void prob_map(Mat* in, Mat* out, double factor)
{
printf("Computing probability map\n");
double vmean = 0;
double vmin = -1;
double vmax = -1;
for (int j = 0; j < in->m; j++)
{
for (int i = 0; i < in->n; i++)
{
if (i == j) continue;
double v = get_mat(in, i, j);
vmean += v;
if (vmin == -1)
vmin = vmax = v;
vmin = fmin(vmin, v);
vmax = fmax(vmax, v);
}
}
vmean /= in->m * in->n;
printf("...Mean non-zero ssd = %f\n", vmean);
printf("...Min non-zero ssd = %f\n", vmin);
printf("...Max non-zero ssd = %f\n", vmax);
double sigma = factor * vmean;
printf("...Sigma = %f\n", sigma);
// Compute probabilities
for (int i = 0; i < in->n - 1; i++)
{
for (int j = 0; j < in->m; j++)
{
double v = get_mat(in, i + 1, j);
double p = exp(-v / sigma);
set_mat(out, i, j, p);
}
}
// Avoid transitions to the last frame
for (int j = 0; j < in->m; j++)
set_mat(out, in->n - 1, j, 0);
for (int i = 0; i < in->n; i++)
set_mat(out, i, in->m - 1, 0);
// Normalize
for (int i = 0; i < in->n; i++)
{
double sum = 0;
for (int j = 0; j < in->m; j++)
sum += get_mat(out, i, j);
for (int j = 0; j < in->m; j++)
set_mat(out, i, j, get_mat(out, i, j) / sum);
}
}
void deadend_filt(Mat* in, Mat* out, double alpha, int p, double thresh)
{
printf("Applying dead-end filter\n");
printf("...Alpha = %f\n", alpha);
printf("...p = %d\n", p);
printf("...Threshold = %f\n", thresh);
int n = in->n;
int m = in->m;
double* ms = (double*) malloc(n * sizeof(double));
// Initialize
for (int i = 0; i < n; i++)
{
for (int j = 0; j < m; j++)
set_mat(out, i, j, pow(get_mat(in, i, j), p));
}
// Iterate
double cmax = -1;
int iters = 0;
while(cmax == -1 || cmax > thresh)
{
for (int i = 0; i < n; i++)
{
double dmin = get_mat(out, i, 0);
for (int j = 0; j < m; j++)
{
if (j != i)
dmin = fmin(dmin, get_mat(out, i, j));
}
ms[i] = dmin;
}
for (int i = n - 1; i >= 0; i--)
{
cmax = 0;
for (int j = 0; j < m; j++)
{
double ta = pow(get_mat(in, i, j), p);
double tb = alpha * ms[j];
double next = ta + tb;
double prev = get_mat(out, i, j);
double diff = abs(next - prev);
cmax = fmax(cmax, diff);
set_mat(out, i, j, next);
}
}
iters++;
}
printf("...Corrected for dead-ends after %d iterations\n", iters);
}
void diag_filt(Mat* in, Mat* out)
{
printf("Applying diagonal filter\n");
int n = in->n;
int m = in->m;
int d = 1;
for (int i = 0; i < n; i++)
{
for (int j = 0; j < m; j++)
{
double c = 0;
double v = 0;
for (int k = -d; k < d; k++)
{
int di = i + k;
int dj = j + k;
if (di >= 0 && di < n && dj >= 0 && dj < m)
{
v += get_mat(in, i + k, j + k);
c++;
}
}
set_mat(out, i, j, v / c);
}
}
}
void ssd(Vid* vid, Mat* out)
{
int nf = vid->nf;
IplImage** imgs = vid->imgs;
printf("Computing SSDs\n");
for (int j = 0; j < nf; j++)
{
for (int i = j + 1; i < nf; i++)
{
double v = ssd(imgs[i], imgs[j]);
set_mat(out, i, j, v);
set_mat(out, j, i, v);
}
set_mat(out, j, j, 0.0);
}
}
pyne::Material pyne::Material::set_mat (std::set<std::string> nucset, double value, std::string n)
{
// Sets a substream from this stream based on a set of strings.
