paper/paper.md
In eddelbuettel/rcppcnpy: Read-Write Support for 'NumPy' Files via 'Rcpp'
title: 'RcppCNPy: Read-Write Support for NumPy Files in R'
tags:
- Python
- NumPy
- R
- data transfer
authors:
- name: Dirk Eddelbuettel
orcid: 0000-0001-6419-907X
affiliation: Debian and R Projects
- name: Wush Wu
orcid: 0000-0001-5180-0567
affiliation: Institute of Electrical Engineering, National Taiwan University
date: 26 August 2016
bibliography: paper.bib
Summary
Python is a widely-used and popular programming
language. It is deployed in use cases ranging from simple scripting to larger-scale
application development. Python is also popular for
quantitative and scientific application due to the existence of extension modules such as
NumPy (which is shorthand for Numeric Python) and many other
packages for data analysis.
NumPy [@NumPy] is used to efficiently represent N-dimensional arrays, and
provides an efficient binary storage model for these files. In practice, N is often equal
to two, and matrices processed or generated in Python
can be stored in this form. As NumPy is popular, many project
utilize this file format.
R has no dedicated reading or writing functionality for these
type of files. However, Carl Rogers has provided a small C++ library called
cnpy [@CNPy]. Using the Rcpp modules feature in
Rcpp [@Eddelbuettel:2013:Rcpp,@CRAN:Rcpp],
we provide (some) features of this library to R via the
RcppCNPy package [@CRAN:RcppCNPy].
References
eddelbuettel/rcppcnpy documentation built on Jan. 4, 2024, 6:34 p.m.
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title: 'RcppCNPy: Read-Write Support for NumPy Files in R' tags: - Python - NumPy - R - data transfer authors: - name: Dirk Eddelbuettel orcid: 0000-0001-6419-907X affiliation: Debian and R Projects - name: Wush Wu orcid: 0000-0001-5180-0567 affiliation: Institute of Electrical Engineering, National Taiwan University date: 26 August 2016 bibliography: paper.bib
Summary
Python is a widely-used and popular programming language. It is deployed in use cases ranging from simple scripting to larger-scale application development. Python is also popular for quantitative and scientific application due to the existence of extension modules such as NumPy (which is shorthand for Numeric Python) and many other packages for data analysis.
NumPy [@NumPy] is used to efficiently represent N-dimensional arrays, and provides an efficient binary storage model for these files. In practice, N is often equal to two, and matrices processed or generated in Python can be stored in this form. As NumPy is popular, many project utilize this file format.
R has no dedicated reading or writing functionality for these type of files. However, Carl Rogers has provided a small C++ library called cnpy [@CNPy]. Using the Rcpp modules feature in Rcpp [@Eddelbuettel:2013:Rcpp,@CRAN:Rcpp], we provide (some) features of this library to R via the RcppCNPy package [@CRAN:RcppCNPy].
References
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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