void undoscale(lprec *lp)
{
int i, j, nz;
MATrec *mat = lp->matA;
REAL *value;
int *rownr, *colnr;
if(lp->scaling_used) {
/* Unscale the OF */
for(j = 1; j <= lp->columns; j++) {
lp->orig_obj[j] = unscaled_mat(lp, lp->orig_obj[j], 0, j);
}
/* Unscale the matrix */
mat_validate(mat);
nz = get_nonzeros(lp);
value = &(COL_MAT_VALUE(0));
rownr = &(COL_MAT_ROWNR(0));
colnr = &(COL_MAT_COLNR(0));
for(j = 0; j < nz;
j++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) {
*value = unscaled_mat(lp, *value, *rownr, *colnr);
}
/* Unscale variable bounds */
for(i = lp->rows + 1, j = 1; i <= lp->sum; i++, j++) {
lp->orig_lowbo[i] = unscaled_value(lp, lp->orig_lowbo[i], i);
lp->orig_upbo[i] = unscaled_value(lp, lp->orig_upbo[i], i);
lp->sc_lobound[j] = unscaled_value(lp, lp->sc_lobound[j], i);
}
/* Unscale the rhs, upper and lower bounds... */
for(i = 0; i <= lp->rows; i++) {
lp->orig_rhs[i] = unscaled_value(lp, lp->orig_rhs[i], i);
j = lp->presolve_undo->var_to_orig[i];
if(j != 0)
lp->presolve_undo->fixed_rhs[j] = unscaled_value(lp, lp->presolve_undo->fixed_rhs[j], i);
lp->orig_lowbo[i] = unscaled_value(lp, lp->orig_lowbo[i], i);
lp->orig_upbo[i] = unscaled_value(lp, lp->orig_upbo[i], i);
}
FREE(lp->scalars);
lp->scaling_used = FALSE;
lp->columns_scaled = FALSE;
set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE);
}
}
STATIC int write_lprow(lprec *lp, int rowno, void *userhandle, write_modeldata_func write_modeldata, int maxlen)
{
int i, ie, j, nchars;
REAL a;
MATrec *mat = lp->matA;
MYBOOL first = TRUE, elements;
if(rowno == 0) {
i = 1;
ie = lp->columns+1;
}
else {
i = mat->row_end[rowno-1];
ie = mat->row_end[rowno];
}
elements = ie - i;
if(write_modeldata != NULL) {
nchars = 0;
for(; i < ie; i++) {
if(rowno == 0) {
j = i;
a = get_mat(lp, 0, i);
if(a == 0)
continue;
}
else {
j = ROW_MAT_COLNR(i);
a = ROW_MAT_VALUE(i);
a = my_chsign(is_chsign(lp, rowno), a);
a = unscaled_mat(lp, a, rowno, j);
}
if(is_splitvar(lp, j))
continue;
if(!first)
nchars += write_data(userhandle, write_modeldata, " ");
else
first = FALSE;
if(a == -1)
nchars += write_data(userhandle, write_modeldata, "-");
else if(a == 1)
nchars += write_data(userhandle, write_modeldata, "+");
else
nchars += write_data(userhandle, write_modeldata, "%+.12g ", (double)a);
nchars += write_data(userhandle, write_modeldata, "%s", get_col_name(lp, j));
/* Check if we should add a linefeed */
if((maxlen > 0) && (nchars >= maxlen) && (i < ie-1)) {
write_data(userhandle, write_modeldata, "%s", "\n");
nchars = 0;
}
}
}
return(elements);
}
STATIC void unscale_columns(lprec *lp)
{
int i, j, nz;
MATrec *mat = lp->matA;
REAL *value;
int *rownr, *colnr;
if(!lp->columns_scaled)
return;
/* Unscale OF */
for(j = 1; j <= lp->columns; j++) {
lp->orig_obj[j] = unscaled_mat(lp, lp->orig_obj[j], 0, j);
}
/* Unscale mat */
mat_validate(mat);
nz = get_nonzeros(lp);
value = &(COL_MAT_VALUE(0));
rownr = &(COL_MAT_ROWNR(0));
colnr = &(COL_MAT_COLNR(0));
for(j = 0; j < nz;
j++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) {
*value = unscaled_mat(lp, *value, *rownr, *colnr);
}
/* Unscale bounds as well */
for(i = lp->rows + 1, j = 1; i <= lp->sum; i++, j++) {
lp->orig_lowbo[i] = unscaled_value(lp, lp->orig_lowbo[i], i);
lp->orig_upbo[i] = unscaled_value(lp, lp->orig_upbo[i], i);
