bool LpSolve::solve() {
set_add_rowmode(lp, TRUE);
for (size_t c = 0; c < moduleIndexMap.size(); ++c) {
colno[c] = c + 1;
set_binary(lp, c + 1, TRUE);
}
for (auto &equation : equations) {
memset(row, 0, moduleIndexMap.size() * sizeof(*row));
for (auto const &module : equation->getModules()) {
row[moduleIndexMap.at(module->toString())] = 1;
}
add_constraintex(lp, moduleIndexMap.size(), row, colno, equation->getIsEqualityConstraint() ? EQ : LE, 1);
}
set_add_rowmode(lp, FALSE);
memset(row, 0, moduleIndexMap.size() * sizeof(*row));
set_obj_fnex(lp, moduleIndexMap.size(), row, colno);
if (::solve(lp) != OPTIMAL) {
return false;
}
get_variables(lp, row);
for (size_t j = 0; j < moduleIndexMap.size(); j++)
printf("%s: %f\n", get_col_name(lp, j + 1), row[j]);
return true;
}
ErrorCode ReadNC::read_header()
{
dbgOut.tprint(1, "Reading header...\n");
// Get the global attributes
int numgatts;
int success;
success = NCFUNC(inq_natts )(fileId, &numgatts);
if (success)
MB_SET_ERR(MB_FAILURE, "Couldn't get number of global attributes");
// Read attributes into globalAtts
ErrorCode result = get_attributes(NC_GLOBAL, numgatts, globalAtts);MB_CHK_SET_ERR(result, "Trouble getting global attributes");
dbgOut.tprintf(1, "Read %u attributes\n", (unsigned int) globalAtts.size());
// Read in dimensions into dimNames and dimLens
result = get_dimensions(fileId, dimNames, dimLens);MB_CHK_SET_ERR(result, "Trouble getting dimensions");
dbgOut.tprintf(1, "Read %u dimensions\n", (unsigned int) dimNames.size());
// Read in variables into varInfo
result = get_variables();MB_CHK_SET_ERR(result, "Trouble getting variables");
dbgOut.tprintf(1, "Read %u variables\n", (unsigned int) varInfo.size());
return MB_SUCCESS;
}
/*
* add new watch
*/
variable* add_watch(gchar* expression)
{
gchar command[1000];
variable *var = variable_new(expression, VT_WATCH);
watches = g_list_append(watches, var);
/* try to create a variable */
gchar *record = NULL;
gchar *escaped = g_strescape(expression, NULL);
sprintf(command, "-var-create - * \"%s\"", escaped);
g_free(escaped);
if (RC_DONE != exec_sync_command(command, TRUE, &record))
{
g_free(record);
return var;
}
gchar *pos = strstr(record, "name=\"") + strlen("name=\"");
*strchr(pos, '\"') = '\0';
g_string_assign(var->internal, pos);
var->evaluated = TRUE;
GList *vars = g_list_append(NULL, var);
get_variables(vars);
g_free(record);
g_list_free(vars);
return var;
}
/// Generates the truth table.
