diff --git a/scripts/R/plotTimeSeriesToyExample.R b/scripts/R/plotTimeSeriesToyExample.R
index 4170b7d..cbb6426 100644
--- a/scripts/R/plotTimeSeriesToyExample.R
+++ b/scripts/R/plotTimeSeriesToyExample.R
@@ -1,17 +1,17 @@
 library(ggplot2)
 
-timeSeries.t0 <- read.csv("/home/josura/Projects/ccc/c2c-sepia/outputsTimeSeries/t2_outputAll.tsv",sep = "\t",header = TRUE)
+timeSeries.t2 <- read.csv("/home/josura/Projects/ccc/c2c-sepia/outputsTimeSeries/t2_outputAll.tsv",sep = "\t",header = TRUE)
 
-library(tidyverse)
+library(dplyr)
 
 
-x <- timeSeries.t0[, 1]
-y <- timeSeries.t0[, (ncol(timeSeries.t0)-11):ncol(timeSeries.t0)]
+x <- timeSeries.t2[, 1]
+y <- timeSeries.t2[, (ncol(timeSeries.t2)-11):ncol(timeSeries.t2)]
 
 # Select only the interesting columns
 #interesting.list <- c("v.in.t3","v.in.t1","v.in.t2","v.out.t3","v.out.t1","v.out.t2")
 interesting.list <- c("v.in.t3","v.in.t1","v.out.t3","v.out.t1","v.out.t2")
-y.int <- timeSeries.t0[, interesting.list]
+y.int <- timeSeries.t2[, interesting.list]
 
 # Combine x and y into a new dataframe
 df_new <- data.frame(x = rep(x, ncol(y)), y)
@@ -27,3 +27,25 @@ ggplot(df_new, aes(x = x, y = value, color = variable)) +
   scale_color_discrete(name = "Y Variables") +
   facet_wrap(~ variable, ncol = 3)  # Adjust the number of columns as needed
 
+
+# Combine x and y into a new dataframe
+df_new <- data.frame(x = rep(x, ncol(y)))
+df_new <- cbind(df_new, y)
+
+# Reshape the data by converting columns into a single column
+df_new <- data.frame(
+  x = rep(df_new$x, times = ncol(y)),
+  variable = rep(colnames(y), each = nrow(y)),
+  value = c(t(y))
+)
+
+
+# Plot the matrix of scatter plots
+ggplot(df_new, aes(x = x, y = value, color = variable)) +
+  geom_point() +
+  labs(x = "X Axis", y = "Y Axis") +
+  scale_color_discrete(name = "Y Variables") +
+  facet_wrap(~ variable, ncol = 3)  # Adjust the number of columns as needed
+
+
+plot(df_new[df_new$variable == "a",]$x,df_new[df_new$variable == "a",]$value)