// Strings can be of any form.
std::set<int> iset;
for (std::set<std::string>::iterator i = nucset.begin(); i != nucset.end(); i++)
{
iset.insert(pyne::nucname::zzaaam(*i));
};
return set_mat(iset, value, n);
};
/* fill in element (Row,Column) of the matrix
Row in [0..Rows] and Column in [1..Columns] */
long __declspec(dllexport) WINAPI _set_mat(lprec *lp, long row, long column, double value)
{
long ret;
if (lp != NULL) {
freebuferror();
ret = set_mat(lp, row, column, value);
}
else
ret = 0;
return(ret);
}
void null_matrix(matrix_t *mat, int r)
{
int i = 0, j = 0;
mat->m = r;
mat->n = r;
alloc_matrix(mat);
for (i = 0; i<mat->m; i++) {
for (j = 0; j<mat->n; j++) {
set_mat(*mat, i, j, (float)0);
}
}
}
void random_matrix(matrix_t *mat, int r)
{
int i = 0, j = 0;
mat->m = r;
mat->n = r;
alloc_matrix(mat);
for (i = 0; i<mat->m; i++) {
for (j = 0; j<mat->n; j++) {
set_mat(*mat, i, j,
((float)(((float)(rand()%100))/(float)(rand()%50))) );
}
}
}
matrix_t set_zero(matrix_t mat)
{
//Assuming Square matrix will add the check latter
int row_len = mat.row_end - mat.row_start + 1;
int column_len = mat.column_end - mat.column_start + 1;
int i = 0, j = 0;
for (i = 0; i<row_len; i++) {
for (j = 0; j<column_len; j++) {
set_mat(mat, i, j, 0);
}
}
return mat;
}
matrix_t matrix_subtraction(matrix_t mat_a, matrix_t mat_b,
matrix_t mat_c)
{
//Assuming Square matrix will add the check latter
int row_len = mat_c.row_end - mat_c.row_start + 1;
int column_len = mat_c.column_end - mat_c.column_start + 1;
int i = 0, j = 0;
for (i = 0; i<row_len; i++) {
for (j = 0; j<column_len; j++) {
set_mat(mat_c, i, j,
get_mat(mat_a, i, j)-get_mat(mat_b, i, j));
}
}
return mat_c;
}
matrix_t matrix_multiplication(matrix_t mat_a, matrix_t mat_b,
matrix_t mat_c)
{
int i = 0, j = 0, k = 0;
int limit = mat_c.row_end - mat_c.row_start;
/* if (validate_matrix(mat_a, mat_b, mat_c) == FALSE) { */
/* return mat_c; */
/* } */
for(i=0; i<=limit; i++) {
for(j=0; j<=limit; j++) {
for (k = 0; k<=limit; k++) {
set_mat(mat_c, i, j,
get_mat(mat_c, i, j)
+ (get_mat(mat_a, i, k)
*get_mat(mat_b, k, j)));
}
}
}
return mat_c;
}
int
py_shader_param_set(PyShaderParamObject *self, PyObject *val)
{
const struct ShaderParam *p = self->param;
int ok = 0;
if (PyObject_TypeCheck(val, &py_mat_type)) {
ok = set_mat(p, val);
} else if (PyObject_TypeCheck(val, &py_vec_type)) {
ok = set_vec(p, val);
} else if (PyFloat_Check(val)) {
ok = set_float(p, val);
} else if (PyLong_Check(val)) {
ok = set_int(p, val);
} else if (PyObject_TypeCheck(val, &py_array_type)) {
ok = set_array(p, (PyArrayObject*)val);
} else {
PyErr_Format(
PyExc_TypeError,
"unsupported type '%s' for shader param '%s'",
Py_TYPE(val)->tp_name,
p->name
);
return 0;
}
if (!ok) {
PyErr_Format(
PyExc_RuntimeError,
"failed to set shader param '%s'",
p->name
);
error_print_tb();
error_clear();
return 0;
}
return 1;
}
int read_nblist(FILE *in,FILE *fp,int **mat,int natoms,bool bSymm)
{
bool bNL;
char buf[256],b1[32],b2[32],solv[256],il_code[256];
int i,ii,j,nnbl,full,icmp,nri,isolv;
int iatom,nrj,nj,shift,gid,nargs,njtot=0;
do {
if (fgets2(buf,255,in) == NULL)
gmx_fatal(FARGS,"EOF when looking for '%s' in logfile",header);
} while (strstr(buf,header) == NULL);
do {
do {
if (fgets2(buf,255,in) == NULL)
return njtot;
} while (strstr(buf,"nri:") == NULL);
if (0) {
if ((nargs = sscanf(buf,"%*s%s%*s%s",il_code,solv)) != 2) {
fprintf(stderr,"Can not find the right il_code\n");
return njtot;
}
for(isolv=0; (isolv<esolNR); isolv++)
if (strstr(esol_names[isolv],solv) != NULL)
