# NumPy arctan()

The `numpy.arctan()` method computes the arctangent (inverse tangent) of an array.

### Example

``````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.