# Getting started with the PCMBaseCpp R-package

#### 2020-03-23

# 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)

    ## Loading required package: Rcpp

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

    ##    user  system elapsed
    ##   0.088   0.002   0.091

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

    ##    user  system elapsed
    ##   0.004   0.000   0.004

    print(llR)

    ## [1] -206.4146
    ## attr(,"X0")
    ## [1] 5 2 1

    print(llCpp)

    ## [1] -206.4146
    ## attr(,"X0")
    ## [1] 5 2 1

    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))

    ##    user  system elapsed
    ##   0.069   0.000   0.069

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

    ##    user  system elapsed
    ##   0.002   0.000   0.002

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

    ##    user  system elapsed
    ##   0.002   0.000   0.002

    print(llR)

    ## [1] -598.092
    ## attr(,"X0")
    ## [1] -4.689827 -2.557522  1.457067

    print(llCpp)

    ## [1] -598.092
    ## attr(,"X0")
    ## [1] -4.689827 -2.557522  1.457067

    print(llCpp2)

    ## [1] -598.092
    ## attr(,"X0")
    ## [1] -4.689827 -2.557522  1.457067

## 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))

    ##    user  system elapsed
    ##    0.07    0.00    0.07

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

    ##    user  system elapsed
    ##   0.002   0.000   0.001

    print(llR)

    ## [1] -206.4146
    ## attr(,"X0")
    ## [1] 5 2 1

    print(llCpp)

    ## [1] -206.4146
    ## attr(,"X0")
    ## [1] 5 2 1

    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))

    ##    user  system elapsed
    ##   0.069   0.000   0.068

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

    ##    user  system elapsed
    ##   0.002   0.000   0.001

    print(llR)

    ## [1] -206.4146
    ## attr(,"X0")
    ## [1] 5 2 1

    print(llCpp)

    ## [1] -206.4146
    ## attr(,"X0")
    ## [1] 5 2 1