void MainWindow::generate()
{
delete_columns();
get_variables();
FunctionParser p;
switch(m_mode)
{
case Function:
char func[128];
Edit_GetText(m_hWndFunction, func, 128);
try {
p = FunctionParser(m_variables, func);
} catch(FunctionParser::FunctionParserException& e) {
MessageBox(e.what(), "Function Parser Error", MB_OK | MB_ICONERROR);
return;
}
build_table(&p);
break;
case Minterm:
break;
case Maxterm:
break;
}
}
void lock_hierarchy::handleError(const char *what, std::size_t lock_level, const void *theLock)
{
variables_t &variables = get_variables();
std::cerr << "locking hierarchy error: " << what << " lock_level=" << lock_level
<< " theLock=" << theLock << std::endl;
std::cerr << "locked levels:\n";
std::size_t lastV = 0, count = 0;
const std::size_t skipAtCount = 3;
for(std::size_t v : variables.lock_levels)
{
if(count == 0 || lastV != v)
{
if(count > skipAtCount)
{
std::cerr << "(" << count - skipAtCount << " not shown)\n";
}
lastV = v;
count = 1;
}
else
{
count++;
}
if(count <= skipAtCount)
std::cerr << v << "\n";
}
if(count > skipAtCount)
{
std::cerr << "(" << count - skipAtCount << " not shown)\n";
}
std::cerr << std::endl;
std::terminate();
}
Solution LpsolveAdaptator::getSolution(lprec * lp) {
Solution sol = Solution();
REAL row[get_Norig_columns(lp)];
#ifdef DEBUG
set_verbose(lp, NORMAL);
write_LP(lp, stdout);
#else
set_verbose(lp, CRITICAL);
#endif
solve(lp);
// WARNING possible conversion failure from double to float
sol.setZ(get_objective(lp));
get_variables(lp, row);
#ifdef DEBUG
for(int j = 0; j < get_Norig_columns(lp); j++) {
printf("%s: %f\n", get_col_name(lp, j + 1), row[j]);
}
#endif
for (int i = 0; i < get_Norig_columns(lp); i++) {
double var_value = (double)row[i];
sol.addVariable(var_value);
}
delete_lp(lp);
return sol;
}
/*
* get list of children
*/
GList* get_children (gchar* path)
{
GList *children = NULL;
gchar command[1000];
result_class rc;
gchar *record = NULL;
gchar *pos = NULL;
/* children number */
sprintf(command, "-var-info-num-children \"%s\"", path);
rc = exec_sync_command(command, TRUE, &record);
if (RC_DONE != rc)
return NULL;
pos = strstr(record, "numchild=\"") + strlen("numchild=\"");
*(strchr(pos, '\"')) = '\0';
int numchild = atoi(pos);
g_free(record);
if (!numchild)
return NULL;
/* recursive get children and put into list */
sprintf(command, "-var-list-children \"%s\"", path);
rc = exec_sync_command(command, TRUE, &record);
if (RC_DONE == rc)
{
pos = record;
while ( (pos = strstr(pos, "child={")) )
{
gchar *name, *internal;
/* name */
pos = strstr(pos, "name=\"") + strlen("name=\"");
*(strstr(pos, "\",exp=\"")) = '\0';
internal = pos;
pos += strlen(pos) + 1;
/* exp */
pos = strstr(pos, "exp=\"") + strlen("exp=\"");
*(strstr(pos, "\",numchild=\"")) = '\0';
name = g_strcompress(pos);
variable *var = variable_new2(name, internal, VT_CHILD);
var->evaluated = TRUE;
pos += strlen(pos) + 1;
children = g_list_prepend(children, var);
g_free(name);
}
}
g_free(record);
get_variables(children);
return children;
}
bool CFeasibilityMap::SolveLP(Matrix &A, ColumnVector &b, ColumnVector &x) {
lprec *lp ;
int n_row = A.nrows(); int n_col = A.ncols();
x = ColumnVector(n_col); x = 0;
lp = make_lp(0,n_col) ;
double *input_row = new double[1+n_col];
for (int i_row=1; i_row<=n_row; i_row++){
input_row[0] = 0 ; // The first zero is for matrix form
for (int j=1; j<=n_col; j++){
input_row[j] = A(i_row,j) ;
}
add_constraint(lp, input_row, LE, b(i_row)) ;
}
delete [] input_row;
double *input_obj = new double[1+n_col]; // The first zero is for matrix form
input_obj[0] = 0 ;
for (int j=1; j<=n_col; j++){
input_obj[j] = 1 ;
}
set_obj_fn(lp, input_obj) ;
delete [] input_obj;
set_verbose(lp, IMPORTANT); // NEUTRAL (0), IMPORTANT (3), NORMAL (4), FULL (6)
bool is_feasible = (solve(lp)==0); // 0: feasible solution found, 2: not found
// solution for minimizing objective function
double* x_min = new double[n_col];
double* x_max = new double[n_col];
if (is_feasible) {
get_variables(lp, x_min);
set_maxim(lp);
is_feasible = (solve(lp)==0); // 0: feasible solution found, 2: not found
if (is_feasible) {
get_variables(lp, x_max);
for (int i = 0; i < n_col; i++) {
x(i+1) = (x_min[i] + x_max[i]) / 2.0;
}
}
}
delete [] x_min;
delete [] x_max;
delete_lp(lp);
return is_feasible;
}
/** \brief Perform backtraking linesearch.
