void printMarcel(int x, int y) {
printM(x,y);
printA(x+5*SIZE+GAP,y);
printR(x+8*SIZE+2*GAP,y);
printC(x+12*SIZE+3*GAP,y);
printE(x+16*SIZE+4*GAP,y);
printL(x+19*SIZE+5*GAP,y);
}
void printDevina(int x, int y) {
printD(x,y);
printE(x+4*SIZE+GAP,y);
printV(x+7*SIZE+2*GAP,y);
printI(x+11*SIZE+3*GAP,y);
printN(x+12*SIZE+4*GAP,y);
printA(x+16*SIZE+5*GAP,y);
}
int main(void)
{
char str[100] = "";
printA();
printB(str);
printC();
return 0;
}
int main()
{
A sample(44, 54.888);
printA(sample);
return 0;
}
void printWilliam(int x, int y) {
printW(x,y);
printI(x+5*SIZE+GAP,y);
printL(x+6*SIZE+2*GAP,y);
printL(x+9*SIZE+3*GAP,y);
printI(x+12*SIZE+4*GAP,y);
printA(x+13*SIZE+5*GAP,y);
printM(x+16*SIZE+6*GAP,y);
}
void printGameOver(int x, int y) {
printG(x,y);
printA(x+5*SIZE+GAP, y);
printM(x+8*SIZE+2*GAP, y);
printE(x+13*SIZE+3*GAP, y);
printO(x+16*SIZE+5*GAP, y);
printV(x+20*SIZE+6*GAP, y);
printE(x+24*SIZE+7*GAP, y);
printR(x+27*SIZE+8*GAP, y);
}
int main(int argc, char *argv[]) {
int ar[N] = {1,4,5,9,13,16,19,28,40,100};
printA(ar, N -1 );
printf("Enter a numbber to insert: \n");
int num;
scanf("%d", &num);
int i = 0;
while (ar[i] < num)
i++;
if (i <= 9) {
for (int k = N - 1; k >= i; k--)
ar[k + 1] = ar[k];
ar[i] = num;
} else
ar[10] = num;
printA(ar, N);
return 0;
}
// Lomuto partitioning scheme
void solve(int n)
{
int piv = A[0];
int a = 1;
for (int b = 1; b < n; b++) {
if (A[b] < piv) {
swap(a, b);
a++;
}
}
swap(0, a - 1);
printA(n);
}
void floyd(int n)
{
int i, j, k;
for(i=0; i<n; i++)
for(j=0; j<n; j++)
A[i][j]=weight[i][j];
for(k=0; k<n; k++){
for(i=0; i<n; i++)
for(j=0; j<n; j++)
if (A[i][k]+A[k][j] < A[i][j])
A[i][j] = A[i][k]+A[k][j];
printA(n);
}
}
void bubbleSort(int *a,int n) {
int t;
printf("size %d\n",n);
if(n <=1) {
return;
}
for (int i=0; i < n-1; i++) { //Feeds value of i to the next loop
for(int j=0; j < n-1-i; j++) { //Every loop move highest value to the 'right most' location.
//Loop shrink every time by one element at right , which is sorted now.
if (a[j] > a[j+1]) {
t = a[j];
a[j] = a[j+1];
a[j+1] = t;
}
}
}
printA(a,n);
}
void main ()
{
int A[] = {20, 40, 10, 30, 0, 90, 70, 60, 50, 80};
int i, min, max = 0;
printA(A);
/**
* Loop Invariant:
*
* Initialization:
* . The first iteration of the loop we have the max and min values
* pointed to the first element of A. If the i element in A is greater
* then max element then max become i. Otherwise if the i element in A
* is less the min element then min become i. The iteration is true
* prior to the first iteration.
*
* Maintenance:
* . For each iteration the loop invariant is maintained. For i
* from 0 to the length of A ([i=0 .. i=9]), if there is a number
* less or greater then max or min, it will be assigned to max or min
* respectively.
*
* Termination:
* . The iteration finishes when i becomes A_size that represents
* the last index inside A. Then, if the entire array A was traversed,
* then min and max has the lowest and highest values of the array A.
