java.lang.Exception: Could not find a proper state to initialise. Perhaps try another seed.

[Carlos Pavón]

Hi y'all! I'm trying to run a *BEAST analysis to obtain the species tree. There are three genes: one with five partitions and the other two with three partitions each. While trying to run the analysis I get the following messages:

Random number seed: 1428525666282

File: brevgroup.xml seed: 1428525666282 threads: 1
WARNING: tree interrogated for taxa, but the tree was not initialised properly. To fix this, specify the taxonset input
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path
Start likelihood: -Infinity after 10 initialisation attempts
P(posterior) = -Infinity (was NaN)
    P(speciescoalescent) = 796.258441255537 (was NaN)
        P(SpeciesTreePopSize.Species) = 220.896751541963 (was NaN)
        P(treePrior.t:mkl1) = 198.28718592304384 (was NaN)
        P(treePrior.t:nd1) = 178.88273187845547 (was NaN)
        P(treePrior.t:r35) = 198.19177191207467 (was NaN)
    P(prior) = -Infinity (was NaN)
        P(YuleModel.t:Species) = 49.55201970409367 (was NaN)
        P(YuleBirthRatePrior.t:Species) = -3.551267582712942 (was NaN)
        P(GammaShapePrior.s:1st) = -1.0 (was NaN)
        P(GammaShapePrior.s:2nd) = -1.0 (was NaN)
        P(GammaShapePrior.s:3rd) = -1.0 (was NaN)
        P(GammaShapePrior.s:RIB) = -1.0 (was NaN)
        P(GammaShapePrior.s:trs) = -1.0 (was NaN)
        P(KappaPrior.s:1M) = -1.8653600339742873 (was NaN)
        P(KappaPrior.s:1R) = -1.8653600339742873 (was NaN)
        P(KappaPrior.s:1st) = -1.8653600339742873 (was NaN)
        P(KappaPrior.s:2M) = -1.8653600339742873 (was NaN)
        P(KappaPrior.s:2nd) = -1.8653600339742873 (was NaN)
        P(KappaPrior.s:3R) = -1.8653600339742873 (was NaN)
        P(KappaPrior.s:RIB) = -1.8653600339742873 (was NaN)
        P(KappaPrior.s:trs) = -1.8653600339742873 (was NaN)
        P(kappa1Prior.s:3M) = -1.8653600339742873 (was NaN)
        P(kappa1Prior.s:3rd) = -1.8653600339742873 (was NaN)
        P(kappa2Prior.s:3M) = -1.8653600339742873 (was NaN)
        P(kappa2Prior.s:3rd) = -1.8653600339742873 (was NaN)
        P(popMean.prior) = -Infinity (was NaN)
        P(MeanRatePrior.c:1M) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:1R) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:1st) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:2M) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:2R) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:2nd) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:3M) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:3R) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:3rd) = -1.8862943611198906 (was NaN)
        P(MeanRatePrior.c:trs) = -1.8862943611198906 (was NaN)
        P(ucldStdevPrior.c:1M) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:1R) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:1st) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:2M) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:2R) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:2nd) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:3M) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:3R) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:3rd) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:RIB) = 0.819364145120802 (was NaN)
        P(ucldStdevPrior.c:trs) = 0.819364145120802 (was NaN)
    P(likelihood) = NaN (was NaN)
        P(treeLikelihood.RIB) = NaN (was NaN)
        P(treeLikelihood.trs) = NaN (was NaN)
        P(treeLikelihood.1st) = NaN (was NaN)
        P(treeLikelihood.2nd) = NaN (was NaN)
        P(treeLikelihood.3rd) = NaN (was NaN)
        P(treeLikelihood.1M) = NaN (was NaN)
        P(treeLikelihood.2M) = NaN (was NaN)
        P(treeLikelihood.3M) = NaN (was NaN)
        P(treeLikelihood.1R) = NaN (was NaN)
        P(treeLikelihood.2R) = NaN (was NaN)
        P(treeLikelihood.3R) = NaN (was NaN)
java.lang.Exception: Could not find a proper state to initialise. Perhaps try another seed.
    at beast.core.MCMC.run(Unknown Source)
    at beast.app.BeastMCMC.run(Unknown Source)
    at beast.app.beastapp.BeastMain.<init>(Unknown Source)
    at beast.app.beastapp.BeastMain.main(Unknown Source)
    at beast.app.beastapp.BeastLauncher.main(Unknown Source)

Does anyone know what could it be? I read in other threads this usually happens when checking "sample from prior". I tried with the option but checked and unchecked and still nothing. Any ideas?

Best,
Carlos

[Remco Bouckaert]

Hi Carlos,

The output shows that the popMean prior is infinity. The default prior for population mean is the 1/X prior. You might want to check the initial value for the popMean parameter and make sure it is positive and inside its range specified by the upper and lower bounds if these are specified.

Hope this helps,

Remco

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[Carlos Pavón]

Thanks Remco!
 I changed the popMean prior from the default following some publications and when BEAST couldn't run I searched in this group and one of the advices was to specify the prior as infinity. I may have done something wrong. Following your advice, I used the default option (1/x) for the prior and it worked.
Thanks!
Carlos

[Maura P]

Similar problem:

Random number seed: 1437513992827

File: Smallrun.xml seed: 1437513992827 threads: 1

  Ignoring ambiguities in tree likelihood.

  With 522 unique site patterns.

  Using rescaling scheme : dynamic

  Ignoring ambiguities in tree likelihood.

  With 515 unique site patterns.

  Using rescaling scheme : dynamic

  Ignoring ambiguities in tree likelihood.

  With 87 unique site patterns.

  Using rescaling scheme : dynamic

  Ignoring ambiguities in tree likelihood.

  With 133 unique site patterns.

