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numpy.arccos () in Python

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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 [0 , pi].

Return:

` An array with inverse cosine of x for all x ie array elements. The values ​​are in the closed interval [-pi / 2, pi / 2]. `

Code # 1: Work

 ` # Python program explaining ` ` # arccos () function `   ` import ` ` numpy as np ` ` `  ` in_array ` ` = ` ` [` ` 0 ` `, ` ` 1 ` `, ` ` 0.3 ` `, ` ` - ` ` 1 ` ` ] ` ` print ` ` (` ` "Input array: "` `, in_array) ` ` `  ` arccos_Values ​​` ` = ` ` np.arccos (in_array ) ` ` print ` ` (` ` "Inverse Cosine values : "` `, arccos_Values) `

Output:

` Input array: [0, 1, 0.3, -1] Inverse Cosine values: [1.57079633 0. 1.26610367 3.14159265] `

Code # 2: Graphic representation

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 cos: [-1. -0.84125353 -0.41541501 0.14231484 0.65486073 0.95949297 0.95949297 0.65486073 0.14231484 -0.41541501 -0.84125353 -1. ] out_arraywith arccos: [-1. -0.84125353 -0.41541501 0.14231484 0.65486073 0.95949297 0.95949297 0.65486073 0.14231484 -0.41541501 -0.84125353 -1. ] RuntimeWarning: invalid value encountered in arccos out_array1 = np.sin (in_array) `

 ` # Show Python program ` ` # Graphical representation ` ` Number of arccos () functions ` ` `  ` import ` ` numpy as np ` ` import matplotlib.pyplot as plt ``   in_array = np.linspace ( - np.pi, np.pi, 12 ) out_array1 = np.cos (in_array) out_array2 = np.arccos (in_array)   print ( "in_array:" , in_array) print ( "out_array with cos:" , out_array1) print ( "out_arraywith arccos:" , 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.cos () red: numpy.arccos ()" ` `) ` ` plt.xlabel (` ` "X" ` `) ` ` plt.ylabel (` `" Y "` `) ` ` plt.show () `