*
*/
for(; i<A_size; i++)
{
if(A[i] > A[max])
max = i;
else if(A[i] < A[min])
min = i;
}
printf("Min: %d, Max: %d\n", A[min], A[max]);
}
int main(int argc, char **argv) {
test(1);
printA();
test(2);
printA();
}
int main()
{
printA();
printB();
return 0;
}
int main(){
/*struct CharachterBuffer test;
test.defaultBuffer(7);
char pull;
printf("empty pull (output riding input) test result: %d\n",test.pull(&pull));
printf("empty push test result: %d\n",test.push('$'));
printf("immenent output riding input occupied pull test result: %d\n",test.pull(&pull));
printf("data integrity check: %c\n",pull);
printf("output riding input push test result: %d\n",test.push('H'));
printf("input && output riding nothing push test result: %d\n",test.push('I'));
printf("input && output riding nothing push test result: %d\n",test.push(' '));
printf("input && output riding nothing push test result: %d\n",test.push('M'));
printf("input && output riding nothing push test result: %d\n",test.push('O'));
printf("input && output riding nothing push test result: %d\n",test.push('M'));
printf("immenent input riding output push test result: %d\n",test.push('!'));
printf("input riding output push test result: %d\n",test.push('?'));
int flow = 0;
std::string gather = "";
while((flow = test.pull(&pull)) != test.ERROR_COLLISION){
printf("The input int is: %d\n",flow);
gather += pull;
if(flow == test.ERROR_COLLISION){
printf("WHOA, DUDE!");
break;
}
}
printf("%s\n\n\n\n**********\n\n\n",gather.c_str());
printf("bufferOutput: %d\n",test.bufferOutputPosition);
printf("bufferInput: %d\n",test.bufferInputPosition);
*/
gpsBuffer.defaultBuffer(1024);
setup();
/* //Tests Buffer and getNMEAstr()
gpsBuffer.push(' ');
gpsBuffer.push('$');
gpsBuffer.push('T');
gpsBuffer.push('E');
gpsBuffer.push('S');
gpsBuffer.push('T');
gpsBuffer.push('\n');
std::string gather="";
getNMEAstr(&gather);
printf("%s\n",gather.c_str());*/
int overflow = readGPS();
while( overflow != ERR_SHTAP){
overflow = readGPS();
}
//printf(gpsBuffer.buffer);
std::string gather="";
getNMEAstr(&gather);
struct nmea_data *gathered_data = new nmea_data(gather);
printf("%s\n",gather.c_str());
printA(gathered_data);
gather = "";
getNMEAstr(&gather);
gathered_data = new nmea_data(gather);
printf("%s\n",gather.c_str());
printA(gathered_data);
gather = "";
getNMEAstr(&gather);
gathered_data = new nmea_data(gather);
printf("%s\n",gather.c_str());
printA(gathered_data);
gather = "";
getNMEAstr(&gather);
gathered_data = new nmea_data(gather);
printf("%s\n",gather.c_str());
printA(gathered_data);
gather = "";
getNMEAstr(&gather);
gathered_data = new nmea_data(gather);
printf("%s\n",gather.c_str());
printA(gathered_data);
gather = "";
getNMEAstr(&gather);
gathered_data = new nmea_data(gather);
printf("%s\n",gather.c_str());
printA(gathered_data);
gather = "";
/*setup();
char input;
while(1){
read(serialHandle, &input, 1);
if(input != 0){
printf("%c\n",input);
}
}*/
}
int main(int argc, const char *argv[])
{
int N,
M,
T,
maxIters,
seed,
i,
j,
iter,
str_len;
char **alphabet;
double logProb,
newLogProb;
double *pi,
*piBar,
**A,
**Abar,
**B,
**Bbar;
struct stepStruct *step;
FILE *in,
*out;
char s[80];
int wantTraining = 1;
if(argc != 10)
{
fprintf(stderr, "\nUsage: %s N M T maxIters filename alphabet modelfile seed\n\n", argv[0]);
fprintf(stderr, "where N == number of states of the HMM\n");
fprintf(stderr, " M == number of observation symbols\n");
fprintf(stderr, " T == number of observations in the training set\n");