lp->sc_lobound[j] = unscaled_value(lp, lp->sc_lobound[j], i);
}
for(i = lp->rows + 1; i<= lp->sum; i++)
lp->scalars[i] = 1;
lp->columns_scaled = FALSE;
set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE);
}
/* List the current basis matrix columns over the selected row range */
void blockWriteBMAT(FILE *output, const char *label, lprec* lp, int first, int last)
{
int i, j, jb, k = 0;
double hold;
if(first < 0)
first = 0;
if(last < 0)
last = lp->rows;
fprintf(output, "%s", label);
fprintf(output, "\n");
for(i = first; i <= last; i++) {
for(j = 1; j <= lp->rows; j++) {
jb = lp->var_basic[j];
if(jb <= lp->rows) {
if(jb == i)
hold = 1;
else
hold = 0;
}
else
hold = get_mat(lp, i, j);
if(i == 0)
modifyOF1(lp, jb, &hold, 1);
hold = unscaled_mat(lp, hold, i, jb);
fprintf(output, " %18g", hold);
k++;
if(my_mod(k, 4) == 0) {
fprintf(output, "\n");
k = 0;
}
}
if(my_mod(k, 4) != 0) {
fprintf(output, "\n");
k = 0;
}
}
if(my_mod(k, 4) != 0)
fprintf(output, "\n");
}
MYBOOL __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector)
{
MYBOOL *isnz = NULL, status = FALSE;
REAL *values = NULL, *violation = NULL,
eps = lp->epsprimal,
*value, error, upB, loB, sortorder = -1.0;
int i, j, jj, n, *rownr, *colnr, *slkpos = NULL,
nrows = lp->rows, ncols = lp->columns, nsum = lp->sum;
int *basisnr;
MATrec *mat = lp->matA;
if(!mat_validate(mat))
return( status );
/* Create helper arrays, providing for multiple use of the violation array */
if(!allocREAL(lp, &values, nsum+1, TRUE) ||
!allocREAL(lp, &violation, nsum+1, TRUE))
goto Finish;
/* Compute the values of the constraints for the given guess vector */
i = 0;
n = get_nonzeros(lp);
rownr = &COL_MAT_ROWNR(i);
colnr = &COL_MAT_COLNR(i);
value = &COL_MAT_VALUE(i);
for(; i < n; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep)
values[*rownr] += unscaled_mat(lp, my_chsign(is_chsign(lp, *rownr), *value), *rownr, *colnr) *
guessvector[*colnr];
MEMMOVE(values+nrows+1, guessvector+1, ncols);
/* Initialize bound "violation" or primal non-degeneracy measures, expressed
as the absolute value of the differences from the closest bound. */
for(i = 1; i <= nsum; i++) {
if(i <= nrows) {
loB = get_rh_lower(lp, i);
upB = get_rh_upper(lp, i);
}
else {
loB = get_lowbo(lp, i-nrows);
upB = get_upbo(lp, i-nrows);
}
/* Free constraints/variables */
if(my_infinite(lp, loB) && my_infinite(lp, upB))
error = 0;
/* Violated constraints/variable bounds */
else if(values[i]+eps < loB)
error = loB-values[i];
else if(values[i]-eps > upB)
error = values[i]-upB;
/* Non-violated constraints/variables bounds */
else if(my_infinite(lp, upB))
error = MAX(0, values[i]-loB);
else if(my_infinite(lp, loB))
error = MAX(0, upB-values[i]);
else
error = MIN(upB-values[i], values[i]-loB); /* MAX(upB-values[i], values[i]-loB); */
if(error != 0)
violation[i] = sortorder*error;
basisvector[i] = i;
}
/* Sort decending , meaning that variables with the largest
"violations" will be designated basic. Effectively, we are performing a
greedy type algorithm, but start at the "least interesting" end. */
sortByREAL(basisvector, violation, nsum, 1, FALSE);
error = violation[1]; /* Used for setting the return value */
/* Let us check for obvious row singularities and try to fix these.
Note that we reuse the memory allocated to the violation array.