*
*/
double backtracking_linesearch(problem_data_t *pdat, variables_t *vars,
double t, double *Adw, double *xnew)
{
int i, m, n;
double phi, s;
double *vnew, *wnew, *unew;
dmatrix *matX1, *matX2;
double *g, *h, *z, *expz, *expmz, *ac, *ar, *b, *d1, *d2, *Aw;
double *x, *v, *w, *u, *dx, *dv, *dw, *du, *gv, *gw, *gu, *gx;
double lambda, gdx;
get_problem_data(pdat, &matX1, &matX2, &ac, &ar, &b, &lambda);
m = matX1->m;
n = matX1->n;
get_variables(vars, &x, &v, &w, &u, &dx, &dv, &dw, &du, &gx, &gv,
&gw, &gu, &g, &h, &z, &expz, &expmz, &d1, &d2, &Aw);
vnew = xnew;
wnew = xnew+1;
unew = xnew+1+n;
s = 1.0;
phi = eval_phi(m, n, z, expz, expmz, w, u, lambda, t);
dmat_yAmpqx(matX1, ac, ar, dw, Adw); /* see below */
dmat_waxpby(m, dv[0], b, 1, Adw, Adw); /* Adw := A*dw+b*dv */
dmat_waxpby(m, v[0], b, 1, Aw, Aw); /* Aw := A*w+b*v */
dmat_waxpby(n+n+1, 1, dx, 1, x, xnew); /* xnew:= x + dx */
gdx = dmat_dot(n+n+1, gx, dx);
for (i = 1; i <= MAX_LS_ITER; i++)
{
/* x := x + s*dx */
if (is_indomain(wnew, unew, n) == TRUE)
{
double newphi;
/* z = A*(w+s*dw) + b*(v+s*dw)
= (Aw+bv) + s*(Adw+bdv),
where Aw, Adw+bdv are vectors. */
dmat_waxpby(m, s, Adw, 1, Aw, z);
dmat_yexpx(m, z, expz);
dmat_yinvx(m, expz, expmz);
newphi = eval_phi(m, n, z, expz, expmz, wnew, unew, lambda, t);
if (newphi <= phi + ALPHA * s * gdx) break;
}
s *= BETA;
dmat_waxpby(n+n+1, s, dx, 1, x, xnew);
}
if (i > MAX_LS_ITER) return -1;
dmat_vcopy(n+n+1,xnew,x);
return s;
}
int LoadBalancing::lp_solve_model() {
//Returns 0 when an optimal solution is found,
//returns 1 if the solution is suboptimal due to an overlap constraint, and we should use fewer nodes
//returns 2 when a suboptimal solution is found (solver timed out)
//returns 3 if another error occurred
int ret;
int Ncol=3*num_using_nodes_+(num_using_nodes_-1)*(num_quantiles_+2);
REAL *vars = (REAL*)malloc(Ncol*sizeof(REAL));
set_verbose(lp, IMPORTANT);
set_timeout(lp, solver_timeout_);
default_basis(lp);
ret = solve(lp);
if(ret==1){
fprintf(stderr, "lp_solve: Suboptimal solution (solver timed out)\n");
return 2;
}
if(ret!=0 && ret!=1){
fprintf(stderr, "lp_solve: Solution not found\n");
return 3;
}
print_solution(lp, 3);
get_variables(lp, vars);
//Cutvector:
optimal_cutvector_.resize(num_using_nodes_);
for(int i=0;i<num_using_nodes_;i++){
optimal_cutvector_.at(i)=round(width_*vars[i]);
}
//Estimated completion time:
est_completion_time_=(float)vars[num_using_nodes_];
/* printf("\nOptimal cutvector:\n");
for(int i=0;i<num_using_nodes_;i++){
printf("%d\n", optimal_cutvector_.at(i));
}
printf("Estimated completion time: %f\n", est_completion_time_);
*/
//If the first cut is 0, that would be an indication that the cutvector we obtained is suboptimal,
//due to the overlap constraint.
