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‎build.gradle‎

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@@ -4,7 +4,7 @@ plugins {
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// project meta data
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group 'de.havox_design.aoc2023'
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version '0.4.0'
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version '0.4.1'
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// Switch to gradle "all" distribution.
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wrapper {

‎day05/README.md‎

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# Day 5: If You Give A Seed A Fertilizer
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You take the boat and find the gardener right where you were told he would be: managing a giant "garden" that looks
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more to you like a farm.
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"A water source? Island Island **is** the water source!" You point out that Snow Island isn't receiving any water.
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"Oh, we had to stop the water because we **ran out of sand** to [filter](https://en.wikipedia.org/wiki/Sand_filter) it
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with! Can't make snow with dirty water. Don't worry, I'm sure we'll get more sand soon; we only turned off the water a
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few days... weeks... oh no." His face sinks into a look of horrified realization.
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"I've been so busy making sure everyone here has food that I completely forgot to check why we stopped getting more
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sand! There's a ferry leaving soon that is headed over in that direction - it's much faster than your boat. Could you
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please go check it out?"
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You barely have time to agree to this request when he brings up another. "While you wait for the ferry, maybe you can
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help us with our **food production problem**. The latest Island Island [Almanac](https://en.wikipedia.org/wiki/Almanac)
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just arrived and we're having trouble making sense of it."
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The almanac (your puzzle input) lists all of the seeds that need to be planted. It also lists what type of soil to use
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with each kind of seed, what type of fertilizer to use with each kind of soil, what type of water to use with each kind
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of fertilizer, and so on. Every type of seed, soil, fertilizer and so on is identified with a number, but numbers are
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reused by each category - that is, soil 123 and fertilizer 123 aren't necessarily related to each other.
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For example:
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```
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seeds: 79 14 55 13
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seed-to-soil map:
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50 98 2
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52 50 48
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soil-to-fertilizer map:
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0 15 37
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37 52 2
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39 0 15
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fertilizer-to-water map:
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49 53 8
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0 11 42
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42 0 7
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57 7 4
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water-to-light map:
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88 18 7
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18 25 70
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light-to-temperature map:
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45 77 23
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81 45 19
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68 64 13
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temperature-to-humidity map:
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0 69 1
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1 0 69
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humidity-to-location map:
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60 56 37
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56 93 4
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```
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The almanac starts by listing which seeds need to be planted: seeds `79`, `14`, `55`, and `13`.
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The rest of the almanac contains a list of **maps** which describe how to convert numbers from a **source category**
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into numbers in a **destination category**. That is, the section that starts with `seed-to-soil map:` describes how to
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convert a **seed number** (the source) to a **soil number** (the destination). This lets the gardener and his team
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know which soil to use with which seeds, which water to use with which fertilizer, and so on.
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Rather than list every source number and its corresponding destination number one by one, the maps describe entire
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**ranges** of numbers that can be converted. Each line within a map contains three numbers: the **destination range
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start**, the **source range start**, and the **range length**.
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Consider again the example `seed-to-soil map:`
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```
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50 98 2
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52 50 48
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```
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The first line has a **destination range start** of `50`, a **source range start** of `98`, and a **range length** of
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`2`. This line means that the source range starts at `98` and contains two values: `98` and `99`. The destination range
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is the same length, but it starts at `50`, so its two values are `50` and `51`. With this information, you know that
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seed number `98` corresponds to soil number `50` and that seed number `99` corresponds to soil number `51`.
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The second line means that the source range starts at `50` and contains `48` values: `50`, `51`, ..., `96`, `97`. This
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corresponds to a destination range starting at `52` and also containing `48` values: `52`, `53`, ..., `98`, `99`. So,
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seed number `53` corresponds to soil number `55`.
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Any source numbers that **aren't mapped** correspond to the **same** destination number. So, seed number `10`
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corresponds to soil number `10`.
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So, the entire list of seed numbers and their corresponding soil numbers looks like this:
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```
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seed soil
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0 0
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1 1
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... ...
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48 48
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49 49
96+
50 52
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51 53
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... ...
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96 98
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97 99
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98 50
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99 51
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```
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With this map, you can look up the soil number required for each initial seed number:
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* Seed number `79` corresponds to soil number `81`.
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* Seed number `14` corresponds to soil number `14`.
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* Seed number `55` corresponds to soil number `57`.
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* Seed number `13` corresponds to soil number `13`.
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The gardener and his team want to get started as soon as possible, so they'd like to know the closest location that
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needs a seed. Using these maps, find **the lowest location number that corresponds to any of the initial seeds**. To
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do this, you'll need to convert each seed number through other categories until you can find its corresponding
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**location number**. In this example, the corresponding types are:
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* Seed `79`, soil `81`, fertilizer `81`, water `81`, light `74`, temperature `78`, humidity `78`, **location `82`**.
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* Seed `14`, soil `14`, fertilizer `53`, water `49`, light `42`, temperature `42`, humidity `43`, **location `43`**.
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* Seed `55`, soil `57`, fertilizer `57`, water `53`, light `46`, temperature `82`, humidity `82`, **location `86`**.
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* Seed `13`, soil `13`, fertilizer `52`, water `41`, light `34`, temperature `34`, humidity `35`, **location `35`**.
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So, the lowest location number in this example is **`35`**.
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**What is the lowest location number that corresponds to any of the initial seed numbers**?

