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 MYBOOL scale_columns(lprec *lp, REAL *scaledelta)
{
int i,j, colMax, nz;
REAL *scalechange;
REAL *value;
int *colnr;
MATrec *mat = lp->matA;
/* Check that columns are in fact targeted */
if((lp->scalemode & SCALE_ROWSONLY) != 0)
return( TRUE );
if(scaledelta == NULL)
scalechange = &lp->scalars[lp->rows];
else
scalechange = &scaledelta[lp->rows];
colMax = lp->columns;
/* Scale matrix entries (including any Lagrangean constraints) */
for(i = 1; i <= lp->columns; i++) {
lp->orig_obj[i] *= scalechange[i];
}
mat_validate(lp->matA);
nz = get_nonzeros(lp);
value = &(COL_MAT_VALUE(0));
colnr = &(COL_MAT_COLNR(0));
for(i = 0; i < nz;
i++, value += matValueStep, colnr += matRowColStep) {
(*value) *= scalechange[*colnr];
}
/* Scale variable bounds as well */
for(i = 1, j = lp->rows + 1; j <= lp->sum; i++, j++) {
if(lp->orig_lowbo[j] > -lp->infinite)
lp->orig_lowbo[j] /= scalechange[i];
if(lp->orig_upbo[j] < lp->infinite)
lp->orig_upbo[j] /= scalechange[i];
if(lp->sc_lobound[i] != 0)
lp->sc_lobound[i] /= scalechange[i];
}
lp->columns_scaled = TRUE;
set_action(&lp->spx_action, ACTION_REBASE | ACTION_REINVERT | ACTION_RECOMPUTE);
return( TRUE );
}
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);
}
/* Compute the scale factor by the formulae:
FALSE: SUM (log |Aij|) ^ 2
TRUE: SUM (log |Aij| - RowScale[i] - ColScale[j]) ^ 2 */
REAL CurtisReidMeasure(lprec *lp, MYBOOL _Advanced, REAL *FRowScale, REAL *FColScale)
{
int i, nz;
REAL absvalue, logvalue;
register REAL result;
MATrec *mat = lp->matA;
REAL *value;
int *rownr, *colnr;
/* Do OF part */
result = 0;
for(i = 1; i <= lp->columns; i++) {
absvalue = fabs(lp->orig_obj[i]);
if(absvalue > 0) {
logvalue = log(absvalue);
if(_Advanced)
logvalue -= FRowScale[0] + FColScale[i];
result += logvalue*logvalue;
}
}
/* Do constraint matrix part */
mat_validate(mat);
value = &(COL_MAT_VALUE(0));
rownr = &(COL_MAT_ROWNR(0));
colnr = &(COL_MAT_COLNR(0));
nz = get_nonzeros(lp);
for(i = 0; i < nz;
i++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) {
absvalue = fabs(*value);
if(absvalue > 0) {
logvalue = log(absvalue);
if(_Advanced)
logvalue -= FRowScale[*rownr] + FColScale[*colnr];
result += logvalue*logvalue;
}
}
return( result );
}
/* List the current user data matrix columns over the selected row range */
void blockWriteAMAT(FILE *output, const char *label, lprec* lp, int first, int last)
{
int i, j, k = 0;
int nzb, nze, jb;
double hold;
MATrec *mat = lp->matA;
if(!mat_validate(mat))
return;
if(first < 0)
first = 0;
if(last < 0)
last = lp->rows;
fprintf(output, "%s", label);
fprintf(output, "\n");
if(first == 0) {
for(j = 1; j <= lp->columns; j++) {
hold = get_mat(lp, 0, j);
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;
}
first++;
}
nze = mat->row_end[first-1];
for(i = first; i <= last; i++) {
nzb = nze;
nze = mat->row_end[i];
if(nzb >= nze)
jb = lp->columns+1;
else
jb = ROW_MAT_COLNR(nzb);
for(j = 1; j <= lp->columns; j++) {
if(j < jb)
hold = 0;
else {
hold = get_mat(lp, i, j);
nzb++;
if(nzb < nze)
jb = ROW_MAT_COLNR(nzb);
else
jb = lp->columns+1;
}
