9.89821442e-01 9.09631995e-01 5.40640817e-01 1.22464680e-16] RuntimeWarning: invalid value encountered in arcsin out_array2 = np.arcsin(in_array)