  Using rescaling scheme : dynamic

  Ignoring ambiguities in tree likelihood.

  With 96 unique site patterns.

  Using rescaling scheme : dynamic

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version:   Ignoring ambiguities in tree likelihood.

  With 102 unique site patterns.

  Using rescaling scheme : dynamic

  Ignoring ambiguities in tree likelihood.

  With 348 unique site patterns.

  Using rescaling scheme : dynamic

  Ignoring ambiguities in tree likelihood.

  With 101 unique site patterns.

  Using rescaling scheme : dynamic

  Ignoring ambiguities in tree likelihood.

  With 155 unique site patterns.

  Using rescaling scheme : dynamic

2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

  Using BEAGLE version: 2.1.2 resource 0: CPU

    with instance flags:  PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

Start likelihood: -Infinity after 10 initialisation attempts

P(posterior) = -Infinity (was NaN)

P(speciescoalescent) = -1774.4628798340377 (was NaN)

P(SpeciesTreePopSize.Species) = 449.1072089178492 (was NaN)

P(treePrior.t:Cytb) = -3748.909991954309 (was NaN)

P(treePrior.t:ENC) = 218.44121550884623 (was NaN)

P(treePrior.t:Glyt) = 218.3816586385932 (was NaN)

P(treePrior.t:Myh6) = 218.10716280547962 (was NaN)

P(treePrior.t:Rag1) = 218.32215562308087 (was NaN)

P(treePrior.t:Rh) = 217.6620518308895 (was NaN)

P(treePrior.t:SH3PX3) = 218.06735224769778 (was NaN)

P(treePrior.t:xsrc) = 216.3583065478348 (was NaN)

P(prior) = -Infinity (was NaN)

P(YuleModel.t:Species) = 169.71800542700765 (was NaN)

P(YuleBirthRatePrior.t:Species) = -5.077558475475514 (was NaN)

P(GammaShapePrior.s:Cytb) = -1.0 (was NaN)

P(GammaShapePrior.s:ND2) = -1.0 (was NaN)

P(KappaPrior.s:ENC) = -1.8653600339742873 (was NaN)

P(KappaPrior.s:Glyt) = -1.8653600339742873 (was NaN)

P(KappaPrior.s:Myh6) = -1.8653600339742873 (was NaN)

P(KappaPrior.s:Rh) = -1.8653600339742873 (was NaN)

P(KappaPrior.s:SH3PX3) = -1.8653600339742873 (was NaN)

P(KappaPrior.s:xsrc) = -1.8653600339742873 (was NaN)

P(kappa1Prior.s:Rag1) = -1.8653600339742873 (was NaN)

P(kappa2Prior.s:Rag1) = -1.8653600339742873 (was NaN)

P(popMean.prior) = 6.135962592750254 (was NaN)

P(PropInvariantPrior.s:Cytb) = 0.0 (was NaN)

P(RateACPrior.s:Cytb) = -3.184008455701433 (was NaN)

P(RateACPrior.s:ND2) = -3.184008455701433 (was NaN)

P(RateAGPrior.s:Cytb) = -3.1686658147294304 (was NaN)

P(RateAGPrior.s:ND2) = -3.1686658147294304 (was NaN)

P(RateATPrior.s:Cytb) = -3.184008455701433 (was NaN)

P(RateATPrior.s:ND2) = -3.184008455701433 (was NaN)

P(RateCGPrior.s:Cytb) = -3.184008455701433 (was NaN)

P(RateCGPrior.s:ND2) = -3.184008455701433 (was NaN)

P(RateGTPrior.s:Cytb) = -3.184008455701433 (was NaN)

P(RateGTPrior.s:ND2) = -3.184008455701433 (was NaN)

P(UCMeanRatePrior.c:ENC) = 0.0 (was NaN)

P(UCMeanRatePrior.c:Glyt) = 0.0 (was NaN)

P(UCMeanRatePrior.c:Myh6) = 0.0 (was NaN)

P(UCMeanRatePrior.c:ND2) = 0.0 (was NaN)

P(UCMeanRatePrior.c:Rag1) = 0.0 (was NaN)

P(UCMeanRatePrior.c:Rh) = 0.0 (was NaN)

P(UCMeanRatePrior.c:SH3PX3) = 0.0 (was NaN)

P(UCMeanRatePrior.c:xsrc) = 0.0 (was NaN)

P(MeanRatePrior.c:Cytb) = 0.0 (was NaN)

P(ucldStdevPrior.c:Cytb) = -0.08307167868818878 (was NaN)

P(ingroup.prior) = -Infinity (was NaN)

P(likelihood) = NaN (was NaN)

P(treeLikelihood.Cytb) = NaN (was NaN)

P(treeLikelihood.ND2) = NaN (was NaN)

P(treeLikelihood.ENC) = NaN (was NaN)

P(treeLikelihood.Glyt) = NaN (was NaN)

P(treeLikelihood.SH3PX3) = NaN (was NaN)

P(treeLikelihood.Myh6) = NaN (was NaN)

P(treeLikelihood.Rag1) = NaN (was NaN)

P(treeLikelihood.Rh) = NaN (was NaN)

P(treeLikelihood.xsrc) = NaN (was NaN)

java.lang.Exception: Could not find a proper state to initialise. Perhaps try another seed.

at beast.core.MCMC.run(Unknown Source)

at beast.app.BeastMCMC.run(Unknown Source)

at beast.app.beastapp.BeastMain.<init>(Unknown Source)

at beast.app.beastapp.BeastMain.main(Unknown Source)

at beast.app.beastapp.BeastLauncher.main(Unknown Source)

Help is appreciated.

Maura

[Andrew Nguyen]

I've tried a bunch of things before I posted, but I get the same error. I'd appreciate any suggestions. Thanks!