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 'contributors()' for more information and
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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_17_05_17_18924\RtmpIN34h6/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_17_05_17_18924\RtmpIN34h6/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 34 qtiles and 43 mtiles
[EEMS::initialize_state] Done.

Input parameters: 
               datapath = D:\temp\2026_04_22_17_05_17_18924\RtmpIN34h6/data_path/in
               mcmcpath = D:\temp\2026_04_22_17_05_17_18924\RtmpIN34h6/eems_out/example-chain1
               prevpath = 
               gridpath = 
               distance = greatcircle
                diploid = 1
                 nIndiv = 16
                 nSites = 10000
                 nDemes = 96
                   seed = 1776870808
            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: 92.22
Initial log llike: 141.08

Iteration 1000 of 2000...
 Ending iteration 1100 with acceptance proportions:
	(62/71) = 87.32% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(3/77) = 3.90% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(42/88) = 47.73% for proposal type "qBirthDeath"
	(172/208) = 82.69% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(105/141) = 74.47% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(38/202) = 18.81% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(65/186) = 34.95% for proposal type "mBirthDeath"
	(2/127) = 1.57% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.10
         number of qVoronoi tiles = 30
         number of mVoronoi tiles = 38
          Log prior = 68.79
          Log llike = 309.72
 Ending iteration 1200 with acceptance proportions:
	(66/76) = 86.84% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(4/84) = 4.76% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(45/92) = 48.91% for proposal type "qBirthDeath"
	(188/228) = 82.46% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(110/152) = 72.37% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(42/226) = 18.58% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(70/202) = 34.65% for proposal type "mBirthDeath"
	(3/140) = 2.14% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.08
         number of qVoronoi tiles = 31
         number of mVoronoi tiles = 41
          Log prior = 58.14
          Log llike = 321.15
 Ending iteration 1300 with acceptance proportions:
	(72/82) = 87.80% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(6/95) = 6.32% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(50/99) = 50.51% for proposal type "qBirthDeath"
	(206/250) = 82.40% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(114/158) = 72.15% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(45/241) = 18.67% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(72/223) = 32.29% for proposal type "mBirthDeath"
	(5/152) = 3.29% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.14
         number of qVoronoi tiles = 34
         number of mVoronoi tiles = 41
          Log prior = 64.14
          Log llike = 325.73
 Ending iteration 1400 with acceptance proportions:
	(77/88) = 87.50% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(6/100) = 6.00% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(58/112) = 51.79% for proposal type "qBirthDeath"
	(219/268) = 81.72% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(118/168) = 70.24% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(47/260) = 18.08% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(76/241) = 31.54% for proposal type "mBirthDeath"
	(8/163) = 4.91% for proposal type "degrees of freedom"
 and effective degrees of freedom = 18.10
         number of qVoronoi tiles = 36
         number of mVoronoi tiles = 41
          Log prior = 70.20
          Log llike = 325.84
 Ending iteration 1500 with acceptance proportions:
	(84/95) = 88.42% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(6/104) = 5.77% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(61/117) = 52.14% for proposal type "qBirthDeath"
	(231/284) = 81.34% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(124/180) = 68.89% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(48/282) = 17.02% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(84/262) = 32.06% for proposal type "mBirthDeath"
	(8/176) = 4.55% for proposal type "degrees of freedom"
 and effective degrees of freedom = 18.10
         number of qVoronoi tiles = 37
         number of mVoronoi tiles = 35
          Log prior = 74.26
          Log llike = 347.49
 Ending iteration 1600 with acceptance proportions:
	(90/102) = 88.24% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(7/112) = 6.25% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(65/125) = 52.00% for proposal type "qBirthDeath"
	(246/304) = 80.92% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(131/191) = 68.59% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(49/300) = 16.33% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(87/280) = 31.07% for proposal type "mBirthDeath"
	(9/186) = 4.84% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.03
         number of qVoronoi tiles = 39
         number of mVoronoi tiles = 36
          Log prior = 78.28
          Log llike = 336.00
 Ending iteration 1700 with acceptance proportions:
	(98/110) = 89.09% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(8/117) = 6.84% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(66/130) = 50.77% for proposal type "qBirthDeath"
	(258/321) = 80.37% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(136/206) = 66.02% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(54/320) = 16.88% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(93/298) = 31.21% for proposal type "mBirthDeath"
	(10/198) = 5.05% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.27
         number of qVoronoi tiles = 38
         number of mVoronoi tiles = 36
          Log prior = 71.44
          Log llike = 344.54
 Ending iteration 1800 with acceptance proportions:
	(102/115) = 88.70% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(8/129) = 6.20% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(67/136) = 49.26% for proposal type "qBirthDeath"
	(274/343) = 79.88% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(142/215) = 66.05% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(56/336) = 16.67% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(98/317) = 30.91% for proposal type "mBirthDeath"
	(12/209) = 5.74% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.42
         number of qVoronoi tiles = 39
         number of mVoronoi tiles = 37
          Log prior = 75.13
          Log llike = 335.97
 Ending iteration 1900 with acceptance proportions:
	(110/124) = 88.71% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(9/137) = 6.57% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(67/138) = 48.55% for proposal type "qBirthDeath"
	(286/359) = 79.67% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(146/220) = 66.36% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(58/360) = 16.11% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(105/339) = 30.97% for proposal type "mBirthDeath"
	(14/223) = 6.28% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.45
         number of qVoronoi tiles = 39
         number of mVoronoi tiles = 38
          Log prior = 65.26
          Log llike = 348.99
Iteration 2000 of 2000...
