RailwayData @ 87b0c6831fab496d2c8fd296969c895fe44136f9 UserData @ 378836f7fa25b29d3f362c24697d292d21008ff9 DataProcessing @ 37c5ee3c2fda58c33a7ce17994193c8db74ce114 Start: Thu Sep 19 21:36:24 2024 [0.0] Making list of travelers. [0.0] Reading listfileinfo.csv. [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. 6183 files found. [0.1] Reading waypoints for all routes. ared 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 bihst 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 chncrh chngdprd chngdgzfm chngdszm 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 espave 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 fratgv fracp frahdfterk frahdfterc frahdfterp franaqterd franaqterf franaqterl frarer fratra frattu frallm fralym framam frapm frarm fratm fraant fraavt 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 grcpa grcpp grcpt grcma grcmt grcta hkgmtr hkglr hkghkt hkgop hkgpt hrvzt hunbm hunbt idnkrlc idnmrtj idnlrtj idnlrtjb imnimr indcmrl inddmrc irlent irlie irlluas itafl itanf itanr itans itanv itabafm itabfm itagu itams itatfm itafc itabm itacm itagm itamm itanm itarm itatm itabat itact itaft itamet itamt itant itaot itapat itapt itart itast itatt itavt itapm itavpm 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 korktx korsrt korsms luxcfl luxst macmlm mexchp mexciit mextm mexfs mexins mexsiteur mexstc mexstcm mexste mysktmk myserl mysmrt mysklm myslrt 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 prtlu prtpu prtlm prtpm prtle prtmts prtpe prtse roubm roubt sgpmrt sgplrt srbbt svkzdb svkedb svkedk svktez swegs swesj swest swesl swess thab turib turim turit turif twnhsr twntpm 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 usatmdart 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 usamata usadsc usaelpsc usagal usamck usakensc usamkehop usapsc usawst usascm usassc nawpy [0.3] Sorting waypoints in Quadtree. [0.3] Finding unprocessed wpt files. 492 .wpt files in /fast/home/terescoj/travelmapping/RailwayData/data not processed, see unprocessedwpts.log. [0.3] Searching for near-miss points. [0.3] Near-miss point log and tm-master.nmp file. [0.4] Concurrent segment detection..............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................! [0.5] Creating label hashes and checking route integrity. [0.5] Reading updates file. [0.5] Reading systemupdates file. [0.5] Processing traveler list files: 25or6to4 NocoRails BMACS001 Mislav210 M3200 Echostatic Ib3kii aterrypenak aznate bartpetat bejacob bubaclex chart33 cebarb98 chordtoll cl94 cockroachking communityrailpartnerships deathtopumpkins dough4872 drebbin37 duke87 ecoDuck7 epzik8 fwydriver405 griffith hoopitypoop hotdogPi imgoph kjslaughter_rail jjbers kevinmc londonpayg michih mm markkos1992 kurzov mojavenc moabdave neptun nagamasa neilbert oscar neroute2 oyster psvenk panda80 ran4sh radison rlee roadgeek99 roadgeek_adam scenicrailbritain sammi rschen7754 selectric shiggins si404 sounderbruce stoneyrails ssoworld tckma testmta theFXexpert terescoj the_spui_ninja the_spui_ninja_mini [0.5] Processed 67 traveler list files. [0.5] Clearing route & label hash tables. [0.5] Writing route and label logs. [0.5] Augmenting travelers for detected concurrent segments....................................................................! [0.5] Writing to concurrencies.log. [0.6] Computing stats...................