break;
if (isolv == esolNR) {
fprintf(stderr,"Can not read il_code or solv (nargs=%d)\n",nargs);
return njtot;
}
}
else
isolv = enlistATOM;
/* gmx_fatal(FARGS,"Can not read il_code or solv (nargs=%d)",nargs);*/
if ((nargs = sscanf(buf,"%*s%d%*s%d",&nri,&nrj)) != 2)
gmx_fatal(FARGS,"Can not read nri or nrj (nargs=%d)",nargs);
for(ii=0; (ii<nri); ii++) {
if ((nargs = fscanf(in,"%*s%d%*s%d%*s%d%*s%d",
&iatom,&shift,&gid,&nj)) != 4)
gmx_fatal(FARGS,"Can not read iatom, shift gid or nj (nargs=%d)",nargs);
/* Number shifts from 1 to 27 iso 0 to 26 to distinguish uninitialized
* matrix elements.
*/
range_check(iatom,0,natoms);
for(i=0; (i<nj); i++) {
if ((nargs = fscanf(in,"%*s%d",&j)) != 1)
gmx_fatal(FARGS,"Can not read j");
range_check(j,0,natoms);
switch (isolv) {
case enlistATOM:
set_mat(fp,mat,iatom,1,j,1,bSymm,shift);
njtot++;
break;
case enlistWATER:
set_mat(fp,mat,iatom,3,j,1,bSymm,shift);
njtot+=3;
break;
case enlistWATERWATER:
set_mat(fp,mat,iatom,3,j,3,bSymm,shift);
njtot+=9;
break;
default:
gmx_incons("non-existing solvent type");
}
}
}
fprintf(fp,"nri = %d nrj = %d\n",nri,nrj);
} while (TRUE);
return -1;
}
int main ( int argv, char * argc[] )
{
# if defined ERROR
# undef ERROR
# endif
# define ERROR() { fprintf(stderr, "Error\n"); exit(1); }
lprec *lp;
int majorversion, minorversion, release, build;
#if defined FORTIFY
Fortify_EnterScope();
#endif
lp_solve_version(&majorversion, &minorversion, &release, &build);
printf("lp_solve %d.%d.%d.%d demo\n\n", majorversion, minorversion, release, build);
printf("This demo will show most of the features of lp_solve %d.%d.%d.%d\n", majorversion, minorversion, release, build);
press_ret();
printf("\nWe start by creating a new problem with 4 variables and 0 constraints\n");
printf("We use: lp=make_lp(0,4);\n");
if ((lp = make_lp(0,4)) == NULL)
ERROR();
press_ret();
printf("We can show the current problem with print_lp(lp)\n");
print_lp(lp);
press_ret();
printf("Now we add some constraints\n");
printf("add_constraint(lp, {0, 3, 2, 2, 1}, LE, 4)\n");
{
double row[] = {0, 3, 2, 2, 1};
if (!add_constraint(lp, row, LE, 4))
ERROR();
}
print_lp(lp);
press_ret();
printf("add_constraintex is now used to add a row. Only the npn-zero values must be specfied with this call.\n");
printf("add_constraintex(lp, 3, {4, 3, 1}, {2, 3, 4}, GE, 3)\n");
{
int colno[] = {2, 3, 4};
double row[] = {4, 3, 1};
if (!add_constraintex(lp, sizeof(colno) / sizeof(*colno), row, colno, GE, 3))
ERROR();
}
print_lp(lp);
press_ret();
printf("Set the objective function\n");
printf("set_obj_fn(lp, {0, 2, 3, -2, 3})\n");
{
double row[] = {0, 2, 3, -2, 3};
if (!set_obj_fn(lp, row))
ERROR();
}
print_lp(lp);
press_ret();
printf("Now solve the problem with printf(solve(lp));\n");
printf("%d",solve(lp));
press_ret();
printf("The value is 0, this means we found an optimal solution\n");
printf("We can display this solution with print_objective(lp) and print_solution(lp)\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("The dual variables of the solution are printed with\n");
printf("print_duals(lp);\n");
print_duals(lp);
press_ret();
printf("We can change a single element in the matrix with\n");
printf("set_mat(lp,2,1,0.5)\n");
if (!set_mat(lp,2,1,0.5))
ERROR();
print_lp(lp);
press_ret();
printf("If we want to maximize the objective function use set_maxim(lp);\n");
set_maxim(lp);
print_lp(lp);
press_ret();
printf("after solving this gives us:\n");
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
print_duals(lp);
press_ret();