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 write_lpex(lprec *lp, void *userhandle, write_modeldata_func write_modeldata)
{
int i, j, b,
nrows = lp->rows,
ncols = lp->columns,
nchars, maxlen = LP_MAXLINELEN;
MYBOOL ok;
REAL a;
char *ptr;
if(lp->matA->is_roworder) {
report(lp, IMPORTANT, "LP_writefile: Cannot write to LP file while in row entry mode.\n");
return(FALSE);
}
if(!mat_validate(lp->matA)) {
report(lp, IMPORTANT, "LP_writefile: Could not validate the data matrix.\n");
return(FALSE);
}
/* Write name of model */
ptr = get_lp_name(lp);
if(ptr != NULL)
if(*ptr)
write_lpcomment(userhandle, write_modeldata, ptr, FALSE);
else
ptr = NULL;
/* Write the objective function */
write_lpcomment(userhandle, write_modeldata, "Objective function", (MYBOOL) (ptr != NULL));
if(is_maxim(lp))
write_data(userhandle, write_modeldata, "max: ");
else
write_data(userhandle, write_modeldata, "min: ");
write_lprow(lp, 0, userhandle, write_modeldata, maxlen);
a = get_rh(lp, 0);
if(a != 0)
write_data(userhandle, write_modeldata, " %+.12g", a);
write_data(userhandle, write_modeldata, ";\n");
/* Write constraints */
if(nrows > 0)
write_lpcomment(userhandle, write_modeldata, "Constraints", TRUE);
for(j = 1; j <= nrows; j++) {
if(((lp->names_used) && (lp->row_name[j] != NULL)) || (write_lprow(lp, j, userhandle, NULL, maxlen) == 1))
ptr = get_row_name(lp, j);
else
ptr = NULL;
if((ptr != NULL) && (*ptr))
write_data(userhandle, write_modeldata, "%s: ", ptr);
#ifndef SingleBoundedRowInLP
/* Write the ranged part of the constraint, if specified */
if ((lp->orig_upbo[j]) && (lp->orig_upbo[j] < lp->infinite)) {
if(my_chsign(is_chsign(lp, j), lp->orig_rhs[j]) == -lp->infinite)
write_data(userhandle, write_modeldata, "-Inf %s ", (is_chsign(lp, j)) ? ">=" : "<=");
else if(my_chsign(is_chsign(lp, j), lp->orig_rhs[j]) == lp->infinite)
write_data(userhandle, write_modeldata, "+Inf %s ", (is_chsign(lp, j)) ? ">=" : "<=");
else
write_data(userhandle, write_modeldata, "%+.12g %s ",
(lp->orig_upbo[j]-lp->orig_rhs[j]) * (is_chsign(lp, j) ? 1.0 : -1.0) / (lp->scaling_used ? lp->scalars[j] : 1.0),
(is_chsign(lp, j)) ? ">=" : "<=");
}
#endif
if((!write_lprow(lp, j, userhandle, write_modeldata, maxlen)) && (ncols >= 1))
write_data(userhandle, write_modeldata, "0 %s", get_col_name(lp, 1));
if(lp->orig_upbo[j] == 0)
write_data(userhandle, write_modeldata, " =");
else if(is_chsign(lp, j))
write_data(userhandle, write_modeldata, " >=");
else
write_data(userhandle, write_modeldata, " <=");
if(fabs(get_rh(lp, j) + lp->infinite) < 1)
write_data(userhandle, write_modeldata, " -Inf;\n");
else if(fabs(get_rh(lp, j) - lp->infinite) < 1)
write_data(userhandle, write_modeldata, " +Inf;\n");
else
write_data(userhandle, write_modeldata, " %.12g;\n", get_rh(lp, j));
#ifdef SingleBoundedRowInLP
/* Write the ranged part of the constraint, if specified */
if ((lp->orig_upbo[j]) && (lp->orig_upbo[j] < lp->infinite)) {
if(((lp->names_used) && (lp->row_name[j] != NULL)) || (write_lprow(lp, j, userhandle, NULL, maxlen) == 1))
ptr = get_row_name(lp, j);
else
ptr = NULL;
if((ptr != NULL) && (*ptr))
write_data(userhandle, write_modeldata, "%s: ", ptr);
