RailwayData @ 69dad367eda95eab908a8af86bf3fa5ce4ea5d56 UserData @ 10ef0a2b0eaefbe95155755d51eed0ff34388eec DataProcessing @ 6c13cfbfa3863439a086d7b08522d19078004814 Start: Wed Jun 19 22:25:30 2024 [0.0] Making list of travelers. [0.0] Reading region, country, and continent descriptions. [0.0] Reading systems list in /fast/home/terescoj/travelmapping/RailwayData/systems.csv.......................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................! [0.1] Finding all .wpt files. 5603 files found. [0.3] Reading waypoints for all routes. argtaold argtaor argbs argmit argroca argsar argsm argtad argurq argsub argmetmen argsubp argtc ausnswtl ausqrt austwa ausvln ausasr ausmtm ausqrc ausst austto aussm ausat ausbt auscm ausgclr ausnlr ausslr ausyt autsk autso autss autsst autst autsv autsw autus autuw autstgm autstg autsti autstl autstw belic bell belrsa belrsb belrsc belrsg belrsl belbm belcm belat belbt belgt belkt bgrsm bgrst bolmtc braefc braefvm braet brasv bratmsp brametba brambh bramdf bramfor brametrec brametrio brametsp bratu brabst bracbtujp bracbtumac bracbtunat braemtu bramforvlt bravltrec brametter bravltrio braair bratc canvia canexo cango cankrc canonr cantsh cantst canwce canmvrd canstm canttc canct canets canion canot canrem canair canedmsc cantsc cheags chebes chebss chechs chefrrer chelx chesgs cheshs chesob chesos chetirc chevdrer chezhs chezss chelm chebet chebst cheget chezht chlefer chlefep chlefes chlefeu chlms colmm colmmt czeduk czedukt czeem czeep czeidol czeiredo czevmjk czemp czetb czetl czetml czetol czetos czetpl czetp deubs deubss deufrs deuhbs deudds deuhhs deuhs deukas deuls deumds deums deuns deurms deurns deuros deurrs deuss deuulrs deubu deubisb deucc deufu deuhhu deuhsb deuksrt deumu deunu deurssb deurru deusb deusu deuws deuat deubt deubrbt deubst deuhbt deuct deuctt deudat deudet deuddt deueft deuft deufft deufrt deugt deugrt deugtht deuhbst deuhalt deujt deukat deukst deult deumdt deumzt deumt deunmbt deundht deunt deuplt deurnt deurrt deurot deusnt deuswat deuult deuwut deuzt deuddb deunwh dnkks dnkkm domopret ecumq ecutc espca espcc espcm espcma espcmu espcsa espcs espcv espcz espet espfs esprab esprad esprc esprf espsfm espbm espmb espmvbl espmm espmma espmp espms espmv espetb espmg espmlm espta esptb esptbc esptmu espts esptt esptv esptz eures euret eurapm eurf eurhr fracp frahdfterk frahdfterc frahdfterp franaqterd franaqterf franaqterl frarer fratra frattu frallm fralym framam frapm frarm fratm fraant fraaut frabet frabrt frabt fracft fract fradt fragt fraidft frallt fralht fralmt fralyt framat framot framut franat franit fraot fraret frarot fraset frast fratot fratt fravt gbncs gbngc gbngr gbngx gbnht gbnhx gbnld gbnsx gbnvt gbnxc gbnaw gbncc gbnch gbnem gbngn gbngw gbnle gbnln gbnlo gbnme gbnnr gbnse gbnsn gbnsr gbnsw gbntl gbntp gbnwm gbnxr irlnir gbndlr gbngs gbnlu gbntwm gbnbt gbnet gbnlt gbnman gbnnet gbnss gbnwmm hkgmtr hkglr hkghkt hkgop hkgpt hrvzt hunbm hunbt imnimr indcmrl irlent irlie irlluas itafl itanf itanr itans itanv itagu itams itatfm itafc itagm itamm itanmitarm itatm itart itamt itant itatt jpnjrsks jpnjrc jpnjre jpnjrh jpnjrk jpnjrs jpnjrw jpnlexc jpnlexe jpnlexh jpnlexk jpnlexs jpnlexw jpntlxk jpntlxw jpn7star jpnrhku jpnrhsn jpnrkeo jpnrkhn jpnrkin jpnrkku jpnrksi