EVOLUTION-MANAGER

Edit File: benchmarkLongley.r

#!/usr/bin/r # # Comparison benchmark -- using old and small Longley data set # # This shows how Armadillo improves on the previous version using GNU GSL, # and how both are doing better than lm.fit() # # Copyright (C) 2010 Dirk Eddelbuettel and Romain Francois # # This file is part of Rcpp. # # Rcpp is free software: you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 2 of the License, or # (at your option) any later version. # # Rcpp 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. # # You should have received a copy of the GNU General Public License # along with Rcpp. If not, see <http://www.gnu.org/licenses/>. suppressMessages(library(utils)) suppressMessages(library(Rcpp)) suppressMessages(library(inline)) suppressMessages(library(datasets)) source("lmArmadillo.R") source("lmGSL.R") data(longley) longleydm <- data.matrix(data.frame(intcp=1, longley)) X <- longleydm[,-8] y <- as.numeric(longleydm[,8]) N <- 1000 lmgsl <- lmGSL() lmarma <- lmArmadillo() tlm <- mean(replicate(N, system.time( lmfit <- lm(y ~ X - 1) )["elapsed"]), trim=0.05) tlmfit <- mean(replicate(N, system.time(lmfitfit <- lm.fit(X, y))["elapsed"]), trim=0.05) tlmgsl <- mean(replicate(N, system.time(lmgsl(y, X))["elapsed"]), trim=0.05) tlmarma <- mean(replicate(N, system.time(lmarma(y, X))["elapsed"]), trim=0.05) res <- c(tlm, tlmfit, tlmgsl, tlmarma) data <- data.frame(results=res, ratios=tlm/res) rownames(data) <- c("lm", "lm.fit", "lmGSL", "lmArma") cat("For Longley\n") print(t(data)) print(t(1/data[,1,drop=FALSE])) # regressions per second