bool sudokuSolver::fillColumn(int row,int column){
if(row==9){
return true;
}
else if(column==9){
if(fillColumn(row+1,0))return true;
else return false;
}
else if(problem[row][column]==0){
for(int i=1;i<=9;i++){
ans[row][column]=i;
for(int k=row;k<9;k++){
if(k==row){
for(int l=column+1;l<9;l++)
ans[k][l]=problem[k][l];
}
else{
for(int l=0;l<9;l++)
ans[k][l]=problem[k][l];
}
}
if(checkColumn(row,column) && checkRow(row,column) && checkBlock(row,column))
if(fillColumn(row,column+1))return true;
}
return false;
}
else {if(fillColumn(row,column+1))return true;else return false;}
}
void moveMap( char** map )
{
++rounds;
if (rounds == 80) {
rounds = 0;
}
for (int x = rounds; x < 80; ++x) {
fillColumn(map[x], x - rounds);
}
for (int x = 0; x < rounds; ++x) {
fillColumn(map[x], 80 + x + 1);
}
}
sudokuSolver::status sudokuSolver::solve(){
if(validateProblem()){
if(fillColumn(0,0))return SOLVED;
else return UNSOLVED;
}
else{
return NOTVALID;
}
}
void CSVVector::fillEmptyCells()
{
//vul bij alle kolommen behalve de eerste twee alle lege velden
for(int column = 0; column < columns(); column++)
{
if(isBooleanColumn(column))
fillBooleanColumn(column);
else
fillColumn(column);
}
}
/** see Kimmen's PhD-Thesis, pp42ff.
I use equations 6.38 and 6.39 for calculating the pi
using the logarithm of the beta-function, as Kimmen suggests.
This method calculates the Xi and stores it in the profile. You have
to call NormalizeColumn to get the correct estimated probabilites.
*/
void ImplRegularizorDirichletFade::fillFrequencies( Frequency * frequencies,
const Count * counts,
const Position length,
const Residue width ) const
{
if (width != ALPHABET_SIZE)
throw AlignlibException( "ImplRegularizorDirichletFade.cpp: profile width of profile has to be 20.")
Position column;
Count ntotal;
int i,j;
double Xi[width];
// helper variables for the conversion of log to floating point
TYPE_BETA_DIFFERENCES beta_differences;
for (column = 0; column < length; column++)
{
const Count * n = &counts[column * width];
ntotal = 0;
// get ntotal = number of observations
for (i = 0; i < width; i++)
ntotal += n[i];
// if the number of total observation is less than the fade cutoff, do the normal calculation. I have pasted and copied
// it, maybe externalize it sometime later..
if (ntotal < FADE_CUTOFF)
{
// use normal Dirichlet-Mixture
fillColumn( beta_differences, n. ntotal );
}
else
{
// calculate raw frequencies:
Frequency * column = frequencies[column * width];
for (i = 0; i < width; i++)
frequencies[i] = (Frequency)(n[i] / ntotal);
}
}
}