jpnrmtu jpnrnki jpnrnnr jpnrodk jpnrsbu jpnrshd jpnrsot jpnrtbu jpnrtku jpnvsgc jpnvsge jpnvsgh jpnvsgk jpnvsgw jpnvech jpnveiz jpnvetr jpnvhch jpnvhkr jpnvicb jpnviyo jpnvizh jpnvkmm jpnvknn jpnvkto jpnvktr jpnvohm jpnvsng jpnvsnn jpnvsny jpnvtch jpnvtke jpnvtos jpnmtfk jpnmtkb jpnmtky jpnmtng jpnmtos jpnmtse jpnmtsp jpnmtto jpnmtyk jpnmono jpnagt jpnagtk jpntmen jpntmfi jpntmhi jpntmhk jpntmkg jpntmkm jpntmky jpntmmy jpntmna jpntmok jpntmos jpntmsp jpntmta jpntmth jpntmto jpntmty jpntmut jpndmv jpnfuni jpntour luxcfl luxst mexchp mexciit mextm mexfs mexins mexsiteur mexstc mexstcm mexste nldic nldre nldrs nldam nldrm nldat nldht nldrt nldut norf norft norre norr norl norot norbb norto nzlatm nzlkr nzlwm panmp perml polksl polpkm polskam polskmb polskmt polskmw polwkd polwm polbt polct polet polgdt polgwt polgrt polkt pollt polot polpt polslt polszt poltt polwt polwrt roubm roubt sgpmrt sgplrt srbbt svkzdb svkedb svkedk svktez swesj swest swesl swess turib turim turit turif uryafe usaamtk usaarr usablfx usacfr usacndx usalirr usamarc usambtx usametx usamncw usanctc usanjtr usanmrx usartdx usascax usasepa usautax usavrex usatr usatrcx usaace usajpbx usasmart usanicd usamnrx usawes usanrtx usacmr usadcta usatex usatre usasdrx usabmsl usambta usapatco usasepta usanycs usapath usasir usawdw usawmat usamarta usamdt usarta usacta usalvm usalams usabart usaharthi usatu usablrl usanfta usadcsc usalynx usambtlr usamtlr usanjlr usaseplr usapitlr usatide usartalr usadart usamtahc usavmr usautat usalamlr usamts usartdz usamuni usasrt usavta usabsda usanorta usamax usastlr usaebart usaair usahart usahunhts usair usajta usakcsc usalvct usammm usarooist usasfcc usatsc usautas usawvuprt usarrm usast usaatlsc usadpm usaql usacc usaokcsc usadsc usamata usaelpsc usagal usamck usakensc usamkehop usapsc usawst usascm usassc nawpy [0.4] Sorting waypoints in Quadtree. [0.5] Finding unprocessed wpt files. 482 .wpt files in /fast/home/terescoj/travelmapping/RailwayData/data not processed, see unprocessedwpts.log. [0.5] Searching for near-miss points. [0.5] Near-miss point log and tm-master.nmp file. [0.5] Concurrent segment detection.......................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................! [0.6] Creating label hashes and checking route integrity. [0.6] Reading updates file. [0.6] Reading systemupdates file. [0.6] Processing traveler list files: Ib3kii aterrypenak BMACS001 aznate NocoRails 25or6to4 bejacob bartpetat bubaclex cebarb98 communityrailpartnerships cockroachking cl94 deathtopumpkins dough4872 drebbin37 ecoDuck7 duke87 griffith imgoph kjslaughter_rail londonpayg kurzov markkos1992 michih moabdave oyster mm oscar neroute2 panda80 rschen7754 scenicrailbritain shiggins si404 psvenk sounderbruce stoneyrails ssoworld testmta terescoj the_spui_ninja theFXexpert [0.6] Processed 43 traveler list files. [0.6] Clearing route & label hash tables. [0.6] Writing route and label logs. [0.6] Augmenting travelers for detected concurrent segments............................................! [0.7] Writing to concurrencies.log. [0.7] Computing stats..........