//We should most likely use fewer nodes.
if(optimal_cutvector_.front()==0){
fprintf(stderr, "lp_solve: Suboptimal solution (first cut was 0), we should use fewer processing nodes\n");
return 1;
}
free(vars);
return ret;
}
long __declspec(dllexport) WINAPI _get_variables(lprec *lp, double *variables)
{
long ret;
if (lp != NULL) {
freebuferror();
ret = get_variables(lp, variables);
}
else
ret = 0;
return(ret);
}
static int get_terms_object(SEXP factors, SEXP variables, struct design *s,
struct design *r, struct design2 *d,
struct terms_object *tm)
{
int err = 0;
err = get_variables(variables, s, r, d, &tm->variables);
if (err < 0)
goto out;
err = get_terms(factors, &tm->variables, s, r, d, &tm->terms);
if (err < 0)
goto out;
out:
return err;
}
int truth_table(char ipstr[], int fnvalues[], int *no_of_variables){
int i, j, output, len;
remove_spaces(ipstr);
if(check_for_valid_characters(ipstr)){
printf("ERROR! Use only valid characters - ~&|() a-z A-Z\n");
return 1;
}
set_precedence(precedence, ipstr);
get_variables(listvar, &numvar, precedence);
if(conv_to_postfix(ipstr, opstr, precedence) == 1){
printf("\nError in input\n");
return 1;
}
len = strlen(ipstr);
/* Truth-table Printing */
printf("\n");
for(i=0; i<numvar; i++){
printf("%c ", listvar[i]);
}
printf("%s ", ipstr);
for(i=0; i<(1<<numvar); i++){
/* For each permutation of bits */
printf("\n");
compute_val_var_from_perm(i, valvar, numvar);
for(j=0; j<numvar; j++)
printf("%d ", valvar[j]);
output = eval_postfix(opstr, valvar, numvar, listvar);
if(output == 1){
printf("Error : eval - not enuff operands\n");
return 1;
}
fnvalues[i] = output - '0';
printf("%*c ", len/2 + 1, output);
}
*no_of_variables = numvar;
printf("\n");
return 0;
}
void testVarParser(char *buf)
{
printf("===== Testing Variable parser ======\n");
// time_t start = GetTickCount();
VariableList li;
// fflush(stdout);
std::map<std::string, std::string> ignoreTokens;
get_variables(buf, li, ignoreTokens, true);
// time_t end = GetTickCount();
for (VariableList::iterator iter = li.begin(); iter != li.end(); iter++) {
Variable var = *iter;
var.Print();
}
// printf("total time: %d\n", end-start);
printf("matches found: %d\n", li.size());
}
struct svalue *
debug_command(char *debcmd, int argc, struct svalue *argv)
{
static struct svalue retval;
int dbnum, dbi, il;
char buff[200];
for (dbi = -1, dbnum = 0; debc[dbnum]; dbnum++)
{
if (strcmp(debcmd, debc[dbnum]) == 0)
dbi = dbnum;
}
if (dbi < 0)
{
retval.type = T_NUMBER;
retval.u.number = 0;
return &retval;
}
switch (dbi)
{
case 0: /* index */
retval.type = T_POINTER;
retval.u.vec = allocate_array(dbnum);
for (il = 0; il < dbnum; il++)
{
retval.u.vec->item[il].type = T_STRING;
retval.u.vec->item[il].string_type = STRING_CSTRING;
retval.u.vec->item[il].u.string = debc[il];
}
return &retval;
case 1: /* malloc */
retval.type = T_STRING;
retval.string_type = STRING_MSTRING;
retval.u.string = make_mstring((char *)dump_malloc_data());
return &retval;
case 2: /* status */
case 3: /* status tables */
