Year 2015 Day 13 Part 1
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@ -132,7 +132,13 @@ solution.
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New Parser Effect stack and DLists
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- [Day 13](src/Years/Y2015/Day13.md)
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Naive ring buffer and `parameters` blocks[^2]
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## References
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[^1]: Idris 2 Manual:
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[Views and the "with" rule](https://idris2.readthedocs.io/en/latest/tutorial/views.html#views-and-the-with-rule)
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[^2]: <https://idris2.readthedocs.io/en/latest/tutorial/modules.html#parameterised-blocks-parameters-blocks>
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@ -34,3 +34,4 @@
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- [Day 10 - Digits View](Years/Y2015/Day10.md)
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- [Day 11 - Refinement Types](Years/Y2015/Day11.md)
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- [Day 12 - Custom Parser Effect and DLists](Years/Y2015/Day12.md)
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- [Day 13 - Naive Ring Buffer and parameters blocks](Years/Y2015/Day13.md)
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@ -19,6 +19,7 @@ import Years.Y2015.Day9
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import Years.Y2015.Day10
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import Years.Y2015.Day11
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import Years.Y2015.Day12
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import Years.Y2015.Day13
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```
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# Days
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@ -101,6 +102,12 @@ y2015 = MkYear 2015 [
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, day12
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```
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## [Day 13](Y2015/Day13.md)
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```idris
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, day13
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```
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```idris
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]
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```
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241
src/Years/Y2015/Day13.md
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241
src/Years/Y2015/Day13.md
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# [Year 2015 Day 13](https://adventofcode.com/2015/day/13)
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This day exhibits a naive, `Vect` based implementation of a ring buffer, as well
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as our first introduction to `parameters` blocks.
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```idris hide
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module Years.Y2015.Day13
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import Data.Primitives.Interpolation
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import Control.Eff
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import Runner
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```
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```idris
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import Data.String
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import Data.List1
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import Data.List.Lazy
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import Data.Vect
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import Data.Maybe
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import Data.SortedMap.Dependent
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import Decidable.Equality
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import Util
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%default total
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```
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## Parsing and Data Structures
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```idris
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Name : Type
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Name = String
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Happiness : Type
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Happiness = Integer
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```
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Describe a change in happiness from a change in seating arrangement as data
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structure, indexed by the name of the individual whose happiness it describes,
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and provide some projections.
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```idris
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data Change : (changee : Name) -> Type where
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NextTo : (changee : Name) -> (other : Name) -> (amount : Happiness)
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-> Change (changee)
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(.changee) : Change changee -> Name
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(.changee) (NextTo changee _ _) = changee
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(.other) : Change changee -> Name
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(.other) (NextTo _ other _) = other
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(.amount) : Change changee -> Happiness
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(.amount) (NextTo _ _ amount) = amount
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```
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Collect the list of changes provided as input into a structure that encodes our
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assumptions at the type level.
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The changes are stored in a in a dependent map, with the name of the individual
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as the key, and lists of potential changes to their happiness as the values.
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This problem is a bit nicer to express in terms of a collection of known size,
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and we don't want to be constantly converting the keys list to a `Vect`, so we
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instead store it in `Changes` as a `Vect`. We don't want to accidentally store
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the wrong thing here, so we store an auto-implicit proof of equality,
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`keys_prf`, proving that the `names` list is exactly the list of keys in
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`change_map` converted to a Vect with `fromList`.
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It will also make things a bit nicer if we can assume that our `names` list is
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non-empty, after all it really doesn't make sense to talk about seating
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arrangements at a table with 0 people at it, so we store an auto-implict
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`nonempty` proof establishing that the length of `change_map`'s keys list, and
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thus `names`, is at least 1.
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```idris
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record Changes where
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constructor MkChanges
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change_map : SortedDMap Name (\n => List (Change n))
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names : Vect (length (keys change_map)) Name
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{auto keys_prf : names = fromList (keys change_map)}
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{auto nonempty : IsSucc (length (keys change_map))}
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```
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Our usual pattern-matching based parsing of one element of the input, returning
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a dependent pair of the name of the individual this record describes, and the
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change described by that record.
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```idris
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parseChange : Has (Except String) fs => String -> Eff fs (name ** Change name)
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parseChange str = do
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changee ::: [_, direction, amount, _, _, _, _, _, _, other]
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<- pure $ split (== ' ') str
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| _ => throw "Invalid input string \{str}"
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amount <- note "Invalid amount \{amount} in \{str}" $ parseInteger amount
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amount : Happiness <-
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case direction of
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"gain" => pure amount
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"lose" => pure $ negate amount
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x => throw "Invalid direction \{x} in \{str}"
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let other = pack . filter (/= '.') . unpack $ other
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pure (_ ** (changee `NextTo` other) amount)
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```
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Parse the entire list of changes in the input, collecting them into a dependent
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map as we go along, and performing the checks needed for Idris to be satisfied
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that the conditions encoded by the auto-implict proofs in `Changes` are met.