 Ending iteration 2000 with acceptance proportions:
	(117/132) = 88.64% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(9/144) = 6.25% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(72/145) = 49.66% for proposal type "qBirthDeath"
	(298/373) = 79.89% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(150/230) = 65.22% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(60/377) = 15.92% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(112/355) = 31.55% for proposal type "mBirthDeath"
	(17/244) = 6.97% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.55
         number of qVoronoi tiles = 38
         number of mVoronoi tiles = 37
          Log prior = 68.64
          Log llike = 353.74
Final log prior: 68.64
Final log llike: 353.74
  Will save EEMS output to D:\temp\2026_04_22_17_05_17_18924\RtmpIN34h6/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 153 qtiles and 121 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_17_05_17_18924\RtmpIN34h6/eems_out
               prevpath = 
               gridpath = 
               distance = euclidean
                diploid = 0
                 nIndiv = 300
                 nSites = 3000
                 nDemes = 200
                   seed = 1776870829
            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: 394.70
Initial log llike: 135021.27

Iteration 1000 of 2000...
 Ending iteration 1100 with acceptance proportions:
	(35/60) = 58.33% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(46/79) = 58.23% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(28/57) = 49.12% for proposal type "qBirthDeath"
	(111/184) = 60.33% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(33/146) = 22.60% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(122/207) = 58.94% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(90/204) = 44.12% for proposal type "mBirthDeath"
	(58/163) = 35.58% for proposal type "degrees of freedom"
 and effective degrees of freedom = 597.08
         number of qVoronoi tiles = 153
         number of mVoronoi tiles = 105
          Log prior = 360.81
          Log llike = 176775.56
 Ending iteration 1200 with acceptance proportions:
	(39/66) = 59.09% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(46/81) = 56.79% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(33/65) = 50.77% for proposal type "qBirthDeath"
	(125/205) = 60.98% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(33/160) = 20.62% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(133/228) = 58.33% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(99/222) = 44.59% for proposal type "mBirthDeath"
	(63/173) = 36.42% for proposal type "degrees of freedom"
 and effective degrees of freedom = 631.82
         number of qVoronoi tiles = 156
         number of mVoronoi tiles = 102
          Log prior = 366.56
          Log llike = 177799.71
 Ending iteration 1300 with acceptance proportions:
	(41/73) = 56.16% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(49/86) = 56.98% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(34/70) = 48.57% for proposal type "qBirthDeath"
	(138/221) = 62.44% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(34/167) = 20.36% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(151/250) = 60.40% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(113/249) = 45.38% for proposal type "mBirthDeath"
	(68/184) = 36.96% for proposal type "degrees of freedom"
 and effective degrees of freedom = 656.21
         number of qVoronoi tiles = 155
         number of mVoronoi tiles = 98
          Log prior = 352.54
          Log llike = 178453.62
 Ending iteration 1400 with acceptance proportions:
	(47/81) = 58.02% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(51/90) = 56.67% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(39/79) = 49.37% for proposal type "qBirthDeath"
	(150/240) = 62.50% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(37/181) = 20.44% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(165/270) = 61.11% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(122/270) = 45.19% for proposal type "mBirthDeath"
	(69/189) = 36.51% for proposal type "degrees of freedom"
 and effective degrees of freedom = 664.90
         number of qVoronoi tiles = 154
         number of mVoronoi tiles = 97
          Log prior = 361.74
          Log llike = 178706.02
 Ending iteration 1500 with acceptance proportions:
	(50/88) = 56.82% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(55/95) = 57.89% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(47/88) = 53.41% for proposal type "qBirthDeath"
	(163/261) = 62.45% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(39/191) = 20.42% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(174/290) = 60.00% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(130/288) = 45.14% for proposal type "mBirthDeath"
	(75/199) = 37.69% for proposal type "degrees of freedom"
 and effective degrees of freedom = 696.55
         number of qVoronoi tiles = 150