printf("Change the value of a rhs element with set_rh(lp,1,7.45)\n");
set_rh(lp,1,7.45);
print_lp(lp);
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We change %s to the integer type with\n", get_col_name(lp, 4));
printf("set_int(lp, 4, TRUE)\n");
set_int(lp, 4, TRUE);
print_lp(lp);
printf("We set branch & bound debugging on with set_debug(lp, TRUE)\n");
set_debug(lp, TRUE);
printf("and solve...\n");
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We can set bounds on the variables with\n");
printf("set_lowbo(lp,2,2); & set_upbo(lp,4,5.3)\n");
set_lowbo(lp,2,2);
set_upbo(lp,4,5.3);
print_lp(lp);
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Now remove a constraint with del_constraint(lp, 1)\n");
del_constraint(lp,1);
print_lp(lp);
printf("Add an equality constraint\n");
{
double row[] = {0, 1, 2, 1, 4};
if (!add_constraint(lp, row, EQ, 8))
ERROR();
}
print_lp(lp);
press_ret();
printf("A column can be added with:\n");
printf("add_column(lp,{3, 2, 2});\n");
{
double col[] = {3, 2, 2};
if (!add_column(lp, col))
ERROR();
}
print_lp(lp);
press_ret();
printf("A column can be removed with:\n");
printf("del_column(lp,3);\n");
del_column(lp,3);
print_lp(lp);
press_ret();
printf("We can use automatic scaling with:\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
print_lp(lp);
press_ret();
printf("The function get_mat(lprec *lp, int row, int column) returns a single\n");
printf("matrix element\n");
printf("%s get_mat(lp,2,3), get_mat(lp,1,1); gives\n","printf(\"%f %f\\n\",");
printf("%f %f\n", (double)get_mat(lp,2,3), (double)get_mat(lp,1,1));
printf("Notice that get_mat returns the value of the original unscaled problem\n");
press_ret();
printf("If there are any integer type variables, then only the rows are scaled\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
printf("set_int(lp,3,FALSE);\n");
set_int(lp,3,FALSE);
print_lp(lp);
press_ret();
solve(lp);
printf("print_objective, print_solution gives the solution to the original problem\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Scaling is turned off with unscale(lp);\n");
unscale(lp);
print_lp(lp);
press_ret();
printf("Now turn B&B debugging off and simplex tracing on with\n");
printf("set_debug(lp, FALSE), set_trace(lp, TRUE) and solve(lp)\n");
set_debug(lp, FALSE);
set_trace(lp, TRUE);
press_ret();
solve(lp);
printf("Where possible, lp_solve will start at the last found basis\n");
printf("We can reset the problem to the initial basis with\n");
printf("default_basis(lp). Now solve it again...\n");
press_ret();
default_basis(lp);
solve(lp);
printf("It is possible to give variables and constraints names\n");
printf("set_row_name(lp,1,\"speed\"); & set_col_name(lp,2,\"money\")\n");
if (!set_row_name(lp,1,"speed"))
ERROR();
if (!set_col_name(lp,2,"money"))
ERROR();
print_lp(lp);
printf("As you can see, all column and rows are assigned default names\n");
printf("If a column or constraint is deleted, the names shift place also:\n");
press_ret();
printf("del_column(lp,1);\n");
del_column(lp,1);
print_lp(lp);
press_ret();
write_lp(lp, "lp.lp");
delete_lp(lp);
printf("An lp structure can be created and read from a .lp file\n");
printf("lp = read_lp(\"lp.lp\", TRUE);\n");
printf("The verbose option is used\n");
if ((lp = read_LP("lp.lp", TRUE, "test")) == NULL)
ERROR();
press_ret();
printf("lp is now:\n");
print_lp(lp);
press_ret();
printf("solution:\n");
set_debug(lp, TRUE);
solve(lp);
set_debug(lp, FALSE);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
delete_lp(lp);
#if defined FORTIFY
