R/create_test_ns_output.R
In richelbilderbeek/rbeast2: Control 'BEAST2'
Defines functions
create_test_ns_output
Documented in
create_test_ns_output
#' Create NS testing output
#'
#' Create testing output similar to when running a 'BEAST2' run
#' with nested sampling
#' @author Richèl J.C. Bilderbeek
#' @seealso Use \link{parse_beast2_output_to_ns} to parse
#' this output to a Nested Sampling result.
#' See \link[beautier]{create_ns_mcmc} to see how to do a marginal
#' likelihood estimation using Nested Sampling.
#' @examples
#' beastier::remove_beaustier_folders()
#' beastier::check_empty_beaustier_folders()
#'
#' create_test_ns_output()
#'
#' beastier::remove_beaustier_folders()
#' beastier::check_empty_beaustier_folders()
#' @export
create_test_ns_output <- function() {
c(
"[/usr/lib/jvm/java-8-oracle/bin/java, -Djava.library.path=/usr/local/lib:/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib, -cp, ::/home/richel/.beast/2.5/MODEL_SELECTION/lib/MODEL_SELECTION.addon.jar:/home/richel/.beast/2.5/BEASTLabs/lib/BEASTlabs.addon.jar:/home/richel/.beast/2.5/NS/lib/NS.addon.jar:/home/richel/.beast/2.5/BEAST/lib/beast.src.jar:/home/richel/.beast/2.5/BEAST/lib/beast.jar, beast.app.beastapp.BeastMain, nested_sampling.xml]", # nolint output is long
"",
" BEAST v2.5.0, 2002-2018",
" Bayesian Evolutionary Analysis Sampling Trees",
" Designed and developed by",
" Remco Bouckaert, Alexei J. Drummond, Andrew Rambaut & Marc A. Suchard",
" ",
" Department of Computer Science",
" University of Auckland",
" remco@cs.auckland.ac.nz",
" alexei@cs.auckland.ac.nz",
" ",
" Institute of Evolutionary Biology",
" University of Edinburgh",
" a.rambaut@ed.ac.uk",
" ",
" David Geffen School of Medicine",
" University of California, Los Angeles",
" msuchard@ucla.edu",
" ",
" Downloads, Help & Resources:",
" http://beast2.org/",
" ",
" Source code distributed under the GNU Lesser General Public License:",
" http://github.com/CompEvol/beast2",
" ",
" BEAST developers:",
" Alex Alekseyenko, Trevor Bedford, Erik Bloomquist, Joseph Heled, ",
" Sebastian Hoehna, Denise Kuehnert, Philippe Lemey, Wai Lok Sibon Li, ",
"Gerton Lunter, Sidney Markowitz, Vladimir Minin, Michael Defoin Platel, ",
" Oliver Pybus, Tim Vaughan, Chieh-Hsi Wu, Walter Xie",
" ",
" Thanks to:",
" Roald Forsberg, Beth Shapiro and Korbinian Strimmer",
"",
"Random number seed: 1539258042094",
"",
"File: nested_sampling.xml seed: 1539258042094 threads: 1",
"61430_aco: 78 4",
"626029_aco: 78 4",
"630116_aco: 78 4",
"630210_aco: 78 4",
"B25702_aco: 78 4",
"Alignment(anthus_aco_sub)",
" 5 taxa",
" 78 sites",
" 9 patterns",
"",
"Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path",
"TreeLikelihood(treeLikelihood.anthus_aco_sub0) uses BeerLikelihoodCore4",
" Alignment(anthus_aco_sub): [taxa, patterns, sites] = [5, 9, 78]",
"===============================================================================", # nolint output is long
"Citations for this model:",
"",
"Patricio Maturana, Brendon J. Brewer, Steffen Klaere, Remco Bouckaert. Model selection and parameter inference in phylogenetics using Nested Sampling. Systematic Biology, syy050, 2018", # nolint output is long
"",
"===============================================================================", # nolint output is long
"Counting 19 parameters",
"replacing logger tracelog with NSLogger",
"Writing file anthus_aco_sub.trees",
" Sample posterior ESS(posterior) likelihood prior", # nolint output is long
"Writing file anthus_aco_sub.log",
"Start likelihood 0: -225.2488738545589 ",
"1 particles initialised",
" 0 -140.6759 N -157.4874 16.8115 --", # nolint output is long
"ML: -158.32601908408833 Information: 0.8385606384288167",
