Rcpp Version 0.12.14
benchmarkLongley.r
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1 #!/usr/bin/env r
2 #
3 # Comparison benchmark -- using old and small Longley data set
4 #
5 # This shows how Armadillo improves on the previous version using GNU GSL,
6 # and how both are doing better than lm.fit()
7 #
8 # Copyright (C) 2010 Dirk Eddelbuettel and Romain Francois
9 #
10 # This file is part of Rcpp.
11 #
12 # Rcpp is free software: you can redistribute it and/or modify it
13 # under the terms of the GNU General Public License as published by
14 # the Free Software Foundation, either version 2 of the License, or
15 # (at your option) any later version.
16 #
17 # Rcpp is distributed in the hope that it will be useful, but
18 # WITHOUT ANY WARRANTY; without even the implied warranty of
19 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
20 # GNU General Public License for more details.
21 #
22 # You should have received a copy of the GNU General Public License
23 # along with Rcpp. If not, see <http://www.gnu.org/licenses/>.
24 
25 suppressMessages(library(utils))
26 suppressMessages(library(Rcpp))
27 suppressMessages(library(inline))
28 suppressMessages(library(datasets))
29 
30 source("lmArmadillo.R")
31 source("lmGSL.R")
32 
33 data(longley)
34 
35 longleydm <- data.matrix(data.frame(intcp=1, longley))
36 X <- longleydm[,-8]
37 y <- as.numeric(longleydm[,8])
38 
39 N <- 1000
40 
41 lmgsl <- lmGSL()
42 lmarma <- lmArmadillo()
43 
44 tlm <- mean(replicate(N, system.time( lmfit <- lm(y ~ X - 1) )["elapsed"]), trim=0.05)
45 tlmfit <- mean(replicate(N, system.time(lmfitfit <- lm.fit(X, y))["elapsed"]), trim=0.05)
46 tlmgsl <- mean(replicate(N, system.time(lmgsl(y, X))["elapsed"]), trim=0.05)
47 tlmarma <- mean(replicate(N, system.time(lmarma(y, X))["elapsed"]), trim=0.05)
48 
49 res <- c(tlm, tlmfit, tlmgsl, tlmarma)
50 data <- data.frame(results=res, ratios=tlm/res)
51 rownames(data) <- c("lm", "lm.fit", "lmGSL", "lmArma")
52 cat("For Longley\n")
53 print(t(data))
54 print(t(1/data[,1,drop=FALSE])) # regressions per second
55