Example runtime decreased

R/mergeCompNeigh.R

@@ -10,29 +10,38 @@
 #'@export
 #'@examples {
 #'
-#'df <- loadData(SubCellBarCode::hcc827Ctrl)
+#'#create mock data
+#'com.df <- data.frame(Proteins = "TP53",
+#'svm.pred = "N1",
+#'S1 = as.numeric(0.02),
+#'S2 = as.numeric(0.02),
+#'S3 = as.numeric(0.02),
+#'S4 = as.numeric(0.02),
+#'N1 = as.numeric(0.72),
+#'N2 = as.numeric(0.02),
+#'N3 = as.numeric(0.02),
+#'N4 = as.numeric(0.02),
+#'C1 = as.numeric(0.02),
+#'C2 = as.numeric(0.02),
+#'C3 = as.numeric(0.02),
+#'C4 = as.numeric(0.02),
+#'C5 = as.numeric(0.02),
+#'M1 = as.numeric(0.02),
+#'M2 = as.numeric(0.02))
 #'
-#'c.prots <- calculateCoveredProtein(rownames(df), markerProteins[,1])
+#'rownames(com.df) <- "TP53"
 #'
-#'set.seed(7)
-#'c.prots <- sample(c.prots, 365)
-#'cls <- svmClassification(c.prots, df, markerProteins)
+#'neig.df <- data.frame(Proteins = "TP53",
+#'svm.pred.all = "Nuclear",
+#'Secretory = as.numeric(0.01),
+#'Nuclear = as.numeric(0.95),
+#'Cytosol = as.numeric(0.02),
+#'Mitochondria = as.numeric(0.02))
 #'
-#'test.A <- cls[[1]]$svm.test.prob.out
-#'test.B <- cls[[2]]$svm.test.prob.out
+#'rownames(neig.df) <- "TP53"
 #'
-#'t.c.df <- computeThresholdCompartment(test.A, test.B)
+#'cls.df <- mergeCls(com.df, neig.df)
 #'
-#'t.n.df <- computeThresholdNeighborhood(test.A, test.B)
-#'
-#'all.A <- cls[[1]]$all.prot.pred
-#'all.B <- cls[[2]]$all.prot.pred
-#'
-#'c.cls.df <- applyThresholdCompartment(all.A[1:300,],all.B[1:300,],t.c.df)
-#'
-#'n.cls.df <- applyThresholdNeighborhood(all.A[1:300,],all.B[1:300,],t.n.df)
-#'
-#'cls.df <- mergeCls(c.cls.df, n.cls.df)
 #'}
 #'@return cls.df
 

R/plotBarcode.R

@@ -9,31 +9,38 @@
 #'@export
 #'@examples {
 #'
-#'df <- loadData(SubCellBarCode::hcc827Ctrl)
+#'#create mock data
+#'plot.df <- data.frame(Protein = "TP53",
+#'NeighborhoodCls = "Nuclear",
+#'CompartmentCls = "N1",
+#'Secretory = as.numeric(0.01),
+#'Nuclear = as.numeric(0.95),
+#'Cytosol = as.numeric(0.02),
+#'Mitochondria = as.numeric(0.02),
+#'S1 = as.numeric(0.02),
+#'S2 = as.numeric(0.02),
+#'S3 = as.numeric(0.02),
+#'S4 = as.numeric(0.02),
+#'N1 = as.numeric(0.72),
+#'N2 = as.numeric(0.02),
+#'N3 = as.numeric(0.02),
+#'N4 = as.numeric(0.02),
+#'C1 = as.numeric(0.02),
+#'C2 = as.numeric(0.02),
+#'C3 = as.numeric(0.02),
+#'C4 = as.numeric(0.02),
+#'C5 = as.numeric(0.02),
+#'M1 = as.numeric(0.02),
+#'M2 = as.numeric(0.02))
 #'
-#'c.prots <- calculateCoveredProtein(rownames(df), markerProteins[,1])
+#'rownames(plot.df) <- "TP53"
 #'
-#'set.seed(7)
-#'c.prots <- sample(c.prots, 365)
-#'cls <- svmClassification(c.prots, df, markerProteins)
+#'psm.df <- data.frame(Protein = "TP53",
+#'PSMs.for.quant = as.numeric(31))
 #'
-#'test.A <- cls[[1]]$svm.test.prob.out
-#'test.B <- cls[[2]]$svm.test.prob.out
+#'rownames(psm.df) <- "TP53"
 #'
-#'t.c.df <- computeThresholdCompartment(test.A, test.B)
-#'
-#'t.n.df <- computeThresholdNeighborhood(test.A, test.B)
-#'
-#'all.A <- cls[[1]]$all.prot.pred
-#'all.B <- cls[[2]]$all.prot.pred
-#'
-#'c.cls.df <- applyThresholdCompartment(all.A[1:300,],all.B[1:300,],t.c.df)
-#'
-#'n.cls.df <- applyThresholdNeighborhood(all.A[1:300,],all.B[1:300,],t.n.df)
-#'
-#'cls.df <- mergeCls(c.cls.df, n.cls.df)
-#'
-#'proteinPlot <- plotBarcode(cls.df, "ACAA2", hcc827CtrlPSMCount)
+#'proteinPlot <- plotBarcode(plot.df, "TP53", psm.df)
 #'}
 #'@import ggplot2
 #'@importFrom graphics plot