The apply_along_axis() method allows you to apply a function to each row or column of a multidimensional array, without using explicit loops.
apply_along_axis() Syntax
The syntax of apply_along_axis() is:
numpy.apply_along_axis(func1d, axis, arr, *args, **kwargs)
apply_along_axis() Arguments
The apply_along_axis() method takes following arguments:
func1d- the function to apply along the specified axisaxis- the axis along which the function is appliedarr- the input array to which the function will be applied*argsand**kwargs- additional arguments and keyword arguments present infunc1d
Note: The func1d should take a 1D array as input and return a single value or an array of values.
apply_along_axis() Return Value
The apply_along_axis() method returns the resultant array with functions applied.
Example 1: Apply a Function That Returns a Single Value
Output
[3 6 9] [7 8 9]
Example 2: Apply a Function That Returns an Array of Values
We can also return an array of values from the function.
Output
[[ 1 4 9] [16 25 36] [49 64 81]]
Example 3: Apply a Function That Returns an N-D Array of Values
We can return an n-D array of values from the function.
Let's see an example.
Output
Along axis 0 [[[ 1 4 9] [ 16 25 36] [ 49 64 81]] [[ 1 8 27] [ 64 125 216] [343 512 729]]] Along axis 1 [[[ 1 4 9] [ 1 8 27]] [[ 16 25 36] [ 64 125 216]] [[ 49 64 81] [343 512 729]]]
For a function that returns a higher dimensional array, the dimensions are inserted in place of the axis dimension.
Example 4: Apply a lambda Function to an Array
Instead of defining a function, we can directly pass a lambda function.
Let's see an example.
Output
[ 6 15 24]