fprintf(stderr, " maxIters == max iterations of re-estimation algorithm\n");
fprintf(stderr, " filename == name of input file\n");
fprintf(stderr, " alphabet == name of file defining the alphabet\n");
fprintf(stderr, " modelfile == name of model output file\n");
fprintf(stderr, " seed == seed value for pseudo-random number generator (PRNG)\n\n");
fprintf(stderr, " wantTraining == to train enter 1, otherwise 0 \n\n");
fprintf(stderr, "For example:\n\n %s 2 10 10000 500 datafile alphabet modelfile 1241\n\n", argv[0]);
fprintf(stderr, "will create a HMM with 2 states and 10 observation symbols,\n");
fprintf(stderr, "will read in the first 10000 observations from `datafile',\n");
fprintf(stderr, "will use the observation symbols defined in file `alphabet', and\n");
fprintf(stderr, "will write the model (pi, A, B) to `modelfile', and\n");
fprintf(stderr, "will seed the PRNG with 1241 and train the HMM with a maximum of 500 iterations.\n\n");
exit(0);
}
N = atoi(argv[1]);
M = atoi(argv[2]);
T = atoi(argv[3]);
maxIters = atoi(argv[4]);
seed = atoi(argv[8]);
wantTraining = atoi(argv[9]);
pi = (double *)malloc(N * sizeof(double));
piBar = (double *)malloc(N * sizeof(double));
A = (double **)malloc(N * sizeof(double*));
Abar =static_cast<double **>(malloc(N * sizeof(double*)));
for (i=0; i<N; ++i)
{
A[i] = static_cast<double *>(malloc(N * sizeof(double)));
Abar[i] = static_cast<double *>(malloc(N * sizeof(double)));
}
B = static_cast<double **>(malloc(N * sizeof(double*)));
Bbar = static_cast<double **>(malloc(N * sizeof(double*)));
for (i=0; i<N; ++i)
{
B[i] = static_cast<double *>(malloc(M * sizeof(double)));
Bbar[i] = static_cast<double *>(malloc(M * sizeof(double)));
}
////////////////////////
// read the data file //
////////////////////////
// allocate memory
printf("allocating %d bytes of memory... ", (T + 1) * sizeof(struct stepStruct));
fflush(stdout);
if((step = static_cast<stepStruct *>(calloc(T + 1, sizeof(struct stepStruct)))) == NULL)
{
fprintf(stderr, "\nUnable to allocate alpha\n\n");
exit(0);
}
for (i=0; i<T+1; ++i)
{
step[i].alpha = static_cast<double *>(malloc(N * sizeof(double)));
step[i].beta = static_cast<double *>(malloc(N * sizeof(double)));
step[i].gamma = static_cast<double *>(malloc(N * sizeof(double)));
step[i].diGamma = static_cast<double **>(malloc(N * sizeof(double*)));
for (j=0; j<N; ++j)
{
step[i].diGamma[j] = static_cast<double *>(malloc(N * sizeof(double)));
}
}
printf("done\n");
// read in the observations from file
printf("GetObservations... ");
fflush(stdout);
in = fopen(argv[5], "r"); // argv[5] = filename
if(in == NULL)
{
fprintf(stderr, "\nError opening file %s\n\n", argv[5]);
exit(0);
}
i = 0;
fgets(s,80,in); // get rid of the first line
while (i < T)
{
fgets(s,80,in);
step[i].obs = atoi(s);
++i;
}
fclose(in);
printf("done\n");
// read in the alphabet from file
printf("GetAlphabet... ");
fflush(stdout);
alphabet = static_cast<char **>(malloc(M * sizeof (char*)));
in = fopen(argv[6], "r"); // argv[6] = alphabet
if(in == NULL)
{
fprintf(stderr, "\nError opening file %s\n\n", argv[6]);
exit(0);
}
i = 0;
fgets(s,80,in); // get rid of the first line
while (i < M)
{
fgets(s,80,in);
str_len = strlen(s);
alphabet[i] = static_cast<char *>(malloc(str_len * sizeof(char)));
strncpy(alphabet[i], s, str_len-1);
alphabet[i][str_len-1] = '\0';
++i;
}
fclose(in);
printf("done\n");
/////////////////////////
// hidden markov model //
/////////////////////////
srand(seed);
// initialize pi[], A[][] and B[][]
