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37165b60fd
...
78b8881016
7 changed files with 0 additions and 402 deletions
3
.gitignore
vendored
3
.gitignore
vendored
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@ -1,3 +0,0 @@
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__pycache__
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.direnv
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venv
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@ -1,33 +0,0 @@
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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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@ -1,219 +0,0 @@
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seeds: 2041142901 113138307 302673608 467797997 1787644422 208119536 143576771 99841043 4088720102 111819874 946418697 13450451 3459931852 262303791 2913410855 533641609 2178733435 26814354 1058342395 175406592
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seed-to-soil map:
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1270068015 1235603193 242614277
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13415696 1478217470 21049126
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825250550 1160341941 75261252
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3786189027 1971702238 242038712
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3191605340 3433644052 172752250
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2389904665 3088515862 345128190
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0 1499266596 13415696
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1197451933 0 72616082
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2139929050 1721726623 249975615
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900511802 222541761 147014452
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1047526254 72616082 149925679
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34464822 980591812 179750129
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2735032855 2631943377 456572485
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3364357590 3606396302 421831437
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214214951 369556213 611035599
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1721726623 2213740950 418202427
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soil-to-fertilizer map:
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226793587 358613369 356867344
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0 1838890301 226793587
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2741010192 0 358613369
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2257843811 715480713 173982825
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3099623561 1264222741 3082010
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1810570233 2912833547 326150077
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4038242924 3815312886 256724372
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2431826636 3268919687 279247493
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866869902 1671637223 167253078
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3102705571 889463538 374759203
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1615333950 2646894858 125679350
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2136720310 1550513722 121123501
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3477464774 2772574208 140259339
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1034122980 2065683888 581210970
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2711074129 3238983624 29936063
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583660931 1267304751 283208971
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1741013300 3548167180 69556933
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3815312886 4072037258 222930038
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fertilizer-to-water map:
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2197389106 1911800263 305927673
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3117278994 244526473 20512291
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2957263700 4069704360 136102838
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1536592951 2749121858 245216219
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3093366538 840656765 23912456
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815267737 2718368501 30753357
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3137791285 3392529258 82147206
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3770129899 390297301 198889495
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2168252150 2217727936 29136956
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770420674 2367771416 44847063
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3304122356 4205807198 44047643
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94626393 318562852 71734449
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2518697514 2262245627 10899396
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1967704281 265038764 53524088
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846021094 2994338077 264934624
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1215514867 3881882833 187821527
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1781809170 2556752263 100818318
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1882627488 1690877042 85076793
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208796777 631622731 209034034
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2583608714 3508227847 39876494
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519341481 1587040614 19652563
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599791964 104559149 139967324
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3430004623 1246915338 340125276
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1110955718 0 104559149
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2623485208 3548104341 333778492
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1403336394 3259272701 133256557
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0 2273145023 94626393
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2529596910 1857788459 54011804
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166360842 589186796 42435935
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3219938491 1606693177 84183865
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2165362153 3505337850 2889997
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2021228369 2412618479 72557496
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538994044 2657570581 60797920
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739759288 3474676464 30661386
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417830811 1154801218 92114120
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509944931 864569221 9396550
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2093785865 2485175975 71576288
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3969019394 873965771 280835447
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2503316779 2246864892 15380735
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3348169999 1775953835 81834624
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water-to-light map:
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3059617387 1101868951 93963271
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2772853640 2098642805 169363292
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193287974 683814429 1482323
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3780234682 1734000399 364642406
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194770297 193287974 490526455
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3550500423 902417243 199451708
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3466829263 2268006097 83671160
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3379471616 2976813583 87357647
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2283311570 2369871058 489542070
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3768145932 1195832222 12088750
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1202605712 3064171230 1080705858
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2942216932 2859413128 107440729
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3749952131 2351677257 18193801
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3049657661 2966853857 9959726
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902417243 1433811930 300188469
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3153580658 1207920972 225890958
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light-to-temperature map:
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1088722200 1345179841 10000894
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4202170199 3029124889 92797097