First assemble necessary basis statistics... */
slkpos = (int *) violation;
n = nrows+1;
MEMCLEAR(slkpos, n);
isnz = (MYBOOL *) (slkpos+n+1);
MEMCLEAR(isnz, n);
for(i = 1; i <= nrows; i++) {
j = abs(basisvector[i]);
if(j <= nrows) {
isnz[j] = TRUE;
slkpos[j] = i;
}
else {
j-= nrows;
jj = mat->col_end[j-1];
jj = COL_MAT_ROWNR(jj);
isnz[jj] = TRUE;
}
}
for(; i <= nsum; i++) {
j = abs(basisvector[i]);
if(j <= nrows)
slkpos[j] = i;
}
/* ...then set the corresponding slacks basic for row rank deficient positions */
for(j = 1; j <= nrows; j++) {
if(slkpos[j] == 0)
report(lp, SEVERE, "guess_basis: Internal error");
if(!isnz[j]) {
isnz[j] = TRUE;
i = slkpos[j];
swapINT(&basisvector[i], &basisvector[j]);
basisvector[j] = abs(basisvector[j]);
}
}
/* Adjust the non-basic indeces for the (proximal) bound state */
for(i = nrows+1, basisnr = basisvector+i; i <= nsum; i++, basisnr++) {
n = *basisnr;
if(n <= nrows) {
values[n] -= get_rh_lower(lp, n);
if(values[n] <= eps)
*basisnr = -(*basisnr);
}
else
if(values[n]-eps <= get_lowbo(lp, n-nrows))
*basisnr = -(*basisnr);
}
/* Lastly normalize all basic variables to be coded as lower-bounded,
or effectively zero-based in the case of free variables. */
for(i = 1; i <= nrows; i++)
basisvector[i] = -abs(basisvector[i]);
/* Clean up and return status */
status = (MYBOOL) (error <= eps);
Finish:
FREE(values);
FREE(violation);
return( status );
}
MYBOOL __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector)
{
MYBOOL *isnz, status = FALSE;
REAL *values = NULL, *violation = NULL,
eps = lp->epsprimal,
*value, error, upB, loB, sortorder = 1.0;
int i, j, jj, n, *rownr, *colnr, *slkpos,
nrows = lp->rows, ncols = lp->columns;
MATrec *mat = lp->matA;
if(!mat_validate(mat))
return( status );
/* Create helper arrays */
if(!allocREAL(lp, &values, lp->sum+1, TRUE) ||
!allocREAL(lp, &violation, lp->sum+1, TRUE))
goto Finish;
/* Compute values of slack variables for given guess vector */
i = 0;
n = get_nonzeros(lp);
rownr = &COL_MAT_ROWNR(i);
colnr = &COL_MAT_COLNR(i);
value = &COL_MAT_VALUE(i);
for(; i < n; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep)
values[*rownr] += unscaled_mat(lp, my_chsign(is_chsign(lp, *rownr), *value), *rownr, *colnr) *
guessvector[*colnr];
MEMMOVE(values+nrows+1, guessvector+1, ncols);
/* Initialize constraint bound violation measures (expressed as positive values) */
for(i = 1; i <= nrows; i++) {
upB = get_rh_upper(lp, i);
loB = get_rh_lower(lp, i);
error = values[i] - upB;
if(error > -eps)
violation[i] = sortorder*MAX(0,error);
else {
error = loB - values[i];
if(error > -eps)
violation[i] = sortorder*MAX(0,error);
else if(my_infinite(lp, loB) && my_infinite(lp, upB))
;
else if(my_infinite(lp, upB))
violation[i] = sortorder*(loB - values[i]);
else if(my_infinite(lp, loB))
violation[i] = sortorder*(values[i] - upB);
else
violation[i] = -sortorder*MAX(upB - values[i], values[i] - loB);
}
basisvector[i] = i;
}
/* Initialize user variable bound violation measures (expressed as positive values) */
for(i = 1; i <= ncols; i++) {
n = nrows+i;
upB = get_upbo(lp, i);
loB = get_lowbo(lp, i);
error = guessvector[i] - upB;
if(error > -eps)
violation[n] = sortorder*MAX(0,error);
else {
error = loB - values[n];
if(error > -eps)
violation[n] = sortorder*MAX(0,error);
else if(my_infinite(lp, loB) && my_infinite(lp, upB))
;
else if(my_infinite(lp, upB))
violation[n] = sortorder*(loB - values[n]);
else if(my_infinite(lp, loB))
violation[n] = sortorder*(values[n] - upB);
else
violation[n] = -sortorder*MAX(upB - values[n], values[n] - loB);
}
basisvector[n] = n;
}
/* Sort decending by violation; this means that variables with
the largest violations will be designated as basic */
sortByREAL(basisvector, violation, lp->sum, 1, FALSE);
error = violation[1];
/* Adjust the non-basic indeces for the (proximal) bound state */
for(i = nrows+1, rownr = basisvector+i; i <= lp->sum; i++, rownr++) {
if(*rownr <= nrows) {
values[*rownr] -= lp->orig_rhs[*rownr];
if(values[*rownr] <= eps)
