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-rw-r--r--run.R25
1 files changed, 15 insertions, 10 deletions
diff --git a/run.R b/run.R
index 80234e1..c943b17 100644
--- a/run.R
+++ b/run.R
@@ -352,11 +352,13 @@ run.manipulation.evo <- function(X, Dx, labels, sample.indices, k, ds, output.di
# Perform manipulation
loginfo("Running manipulation procedures")
- loginfo("Ys.f: Silhouette")
- Dx.m <- automated.silh(X[sample.indices, ], labels[sample.indices])
- Ys.silhouette <- scale.Ys(cmdscale(Dx.m))
- Ys.m <- Ys.silhouette
- write.table(Ys.m, file.path(output.dir, ds$name, "Ysf-silhouette.tbl"), row.names=F, col.names=F)
+ if (!is.null(ds$labels.file)) {
+ loginfo("Ys.f: Silhouette")
+ Dx.m <- automated.silh(X[sample.indices, ], labels[sample.indices])
+ Ys.silhouette <- scale.Ys(cmdscale(Dx.m))
+ Ys.m <- Ys.silhouette
+ write.table(Ys.m, file.path(output.dir, ds$name, "Ysf-silhouette.tbl"), row.names=F, col.names=F)
+ }
loginfo("Ys.f: NP")
Ys.np <- scale.Ys(Rtsne(X[sample.indices, ], perplexity=k)$Y)
@@ -384,7 +386,9 @@ run.technique.evo <- function(X, Dx, labels, k, ds, tech, n.samples, output.dir)
loginfo("Technique: %s", tech$name)
dir.create.safe(file.path(output.dir, ds$name, tech$name))
- classes <- as.factor(labels)
+ if (!is.null(ds$labels.file)) {
+ classes <- as.factor(labels)
+ }
# Load sample indices...
sample.indices <- read.table(file.path(output.dir, ds$name, "sample-indices.tbl"))$V1
@@ -608,7 +612,7 @@ run.evo <- function(datasets,
Dx <- as.matrix(Dx)
loginfo("Extracting control points")
- sample.indices <- extract.CPs(Dx)
+ sample.indices <- extract.CPs(Dx, k=max(sqrt(n)*3, ncol(X)))
write.table(sample.indices, file.path(output.dir, ds$name, "sample-indices.tbl"), row.names=F, col.names=F)
# Computes each manipulation target
@@ -738,9 +742,10 @@ addHandler(writeToFile,
file=args[1],
level="FINEST")
-# The alpha and omega
+# CP positioning improvement
run(datasets, techniques, output.dir=output.dir, initial.manipulation=F)
-run.evo(datasets, techniques, output.dir=output.dir)
-
# Compute all confidence intervals
confidence.intervals(datasets, techniques, measures, output.dir)
+
+# CP improvement evolution experiment
+run.evo(datasets, techniques, output.dir=output.dir)