" 1 -124.4630 2.0 -143.0242 18.5611 --", # nolint output is long
"ML: -144.86277038390745 Information: 1.8385386453449868",
" 2 -124.6624 3.0 -141.6496 16.9872 --", # nolint output is long
"ML: -143.96492404000415 Information: 1.7551898946725117",
" 3 -124.9536 4.0 -139.0497 14.0961 --", # nolint output is long
"ML: -142.59510010333074 Information: 2.7422179576086307",
" 24 -125.0399 14.8 -137.0128 11.9729 --", # nolint output is long
"ML: -141.98047696172614 Information: 2.8349216678190885",
" 25 -124.7614 15.4 -137.0127 12.2512 --", # nolint output is long
"ML: -141.98047696086337 Information: 2.8349216687952605",
" 26 -124.7070 15.9 -137.0124 12.3054 --", # nolint output is long
"ML: -141.98047696054587 Information: 2.8349216691561026",
" 27 -124.6071 16.2 -137.0106 12.4035 --", # nolint output is long
"ML: -141.98047696042886 Information: 2.8349216692884056",
"28<=10000&& (28<2.0*2.8349216692884056*1||Math.abs(-141.98047696042886 - -141.98047696054587)/Math.abs(-141.98047696042886) > 1.0E-12", # nolint output is long
"Finished in 28 steps!",
"Marginal likelihood: -141.31236790862764 (bootstrap SD=1.4240215445106443)", # nolint output is long
"Marginal likelihood: -140.98848039195855 (subsample SD=1.8638865000383444)", # nolint output is long
"Marginal likelihood: -141.1644574217485(1.1601428428211327)",
"Information: 2.8349216692884056",
"SD: 1.6837225630395305",
"",
"Operator Tuning #accept #reject Pr(m) Pr(acc|m)", # nolint output is long
"ScaleOperator(YuleBirthRateScaler.t:anthus_aco_sub) 0.75000 4797 998 0.04000 0.82778 Try setting scaleFactor to about 0.562", # nolint output is long
"ScaleOperator(YuleModelTreeScaler.t:anthus_aco_sub) 0.50000 1116 4748 0.04000 0.19031 ", # nolint output is long
"ScaleOperator(YuleModelTreeRootScaler.t:anthus_aco_sub) 0.50000 887 4915 0.04000 0.15288 ", # nolint output is long
"Uniform(YuleModelUniformOperator.t:anthus_aco_sub) - 11869 46191 0.40000 0.20443 ", # nolint output is long
"SubtreeSlide(YuleModelSubtreeSlide.t:anthus_aco_sub) 1.00000 128 28742 0.20000 0.00443 Try decreasing size to about 0.5", # nolint output is long
"Exchange(YuleModelNarrow.t:anthus_aco_sub) - 3007 26046 0.20000 0.10350 ", # nolint output is long
"Exchange(YuleModelWide.t:anthus_aco_sub) - 180 5641 0.04000 0.03092 ", # nolint output is long
"WilsonBalding(YuleModelWilsonBalding.t:anthus_aco_sub) - 92 5643 0.04000 0.01604 ", # nolint output is long
"",
" Tuning: The value of the operator's tuning parameter, or '-' if the operator can't be optimized.", # nolint output is long
" #accept: The total number of times a proposal by this operator has been accepted.", # nolint output is long
" #reject: The total number of times a proposal by this operator has been rejected.", # nolint output is long
" Pr(m): The probability this operator is chosen in a step of the MCMC (i.e. the normalized weight).", # nolint output is long
" Pr(acc|m): The acceptance probability (#accept as a fraction of the total proposals for this operator).", # nolint output is long
"",
"",
"Total calculation time: 0.823 seconds",
"End likelihood: 12.388056869575024",
"Producing posterior samples",
"",
"Marginal likelihood: -141.3000915386624 sqrt(H/N)=(NaN)=?=SD=(1.4593051179523482) Information: -0.19242514244311712", # nolint output is long
"Max ESS: 5.659472090348357",
"",
"",
"Processing 28 trees from file.",
"Log file written to anthus_aco_sub.posterior.trees",
"Done!",
"",
"Marginal likelihood: -141.31271098696405 sqrt(H/N)=(NaN)=?=SD=(1.462246661656647) Information: -0.1353639346412825", # nolint output is long
"Max ESS: 5.4945059635784155",
"",
"",
"Log file written to anthus_aco_sub.posterior.log",
"Done!"
