From: Benjamin Auder <benjamin.auder@somewhere>
Date: Mon, 30 Jan 2017 12:35:25 +0000 (+0100)
Subject: somewhat unroll the code in WER distances computations
X-Git-Url: https://git.auder.net/variants/current/css/doc/scripts/getGraph_%22%20%20%20this.image%20%20%20%22.php?a=commitdiff_plain;h=47395e4f93feadfb1b8f6ab11742a4616b32c1d5;p=epclust.git

somewhat unroll the code in WER distances computations
---

diff --git a/old_C_code/stage2_UNFINISHED/src/05_cluster2stepWER.r b/old_C_code/stage2_UNFINISHED/src/05_cluster2stepWER.r
index 9b55da1..69939b2 100644
--- a/old_C_code/stage2_UNFINISHED/src/05_cluster2stepWER.r
+++ b/old_C_code/stage2_UNFINISHED/src/05_cluster2stepWER.r
@@ -42,14 +42,14 @@ rm(synchros09, nas)
 ## 2. Compute WER distance matrix ####
 
 ## _.a CWT -- Filtering the lowest freqs (>6m) ####
-# nvoice   <- 4
+nvoice   <- 4
 # # noctave4 = 2^13 = 8192 half hours ~ 180 days
-# noctave4 <- adjust.noctave(N = delta, dt = 1, s0 = 2,
+noctave4 <- adjust.noctave(N = delta, dt = 1, s0 = 2,
 #                           tw = 0, noctave = 13)
 # # 4 here represent 2^5 = 32 half-hours ~ 1 day
-# scalevector4  <- 2^(4:(noctave4 * nvoice) / nvoice) * 2
-# lscvect4      <- length(scalevector4)
-# lscvect <- lscvect4  # i should clean my code: werFam demands a lscvect
+scalevector4  <- 2^(4:(noctave4 * nvoice) / nvoice) * 2
+lscvect4      <- length(scalevector4)
+lscvect <- lscvect4  # i should clean my code: werFam demands a lscvect
 
 
 #17000 colonnes coeff 1, puis 17000 coeff 2... [non : dans chaque tranche du cube]
@@ -95,6 +95,96 @@ rm(synchros09, nas)
 # save(Xwer_dist, file = "../res/2009_synchros200WER.Rdata")
 # save(Xwer_dist, file = "../res/2009_synchros200-randomWER.Rdata")
 
+
+
+#lignes 59 à 91 "dépliées" :
+Xcwt4   <- toCWT(conso, noctave = noctave4, dt = 1,
+                 scalevector = scalevector4,
+                 lt = delta, smooth = FALSE, 
+                 nvoice = nvoice)      # observations node with CWT
+ 
+ #matrix:
+ ############Xcwt2 <- matrix(0.0, nrow= n, ncol= 2 + delta * lscvect)
+ Xcwt2 <- matrix(NA_complex_, nrow= n, ncol= 2 + length((c(Xcwt4[,,1]))))
+ 
+ #NOTE: delta et lscvect pourraient etre gardés à part (communs)
+ for(i in 1:n) 
+    Xcwt2[i,] <- c(delta, lscvect, Xcwt4[,,i] / max(Mod(Xcwt4[,,i])) ) 
+ 
+ #rm(conso, Xcwt4); gc()
+ 
+ ## _.b WER^2 distances  ########
+ Xwer_dist    <- matrix(0.0, n, n)
+ for(i in 1:(n - 1)){
+  mat1   <- vect2mat(Xcwt2[i,])
+
+ #NOTE: vect2mat = as.matrix ?! (dans aux.R)
+  vect2mat <- function(vect){
+                 vect <- as.vector(vect)
+                 matrix(vect[-(1:2)], delta, lscvect)
+               }
+ 
+ for(j in (i + 1):n){
+     mat2 <- vect2mat(Xcwt2[j,])
+     num     <- Mod(mat1 * Conj(mat2))
+     WX      <- Mod(mat1 * Conj(mat1))
+     WY      <- Mod(mat2 * Conj(mat2))
+     smsmnum <- smCWT(num, scalevector = scalevector4)
+     smsmWX  <- smCWT(WX,  scalevector = scalevector4)
+     smsmWY  <- smCWT(WY,  scalevector = scalevector4)
+     wer2    <- sum(colSums(smsmnum)^2)  /
+       sum( sum(colSums(smsmWX) * colSums(smsmWY)) )
+     Xwer_dist[i, j] <- sqrt(delta * lscvect * (1 - wer2))
+     Xwer_dist[j, i] <- Xwer_dist[i, j]
+   }
+ }
+ diag(Xwer_dist) <- numeric(n)
+
+#fonction smCWT (dans aux.R)
+  smCWT <- function(CWT, sw=  0,  tw=  0, swabs= 0,
+                       nvoice= 12, noctave= 2, s0= 2, w0= 2*pi, 
+					   lt= 24, dt= 0.5, scalevector )
+		 {
+#         noctave  <- adjust.noctave(lt, dt, s0, tw, noctave)
+#         scalevector  <- 2^(0:(noctave * nvoice) / nvoice) * s0
+         wsp     <- Mod(CWT)  
+         smwsp   <- smooth.matrix(wsp, swabs)
+         smsmwsp <- smooth.time(smwsp, tw, dt, scalevector)
+         smsmwsp
+       }
+
+ #dans sowas.R
+smooth.matrix <- function(wt,swabs){
+  
+  if (swabs != 0)
+    smwt <- t(filter(t(wt),rep(1,2*swabs+1)/(2*swabs+1)))
+  else
+    smwt <- wt
+  
+  smwt
+  
+}
+smooth.time <- function(wt,tw,dt,scalevector){
+  
+  smwt <- wt
+  
+  if (tw != 0){
+    for (i in 1:length(scalevector)){
+      
+      twi <- as.integer(scalevector[i]*tw/dt)
+      smwt[,i] <- filter(wt[,i],rep(1,2*twi+1)/(2*twi+1))
+      
+    }
+  } 
+  smwt
+}
+
+#et filter() est dans stats::
+
+#cf. filters en C dans : https://svn.r-project.org/R/trunk/src/library/stats/src/filter.c
+
+
+
 load("../res/2009_synchros200WER.Rdata")
 #load("../res/2009_synchros200-randomWER.Rdata")