% Cellular Automaton LO27 % Bartuccio Antoine \cr Porée De Ridder Jean % Autumn 2016 \newpage # Introduction The goal of this project is to provide a library containing a new abstract data type called **Matrix** with associated function to manipulate them. The final program have to enable a user to test the library in an interactive and practical way. Since we decided to not store false value \footnote{cellElement does not contains values anymore, their existence is their value}in our matrix and to not store the colElement and rowElement \footnote{they are unified and renamed as listElement}that are empty, we decided not to worry too much about performances and we encapsulated all access to stored data in the Matrix structure to avoid too much complexity and allow more modularity, readability and re-usability. We created high level tools to manipulate our matrix and used it all along the project. For compilation we didn't used the **-ansi** flag since we had to deal with both clang and gcc for compilation and clang didn't accept this flag. Instead, we used the **-std=c89** flag witch contains the same rules but is accepted on both softwares. Compiling with **-ansi** still works. We decided to create two different library. One for the graphical interface (which require SDL2) and the other with the Matrix data type) so this way you may just have to compile one lib if you don't need the gui. # Description of abstract data types Every function and data type are described in the documentation given with the project. This documentation is generated with doxygen. # Algorithmic The most interesting function are *getCellValue* and *setCellValue*. Those are the one we rely on the most. They are our way of dealing with our complex data structure allowing us to avoid to store false values. They are the functions that need the more computational power on the long run but are really useful due to their level of abstraction and their high level. *getCellValue* is a simple function based on *findMatrixElem* : ```C getCellValue(matrix:Matrix, ColPos:integer , RowPos:integer ) : bool BEGIN if ( colCount(matrix) <= ColPos OR rowCount(matrix) <= RowPos) getCellValue <- ERROR endif if (findMatrixElem( matrix , ColPos , RowPos ) == NULL) getCellValue <- false endif getCellValue <- true END findMatrixElem( matrix:Matrix , ColPos:integer, RowPos:integer ) : *cellElement BEGIN Row:ListElement <- NULL elem:*cellElement <- NULL Row <- getElementPos(rows(matrix),RowPos) if (Row == NULL) findMatrixElem <- NULL endif elem <- data(Row) while (elem != NULL AND colIndex(elem) != ColPos) elem <- nextCol(elem) endwhile findMatrixElem <- elem END ``` *setCellValue* is a simple function based on *createMatrixElem* and *deleteMatrixElement* : ```C setCellValue(matrix:Matrix, ColPos:integer, RowPos:integer,value:bool):bool BEGIN if (value == true) setCellValue <- createMatrixElem(matrix,ColPos,RowPos) else if ( deleteMatrixElem(matrix,ColPos,RowPos) >= 0 ) setCellValue <- true else setCellValue <- false endif endif END createMatrixElem( matrix:Matrix, ColPos:integer, RowPos:integer):bool Row:*ListElement <-NULL Col:*Listelemnt <- NULL error:integer <- 0 elem: *cellElement <- NULL tmp: *cellElement<- NULL if (colCount(matrix) <= ColPos OR rowCount(matrix) <= RowPos ) createMatrixElem <- ERROR endif elem <- CreateCellElem() SetPositionIndex(elem,ColPos,RowPos) Row <- getElementPos(rows(matrix),RowPos) if (Row != NULL AND data(Row) != NULL) if (colIndex(data(Row)) == ColPos) error ++ else if (colIndex(data(Row)) > ColPos) nextCol(elem) <- data(Row) data(Row) <- elem endif else tmp <- data(Row) while ( nextCol(tmp) != NULL AND nextCol(colIndex(tmp)) < ColPos) do tmp <- nextCol(tmp) endwhile if ( nextCol(tmp) == NULL OR colIndex(nextCol(tmp)) > ColPos) nextCol(elem) <- nextCol(tmp) nextCol(tmp) <- elem else error ++ endif endif else push(rows(matrix),elem) pos(tail(rows(matrix))) <- RowPos endif Col <- getElementPos(cols(matrix),ColPos) if (Col != NULL AND data(Col) != NULL) if (rowIndex(data(Col)) == RowPos) error ++ else if (rowIndex(data(Col)) > RowPos) nextRow(elem) <- data(Col) data(Col) <- elem endif else tmp <- data(Col) while (nextRow(tmp) != NULL AND rowIndex(nextRow(tmp)) < RowPos) do tmp <- nextRow(tmp) endwhile if (nextRow(tmp) == NULL OR rowIndex(nextRow(tmp)) > RowPos) nexRow(elem) <- nextRow(tmp) newRow(tmp) <- elem else error ++ endif endif else push(cols(matrix),elem) pos(tail(cols(matrix))) <- ColPos endif if (error != 0) FreeCellElement(elem) createMatrixElem <- true else createMatrixElem <- false endif END deleteMatrixElem(matrix:Matrix,ColPos:integer, RowPos:integer ):integer BEGIN elem : *cellElement <- NULL tmp : *cellElement <- NULL Row : *ListElement <- NULL Col : *ListElement <- NULL elem <- findMatrixElem(matrix,ColPos,RowPos) if (elem == NULL) deleteMatrixElem <- 0 endif Row <- getElementPos(rows(matrix),RowPos) if (Row == NULL) deleteMatrixElem <- -1 endif if (data(Row) == NULL) removeElementPos(rows(matrix),RowPos) deleteMatrixElem <- -1 endif if (colIndex(data(Row)) == ColPos) data(Row) <- nextCol(elem) else tmp <- data(Row) while (nextCol(tmp) != NULL AND nextCol(tmp) != elem) do tmp <- nextCol(tmp) endwhile if (nextCol(tmp) != NULL) nextCol(tmp) <- nextCol(elem) endif endif if (data(Row) == NULL) removeElementPos(rows(matrix),RowPos) endif Col <- getElementPos(cols(matrix),ColPos) if (Col == NULL) deleteMatrixElem <- -2 endif if (data(Col) == NULL) removeElementPos(cols(matrix),ColPos) deleteMatrixElem <- -1 endif if (rowIndex(data(Col)) == RowPos) data(Col) <- nextRow(elem) else tmp <- data(Col) while (nextRow(tmp) != NULL AND nextRow(tmp) != elem) do tmp <- nextRow(tmp) endwhile if (nextRow(tmp) != NULL) nextRow(tmp) <- nextRow(elem) endif endif if (data(Col) == NULL) removeElementPos(cols(matrix),ColPos) endif FreeCellElement(elem) deleteMatrixElem <- 1 END ``` Functions *andColSequenceOnMatrix* and *orColSequenceOnMatrix* are implemented with *colSequenceOnMatrix* and are really not interesting so we're gonna provide the algorithm of the last one : ```C ``` This is the same thing for *andRowSequenceOnMatrix* and *orRowSequenceOnMatrix* : ```C colSequenceOnMatrix(m:Matrix, operator:(function(bool, bool):bool)): Matrix BEGIN a:integer b:integer i:integer j:integer newM:Matrix <- createMatrix() rowCount(newM) <- rowCount(m) if (colCount(m) <= 1) then colCount(newM) <- 0 colSequenceOnMatrix <- newM endif colCount(newM) <- colCount(m) - 1 for i from 0 to colCount(m) - 2 do for j from 0 to rowCount(m) - 2 do a <- getCellValue(m, i, j) b <- getCellValue(m, i + 1, j) if operator(a, b) then setCellValue(newM, i, j, true) endif endfor endfor colSequenceOnMatrix <- newM END ``` Here are the algorithm of the function *applyRules* and all the one related to it : ```C applyRules ( matrix:Matrix, Rules:integer, N:integer):Matrix BEGIN RulesMatrix :integer[9] i:integer <- 0 power:integer <- 2 sum:integer <- 0 j:integer <- 0 tempMatrix1:Matrix tempMatrix2:Matrix if (Rules <= 0 OR N < 1) applyRules <- matrix endif while(power <= 512) do RulesMatrix[i] <- Rules%power - sum sum <- Rules%power if (RulesMatrix[i]!=0) i++ endif power <- power*2 endwhile tempMatrix1 <- matrixFromRules(matrix, i, RulesMatrix) for j from 0 to N do tempMatrix2 <- matrixFromRules(tempMatrix1 ,i, RulesMatrix) freeMatrix(tempMatrix1) tempMatrix1 <- tempMatrix2 endfor applyRules <- tempMatrix1 END ``` # Conclusion