diff --git a/07_final_assignment/.RData b/07_final_assignment/.RData
new file mode 100644
index 0000000..e08dca5
--- /dev/null
+++ b/07_final_assignment/.RData
Binary files differ
diff --git a/07_final_assignment/baboonSimulation.R b/07_final_assignment/baboonSimulation.R
index 5cc73f4..2741a1c 100644
--- a/07_final_assignment/baboonSimulation.R
+++ b/07_final_assignment/baboonSimulation.R
@@ -1,9 +1,10 @@
-# install.packages("fields")
 library(testthat)
 library(ndl)
 library(compiler)
 library(fields)
 library(parallel)
+library(doParallel)
+library(foreach)
 enableJIT(3)
 
 monkeydat <- data.frame(Monkey=c("DAN", "ART", "CAU", "DOR", "VIO", "ARI"),
@@ -100,43 +101,91 @@
     # TODO: Decide what should be expected for empty vectors?
 })
 
+
+########## DELETE
+
+st.stimulus = character(trialCount)
+st.stimulustype = character(trialCount)
+st.block = numeric(trialCount)
+st.trialinblock   = numeric(trialCount)
+st.trial = numeric(trialCount)
+st.response = character(trialCount)
+
+#View(block[curTrialNumInBlock, ])
+#asdfasdf = block[curTrialNumInBlock, ]
+#stop("try")
+st.stimulus[curTrialNum] = block[curTrialNumInBlock, ][1]
+lev = unclass(block[curTrialNumInBlock, ][2])
+st.stimulustype[curTrialNum] = ifelse(lev==1, "LearnedWord", ifelse(lev==2, "NewWord", "Nonword"))
+st.block[curTrialNum] = block[curTrialNumInBlock, ][3]
+st.trialinblock[curTrialNum]   = block[curTrialNumInBlock, ][4]
+st.trial[curTrialNum] = block[curTrialNumInBlock, ][5]
+st.response[curTrialNum] = block[curTrialNumInBlock, ][6]
+
+#trials[curTrialNum, ] <- block[curTrialNumInBlock, ]  
+
+
+trialsResult = data.frame(cbind(st.stimulus, st.stimulustype, st.block,
+                                st.trialinblock, st.trial,
+                                st.response))
+
+
+colnames(trialsResult) <- c("Stimulus", "StimulusType", "Block",
+                            "TrialInBlock", "Trial", "Response")
+
+
+#trials <- data.frame(Stimulus=character(trialCount),
+#                     StimulusType=character(trialCount),
+#                     Block=numeric(trialCount),
+#                     TrialInBlock=numeric(trialCount),
+#                     Trial=numeric(trialCount),
+#                     Response=character(trialCount))
+
+
+######
+
+
 PresentTrials <- function(trialCount, present, data){
-    trials <- data.frame()
-    for ( curTrialNum in 1:trialCount ) {
-        curBlock <- ( (curTrialNum - 1) %/% BLOCK_SIZE) + 1
-        curTrialNumInBlock <- ( (curTrialNum - 1) %% BLOCK_SIZE ) + 1
-        isNewBlock <- curTrialNumInBlock == 1
-
-        if ( isNewBlock ){
-            isNotFirstBlock <- curBlock > 1
-            if ( isNotFirstBlock ){
-                newWordTrials <- block[block$StimulusType == "NewWord",]
-                if( length(unique(newWordTrials$Stimulus)) == 1 ){
-                    newWordTrials <- newWordTrials[1,]
-                    wordResponses <- newWordTrials[newWordTrials$Response == "Word",]
-                    wordResponseRate <- nrow(wordResponses) / nrow(newWordTrials)
-                    if ( wordResponseRate >= 0.8  ){
-                        data$StimulusType[data$Stimulus == newWordTrials$Stimulus] <- "LearnedWord"
-                    }
-                }
-            }
-            block <- CreateBlock(data)
-            block$Block <- curBlock
-            block$TrialInBlock <- 1:nrow(block)
+  
+  trials = data.frame()
+  
+  for ( curTrialNum in 1:trialCount ) {
+    curBlock <- ( (curTrialNum - 1) %/% BLOCK_SIZE) + 1
+    curTrialNumInBlock <- ( (curTrialNum - 1) %% BLOCK_SIZE ) + 1
+    isNewBlock <- curTrialNumInBlock == 1
+    
+    if ( isNewBlock ) {
+      if ( curBlock > 1 ){
+        newWordTrials <- block[block$StimulusType == "NewWord", ]
+        if( length(unique(newWordTrials$Stimulus)) == 1 ){
+          newWordTrials <- newWordTrials[1, ]
+          wordResponses <- newWordTrials[newWordTrials$Response == "Word", ]
+          wordResponseRate <- nrow(wordResponses) / nrow(newWordTrials)
+          if ( wordResponseRate >= 0.8  ){
+            data$StimulusType[data$Stimulus == newWordTrials$Stimulus] <- "LearnedWord"
+          }
         }
-
-        curTrial <- block[curTrialNumInBlock,]
-        curStim <- curTrial$Stimulus
-        curStimIsWord <- present(curStim, ifelse(curTrial$StimulusType == "Nonword", "Nonword", "Word"))
-
-        block$Trial[curTrialNumInBlock] <- curTrialNum
-        block$Response[curTrialNumInBlock] <- curStimIsWord
-
-        trials <- rbind(trials, block[curTrialNumInBlock,])
+      }
+      block <- CreateBlock(data)
+      block$Block <- curBlock
+      block$TrialInBlock <- 1:nrow(block)
     }
-    rownames(trials) <- 1:trialCount
-    result <- list(Trials=trials,Stimuli=data)
-    result
+    
+    curTrial <- block[curTrialNumInBlock,]
+    curStim <- curTrial$Stimulus
+    curStimIsWord <- present(curStim, ifelse(curTrial$StimulusType == "Nonword", "Nonword", "Word"))
+    
+    block$Trial[curTrialNumInBlock] <- curTrialNum
+    block$Response[curTrialNumInBlock] <- curStimIsWord
+    
+    trials <- rbind(trials, block[curTrialNumInBlock, ])
+  }
+  
+  rownames(trials) <- 1:trialCount
+  
+  result <- list(Trials=trials, Stimuli=data)
+  
+  return(result)
 }
 
