#'@title Sum compartment test data probabilities to
#'neighborhood probabilities
#'@description Compartment levels classifications on the test data are
#'summed up to associated neighborhood levels. It is a helper function.
#'@param df data.frame; test data classifications at the neighborhood
#'level and probablity vectors for each protein.
#'@export
#'@examples {
#'
#'#create mock data
#'df <- data.frame(Protein = "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))
#'
#'rownames(df) <- "TP53"
#'
#'sum.df <- sumProbability(df)
#'
#'}
#'@return summed.df
sumProbability <- function(df){
t.secretory.df <- data.frame(df[, colnames(df)[3:6]])
t.secretory.df$Secretory <- rowSums(t.secretory.df)
t.nuclear.df <- data.frame(df[, colnames(df)[7:10]])
t.nuclear.df$Nuclear <- rowSums(t.nuclear.df)
t.cytosol.df <- data.frame(df[, colnames(df)[11:15]])
t.cytosol.df$Cytosol <- rowSums(t.cytosol.df)
t.Mitochondria.df <- data.frame(df[, colnames(df)[16:17]])
t.Mitochondria.df$Mitochondria <- rowSums(t.Mitochondria.df)
summed.df <- data.frame(Proteins = rownames(df),
df[,colnames(df)[seq_len(2)]],
Secretory = t.secretory.df$Secretory,
Nuclear = t.nuclear.df$Nuclear,
Cytosol = t.cytosol.df$Cytosol,
Mitochondria = t.Mitochondria.df$Mitochondria)
#temp neighborhood df
t.n.df <- summed.df[,4:7]
summed.df$svm.pred <- colnames(t.n.df)[apply(t.n.df, 1, which.max)]
return(summed.df)
}
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