)
}
richelbilderbeek/rbeast2 documentation built on Sept. 30, 2023, 9:39 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions create_test_ns_output
Documented in create_test_ns_output
#' Create NS testing output
#'
#' Create testing output similar to when running a 'BEAST2' run
#' with nested sampling
#' @author Richèl J.C. Bilderbeek
#' @seealso Use \link{parse_beast2_output_to_ns} to parse
#' this output to a Nested Sampling result.
#' See \link[beautier]{create_ns_mcmc} to see how to do a marginal
#' likelihood estimation using Nested Sampling.
#' @examples
#' beastier::remove_beaustier_folders()
#' beastier::check_empty_beaustier_folders()
#'
#' create_test_ns_output()
#'
#' beastier::remove_beaustier_folders()
#' beastier::check_empty_beaustier_folders()
#' @export
create_test_ns_output <- function() {
c(
"[/usr/lib/jvm/java-8-oracle/bin/java, -Djava.library.path=/usr/local/lib:/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib, -cp, ::/home/richel/.beast/2.5/MODEL_SELECTION/lib/MODEL_SELECTION.addon.jar:/home/richel/.beast/2.5/BEASTLabs/lib/BEASTlabs.addon.jar:/home/richel/.beast/2.5/NS/lib/NS.addon.jar:/home/richel/.beast/2.5/BEAST/lib/beast.src.jar:/home/richel/.beast/2.5/BEAST/lib/beast.jar, beast.app.beastapp.BeastMain, nested_sampling.xml]", # nolint output is long
"",
" BEAST v2.5.0, 2002-2018",
" Bayesian Evolutionary Analysis Sampling Trees",
" Designed and developed by",
" Remco Bouckaert, Alexei J. Drummond, Andrew Rambaut & Marc A. Suchard",
" ",
" Department of Computer Science",
" University of Auckland",
" remco@cs.auckland.ac.nz",
" alexei@cs.auckland.ac.nz",
" ",
" Institute of Evolutionary Biology",
" University of Edinburgh",
" a.rambaut@ed.ac.uk",
" ",
" David Geffen School of Medicine",
" University of California, Los Angeles",
" msuchard@ucla.edu",
" ",
" Downloads, Help & Resources:",
" http://beast2.org/",
" ",
" Source code distributed under the GNU Lesser General Public License:",
" http://github.com/CompEvol/beast2",
" ",
" BEAST developers:",
" Alex Alekseyenko, Trevor Bedford, Erik Bloomquist, Joseph Heled, ",
" Sebastian Hoehna, Denise Kuehnert, Philippe Lemey, Wai Lok Sibon Li, ",
"Gerton Lunter, Sidney Markowitz, Vladimir Minin, Michael Defoin Platel, ",
" Oliver Pybus, Tim Vaughan, Chieh-Hsi Wu, Walter Xie",
" ",
" Thanks to:",
" Roald Forsberg, Beth Shapiro and Korbinian Strimmer",
"",
"Random number seed: 1539258042094",
"",
"File: nested_sampling.xml seed: 1539258042094 threads: 1",
"61430_aco: 78 4",
"626029_aco: 78 4",
"630116_aco: 78 4",
"630210_aco: 78 4",
"B25702_aco: 78 4",
"Alignment(anthus_aco_sub)",
" 5 taxa",
" 78 sites",
" 9 patterns",
"",
"Failed to load BEAGLE library: no hmsbeagle-jni in java.library.path",
"TreeLikelihood(treeLikelihood.anthus_aco_sub0) uses BeerLikelihoodCore4",
" Alignment(anthus_aco_sub): [taxa, patterns, sites] = [5, 9, 78]",
"===============================================================================", # nolint output is long
"Citations for this model:",
"",
"Patricio Maturana, Brendon J. Brewer, Steffen Klaere, Remco Bouckaert. Model selection and parameter inference in phylogenetics using Nested Sampling. Systematic Biology, syy050, 2018", # nolint output is long
"",
"===============================================================================", # nolint output is long
"Counting 19 parameters",
"replacing logger tracelog with NSLogger",
"Writing file anthus_aco_sub.trees",
" Sample posterior ESS(posterior) likelihood prior", # nolint output is long
"Writing file anthus_aco_sub.log",
"Start likelihood 0: -225.2488738545589 ",
"1 particles initialised",
" 0 -140.6759 N -157.4874 16.8115 --", # nolint output is long
"ML: -158.32601908408833 Information: 0.8385606384288167",