 test_that("PresentTrials", {
@@ -258,7 +307,7 @@
     pres <- PresentTrials(
                     trialNum,
                     monkey$Learner,data$dat)
-    pres
+    return(pres)
 }
 
 analyseSim <- function(pres){
@@ -288,44 +337,102 @@
 
 data <- prepareDat()
 
-n <- 10
-trialCount <- 1000
-for( a in 0:n) {
+testfunc = function() {
+  n <- 10
+  trialCount <- 300
+  for( a in 0:n) {
     k <- 1.0 / n * a
     print(k)
     s <- simulateAndAnalyse(data, trialCount, alpha=1, beta=k)
     s[1] <- as.character(k)
     monkeydat <- rbind(monkeydat,
                        s)
+  }
+  return(monkeydat)
 }
-monkeydat
 
 
-resultdat <- data.frame(alpha=numeric(1), beta=numeric(1), NumTrials=numeric(1), NumWordsLearned=numeric(1),
-                       NumNonwordsPresented=numeric(1), GeneralAccuracy=numeric(1),
-                       WordAccuracy=numeric(1), NonwordAccuracy=numeric(1))
-write.table(resultdat, file="resultdat.txt", col.names=names(resultdat))
+testfunc()
 
-trialCount <- 50000
+first.result = c()
+system.time(first.result <- testfunc())
 
