NumPy arctan()

import numpy as np

# create an array 
array1 = np.array([0, 1, -1])

# calculates the element-wise arctangent (inverse tangent) of array1
result = np.arctan(array1)

print(result)

# Output: [ 0.          0.78539816 -0.78539816]

arctan() Syntax

The syntax of the numpy.arctan() method is:

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

arctan() Arguments

The numpy.arctan() method takes the 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 arctangent
• dtype (optional) - data type of the output array

arctan() Return Value

The numpy.arctan() method returns an array with the corresponding inverse tangent values.

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

import numpy as np

array1 = np.array([0, -1, 1, 10, 100, -2])

# create an array of zeros with the same shape as array1
result = np.zeros_like(array1, dtype=float)  

# compute inverse tangent of elements in array1 
# only where the element is greater than or equal to 0
np.arctan(array1, out = result, where = (array1 >= 0))

print(result)

Output

[0.         0.         0.78539816 1.47112767 1.56079666 0.        ]

Here,

• out = result specifies that the output of the numpy.arctan() method should be stored in the result array,
• where = (array1 >= 0) specifies that the inverse tangent operation should only be applied to elements in array1 that are greater than or equal to 0.

Example 2: Use of dtype Argument in arctan()

import numpy as np

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

# calculate the inverse tangent of
# each value with float data type
arctans_float = np.arctan(values, dtype = float)

print("Inverse Tangent with 'float' dtype:")
print(arctans_float)

# calculate the inverse tangent of
# each value with complex data type
arctans_complex = np.arctan(values, dtype = complex)

print("\nInverse Tangent with 'complex' dtype:")
print(arctans_complex)

Output

Inverse Tangent with 'float' dtype:
[ 0.          0.78539816 -0.78539816]

Inverse Tangent with 'complex' dtype:
[ 0.        +0.j  0.78539816+0.j -0.78539816+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.