if((!write_lprow(lp, j, userhandle, write_modeldata, maxlen)) && (get_Ncolumns(lp) >= 1))
write_data(userhandle, write_modeldata, "0 %s", get_col_name(lp, 1));
write_data(userhandle, write_modeldata, " %s %g;\n",
(is_chsign(lp, j)) ? "<=" : ">=",
(lp->orig_upbo[j]-lp->orig_rhs[j]) * (is_chsign(lp, j) ? 1.0 : -1.0) / (lp->scaling_used ? lp->scalars[j] : 1.0));
}
#endif
}
/* Write bounds on variables */
ok = FALSE;
for(i = nrows + 1; i <= lp->sum; i++)
if(!is_splitvar(lp, i - nrows)) {
if(lp->orig_lowbo[i] == lp->orig_upbo[i]) {
if(!ok) {
write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE);
ok = TRUE;
}
write_data(userhandle, write_modeldata, "%s = %.12g;\n", get_col_name(lp, i - nrows), get_upbo(lp, i - nrows));
}
else {
#ifndef SingleBoundedRowInLP
if((lp->orig_lowbo[i] != 0) && (lp->orig_upbo[i] < lp->infinite)) {
if(!ok) {
write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE);
ok = TRUE;
}
if(lp->orig_lowbo[i] == -lp->infinite)
write_data(userhandle, write_modeldata, "-Inf");
else
write_data(userhandle, write_modeldata, "%.12g", get_lowbo(lp, i - nrows));
write_data(userhandle, write_modeldata, " <= %s <= ", get_col_name(lp, i - nrows));
if(lp->orig_lowbo[i] == lp->infinite)
write_data(userhandle, write_modeldata, "+Inf");
else
write_data(userhandle, write_modeldata, "%.12g", get_upbo(lp, i - nrows));
write_data(userhandle, write_modeldata, ";\n");
}
else
#endif
{
if(lp->orig_lowbo[i] != 0) {
if(!ok) {
write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE);
ok = TRUE;
}
if(lp->orig_lowbo[i] == -lp->infinite)
write_data(userhandle, write_modeldata, "%s >= -Inf;\n", get_col_name(lp, i - nrows));
else if(lp->orig_lowbo[i] == lp->infinite)
write_data(userhandle, write_modeldata, "%s >= +Inf;\n", get_col_name(lp, i - nrows));
else
write_data(userhandle, write_modeldata, "%s >= %.12g;\n",
get_col_name(lp, i - nrows), get_lowbo(lp, i - nrows));
}
if(lp->orig_upbo[i] != lp->infinite) {
if(!ok) {
write_lpcomment(userhandle, write_modeldata, "Variable bounds", TRUE);
ok = TRUE;
}
write_data(userhandle, write_modeldata, "%s <= %.12g;\n",
get_col_name(lp, i - nrows), get_upbo(lp, i - nrows));
}
}
}
}
/* Write optional integer section */
if(lp->int_vars > 0) {
write_lpcomment(userhandle, write_modeldata, "Integer definitions", TRUE);
i = 1;
while((i <= ncols) && !is_int(lp, i))
i++;
if(i <= ncols) {
nchars = write_data(userhandle, write_modeldata, "int %s", get_col_name(lp, i));
i++;
for(; i <= ncols; i++)
if((!is_splitvar(lp, i)) && (is_int(lp, i))) {
if((maxlen!= 0) && (nchars > maxlen)) {
write_data(userhandle, write_modeldata, "%s", "\n");
nchars = 0;
}
write_data(userhandle, write_modeldata, ",%s", get_col_name(lp, i));
}
write_data(userhandle, write_modeldata, ";\n");
}
}
/* Write optional SEC section */
if(lp->sc_vars > 0) {
write_lpcomment(userhandle, write_modeldata, "Semi-continuous variables", TRUE);
i = 1;
while((i <= ncols) && !is_semicont(lp, i))
i++;
if(i <= ncols) {
nchars = write_data(userhandle, write_modeldata, "sec %s", get_col_name(lp, i));
i++;
for(; i <= ncols; i++)
if((!is_splitvar(lp, i)) && (is_semicont(lp, i))) {
