| 17 August 2025 | Challenge 334 |
Slice and Dice
Task 1: Range Sum
Submitted by: Mohammad Sajid Anwar
You are given a list integers and pair of indices.
Write a script to return the sum of integers between the given indices (inclusive).
Example 1
Input: @ints = (-2, 0, 3, -5, 2, -1), $x = 0, $y = 2
Output: 1
Elements between indices (0, 2) => (-2, 0, 3)
Range Sum: (-2) + 0 + 3 => 1
Example 2
Input: @ints = (1, -2, 3, -4, 5), $x = 1, $y = 3
Output: -3
Elements between indices (1, 3) => (-2, 3, -4)
Range Sum: (-2) + 3 + (-4) => -3
Example 3
Input: @ints = (1, 0, 2, -1, 3), $x = 3, $y = 4
Output: 2
Elements between indices (3, 4) => (-1, 3)
Range Sum: (-1) + 3 => 2
Example 4
Input: @ints = (-5, 4, -3, 2, -1, 0), $x = 0, $y = 3
Output: -2
Elements between indices (0, 3) => (-5, 4, -3, 2)
Range Sum: (-5) + 4 + (-3) + 2 => -2
Example 5
Input: @ints = (-1, 0, 2, -3, -2, 1), $x = 0, $y = 2
Output: 1
Elements between indices (0, 2) => (-1, 0, 2)
Range Sum: (-1) + 0 + 2 => 1
Solution
Two basic PDL operations:
slice
an ndarray and take the sum over an ndarray.
The slice operation is very flexible: non-negative indices count from the start, negative indices count from the end and a start index behind the end index reverses the slice.
Using the NiceSlice syntax for slice.
use strict;
use warnings;
use PDL;
use PDL::NiceSlice;
use experimental 'signatures';
sub range_sum ($x, $y, @ints) {
pdl(@ints)->($x:$y)->sum;
}
See the full solution to task 1.
Task 2: Nearest Valid Point
Submitted by: Mohammad Sajid Anwar
You are given current location as two integers: x and y. You are also given a list of points on the grid.
A point is considered valid if it shares either the same x-coordinate or the same y-coordinate as the current location.
Write a script to return the index of the valid point that has the smallest Manhattan distance to the current location. If multiple valid points are tied for the smallest distance, return the one with the lowest index. If no valid points exist, return -1.
The Manhattan distance between two points (x1, y1) and (x2, y2) is calculated as: |x1 - x2| + |y1 - y2|
Example 1
Input: $x = 3, $y = 4, @points ([1, 2], [3, 1], [2, 4], [2, 3])
Output: 2
Valid points: [3, 1] (same x), [2, 4] (same y)
Manhattan distances:
[3, 1] => |3-3| + |4-1| = 3
[2, 4] => |3-2| + |4-4| = 1
Closest valid point is [2, 4] at index 2.
Example 2
Input: $x = 2, $y = 5, @points ([3, 4], [2, 3], [1, 5], [2, 5])
Output: 3
Valid points: [2, 3], [1, 5], [2, 5]
Manhattan distances:
[2, 3] => 2
[1, 5] => 1
[2, 5] => 0
Closest valid point is [2, 5] at index 3.
Example 3
Input: $x = 1, $y = 1, @points ([2, 2], [3, 3], [4, 4])
Output: -1
No point shares x or y with (1, 1).
Example 4
Input: $x = 0, $y = 0, @points ([0, 1], [1, 0], [0, 2], [2, 0])
Output: 0
Valid points: all of them
Manhattan distances:
[0, 1] => 1
[1, 0] => 1
[0, 2] => 2
[2, 0] => 2
Tie between index 0 and 1, pick the smaller index: 0
Example 5
Input: $x = 5, $y = 5, @points ([5, 6], [6, 5], [5, 4], [4, 5])
Output: 0
Valid points: all of them
[5, 6] => 1
[6, 5] => 1
[5, 4] => 1
[4, 5] => 1
All tie, return the one with the lowest index: 0
Solution
Convert the points’ coordinates into absolute differences from the current location. The Manhattan distance between a point and the current location is simply the sum over the differences.
A valid point can then be identified by at least one zero difference.
Creating the index set of valid points and performing a
dice
operation with these indices on the points results in the valid points.
The index of the minimum Manhattan distance is then an index into the valid points, which points to the respective point.
This procedure is applicable to any number of dimension.
Using the NiceSlice syntax for dice.
use strict;
use warnings;
use PDL;
use PDL::NiceSlice;
use experimental 'signatures';
sub nearest_valid_point ($x, @points) {
my $d = abs pdl(@points) - pdl($x);
(my $valid = which !$d->minover)->isempty && return -1;
$valid($d(,$valid)->sumover->minimum_ind)->sclr;
}
See the full solution to task 2.
If you have a question about this post or if you like to comment on it, feel free to open an issue in my github repository.