Added custom color scales; new automatic manipulation mechanism (Schaefer et al.); More data saved on each run.

1 files changed, 99 insertions, 38 deletions

diff --git a/tests.R b/tests.R
index f313b7b..4c073a0 100644
--- a/tests.R
+++ b/tests.R
@@ -4,14 +4,34 @@ require(mp)
 
 source("measures.R")
 
-automated.m <- function(D, labels) {
-  D.m <- D
+#automated.m <- function(D, labels) {
+#  D.m <- D
+#  for (label in unique(labels)) {
+#    same.label <- labels == label
+#    D.m[same.label, same.label] <- D[same.label, same.label] * 0.1
+#  }
+#
+#  D.m
+#}
+automated.m <- function(Xs, labels) {
+  n <- nrow(Xs)
+  p <- ncol(Xs)
+  Xs <- cbind(Xs, matrix(data=0, nrow=n, ncol=p))
   for (label in unique(labels)) {
-    same.label <- labels == label
-    D.m[same.label, same.label] <- D[same.label, same.label] * 0.1
+    for (j in 1:p) {
+      Xs[labels == label, j + p] <- mean(Xs[labels == label, j])
+    }
   }
 
-  D.m
+  dist(Xs)
+}
+
+color_scale.blue_orange <- function(name) {
+  scale_colour_gradient(name = name, high = "#376092", low = "#e46c0a", space = "Lab")
+}
+
+color_scale.gradient2 <- function(name) {
+  scale_colour_gradient2(name = name, mid = "#dddddd", space = "Lab")
 }
 
 test <- function(file, suffix, output.dir) {
@@ -62,6 +82,12 @@ test <- function(file, suffix, output.dir) {
   precision <- klDivergence(Q, P)
   recall <- klDivergence(P, Q)
 
+  measures <- rbind(data.frame(mean=mean(np), median=median(np), sd=sd(np)),
+                    data.frame(mean=mean(silh), median=median(silh), sd=sd(silh)),
+                    data.frame(mean=mean(precision), median=median(precision), sd=sd(precision)),
+                    data.frame(mean=mean(recall), median=median(recall), sd=sd(recall)))
+  write.table(measures, paste(output.dir, suffix, "-measures.csv", sep=""), row.names=F)
+
   if (!(all(is.finite(np)) &&
       all(is.finite(silh)) &&
       all(is.finite(precision)) &&
@@ -71,48 +97,59 @@ test <- function(file, suffix, output.dir) {
 
   # Plot results
   message("\tPlotting results")
-  color_scale <- scale_colour_gradient(high = "#376092", low = "#e46c0a", space = "Lab")
-  shape_scale <- scale_shape_manual(values = 1:nlevels(classes))
+  shape_scale <- scale_shape_manual(name = "Classe", values = 1:nlevels(classes))
   Ys <- cbind(as.data.frame(Ys), classes.s)
   Y  <- cbind(as.data.frame(Y), classes, np, silh, precision, recall)
   p.s <- ggplot(Ys) +
       theme_bw() +
       labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes.s, colour = classes.s)) +
-      shape_scale
+      shape_scale + scale_color_manual(name = "Classe", values = 1:nlevels(classes))
+  ggsave(paste(output.dir, "subsample-", suffix, ".pdf", sep=""), p.s, width=5, height=5)
+
   p <- ggplot(Y) +
       theme_bw() +
       labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = classes)) +
-      shape_scale
+      shape_scale + scale_color_manual(name = "Classe", values = 1:nlevels(classes))
+  ggsave(paste(output.dir, suffix, ".pdf", sep=""), p, width=5, height=5)
+
   p.np <- ggplot(Y) +
       theme_bw() +
-      labs(x = "", y = "", title = "NP (9)") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = np)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.blue_orange("NP")
+  ggsave(paste(output.dir, "np-", suffix, ".pdf", sep=""), p.np, width=5, height=5)
+
   p.silh <- ggplot(Y) +
       theme_bw() +
-      labs(x = "", y = "", title = "Silhouette") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = silh)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.blue_orange("Silhueta")
+  ggsave(paste(output.dir, "silh-", suffix, ".pdf", sep=""), p.silh, width=5, height=5)
+
   p.precision <- ggplot(Y) +
       theme_bw() +
-      labs(x = "", y = "", title = "Precision") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = precision)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.blue_orange("Precisão")
+  ggsave(paste(output.dir, "precision-", suffix, ".pdf", sep=""), p.precision, width=5, height=5)
+
   p.recall <- ggplot(Y) +
       theme_bw() +
-      labs(x = "", y = "", title = "Recall") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = recall)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.blue_orange("Revocação")
+  ggsave(paste(output.dir, "recall-", suffix, ".pdf", sep=""), p.recall, width=5, height=5)
+
   
-  pdf(paste(output.dir, "original-", suffix, ".pdf", sep=""), width = 12, height = 16)
+  pdf(paste(output.dir, "all-", suffix, ".pdf", sep=""), width = 12, height = 16)
   grid.arrange(p.s, p, p.np, p.silh, p.precision, p.recall, ncol = 2)
   dev.off()
 
