source('statusToValue.R')
source('replaceAllNA.R')
calculateCorr <- function(data.frame){
data <-data.frame;
df <- statusToValue(data);
df <- replaceAllNA(df);
# M1 = cor(df[,2],df[,15],method="spearman")
# M2 = cor(df[,4], df[,15],method="spearman")
# M3 = cor(df[,5], df[,15],method="spearman")
# M4 = cor(df[,6], df[,15],method="spearman")
# M5 = cor(df[,7], df[,15],method="spearman")
# M6 = cor(df[,8], df[,15],method="spearman")
# M7 = cor(df[,9], df[,15],method="spearman")
# M8 = cor(df[,10], df[,15],method="spearman")
# M9 = cor(df[,11], df[,15],method="spearman")
# M10 = cor(df[,12], df[,15],method="spearman")
# M11 = cor(df[,13], df[,15],method="spearman")
# M12 = cor(df[,14], df[,15],method="spearman")
# M3 = cor(df[,5], df[,15],method="spearman")
# M4 = cor(df[,6], df[,15],method="spearman")
# M5 = cor(df[,7], df[,15],method="spearman")
# M6 = cor(df[,8], df[,15],method="spearman")
# M7 = cor(df[,9], df[,15],method="spearman")
# M8 = cor(df[,10], df[,15],method="spearman")
# M9 = cor(df[,11], df[,15],method="spearman")
# M10 = cor(df[,12], df[,15],method="spearman")
# M11 = cor(df[,13], df[,15],method="spearman")
# M12 = cor(df[,14], df[,15],method="spearman")
M=cor(df[,2:30])
# col<- colorRampPalette(c("blue", "white", "red"))(20)
# heatmap(x = M, col = col, symm = TRUE)
png(filename="Wykresy/CorrelationMatrix.png");
corrplot(M, type = "upper", order = "hclust",
tl.col = "black", tl.srt = 45);
#dev.off();
#corrplot(M, method = "circle")
#
# cells <-c(M1,M2,M3,M4,M5,M6,M7,M8,M9,M10,M11,M12)
# rnames <- c("1")
# cnames <- c("team size", "test churn", "src churn","files added","files deleted",
# "tests added","tests deleted","files modified",
# "src files","sloc","test lines per kloc",
# "test cases per kloc"
# )
# corrMatrix <- matrix(cells, nrow=1, ncol=12, byrow=TRUE,
# dimnames=list(rnames, cnames))
return (M)
}
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