major folder reorganisation, R pkg is now epclust/ at first level. Experimental usage...

[epclust.git] / old_C_code / stage2 / src / unused / aux.r

diff --git a/old_C_code/stage2/src/unused/aux.r b/old_C_code/stage2/src/unused/aux.r
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+####################################################################
+##
+## File:        aux.r
+##
+## Description: Miscelaneous functions for clustering with kcca
+##
+## Modified:    june 2010
+##
+####################################################################
+
+
+  #######################################################
+
+  # Transforms a matrix of data (one observation by row)
+  #     into an array where position[ , , i] gives
+  #     the smoothed modulus of the i-th cwt observation 
+
+  ########################################################
+
+
+##NOTE: renvoie une matrice 3D
+  toCWT  <- function(X, sw=  0,  tw=  0, swabs= 0,
+                       nvoice= 12, noctave= 5, 
+                       s0= 2, w0= 2*pi, lt= 24, dt= 0.5,
+                       spectra = FALSE, smooth = TRUE,
+                       scaled  = FALSE,
+                     scalevector)
+     { noctave  <- adjust.noctave(lt, dt, s0, tw, noctave)
+       if(missing(scalevector)) 
+          scalevector  <- 2^(0:(noctave * nvoice) / nvoice) * s0
+       res <- lapply(1:nrow(X), function(n)
+           { tsX         <- ts( X[n,] )
+             tsCent      <- tsX - mean(tsX)
+             if(scaled)  tsCent <- ts(scale(tsCent))           
+             tsCent.cwt  <- cwt.ts(tsCent, s0, noctave, nvoice, w0)
+             tsCent.cwt
+           } )
+          if( spectra ) res <- lapply(res, function(l) Mod(l)^2 )
+          if( smooth  ) res <- lapply(res, smCWT, swabs = swabs,
+                                      tw = tw, dt = dt, 
+                                      scalevector = scalevector)
+       resArray <- array(NA, c(nrow(res[[1]]), ncol(res[[1]]),
+                               length(res)))
+       for( l in 1:length(res) ) resArray[ , , l] <- res[[l]]
+       resArray
+     }
+
+
+  # ===============================================================
+
+  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
+       }
+
+
+  # ===============================================================
+
+  toDWT <- function(x, filter.number = 6, family = "DaubLeAsymm")
+{ x2   <- spline(x, n = 2^ceiling( log(length(x), 2) ),
+            method = 'natural')$y
+  Dx2 <- wd(x2, family = family, filter.number = filter.number)$D
+               Dx2
+}
+
+  # ===============================================================
+
+  contrib <- function(x) 
+      { J   <- log( length(x)+1, 2)
+        nrj <- numeric(J)
+        t0  <- 1
+        t1  <- 0
+        for( j in 1:J ) {
+          t1     <- t1 + 2^(J-j)
+          nrj[j] <- sqrt( sum( x[t0:t1]^2 ) )
+          t0     <- t1 + 1
+        }
+        return(nrj)  
+         }
+
+
+    # ========================================= distance for coh ===
+
+  coherence <- function( x, y)
+       { J <- log(length(x) + 1, 2)
+            t0 <- 1
+                sg2_x <- 0
+                sg2_y <- 0
+                sg_xy <- 0
+            for(j in 0:(J - 1))
+                {  t1 <- t0 + 2^(J - j)/2  - 1
+                   tt <- t0:t1
+                   sg2_x <- sg2_x + mean(x[t0:t1]^2)
+                       sg2_y <- sg2_y + mean(y[t0:t1]^2)
+                       sg_xy <- sg_xy + mean(x[t0:t1] * y[t0:t1])
+            t0 <- t1 + 1
+                }
+               res <- sg_xy^2 / sg2_x / sg2_y
+               res
+          }
+
+
+  vect2mat <- function(vect){
+                 vect <- as.vector(vect)
+                 matrix(vect[-(1:2)], delta, lscvect)
+               }
+
+
+  # =========================================  # myimg for graphics 
+  jet.colors <- colorRampPalette(c("#00007F", "blue", "#007FFF", 
+                                "cyan", "#7FFF7F", "yellow", 
+                                "#FF7F00", "red", "#7F0000"))
+
+  myimg <- function(MAT, x = 1:nrow(MAT), y = 1:col(MAT), ... )
+              filled.contour(  x = x, y = y, z = MAT, 
+                              xlab= 'Time', ylab= 'scale',
+                              color.palette = jet.colors,
+                              ... )
+
+