-a.seq = seq(from=0, to=0.25, length.out=10)
-b.seq = seq(from=0, to=0.25, length.out=10)
-for( a in a.seq) {
-  for (b in b.seq) {
+first.result
+#  user  system elapsed 
+# 10.05    0.00   10.06 
+
+#   user  system elapsed 
+#  17.39    0.03   17.87 
+
+
+###############################################################################################
+
+x = matrix(nrow=2, ncol=0)
+
+for(a in seq(from=0.01, to=0.20, by=0.025)) {
+  for(b in seq(from=0.01, to=a, by=0.025)) {
+    x = cbind(x, c(a, b))
+  }
+}
+
+l = 12
+st.1 = x[, 1:l]
+st.2 = x[, (l+1):(2*l)]
+st.3 = x[, (2*l+1):(3*l)]
+
+get.a = function(i, index) {
+  if(i==1) return(st.1[1, index])
+  if(i==2) return(st.2[1, index])
+  if(i==3) return(st.3[1, index])
+}
+
+get.b = function(i, index) {
+  if(i==1) return(st.1[2, index])
+  if(i==2) return(st.2[2, index])
+  if(i==3) return(st.3[2, index])
+}
+
+do.experiment = function(i) {
+  filename = paste("resultdat", i, ".txt", sep="")
+  resultdat <- data.frame(alpha=numeric(1), beta=numeric(1), NumTrials=numeric(1), NumWordsLearned=numeric(1),
+                          NumNonwordsPresented=numeric(1), GeneralAccuracy=numeric(1),
+                          WordAccuracy=numeric(1), NonwordAccuracy=numeric(1))
+  write.table(resultdat, file=filename, col.names=names(resultdat))
+  
+  trialCount <- 50000 
+      
+  for(index in 1:l) {
+    a = get.a(i, index)
+    b = get.b(i, index)
+    resultdat = read.table(filename)
     
-    resultdat = read.table("resultdat.txt")
-    
-    print(cat(a, b))
+    print(paste("i: ", i, " a: ", a, " b: ", b, sep="" ))
     s <- simulateAndAnalyse(data, trialCount, alpha=a, beta=b)
     s[1] <- as.character(trialCount)
     resultdat <- rbind(resultdat,
                        c(a, b, s[2:length(s)]))
     
-    write.table(resultdat, file="resultdat.txt", col.names=names(resultdat))
+    write.table(resultdat, file=filename, col.names=names(resultdat))
+    
   }
+  
+  resultdat = resultdat[-1, ] #remove 1st row which is just always 0 
+  
+  write.table(resultdat, file=filename, col.names=names(resultdat))
+  
+  return(resultdat)
 }
 
-resultdat = resultdat[-1, ] #remove 1st row which is just always 0 
+
+num.cores = detectCores() - 1 #don't use all if you want to do anything else
+cl <- makeCluster(num.cores)
+registerDoParallel(cl)
+
+foreach(i=1:num.cores) %dopar% do.experiment(i)
+
+
+
+###########################
 View(resultdat)
 
 res.matrix = matrix(nrow=length(a.seq), ncol=length(b.seq))
@@ -356,6 +463,16 @@
 
 View(m1)
 
+dat03 = data.frame()
+for(i in 0:3) {
+  d = read.table(paste("resultdat", i, ".txt", sep=""))
+  d = d[-1, ]
+  dat03 = rbind(dat03, d)
+}
+View(dat03)
+
+write.table(dat03, file="preliminary_results.txt", col.names=names(dat03))
+
 
