rcppmlpack / rcppmlpack2 Goto Github PK

> sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux

Matrix products: default
BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so

locale:
 [1] LC_CTYPE=en_AU.UTF-8       LC_NUMERIC=C               LC_TIME=en_AU.UTF-8        LC_COLLATE=en_AU.UTF-8     LC_MONETARY=en_AU.UTF-8    LC_MESSAGES=en_AU.UTF-8   
 [7] LC_PAPER=en_AU.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.0        rstudioapi_0.8    magrittr_1.5      usethis_1.4.0     devtools_2.0.1    pkgload_1.0.2     R6_2.3.0          rlang_0.3.0.1     tools_3.5.1      
[10] pkCould yougbuild_1.0.2    sessioninfo_1.1.1 cli_1.0.1         withr_2.1.2       remotes_2.0.2     assertthat_0.2.0  digest_0.6.18     rprojroot_1.3-2   crayon_1.3.4     
[19] processx_3.2.0    callr_3.0.0       base64enc_0.1-3   fs_1.2.6          ps_1.2.1          curl_3.2          memoise_1.1.0     glue_1.3.0        compiler_3.5.1   
[28] desc_1.2.0        backports_1.1.2   prettyunits_1.0.2

> devtools::install_github("rcppmlpack/rcppmlpack2")
Downloading GitHub repo rcppmlpack/rcppmlpack2@master
✔  checking for file ‘/tmp/RtmpTGbarz/remotes691f797e3951/rcppmlpack-rcppmlpack2-4af4b01/DESCRIPTION’ ...
─  preparing ‘RcppMLPACK’:
✔  checking DESCRIPTION meta-information ...
─  cleaning src
─  running ‘cleanup’
─  checking for LF line-endings in source and make files and shell scripts
─  checking for empty or unneeded directories
─  looking to see if a ‘data/datalist’ file should be added
─  building ‘RcppMLPACK_3.0.1-0.0.tar.gz’
   
Installing package into ‘/root/R/x86_64-pc-linux-gnu-library/3.5.1’
(as ‘lib’ is unspecified)
* installing *source* package ‘RcppMLPACK’ ...
checking whether the C++ compiler works... yes
checking for C++ compiler default output file name... a.out
checking for suffix of executables... 
checking whether we are cross compiling... no
checking for suffix of object files... o
checking whether we are using the GNU C++ compiler... yes
checking whether g++ accepts -g... yes
checking how to run the C++ preprocessor... g++ -E
checking for gcc... gcc
checking whether we are using the GNU C compiler... yes
checking whether gcc accepts -g... yes
checking for gcc option to accept ISO C89... none needed
checking whether we are using the GNU C++ compiler... (cached) yes
checking whether g++ accepts -g... (cached) yes
checking whether g++ supports C++11 features by default... yes
checking for pkg-config... yes
checking for grep that handles long lines and -e... /bin/grep
checking for egrep... /bin/grep -E
checking for ANSI C header files... yes
checking for sys/types.h... yes
checking for sys/stat.h... yes
checking for stdlib.h... yes
checking for string.h... yes
checking for memory.h... yes
checking for strings.h... yes
checking for inttypes.h... yes
checking for stdint.h... yes
checking for unistd.h... yes
checking mlpack/core.hpp usability... no
checking mlpack/core.hpp presence... no
checking for mlpack/core.hpp... no
configure: error: Cannot find MLPACK headers.
ERROR: configuration failed for package ‘RcppMLPACK’
* removing ‘/root/R/x86_64-pc-linux-gnu-library/3.5.1/RcppMLPACK’
* restoring previous ‘/root/R/x86_64-pc-linux-gnu-library/3.5.1/RcppMLPACK’
Error in i.p(...) : 
  (converted from warning) installation of package ‘/tmp/RtmpTGbarz/file691f4fd5f752/RcppMLPACK_3.0.1-0.0.tar.gz’ had non-zero exit status

#include <RcppMLPACK.h>				// MLPACK, Rcpp and RcppArmadillo

#include <mlpack/methods/logistic_regression/logistic_regression.hpp> 	// particular algorithm used here

// [[Rcpp::depends(RcppMLPACK)]]

// [[Rcpp::export]]
Rcpp::List logisticRegression(const arma::mat& train,
                              const arma::irowvec& labels,
                              const Rcpp::Nullable<Rcpp::NumericMatrix>& test = R_NilValue) {
    
    // MLPACK wants Row<size_t> which is an unsigned representation
    // that R does not have
    arma::Row<size_t> labelsur, resultsur;

    // TODO: check that all values are non-negative
    labelsur = arma::conv_to<arma::Row<size_t>>::from(labels);

    // Initialize with the default arguments.
    // TODO: support more arguments>
    mlpack::regression::LogisticRegression<> lrc(train, labelsur);
    
    arma::vec parameters = lrc.Parameters();

    Rcpp::List return_val;
    
    if (test.isNotNull()) {
        arma::mat test2 = Rcpp::as<arma::mat>(test);
        lrc.Classify(test2, resultsur);
        arma::vec results = arma::conv_to<arma::vec>::from(resultsur);
        return_val = Rcpp::List::create(Rcpp::Named("parameters") = parameters,
                                        Rcpp::Named("results") = results);
    } else {
        return_val = Rcpp::List::create(Rcpp::Named("parameters") = parameters);
    }

    return return_val;

}

logisticRegression(matrix(c(1, 2, 3, 1, 2, 3), nrow=2, byrow=TRUE), c(1L, 1L, 0L))

#include <RcppMLPACK.h>				// MLPACK, Rcpp and RcppArmadillo

#include <mlpack/methods/naive_bayes/naive_bayes_classifier.hpp> 	// particular algorithm used here

// [[Rcpp::depends(RcppMLPACK)]]

// [[Rcpp::export]]
arma::irowvec naiveBayesClassifier(const arma::mat& train,
                                   const arma::mat& test,
                                   const arma::irowvec& labels,
                                   const int& classes) {
    
    // MLPACK wants Row<size_t> which is an unsigned representation
    // that R does not have
    arma::Row<size_t> labelsur, resultsur;

    // TODO: check that all values are non-negative
    labelsur = arma::conv_to<arma::Row<size_t>>::from(labels);

    // Initialize with the default arguments.
    // TODO: support more arguments>
    mlpack::naive_bayes::NaiveBayesClassifier<> nbc(train, labelsur, classes);
    
    nbc.Classify(test, resultsur);
    
    arma::irowvec results = arma::conv_to<arma::irowvec>::from(resultsur);
    
    return results;
}