Getting started with the PCMBaseCpp R-package

In PCMBaseCpp: Fast Likelihood Calculation for Phylogenetic Comparative Models

knitr::opts_chunk$set(echo = TRUE)

How to use the package?

There are two ways to use PCMBaseCpp:

Passing the function PCMInfoCpp as a metaI argument of PCMLik and/or PCMCreateLikelihood

library(PCMBase)
library(PCMBaseCpp)

system.time(llR <- PCMLik(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab))

system.time(llCpp <- PCMLik(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = PCMInfoCpp))

print(llR)
print(llCpp)

logLikFunR <- PCMCreateLikelihood(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab)

logLikFunCpp <- PCMCreateLikelihood(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = PCMInfoCpp)

metaICpp <- PCMInfoCpp(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab)

logLikFunCpp2 <- PCMCreateLikelihood(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = metaICpp)

set.seed(1, kind = "Mersenne-Twister", normal.kind = "Inversion")
randParam <- PCMParamRandomVecParams(PCMBaseTestObjects$model_MixedGaussian_ab)

system.time(llR <- logLikFunR(randParam))

system.time(llCpp <- logLikFunCpp(randParam))

system.time(llCpp2 <- logLikFunCpp2(randParam))

print(llR)
print(llCpp)
print(llCpp2)

Passing the meta-information object returned by PCMInfoCpp as a metaI argument of PCMLik and PCMCreateLikelihood

This is the recommended usage in the case of multiple likelihood evaluations, e.g. during model inference:

metaIR <- PCMInfo(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab)

metaICpp <- PCMInfoCpp(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab)

system.time(llR <- PCMLik(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = metaIR))

system.time(llCpp <- PCMLik(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = metaICpp))

print(llR)
print(llCpp)

logLikFunR <- PCMCreateLikelihood(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = metaIR)

logLikFunCpp <- PCMCreateLikelihood(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = metaICpp)

system.time(llR <- PCMLik(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = metaIR))

system.time(llCpp <- PCMLik(
  X = PCMBaseTestObjects$traits.ab.123, 
  tree = PCMBaseTestObjects$tree.ab,
  model = PCMBaseTestObjects$model_MixedGaussian_ab, 
  metaI = metaICpp))

print(llR)
print(llCpp)

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