PCMBaseCpp
This is a fast C++ backend for the PCMBase R-package.
Installation
The package needs a C++ 11 compiler and Rcpp to be installed in you R-environment. Once this is done, you can install the most recent version of the package from github:
devtools::install_github("venelin/PCMBaseCpp")
If you experience problems installing the package from github, you may try installing a possibly older version from CRAN:
install.packages("PCMBaseCpp")
Once the package is installed, use the function BenchmarkRvsCpp to
evaluate the gain in speed of the likelihood calculation on your
machine, relative to the R implementation:
library(PCMBaseCpp)
library(data.table)
options(digits = 4)
# Depending on your use case, you can change the number of traits, as well as the
# other arguments:
benchRes <- BenchmarkRvsCpp(ks = 2, includeParallelMode = FALSE, verbose = TRUE)
# Example output:
# Performing benchmark for k: 2 ; optionSet: serial / 1D-multiv. ...
# k modelType N R mode logLik logLikCpp timeR timeCpp
# 1: 2 MGPM (A-F) 10 2 11 -7.416e+02 -7.416e+02 0.010 0.0007
# 2: 2 MGPM (A-F) 100 4 11 -4.294e+03 -4.294e+03 0.107 0.0016
# 3: 2 MGPM (A-F) 1000 11 11 -1.700e+05 -1.700e+05 1.221 0.0095
# 4: 2 MGPM (A-F) 10000 11 11 -1.210e+06 -1.210e+06 12.443 0.0795
# 5: 2 BM (B) 10 2 11 -4.451e+03 -4.451e+03 0.010 0.0003
# 6: 2 BM (B) 100 4 11 -8.427e+03 -8.427e+03 0.082 0.0008
# 7: 2 BM (B) 1000 11 11 -1.830e+04 -1.830e+04 0.847 0.0064
# 8: 2 BM (B) 10000 11 11 -6.574e+05 -6.574e+05 8.414 0.0663
# 9: 2 OU (E) 10 2 11 -1.126e+04 -1.126e+04 0.016 0.0006
# 10: 2 OU (E) 100 4 11 -8.486e+05 -8.486e+05 0.147 0.0015
# 11: 2 OU (E) 1000 11 11 -1.234e+06 -1.234e+06 1.505 0.0096
# 12: 2 OU (E) 10000 11 11 -1.058e+07 -1.058e+07 15.062 0.0854
For further examples, read the Getting started guide and the reference available on the package homepage.
Citing PCMBase
To give credit to the PCMBase package in a publication, please cite the following articles:
Mitov, V., & Stadler, T. (2018). Parallel likelihood calculation for phylogenetic comparative models: The SPLITT C++ library. Methods in Ecology and Evolution, 2041–210X.13136. http://doi.org/10.1111/2041-210X.13136
Mitov, V., Bartoszek, K., Asimomitis, G., & Stadler, T. (2019). Fast likelihood calculation for multivariate Gaussian phylogenetic models with shifts. Theor. Popul. Biol. https://doi.org/10.1016/j.tpb.2019.11.005
Used 3rd party libraries
The PCMBaseCpp R-package uses the following R-packages and C++ libraries:
- For tree processing in C++: The SPLITT library (Mitov and Stadler 2018);
- For data processing in R: data.table v1.12.2 (Dowle and Srinivasan 2019);
- For algebraic manipulation: The Armadillo C++ template library (Sanderson and Curtin 2016) and its port to R RcppArmadillo v0.9.700.2.0 (Eddelbuettel et al. 2019);
- For unit-testing: testthat v2.1.1 (Wickham 2019), covr v3.2.1 (Hester 2018);
- For documentation and web-site generation: roxygen2 v6.1.1 (Wickham, Danenberg, and Eugster 2018), pkgdown v1.3.0 (Wickham and Hesselberth 2018);
Licence and copyright
Copyright 2016-2019 Venelin Mitov
Source code to PCMBaseCpp is made available under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. PCMBaseCpp is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.