R version 4.6.0 RC (2026-04-22 r89945 ucrt) -- "Because it was There" Copyright (C) 2026 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(reems) reems is an R wrapper for the EEMS spatial population genetics method. It also integrates the R plotting functions bundled with the original EEMS command-line utility. reems uses DarkOrange to Blue color scheme, with 'white' as the midpoint color. It combines two color schemes from the 'dichromat' package, which itself is based on a collection of color schemes for scientific data graphics: Light A and Bartlein PJ (2004). The End of the Rainbow? Color Schemes for Improved Data Graphics. EOS Transactions of the American Geophysical Union, 85(40), 385. See also http://geog.uoregon.edu/datagraphics/color_scales.htm > > test_check("reems") [Habitat::initialize] Loaded habitat points from D:\temp\2026_04_23_13_35_17_30548\RtmpqQU3Ud/data_path/in.outer Input habitat: POLYGON((-84.4328 42.7828,-84.4328 42.8308,-84.3848 42.8308,-84.3848 42.7828,-84.4328 42.7828)) [Habitat::initialize] Done. [Graph::initialize] Generate population grid and sample assignment Loaded sample coordinates from D:\temp\2026_04_23_13_35_17_30548\RtmpqQU3Ud/data_path/in.coord There are 16 observed demes (out of 81 demes) The population grid has 81 demes and 208 edges There are 16 samples assigned to 16 observed demes [Graph::initialize] Done. [Diffs::initialize] [Diffs::initialize] Done. Initialize EEMS random state [EEMS::initialize_state] EEMS starts with 19 qtiles and 29 mtiles [EEMS::initialize_state] Done. Input parameters: datapath = D:\temp\2026_04_23_13_35_17_30548\RtmpqQU3Ud/data_path/in mcmcpath = D:\temp\2026_04_23_13_35_17_30548\RtmpqQU3Ud/eems_out/example-chain1 prevpath = gridpath = distance = greatcircle diploid = 1 nIndiv = 16 nSites = 10000 nDemes = 96 seed = 1776945107 numMCMCIter = 2000 numBurnIter = 1000 numThinIter = 99 negBiSize = 10 negBiProb = 0.670000 qVoronoiPr = 0.250000 mrateShape = 0.000500 qrateShape = 0.002000 sigmaShape = 0.001000 qrateScale = 0.500000 mrateScale = 2.000000 sigmaScale = 1.000000 mSeedsProposalS2 = 0.010000 qSeedsProposalS2 = 0.100000 mEffctProposalS2 = 0.100000 qEffctProposalS2 = 0.001000 mrateMuProposalS2 = 0.010000 Initial log prior: 62.71 Initial log llike: 135.12 Iteration 1000 of 2000... Ending iteration 1100 with acceptance proportions: (50/64) = 78.12% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (5/83) = 6.02% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (32/68) = 47.06% for proposal type "qBirthDeath" (171/204) = 83.82% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (101/143) = 70.63% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (46/217) = 21.20% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (54/186) = 29.03% for proposal type "mBirthDeath" (0/135) = 0.00% for proposal type "degrees of freedom" and effective degrees of freedom = 16.00 number of qVoronoi tiles = 13 number of mVoronoi tiles = 31 Log prior = 37.80 Log llike = 289.42 Ending iteration 1200 with acceptance proportions: (54/70) = 77.14% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (6/92) = 6.52% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (37/75) = 49.33% for proposal type "qBirthDeath" (186/223) = 83.41% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (105/154) = 68.18% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (49/231) = 21.21% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (59/205) = 28.78% for proposal type "mBirthDeath" (1/150) = 0.67% for proposal type "degrees of freedom" and effective degrees of freedom = 16.08 number of qVoronoi tiles = 12 number of mVoronoi tiles = 32 Log prior = 28.74 Log llike = 308.17 Ending iteration 1300 with acceptance proportions: (58/76) = 76.32% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (7/102) = 6.86% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (44/83) = 53.01% for proposal type "qBirthDeath" (201/241) = 83.40% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (113/166) = 68.07% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (53/250) = 21.20% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (63/220) = 28.64% for proposal type "mBirthDeath" (2/162) = 1.23% for proposal type "degrees of freedom" and effective degrees of freedom = 16.34 number of qVoronoi tiles = 13 number of mVoronoi tiles = 28 Log prior = 29.61 Log llike = 323.06 Ending iteration 1400 with acceptance proportions: (62/80) = 77.50% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (7/108) = 6.48% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (48/90) = 53.33% for proposal type "qBirthDeath" (216/260) = 83.08% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (120/179) = 67.04% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (56/270) = 20.74% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (67/240) = 27.92% for proposal type "mBirthDeath" (2/173) = 1.16% for proposal type "degrees of freedom" and effective degrees of freedom = 16.34 number of qVoronoi tiles = 13 number of mVoronoi tiles = 28 Log prior = 25.97 Log llike = 343.45 Ending iteration 1500 with acceptance proportions: (70/90) = 77.78% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (7/117) = 5.98% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (49/93) = 52.69% for proposal type "qBirthDeath" (225/274) = 82.12% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (125/191) = 65.45% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (57/288) = 19.79% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (68/258) = 26.36% for