R version 4.6.0 RC (2026-04-21 r89932 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.
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Type 'license()' or 'licence()' for distribution details.

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> # 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_22_11_35_17_19802\Rtmp4yJpHG/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_22_11_35_17_19802\Rtmp4yJpHG/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 32 qtiles and 22 mtiles
[EEMS::initialize_state] Done.

Input parameters: 
               datapath = D:\temp\2026_04_22_11_35_17_19802\Rtmp4yJpHG/data_path/in
               mcmcpath = D:\temp\2026_04_22_11_35_17_19802\Rtmp4yJpHG/eems_out/example-chain1
               prevpath = 
               gridpath = 
               distance = greatcircle
                diploid = 1
                 nIndiv = 16
                 nSites = 10000
                 nDemes = 96
                   seed = 1776851047
            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: 105.21
Initial log llike: 172.85

Iteration 1000 of 2000...
 Ending iteration 1100 with acceptance proportions:
	(83/90) = 92.22% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(5/80) = 6.25% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(29/55) = 52.73% for proposal type "qBirthDeath"
	(167/218) = 76.61% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(86/122) = 70.49% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(54/210) = 25.71% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(67/186) = 36.02% for proposal type "mBirthDeath"
	(1/139) = 0.72% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.48
         number of qVoronoi tiles = 27
         number of mVoronoi tiles = 19
          Log prior = 67.82
          Log llike = 314.49
 Ending iteration 1200 with acceptance proportions:
	(86/95) = 90.53% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(5/82) = 6.10% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(31/58) = 53.45% for proposal type "qBirthDeath"
	(185/242) = 76.45% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(93/133) = 69.92% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(55/227) = 24.23% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(71/207) = 34.30% for proposal type "mBirthDeath"
	(3/156) = 1.92% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.25
         number of qVoronoi tiles = 29
         number of mVoronoi tiles = 19
          Log prior = 53.97
          Log llike = 327.86
 Ending iteration 1300 with acceptance proportions:
	(88/98) = 89.80% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(5/92) = 5.43% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(36/64) = 56.25% for proposal type "qBirthDeath"
	(197/258) = 76.36% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(105/150) = 70.00% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(57/250) = 22.80% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(72/219) = 32.88% for proposal type "mBirthDeath"
	(4/169) = 2.37% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.00
         number of qVoronoi tiles = 30
         number of mVoronoi tiles = 18
          Log prior = 72.53
          Log llike = 317.14
 Ending iteration 1400 with acceptance proportions:
	(91/102) = 89.22% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(5/97) = 5.15% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(42/70) = 60.00% for proposal type "qBirthDeath"
	(214/281) = 76.16% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(112/160) = 70.00% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(60/274) = 21.90% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(78/240) = 32.50% for proposal type "mBirthDeath"
	(4/176) = 2.27% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.00
         number of qVoronoi tiles = 32
         number of mVoronoi tiles = 16
          Log prior = 79.66
          Log llike = 308.97
 Ending iteration 1500 with acceptance proportions:
	(102/113) = 90.27% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(5/98) = 5.10% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(48/83) = 57.83% for proposal type "qBirthDeath"
	(227/297) = 76.43% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(116/171) = 67.84% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(62/291) = 21.31% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(82/263) = 31.18% for proposal type "mBirthDeath"
	(5/184) = 2.72% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.22
         number of qVoronoi tiles = 30
         number of mVoronoi tiles = 16
          Log prior = 71.72
          Log llike = 332.76
 Ending iteration 1600 with acceptance proportions:
	(107/119) = 89.92% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(5/100) = 5.00% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(51/87) = 58.62% for proposal type "qBirthDeath"
	(240/316) = 75.95% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(126/188) = 67.02% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(64/313) = 20.45% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(88/286) = 30.77% for proposal type "mBirthDeath"
	(7/191) = 3.66% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.76
         number of qVoronoi tiles = 29
         number of mVoronoi tiles = 18
          Log prior = 63.93
          Log llike = 353.30
 Ending iteration 1700 with acceptance proportions:
	(111/123) = 90.24% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(5/103) = 4.85% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(54/93) = 58.06% for proposal type "qBirthDeath"
	(258/340) = 75.88% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(130/200) = 65.00% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(64/329) = 19.45% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(89/305) = 29.18% for proposal type "mBirthDeath"
	(9/207) = 4.35% for proposal type "degrees of freedom"
 and effective degrees of freedom = 18.46
         number of qVoronoi tiles = 28
         number of mVoronoi tiles = 19
          Log prior = 56.96
          Log llike = 343.90
 Ending iteration 1800 with acceptance proportions:
	(122/136) = 89.71% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(6/111) = 5.41% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(55/99) = 55.56% for proposal type "qBirthDeath"
	(273/360) = 75.83% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(133/208) = 63.94% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(64/351) = 18.23% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(90/317) = 28.39% for proposal type "mBirthDeath"
	(13/218) = 5.96% for proposal type "degrees of freedom"
 and effective degrees of freedom = 20.59
         number of qVoronoi tiles = 29
         number of mVoronoi tiles = 20
          Log prior = 52.53
          Log llike = 357.58
 Ending iteration 1900 with acceptance proportions:
	(134/148) = 90.54% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(6/120) = 5.00% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(57/104) = 54.81% for proposal type "qBirthDeath"
	(287/379) = 75.73% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(137/217) = 63.13% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(64/364) = 17.58% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(94/336) = 27.98% for proposal type "mBirthDeath"
	(16/232) = 6.90% for proposal type "degrees of freedom"
 and effective degrees of freedom = 21.55
         number of qVoronoi tiles = 27
         number of mVoronoi tiles = 20
          Log prior = 57.33
          Log llike = 349.92
Iteration 2000 of 2000...
