1
0
mirror of https://gitlab.com/klmp200/LO27.git synced 2024-11-26 02:04:14 +00:00

Merge branch 'NaejBranch' into 'master'

added algos

See merge request !24
This commit is contained in:
Antoine Bartuccio 2017-01-01 22:41:23 +00:00
commit 7fc34d9b9e
3 changed files with 254 additions and 16 deletions

View File

@ -188,11 +188,6 @@ int deleteListContent(List *list){
while (current != NULL){ while (current != NULL){
toDelete = current; toDelete = current;
current = current->next; current = current->next;
/*
if (toDelete->data != NULL){
FreeCellElement(toDelete->data);
}
*/
free(toDelete); free(toDelete);
} }
list->head = NULL; list->head = NULL;

View File

@ -263,7 +263,6 @@ bool setCellValue(Matrix matrix, int ColPos, int RowPos,bool value){
} }
void printMatrix(Matrix matrix){ void printMatrix(Matrix matrix){
/* Non optimisé : debug fx */
int i = 0; int i = 0;
int j = 0; int j = 0;
bool b; bool b;
@ -666,8 +665,3 @@ bool equalsMatrix(Matrix m1, Matrix m2){
return true; return true;
} }
/* todos :
*faire les fontions débiles qui restent
*ecrire doc
*/

259
report.md
View File

@ -8,7 +8,7 @@
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. 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 in our matrix, 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. 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. 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.
@ -21,10 +21,218 @@ Every function and data type are described in the documentation given with the p
# Algorithmic # 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. 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 ```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 : Functions *andColSequenceOnMatrix* and *orColSequenceOnMatrix* are implemented with *colSequenceOnMatrix* and are really not interesting so we're gonna provide the algorithm of the last one :
@ -51,8 +259,8 @@ BEGIN
endif endif
colCount(newM) <- colCount(m) - 1 colCount(newM) <- colCount(m) - 1
for i from 0 to colCount(m) - 2, step 1 for i from 0 to colCount(m) - 2 do
for j from 0 to rowCount(m) - 2, step 1 for j from 0 to rowCount(m) - 2 do
a <- getCellValue(m, i, j) a <- getCellValue(m, i, j)
b <- getCellValue(m, i + 1, j) b <- getCellValue(m, i + 1, j)
if operator(a, b) then if operator(a, b) then
@ -60,13 +268,54 @@ BEGIN
endif endif
endfor endfor
endfor endfor
colSequenceOnMatrix <- newM; colSequenceOnMatrix <- newM
END END
``` ```
Here are the algorithm of the function *applyRules* and all the one related to it : Here are the algorithm of the function *applyRules* and all the one related to it :
```C ```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
``` ```