Readmat requires a full license and installation of Matlab(R)
if you don’t have this then the R.matlab (Bengtsson 2018) package is
much more suitable. The only goal of this package is to provide a
potentially faster approach, especially when dealing with large
matrices.
This package is definitely under development!
A data cube of 400 x 400 x 400 values.
readmat::read_mat(readmat::get_matlab("double-large-cube.mat"))[[1]] |>
dim()
#> 1 object(s) found in this MAT file.
#> Object has 3 dimensions of size: 400, 400, 400, with type: double.
#> [1] 400 400 400Comparing R.matlab and readmat.
| package | min | median | itr/sec | mem_alloc | n_itr | n_gc | total_time |
|---|---|---|---|---|---|---|---|
| R.matlab | 3.31 | 3.36 | 1.00 | 3.98 | 10 | 0 | 27.775926 |
| readmat | 1.00 | 1.00 | 3.33 | 1.00 | 5 | 5 | 4.173084 |
You can install the development version of readmat from GitHub with:
# install.packages("devtools")
devtools::install_github("MartinSchobben/readmat")The construction of the R (R Core Team 2022) package readmat and
associated documentation was aided by the packages; devtools (Wickham
et al. 2021) and cpp11 (Hester and François 2021).
Bengtsson, Henrik. 2018. R.matlab: Read and Write MAT Files and Call MATLAB from Within r. https://github.com/HenrikBengtsson/R.matlab.
Hester, Jim, and Romain François. 2021. Cpp11: A c++11 Interface for r’s c Interface. https://CRAN.R-project.org/package=cpp11.
R Core Team. 2022. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Wickham, Hadley, Jim Hester, Winston Chang, and Jennifer Bryan. 2021. Devtools: Tools to Make Developing r Packages Easier. https://CRAN.R-project.org/package=devtools.