@@ -27,7 +27,7 @@ update.expectation.dmat <- function(PARAM, update.logL = TRUE){
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# ## WCC: temp spmd
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tmp.1 <- as.matrix(.pmclustEnv $ W.dmat )
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tmp.2 <- sweep(tmp.1 , 2 , PARAM $ log.ETA , FUN = " +" )
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- .pmclustEnv $ U.dmat <- as.ddmatrix(tmp.2 )
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+ .pmclustEnv $ U.dmat <- pbdDMAT :: as.ddmatrix(tmp.2 )
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# ## WCC: original
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# .pmclustEnv$Z.dmat <- exp(.pmclustEnv$U.dmat)
@@ -37,7 +37,7 @@ update.expectation.dmat <- function(PARAM, update.logL = TRUE){
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# ## WCC: temp spmd
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tmp.1 <- as.matrix(.pmclustEnv $ U.dmat )
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tmp.2 <- exp(tmp.1 )
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- .pmclustEnv $ Z.dmat <- as.ddmatrix(tmp.2 )
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+ .pmclustEnv $ Z.dmat <- pbdDMAT :: as.ddmatrix(tmp.2 )
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# ## WCC: original
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# tmp.id <- rowSums(.pmclustEnv$U.dmat < .pmclustEnv$CONTROL$exp.min) == K |
@@ -67,7 +67,7 @@ update.expectation.dmat <- function(PARAM, update.logL = TRUE){
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if (tmp.flag == 1 ){
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tmp.2 <- matrix (tmp.2 , nrow = 1 )
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}
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- tmp.dmat <- as.ddmatrix(tmp.2 )
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+ tmp.dmat <- pbdDMAT :: as.ddmatrix(tmp.2 )
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if (tmp.flag == 1 ){
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# ## WCC: original
@@ -106,7 +106,7 @@ update.expectation.dmat <- function(PARAM, update.logL = TRUE){
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tmp.id <- which(tmp.id )
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tmp.2 <- as.matrix(.pmclustEnv $ Z.dmat )
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tmp.2 [tmp.id ,] <- tmp.1
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- .pmclustEnv $ Z.dmat <- as.ddmatrix(tmp.2 )
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+ .pmclustEnv $ Z.dmat <- pbdDMAT :: as.ddmatrix(tmp.2 )
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}
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# ## WCC: original
@@ -124,7 +124,7 @@ update.expectation.dmat <- function(PARAM, update.logL = TRUE){
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# ## WCC: temp spmd
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tmp.1 <- as.matrix(.pmclustEnv $ Z.dmat )
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tmp.2 <- tmp.1 / .pmclustEnv $ W.rowSums
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- .pmclustEnv $ Z.dmat <- as.ddmatrix(tmp.2 )
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+ .pmclustEnv $ Z.dmat <- pbdDMAT :: as.ddmatrix(tmp.2 )
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# ## For semi-supervised clustering.
@@ -345,7 +345,7 @@ em.update.class.dmat <- function(){
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# ## WCC: temp spmd
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# tmp.1 <- as.matrix(.pmclustEnv$Z.dmat)
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# tmp.2 <- matrix(apply(tmp.1, 1, which.max), ncol = 1)
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- # tmp.3 <- as.ddmatrix(tmp.2)
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+ # tmp.3 <- pbdDMAT:: as.ddmatrix(tmp.2)
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# .pmclustEnv$CLASS.dmat <- tmp.3
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invisible ()
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