improvements

[epclust.git] / epclust / src / WER.c

diff --git a/epclust/src/WER.c b/epclust/src/WER.c
deleted file mode 100644 (file)
index 36bfba7..0000000
--- a/epclust/src/WER.c
+++ /dev/null
@@ -1,117 +0,0 @@
-#include <stdlib.h>
-#include <math.h>
-#include <stdbool.h>
-
-#ifndef M_PI
-#define M_PI 3.14159265358979323846
-#endif
-
-// n: number of synchrones, m: length of a synchrone
-float computeWerDist(float* s1, float* s2, int n, int m)
-{
-       //TODO: automatic tune of all these parameters ? (for other users)
-       int nvoice = 4;
-       //noctave 2^13 = 8192 half hours ~ 180 days ; ~log2(ncol(synchrones))
-       int noctave = 13
-       // 4 here represent 2^5 = 32 half-hours ~ 1 day
-       //NOTE: default scalevector == 2^(0:(noctave * nvoice) / nvoice) * s0 (?)
-       //R: scalevector <- 2^(4:(noctave * nvoice) / nvoice + 1)
-       int* scalevector = (int*)malloc( (noctave*nvoice-4 + 1) * sizeof(int))
-       for (int i=4; i<=noctave*nvoice; i++)
-               scalevector[i-4] = pow(2., (float)i/nvoice + 1.);
-       //condition: ( log2(s0*w0/(2*pi)) - 1 ) * nvoice + 1.5 >= 1
-       int s0 = 2;
-       double w0 = 2*M_PI;
-       bool scaled = false;
-       int s0log = as.integer( (log2( s0*w0/(2*pi) ) - 1) * nvoice + 1.5 )
-       int totnoct = noctave + as.integer(s0log/nvoice) + 1
-
-
-
-
-
-///TODO: continue
-
-
-
-       computeCWT = function(i)
-       {
-               if (verbose)
-                       cat(paste("+++ Compute Rwave::cwt() on serie ",i,"\n", sep=""))
-               ts <- scale(ts(synchrones[i,]), center=TRUE, scale=scaled)
-               totts.cwt = Rwave::cwt(ts,totnoct,nvoice,w0,plot=0)
-               ts.cwt = totts.cwt[,s0log:(s0log+noctave*nvoice)]
-               #Normalization
-               sqs <- sqrt(2^(0:(noctave*nvoice)/nvoice)*s0)
-               sqres <- sweep(ts.cwt,2,sqs,'*')
-               sqres / max(Mod(sqres))
-       }
-
-       if (parll)
-       {
-               cl = parallel::makeCluster(ncores_clust)
-               parallel::clusterExport(cl,
-                       varlist=c("synchrones","totnoct","nvoice","w0","s0log","noctave","s0","verbose"),
-                       envir=environment())
-       }
-
-       # (normalized) observations node with CWT
-       Xcwt4 <-
-               if (parll)
-                       parallel::parLapply(cl, seq_len(n), computeCWT)
-               else
-                       lapply(seq_len(n), computeCWT)
-
-       if (parll)
-               parallel::stopCluster(cl)
-
-       Xwer_dist <- bigmemory::big.matrix(nrow=n, ncol=n, type="double")
-       fcoefs = rep(1/3, 3) #moving average on 3 values (TODO: very slow! correct?!)
-       if (verbose)
-               cat("*** Compute WER distances from CWT\n")
-
-       #TODO: computeDistances(i,j), et répartir les n(n-1)/2 couples d'indices
-       #là c'est trop déséquilibré
-
-       computeDistancesLineI = function(i)
-       {
-               if (verbose)
-                       cat(paste("   Line ",i,"\n", sep=""))
-               for (j in (i+1):n)
-               {
-                       #TODO: 'circular=TRUE' is wrong, should just take values on the sides; to rewrite in C
-                       num <- filter(Mod(Xcwt4[[i]] * Conj(Xcwt4[[j]])), fcoefs, circular=TRUE)
-                       WX <- filter(Mod(Xcwt4[[i]] * Conj(Xcwt4[[i]])), fcoefs, circular=TRUE)
-                       WY <- filter(Mod(Xcwt4[[j]] * Conj(Xcwt4[[j]])), fcoefs, circular=TRUE)
-                       wer2    <- sum(colSums(num)^2) / sum( sum(colSums(WX) * colSums(WY)) )
-                       if (parll)
-                               synchronicity::lock(m)
-                       Xwer_dist[i,j] <- sqrt(delta * ncol(Xcwt4[[1]]) * (1 - wer2))
-                       Xwer_dist[j,i] <- Xwer_dist[i,j]
-                       if (parll)
-                               synchronicity::unlock(m)
-               }
-               Xwer_dist[i,i] = 0.
-       }
-
-       parll = (requireNamespace("synchronicity",quietly=TRUE)
-               && parll && Sys.info()['sysname'] != "Windows")
-       if (parll)
-               m <- synchronicity::boost.mutex()
-
-       ignored <-
-               if (parll)
-               {
-                       parallel::mclapply(seq_len(n-1), computeDistancesLineI,
-                               mc.cores=ncores_clust, mc.allow.recursive=FALSE)
-               }
-               else
-                       lapply(seq_len(n-1), computeDistancesLineI)
-       Xwer_dist[n,n] = 0.
-
-       mat_dists = matrix(nrow=n, ncol=n)
-       #TODO: avoid this loop?
-       for (i in 1:n)
-               mat_dists[i,] = Xwer_dist[i,]
-       mat_dists
-