The next test compares the
speeds:
// [[Rcpp::export]]
NumericVector rowApply0(NumericMatrix&
x, const Function& FUN)
{
int n = x.nrow();
NumericVector result =
no_init(n);
for (int r = 0; r < n; r++)
{
result[r] = as<double>(FUN(x(r,
_) ) );
}
return result;
}
// [[Rcpp::export]]
NumericVector rowApply1(NumericMatrix&
x, const Function& FUN)
{
int n = x.nrow();
NumericVector result =
no_init(n);
for (int r = 0; r < n; r++)
{
Language call(FUN, x(r, _))
;
result[r] =
as<double>(call.fast_eval() );
}
return result;
}
// [[Rcpp::export]]
NumericVector rowApply2(NumericMatrix&
x, const Function& FUN)
{
int n = x.nrow();
NumericVector result =
no_init(n);
Language call(FUN,
R_NilValue);
Language::Proxy proxy(call,
1);
for (int r = 0; r < n; r++)
{
proxy = x(r, _) ;
result[r] =
as<double>(call.fast_eval() );
}
return result;
}
> M <- matrix(rnorm(15L),
nrow=3L);
> identical(rowMeans(M), apply(M, 1L,
mean));
[1] TRUE
> identical(rowMeans(M), rowApply0(M,
mean));
[1] TRUE
> identical(rowMeans(M), rowApply1(M,
mean));
[1] TRUE
> identical(rowMeans(M), rowApply2(M,
mean));
[1] TRUE
> benchmark(rowMeans(M),
+ apply(M, 1L,
mean),
+ rowApply0(M,
mean),
+ rowApply1(M,
mean),
+ rowApply2(M,
mean),
+
replications=300000L);
test replications elapsed
relative user.self sys.self user.child sys.child
3 rowApply0(M, mean) 300000 23.26
8.551 23.14 0 NA NA
2 apply(M, 1, mean) 300000 21.30
7.831 21.13 0 NA NA
4 rowApply1(M, mean) 300000 10.23
3.761 10.22 0 NA NA
5 rowApply2(M, mean) 300000 9.87
3.629 9.82 0 NA NA
1 rowMeans(M) 300000 2.72
1.000 2.72 0 NA NA
> M <- matrix(rnorm(1500L),
nrow=30L);
> benchmark(rowMeans(M),
+ apply(M, 1L,
mean),
+ rowApply0(M,
mean),
+ rowApply1(M,
mean),
+ rowApply2(M,
mean),
+
replications=30000L);
test replications elapsed
relative user.self sys.self user.child sys.child
3 rowApply0(M, mean) 30000 21.32
48.455 21.30 0 NA NA
2 apply(M, 1, mean) 30000 11.17
25.386 11.17 0 NA NA
4 rowApply1(M, mean) 30000 8.24
18.727 8.19 0 NA NA
5 rowApply2(M, mean) 30000 8.10
18.409 8.08 0 NA NA
1 rowMeans(M) 30000 0.44
1.000 0.43 0 NA NA
> M <- matrix(rnorm(150000L),
nrow=300L);
> benchmark(rowMeans(M),
+ apply(M, 1L,
mean),
+ rowApply0(M,
mean),
+ rowApply1(M,
mean),
+ rowApply2(M,
mean),
+
replications=3000L);
test replications elapsed
relative user.self sys.self user.child sys.child
3 rowApply0(M, mean) 3000 26.65
18.379 26.41 0.01 NA NA
2 apply(M, 1, mean) 3000 19.76
13.628 19.71 0.00 NA NA
4 rowApply1(M, mean) 3000 12.79
8.821 12.78 0.00 NA NA
5 rowApply2(M, mean) 3000 12.69
8.752 12.68 0.00 NA NA
1 rowMeans(M) 3000 1.45
1.000 1.45 0.00 NA NA
again, as Romain suggested, implementation
rowApply2 is faster than rowApply1, and rowApply0 (which triggers tryCatch) is
even slower than R's apply.
Thanks Romain !
_______________________________________________
Rcpp-devel mailing list
Rcpp-devel@lists.r-forge.r-project.org
https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
