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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# cpp11eigen <img src="man/figures/logo.svg" align="right" height="139" alt="" />
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[](https://app.codecov.io/gh/pachadotdev/cpp11eigen)
[](https://buymeacoffee.com/pacha)
[](https://CRAN.R-project.org/package=cpp11eigen)
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The goal of cpp11eigen is to provide a novel approach to use the [Eigen
C++ library](https://eigen.tuxfamily.org/index.php?title=Main_Page) by using the
header-only cpp11 R package and to simplify things for the end-user.
The idea is to pass matrices/vectors from R to C++, write pure C++/Eigen
code for the computation, and then export the result back to R with the proper
data structures.
This follows from the same goals as cpp11:
* Enforcing copy-on-write semantics.
* Improving the safety of using the R API from C++ code.
* Using UTF-8 strings everywhere.
* Applying newer C++11 features.
* Having a more straightforward, simpler implementation.
* Faster compilation time with lower memory requirements.
* Growing vectors more efficiently.
If this software is useful to you, please consider donating on
[Buy Me A Coffee](https://buymeacoffee.com/pacha). All donations will
be used to continue improving `cpp11eigen`.
## Installation
You can install the development version of cpp11eigen from GitHub:
``` r
remotes::install_github("pachadotdev/cpp11eigen")
```
## Examples
I have provided a package template for RStudio that also works with VS Code.
The idea of this package is to be naive and simple (like me).
From RStudio/VSCode create a new project and run:
```r
cpp11eigen::pkg_template()
```
Then follow the instructions from the README.
The vignettes contains detailed examples that I use to test `cpp11eigen`,
these include Ordinary Least Squares.
# Linear Algebra Libraries
Eigen supports OpenBLAS, Intel MKL, and the Accelerate framework (Mac). You
can install OpenBLAS on Debian-based systems with:
```sh
sudo apt-get install libopenblas-dev
```
You can also use other commands for your specific operating system.
To verify that R is using OpenBLAS, you can run `sessionInfo()` after restarting
R to check the BLAS/LAPACK libraries in use:
```r
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
```