‎day05/src/main/resources/day05.txt‎

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seeds: 629551616 310303897 265998072 58091853 3217788227 563748665 2286940694 820803307 1966060902 108698829 190045874 3206262 4045963015 223661537 1544688274 293696584 1038807941 31756878 1224711373 133647424
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seed-to-soil map:
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3809825462 2725979505 339457863
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3359244708 2085610478 450580754
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652041572 2536191232 189788273
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841829845 3346349446 343599367
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1408035723 73701258 732851393
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2140887116 3689948813 88205018
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0 3778153831 371129494
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2953980724 0 73701258
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3027681982 1754047752 331562726
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2229092134 1029159162 724888590
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1185429212 806552651 222606511
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371129494 3065437368 280912078
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soil-to-fertilizer map:
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201390752 0 263005475
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772560454 263005475 186665885
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3597849741 3228095269 216867970
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959226339 951560560 85171934
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2882237029 3813801625 34286208
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0 586356609 16090261
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1460387186 1189054013 136970257
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2511361703 2581174071 147006778
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201110502 1477157137 280250
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3582774663 3444963239 15075078
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2073881675 2245158204 30510333
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3127914126 3163440286 64654983
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1724767985 602446870 349113690
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1597357443 1036732494 127410542
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1044398273 1164143036 24910977
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635875205 449671360 136685249
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2916523237 2728180849 211390889
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1069309250 1854080268 391077936
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167223128 1820192894 33887374
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4168481019 2454687794 126486277
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3496254979 4048626015 86519684
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2454687794 4238293387 56673909
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2104392008 1648916365 171276529
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3814717711 3460038317 353763308
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464396227 1477437387 171478978
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2658368481 2939571738 223868548
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16090261 1326024270 151132867
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3393107291 4135145699 103147688
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3192569109 3848087833 200538182
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fertilizer-to-water map:
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357701033 441924316 54941059
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2047098412 1574732688 106451110
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2414997091 2961420861 217583761
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3647103220 3202843177 147888878
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1781607871 3397471081 265490541
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433955285 629676938 29320532
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3280739425 2494455782 366363795
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2818710889 1426835569 147897119
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1120892574 3179004622 23838555
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1539573533 3662961622 195295312
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3794992098 1820059317 63264836
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0 84223283 357701033
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1144731129 1702496991 117562326
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2153549522 2046878176 261447569
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593734757 726830618 239035306
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987137385 83279657 943626
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2966608008 0 83279657
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1734868845 3350732055 46739026
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1438972249 2860819577 100601284
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2632580852 2308325745 186130037
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1262293455 965865924 108845646
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412642092 1681183798 21313193
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472462518 1305563330 121272239
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988081011 496865375 132811563
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463275817 2037691475 9186701
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3049887665 1074711570 230851760
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832770063 1883324153 154367322
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1371139101 658997470 67833148
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water-to-light map:
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4062286509 3839153068 91029970
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1610728246 3827168971 11474903
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2753947407 2725849236 1101319735
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2525484879 1829977386 228462528
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657837215 1095779595 241604827
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1895347620 1337384422 492592964
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1425623249 4009599599 185104997
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2446068318 3930183038 79416561
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1894838426 3838643874 509194
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2389619503 896001044 56448815
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3855267142 2058439914 207019367
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1187459420 657837215 238163829
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1622203149 2467395620 172372577
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2387940584 952449859 1678919
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985523081 2265459281 201936339
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4153316479 954128778 141650817
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1794575726 4194704596 100262700
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899442042 2688664470 37184766
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936626808 2639768197 48896273
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light-to-temperature map:
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0 2682471120 43545350
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2829609407 2423668531 227914183
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3685065657 3821208881 65673550
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1319277847 0 33132672
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818263707 3091863377 5216721
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3144636417 670795080 1340457
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1352410519 895535914 570572224
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2709351136 1662268878 120258271
