Thanks, Uwe, Peter, and Ray, for taking the time to look into this.
Just to wrap up this thread, and so that others may benefit,
I tried writing both a R code version and an inline C version.
Tested on a 8GB Ubuntu 64amd box, R 2.81, the speed difference was:
104secs vs 0.534secs, or the C version was about 200 times faster.
#
-------------------------------------------------------------------------------------
require( inline )
require( RUnit )
set.seed(1)
x <- runif(1e+7)
.c.code <-
" SEXP res, inp;
int cnt = 0, i;
PROTECT(inp = AS_NUMERIC(p)); cnt++;
PROTECT(res = Rf_duplicate(inp)); cnt++;
int nx = INTEGER(GET_DIM(inp))[0], ny =
INTEGER(GET_DIM(inp))[1];
double* pdata = REAL(AS_NUMERIC(inp));
double* rdata = REAL(res); double last;
for (int y = 0; y < ny; y++) {
last = 0.0;
for (int x = 0; x < nx; x++) {
i = x + y*nx;
if ( pdata[i]>0.75 ) {
rdata[i] = 1.0;
} else if ( pdata[i]<0.25 ) {
rdata[i] = -1.0;
} else if ( last==1 && pdata[i]<0.5 ) {
rdata[i] = 0.0;
} else if ( last==-1 && pdata[i]>0.5 ) {
rdata[i] = 0.0;
} else {
rdata[i] = last;
}
last = rdata[i];
}
}
UNPROTECT(cnt);
return res;";
.c.code.raw <- cfunction(signature(p="matrix"), .c.code);
# NOTE: I converted to matrix because I actually want to do many columns,
one at a time
ccode <- function( x ) { as.vector( .c.code.raw( p=as.matrix( x ) )); }
rcode <- function( x ) {
n <- length( x )
y <- rep(NA, n)
yprev <- 0;
for ( i in (1:n)) {
if ( x[i]>0.75 ) {
y[i] <- 1;
} else if ( x[i]<0.25 ) {
y[i] <- -1;
} else if ( yprev==1 & x[i]<0.5) {
y[i] <- 0;
} else if ( yprev==-1 & x[i]>0.5) {
y[i] <- 0;
} else {
y[i] <- yprev
}
yprev <- y[i];
}
y;
}
system.time( r.result <- rcode( x ));
system.time( c.result <- ccode( x ));
checkEquals( r.result, c.result );
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