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3016749137 3130683307 53232372
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534766220 331633133 9297796
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190275035 286706851 44926282
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3069981509 1355180735 96127340
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1579189291 3913052943 379484702
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3918942962 3793498681 21754451
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262413801 377451173 88614642
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2452226090 2443004441 143726844
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1958673993 2586731285 188604820
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2595952934 3815253132 97799811
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882433672 754981589 206288528
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608195463 3121921986 8761321
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393888178 145828809 140878042
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3166108849 1530740045 97835767
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351028443 139489318 6339491
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3410232629 961270117 222147493
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2449796439 4292537645 2429651
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2401067597 1890048598 48728842
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3263944616 2376148398 66856043
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3330800659 1451308075 79431970
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3632380122 2019388074 205952206
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1548873457 1323582243 21597598
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2693752745 2225340280 142089882
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357367934 340930929 36520244
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0 493278299 50785717
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768194739 645497224 68742488
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2876584504 1183417610 140164633
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235201317 466065815 27212484
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1570471055 2367430162 8718236
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2147278813 2775336105 253788784
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874238988 3335153634 8194684
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2835842627 714239712 40741877
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3838332328 1938777440 80610634
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50785717 0 139489318
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616956784 3183915679 151237955
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836937227 608195463 37301761
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1098723094 3343348318 450150363
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3940697413 1628575812 261472786
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temperature-to-humidity map:
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3865679795 3411240257 137388137
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0 569718370 128927628
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2284256983 1093255418 349419361
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2189606444 2745948834 16886013
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3861728218 3796217004 3951577
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700036088 2134161201 67667679
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2639129496 1078899666 14355752
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4003067932 4146768977 27598493
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569558723 2311178479 130477365
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4125126694 3887925067 11822916
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1884679865 1442674779 129657290
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2633676344 1572332069 5453152
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862461784 1577785221 531688422
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4030666425 4120171499 26597478
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195554894 115268399 39538402
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235093296 235252943 334465427
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2132287170 698645998 57319274
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4158735055 3550090086 136232241
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2206492457 157488417 77764526
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3562496130 3899747983 220423516
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2653485248 2201828880 109349599
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2014337155 154806801 2681616
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1580787383 2536413861 97415145
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3453031511 3880534101 7390966
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1394150206 2633829006 45492562
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4057263903 3686322327 7821024
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4157273363 3548628394 1461692
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3460422477 3694143351 102073653
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4136949610 3800168581 20323753
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1678202528 872422329 206477337
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1556099825 2109473643 24687558
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128927628 2679321568 66627266
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2017018771 0 115268399
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4065084927 3820492334 60041767
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3411240257 4253176042 41791254
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767703767 2441655844 94758017
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1439642768 755965272 116457057
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3782919646 4174367470 78808572
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humidity-to-location map:
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347042062 4204488573 2962316
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877642375 2878291222 23518224
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3638916554 3484768713 5466055
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2890676240 3280663590 83564486
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201731623 3228655138 52008452
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1692198890 1946017811 25211210
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1717410100 1270737209 92827656
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3598929376 3630765534 39987178
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2226479211 1578430526 262844314
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687169155 3670752712 117494406
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3884728324 1515480569 62949957
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3494186405 1841274840 104742971
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2753482998 2630924017 120642845
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572458731 2235388494 114710424
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3947678281 3490234768 140530766
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3433348031 3167816764 60838374
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350004378 2406580589 222454353
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804663561 1442501755 72978814
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4132461733 2901809446 35781203
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4088209047 2937590649 38937925
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1441554453 2350098918 56481671
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3644382609 201731623 240345715
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2489323525 1971229021 264159473
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2974240726 3086380958 81435806
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4127146972 3364228076 5314761
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901160599 4207450889 87516407
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988677006 442077338 350976352
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1498036124 3369542837 115225876
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1810237756 3788247118 416241455
