MiniBenchmarkRvsCpp: Evaluate the likelihood calculation times for example trees...

In PCMBaseCpp: Fast Likelihood Calculation for Phylogenetic Comparative Models

Description

Evaluate the likelihood calculation times for example trees and data

Usage

MiniBenchmarkRvsCpp(data = PCMBaseCpp::benchmarkData, includeR = TRUE,
  includeTransformationTime = TRUE, nRepsCpp = 10L,
  listOptions = list(PCMBase.Lmr.mode = 11, PCMBase.Threshold.EV = 0,
  PCMBase.Threshold.SV = 0), doProf = FALSE, RprofR.out = "RprofR.out",
  RprofCpp.out = "RprofCpp.out")

Arguments

data	a 'data.frame' with at least the following columns: tree: a list column of phylo objects with an edge.part member set. X: a list column of k x N numerical matrices. model: a list column of PCM objects. Defaults: to 'benchmarkData', which is small data.table included with the PCMBaseCpp package.
includeR	logical (default TRUE) indicating if likelihood calculations in R should be included in the benchmark (can be slow).
includeTransformationTime	logical (default TRUE) indicating if the time for PCMApplyTransformation should be included in the benchmark.
nRepsCpp	: number of repetitions for the cpp likelihood calculation calls: a bigger value increases the precision of time estimation at the expense of longer running time for the benchmark. Defaults to 10.
listOptions	options to set before measuring the calculation times. Defaults to 'list(PCMBase.Lmr.mode = 11, PCMBase.Threshold.EV = 0, PCMBase.Threshold.SV = 0)'. 'PCMBase.Lmr.mode' corresponds to the parallel traversal mode for the tree traversal algorithm (see this page for possible values).
doProf	logical indicating if profiling should be activated (see Rprof from the utils R-package). Default: FALSE. Additional arguments to Rprof can be specified by assigning lists of arguments to the options 'PCMBaseCpp.ArgsRprofR' and 'PCMBaseCpp.ArgsRprofCpp'. The default values for both options is list(append = TRUE, line.profiling = TRUE).
RprofR.out, RprofCpp.out	character strings indicating Rprof.out files for the R and Cpp implementations; ignored if doProf is FALSE. Default values: 'RprofR.out' and 'Rprofcpp.out'.

Value

a data.frame.

Examples

library(PCMBase)
library(PCMBaseCpp)
library(data.table)

testData <- PCMBaseCpp::benchmarkData[1]
# original MGPM model
MiniBenchmarkRvsCpp(data = testData)

# original MGPM model and parallel mode
MiniBenchmarkRvsCpp(
data = testData,
listOptions = list(PCMBase.Lmr.mode = 21, PCMBase.Threshold.EV = 1e-9, 
PCMBase.Threshold.SV = 1e-9))

# single-trait data, original MGPM model and single mode and enabled option 
# PCMBase.Use1DClasses
MiniBenchmarkRvsCpp(
data = PCMBaseCpp::benchmarkData[1, list(
 tree, 
 X = lapply(X, function(x) x[1,, drop=FALSE]), 
 model = lapply(model, function(m) PCMExtractDimensions(m, dims = 1)))],
listOptions = list(
  PCMBase.Lmr.mode = 11, 
  PCMBase.Threshold.EV = 1e-9, 
  PCMBase.Threshold.SV = 1e-9,
  PCMBase.Use1DClasses = FALSE))

PCMBaseCpp documentation built on March 23, 2020, 1:06 a.m.