R Under development (unstable) (2026-04-26 r89963 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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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_27_23_20_17_28570\RtmpOOtwMT/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_27_23_20_17_28570\RtmpOOtwMT/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 50 qtiles and 20 mtiles
[EEMS::initialize_state] Done.

Input parameters: 
               datapath = D:\temp\2026_04_27_23_20_17_28570\RtmpOOtwMT/data_path/in
               mcmcpath = D:\temp\2026_04_27_23_20_17_28570\RtmpOOtwMT/eems_out/example-chain1
               prevpath = 
               gridpath = 
               distance = greatcircle
                diploid = 1
                 nIndiv = 16
                 nSites = 10000
                 nDemes = 96
                   seed = 1777325342
            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: 145.79
Initial log llike: 13.76

Iteration 1000 of 2000...
 Ending iteration 1100 with acceptance proportions:
	(56/67) = 83.58% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(1/72) = 1.39% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(44/84) = 52.38% for proposal type "qBirthDeath"
	(153/187) = 81.82% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(106/147) = 72.11% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(52/196) = 26.53% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(62/217) = 28.57% for proposal type "mBirthDeath"
	(2/130) = 1.54% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.19
         number of qVoronoi tiles = 40
         number of mVoronoi tiles = 22
          Log prior = 86.15
          Log llike = 297.64
 Ending iteration 1200 with acceptance proportions:
	(62/75) = 82.67% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(1/79) = 1.27% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(48/90) = 53.33% for proposal type "qBirthDeath"
	(163/206) = 79.13% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(110/159) = 69.18% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(54/213) = 25.35% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(67/238) = 28.15% for proposal type "mBirthDeath"
	(2/140) = 1.43% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.19
         number of qVoronoi tiles = 42
         number of mVoronoi tiles = 19
          Log prior = 97.32
          Log llike = 313.37
 Ending iteration 1300 with acceptance proportions:
	(68/83) = 81.93% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(1/84) = 1.19% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(48/94) = 51.06% for proposal type "qBirthDeath"
	(183/231) = 79.22% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(114/166) = 68.67% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(56/232) = 24.14% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(71/254) = 27.95% for proposal type "mBirthDeath"
	(2/156) = 1.28% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.19
         number of qVoronoi tiles = 42
         number of mVoronoi tiles = 21
          Log prior = 98.80
          Log llike = 318.47
 Ending iteration 1400 with acceptance proportions:
	(71/87) = 81.61% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(1/88) = 1.14% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(52/101) = 51.49% for proposal type "qBirthDeath"
	(194/248) = 78.23% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(121/176) = 68.75% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(59/258) = 22.87% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(76/271) = 28.04% for proposal type "mBirthDeath"
	(2/171) = 1.17% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.19
         number of qVoronoi tiles = 40
         number of mVoronoi tiles = 20
          Log prior = 85.71
          Log llike = 327.88
 Ending iteration 1500 with acceptance proportions:
	(73/90) = 81.11% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(2/90) = 2.22% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(55/107) = 51.40% for proposal type "qBirthDeath"
	(205/264) = 77.65% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(131/196) = 66.84% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(61/281) = 21.71% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(83/288) = 28.82% for proposal type "mBirthDeath"
	(2/184) = 1.09% for proposal type "degrees of freedom"
 and effective degrees of freedom = 16.19
         number of qVoronoi tiles = 39
         number of mVoronoi tiles = 21
          Log prior = 88.73
          Log llike = 337.32
 Ending iteration 1600 with acceptance proportions:
	(76/93) = 81.72% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(2/98) = 2.04% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(57/111) = 51.35% for proposal type "qBirthDeath"
	(219/283) = 77.39% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(141/215) = 65.58% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(63/300) = 21.00% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(87/306) = 28.43% for proposal type "mBirthDeath"
	(3/194) = 1.55% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.17
         number of qVoronoi tiles = 37
         number of mVoronoi tiles = 19
          Log prior = 82.20
          Log llike = 339.29
 Ending iteration 1700 with acceptance proportions:
	(80/99) = 80.81% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(3/107) = 2.80% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(60/118) = 50.85% for proposal type "qBirthDeath"
	(234/299) = 78.26% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(149/230) = 64.78% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(65/319) = 20.38% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(90/325) = 27.69% for proposal type "mBirthDeath"
	(3/203) = 1.48% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.17
         number of qVoronoi tiles = 36
         number of mVoronoi tiles = 18
          Log prior = 79.58
          Log llike = 343.00
 Ending iteration 1800 with acceptance proportions:
	(82/102) = 80.39% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(3/114) = 2.63% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(64/123) = 52.03% for proposal type "qBirthDeath"
	(244/316) = 77.22% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(161/245) = 65.71% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(68/341) = 19.94% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(94/344) = 27.33% for proposal type "mBirthDeath"
	(5/215) = 2.33% for proposal type "degrees of freedom"
 and effective degrees of freedom = 17.24
         number of qVoronoi tiles = 32
         number of mVoronoi tiles = 16
          Log prior = 72.92
          Log llike = 348.65
 Ending iteration 1900 with acceptance proportions:
	(88/108) = 81.48% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(4/119) = 3.36% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(70/132) = 53.03% for proposal type "qBirthDeath"
	(257/335) = 76.72% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(164/257) = 63.81% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(70/364) = 19.23% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(95/357) = 26.61% for proposal type "mBirthDeath"
	(6/228) = 2.63% for proposal type "degrees of freedom"
 and effective degrees of freedom = 20.26
         number of qVoronoi tiles = 28
         number of mVoronoi tiles = 17
          Log prior = 54.04
          Log llike = 359.83
Iteration 2000 of 2000...