" 1 -124.4630 2.0 -143.0242 18.5611 --", # nolint output is long
"ML: -144.86277038390745 Information: 1.8385386453449868",
" 2 -124.6624 3.0 -141.6496 16.9872 --", # nolint output is long
"ML: -143.96492404000415 Information: 1.7551898946725117",
" 3 -124.9536 4.0 -139.0497 14.0961 --", # nolint output is long
"ML: -142.59510010333074 Information: 2.7422179576086307",
" 24 -125.0399 14.8 -137.0128 11.9729 --", # nolint output is long
"ML: -141.98047696172614 Information: 2.8349216678190885",
" 25 -124.7614 15.4 -137.0127 12.2512 --", # nolint output is long
"ML: -141.98047696086337 Information: 2.8349216687952605",
" 26 -124.7070 15.9 -137.0124 12.3054 --", # nolint output is long
"ML: -141.98047696054587 Information: 2.8349216691561026",
" 27 -124.6071 16.2 -137.0106 12.4035 --", # nolint output is long
"ML: -141.98047696042886 Information: 2.8349216692884056",
"28<=10000&& (28<2.0*2.8349216692884056*1||Math.abs(-141.98047696042886 - -141.98047696054587)/Math.abs(-141.98047696042886) > 1.0E-12", # nolint output is long
"Finished in 28 steps!",
"Marginal likelihood: -141.31236790862764 (bootstrap SD=1.4240215445106443)", # nolint output is long
"Marginal likelihood: -140.98848039195855 (subsample SD=1.8638865000383444)", # nolint output is long
"Marginal likelihood: -141.1644574217485(1.1601428428211327)",
"Information: 2.8349216692884056",
"SD: 1.6837225630395305",
"",
"Operator Tuning #accept #reject Pr(m) Pr(acc|m)", # nolint output is long
"ScaleOperator(YuleBirthRateScaler.t:anthus_aco_sub) 0.75000 4797 998 0.04000 0.82778 Try setting scaleFactor to about 0.562", # nolint output is long
"ScaleOperator(YuleModelTreeScaler.t:anthus_aco_sub) 0.50000 1116 4748 0.04000 0.19031 ", # nolint output is long
"ScaleOperator(YuleModelTreeRootScaler.t:anthus_aco_sub) 0.50000 887 4915 0.04000 0.15288 ", # nolint output is long
"Uniform(YuleModelUniformOperator.t:anthus_aco_sub) - 11869 46191 0.40000 0.20443 ", # nolint output is long
"SubtreeSlide(YuleModelSubtreeSlide.t:anthus_aco_sub) 1.00000 128 28742 0.20000 0.00443 Try decreasing size to about 0.5", # nolint output is long
"Exchange(YuleModelNarrow.t:anthus_aco_sub) - 3007 26046 0.20000 0.10350 ", # nolint output is long
"Exchange(YuleModelWide.t:anthus_aco_sub) - 180 5641 0.04000 0.03092 ", # nolint output is long
"WilsonBalding(YuleModelWilsonBalding.t:anthus_aco_sub) - 92 5643 0.04000 0.01604 ", # nolint output is long
"",
" Tuning: The value of the operator's tuning parameter, or '-' if the operator can't be optimized.", # nolint output is long
" #accept: The total number of times a proposal by this operator has been accepted.", # nolint output is long
" #reject: The total number of times a proposal by this operator has been rejected.", # nolint output is long
" Pr(m): The probability this operator is chosen in a step of the MCMC (i.e. the normalized weight).", # nolint output is long
" Pr(acc|m): The acceptance probability (#accept as a fraction of the total proposals for this operator).", # nolint output is long
"",
"",
"Total calculation time: 0.823 seconds",
"End likelihood: 12.388056869575024",
"Producing posterior samples",
"",
"Marginal likelihood: -141.3000915386624 sqrt(H/N)=(NaN)=?=SD=(1.4593051179523482) Information: -0.19242514244311712", # nolint output is long
"Max ESS: 5.659472090348357",
"",
"",
"Processing 28 trees from file.",
"Log file written to anthus_aco_sub.posterior.trees",
"Done!",
"",
"Marginal likelihood: -141.31271098696405 sqrt(H/N)=(NaN)=?=SD=(1.462246661656647) Information: -0.1353639346412825", # nolint output is long
"Max ESS: 5.4945059635784155",
"",
"",
"Log file written to anthus_aco_sub.posterior.log",
"Done!"
)
}
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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