numpy.arctan(x[, out]) = ufunc ‘arctan’) : This mathematical function helps user to calculate inverse tangent for all x(being the array elements).
Parameters :
array : [array_like]elements are in radians. out : [array_like]array of same shape as x.
Note :
2pi Radians = 360 degrees
The convention is to return the angle z whose real part lies in [-pi/2, pi/2].
Return :
An array with inverse tangent of x for all x i.e. array elements. The values are in the closed interval [-pi/2, pi/2].
Code #1 : Working
# Python program explaining # arctan() function import numpy as np in_array = [0, 1, 0.3, -1] print ("Input array : \n", in_array) arctan_Values = np.arctan(in_array) print ("\nInverse Tangent values : \n", arctan_Values) |
Output :
Input array : [0, 1, 0.3, -1] Inverse Tangent values : [ 0. 0.78539816 0.29145679 -0.78539816]
Code #2 : Graphical representation
# Python program showing # Graphical representation # of arctan() function import numpy as np import matplotlib.pyplot as plt in_array = np.linspace(-np.pi, np.pi, 12) out_array1 = np.tan(in_array) out_array2 = np.arctan(in_array) print("in_array : ", in_array) print("\nout_array with tan : ", out_array1) print("\nout_arraywith arctan : ", out_array1) # red for numpy.arccos() plt.plot(in_array, out_array1, color = 'blue', marker = "*") plt.plot(in_array, out_array2, color = 'red', marker = "o") plt.title("blue : numpy.tan() \nred : numpy.arctan()") 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 tan : [ 1.22464680e-16 6.42660977e-01 2.18969456e+00 -6.95515277e+00 -1.15406152e+00 -2.93626493e-01 2.93626493e-01 1.15406152e+00 6.95515277e+00 -2.18969456e+00 -6.42660977e-01 -1.22464680e-16] out_arraywith arctan : [ 1.22464680e-16 6.42660977e-01 2.18969456e+00 -6.95515277e+00 -1.15406152e+00 -2.93626493e-01 2.93626493e-01 1.15406152e+00 6.95515277e+00 -2.18969456e+00 -6.42660977e-01 -1.22464680e-16]
References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.arcsin.html#numpy.arccos
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