Fortify_LeaveScope();
#endif
return 0;
}
int CLPLpsolve::changeCoefs(int rowindex, int varIndex, double coef)
{
set_mat(m_env, rowindex + 1, varIndex + 1, coef);
return 1;
}
int main(void)
{
lprec *lp1,*lp2;
FILE *input_file;
printf("lp_solve 2.0 demo by Jeroen J. Dirks ([email protected])\n\n");
printf("This demo will show most of the features of lp_solve 2.0\n");
press_ret();
printf("\nWe start by creating a new problem with 4 variables and 0 constraints\n");
printf("We use: lp1=make_lp(0,4);\n");
lp1=make_lp(0,4);
press_ret();
printf("We can show the current problem with print_lp(lp1)\n");
print_lp(lp1);
press_ret();
printf("Now we add some constraints\n");
printf("str_add_constraint(lp1, \"3 2 2 1\" ,LE,4)\n");
printf("This is the string version of add_constraint. For the normal version\n");
printf("of add_constraint see the file lpkit.h\n");
str_add_constraint(lp1, "3 2 2 1", LE, 4);
print_lp(lp1);
press_ret();
printf("str_add_constraint(lp1, \"0 4 3 1\" ,GE,3)\n");
str_add_constraint(lp1, "0 4 3 1", GE, 3);
print_lp(lp1);
press_ret();
printf("Set the objective function\n");
printf("str_set_obj_fn(lp1, \"2 3 -2 3\")\n");
str_set_obj_fn(lp1, "2 3 -2 3");
print_lp(lp1);
press_ret();
printf("Now solve the problem with printf(solve(lp1));\n");
printf("%d",solve(lp1));
press_ret();
printf("The value is 0, this means we found an optimal solution\n");
printf("We can display this solution with print_solution(lp1)\n");
print_solution(lp1);
press_ret();
printf("The dual variables of the solution are printed with\n");
printf("print_duals(lp1);\n");
print_duals(lp1);
press_ret();
printf("We can change a single element in the matrix with\n");
printf("set_mat(lp1,2,1,0.5)\n");
set_mat(lp1,2,1,0.5);
print_lp(lp1);
press_ret();
printf("It we want to maximise the objective function use set_maxim(lp1);\n");
set_maxim(lp1);
print_lp(lp1);
press_ret();
printf("after solving this gives us:\n");
solve(lp1);
print_solution(lp1);
print_duals(lp1);
press_ret();
printf("Change the value of a rhs element with set_rh(lp1,1,7.45)\n");
set_rh(lp1,1,7.45);
print_lp(lp1);
solve(lp1);
print_solution(lp1);
press_ret();
printf("We change Var[4] to the integer type with\n");
printf("set_int(lp1, 4, TRUE)\n");
set_int(lp1, 4, TRUE);
print_lp(lp1);
printf("We set branch & bound debugging on with lp1->debug=TRUE\n");
lp1->debug=TRUE;
printf("and solve...\n");
press_ret();
solve(lp1);
print_solution(lp1);
press_ret();
printf("We can set bounds on the variables with\n");
printf("set_lowbo(lp1,2,2); & set_upbo(lp1,4,5.3)\n");
set_lowbo(lp1,2,2);
set_upbo(lp1,4,5.3);
print_lp(lp1);
press_ret();
solve(lp1);
print_solution(lp1);
press_ret();
printf("Now remove a constraint with del_constraint(lp1, 1)\n");
del_constraint(lp1,1);
print_lp(lp1);
printf("Add an equality constraint\n");
str_add_constraint(lp1, "1 2 1 4", EQ, 8);
print_lp(lp1);
press_ret();
printf("A column can be added with:\n");
printf("str_add_column(lp1,\"3 2 2\");\n");
str_add_column(lp1,"3 2 2");
print_lp(lp1);
press_ret();
printf("A column can be removed with:\n");
printf("del_column(lp1,3);\n");
del_column(lp1,3);
print_lp(lp1);
press_ret();
printf("We can use automatic scaling with:\n");
printf("auto_scale(lp1);\n");
auto_scale(lp1);
print_lp(lp1);
press_ret();
printf("The function mat_elm(lprec *lp, int row, int column) returns a single\n");
printf("matrix element\n");
printf("%s mat_elm(lp1,2,3), mat_elm(lp1,1,1); gives\n","printf(\"%f %f\\n\",");
printf("%f %f\n",mat_elm(lp1,2,3), mat_elm(lp1,1,1));