initMatrices(pi, A, B, N, M, seed);
// print pi[], A[][] and B[][] transpose
printf("\nN = %d, M = %d, T = %d\n", N, M, T);
printf("initial pi =\n");
printPi(pi, N);
printf("initial A =\n");
printA(A, N);
printf("initial B^T =\n");
printBT(B, N, M, alphabet);
// initialization
iter = 0;
logProb = -1.0;
newLogProb = 0.0;
if (wantTraining) {
// main loop
while((iter < maxIters) && (newLogProb > logProb))
{
printf("\nbegin iteration = %d\n", iter);
logProb = newLogProb;
// alpha (or forward) pass
printf("alpha pass... ");
fflush(stdout);
alphaPass(step, pi, A, B, N, T);
printf("done\n");
// beta (or backwards) pass
printf("beta pass... ");
fflush(stdout);
betaPass(step, pi, A, B, N, T);
printf("done\n");
// compute gamma's and diGamma's
printf("compute gamma's and diGamma's... ");
fflush(stdout);
computeGammas(step, pi, A, B, N, T);
printf("done\n");
// find piBar, reestimate of pi
printf("reestimate pi... ");
fflush(stdout);
reestimatePi(step, piBar, N);
printf("done\n");
// find Abar, reestimate of A
printf("reestimate A... ");
fflush(stdout);
reestimateA(step, Abar, N, T);
printf("done\n");
// find Bbar, reestimate of B
printf("reestimate B... ");
fflush(stdout);
reestimateB(step, Bbar, N, M, T);
printf("done\n");
#ifdef PRINT_REESTIMATES
printf("piBar =\n");
printPi(piBar, N);
printf("Abar =\n");
printA(Abar, N);
printf("Bbar^T = \n");
printBT(Bbar, N, M, alphabet);
#endif // PRINT_REESTIMATES
// assign pi, A and B corresponding "bar" values
for(i = 0; i < N; ++i)
{
pi[i] = piBar[i];
for(j = 0; j < N; ++j)
{
A[i][j] = Abar[i][j];
}
for(j = 0; j < M; ++j)
{
B[i][j] = Bbar[i][j];
}
}// next i
// compute log [P(observations | lambda)], where lambda = (A,B,pi)
newLogProb = 0.0;
for(i = 0; i < T; ++i)
{
newLogProb += log(step[i].c);
}
newLogProb = -newLogProb;
// a little trick so that no initial logProb is required
if(iter == 0)
{
logProb = newLogProb - 1.0;
}
printf("completed iteration = %d, log [P(observation | lambda)] = %f\n",
iter, newLogProb);
++iter;
}// end while
out = fopen(argv[7], "w"); // argv[7] = modelfile
writeModel(pi, A, B, N, M, T, alphabet, out);
fclose(out);
printf("\nT = %d, N = %d, M = %d, iterations = %d\n\n", T, N, M, iter);
printf("final pi =\n");
printPi(pi, N);
printf("\nfinal A =\n");
printA(A, N);
printf("\nfinal B^T =\n");
printBT(B, N, M, alphabet);
printf("\nlog [P(observations | lambda)] = %f\n\n", newLogProb);
} // end of training
else { //want to do testing
out = fopen(argv[7], "r"); // argv[7] = modelfile
readModelFile(pi, A, B, N, M, T, alphabet, out);
// alpha (or forward) pass
printf("alpha pass... ");
fflush(stdout);
alphaPass(step, pi, A, B, N, T);
printf("done\n");
printf("logProb %f\n", computeLogProb(step, T)/T);
// FILE * newFile = fopen("testing.txt", "a");
//writeModel(pi, A, B, N, M, T, alphabet, newFile);
//fclose(newFile);
fclose(out);
} // end of testing
}// end hmm
int main(int argc, char *argv[]) {
printA();
printB();
return 0;
}
void printAB()
{
printA();
printB();
}
/********* end of lrs_getfirstbasis ***************/
long
getabasis2 (lrs_dic * P, lrs_dat * Q, lrs_dic * P2orig, long order[])
/* Pivot Ax<=b to standard form */
/*Try to find a starting basis by pivoting in the variables x[1]..x[d] */
/*If there are any input linearities, these appear first in order[] */
/* Steps: (a) Try to pivot out basic variables using order */
/* Stop if some linearity cannot be made to leave basis */
/* (b) Permanently remove the cobasic indices of linearities */