 
 # EOF
\ No newline at end of file
diff --git a/07_final_assignment/monkey01.txt b/07_final_assignment/monkey01.txt
new file mode 100644
index 0000000..ed50d78
--- /dev/null
+++ b/07_final_assignment/monkey01.txt
@@ -0,0 +1,18 @@
+"Monkey" "NumTrials" "NumWordsLearned" "NumNonwordsPresented" "GeneralAccuracy" "WordAccuracy" "NonwordAccuracy"
+"1" "DAN" "56689" "308" "7832" "79.81" "80.01" "79.61"
+"2" "ART" "50985" "125" "7832" "73.41" "74.83" "72"
+"3" "CAU" "61142" "112" "7832" "72.43" "73.15" "71.72"
+"4" "DOR" "49608" "121" "7832" "73.15" "79.26" "67.06"
+"5" "VIO" "43041" "81" "7832" "71.55" "76.75" "66.33"
+"6" "ARI" "55407" "87" "7832" "71.14" "75.38" "66.9"
+"7" "0" "1000" "2" "484" "0.484" "0.448" "0.52"
+"8" "0.1" "1000" "8" "482" "0.999" "0.998" "1"
+"9" "0.2" "1000" "9" "483" "1" "1" "1"
+"10" "0.3" "1000" "9" "486" "1" "1" "1"
+"11" "0.4" "1000" "9" "488" "0.867" "0.794" "0.94"
+"12" "0.5" "1000" "6" "478" "0.508" "0.512" "0.504"
+"13" "0.6" "1000" "5" "483" "0.52" "0.502" "0.538"
+"14" "0.7" "1000" "6" "489" "0.515" "0.504" "0.526"
+"15" "0.8" "1000" "6" "478" "0.51" "0.492" "0.528"
+"16" "0.9" "1000" "5" "487" "0.506" "0.5" "0.512"
+"17" "1" "1000" "4" "486" "0.504" "0.496" "0.512"
diff --git a/07_final_assignment/preliminary_results.txt b/07_final_assignment/preliminary_results.txt
new file mode 100644
index 0000000..1a19773
--- /dev/null
+++ b/07_final_assignment/preliminary_results.txt
@@ -0,0 +1,37 @@
+"alpha" "beta" "NumTrials" "NumWordsLearned" "NumNonwordsPresented" "GeneralAccuracy" "WordAccuracy" "NonwordAccuracy"
+"2" 0 0 50000 246 7539 0.49816 0.49788 0.49844
+"3" 0 0.0277777777777778 50000 249 7507 0.50252 0.50348 0.50156
+"4" 0 0.0555555555555556 50000 254 7513 0.49934 0.49992 0.49876
+"5" 0 0.0833333333333333 50000 257 7561 0.49952 0.5002 0.49884
+"6" 0 0.111111111111111 50000 238 7481 0.4976 0.49928 0.49592
+"7" 0 0.138888888888889 50000 247 7511 0.49922 0.49828 0.50016
+"8" 0 0.166666666666667 50000 245 7529 0.49584 0.49892 0.49276
+"9" 0 0.194444444444444 50000 258 7495 0.49718 0.50036 0.494
+"10" 0 0.222222222222222 50000 237 7516 0.49704 0.49556 0.49852
+"11" 0 0.25 50000 252 7533 0.5003 0.50024 0.50036
+"12" 0.0277777777777778 0 50000 258 7512 0.50084 0.49832 0.50336
+"13" 0.0277777777777778 0.0277777777777778 50000 307 7507 0.89304 0.91932 0.86676
+"14" 0.0277777777777778 0.0555555555555556 50000 307 7504 0.92238 0.93996 0.9048
+"15" 0.0277777777777778 0.0833333333333333 50000 307 7474 0.94464 0.959 0.93028
+"16" 0.0277777777777778 0.111111111111111 50000 307 7509 0.94342 0.9586 0.92824
+"17" 0.0277777777777778 0.138888888888889 50000 307 7492 0.95592 0.96752 0.94432
+"18" 0.0277777777777778 0.166666666666667 50000 307 7525 0.95826 0.97004 0.94648
+"19" 0.0277777777777778 0.194444444444444 50000 307 7524 0.96136 0.97356 0.94916
+"20" 0.0277777777777778 0.222222222222222 50000 307 7519 0.96428 0.975 0.95356
+"21" 0.0277777777777778 0.25 50000 307 7491 0.96798 0.9796 0.95636