if((maxlen != 0) && (nchars > maxlen)) {
write_data(userhandle, write_modeldata, "%s", "\n");
nchars = 0;
}
nchars += write_data(userhandle, write_modeldata, ",%s", get_col_name(lp, i));
}
write_data(userhandle, write_modeldata, ";\n");
}
}
/* Write optional SOS section */
if(SOS_count(lp) > 0) {
SOSgroup *SOS = lp->SOS;
write_lpcomment(userhandle, write_modeldata, "SOS definitions", TRUE);
write_data(userhandle, write_modeldata, "SOS\n");
for(b = 0, i = 0; i < SOS->sos_count; b = SOS->sos_list[i]->priority, i++) {
nchars = write_data(userhandle, write_modeldata, "%s: ",
(SOS->sos_list[i]->name == NULL) ||
(*SOS->sos_list[i]->name==0) ? "SOS" : SOS->sos_list[i]->name); /* formatnumber12((double) lp->sos_list[i]->priority) */
for(a = 0.0, j = 1; j <= SOS->sos_list[i]->size; a = SOS->sos_list[i]->weights[j], j++) {
if((maxlen != 0) && (nchars > maxlen)) {
write_data(userhandle, write_modeldata, "%s", "\n");
nchars = 0;
}
if(SOS->sos_list[i]->weights[j] == ++a)
nchars += write_data(userhandle, write_modeldata, "%s%s",
(j > 1) ? "," : "",
get_col_name(lp, SOS->sos_list[i]->members[j]));
else
nchars += write_data(userhandle, write_modeldata, "%s%s:%.12g",
(j > 1) ? "," : "",
get_col_name(lp, SOS->sos_list[i]->members[j]),
SOS->sos_list[i]->weights[j]);
}
if(SOS->sos_list[i]->priority == ++b)
nchars += write_data(userhandle, write_modeldata, " <= %d;\n", SOS->sos_list[i]->type);
else
nchars += write_data(userhandle, write_modeldata, " <= %d:%d;\n", SOS->sos_list[i]->type, SOS->sos_list[i]->priority);
}
}
ok = TRUE;
return(ok);
}
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 );
}
MYBOOL crash_basis(lprec *lp)
{
int i;
MATrec *mat = lp->matA;
MYBOOL ok = TRUE;
/* Initialize basis indicators */
if(lp->basis_valid)
lp->var_basic[0] = FALSE;
else
default_basis(lp);
/* Set initial partial pricing blocks */
if(lp->rowblocks != NULL)
lp->rowblocks->blocknow = 1;
if(lp->colblocks != NULL)
lp->colblocks->blocknow = ((lp->crashmode == CRASH_NONE) || (lp->colblocks->blockcount == 1) ? 1 : 2);
/* Construct a basis that is in some measure the "most feasible" */
if((lp->crashmode == CRASH_MOSTFEASIBLE) && mat_validate(mat)) {
/* The logic here follows Maros */
LLrec *rowLL = NULL, *colLL = NULL;
int ii, rx, cx, ix, nz;
REAL wx, tx, *rowMAX = NULL, *colMAX = NULL;
int *rowNZ = NULL, *colNZ = NULL, *rowWT = NULL, *colWT = NULL;
REAL *value;
int *rownr, *colnr;
report(lp, NORMAL, "crash_basis: 'Most feasible' basis crashing selected\n");
/* Tally row and column non-zero counts */
ok = allocINT(lp, &rowNZ, lp->rows+1, TRUE) &&
allocINT(lp, &colNZ, lp->columns+1, TRUE) &&
allocREAL(lp, &rowMAX, lp->rows+1, FALSE) &&
allocREAL(lp, &colMAX, lp->columns+1, FALSE);
if(!ok)
goto Finish;
nz = mat_nonzeros(mat);
rownr = &COL_MAT_ROWNR(0);
colnr = &COL_MAT_COLNR(0);
value = &COL_MAT_VALUE(0);
for(i = 0; i < nz;
i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) {
rx = *rownr;
cx = *colnr;
wx = fabs(*value);
rowNZ[rx]++;
colNZ[cx]++;
if(i == 0) {
rowMAX[rx] = wx;
colMAX[cx] = wx;
colMAX[0] = wx;
}
else {
SETMAX(rowMAX[rx], wx);
SETMAX(colMAX[cx], wx);
SETMAX(colMAX[0], wx);
}
}