/* (c) If some decision variable cobasic, it is a linearity, */
/* and will be removed. */
{
long i, j, k;
/* assign local variables to structures */
lrs_mp_matrix A = P->A;
long *B = P->B;
long *C = P->C;
long *Row = P->Row;
long *Col = P->Col;
long *linearity = Q->linearity;
long *redundcol = Q->redundcol;
long m, d, nlinearity;
long nredundcol = 0L; /* will be calculated here */
static long firsttime=TRUE;
static long *linindex;
m = P->m;
d = P->d;
nlinearity = Q->nlinearity;
if(firsttime)
{
firsttime = FALSE;
linindex = calloc ((m + d + 2), sizeof (long));
}
else /* after first time we update the change in linearities from the last time, saving many pivots */
{
for(i=1;i<=m+d;i++)
linindex[i]=FALSE;
if(Q->debug)
fprintf(lrs_ofp,"\nlindex =");
for(i=0;i<nlinearity;i++)
{
linindex[d+linearity[i]]=TRUE;
if(Q->debug)
fprintf(lrs_ofp," %ld",d+linearity[i]);
}
for(i=1;i<=m;i++)
{
if(linindex[B[i]]) /* pivot out unwanted linearities */
{
k=0;
while(k<d && (linindex[C[k]] || zero (A[Row[i]][Col[k]])))
k++;
if (k < d)
{
j=i; /* note this index changes in update, cannot use i!)*/
if(C[k] > B[j]) /* decrease i or we may skip a linearity */
i--;
pivot (P, Q, j, k);
update (P, Q, &j, &k);
}
else
{
/* this is not necessarily an error, eg. two identical rows/cols in payoff matrix */
if(! zero(A[Row[i]][0])) /* error condition */
{
if(Q->debug || Q->verbose)
{
fprintf(lrs_ofp,"\n*Infeasible linearity i=%ld B[i]=%ld",i,B[i]);
if (Q->debug)
printA(P,Q);
}
return(FALSE);
}
if(Q->debug || Q->verbose)
{
fprintf(lrs_ofp,"\n*Couldn't remove linearity i=%ld B[i]=%ld",i,B[i]);
}
}
} /* if linindex */
} /* for i ..*/
goto hotstart;
}
/* standard lrs processing is done on only the first call to getabasis2 */
if (Q->debug)
{
fprintf (lrs_ofp, "\ngetabasis from inequalities given in order");
for (i = 0; i < m; i++)
fprintf (lrs_ofp, " %ld", order[i]);
}
for (j = 0; j < m; j++)
{
i = 0;
while (i <= m && B[i] != d + order[j])
i++; /* find leaving basis index i */
if (j < nlinearity && i > m) /* cannot pivot linearity to cobasis */
{
if (Q->debug)
printA (P, Q);
#ifndef LRS_QUIET
fprintf (lrs_ofp, "\nCannot find linearity in the basis");
#endif
return FALSE;
}
if (i <= m)
{ /* try to do a pivot */
k = 0;
while (C[k] <= d && zero (A[Row[i]][Col[k]]))
k++;
if (C[k] <= d)
{
pivot (P, Q, i, k);
update (P, Q, &i, &k);
}
else if (j < nlinearity)
{ /* cannot pivot linearity to cobasis */
if (zero (A[Row[i]][0]))
{
#ifndef LRS_QUIET
fprintf (lrs_ofp, "\n*Input linearity in row %ld is redundant--skipped", order[j]);
#endif
linearity[j] = 0;
}
else
{
if (Q->debug)
printA (P, Q);
if (Q->verbose)
fprintf (lrs_ofp, "\nInconsistent linearities");
return FALSE;
}
} /* end if j < nlinearity */
} /* end of if i <= m .... */
} /* end of for */
/* update linearity array to get rid of redundancies */
i = 0;
k = 0; /* counters for linearities */
while (k < nlinearity)
{
while (k < nlinearity && linearity[k] == 0)
k++;
if (k < nlinearity)
linearity[i++] = linearity[k++];
}
nlinearity = i;
/* column dependencies now can be recorded */
/* redundcol contains input column number 0..n-1 where redundancy is */
k = 0;
while (k < d && C[k] <= d)
{
if (C[k] <= d) /* decision variable still in cobasis */
redundcol[nredundcol++] = C[k] - Q->hull; /* adjust for hull indices */
k++;
}
/* now we know how many decision variables remain in problem */
Q->nredundcol = nredundcol;
Q->lastdv = d - nredundcol;
/* if not first time we continue from here after loading dictionary */
hotstart:
if (Q->debug)
{