         number of mVoronoi tiles = 99
          Log prior = 342.58
          Log llike = 179462.18
 Ending iteration 1600 with acceptance proportions:
	(55/95) = 57.89% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(57/99) = 57.58% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(50/93) = 53.76% for proposal type "qBirthDeath"
	(179/285) = 62.81% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(40/204) = 19.61% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(186/313) = 59.42% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(136/303) = 44.88% for proposal type "mBirthDeath"
	(81/208) = 38.94% for proposal type "degrees of freedom"
 and effective degrees of freedom = 735.24
         number of qVoronoi tiles = 151
         number of mVoronoi tiles = 99
          Log prior = 350.40
          Log llike = 180305.19
 Ending iteration 1700 with acceptance proportions:
	(60/103) = 58.25% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(61/104) = 58.65% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(52/101) = 51.49% for proposal type "qBirthDeath"
	(186/294) = 63.27% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(41/218) = 18.81% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(198/335) = 59.10% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(148/326) = 45.40% for proposal type "mBirthDeath"
	(88/219) = 40.18% for proposal type "degrees of freedom"
 and effective degrees of freedom = 784.82
         number of qVoronoi tiles = 151
         number of mVoronoi tiles = 97
          Log prior = 344.67
          Log llike = 181257.35
 Ending iteration 1800 with acceptance proportions:
	(61/106) = 57.55% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(65/110) = 59.09% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(55/109) = 50.46% for proposal type "qBirthDeath"
	(196/309) = 63.43% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(44/239) = 18.41% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(206/350) = 58.86% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(154/349) = 44.13% for proposal type "mBirthDeath"
	(92/228) = 40.35% for proposal type "degrees of freedom"
 and effective degrees of freedom = 794.60
         number of qVoronoi tiles = 150
         number of mVoronoi tiles = 97
          Log prior = 346.12
          Log llike = 181436.74
 Ending iteration 1900 with acceptance proportions:
	(66/114) = 57.89% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(68/116) = 58.62% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(58/116) = 50.00% for proposal type "qBirthDeath"
	(207/327) = 63.30% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(47/253) = 18.58% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(220/368) = 59.78% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(164/369) = 44.44% for proposal type "mBirthDeath"
	(98/237) = 41.35% for proposal type "degrees of freedom"
 and effective degrees of freedom = 822.71
         number of qVoronoi tiles = 147
         number of mVoronoi tiles = 97
          Log prior = 336.33
          Log llike = 181943.15
Iteration 2000 of 2000...
 Ending iteration 2000 with acceptance proportions:
	(73/122) = 59.84% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(72/120) = 60.00% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(60/119) = 50.42% for proposal type "qBirthDeath"
	(216/343) = 62.97% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(50/273) = 18.32% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(231/387) = 59.69% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(170/389) = 43.70% for proposal type "mBirthDeath"
	(105/247) = 42.51% for proposal type "degrees of freedom"
 and effective degrees of freedom = 854.63
         number of qVoronoi tiles = 147
         number of mVoronoi tiles = 95
          Log prior = 328.24
          Log llike = 182462.99
Final log prior: 328.24
Final log llike: 182462.99
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 #82 (out of 100)
Plotting effective migration surface (one posterior draw of m rates)
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw #28 (out of 100)
Plotting effective diversity surface (one posterior draw of q rates)
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw #36 (out of 100)
Plotting effective diversity surface (one posterior draw of q rates)
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw #64 (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 18 (out of 100)
Plotting Voronoi tessellation of estimated effective rates
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw 25 (out of 100)
Plotting Voronoi tessellation of estimated effective rates
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw 96 (out of 100)
Plotting Voronoi tessellation of estimated effective rates
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw 14 (out of 100)
[Habitat::initialize]
  Loaded habitat points from D:\temp\2026_04_22_17_05_17_18924\RtmpIN34h6/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 
  26.06    3.48   46.87