 Ending iteration 2000 with acceptance proportions:
	(139/154) = 90.26% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(6/124) = 4.84% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(59/109) = 54.13% for proposal type "qBirthDeath"
	(300/398) = 75.38% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(143/237) = 60.34% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(64/380) = 16.84% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(96/361) = 26.59% for proposal type "mBirthDeath"
	(17/237) = 7.17% for proposal type "degrees of freedom"
 and effective degrees of freedom = 19.80
         number of qVoronoi tiles = 25
         number of mVoronoi tiles = 22
          Log prior = 56.30
          Log llike = 356.44
Final log prior: 56.30
Final log llike: 356.44
  Will save EEMS output to D:\temp\2026_04_22_11_35_17_19802\Rtmp4yJpHG/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 120 qtiles and 157 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_22_11_35_17_19802\Rtmp4yJpHG/eems_out
               prevpath = 
               gridpath = 
               distance = euclidean
                diploid = 0
                 nIndiv = 300
                 nSites = 3000
                 nDemes = 200
                   seed = 1776851068
            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: 207.20
Initial log llike: 142333.25

Iteration 1000 of 2000...
 Ending iteration 1100 with acceptance proportions:
	(53/78) = 67.95% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(51/80) = 63.75% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(25/56) = 44.64% for proposal type "qBirthDeath"
	(144/217) = 66.36% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(31/124) = 25.00% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(121/202) = 59.90% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(79/210) = 37.62% for proposal type "mBirthDeath"
	(40/133) = 30.08% for proposal type "degrees of freedom"
 and effective degrees of freedom = 522.30
         number of qVoronoi tiles = 123
         number of mVoronoi tiles = 148
          Log prior = 197.01
          Log llike = 173950.38
 Ending iteration 1200 with acceptance proportions:
	(57/84) = 67.86% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(54/87) = 62.07% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(29/62) = 46.77% for proposal type "qBirthDeath"
	(161/236) = 68.22% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(34/135) = 25.19% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(131/221) = 59.28% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(85/230) = 36.96% for proposal type "mBirthDeath"
	(47/145) = 32.41% for proposal type "degrees of freedom"
 and effective degrees of freedom = 553.10
         number of qVoronoi tiles = 125
         number of mVoronoi tiles = 146
          Log prior = 207.12
          Log llike = 175116.75
 Ending iteration 1300 with acceptance proportions:
	(59/88) = 67.05% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(56/94) = 59.57% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(30/68) = 44.12% for proposal type "qBirthDeath"
	(176/262) = 67.18% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(35/147) = 23.81% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(143/243) = 58.85% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(91/241) = 37.76% for proposal type "mBirthDeath"
	(53/157) = 33.76% for proposal type "degrees of freedom"
 and effective degrees of freedom = 602.88
         number of qVoronoi tiles = 126
         number of mVoronoi tiles = 146
          Log prior = 214.54
          Log llike = 176732.95
 Ending iteration 1400 with acceptance proportions:
	(60/91) = 65.93% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(61/103) = 59.22% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(35/76) = 46.05% for proposal type "qBirthDeath"
	(191/283) = 67.49% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(36/157) = 22.93% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(152/263) = 57.79% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(96/260) = 36.92% for proposal type "mBirthDeath"
	(58/167) = 34.73% for proposal type "degrees of freedom"
 and effective degrees of freedom = 628.68
         number of qVoronoi tiles = 125
         number of mVoronoi tiles = 141
          Log prior = 215.27
          Log llike = 177552.01
 Ending iteration 1500 with acceptance proportions:
	(62/93) = 66.67% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(64/111) = 57.66% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(37/82) = 45.12% for proposal type "qBirthDeath"
	(206/302) = 68.21% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(41/175) = 23.43% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(157/273) = 57.51% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(103/289) = 35.64% for proposal type "mBirthDeath"