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```idris
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parseChanges : Has (Except String) fs =>
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List String -> Eff fs Changes
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parseChanges strs = do
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changes <- traverse parseChange strs
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let change_map = insertChanges changes empty
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case isItSucc (length (keys change_map)) of
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Yes prf => pure $ MkChanges change_map (fromList (keys change_map))
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No contra => throw "Empty table, not very interesting"
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where
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insertChanges : List (name ** Change name)
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-> (acc : SortedDMap Name (\n => List (Change n)))
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-> SortedDMap Name (\n => List (Change n))
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insertChanges [] acc = acc
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insertChanges ((name ** change) :: xs) acc =
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case lookupPrecise name acc of
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Nothing => insertChanges xs (insert name [change] acc)
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Just ys => insertChanges xs (insert name (change :: ys) acc)
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```
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## Solver functions
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All of these functions are about to take the same first argument,
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`(cs : Changes)`. This is a really common occurrence, especially when dealing
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with dependent proof types, so Idris has syntax sugar to avoid repeating your
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self in theses situations, `parameters` blocks[^1].
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A `parameters` block adds the provided arguments to the start of every top level
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signature contained within it, in this case, making the first argument of all of
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these functions have type `(cs : Changes)`. The arguments to the `parameters`
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blocks are also added to the front of the arguments list, using the names
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provided in the signature.
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`parameters` blocks also provide another fun bit of functionality that makes
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code within them more concise, within a `parameters` block, the parameters are
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implicitly passed as arguments to calls to functions in the same block.
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```idris
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parameters (cs : Changes)
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```
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Calculate the happiness change for a given person in a seating arrangement, use
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`finS` and `unfinS` to get the indexes of the parties seated to either side of
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us, and look them up in our map, adding the amount of change described by them
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together.
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Notice how `cs` appears neither in the arguments list, nor the type signature,
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yet we can still refer to it as if it was included at the start of both.
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```idris
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happinessFor :
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(arrangement : Vect (length (keys cs.change_map)) Name)
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-> (idx : Fin (length (keys cs.change_map)))
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-> Happiness
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happinessFor arrangement idx =
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let name = idx `index` arrangement
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in case name `lookupPrecise` cs.change_map of
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Nothing => 0
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Just changes =>
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let name_right = (finS idx) `index` arrangement
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change_right =
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fromMaybe 0 . map (.amount) . find ((== name_right) . (.other)) $
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changes
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name_left = (unfinS idx) `index` arrangement
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change_left =
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fromMaybe 0 . map (.amount) . find ((== name_left) . (.other)) $
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changes
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in change_right + change_left
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```
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Calculate the overall happiness change for a given arrangement by mapping our
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`happinessFor` function over a list of all possible indexes to the `arrangement`
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vect, and summing the results.
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Notice how the `cs` parameter is implicitly passed to `happinessFor`, as we are
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inside the same `parameters` block as it.
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```idris
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happinessChange :
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(arrangement : Vect (length (keys cs.change_map)) Name)
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-> Happiness
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happinessChange arrangement =
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let idxes = List.allFins (length (keys cs.change_map))
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changes = map (happinessFor arrangement) idxes
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in sum changes
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```
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Find the arrangement with the maximum total change in happiness by mapping
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`happinessChange` over a list of all the possible permutations of our seed
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arrangement described by `names`, and using `maxBy` to identify the largest
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positive change in overall happiness.
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```idris
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maxHappiness : Has (Except String) fs =>
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Eff fs (Happiness, Vect (length (keys cs.change_map)) Name)
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maxHappiness =
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let arrangements = permutations cs.names
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changes = map happinessChange arrangements
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pairs = zip changes arrangements
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in case pairs of
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[] => throw "No arrangements"
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(x :: xs) => pure $ maxBy (compare `on` fst) x xs
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```
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## Part Functions
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### Part 1
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Parse our input and feed it into our `maxHappiness` function.
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Notice how, since we are outside the `parameters` block, we have to provide the
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`cs` argument to `maxHappiness` explicitly.
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```idris
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part1 : Eff (PartEff String) (Happiness, ())
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part1 = do
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input <- map lines $ askAt "input"
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changes <- parseChanges input
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(max, arrangement) <- maxHappiness changes
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pure (max, ())
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```
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```idris hide
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public export
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day13 : Day
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day13 = First 13 part1
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```
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## References
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[^1]: <https://idris2.readthedocs.io/en/latest/tutorial/modules.html#parameterised-blocks-parameters-blocks>
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