proposal type "mBirthDeath" (3/189) = 1.59% for proposal type "degrees of freedom" and effective degrees of freedom = 18.79 number of qVoronoi tiles = 14 number of mVoronoi tiles = 29 Log prior = 26.00 Log llike = 346.09 Ending iteration 1600 with acceptance proportions: (75/96) = 78.12% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (7/121) = 5.79% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (53/100) = 53.00% for proposal type "qBirthDeath" (242/294) = 82.31% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (134/208) = 64.42% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (59/305) = 19.34% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (71/276) = 25.72% for proposal type "mBirthDeath" (4/200) = 2.00% for proposal type "degrees of freedom" and effective degrees of freedom = 20.76 number of qVoronoi tiles = 14 number of mVoronoi tiles = 28 Log prior = 24.75 Log llike = 357.80 Ending iteration 1700 with acceptance proportions: (82/104) = 78.85% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (7/125) = 5.60% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (55/106) = 51.89% for proposal type "qBirthDeath" (253/307) = 82.41% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (138/219) = 63.01% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (62/328) = 18.90% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (76/295) = 25.76% for proposal type "mBirthDeath" (6/216) = 2.78% for proposal type "degrees of freedom" and effective degrees of freedom = 18.16 number of qVoronoi tiles = 14 number of mVoronoi tiles = 31 Log prior = 19.16 Log llike = 373.44 Ending iteration 1800 with acceptance proportions: (84/106) = 79.25% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (9/134) = 6.72% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (61/114) = 53.51% for proposal type "qBirthDeath" (262/323) = 81.11% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (145/229) = 63.32% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (62/347) = 17.87% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (82/318) = 25.79% for proposal type "mBirthDeath" (10/229) = 4.37% for proposal type "degrees of freedom" and effective degrees of freedom = 19.18 number of qVoronoi tiles = 14 number of mVoronoi tiles = 31 Log prior = 17.96 Log llike = 378.62 Ending iteration 1900 with acceptance proportions: (85/107) = 79.44% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (10/140) = 7.14% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (63/116) = 54.31% for proposal type "qBirthDeath" (285/350) = 81.43% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (153/243) = 62.96% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (63/367) = 17.17% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (89/341) = 26.10% for proposal type "mBirthDeath" (11/236) = 4.66% for proposal type "degrees of freedom" and effective degrees of freedom = 24.11 number of qVoronoi tiles = 14 number of mVoronoi tiles = 30 Log prior = 18.68 Log llike = 384.86 Iteration 2000 of 2000... Ending iteration 2000 with acceptance proportions: (89/111) = 80.18% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (10/145) = 6.90% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (68/127) = 53.54% for proposal type "qBirthDeath" (299/367) = 81.47% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (162/262) = 61.83% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (64/387) = 16.54% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (91/357) = 25.49% for proposal type "mBirthDeath" (13/244) = 5.33% for proposal type "degrees of freedom" and effective degrees of freedom = 21.74 number of qVoronoi tiles = 13 number of mVoronoi tiles = 28 Log prior = 12.87 Log llike = 384.98 Final log prior: 12.87 Final log llike: 384.98 Will save EEMS output to D:\temp\2026_04_23_13_35_17_30548\RtmpqQU3Ud/eems_out/ [Habitat::initialize] Loaded habitat points from D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/barrier-schemeX-nIndiv300-nSites3000.outer Input habitat: POLYGON((0 0,0 6.1,11.5 6.1,11.5 0,0 0)) [Habitat::initialize] Done. [Graph::initialize] Generate population grid and sample assignment Loaded sample coordinates from D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/barrier-schemeX-nIndiv300-nSites3000.coord There are 71 observed demes (out of 190 demes) The population grid has 190 demes and 513 edges There are 300 samples assigned to 71 observed demes [Graph::initialize] Done. [Diffs::initialize] [Diffs::initialize] Done. Initialize EEMS random state [EEMS::initialize_state] EEMS starts with 160 qtiles and 139 mtiles [EEMS::initialize_state] Done. Input parameters: datapath = D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/barrier-schemeX-nIndiv300-nSites3000 mcmcpath = D:\temp\2026_04_23_13_35_17_30548\RtmpqQU3Ud/eems_out prevpath = gridpath = distance = euclidean diploid = 0 nIndiv = 300 nSites = 3000 nDemes = 200 seed = 1776945127 numMCMCIter = 2000 numBurnIter = 1000 numThinIter = 99 negBiSize = 10 negBiProb = 0.670000 qVoronoiPr = 0.250000 mrateShape = 0.000500 qrateShape = 0.002000 sigmaShape = 0.001000 qrateScale = 0.500000 mrateScale = 2.000000 sigmaScale = 1.000000 mSeedsProposalS2 = 0.010000 qSeedsProposalS2 = 0.100000 mEffctProposalS2 = 0.100000 qEffctProposalS2 = 0.001000 mrateMuProposalS2 = 0.010000 Initial log prior: 315.92 Initial log llike: 151499.18 Iteration 1000 of 2000... Ending iteration 1100 with acceptance proportions: (58/80) = 72.50% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (40/66) = 