fprintf (lrs_ofp, "\nend of first phase of getabasis2: ");
fprintf (lrs_ofp, "lastdv=%ld nredundcol=%ld", Q->lastdv, Q->nredundcol);
fprintf (lrs_ofp, "\nredundant cobases:");
for (i = 0; i < nredundcol; i++)
fprintf (lrs_ofp, " %ld", redundcol[i]);
printA (P, Q);
}
/* here we save dictionary for use next time, *before* we resize */
copy_dict(Q,P2orig,P);
/* Remove linearities from cobasis for rest of computation */
/* This is done in order so indexing is not screwed up */
for (i = 0; i < nlinearity; i++)
{ /* find cobasic index */
k = 0;
while (k < d && C[k] != linearity[i] + d)
k++;
if (k >= d)
{
if(Q->debug || Q->verbose)
{
fprintf (lrs_ofp, "\nCould not remove cobasic index");
}
/* not neccesarily an error as eg., could be repeated row/col in payoff */
}
else
{
removecobasicindex (P, Q, k);
d = P->d;
}
}
if (Q->debug && nlinearity > 0)
printA (P, Q);
/* set index value for first slack variable */
/* Check feasability */
if (Q->givenstart)
{
i = Q->lastdv + 1;
while (i <= m && !negative (A[Row[i]][0]))
i++;
if (i <= m)
fprintf (lrs_ofp, "\n*Infeasible startingcobasis - will be modified");
}
return TRUE;
} /* end of getabasis2 */
long
lrs_getfirstbasis2 (lrs_dic ** D_p, lrs_dat * Q, lrs_dic * P2orig, lrs_mp_matrix * Lin, long no_output)
/* gets first basis, FALSE if none */
/* P may get changed if lin. space Lin found */
/* no_output is TRUE supresses output headers */
{
long i, j, k;
/* assign local variables to structures */
lrs_mp_matrix A;
long *B, *C, *Row, *Col;
long *inequality;
long *linearity;
long hull = Q->hull;
long m, d, lastdv, nlinearity, nredundcol;
static long ocount=0;
m = D->m;
d = D->d;
lastdv = Q->lastdv;
nredundcol = 0L; /* will be set after getabasis */
nlinearity = Q->nlinearity; /* may be reset if new linearity read */
linearity = Q->linearity;
A = D->A;
B = D->B;
C = D->C;
Row = D->Row;
Col = D->Col;
inequality = Q->inequality;
/* default is to look for starting cobasis using linearies first, then */
/* filling in from last rows of input as necessary */
/* linearity array is assumed sorted here */
/* note if restart/given start inequality indices already in place */
/* from nlinearity..d-1 */
for (i = 0; i < nlinearity; i++) /* put linearities first in the order */
inequality[i] = linearity[i];
k = 0; /* index for linearity array */
if (Q->givenstart)
k = d;
else
k = nlinearity;
for (i = m; i >= 1; i--)
{
j = 0;
while (j < k && inequality[j] != i)
j++; /* see if i is in inequality */
if (j == k)
inequality[k++] = i;
}
if (Q->debug)
{
fprintf (lrs_ofp, "\n*Starting cobasis uses input row order");
for (i = 0; i < m; i++)
fprintf (lrs_ofp, " %ld", inequality[i]);
}
if (!Q->maximize && !Q->minimize)
for (j = 0; j <= d; j++)
itomp (ZERO, A[0][j]);
/* Now we pivot to standard form, and then find a primal feasible basis */
/* Note these steps MUST be done, even if restarting, in order to get */
/* the same index/inequality correspondance we had for the original prob. */
/* The inequality array is used to give the insertion order */
/* and is defaulted to the last d rows when givenstart=FALSE */
if (!getabasis2 (D, Q,P2orig, inequality))
return FALSE;
if(Q->debug)
{
fprintf(lrs_ofp,"\nafter getabasis2");
printA(D, Q);
}
nredundcol = Q->nredundcol;
lastdv = Q->lastdv;
d = D->d;
/********************************************************************/
/* now we start printing the output file unless no output requested */
/********************************************************************/
if (!no_output || Q->debug)