*rownr = -(*rownr);
}
else
if(values[i] <= get_lowbo(lp, (*rownr)-nrows)+eps)
*rownr = -(*rownr);
}
/* Let us check for obvious row singularities and try to fix these;
First assemble necessary basis statistics... */
isnz = (MYBOOL *) values;
MEMCLEAR(isnz, nrows+1);
slkpos = (int *) violation;
MEMCLEAR(slkpos, nrows+1);
for(i = 1; i <= nrows; i++) {
j = abs(basisvector[i]);
if(j <= nrows) {
isnz[j] = TRUE;
slkpos[j] = i;
}
else {
j-= nrows;
jj = mat->col_end[j-1];
isnz[COL_MAT_ROWNR(jj)] = TRUE;
/* if(++jj < mat->col_end[j])
isnz[COL_MAT_ROWNR(jj)] = TRUE; */
}
}
for(; i <= lp->sum; i++) {
j = abs(basisvector[i]);
if(j <= nrows)
slkpos[j] = i;
}
/* ...then set the corresponding slacks basic for row rank deficient positions */
for(j = 1; j <= nrows; j++) {
#ifdef Paranoia
if(slkpos[j] == 0)
report(lp, SEVERE, "guess_basis: Internal error");
#endif
if(!isnz[j]) {
isnz[j] = TRUE;
i = slkpos[j];
swapINT(&basisvector[i], &basisvector[j]);
basisvector[j] = abs(basisvector[j]);
}
}
/* Lastly normalize all basic variables to be coded as lower-bounded */
for(i = 1; i <= nrows; i++)
basisvector[i] = -abs(basisvector[i]);
/* Clean up and return status */
status = (MYBOOL) (error <= eps);
Finish:
FREE(values);
FREE(violation);
return( status );
}
MYBOOL __WINAPI guess_basis(lprec *lp, REAL *guessvector, int *basisvector)
{
MYBOOL status = FALSE;
REAL *values = NULL, *violation = NULL,
*value, error, upB, loB, sortorder = 1.0;
int i, n, *rownr, *colnr;
MATrec *mat = lp->matA;
if(!mat_validate(lp->matA))
return( status );
/* Create helper arrays */
if(!allocREAL(lp, &values, lp->sum+1, TRUE) ||
!allocREAL(lp, &violation, lp->sum+1, TRUE))
goto Finish;
/* Compute values of slack variables for given guess vector */
i = 0;
n = get_nonzeros(lp);
rownr = &COL_MAT_ROWNR(i);
colnr = &COL_MAT_COLNR(i);
value = &COL_MAT_VALUE(i);
for(; i < n; i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep)
values[*rownr] += unscaled_mat(lp, my_chsign(is_chsign(lp, *rownr), *value), *rownr, *colnr) *
guessvector[*colnr];
MEMMOVE(values+lp->rows+1, guessvector+1, lp->columns);
/* Initialize constraint bound violation measures */
for(i = 1; i <= lp->rows; i++) {
upB = get_rh_upper(lp, i);
loB = get_rh_lower(lp, i);
error = values[i] - upB;
if(error > lp->epsprimal)
violation[i] = sortorder*error;
else {
error = loB - values[i];
if(error > lp->epsprimal)
violation[i] = sortorder*error;
else if(is_infinite(lp, loB) && is_infinite(lp, upB))
;
else if(is_infinite(lp, upB))
violation[i] = sortorder*(loB - values[i]);
else if(is_infinite(lp, loB))
violation[i] = sortorder*(values[i] - upB);
else
violation[i] = - sortorder*MAX(upB - values[i], values[i] - loB);
}
basisvector[i] = i;
}
/* Initialize user variable bound violation measures */
for(i = 1; i <= lp->columns; i++) {
n = lp->rows+i;
upB = get_upbo(lp, i);
loB = get_lowbo(lp, i);
error = guessvector[i] - upB;
if(error > lp->epsprimal)
violation[n] = sortorder*error;
else {
error = loB - values[n];
if(error > lp->epsprimal)
violation[n] = sortorder*error;
else if(is_infinite(lp, loB) && is_infinite(lp, upB))
;
else if(is_infinite(lp, upB))
violation[n] = sortorder*(loB - values[n]);
else if(is_infinite(lp, loB))
violation[n] = sortorder*(values[n] - upB);
else
violation[n] = - sortorder*MAX(upB - values[n], values[n] - loB);
}
basisvector[n] = n;
}
/* Sort decending by violation; this means that variables with
the largest violations will be designated as basic */
sortByREAL(basisvector, violation, lp->sum, 1, FALSE);
/* Adjust the non-basic indeces for the (proximal) bound state */
error = lp->epsprimal;
for(i = lp->rows+1, rownr = basisvector+i; i <= lp->sum; i++, rownr++) {
if(*rownr <= lp->rows) {
if(values[*rownr] <= get_rh_lower(lp, *rownr)+error)
*rownr = -(*rownr);
}
else
if(values[i] <= get_lowbo(lp, (*rownr)-lp->rows)+error)
*rownr = -(*rownr);
}
/* Clean up and return status */
status = (MYBOOL) (violation[1] == 0);
Finish:
FREE(values);
FREE(violation);
return( status );
}