	(63/175) = 36.00% for proposal type "degrees of freedom"
 and effective degrees of freedom = 659.33
         number of qVoronoi tiles = 123
         number of mVoronoi tiles = 146
          Log prior = 197.61
          Log llike = 178409.13
 Ending iteration 1600 with acceptance proportions:
	(62/96) = 64.58% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(70/118) = 59.32% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(40/87) = 45.98% for proposal type "qBirthDeath"
	(217/316) = 68.67% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(43/186) = 23.12% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(167/294) = 56.80% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(111/312) = 35.58% for proposal type "mBirthDeath"
	(70/191) = 36.65% for proposal type "degrees of freedom"
 and effective degrees of freedom = 698.45
         number of qVoronoi tiles = 124
         number of mVoronoi tiles = 144
          Log prior = 208.37
          Log llike = 179346.05
 Ending iteration 1700 with acceptance proportions:
	(65/101) = 64.36% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(74/126) = 58.73% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(43/94) = 45.74% for proposal type "qBirthDeath"
	(226/336) = 67.26% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(45/202) = 22.28% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(177/314) = 56.37% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(116/327) = 35.47% for proposal type "mBirthDeath"
	(78/200) = 39.00% for proposal type "degrees of freedom"
 and effective degrees of freedom = 745.36
         number of qVoronoi tiles = 125
         number of mVoronoi tiles = 145
          Log prior = 212.81
          Log llike = 180392.61
 Ending iteration 1800 with acceptance proportions:
	(67/106) = 63.21% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(80/134) = 59.70% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(46/99) = 46.46% for proposal type "qBirthDeath"
	(240/355) = 67.61% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(45/217) = 20.74% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(183/329) = 55.62% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(120/345) = 34.78% for proposal type "mBirthDeath"
	(86/215) = 40.00% for proposal type "degrees of freedom"
 and effective degrees of freedom = 781.16
         number of qVoronoi tiles = 126
         number of mVoronoi tiles = 143
          Log prior = 211.58
          Log llike = 181102.81
 Ending iteration 1900 with acceptance proportions:
	(76/117) = 64.96% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(84/141) = 59.57% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(50/108) = 46.30% for proposal type "qBirthDeath"
	(247/369) = 66.94% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(45/232) = 19.40% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(190/343) = 55.39% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(125/363) = 34.44% for proposal type "mBirthDeath"
	(93/227) = 40.97% for proposal type "degrees of freedom"
 and effective degrees of freedom = 834.00
         number of qVoronoi tiles = 128
         number of mVoronoi tiles = 142
          Log prior = 212.37
          Log llike = 181979.29
Iteration 2000 of 2000...
 Ending iteration 2000 with acceptance proportions:
	(82/127) = 64.57% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(88/148) = 59.46% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(51/113) = 45.13% for proposal type "qBirthDeath"
	(256/379) = 67.55% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(46/240) = 19.17% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(201/370) = 54.32% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(131/385) = 34.03% for proposal type "mBirthDeath"
	(101/238) = 42.44% for proposal type "degrees of freedom"
 and effective degrees of freedom = 869.67
         number of qVoronoi tiles = 127
         number of mVoronoi tiles = 144
          Log prior = 216.61
          Log llike = 182524.60
Final log prior: 216.61
Final log llike: 182524.60
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 #95 (out of 100)
Plotting effective migration surface (one posterior draw of m rates)
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw #10 (out of 100)
Plotting effective diversity surface (one posterior draw of q 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 #52 (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 66 (out of 100)
Plotting Voronoi tessellation of estimated effective rates
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw 82 (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)
Plotting Voronoi tessellation of estimated effective rates
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw 94 (out of 100)
[Habitat::initialize]
  Loaded habitat points from D:\temp\2026_04_22_11_35_17_19802\Rtmp4yJpHG/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 
  27.42    4.48   50.46