printf("Notice that mat_elm returns the value of the original unscaled problem\n");
press_ret();
printf("It there are any integer type variables, then only the rows are scaled\n");
printf("set_int(lp1,3,FALSE);\n");
printf("auto_scale(lp1);\n");
set_int(lp1,3,FALSE);
auto_scale(lp1);
print_lp(lp1);
press_ret();
solve(lp1);
printf("print_solution gives the solution to the original problem\n");
print_solution(lp1);
press_ret();
printf("Scaling is turned off with unscale(lp1);\n");
unscale(lp1);
print_lp(lp1);
press_ret();
printf("Now turn B&B debugging of and simplex tracing on with\n");
printf("lp1->debug=FALSE, lp1->trace=TRUE and solve(lp1)\n");
lp1->debug=FALSE;
lp1->trace=TRUE;
press_ret();
solve(lp1);
printf("Where possible, lp_solve will start at the last found basis\n");
printf("We can reset the problem to the initial basis with\n");
printf("reset_basis(lp1). Now solve it again...\n");
press_ret();
reset_basis(lp1);
solve(lp1);
press_ret();
printf("It is possible to give variables and constraints names\n");
printf("set_row_name(lp1,1,\"speed\"); & set_col_name(lp1,2,\"money\")\n");
set_row_name(lp1,1,"speed");
set_col_name(lp1,2,"money");
print_lp(lp1);
printf("As you can see, all column and rows are assigned default names\n");
printf("If a column or constraint is deleted, the names shift place also:\n");
press_ret();
printf("del_column(lp1,1);\n");
del_column(lp1,1);
print_lp(lp1);
press_ret();
printf("A lp structure can be created and read from a .lp file\n");
printf("input_file=fopen(\"lp_examples/demo_lag.lp\",\"r\");\n");
printf("lp2 = read_lp_file(input_file, TRUE);\n");
printf("The verbose option is used\n");
input_file = fopen("lp_examples/demo_lag.lp", "r");
if (input_file == NULL)
{
printf("Can't find demo_lag.lp, stopping\n");
exit(EXIT_FAILURE);
}
lp2 = read_lp_file(input_file, TRUE, "test");
press_ret();
printf("lp2 is now:\n");
print_lp(lp2);
press_ret();
printf("solution:\n");
lp2->debug=TRUE;
solve(lp2);
lp2->debug=FALSE;
print_solution(lp2);
press_ret();
printf("You can see that branch & bound was used in this problem\n");
printf("Now remove the last constraint and use lagrangian relaxation\n");
printf("del_constraint(lp2,6);\n");
printf("str_add_lag_con(lp2, \"1 1 1 0 0 0\", LE, 2);\n");
del_constraint(lp2,6);
str_add_lag_con(lp2, "1 1 1 0 0 0", LE, 2);
print_lp(lp2);
printf("Lagrangian relaxation is used in some heuristics. It is now possible\n");
printf("to get a feasible integer soltution without usage of branch & bound.\n");
printf("Use lag_solve(lp2, 0, 40, TRUE); 0 is the initial bound, 30 the maximum\n");
printf("number of iterations, the last variable turns the verbose mode on.\n");
press_ret();
printf("%d\n",lag_solve(lp2, 0, 30, TRUE));
printf("The returncode of lag_solve is 6 or FEAS_FOUND. this means that a feasible\n");
printf("solution has been found. For a list of other possible return values\n");
printf("see \"lpkit.h\". Print this solution with print_solution\n");
print_solution(lp2);
press_ret();
return(0);
}
int demoImplicit(void)
{
# if defined ERROR
# undef ERROR
# endif
# define ERROR() { fprintf(stderr, "Error\n"); return(1); }
lprec *lp;
int majorversion, minorversion, release, build;
char buf[1024];
if ((lp = make_lp(0,4)) == NULL)
ERROR();
lp_solve_version(&majorversion, &minorversion, &release, &build);
/* let's first demonstrate the logfunc callback feature */
put_logfunc(lp, Mylogfunc, 0);
sprintf(buf, "lp_solve %d.%d.%d.%d demo\n\n", majorversion, minorversion, release, build);
print_str(lp, buf);
