add graduel with tids and dataset

.gitignore

@@ -26,4 +26,7 @@ yarn-error.log
 /.env
 /admin/node_modules/
 /mercure/updates.db
-/public/uploads/
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+/public/uploads/
+.vscode
+FileForAprioriTID.txt
+**/FileForAprioriTID.txt
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bin/source_code_graduel_avec_tid.R

+## inputs parameters
+argv <- commandArgs(TRUE)
+
+# -- The minimum support --
+   #minSup <- as.double(argv[1])
+minSup <- as.double(argv[2])
+
+# -- The minimum length of extracted gradual pattern
+  #minLength <- as.integer(argv[2])
+minLength <- as.integer(1)
+
+# -- Input file 
+   #input <- argv[3]
+input <- argv[1]
+
+# -- Output file
+output <- argv[3]
+
+# -- Define output tempon file & input Convolution
+outputInputTemp <- "FileForAprioriTID.txt"
+
+# -- The Firts constant
+  #k1 <- as.numeric(argv[5])
+k1 <- 0
+
+# -- The Second constant
+   #k2 <- as.numeric(argv[6])
+k2 <- 0
+
+cat("\n")
+cat("----- The minimum support is ", minSup, "------ \n")
+cat("\n")
+cat("----- The minimum length of extracted gradual pattern is ", minLength, "----\n")
+cat("\n")
+cat("----- The Firts constant is", k1, "----\n")
+cat("\n")
+cat("----- The second constant is ", k2, "----\n")
+cat("\n")
+#cat("----- The separator of data is ", argv[7], "------ \n")
+#cat("----- The separator of data is ", argv[3], "------ \n")
+cat("----- The separator of data is ",  " ", "------ \n")
+
+
+cat("\n")
+
+## import library Java
+library("rJava")
+
+## Read input data file 
+#data <- read.csv(input, sep = argv[7])
+#data <- read.csv(input, sep = argv[3])
+data <- read.csv(input, sep = " ")
+
+
+
+## ------ The beginning of the standard deviation ------
+## Transform dataframe to matrix 
+data_mat <- as.matrix(data)
+
+## ------ Time ------
+t1 <- Sys.time()
+## ------ Debut standard deviation (sd) ------
+ecarttype <- vector("numeric",ncol(data_mat))
+
+for (i in 1 : ncol(data_mat)){
+  ecarttype[i] <- (sd(data_mat[,i]) * k1) + k2
+}
+## ------ Fin  standard deviation ------
+
+## ------ The beginning of the NumVersCat procedure -------
+data_diff <- diff(data_mat)
+## -- Util pour APRIORI
+tab_vec <- array()
+
+## Transform numerical data matrix to categorical data matrix containing  "+", "-" and "o" items
+data_cat <- matrix(0, nrow = nrow(data_diff), ncol = ncol(data_diff))
+
+for(i in 1:ncol(data_diff)){
+  for(j in 1 : nrow(data_diff)){
+    if ((data_diff[j,i] > ecarttype[i]) & (data_diff[j,i] > 0)){
+      data_cat[j,i] <-paste0(paste0("X",i),"=+") # Xi=+
+    }else if((abs(data_diff[j,i]) > ecarttype[i]) & (data_diff[j,i] < 0)){
+      data_cat[j,i] <-paste0(paste0("X",i),"=-") #Xi=-
+    }else{
+      data_cat[j,i] <-paste0(paste0("X",i),"=o") #Xi=o
+    }
+  }
+}
+# ----------------------------------
+for (i in 1:nrow(data_cat)) {
+  for(j in 1:ncol(data_cat)){
+    if (j == 1) {tab_vec[i] <- data_cat[i,j]}else{tab_vec[i] <- paste(tab_vec[i], data_cat[i,j])}
+  }
+}
+# ----------------------------------
+
+# -- Ecrire dans un fichier tempon pour traitement par AprioriTID
+write(tab_vec, file = outputInputTemp, sep =" ")
+
+### ----- Dbut Insertion du code java -----
+# -- initialisation of the JVM
+.jinit()
+
+# -- Add .jar file to the class path
+.jaddClassPath("AprioriTID.jar")
+
+# -- instatiation of the Class
+obj <- .jnew("AlgoAprioriTID")
+
+cat("----- BEFORE APRIORI ----\n")
+# -- Call function directly with parameters
+.jcall(obj, "V", "runAlgorithmModifier", outputInputTemp, output, minSup, minLength)
+cat("----- AFTER APRIORI ----\n")
+t2 <- Sys.time()
+t2 - t1
+cat("\n")
+

datasheets/exampleDataSet-with-espace.data

+x1 x2 x3 x4 x5 x6 x7
+84 61 7 0 1 8 0
+116 36 4 1 11 2 31
+90 52 2 3 5 1 13
+124 34 1 5 12 7 36
+102 49 0 6 7 10 17
+135 17 0 1 18 3 62
+106 40 3 1 9 0 18
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