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................! [0.7] Writing routedatastats.log. [0.7] Creating per-traveler stats logs and augmenting data structure............................................! [0.7] Writing stats csv files. [0.7] Reading datacheckfps.csv. [0.7] Marking datacheck false positives..............! [0.8] Found 13036 datacheck errors and matched 0 FP entries. [0.8] Writing log of unmatched datacheck FP entries. [0.8] Writing datacheck.log [0.8] Reading subgraph descriptions and checking for errors. [0.8] Start writing database file TravelMappingRail-2024-06-19@22:25:28.sql. [0.8] Setting up for graphs of highway data. [0.8] Creating unique names and vertices........! [0.9] Estimating failsafe edge array size: 138009 total active/preview segments, 22508 hidden vertices [0.9] Creating edges............................................................................................................! [0.9] Compressing collapsed edges......ERROR: segment name mismatch in HGEdge collapse constructor: edge1 named BLp,BLp,NSLn edge2 named NSLn ..! [1.0] Creating per-region vertex & edge sets. [1.0] Creating per-system vertex & edge sets. [1.0] Master graph construction complete. Destroying temporary variables. [1.0] Writing graph waypoint simplification log. [1.0] Writing master TM graph files. Simple graph has 73084 vertices, 75744 edges. Collapsed graph has 53672 vertices, 56332 edges. Traveled graph has 53705 vertices, 56365 edges. [1.0] Writing continent graphs. AFR (27,26) (27,26) (27,26) SA (2823,2815) (1845,1837) (1845,1837) [1.0] Writing multisystem graphs. RoundelRail (549,626) (505,582) (505,582) OCE (3286,3383) (2201,2298) (2201,2298) MTA (926,969) (791,834) (791,834) ASI (11837,12291) (9875,10329) (9875,10329) NA (15218,15348) (6892,7022) (6896,7026) EUR (39893,41881) (32832,34820) (32861,34849) NYC (1262,1314) (1016,1068) (1016,1068) NJ (346,349) (240,243) (240,243) SEPTA (532,538) (505,511) (505,511) Philly (553,559) (519,525) (519,525) DCArea (277,288) (183,194) (183,194) Boston (429,442) (284,297) (284,297) NWCor (2653,2740) (2065,2152) (2065,2152) Chicago (631,635) (423,427) (423,427) LAMet (170,171) (107,108) (107,108) LosAngeles (399,403) (186,190) (186,190) RTA (74,73) (53,52) (53,52) SanFran (319,318) (255,254) (255,254) Montreal (105,105) (75,75) (75,75) Toronto (470,500) (401,431) (401,431) Amsterdam (251,282) (236,267) (236,267) Antwerp (287,309) (257,279) (257,279) Barcelona (259,289) (248,278) (248,278) MetroBarcelona (209,229) (199,219) (199,219) Basel (302,319) (272,289) (272,289) Berlin (894,962) (861,929) (861,929) Bern (239,244) (216,221) (216,221) Bilbao (105,105) (92,92) (92,92) BiTCity (142,147) (133,138) (133,138) Bodensee (393,402) (304,313) (304,313) Bremen (298,305) (252,259) (254,261) Brno (479,489) (387,397) (387,397) Brussels (580,651) (533,604) (533,604) Cadiz (37,36) (30,29) (30,29) Charleroi (162,165) (124,127) (124,127) Chemnitz (143,146) (122,125) (123,126) Dresden (363,385) (334,356) (335,357) Breisgau (180,183) (147,150) (148,151) Gdansk (222,236) (199,213) (199,213) Geneva (161,166) (131,136) (131,136) Genoa (99,101) (69,71) (69,71) Ghent (139,142) (123,126) (123,126) Graz (297,301) (231,235) (231,235) Hamburg (202,210) (181,189) (181,189) Hannover (342,349) (285,292) (285,292) Innsbruck (289,294) (229,234) (229,234) Karlsruhe (507,520) (464,477) (467,480) Kassel (186,190) (166,170) (166,170) Krakow (272,290) (245,263) (245,263) Lausanne (163,164) (127,128) (127,128) Liberec (313,313) (231,231) (231,231) Lille (95,99) (92,96) (92,96) Linz (171,172) (142,143) (142,143) Lyon (141,153) (139,151) (139,151) Madrid (438,506) (380,448) (380,448) Malaga (49,48) (41,40) (41,40) Marseille (60,63) (60,63) (60,63) Milan (618,696) (561,639) (561,639) LeipzigHalle (694,721) (632,659) (636,663) Magdeburg (190,192) (171,173) (173,175) Munich (442,470) (417,445) (419,447) MurciaAlicante (160,160) (133,133) (133,133) Naples (307,323) (261,277) (261,277) Nice (113,112) (92,91) (92,91) Nuremburg (247,252) (218,223) (218,223) Ostrava (377,389) (306,318) (306,318) Paris (1180,1329) (1031,1180) (1031,1180) Poznan (272,288) (244,260) (244,260) Prague (1155,1258) (944,1047) (944,1047) Randstad (504,548) (484,528) (484,528) RhineMain (533,551) (491,509) (493,511) RhineNecker (568,585) (498,515) (501,518) Rome (457,471) (367,381) (367,381) Rostock (102,105) (89,92) (89,92) RheinRuhr (1688,1769) (1561,1642) (1568,1649) Sevilla (82,84) (58,60) (58,60) Silesia (743,772) (630,659) (630,659) Stuttgart (332,344) (302,314) (302,314) TERHdF (706,730) (459,483) (459,483) TERAqu (778,787) (360,369) (360,369) Toulouse (70,70) (69,69) (69,69) Turin (335,356) (307,328) (307,328) Ulm (125,124) (102,101) (102,101) Usti (681,697) (474,490) (474,490) Valencia (274,276) (224,226) (224,226) Metrovalencia (163,164) (154,155) (154,155) Vienna (743,859) (651,767) (651,767) Warsaw (371,410) (353,392) (353,392) Zaragoza (33,32) (30,29) (30,29) Zurich (655,713) (566,624) (566,624) Adelaide (133,132) (127,126) (127,126) Melbourne (1051,1132) (1039,1120) (1039,1120) SEQLD (200,200) (182,182) (182,182) Sydney (256,269) (239,252) (239,252) Sxx (7889,8066) (5969,6146) (5992,6169) [1.1] Writing country graphs. AUS (3135,3234) (2090,2189) (2090,2189) BRA (1238,1234) (697,693) (697,693) CAN (3203,3226) (1168,1191) (1169,1192) DEU (9082,9407) (8265,8590) (8293,8618) ESP (2736,2863) (2197,2324) (2197,2324) FRA (4251,4453) (3352,3554) (3352,3554) GBR (6128,6386) (4429,4687) (4430,4688) ITA (1881,2009) (1618,1746) (1618,1746) MEX (658,671) (345,358) (345,358) USA (11294,11385) (5328,5419) (5331,5422) [1.3] Writing region graphs. AB (218,214) (92,88) (92,88) AK (220,219) (30,29) (30,29) AL (61,59) (11,9) (11,9) AR (67,67) (22,22) (22,22) ARG (956,953) (722,719) (722,719) AUS-ACT (14,13) (14,13) (14,13) AUS-NSW (873,887) (445,459) (445,459) AUS-QLD (613,614) (243,244) (243,244) AUS-SA (133,132) (127,126) (127,126) AUS-VIC (1284,1368) (1142,1226) (1142,1226) AUS-WA (220,220) (121,121) (121,121) AUT (1781,1902) (1465,1586) (1465,1586) AZ (252,250) (90,88) (90,88) BC (624,619) (128,123) (128,123) BEL (1780,1934) (1420,1574) (1420,1574) BGR (203,212) (202,211) (202,211) BOL (35,34) (32,31) (32,31) BRA-AL (21,19) (15,13) (15,13) BRA-BA (29,28) (21,20) (21,20) BRA-CE (120,116) (63,59) (63,59) BRA-DF (29,28) (27,26) (27,26) BRA-ES (36,35) (10,9) (10,9) BRA-MA (103,102) (13,12) (13,12) BRA-MG (187,185) (44,42) (44,42) BRA-PA (29,28) (4,3) (4,3) BRA-PB (14,13) (13,12) (13,12) BRA-PE (53,54) (37,38) (37,38) BRA-PI (16,15) (11,10) (11,10) BRA-RJ (269,269) (198,198) (198,198) BRA-RN (33,32) (28,27) (28,27) BRA-RS (32,31) (23,22) (23,22) BRA-SP (269,279) (192,202) (192,202) CA (1588,1595) (768,775) (768,775) CHE (2112,2232) (1749,1869) (1749,1869) CHL (414,420) (265,271) (265,271) CO (400,386) (141,127) (141,127) COL (43,42) (35,34) (35,34) CT (136,134) (68,66) (68,66) CZE (3138,3296) (2479,2637) (2479,2637) DC (69,71) (63,65) (63,65) DE (11,10) (6,5) (6,5) DEU-BB (315,299) (299,283) (299,283) DEU-BE (739,807) (718,786) (718,786) DEU-BW (1546,1584) (1381,1419) (1385,1423) DEU-BY (912,941) (833,862) (835,864) DEU-HB (213,218) (196,201) (197,202) DEU-HE (677,695) (611,629) (613,631) DEU-HH (176,183) (157,164) (157,164) DEU-MV (143,147) (129,133) (129,133) DEU-NI (511,511) (439,439) (440,440) DEU-NW (1816,1896) (1647,1727) (1655,1735) DEU-RP (238,235) (208,205) (210,207) DEU-SH (24,18) (24,18) (24,18) DEU-SL (47,45) (45,43) (45,43) DEU-SN (1022,1056) (921,955) (925,959) DEU-ST (486,496) (452,462) (456,466) DEU-TH (276,276) (264,264) (264,264) DNK (148,158) (128,138) (128,138) DOM (37,36) (33,32) (33,32) ECU (58,56) (40,38) (40,38) ENG (4609,4851) (3516,3758) (3517,3759) ESP-AN (201,199) (159,157) (159,157) ESP-AR (33,32) (30,29) (30,29) ESP-CB (127,126) (87,86) (87,86) ESP-AS (285,289) (218,222) (218,222) ESP-CL (100,97) (66,63) (66,63) ESP-CM (6,4) (5,3) (5,3) ESP-CN (27,26) (27,26) (27,26) ESP-CT (639,691) (488,540) (488,540) ESP-GA (67,66) (53,52) (53,52) ESP-IB (64,64) (53,53) (53,53) ESP-MC (73,70) (59,56) (59,56) ESP-MD (434,501) (377,444) (377,444) ESP-PV (320,323) (276,279) (276,279) ESP-VC (373,375) (312,314) (312,314) FL (244,245) (132,133) (132,133) FRA-ARA (368,376) (335,343) (335,343) FRA-BFC (68,66) (68,66) (68,66) FRA-BRE (57,56) (57,56) (57,56) FRA-CVL (109,104) (95,90) (95,90) FRA-GES (186,179) (172,165) (172,165) FRA-HDF (780,808) (542,570) (542,570) FRA-IDF (1160,1311) (1011,1162) (1011,1162) FRA-NAQ (882,898) (482,498) (482,498) FRA-NOR (131,124) (112,105) (112,105) FRA-OCC (177,180) (168,171) (168,171) FRA-PAC (180,181) (159,160) (159,160) FRA-PDL (172,170) (170,168) (170,168) GA (166,164) (64,62) (64,62) GGY (3,2) (3,2) (3,2) HI (9,8) (9,8) (9,8) HKG (295,320) (278,303) (278,303) HRV (126,133) (125,132) (125,132) HUN (374,390) (370,386) (370,386) IA (67,65) (11,9) (11,9) ID (31,30) (3,2) (3,2) IL (787,789) (462,464) (463,465) IMN (108,104) (96,92) (96,92) IN (103,100) (31,28) (31,28) IND-TN (41,41) (41,41) (41,41) IRL (453,457) (233,237) (233,237) ITA-CAM (318,335) (272,289) (272,289) ITA-LAZ (457,471) (367,381) (367,381) ITA-LIG (103,103) (79,79) (79,79) ITA-LOM (653,731) (582,660) (582,660) ITA-PIE (347,366) (315,334) (315,334) ITA-TRE (5,3) (5,3) (5,3) KS (83,82) (9,8) (9,8) JPN (11013,11416) (9086,9489) (9086,9489) KY (55,53) (9,7) (9,7) LA (161,159) (113,111) (113,111) LIE (5,4) (5,4) (5,4) LUX (124,124) (94,94) (94,94) MA (477,490) (289,302) (289,302) MB (290,289) (94,93) (94,93) MD (220,215) (125,120) (125,120) ME (19,19) (8,8) (8,8) MEX-CAM (43,42) (10,9) (10,9) MEX-CHIH (130,129) (19,18) (19,18) MEX-CHIS (7,6) (2,1) (2,1) MEX-DF (220,237) (177,194) (177,194) MEX-EMEX (30,25) (24,19) (24,19) MEX-JAL (49,49) (45,45) (45,45) MEX-NL (43,43) (38,38) (38,38) MEX-OAX (32,31) (7,6) (7,6) MEX-QROO (16,15) (7,6) (7,6) MEX-SIN (30,29) (7,6) (7,6) MEX-TAB (13,12) (5,4) (5,4) MEX-VER (27,26) (5,4) (5,4) MEX-YUC (28,27) (9,8) (9,8) MI (143,141) (56,54) (56,54) MN (150,147) (58,55) (58,55) MO (213,212) (66,65) (66,65) MS (96,94) (18,16) (18,16) MT (178,175) (19,16) (19,16) NB (56,55) (11,10) (11,10) NC (167,166) (65,64) (65,64) ND (70,69) (9,8) (9,8) NE (68,67) (7,6) (7,6) NH (16,14) (8,6) (8,6) NIR (111,109) (66,64) (66,64) NJ (368,373) (254,259) (255,260) NL (59,58) (17,16) (17,16) NLD (1074,1150) (934,1010) (934,1010) NM (167,160) (41,34) (41,34) NOR (884,901) (478,495) (478,495) NS (51,50) (5,4) (5,4) NV (171,165) (26,20) (26,20) NY (1059,1103) (798,842) (798,842) NZL (142,141) (102,101) (102,101) OH (172,170) (84,82) (84,82) OK (59,59) (29,29) (29,29) ON (1175,1202) (552,579) (552,579) OR (295,295) (162,162) (163,163) PA (797,804) (587,594) (587,594) PAN (39,38) (31,30) (31,30) PER (42,40) (31,29) (31,29) PR (16,15) (16,15) (16,15) POL (2619,2775) (2394,2550) (2394,2550) PRY (2,1) (2,1) (2,1) QC (623,622) (260,259) (261,260) RI (22,21) (9,8) (9,8) ROU (340,367) (331,358) (331,358) SC (111,108) (17,14) (17,14) SCT (891,912) (492,513) (492,513) SD (11,10) (3,2) (3,2) SGP (183,210) (179,206) (179,206) SK (111,109) (18,16) (18,16) SRB (89,92) (85,88) (85,88) SVK (227,233) (195,201) (195,201) SWE (313,323) (271,281) (271,281) TN (62,58) (28,24) (28,24) TUR (305,304) (291,290) (291,290) TX (596,595) (248,247) (248,247) URY (36,35) (22,21) (22,21) UT (241,237) (89,85) (89,85) VA (265,267) (96,98) (96,98) VT (89,87) (20,18) (20,18) WA (358,352) (92,86) (92,86) WI (96,94) (45,43) (45,43) WLS (528,514) (366,352) (366,352) WV (121,117) (23,19) (23,19) YT (9,8) (4,3) (4,3) ! [1.7] Clearing HighwayGraph contents from memory. [1.7] Pause writing database file TravelMappingRail-2024-06-19@22:25:28.sql. [1.7] Resume writing database file TravelMappingRail-2024-06-19@22:25:28.sql. [1.7] Processed 646 highway systems. Processed 5121 routes with a total of 143130 points and 138009 segments. [1.7] WaypointQuadtree contains 6821 total nodes. [1.7] Computing waypoint colocation stats. Waypoint colocation counts: 43054 are each occupied by 1 waypoints. 15079 are each occupied by 2 waypoints. 6722 are each occupied by 3 waypoints. 3341 are each occupied by 4 waypoints. 1666 are each occupied by 5 waypoints. 974 are each occupied by 6 waypoints. 708 are each occupied by 7 waypoints. 473 are each occupied by 8 waypoints. 271 are each occupied by 9 waypoints. 146 are each occupied by 10 waypoints. 138 are each occupied by 11 waypoints. 98 are each occupied by 12 waypoints. 121 are each occupied by 13 waypoints. 60 are each occupied by 14 waypoints. 53 are each occupied by 15 waypoints. 49 are each occupied by 16 waypoints. 31 are each occupied by 17 waypoints. 9 are each occupied by 18 waypoints. 10 are each occupied by 19 waypoints. 10 are each occupied by 20 waypoints. 10 are each occupied by 21 waypoints. 11 are each occupied by 22 waypoints. 6 are each occupied by 23 waypoints. 14 are each occupied by 24 waypoints. 4 are each occupied by 25 waypoints. 6 are each occupied by 26 waypoints. 0 are each occupied by 27 waypoints. 2 are each occupied by 28 waypoints. 3 are each occupied by 29 waypoints. 6 are each occupied by 30 waypoints. 1 are each occupied by 31 waypoints. 2 are each occupied by 32 waypoints. 1 are each occupied by 33 waypoints. 2 are each occupied by 34 waypoints. 0 are each occupied by 35 waypoints. 2 are each occupied by 36 waypoints. 1 are each occupied by 37 waypoints. Unique locations: 73084 Finish: Wed Jun 19 22:25:31 2024 Total run time: [1.8]