solve(lp); /* just to see that a message is send via the logfunc routine ... */
/* ok, that is enough, no more callback */
put_logfunc(lp, NULL, 0);
/* Now redirect all output to a file */
/* set_outputfile(lp, "result.txt"); */
/* set an abort function. Again optional */
put_abortfunc(lp, Myctrlcfunc, 0);
/* set a message function. Again optional */
put_msgfunc(lp, Mymsgfunc, 0, MSG_PRESOLVE | MSG_LPFEASIBLE | MSG_LPOPTIMAL | MSG_MILPEQUAL | MSG_MILPFEASIBLE | MSG_MILPBETTER);
printf("lp_solve %d.%d.%d.%d demo\n\n", majorversion, minorversion, release, build);
printf("This demo will show most of the features of lp_solve %d.%d.%d.%d\n", majorversion, minorversion, release, build);
press_ret();
printf("\nWe start by creating a new problem with 4 variables and 0 constraints\n");
printf("We use: lp=make_lp(0,4);\n");
press_ret();
printf("We can show the current problem with print_lp(lp)\n");
print_lp(lp);
press_ret();
printf("Now we add some constraints\n");
printf("str_add_constraint(lp, \"3 2 2 1\" ,LE,4)\n");
printf("This is the string version of add_constraint. For the normal version\n");
printf("of add_constraint see the help file.\n");
if (!str_add_constraint(lp, "3 2 2 1", LE, 4))
ERROR();
print_lp(lp);
press_ret();
printf("str_add_constraint(lp, \"0 4 3 1\" ,GE,3)\n");
if (!str_add_constraint(lp, "0 4 3 1", GE, 3))
ERROR();
print_lp(lp);
press_ret();
printf("Set the objective function\n");
printf("str_set_obj_fn(lp, \"2 3 -2 3\")\n");
if (!str_set_obj_fn(lp, "2 3 -2 3"))
ERROR();
print_lp(lp);
press_ret();
printf("Now solve the problem with printf(solve(lp));\n");
printf("%d",solve(lp));
press_ret();
printf("The value is 0, this means we found an optimal solution\n");
printf("We can display this solution with print_objective(lp) and print_solution(lp)\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("The dual variables of the solution are printed with\n");
printf("print_duals(lp);\n");
print_duals(lp);
press_ret();
printf("We can change a single element in the matrix with\n");
printf("set_mat(lp,2,1,0.5)\n");
if (!set_mat(lp,2,1,0.5))
ERROR();
print_lp(lp);
press_ret();
printf("If we want to maximize the objective function use set_maxim(lp);\n");
set_maxim(lp);
print_lp(lp);
press_ret();
printf("after solving this gives us:\n");
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
print_duals(lp);
press_ret();
printf("Change the value of a rhs element with set_rh(lp,1,7.45)\n");
set_rh(lp,1,7.45);
print_lp(lp);
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We change %s to the integer type with\n", get_col_name(lp, 4));
printf("set_int(lp, 4, TRUE)\n");
set_int(lp, 4, TRUE);
print_lp(lp);
printf("We set branch & bound debugging on with set_debug(lp, TRUE)\n");
set_debug(lp, TRUE);
printf("and solve...\n");
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We can set bounds on the variables with\n");
printf("set_lowbo(lp,2,2); & set_upbo(lp,4,5.3)\n");
set_lowbo(lp,2,2);
set_upbo(lp,4,5.3);
print_lp(lp);
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Now remove a constraint with del_constraint(lp, 1)\n");
del_constraint(lp,1);
print_lp(lp);
printf("Add an equality constraint\n");
if (!str_add_constraint(lp, "1 2 1 4", EQ, 8))
ERROR();
print_lp(lp);
press_ret();
printf("A column can be added with:\n");
printf("str_add_column(lp,\"3 2 2\");\n");
if (!str_add_column(lp,"3 2 2"))
ERROR();
print_lp(lp);
press_ret();
printf("A column can be removed with:\n");
printf("del_column(lp,3);\n");
del_column(lp,3);
print_lp(lp);
press_ret();