   # Perform manipulation
   message("\tCalculating Ys.m")
-  Dx.m <- automated.m(Dx.s, labels[sample.indices])
+  Dx.m <- automated.m(X[sample.indices, ], labels[sample.indices])
   Ys.m <- forceScheme(Dx.m, Ys[, 1:2])
 
   # LAMP
@@ -135,6 +172,12 @@ test <- function(file, suffix, output.dir) {
   precision <- klDivergence(Q, P) - precision
   recall <- klDivergence(P, Q) - recall
 
+  measures <- rbind(data.frame(mean=mean(np), median=median(np), sd=sd(np)),
+                    data.frame(mean=mean(silh), median=median(silh), sd=sd(silh)),
+                    data.frame(mean=mean(precision), median=median(precision), sd=sd(precision)),
+                    data.frame(mean=mean(recall), median=median(recall), sd=sd(recall)))
+  write.table(measures, paste(output.dir, suffix, "-manip-measures.csv", sep=""), row.names=F)
+
   if (!(all(is.finite(np)) &&
       all(is.finite(silh)) &&
       all(is.finite(precision)) &&
@@ -144,46 +187,64 @@ test <- function(file, suffix, output.dir) {
 
   # Plot results
   message("\tPlotting results")
-  color_scale <- scale_colour_gradient2(mid = "#dddddd", space = "Lab")
   Ys.m <- cbind(as.data.frame(Ys.m), classes.s)
   Y.m  <- cbind(as.data.frame(Y.m), classes, np, silh, precision, recall)
-  p.s <- ggplot(Ys.m) +
+  pm.s <- ggplot(Ys.m) +
       theme_bw() +
       labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes.s, colour = classes.s)) +
-      shape_scale
-  p <- ggplot(Y.m) +
+      shape_scale + scale_color_manual(name = "Classe", values = 1:nlevels(classes))
+  ggsave(paste(output.dir, "manip-subsample-", suffix, ".pdf", sep=""), pm.s, width=5, height=5)
+
+  pm <- ggplot(Y.m) +
       theme_bw() +
       labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = classes)) +
-      shape_scale
+      shape_scale + scale_color_manual(name = "Classe", values = 1:nlevels(classes))
+  ggsave(paste(output.dir, "manip-", suffix, ".pdf", sep=""), pm, width=5, height=5)
+
   p.np <- ggplot(Y.m) +
       theme_bw() +
-      labs(x = "", y = "", title = "NP (9)") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = np)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.gradient2("NP")
+  ggsave(paste(output.dir, "manip-np-", suffix, ".pdf", sep=""), p.np, width=5, height=5)
+
   p.silh <- ggplot(Y.m) +
       theme_bw() +
-      labs(x = "", y = "", title = "Silhouette") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = silh)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.gradient2("Silhueta")
+  ggsave(paste(output.dir, "manip-silh-", suffix, ".pdf", sep=""), p.silh, width=5, height=5)
+
   p.precision <- ggplot(Y.m) +
       theme_bw() +
-      labs(x = "", y = "", title = "Precision") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = precision)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.gradient2("Precisão")
+  ggsave(paste(output.dir, "manip-precision-", suffix, ".pdf", sep=""), p.precision, width=5, height=5)
+
   p.recall <- ggplot(Y.m) +
       theme_bw() +
-      labs(x = "", y = "", title = "Recall") +
+      labs(x = "", y = "") +
       geom_point(aes(x = V1, y = V2, shape = classes, colour = recall)) +
-      shape_scale + color_scale
+      shape_scale + color_scale.gradient2("Revocação")
+  ggsave(paste(output.dir, "manip-recall-", suffix, ".pdf", sep=""), p.recall, width=5, height=5)
+
+  pdf(paste(output.dir, "original-manip-", suffix, ".pdf", sep=""), width = 10, height = 8)
+  grid.arrange(p.s, p, pm.s, pm, ncol = 2)
+  dev.off()
+
+  pdf(paste(output.dir, "manip-measures-", suffix, ".pdf", sep=""), width = 10, height = 8)
+  grid.arrange(p.np, p.silh, p.precision, p.recall, ncol = 2)
+  dev.off()
   
-  pdf(paste(output.dir, "manip-", suffix, ".pdf", sep=""), width = 12, height = 16)
-  grid.arrange(p.s, p, p.np, p.silh, p.precision, p.recall, ncol = 2)
+  pdf(paste(output.dir, "manip-all-", suffix, ".pdf", sep=""), width = 12, height = 16)
+  grid.arrange(pm.s, pm, p.np, p.silh, p.precision, p.recall, ncol = 2)
   dev.off()
 }
 
-test(file = "datasets/iris-std.tbl", suffix = "iris", "plots/")
-test(file = "datasets/wdbc.tbl", suffix = "wdbc", "plots/")
-test(file = "datasets/segmentation.tbl", suffix = "segmentation", "plots/")
-test(file = "datasets/images.tbl", suffix = "images", "plots/")
+#test(file = "datasets/iris.tbl", suffix = "iris", "tests/")
+test(file = "datasets/wdbc.tbl", suffix = "wdbc", "tests/")
+test(file = "datasets/segmentation.tbl", suffix = "segmentation", "tests/")
+test(file = "datasets/glass.tbl", suffix = "glass", "tests/")