+"22" 0.0555555555555556 0 50000 250 7485 0.50116 0.50108 0.50124
+"23" 0.01 0.01 50000 307 7529 0.8255 0.92116 0.72984
+"31" 0.035 0.01 50000 307 7518 0.85618 0.9088 0.80356
+"41" 0.035 0.035 50000 307 7500 0.91126 0.93668 0.88584
+"51" 0.06 0.01 50000 307 7448 0.88458 0.9022 0.86696
+"61" 0.06 0.035 50000 307 7489 0.9405 0.95708 0.92392
+"24" 0.11 0.06 50000 307 7504 0.9655 0.97776 0.95324
+"32" 0.11 0.085 50000 307 7511 0.97114 0.98244 0.95984
+"42" 0.11 0.11 50000 307 7508 0.97604 0.98584 0.96624
+"52" 0.135 0.01 50000 307 7520 0.92474 0.94632 0.90316
+"62" 0.135 0.035 50000 307 7522 0.96084 0.976 0.94568
+"25" 0.16 0.085 50000 307 7525 0.97652 0.98644 0.9666
+"33" 0.16 0.11 50000 307 7498 0.98204 0.98928 0.9748
+"43" 0.16 0.135 50000 307 7518 0.9832 0.99012 0.97628
+"53" 0.16 0.16 50000 307 7511 0.98534 0.99096 0.97972
+"63" 0.185 0.01 50000 307 7515 0.9304 0.93784 0.92296
diff --git a/07_final_assignment/resultdat0.txt b/07_final_assignment/resultdat0.txt
new file mode 100644
index 0000000..b8bbd6c
--- /dev/null
+++ b/07_final_assignment/resultdat0.txt
@@ -0,0 +1,23 @@
+"alpha" "beta" "NumTrials" "NumWordsLearned" "NumNonwordsPresented" "GeneralAccuracy" "WordAccuracy" "NonwordAccuracy"
+"1" "0" "0" "0" "0" "0" "0" "0" "0"
+"2" "0" "0" "50000" "246" "7539" "0.49816" "0.49788" "0.49844"
+"3" "0" "0.0277777777777778" "50000" "249" "7507" "0.50252" "0.50348" "0.50156"
+"4" "0" "0.0555555555555556" "50000" "254" "7513" "0.49934" "0.49992" "0.49876"
+"5" "0" "0.0833333333333333" "50000" "257" "7561" "0.49952" "0.5002" "0.49884"
+"6" "0" "0.111111111111111" "50000" "238" "7481" "0.4976" "0.49928" "0.49592"
+"7" "0" "0.138888888888889" "50000" "247" "7511" "0.49922" "0.49828" "0.50016"
+"8" "0" "0.166666666666667" "50000" "245" "7529" "0.49584" "0.49892" "0.49276"
+"9" "0" "0.194444444444444" "50000" "258" "7495" "0.49718" "0.50036" "0.494"
+"10" "0" "0.222222222222222" "50000" "237" "7516" "0.49704" "0.49556" "0.49852"
+"11" "0" "0.25" "50000" "252" "7533" "0.5003" "0.50024" "0.50036"
+"12" "0.0277777777777778" "0" "50000" "258" "7512" "0.50084" "0.49832" "0.50336"
+"13" "0.0277777777777778" "0.0277777777777778" "50000" "307" "7507" "0.89304" "0.91932" "0.86676"
+"14" "0.0277777777777778" "0.0555555555555556" "50000" "307" "7504" "0.92238" "0.93996" "0.9048"
+"15" "0.0277777777777778" "0.0833333333333333" "50000" "307" "7474" "0.94464" "0.959" "0.93028"
+"16" "0.0277777777777778" "0.111111111111111" "50000" "307" "7509" "0.94342" "0.9586" "0.92824"
+"17" "0.0277777777777778" "0.138888888888889" "50000" "307" "7492" "0.95592" "0.96752" "0.94432"
+"18" "0.0277777777777778" "0.166666666666667" "50000" "307" "7525" "0.95826" "0.97004" "0.94648"
+"19" "0.0277777777777778" "0.194444444444444" "50000" "307" "7524" "0.96136" "0.97356" "0.94916"
+"20" "0.0277777777777778" "0.222222222222222" "50000" "307" "7519" "0.96428" "0.975" "0.95356"
+"21" "0.0277777777777778" "0.25" "50000" "307" "7491" "0.96798" "0.9796" "0.95636"