/* Reduce counts for small magnitude to preserve stability */
rownr = &COL_MAT_ROWNR(0);
colnr = &COL_MAT_COLNR(0);
value = &COL_MAT_VALUE(0);
for(i = 0; i < nz;
i++, rownr += matRowColStep, colnr += matRowColStep, value += matValueStep) {
rx = *rownr;
cx = *colnr;
wx = fabs(*value);
#ifdef CRASH_SIMPLESCALE
if(wx < CRASH_THRESHOLD * colMAX[0]) {
rowNZ[rx]--;
colNZ[cx]--;
}
#else
if(wx < CRASH_THRESHOLD * rowMAX[rx])
rowNZ[rx]--;
if(wx < CRASH_THRESHOLD * colMAX[cx])
colNZ[cx]--;
#endif
}
/* Set up priority tables */
ok = allocINT(lp, &rowWT, lp->rows+1, TRUE);
createLink(lp->rows, &rowLL, NULL);
ok &= (rowLL != NULL);
if(!ok)
goto Finish;
for(i = 1; i <= lp->rows; i++) {
if(get_constr_type(lp, i)==EQ)
ii = 3;
else if(lp->upbo[i] < lp->infinite)
ii = 2;
else if(fabs(lp->rhs[i]) < lp->infinite)
ii = 1;
else
ii = 0;
rowWT[i] = ii;
if(ii > 0)
appendLink(rowLL, i);
}
ok = allocINT(lp, &colWT, lp->columns+1, TRUE);
createLink(lp->columns, &colLL, NULL);
ok &= (colLL != NULL);
if(!ok)
goto Finish;
for(i = 1; i <= lp->columns; i++) {
ix = lp->rows+i;
if(is_unbounded(lp, i))
ii = 3;
else if(lp->upbo[ix] >= lp->infinite)
ii = 2;
else if(fabs(lp->upbo[ix]-lp->lowbo[ix]) > lp->epsmachine)
ii = 1;
else
ii = 0;
colWT[i] = ii;
if(ii > 0)
appendLink(colLL, i);
}
/* Loop over all basis variables */
for(i = 1; i <= lp->rows; i++) {
/* Select row */
rx = 0;
wx = -lp->infinite;
for(ii = firstActiveLink(rowLL); ii > 0; ii = nextActiveLink(rowLL, ii)) {
tx = rowWT[ii] - CRASH_SPACER*rowNZ[ii];
if(tx > wx) {
rx = ii;
wx = tx;
}
}
if(rx == 0)
break;
removeLink(rowLL, rx);
/* Select column */
cx = 0;
wx = -lp->infinite;
for(ii = mat->row_end[rx-1]; ii < mat->row_end[rx]; ii++) {
/* Update NZ column counts for row selected above */
tx = fabs(ROW_MAT_VALUE(ii));
ix = ROW_MAT_COLNR(ii);
#ifdef CRASH_SIMPLESCALE
if(tx >= CRASH_THRESHOLD * colMAX[0])
#else
if(tx >= CRASH_THRESHOLD * colMAX[ix])
#endif
colNZ[ix]--;
if(!isActiveLink(colLL, ix) || (tx < CRASH_THRESHOLD * rowMAX[rx]))
continue;
/* Now do the test for best pivot */
tx = my_sign(lp->orig_obj[ix]) - my_sign(ROW_MAT_VALUE(ii));
tx = colWT[ix] + CRASH_WEIGHT*tx - CRASH_SPACER*colNZ[ix];
if(tx > wx) {
cx = ix;
wx = tx;
}
}
if(cx == 0)
break;
removeLink(colLL, cx);
/* Update row NZ counts */
ii = mat->col_end[cx-1];
rownr = &COL_MAT_ROWNR(ii);
value = &COL_MAT_VALUE(ii);
for(; ii < mat->col_end[cx];
ii++, rownr += matRowColStep, value += matValueStep) {
wx = fabs(*value);
ix = *rownr;
#ifdef CRASH_SIMPLESCALE
if(wx >= CRASH_THRESHOLD * colMAX[0])
#else
if(wx >= CRASH_THRESHOLD * rowMAX[ix])
#endif
rowNZ[ix]--;
}
/* Set new basis variable */
set_basisvar(lp, rx, lp->rows+cx);
}
/* Clean up */
Finish:
FREE(rowNZ);
FREE(colNZ);
FREE(rowMAX);
FREE(colMAX);
FREE(rowWT);
FREE(colWT);
freeLink(&rowLL);
freeLink(&colLL);
}
/* Construct a basis that is in some measure the "least degenerate" */
else if((lp->crashmode == CRASH_LEASTDEGENERATE) && mat_validate(mat)) {
/* The logic here follows Maros */
LLrec *rowLL = NULL, *colLL = NULL;
int ii, rx, cx, ix, nz, *merit = NULL;
REAL *value, wx, hold, *rhs = NULL, *eta = NULL;
int *rownr, *colnr;