{
fprintf (lrs_ofp, "\nV-representation");
/* Print linearity space */
/* Don't print linearity if first column zero in hull computation */
k = 0;
if (nredundcol > k)
{
fprintf (lrs_ofp, "\nlinearity %ld ", nredundcol - k); /*adjust nredundcol for homog. */
for (i = 1; i <= nredundcol - k; i++)
fprintf (lrs_ofp, " %ld", i);
} /* end print of linearity space */
fprintf (lrs_ofp, "\nbegin");
fprintf (lrs_ofp, "\n***** %ld rational", Q->n);
} /* end of if !no_output ....... */
/* Reset up the inequality array to remember which index is which input inequality */
/* inequality[B[i]-lastdv] is row number of the inequality with index B[i] */
/* inequality[C[i]-lastdv] is row number of the inequality with index C[i] */
for (i = 1; i <= m; i++)
inequality[i] = i;
if (nlinearity > 0) /* some cobasic indices will be removed */
{
for (i = 0; i < nlinearity; i++) /* remove input linearity indices */
inequality[linearity[i]] = 0;
k = 1; /* counter for linearities */
for (i = 1; i <= m - nlinearity; i++)
{
while (k <= m && inequality[k] == 0)
k++; /* skip zeroes in corr. to linearity */
inequality[i] = inequality[k++];
}
} /* end if linearity */
if (Q->debug)
{
fprintf (lrs_ofp, "\ninequality array initialization:");
for (i = 1; i <= m - nlinearity; i++)
fprintf (lrs_ofp, " %ld", inequality[i]);
}
if (nredundcol > 0)
{
*Lin = lrs_alloc_mp_matrix (nredundcol, Q->n);
for (i = 0; i < nredundcol; i++)
{
if (!(Q->homogeneous && Q->hull && i == 0)) /* skip redund col 1 for homog. hull */
{
lrs_getray (D, Q, Col[0], D->C[0] + i - hull, (*Lin)[i]); /* adjust index for deletions */
}
if (!removecobasicindex (D, Q, 0L))
return FALSE;
}
} /* end if nredundcol > 0 */
if (Q->verbose)
{
fprintf (lrs_ofp, "\nNumber of pivots for starting dictionary: %ld",Q->count[3]);
ocount=Q->count[3];
}
/* Do dual pivots to get primal feasibility */
if (!primalfeasible (D, Q))
{
if ( Q->verbose )
{
fprintf (lrs_ofp, "\nNumber of pivots for feasible solution: %ld",Q->count[3]);
fprintf (lrs_ofp, " - No feasible solution");
ocount=Q->count[3];
}
return FALSE;
}
if (Q->verbose)
{
fprintf (lrs_ofp, "\nNumber of pivots for feasible solution: %ld",Q->count[3]);
ocount=Q->count[3];
}
/* Now solve LP if objective function was given */
if (Q->maximize || Q->minimize)
{
Q->unbounded = !lrs_solvelp (D, Q, Q->maximize);
/* check to see if objective is dual degenerate */
j = 1;
while (j <= d && !zero (A[0][j]))
j++;
if (j <= d)
Q->dualdeg = TRUE;
}
else
/* re-initialize cost row to -det */
{
for (j = 1; j <= d; j++)
{
copy (A[0][j], D->det);
storesign (A[0][j], NEG);
}
itomp (ZERO, A[0][0]); /* zero optimum objective value */
}
/* reindex basis to 0..m if necessary */
/* we use the fact that cobases are sorted by index value */
if (Q->debug)
printA (D, Q);
while (C[0] <= m)
{
i = C[0];
j = inequality[B[i] - lastdv];
inequality[B[i] - lastdv] = inequality[C[0] - lastdv];
inequality[C[0] - lastdv] = j;
C[0] = B[i];
B[i] = i;
reorder1 (C, Col, ZERO, d);
}
if (Q->debug)
{
fprintf (lrs_ofp, "\n*Inequality numbers for indices %ld .. %ld : ", lastdv + 1, m + d);
for (i = 1; i <= m - nlinearity; i++)
fprintf (lrs_ofp, " %ld ", inequality[i]);
printA (D, Q);
}
if (Q->restart)
{
if (Q->debug)
fprintf (lrs_ofp, "\nPivoting to restart co-basis");
if (!restartpivots (D, Q))
return FALSE;
D->lexflag = lexmin (D, Q, ZERO); /* see if lexmin basis */
if (Q->debug)
printA (D, Q);
}
/* Check to see if necessary to resize */
if (Q->inputd > D->d)
*D_p = resize (D, Q);
return TRUE;
}