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1613262000 1363564865 78936890
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253740075 2993078971 93301987
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3055676532 894954785 375782424
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1339653358 793053690 101901095
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2874125843 2976528574 16550397
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3431458956 2629034942 1889075
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4168242936 2751566862 126724360
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@ -1,85 +0,0 @@
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import math
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seeds = []
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mappings = {}
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with open("input.txt", "r") as f:
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current_map = None
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for line in f:
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line = line.strip()
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if line == "":
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continue
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elif line.startswith("seeds:"):
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seeds = list(map(int, line.removeprefix("seeds: ").split(" ")))
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elif line.endswith(" map:"):
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x, _, y = line.removesuffix(" map:").split("-")
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current_map = (x, y)
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mappings[x] = {"next": y, "maps": []}
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else:
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dest_start, src_start, length = list(map(int, line.split(" ")))
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mappings[current_map[0]]["maps"].append((dest_start, src_start, length))
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locations = []
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for seed in seeds:
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current_type = "seed"
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current_number = seed
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while current_type != "location":
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mapping = mappings[current_type]
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found_dest = None
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for dest_start, src_start, length in mapping["maps"]:
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if current_number in range(src_start, src_start + length):
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found_dest = dest_start + (current_number - src_start)
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break
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if found_dest == None:
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found_dest = current_number
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current_type = mapping["next"]
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current_number = found_dest
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locations.append(current_number)
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print("part1", min(locations))
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def partition(lst, size):
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for i in range(0, len(lst) // size):
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yield lst[i::size]
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# current_type = "seed"
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# ranges = []
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lowest = math.inf
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first_seed = None
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for seed in seeds:
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if first_seed == None:
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first_seed = seed
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continue
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second_seed = seed
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print("Lezgo", first_seed, second_seed)
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# ranges.append((first_seed, first_seed + second_seed))
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for seed in range(first_seed, first_seed + second_seed):
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# print((seed - first_seed) / second_seed * 100)
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current_type = "seed"
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current_number = seed
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while current_type != "location":
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mapping = mappings[current_type]
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found_dest = None
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for dest_start, src_start, length in mapping["maps"]:
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if current_number in range(src_start, src_start + length):
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found_dest = dest_start + (current_number - src_start)
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break
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if found_dest == None:
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found_dest = current_number
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current_type = mapping["next"]
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current_number = found_dest
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if current_number < lowest:
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lowest = current_number
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first_seed = None
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print("part2", lowest)
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@ -1,2 +0,0 @@
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Time: 7 15 30
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Distance: 9 40 200
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@ -1,2 +0,0 @@
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Time: 46 68 98 66
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Distance: 358 1054 1807 1080
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@ -1,58 +0,0 @@
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import tqdm
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import re
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input = "input.txt"
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times = []
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||||||
distances = []
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||||||
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||||||
with open(input, "r") as f:
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||||||
for line in f:
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||||||
line = line.strip()
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|
||||||
if line.startswith("Time"):
|
|
||||||
times = map(int, re.split("\\s+", line)[1:])
|
|
||||||
else:
|
|
||||||
distances = map(int, re.split("\\s+", line)[1:])
|
|
||||||
|
|
||||||
races = []
|
|
||||||
|
|
||||||
for time, distance in zip(times, distances):
|
|
||||||
races.append((time, distance))
|
|
||||||
|
|
||||||
part1 = 1
|
|
||||||
for time, record_distance in races:
|
|
||||||
record_beaten_times = 0
|
|
||||||
for time_held in range(time):
|
|
||||||
time_left = time - time_held
|
|
||||||
speed = time_held
|
|
||||||
|
|
||||||
distance = speed * time_left
|
|
||||||
|
|
||||||
if distance > record_distance:
|
|
||||||
record_beaten_times += 1
|
|
||||||
part1 *= record_beaten_times
|
|
||||||
|
|
||||||
print("part1", part1)
|
|
||||||
|
|
||||||
time = 0
|
|
||||||
record_distance = 0
|
|
||||||
|
|
||||||
with open(input, "r") as f:
|
|
||||||
for line in f:
|
|
||||||
line = line.strip()
|
|
||||||
if line.startswith("Time"):
|
|
||||||
time = int("".join(re.split("\\s+", line)[1:]))
|
|
||||||
else:
|
|
||||||
record_distance = int("".join(re.split("\\s+", line)[1:]))
|
|
||||||
|
|
||||||
print(time)
|
|
||||||
part2 = 0
|
|
||||||
for time_held in tqdm.tqdm(range(time)):
|
|
||||||
time_left = time - time_held
|
|
||||||
speed = time_held
|
|
||||||
|
|
||||||
distance = speed * time_left
|
|
||||||
|
|
||||||
if distance > record_distance:
|
|
||||||
part2 += 1
|
|
||||||
print("part2", part2)
|
|
||||||
Loading…
Reference in a new issue