report(lp, NORMAL, "crash_basis: 'Least degenerate' basis crashing selected\n");
/* Create temporary arrays */
ok = allocINT(lp, &merit, lp->columns + 1, FALSE) &&
allocREAL(lp, &eta, lp->rows + 1, FALSE) &&
allocREAL(lp, &rhs, lp->rows + 1, FALSE);
createLink(lp->columns, &colLL, NULL);
createLink(lp->rows, &rowLL, NULL);
ok &= (colLL != NULL) && (rowLL != NULL);
if(!ok)
goto FinishLD;
MEMCOPY(rhs, lp->orig_rhs, lp->rows + 1);
for(i = 1; i <= lp->columns; i++)
appendLink(colLL, i);
for(i = 1; i <= lp->rows; i++)
appendLink(rowLL, i);
/* Loop until we have found enough new bases */
while(colLL->count > 0) {
/* Tally non-zeros matching in RHS and each active column */
nz = mat_nonzeros(mat);
rownr = &COL_MAT_ROWNR(0);
colnr = &COL_MAT_COLNR(0);
ii = 0;
MEMCLEAR(merit, lp->columns + 1);
for(i = 0; i < nz;
i++, rownr += matRowColStep, colnr += matRowColStep) {
rx = *rownr;
cx = *colnr;
if(isActiveLink(colLL, cx) && (rhs[rx] != 0)) {
merit[cx]++;
ii++;
}
}
if(ii == 0)
break;
/* Find maximal match; break ties with column length */
i = firstActiveLink(colLL);
cx = i;
for(i = nextActiveLink(colLL, i); i != 0; i = nextActiveLink(colLL, i)) {
if(merit[i] >= merit[cx]) {
if((merit[i] > merit[cx]) || (mat_collength(mat, i) > mat_collength(mat, cx)))
cx = i;
}
}
/* Determine the best pivot row */
i = mat->col_end[cx-1];
nz = mat->col_end[cx];
rownr = &COL_MAT_ROWNR(i);
value = &COL_MAT_VALUE(i);
rx = 0;
wx = 0;
MEMCLEAR(eta, lp->rows + 1);
for(; i < nz;
i++, rownr += matRowColStep, value += matValueStep) {
ix = *rownr;
hold = *value;
eta[ix] = rhs[ix] / hold;
hold = fabs(hold);
if(isActiveLink(rowLL, ix) && (hold > wx)) {
wx = hold;
rx = ix;
}
}
/* Set new basis variable */
if(rx > 0) {
/* We have to update the rhs vector for the implied transformation
in order to be able to find the new RHS non-zero pattern */
for(i = 1; i <= lp->rows; i++)
rhs[i] -= wx * eta[i];
rhs[rx] = wx;
/* Do the exchange */
set_basisvar(lp, rx, lp->rows+cx);
removeLink(rowLL, rx);
}
removeLink(colLL, cx);
}
/* Clean up */
FinishLD:
FREE(merit);
FREE(rhs);
freeLink(&rowLL);
freeLink(&colLL);
}
return( ok );
}
int CurtisReidScales(lprec *lp, MYBOOL _Advanced, REAL *FRowScale, REAL *FColScale)
{
int i, row, col, ent, nz;
REAL *RowScalem2, *ColScalem2,
*RowSum, *ColSum,
*residual_even, *residual_odd;
REAL sk, qk, ek,
skm1, qkm1, ekm1,
qkm2, qkqkm1, ekm2, ekekm1,
absvalue, logvalue,
StopTolerance;
int *RowCount, *ColCount, colMax;
int Result;
MATrec *mat = lp->matA;
REAL *value;
int *rownr, *colnr;
if(CurtisReidMeasure(lp, _Advanced, FRowScale, FColScale)<0.1*get_nonzeros(lp))
return(0);
/* Allocate temporary memory and find RowSum and ColSum measures */
nz = get_nonzeros(lp);
colMax = lp->columns;
allocREAL(lp, &RowSum, lp->rows+1, TRUE);
allocINT(lp, &RowCount, lp->rows+1, TRUE);
allocREAL(lp, &residual_odd, lp->rows+1, TRUE);
allocREAL(lp, &ColSum, colMax+1, TRUE);
allocINT(lp, &ColCount, colMax+1, TRUE);
allocREAL(lp, &residual_even, colMax+1, TRUE);
allocREAL(lp, &RowScalem2, lp->rows+1, FALSE);
allocREAL(lp, &ColScalem2, colMax+1, FALSE);
/* Set origin for row scaling */
for(i = 1; i <= colMax; i++) {
absvalue=fabs(lp->orig_obj[i]);
