### Advent of Code 2020 review

A look back on the event

Sledding and laziness

Day 3 showed both the advantages of lazy evaluation, and the constant pain of off-by-one errors.

My first decision was how to represent the grid of trees. I decided on a `Set`

of points, one for each tree. The next decision was how to describe each point: as (*x*, *y*) coordinates, or as (row, column) coordinates? I decided on (row, column) for no particular reason. I did think about representing each position as a complex number, but I quickly discovered I never used both parts together in the same way.

Reading the grid was essentially `zip`

ping the elements of the grid with their indices, and keeping the indices that contain a tree.

```
readGrid input = (trees, (maxR, maxC))
where trees = S.fromList $ concat
[ [(r, c) | (t, c) <- zip row [0..], t == '#']
| (row, r) <- zip rows [0..] ]
rows = lines input
maxC = (length $ head rows) - 1
maxR = (length rows) - 1
```

Given a set of tree locations, I then had to generate a set of locations visited by the sled. The size of the intersection of these sets would give the number of trees visited. I could either wrap the map (using `cycle`

) or wrap the indices (using modulus). Given I already had a set rather than separate rows, I decided to wrap the indices.

The places visited by the sled are generated as an infinite list of positions (using `iterate`

, but taking only those within the grid (using `takeWhile withinTrees`

).

```
part1 trees maxCorner = countEncounteredTrees trees maxCorner (1, 3)
countEncounteredTrees trees maxCorner delta = S.size $ S.intersection trees visited
where visited = S.fromList $ takeWhile (withinTrees maxCorner) $ visitedPlaces delta maxCorner
visitedPlaces :: Position -> Position -> [Position]
visitedPlaces (dr, dc) (_maxR, maxC) = iterate wrappingStep (0, 0)
where wrappingStep (r, c) = (r + dr, (c + dc) `mod` (maxC + 1))
withinTrees (maxR, maxC) (r, c) = r >= 0 && r <= maxR && c >= 0 && c <= maxC
```

Part 2 was much the same, but using several steps and multiplying their results together with `product`

.

```
part2 trees maxCorner = product $ map cet [(1, 1), (1, 3), (1, 5), (1, 7), (2, 1)]
where cet = countEncounteredTrees trees maxCorner
```

You can find the code here or on Gitlab.