+"22" "0.0555555555555556" "0" "50000" "250" "7485" "0.50116" "0.50108" "0.50124"
diff --git a/07_final_assignment/resultdat1.txt b/07_final_assignment/resultdat1.txt
new file mode 100644
index 0000000..b4341e9
--- /dev/null
+++ b/07_final_assignment/resultdat1.txt
@@ -0,0 +1,7 @@
+"alpha" "beta" "NumTrials" "NumWordsLearned" "NumNonwordsPresented" "GeneralAccuracy" "WordAccuracy" "NonwordAccuracy"
+"1" "0" "0" "0" "0" "0" "0" "0" "0"
+"2" "0.01" "0.01" "50000" "307" "7529" "0.8255" "0.92116" "0.72984"
+"3" "0.035" "0.01" "50000" "307" "7518" "0.85618" "0.9088" "0.80356"
+"4" "0.035" "0.035" "50000" "307" "7500" "0.91126" "0.93668" "0.88584"
+"5" "0.06" "0.01" "50000" "307" "7448" "0.88458" "0.9022" "0.86696"
+"6" "0.06" "0.035" "50000" "307" "7489" "0.9405" "0.95708" "0.92392"
diff --git a/07_final_assignment/resultdat2.txt b/07_final_assignment/resultdat2.txt
new file mode 100644
index 0000000..23c9be5
--- /dev/null
+++ b/07_final_assignment/resultdat2.txt
@@ -0,0 +1,7 @@
+"alpha" "beta" "NumTrials" "NumWordsLearned" "NumNonwordsPresented" "GeneralAccuracy" "WordAccuracy" "NonwordAccuracy"
+"1" "0" "0" "0" "0" "0" "0" "0" "0"
+"2" "0.11" "0.06" "50000" "307" "7504" "0.9655" "0.97776" "0.95324"
+"3" "0.11" "0.085" "50000" "307" "7511" "0.97114" "0.98244" "0.95984"
+"4" "0.11" "0.11" "50000" "307" "7508" "0.97604" "0.98584" "0.96624"
+"5" "0.135" "0.01" "50000" "307" "7520" "0.92474" "0.94632" "0.90316"
+"6" "0.135" "0.035" "50000" "307" "7522" "0.96084" "0.976" "0.94568"
diff --git a/07_final_assignment/resultdat3.txt b/07_final_assignment/resultdat3.txt
new file mode 100644
index 0000000..1346a87
--- /dev/null
+++ b/07_final_assignment/resultdat3.txt
@@ -0,0 +1,7 @@
+"alpha" "beta" "NumTrials" "NumWordsLearned" "NumNonwordsPresented" "GeneralAccuracy" "WordAccuracy" "NonwordAccuracy"
+"1" "0" "0" "0" "0" "0" "0" "0" "0"
+"2" "0.16" "0.085" "50000" "307" "7525" "0.97652" "0.98644" "0.9666"
+"3" "0.16" "0.11" "50000" "307" "7498" "0.98204" "0.98928" "0.9748"
+"4" "0.16" "0.135" "50000" "307" "7518" "0.9832" "0.99012" "0.97628"
+"5" "0.16" "0.16" "50000" "307" "7511" "0.98534" "0.99096" "0.97972"
+"6" "0.185" "0.01" "50000" "307" "7515" "0.9304" "0.93784" "0.92296"
diff --git a/07_final_assignment/resultz/0 0NULL.docx b/07_final_assignment/resultz/0 0NULL.docx
new file mode 100644
index 0000000..c4cb17a
--- /dev/null
+++ b/07_final_assignment/resultz/0 0NULL.docx
Binary files differ
diff --git a/07_final_assignment/resultz/resultdat.txt b/07_final_assignment/resultz/resultdat.txt
new file mode 100644
index 0000000..b8bbd6c
--- /dev/null
+++ b/07_final_assignment/resultz/resultdat.txt
@@ -0,0 +1,23 @@
+"alpha" "beta" "NumTrials" "NumWordsLearned" "NumNonwordsPresented" "GeneralAccuracy" "WordAccuracy" "NonwordAccuracy"
+"1" "0" "0" "0" "0" "0" "0" "0" "0"
+"2" "0" "0" "50000" "246" "7539" "0.49816" "0.49788" "0.49844"
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