if(absvalue>0) {
logvalue = log(absvalue);
ColSum[i] += logvalue;
RowSum[0] += logvalue;
ColCount[i]++;
RowCount[0]++;
}
}
value = &(COL_MAT_VALUE(0));
rownr = &(COL_MAT_ROWNR(0));
colnr = &(COL_MAT_COLNR(0));
for(i = 0; i < nz;
i++, value += matValueStep, rownr += matRowColStep, colnr += matRowColStep) {
absvalue=fabs(*value);
if(absvalue>0) {
logvalue = log(absvalue);
ColSum[*colnr] += logvalue;
RowSum[*rownr] += logvalue;
ColCount[*colnr]++;
RowCount[*rownr]++;
}
}
/* Make sure we dont't have division by zero errors */
for(row = 0; row <= lp->rows; row++)
if(RowCount[row] == 0)
RowCount[row] = 1;
for(col = 1; col <= colMax; col++)
if(ColCount[col] == 0)
ColCount[col] = 1;
/* Initialize to RowScale = RowCount-1 RowSum
ColScale = 0.0
residual = ColSum - ET RowCount-1 RowSum */
StopTolerance= MAX(lp->scalelimit-floor(lp->scalelimit), DEF_SCALINGEPS);
StopTolerance *= (REAL) nz;
for(row = 0; row <= lp->rows; row++) {
FRowScale[row] = RowSum[row] / (REAL) RowCount[row];
RowScalem2[row] = FRowScale[row];
}
/* Compute initial residual */
for(col = 1; col <= colMax; col++) {
FColScale[col] = 0;
ColScalem2[col] = 0;
residual_even[col] = ColSum[col];
if(lp->orig_obj[col] != 0)
residual_even[col] -= RowSum[0] / (REAL) RowCount[0];
i = mat->col_end[col-1];
rownr = &(COL_MAT_ROWNR(i));
ent = mat->col_end[col];
for(; i < ent;
i++, rownr += matRowColStep) {
residual_even[col] -= RowSum[*rownr] / (REAL) RowCount[*rownr];
}
}
/* Compute sk */
sk = 0;
skm1 = 0;
for(col = 1; col <= colMax; col++)
sk += (residual_even[col]*residual_even[col]) / (REAL) ColCount[col];
Result = 0;
qk=1; qkm1=0; qkm2=0;
ek=0; ekm1=0; ekm2=0;
while(sk>StopTolerance) {
/* Given the values of residual and sk, construct
ColScale (when pass is even)
RowScale (when pass is odd) */
qkqkm1 = qk * qkm1;
ekekm1 = ek * ekm1;
if((Result % 2) == 0) { /* pass is even; construct RowScale[pass+1] */
if(Result != 0) {
for(row = 0; row <= lp->rows; row++)
RowScalem2[row] = FRowScale[row];
if(qkqkm1 != 0) {
for(row = 0; row <= lp->rows; row++)
FRowScale[row]*=(1 + ekekm1 / qkqkm1);
for(row = 0; row<=lp->rows; row++)
FRowScale[row]+=(residual_odd[row] / (qkqkm1 * (REAL) RowCount[row]) -
RowScalem2[row] * ekekm1 / qkqkm1);
}
}
}
else { /* pass is odd; construct ColScale[pass+1] */
for(col = 1; col <= colMax; col++)
ColScalem2[col] = FColScale[col];
if(qkqkm1 != 0) {
for(col = 1; col <= colMax; col++)
FColScale[col] *= (1 + ekekm1 / qkqkm1);
for(col = 1; col <= colMax; col++)
FColScale[col] += (residual_even[col] / ((REAL) ColCount[col] * qkqkm1) -
ColScalem2[col] * ekekm1 / qkqkm1);
}
}
/* update residual and sk (pass + 1) */
if((Result % 2) == 0) { /* even */
/* residual */
for(row = 0; row <= lp->rows; row++)
residual_odd[row] *= ek;
for(i = 1; i <= colMax; i++)
if(lp->orig_obj[i] != 0)
residual_odd[0] += (residual_even[i] / (REAL) ColCount[i]);
rownr = &(COL_MAT_ROWNR(0));
colnr = &(COL_MAT_COLNR(0));
for(i = 0; i < nz;
i++, rownr += matRowColStep, colnr += matRowColStep) {
residual_odd[*rownr] += (residual_even[*colnr] / (REAL) ColCount[*colnr]);
}
for(row = 0; row <= lp->rows; row++)
residual_odd[row] *= (-1 / qk);
/* sk */