60.61% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (38/78) = 48.72% for proposal type "qBirthDeath" (136/203) = 67.00% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (26/130) = 20.00% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (107/204) = 52.45% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (70/203) = 34.48% for proposal type "mBirthDeath" (40/136) = 29.41% for proposal type "degrees of freedom" and effective degrees of freedom = 574.98 number of qVoronoi tiles = 150 number of mVoronoi tiles = 147 Log prior = 243.68 Log llike = 175929.94 Ending iteration 1200 with acceptance proportions: (63/86) = 73.26% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (45/73) = 61.64% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (38/79) = 48.10% for proposal type "qBirthDeath" (149/221) = 67.42% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (28/142) = 19.72% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (115/223) = 51.57% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (72/225) = 32.00% for proposal type "mBirthDeath" (48/151) = 31.79% for proposal type "degrees of freedom" and effective degrees of freedom = 595.97 number of qVoronoi tiles = 150 number of mVoronoi tiles = 147 Log prior = 248.73 Log llike = 176676.55 Ending iteration 1300 with acceptance proportions: (68/94) = 72.34% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (50/81) = 61.73% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (39/82) = 47.56% for proposal type "qBirthDeath" (155/237) = 65.40% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (28/157) = 17.83% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (122/237) = 51.48% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (77/245) = 31.43% for proposal type "mBirthDeath" (60/167) = 35.93% for proposal type "degrees of freedom" and effective degrees of freedom = 670.76 number of qVoronoi tiles = 151 number of mVoronoi tiles = 146 Log prior = 263.23 Log llike = 178734.27 Ending iteration 1400 with acceptance proportions: (72/100) = 72.00% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (52/84) = 61.90% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (42/88) = 47.73% for proposal type "qBirthDeath" (170/255) = 66.67% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (31/179) = 17.32% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (130/256) = 50.78% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (81/259) = 31.27% for proposal type "mBirthDeath" (65/179) = 36.31% for proposal type "degrees of freedom" and effective degrees of freedom = 681.92 number of qVoronoi tiles = 150 number of mVoronoi tiles = 144 Log prior = 267.32 Log llike = 179033.73 Ending iteration 1500 with acceptance proportions: (77/105) = 73.33% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (56/91) = 61.54% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (46/97) = 47.42% for proposal type "qBirthDeath" (183/272) = 67.28% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (33/194) = 17.01% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (134/271) = 49.45% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (86/280) = 30.71% for proposal type "mBirthDeath" (69/190) = 36.32% for proposal type "degrees of freedom" and effective degrees of freedom = 701.18 number of qVoronoi tiles = 150 number of mVoronoi tiles = 147 Log prior = 250.29 Log llike = 179561.79 Ending iteration 1600 with acceptance proportions: (79/107) = 73.83% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (62/101) = 61.39% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (46/100) = 46.00% for proposal type "qBirthDeath" (200/293) = 68.26% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (37/210) = 17.62% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (143/288) = 49.65% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (94/301) = 31.23% for proposal type "mBirthDeath" (74/200) = 37.00% for proposal type "degrees of freedom" and effective degrees of freedom = 727.50 number of qVoronoi tiles = 150 number of mVoronoi tiles = 147 Log prior = 265.08 Log llike = 180182.32 Ending iteration 1700 with acceptance proportions: (84/114) = 73.68% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (67/109) = 61.47% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (49/105) = 46.67% for proposal type "qBirthDeath" (215/313) = 68.69% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (38/220) = 17.27% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (158/313) = 50.48% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (97/316) = 30.70% for proposal type "mBirthDeath" (81/210) = 38.57% for proposal type "degrees of freedom" and effective degrees of freedom = 779.64 number of qVoronoi tiles = 149 number of mVoronoi tiles = 144 Log prior = 264.35 Log llike = 181226.73 Ending iteration 1800 with acceptance proportions: (90/122) = 73.77% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (72/115) = 62.61% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (50/112) = 44.64% for proposal type "qBirthDeath" (224/329) = 68.09% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (42/232) = 18.10% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (171/332) = 51.51% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (100/334) = 29.94% for proposal type "mBirthDeath" (90/224) = 40.18% for proposal type "degrees of freedom" and effective degrees of freedom = 836.87 number of qVoronoi tiles = 150 number of mVoronoi tiles = 145 Log prior = 259.90 Log llike = 182178.40 Ending iteration 1900 with acceptance