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115643652 2726016470 93054822
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455333494 1538206440 124062438
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3839611769 4030334543 30664857
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3750739207 4258515305 36451991
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2070721515 33132672 155555065
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3132740473 2067641423 5192544
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4147162986 3685065657 58311172
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4278703737 3743376829 16263559
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1070098598 2174489282 249179249
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716608392 2072833967 101655315
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43545350 1466108138 72098302
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3057523590 3016646494 75216883
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2700979566 887164344 8371570
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4205474158 4060999400 73229579
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2226276580 188687737 474702986
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1971879519 1968799427 98841996
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3931845119 4134228979 124286326
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579395932 2819071292 137212460
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3137933017 672135537 6703400
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1062694241 663390723 7404357
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3787191198 3886882431 52420571
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269061216 1782527149 186272278
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1031805835 2651582714 30888406
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823480428 678838937 208325407
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3870276626 3759640388 61568493
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4056131445 3939303002 91031541
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1922982743 3097080098 48896776
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208698474 2956283752 60362742
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temperature-to-humidity map:
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219529182 731674447 232727899
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2748076784 2771987989 46463882
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2514344851 4061235363 233731933
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0 1369964423 219529182
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452257081 362359049 21789881
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4243457964 2720478657 51509332
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3085663754 3109574959 64704581
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1639319644 384148930 347525517
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3150368335 3626166922 251414834
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1986845161 0 139120377
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1382707786 1339581093 30383330
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1413091116 1113352565 226228528
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2794540666 2818451871 291123088
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2125965538 338187591 24171458
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474046962 139120377 157229612
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2361125570 1100881680 12470885
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631276574 296349989 41837602
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3401783169 3428035243 198131679
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3989702261 3174279540 253755703
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2224646236 964402346 136479334
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2150136996 2299087215 74509240
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3806048654 3877581756 183653607
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3599914848 2514344851 206133806
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673114176 1589493605 709593610
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humidity-to-location map:
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4029426902 1202474782 191291587
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2764446301 708692227 493782555
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2188304413 3350514524 33021460
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3318755823 4213528230 67155117
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2000392671 620732246 87959981
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3754724301 3075811923 274702601
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3258228856 1393766369 60526967
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2088352652 4113576469 99951761
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363515622 1849258760 614077493
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1213242541 342257124 11129119
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1733046668 353386243 267346003
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1224371660 4280683347 14283949
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2577070088 2888435710 187376213
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4220718489 2832149614 56286096
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324294413 1810037551 39221209
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3385910940 2463336253 368813361
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977593115 3383535984 235649426
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1238655609 3619185410 494391059
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4277004585 324294413 17962711
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2221325873 1454293336 355744215

‎day05/src/test/kotlin/de/havox_design/aoc2023/day05/Day05Test.kt‎

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@JvmStatic
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private fun getDataForTestSolvePart1(): Stream<Arguments> =
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Stream.of(
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Arguments.of("part1sample1.txt", 0L)
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Arguments.of("part1sample.txt", 0L)
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)
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@JvmStatic

‎day05/src/test/resources/part1sample.txt‎

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seeds: 79 14 55 13
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seed-to-soil map:
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50 98 2
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52 50 48
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soil-to-fertilizer map:
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0 15 37
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37 52 2
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39 0 15
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fertilizer-to-water map:
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49 53 8
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0 11 42
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42 0 7
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57 7 4
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water-to-light map:
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88 18 7
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18 25 70
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light-to-temperature map:
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45 77 23
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81 45 19
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68 64 13
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temperature-to-humidity map:
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0 69 1
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1 0 69
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humidity-to-location map:
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60 56 37
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56 93 4

‎day05/src/test/resources/part1sample1.txt‎

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