skm1 = sk;
sk = 0;
for(row = 0; row <= lp->rows; row++)
sk += (residual_odd[row]*residual_odd[row]) / (REAL) RowCount[row];
}
else { /* odd */
/* residual */
for(col = 1; col <= colMax; col++)
residual_even[col] *= ek;
for(i = 1; i <= colMax; i++)
if(lp->orig_obj[i] != 0)
residual_even[i] += (residual_odd[0] / (REAL) RowCount[0]);
rownr = &(COL_MAT_ROWNR(0));
colnr = &(COL_MAT_COLNR(0));
for(i = 0; i < nz;
i++, rownr += matRowColStep, colnr += matRowColStep) {
residual_even[*colnr] += (residual_odd[*rownr] / (REAL) RowCount[*rownr]);
}
for(col = 1; col <= colMax; col++)
residual_even[col] *= (-1 / qk);
/* sk */
skm1 = sk;
sk = 0;
for(col = 1; col <= colMax; col++)
sk += (residual_even[col]*residual_even[col]) / (REAL) ColCount[col];
}
/* Compute ek and qk */
ekm2=ekm1;
ekm1=ek;
ek=qk * sk / skm1;
qkm2=qkm1;
qkm1=qk;
qk=1-ek;
Result++;
}
/* Synchronize the RowScale and ColScale vectors */
ekekm1 = ek * ekm1;
if(qkm1 != 0) {
if((Result % 2) == 0) { /* pass is even, compute RowScale */
for(row = 0; row<=lp->rows; row++)
FRowScale[row]*=(1.0 + ekekm1 / qkm1);
for(row = 0; row<=lp->rows; row++)
FRowScale[row]+=(residual_odd[row] / (qkm1 * (REAL) RowCount[row]) -
RowScalem2[row] * ekekm1 / qkm1);
}
else { /* pass is odd, compute ColScale */
for(col=1; col<=colMax; col++)
FColScale[col]*=(1 + ekekm1 / qkm1);
for(col=1; col<=colMax; col++)
FColScale[col]+=(residual_even[col] / ((REAL) ColCount[col] * qkm1) -
ColScalem2[col] * ekekm1 / qkm1);
}
}
/* Do validation, if indicated */
if(FALSE && mat_validate(mat)){
double check, error;
/* CHECK: M RowScale + E ColScale = RowSum */
error = 0;
for(row = 0; row <= lp->rows; row++) {
check = (REAL) RowCount[row] * FRowScale[row];
if(row == 0) {
for(i = 1; i <= colMax; i++) {
if(lp->orig_obj[i] != 0)
check += FColScale[i];
}
}
else {
i = mat->row_end[row-1];
ent = mat->row_end[row];
for(; i < ent; i++) {
col = ROW_MAT_COLNR(i);
check += FColScale[col];
}
}
check -= RowSum[row];
error += check*check;
}
/* CHECK: E^T RowScale + N ColScale = ColSum */
error = 0;
for(col = 1; col <= colMax; col++) {
check = (REAL) ColCount[col] * FColScale[col];
if(lp->orig_obj[col] != 0)
check += FRowScale[0];
i = mat->col_end[col-1];
ent = mat->col_end[col];
rownr = &(COL_MAT_ROWNR(i));
for(; i < ent;
i++, rownr += matRowColStep) {
check += FRowScale[*rownr];
}
check -= ColSum[col];
error += check*check;
}
}
/* Convert to scaling factors (rounding to nearest power
of 2 can optionally be done as a separate step later) */
for(col = 1; col <= colMax; col++) {
absvalue = exp(-FColScale[col]);
if(absvalue < MIN_SCALAR) absvalue = MIN_SCALAR;
if(absvalue > MAX_SCALAR) absvalue = MAX_SCALAR;
if(!is_int(lp,col) || is_integerscaling(lp))
FColScale[col] = absvalue;
else
FColScale[col] = 1;
}
for(row = 0; row <= lp->rows; row++) {
absvalue = exp(-FRowScale[row]);
if(absvalue < MIN_SCALAR) absvalue = MIN_SCALAR;
if(absvalue > MAX_SCALAR) absvalue = MAX_SCALAR;
FRowScale[row] = absvalue;
}
/* free temporary memory */
FREE(RowSum);
FREE(ColSum);
FREE(RowCount);
FREE(ColCount);
FREE(residual_even);
FREE(residual_odd);
FREE(RowScalem2);
FREE(ColScalem2);
return(Result);
}