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................! [0.6] Writing routedatastats.log. [0.6] Creating per-traveler stats logs and augmenting data structure....................................................................! [0.6] Writing stats csv files. [0.6] Reading datacheckfps.csv. [0.6] Marking datacheck false positives...............! [0.7] Found 14115 datacheck errors and matched 0 FP entries. [0.7] Writing log of unmatched datacheck FP entries. [0.7] Writing datacheck.log [0.7] Reading subgraph descriptions and checking for errors. [0.7] Start writing database file TravelMappingRail-2024-09-19@21:36:23.sql. [0.7] Setting up for graphs of highway data. [0.7] Creating unique names and vertices.........! [0.8] Estimating failsafe edge array size: 156417 total active/preview segments, 30010 hidden vertices [0.8] Creating edges.....................................................................................................................! [0.9] Compressing collapsed edges.......ERROR: segment name mismatch in HGEdge collapse constructor: edge1 named BLp,BLp,NSLn edge2 named NSLn ..! [0.9] Creating per-region vertex & edge sets. [0.9] Creating per-system vertex & edge sets. [0.9] Master graph construction complete. Destroying temporary variables. [0.9] Writing graph waypoint simplification log. [0.9] Writing master TM graph files. Simple graph has 84544 vertices, 87534 edges. Collapsed graph has 57810 vertices, 60800 edges. Traveled graph has 57844 vertices, 60834 edges. [0.9] Writing continent graphs. AFR (27,26) (27,26) (27,26) OCE (3311,3411) (2223,2323) (2223,2323) [0.9] Writing multisystem graphs. RoundelRail (557,633) (505,581) (505,581) MTA (926,969) (791,834) (791,834) SA (2823,2815) (1845,1837) (1845,1837) NA (15382,15510) (6908,7036) (6912,7040) ASI (19615,20293) (12429,13107) (12429,13107) EUR (43386,45479) (34378,36471) (34408,36501) 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 (469,499) (400,430) (400,430) 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) (305,314) 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) (132,137) 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) (465,478) Kassel (186,190) (166,170) (166,170) Krakow (273,290) (246,263) (246,263) 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 (143,155) (141,153) (141,153) Madrid (438,506) (385,453) (385,453) Malaga (49,48) (43,42) (43,42) Marseille (59,63) (59,63) (59,63) Milan (618,696) (562,640) (562,640) LeipzigHalle (694,721) (632,659) (636,663) Magdeburg (190,192) (171,173) (173,175) Munich (442,470) (417,445) (418,446) 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) Poznan (272,287) (244,259) (244,259) Paris (1195,1347) (1047,1199) (1048,1200) Prague (1155,1258) (944,1047) (944,1047) Randstad (504,548) (484,528) (484,528) RhineMain (533,551) (491,509) (492,510) RhineNecker (568,585) (498,515) (500,517) Rome (457,471) (367,381) (367,381) Rostock (102,105) (89,92) (89,92) RheinRuhr (1681,1760) (1554,1633) (1559,1638) Sevilla (81,82) (60,61) (60,61) Silesia (743,772) (630,659) (630,659) Stuttgart (332,344) (302,314) (302,314) TERHdF (706,730) (461,485) (461,485) TERAqu (777,786) (370,379) (370,379) Toulouse (70,70) (69,69) (69,69) Turin (335,356) (310,331) (310,331) Ulm (125,124) (102,101) (102,101) Usti (681,697) (474,490) (474,490) Valencia (304,307) (228,231) (228,231) Metrovalencia (163,164) (154,155) (154,155) Vienna (743,859) (651,767) (652,768) Warsaw (371,410) (353,392) (353,392) Zaragoza (37,36) (31,30) (31,30) Zurich (655,713) (566,624) (566,624) Adelaide (133,132) (127,126) (127,126) Melbourne (1052,1133) (1040,1121) (1040,1121) SEQLD (200,200) (182,182) (182,182) Sydney (280,296) (260,276) (260,276) Sxx (7887,8063) (5969,6145) (5988,6164) [1.1] Writing country graphs. AUS (3160,3262) (2112,2214) (2112,2214) BRA (1238,1234) (697,693) (697,693) CAN (3202,3225) (1167,1190) (1168,1191) CHN (4214,4336) (1307,1429) (1307,1429) DEU (9079,9401) (8262,8584) (8285,8607) ESP (3528,3677) (2260,2409) (2262,2411) FRA (5507,5770) (3567,3830) (3569,3832) GBR (6118,6367) (4405,4654) (4405,4654) IND (280,294) (280,294) (280,294) ITA (2301,2415) (1993,2107) (1993,2107) MEX (658,671) (345,358) (345,358) USA (11459,11548) (5345,5434) (5348,5437) [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) ARE (155,155) (71,71) (71,71) ARG (956,953) (722,719) (722,719) AUS-ACT (14,13) (14,13) (14,13) AUS-NSW (897,914) (466,483) (466,483) AUS-QLD (613,614) (243,244) (243,244) AUS-SA (133,132) (127,126) (127,126) AUS-VIC (1285,1369) (1143,1227) (1143,1227) AUS-WA (220,220) (121,121) (121,121) AUT (1781,1902) (1465,1586) (1466,1587) 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) BIH (28,27) (28,27) (28,27) 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 (1627,1633) (774,780) (774,780) CHE (2112,2232) (1749,1869) (1750,1870) CHL (414,420) (265,271) (265,271) CHN-AH (29,28) (6,5) (6,5) CHN-BJ (50,48) (4,2) (4,2) CHN-GD (1967,2053) (711,797) (711,797) CHN-GZ (113,112) (14,13) (14,13) CHN-HA (106,105) (11,10) (11,10) CHN-HB (61,60) (7,6) (7,6) CHN-HE (101,98) (17,14) (17,14) CHN-HN (151,150) (24,23) (24,23) CHN-JS (87,85) (12,10) (12,10) CHN-JX (119,118) (13,12) (13,12) CHN-SD (78,77) (8,7) (8,7) CHN-SH (30,29) (5,4) (5,4) CHN-TJ (22,22) (6,6) (6,6) CHN-YN (36,35) (5,4) (5,4) CHN-ZJ (115,114) (15,14) (15,14) 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) (1384,1422) DEU-BY (912,941) (833,862) (834,863) DEU-HB (213,218) (196,201) (197,202) DEU-HE (681,698) (615,632) (616,633) 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 (1809,1887) (1640,1718) (1646,1724) 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 (153,165) (132,144) (132,144) DOM (37,36) (33,32) (33,32) ECU (58,56) (40,38) (40,38) ENG (4612,4850) (3504,3742) (3504,3742) ESP-AN (313,313) (173,173) (175,175) ESP-AR (87,86) (34,33) (34,33) ESP-AS (294,299) (218,223) (218,223) ESP-CB (127,126) (87,86) (87,86) ESP-CL (247,242) (74,69) (74,69) ESP-CM (164,158) (17,11) (17,11) ESP-CN (27,26) (27,26) (27,26) ESP-CT (778,837) (500,559) (500,559) 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 (517,586) (390,459) (390,459) ESP-PV (320,323) (276,279) (276,279) ESP-VC (475,481) (324,330) (324,330) FL (244,245) (132,133) (132,133) FRA-ARA (528,543) (356,371) (357,372) FRA-BFC (176,176) (85,85) (85,85) FRA-BRE (211,208) (80,77) (80,77) FRA-CVL (160,158) (110,108) (110,108) FRA-GES (436,437) (212,213) (212,213) FRA-HDF (787,814) (549,576) (549,576) FRA-IDF (1212,1372) (1036,1196) (1037,1197) FRA-NAQ (915,935) (494,514) (494,514) FRA-NOR (171,166) (113,108) (113,108) FRA-OCC (310,313) (190,193) (190,193) FRA-PAC (333,334) (191,192) (191,192) FRA-PDL (312,314) (195,197) (195,197) GA (166,164) (64,62) (64,62) GGY (3,2) (3,2) (3,2) GRC (332,344) (245,257) (245,257) HI (9,8) (9,8) (9,8) HRV (126,133) (125,132) (125,132) HKG (583,612) (276,305) (276,305) HUN (374,390) (370,386) (370,386) IA (67,65) (11,9) (11,9) ID (31,30) (3,2) (3,2) IDN-JW (140,138) (131,129) (131,129) IL (787,789) (462,464) (463,465) IMN (108,104) (96,92) (96,92) IN (103,100) (31,28) (31,28) IND-DL (196,208) (196,208) (196,208) IND-HR (22,19) (22,19) (22,19) IND-TN (41,41) (41,41) (41,41) IND-UP (30,26) (30,26) (30,26) IRL (453,457) (233,237) (233,237) ITA-CAM (318,335) (272,289) (272,289) ITA-EMI (108,107) (86,85) (86,85) ITA-FRI (13,12) (13,12) (13,12) ITA-LAZ (457,471) (367,381) (367,381) ITA-LIG (103,103) (79,79) (79,79) ITA-LOM (691,766) (619,694) (619,694) ITA-PIE (355,375) (319,339) (319,339) ITA-PUG (45,45) (33,33) (33,33) ITA-SAR (24,22) (22,20) (22,20) ITA-SIC (71,67) (70,66) (70,66) ITA-TOS (44,41) (43,40) (43,40) ITA-TRE (5,3) (5,3) (5,3) ITA-UMB (7,6) (7,6) (7,6) ITA-VEN (64,62) (62,60) (62,60) KOR (2632,2730) (701,799) (701,799) JPN (11013,11416) (9086,9489) (9086,9489) KS (83,82) (9,8) (9,8) KY (55,53) (9,7) (9,7) LA (161,159) (113,111) (113,111) LIE (5,4) (5,4) (5,4) LUX (126,126) (95,95) (95,95) MA (477,490) (289,302) (289,302) MAC (23,22) (12,11) (12,11) MB (290,289) (94,93) (94,93) MCO (3,2) (3,2) (3,2) 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) MYS (254,271) (191,208) (191,208) NB (56,55) (11,10) (11,10) NC (167,166) (65,64) (65,64) ND (70,69) (9,8) (9,8) NE (77,76) (9,8) (9,8) 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 (1174,1201) (551,578) (551,578) 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) POL (2677,2838) (2450,2611) (2450,2611) PR (16,15) (16,15) (16,15) PRT (467,483) (441,457) (441,457) 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 (880,897) (484,501) (484,501) SD (11,10) (3,2) (3,2) SGP (191,218) (186,213) (186,213) SK (111,109) (18,16) (18,16) SRB (89,92) (85,88) (85,88) SVK (227,233) (195,201) (195,201) SWE (460,481) (417,438) (418,439) THA (431,431) (185,185) (185,185) TN (62,58) (28,24) (28,24) TUR (305,304) (291,290) (291,290) TWN (562,568) (180,186) (180,186) TX (603,602) (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 (435,429) (96,90) (96,90) WI (96,94) (45,43) (45,43) WLS (526,511) (362,347) (362,347) WV (154,149) (28,23) (28,23) YT (9,8) (4,3) (4,3) [1.8] Pause writing database file TravelMappingRail-2024-09-19@21:36:23.sql. ! [1.8] Clearing HighwayGraph contents from memory. [1.8] Resume writing database file TravelMappingRail-2024-09-19@21:36:23.sql. [1.8] Processed 701 highway systems. Processed 5691 routes with a total of 162108 points and 156417 segments. [1.8] WaypointQuadtree contains 7849 total nodes. [1.8] Computing waypoint colocation stats. Waypoint colocation counts: 51662 are each occupied by 1 waypoints. 16748 are each occupied by 2 waypoints. 7218 are each occupied by 3 waypoints. 3542 are each occupied by 4 waypoints. 1809 are each occupied by 5 waypoints. 1045 are each occupied by 6 waypoints. 726 are each occupied by 7 waypoints. 487 are each occupied by 8 waypoints. 313 are each occupied by 9 waypoints. 174 are each occupied by 10 waypoints. 164 are each occupied by 11 waypoints. 120 are each occupied by 12 waypoints. 130 are each occupied by 13 waypoints. 75 are each occupied by 14 waypoints. 74 are each occupied by 15 waypoints. 52 are each occupied by 16 waypoints. 58 are each occupied by 17 waypoints. 29 are each occupied by 18 waypoints. 13 are each occupied by 19 waypoints. 22 are each occupied by 20 waypoints. 7 are each occupied by 21 waypoints. 18 are each occupied by 22 waypoints. 10 are each occupied by 23 waypoints. 7 are each occupied by 24 waypoints. 5 are each occupied by 25 waypoints. 7 are each occupied by 26 waypoints. 1 are each occupied by 27 waypoints. 3 are each occupied by 28 waypoints. 6 are each occupied by 29 waypoints. 6 are each occupied by 30 waypoints. 2 are each occupied by 31 waypoints. 2 are each occupied by 32 waypoints. 1 are each occupied by 33 waypoints. 4 are each occupied by 34 waypoints. 1 are each occupied by 35 waypoints. 2 are each occupied by 36 waypoints. 0 are each occupied by 37 waypoints. 0 are each occupied by 38 waypoints. 0 are each occupied by 39 waypoints. 0 are each occupied by 40 waypoints. 0 are each occupied by 41 waypoints. 1 are each occupied by 42 waypoints. Unique locations: 84544 Finish: Thu Sep 19 21:36:25 2024 Total run time: [1.8]