Handling edge cases

Now that we have seen how to write the function for applying the red filter to a specific region in an image, let us see how we can handle few edge cases that arise depending on the given input parameters. We will only focus on the following edge cases:

• The given height is out of bounds which means the given height parameter when added to the row index given in the top_left tuple is greater than the total number of rows present in the 2D list.

• The given width is out of bounds which means the given width parameter when added to the column index given in the top_left tuple is greater than the total number of columns present in the 2D list.

• If height or width or the elements of the tuple top_left are negative, it is considered as invalid input.

The way we will handle these cases is returning a message to the user either saying “Input parameter out of bounds” or “Invalid input”.

So the function will now be modified as follows:

Sample 1

Then the output from the function would be:

Input parameter out of bounds

This is because top_left[1] + width would give us 1+2=3 which is greater than the number of columns present in the given 2 Dimensional list.

Sample 2

Invalid input

This is because one of the input parameters height is negative.

Sample 3

Then the output from the function would be:

Input parameter out of bounds

This is because top_left[0] + height would give us 0+3=3 which is greater than the number of rows present in the given 2D list.