printf("We can use automatic scaling with:\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
print_lp(lp);
press_ret();
printf("The function get_mat(lprec *lp, int row, int column) returns a single\n");
printf("matrix element\n");
printf("%s get_mat(lp,2,3), get_mat(lp,1,1); gives\n","printf(\"%f %f\\n\",");
printf("%f %f\n", (double)get_mat(lp,2,3), (double)get_mat(lp,1,1));
printf("Notice that get_mat returns the value of the original unscaled problem\n");
press_ret();
printf("If there are any integer type variables, then only the rows are scaled\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
printf("set_int(lp,3,FALSE);\n");
set_int(lp,3,FALSE);
print_lp(lp);
press_ret();
solve(lp);
printf("print_objective, print_solution gives the solution to the original problem\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Scaling is turned off with unscale(lp);\n");
unscale(lp);
print_lp(lp);
press_ret();
printf("Now turn B&B debugging off and simplex tracing on with\n");
printf("set_debug(lp, FALSE), set_trace(lp, TRUE) and solve(lp)\n");
set_debug(lp, FALSE);
set_trace(lp, TRUE);
press_ret();
solve(lp);
printf("Where possible, lp_solve will start at the last found basis\n");
printf("We can reset the problem to the initial basis with\n");
printf("default_basis(lp). Now solve it again...\n");
press_ret();
default_basis(lp);
solve(lp);
printf("It is possible to give variables and constraints names\n");
printf("set_row_name(lp,1,\"speed\"); & set_col_name(lp,2,\"money\")\n");
if (!set_row_name(lp,1,"speed"))
ERROR();
if (!set_col_name(lp,2,"money"))
ERROR();
print_lp(lp);
printf("As you can see, all column and rows are assigned default names\n");
printf("If a column or constraint is deleted, the names shift place also:\n");
press_ret();
printf("del_column(lp,1);\n");
del_column(lp,1);
print_lp(lp);
press_ret();
delete_lp(lp);
/*
printf("A lp structure can be created and read from a .lp file\n");
printf("lp = read_LP(\"lp_examples/demo_lag.lp\", TRUE);\n");
printf("The verbose option is used\n");
if ((lp = read_LP("lp_examples/demo_lag.lp", TRUE, "test")) == NULL)
ERROR();
press_ret();
printf("lp is now:\n");
print_lp(lp);
press_ret();
printf("solution:\n");
set_debug(lp, TRUE);
solve(lp);
set_debug(lp, FALSE);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("You can see that branch & bound was used in this problem\n");
printf("Now remove the last constraint and use lagrangian relaxation\n");
printf("del_constraint(lp,6);\n");
printf("str_add_lag_con(lp, \"1 1 1 0 0 0\", LE, 2);\n");
del_constraint(lp,6);
if (!str_add_lag_con(lp, "1 1 1 0 0 0", LE, 2))
ERROR();
print_lp(lp);
*/
/*
printf("Lagrangian relaxation is used in some heuristics. It is now possible\n");
printf("to get a feasible integer solution without usage of branch & bound.\n");
printf("Use lag_solve(lp, 0, 30); 0 is the initial bound, 30 the maximum\n");
printf("number of iterations, the last variable turns the verbose mode on.\n");
press_ret();
set_lag_trace(lp, TRUE);
printf("%d\n",lag_solve(lp, 0, 30));
printf("The returncode of lag_solve is 6 or FEAS_FOUND. this means that a feasible\n");
printf("solution has been found. For a list of other possible return values\n");
printf("see the help file. Print this solution with print_objective, print_solution\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
delete_lp(lp);
*/
press_ret();
return(0);
}
void copy_mat(Mat* in, Mat* out)
{
for (int i = 0; i < in->n; i++)
for (int j = 0; j < in->m; j++)
set_mat(out, i, j, get_mat(in, i, j));
}