 Ending iteration 2000 with acceptance proportions:
	(92/113) = 81.42% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(4/124) = 3.23% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(72/136) = 52.94% for proposal type "qBirthDeath"
	(266/357) = 74.51% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(175/274) = 63.87% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(72/381) = 18.90% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(102/377) = 27.06% for proposal type "mBirthDeath"
	(11/238) = 4.62% for proposal type "degrees of freedom"
 and effective degrees of freedom = 20.01
         number of qVoronoi tiles = 26
         number of mVoronoi tiles = 18
          Log prior = 51.34
          Log llike = 378.11
Final log prior: 51.34
Final log llike: 378.11
  Will save EEMS output to D:\temp\2026_04_27_23_20_17_28570\RtmpOOtwMT/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 133 qtiles and 154 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_27_23_20_17_28570\RtmpOOtwMT/eems_out
               prevpath = 
               gridpath = 
               distance = euclidean
                diploid = 0
                 nIndiv = 300
                 nSites = 3000
                 nDemes = 200
                   seed = 1777325363
            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: 224.90
Initial log llike: 125054.49

Iteration 1000 of 2000...
 Ending iteration 1100 with acceptance proportions:
	(42/58) = 72.41% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(51/66) = 77.27% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(29/69) = 42.03% for proposal type "qBirthDeath"
	(159/223) = 71.30% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(46/145) = 31.72% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(110/179) = 61.45% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(85/225) = 37.78% for proposal type "mBirthDeath"
	(33/135) = 24.44% for proposal type "degrees of freedom"
 and effective degrees of freedom = 476.48
         number of qVoronoi tiles = 132
         number of mVoronoi tiles = 151
          Log prior = 188.79
          Log llike = 171860.17
 Ending iteration 1200 with acceptance proportions:
	(48/67) = 71.64% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(56/76) = 73.68% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(34/75) = 45.33% for proposal type "qBirthDeath"
	(170/240) = 70.83% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(48/160) = 30.00% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(120/200) = 60.00% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(92/240) = 38.33% for proposal type "mBirthDeath"
	(39/142) = 27.46% for proposal type "degrees of freedom"
 and effective degrees of freedom = 509.89
         number of qVoronoi tiles = 135
         number of mVoronoi tiles = 150
          Log prior = 194.14
          Log llike = 173412.48
 Ending iteration 1300 with acceptance proportions:
	(54/75) = 72.00% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(60/82) = 73.17% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(36/79) = 45.57% for proposal type "qBirthDeath"
	(176/252) = 69.84% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(49/177) = 27.68% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(128/223) = 57.40% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(101/261) = 38.70% for proposal type "mBirthDeath"
	(42/151) = 27.81% for proposal type "degrees of freedom"
 and effective degrees of freedom = 518.83
         number of qVoronoi tiles = 135
         number of mVoronoi tiles = 153
          Log prior = 198.63
          Log llike = 173865.07
 Ending iteration 1400 with acceptance proportions:
	(62/85) = 72.94% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(63/89) = 70.79% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(39/86) = 45.35% for proposal type "qBirthDeath"
	(193/273) = 70.70% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(51/187) = 27.27% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(139/242) = 57.44% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(105/278) = 37.77% for proposal type "mBirthDeath"
	(47/160) = 29.38% for proposal type "degrees of freedom"
 and effective degrees of freedom = 547.90
         number of qVoronoi tiles = 136
         number of mVoronoi tiles = 155
          Log prior = 191.39
          Log llike = 175036.93
 Ending iteration 1500 with acceptance proportions:
	(67/93) = 72.04% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(66/95) = 69.47% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(45/92) = 48.91% for proposal type "qBirthDeath"
	(207/293) = 70.65% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(54/195) = 27.69% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(154/264) = 58.33% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(112/298) = 37.58% for proposal type "mBirthDeath"
	(54/170) = 31.76% for proposal type "degrees of freedom"
 and effective degrees of freedom = 603.89
         number of qVoronoi tiles = 140
         number of mVoronoi tiles = 156