proportions: (97/132) = 73.48% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (75/123) = 60.98% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (54/121) = 44.63% for proposal type "qBirthDeath" (233/340) = 68.53% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (43/245) = 17.55% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (177/346) = 51.16% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (107/358) = 29.89% for proposal type "mBirthDeath" (95/235) = 40.43% for proposal type "degrees of freedom" and effective degrees of freedom = 845.84 number of qVoronoi tiles = 150 number of mVoronoi tiles = 148 Log prior = 270.53 Log llike = 182331.89 Iteration 2000 of 2000... Ending iteration 2000 with acceptance proportions: (103/144) = 71.53% for proposal type "qTileRate", with proposal variance "qEffctProposalS2" (77/127) = 60.63% for proposal type "qTileMove", with proposal variance "qSeedsProposalS2" (54/126) = 42.86% for proposal type "qBirthDeath" (242/353) = 68.56% for proposal type "mTileRate", with proposal variance "mEffctProposalS2" (44/262) = 16.79% for proposal type "mMeanRate", with proposal variance "mrateMuProposalS2" (189/369) = 51.22% for proposal type "mTileMove", with proposal variance "mSeedsProposalS2" (110/371) = 29.65% for proposal type "mBirthDeath" (101/248) = 40.73% for proposal type "degrees of freedom" and effective degrees of freedom = 869.79 number of qVoronoi tiles = 150 number of mVoronoi tiles = 147 Log prior = 267.64 Log llike = 182709.96 Final log prior: 267.64 Final log llike: 182709.96 Input projection: Output projection: Using 'euclidean' distance to assign interpolation points to Voronoi tiles. Processing the following EEMS output directories : D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting effective migration surface (posterior mean of m rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting effective diversity surface (posterior mean of q rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting posterior probability trace D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting average dissimilarities within and between demes D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Input projection: +proj=longlat +datum=WGS84 Output projection: +proj=merc +datum=WGS84 Using 'euclidean' distance to assign interpolation points to Voronoi tiles. Processing the following EEMS output directories : D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting effective migration surface (posterior mean of m rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting effective diversity surface (posterior mean of q rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting posterior probability trace D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting average dissimilarities within and between demes D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Input projection: Output projection: Using 'euclidean' distance to assign interpolation points to Voronoi tiles. Processing the following EEMS output directories : D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting effective migration surface (posterior mean of m rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting effective diversity surface (posterior mean of q rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting posterior probability trace D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting average dissimilarities within and between demes D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Input projection: Output projection: Processing the following EEMS output directories : D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Input projection: Output projection: Using 'euclidean' distance to assign interpolation points to Voronoi tiles. Plotting effective migration surface (one posterior draw of m rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw #13 (out of 100) Plotting effective migration surface (one posterior draw of m rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw #47 (out of 100) Plotting effective diversity surface (one posterior draw of q rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw #24 (out of 100) Plotting effective diversity surface (one posterior draw of q rates) D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw #3 (out of 100) Loading deldir (required by eems.voronoi.samples) Input projection: Output projection: Using 'euclidean' distance to assign interpolation points to Voronoi tiles. Processing the following EEMS output directory : D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Plotting Voronoi tessellation of estimated effective rates D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw 55 (out of 100) Plotting Voronoi tessellation of estimated effective rates D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw 37 (out of 100) Plotting Voronoi tessellation of estimated effective rates D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw 5 (out of 100) Plotting Voronoi tessellation of estimated effective rates D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example Draw 2 (out of 100) [Habitat::initialize] Loaded habitat points from D:\temp\2026_04_23_13_35_17_30548\RtmpqQU3Ud/data_path/in.outer Input habitat: POLYGON((0 0,0 6.1,11.5 6.1,11.5 0,0 0)) [Habitat::initialize] Done. [Graph::initialize] Generate population grid and sample assignment The population grid has 254 demes and 693 edges [Graph::initialize] Done. [ FAIL 0 | WARN 0 | SKIP 0 | PASS 36 ] > > proc.time() user system elapsed 26.54 3.85 46.68