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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) 

Links:
arcsin.html#numpy.arccos>https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.arcsin.html#numpy.arccos
,

# 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 ()