          Log prior = 200.04
          Log llike = 176887.40
 Ending iteration 1600 with acceptance proportions:
	(69/97) = 71.13% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(68/99) = 68.69% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(47/100) = 47.00% for proposal type "qBirthDeath"
	(220/314) = 70.06% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(56/209) = 26.79% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(164/280) = 58.57% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(117/324) = 36.11% for proposal type "mBirthDeath"
	(59/177) = 33.33% for proposal type "degrees of freedom"
 and effective degrees of freedom = 622.80
         number of qVoronoi tiles = 138
         number of mVoronoi tiles = 155
          Log prior = 188.85
          Log llike = 177462.17
 Ending iteration 1700 with acceptance proportions:
	(77/106) = 72.64% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(73/107) = 68.22% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(50/106) = 47.17% for proposal type "qBirthDeath"
	(233/328) = 71.04% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(59/221) = 26.70% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(176/297) = 59.26% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(124/343) = 36.15% for proposal type "mBirthDeath"
	(64/192) = 33.33% for proposal type "degrees of freedom"
 and effective degrees of freedom = 653.58
         number of qVoronoi tiles = 139
         number of mVoronoi tiles = 158
          Log prior = 206.12
          Log llike = 178306.85
 Ending iteration 1800 with acceptance proportions:
	(81/113) = 71.68% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(74/111) = 66.67% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(53/115) = 46.09% for proposal type "qBirthDeath"
	(242/341) = 70.97% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(59/233) = 25.32% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(193/320) = 60.31% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(126/362) = 34.81% for proposal type "mBirthDeath"
	(71/205) = 34.63% for proposal type "degrees of freedom"
 and effective degrees of freedom = 708.47
         number of qVoronoi tiles = 136
         number of mVoronoi tiles = 158
          Log prior = 207.23
          Log llike = 179593.94
 Ending iteration 1900 with acceptance proportions:
	(81/114) = 71.05% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(80/120) = 66.67% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(56/123) = 45.53% for proposal type "qBirthDeath"
	(254/366) = 69.40% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(61/243) = 25.10% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(207/339) = 61.06% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(130/375) = 34.67% for proposal type "mBirthDeath"
	(79/220) = 35.91% for proposal type "degrees of freedom"
 and effective degrees of freedom = 768.14
         number of qVoronoi tiles = 133
         number of mVoronoi tiles = 156
          Log prior = 202.16
          Log llike = 180812.36
Iteration 2000 of 2000...
 Ending iteration 2000 with acceptance proportions:
	(86/121) = 71.07% for proposal type "qTileRate",		 with proposal variance "qEffctProposalS2"
	(82/126) = 65.08% for proposal type "qTileMove",		 with proposal variance "qSeedsProposalS2"
	(58/132) = 43.94% for proposal type "qBirthDeath"
	(268/385) = 69.61% for proposal type "mTileRate",		 with proposal variance "mEffctProposalS2"
	(62/251) = 24.70% for proposal type "mMeanRate",		 with proposal variance "mrateMuProposalS2"
	(215/354) = 60.73% for proposal type "mTileMove",		 with proposal variance "mSeedsProposalS2"
	(137/396) = 34.60% for proposal type "mBirthDeath"
	(86/235) = 36.60% for proposal type "degrees of freedom"
 and effective degrees of freedom = 803.39
         number of qVoronoi tiles = 135
         number of mVoronoi tiles = 149
          Log prior = 197.67
          Log llike = 181445.14
Final log prior: 197.67
Final log llike: 181445.14
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 #71 (out of 100)
Plotting effective migration surface (one posterior draw of m rates)
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw #30 (out of 100)
Plotting effective diversity surface (one posterior draw of q rates)
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw #43 (out of 100)
Plotting effective diversity surface (one posterior draw of q rates)
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw #96 (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 36 (out of 100)
Plotting Voronoi tessellation of estimated effective rates
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw 26 (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)
Plotting Voronoi tessellation of estimated effective rates
D:/RCompile/CRANincoming/R-devel/lib/reems/extdata/EEMS-example
Draw 81 (out of 100)
[Habitat::initialize]
  Loaded habitat points from D:\temp\2026_04_27_23_20_17_28570\RtmpOOtwMT/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 
  26.17    3.93   46.79