NumPy arccos()

import numpy as np

# create an array of values between -1 and 1
values = np.array([-1, -0.5, 0, 0.5, 1])

# calculate the inverse cosine of each value
inverseCosines = np.arccos(values)

print(inverseCosines)

# Output: [3.14159265 2.0943951  1.57079633 1.04719755 0.        ]

arccos() Syntax

The syntax of arccos() is:

numpy.arccos(x, out = None, where = True, dtype = None)

arccos() Arguments

The arccos() method takes following arguments:

• x - an input array
• out (optional) - the output array where the result will be stored
• where (optional) - a boolean array or condition indicating where to compute the arccosine
• dtype (optional) - data type of the output array

arccos() Return Value

The arccos() method returns an array with the corresponding inverse cosine values.

Example 1: Use of out and where in arccos()

import numpy as np

# create an array of values between -0.5 and 0.5
values = np.array([-0.5, -0.2, 0, 0.2, 0.5])

# create an array of zeros with the same shape as values
result = np.zeros_like(values, dtype = float)  

# calculate inverse cosine where values >= 0 and store in result.
np.arccos(values, out = result, where = (values >= 0))

print(result)

Output

[0.         0.         1.57079633 1.36943841 1.04719755]

Here,

• out = result specifies that the output of the np.arccos() function should be stored in the result array
• where=(values >= 0) specifies that the inverse cosine operation should only be applied to elements in values that are greater than or equal to 0.

Example 2: Use of dtype Argument in arccos()

import numpy as np

# create an array of values
values = np.array([0, 1, -1])

# calculate the inverse cosine of each value with float data type
arccos Float = np.arccos(values, dtype = float)

print("Inverse Cosine with 'float' dtype:")
print(arccos Float)

# calculate the inverse cosine of each value with complex data type
arccosComplex = np.arccos(values, dtype = complex)

print("\nInverse Cosine with 'complex' dtype:")
print(arccosComplex)

Output

Inverse Cosine with 'float' dtype:
[1.57079633 0.         3.14159265]

Inverse Cosine with 'complex' dtype:
[1.57079633-0.j 0.        -0.j 3.14159265-0.j]

Here, by specifying the desired dtype, we can control the data type of the output array according to our specific requirements.

Note: To learn more about the dtype argument, please visit NumPy Data Types.