retval.type = T_STRING;
retval.string_type = STRING_MSTRING;
retval.u.string = (char *)get_gamedriver_info(debc[dbi]);
return &retval;
case 4: /* mudstatus on/off eval_lim time_lim */
if (argc < 3 ||
argv[0].type != T_STRING ||
argv[1].type != T_NUMBER ||
argv[2].type != T_NUMBER)
break;
if (strcmp(argv[0].u.string, "on") == 0)
mudstatus_set(1, argv[1].u.number, argv[2].u.number);
else if (strcmp(argv[0].u.string, "off") == 0)
mudstatus_set(0, argv[1].u.number, argv[2].u.number);
else
break;
retval.type = T_NUMBER;
retval.u.number = 1;
return &retval;
case 5: /* functionlist object */
if (argc < 1 || argv[0].type != T_OBJECT)
break;
retval.type = T_POINTER;
retval.u.vec = allocate_array(argv[0].u.ob->prog->num_functions);
for (il = 0; il < (int)argv[0].u.ob->prog->num_functions; il++)
{
retval.u.vec->item[il].type = T_STRING;
retval.u.vec->item[il].string_type = STRING_SSTRING;
retval.u.vec->item[il].u.string =
reference_sstring(argv[0].u.ob->prog->functions[il].name);
}
return &retval;
case 6: /* rusage */
{
#ifdef RUSAGE /* Only defined if we compile GD with RUSAGE */
char buff[500];
struct rusage rus;
long utime, stime;
long maxrss;
if (getrusage(RUSAGE_SELF, &rus) < 0)
buff[0] = 0;
else {
utime = rus.ru_utime.tv_sec * 1000 + rus.ru_utime.tv_usec / 1000;
stime = rus.ru_stime.tv_sec * 1000 + rus.ru_stime.tv_usec / 1000;
maxrss = rus.ru_maxrss;
(void)sprintf(buff, "%ld %ld %ld %ld %ld %ld %ld %ld %ld %ld %ld %ld %ld %ld %ld %ld",
utime, stime, maxrss, rus.ru_ixrss, rus.ru_idrss,
rus.ru_isrss, rus.ru_minflt, rus.ru_majflt, rus.ru_nswap,
rus.ru_inblock, rus.ru_oublock, rus.ru_msgsnd,
rus.ru_msgrcv, rus.ru_nsignals, rus.ru_nvcsw,
rus.ru_nivcsw);
}
retval.type = T_STRING;
retval.string_type = STRING_MSTRING;
retval.u.string = make_mstring(buff);
return &retval;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with RUSAGE flag.\n";
return &retval;
#endif
}
#if defined(PROFILE_LPC)
case 7: /* top_ten_cpu */
{
#define NUMBER_OF_TOP_TEN 100
struct program *p[NUMBER_OF_TOP_TEN];
struct vector *v;
struct program *prog;
int i, j;
for(i = 0; i < NUMBER_OF_TOP_TEN; i++)
p[i] = (struct program *)0L;
prog = prog_list;
do
{
for(i = NUMBER_OF_TOP_TEN-1; i >= 0; i--)
{
if ( p[i] && (prog->cpu <= p[i]->cpu))
break;
}
if (i < (NUMBER_OF_TOP_TEN - 1))
for (j = 0; j <= i; j++)
if (strcmp(p[j]->name,prog->name) == 0)
{
i = NUMBER_OF_TOP_TEN-1;
break;
}
if (i < (NUMBER_OF_TOP_TEN - 1))
{
j = NUMBER_OF_TOP_TEN - 2;
while(j > i)
{
p[j + 1] = p[j];
j--;
}
p[i + 1] = prog;
}
} while (prog_list != (prog = prog->next_all));
v = make_cpu_array(NUMBER_OF_TOP_TEN, p);
if (v)
{
retval.type = T_POINTER;
retval.u.vec = v;
return &retval;
}
break;
#undef NUMBER_OF_TOP_TEN
}
#else
case 7:
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC flag.\n";
return &retval;
#endif
case 8: /* object_cpu object */
{
long long c_num;
if (argc && (argv[0].type == T_OBJECT))
{
#if defined(PROFILE_LPC)
c_num = argv[0].u.ob->prog->cpu * 1e6;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC flag.\n";
return &retval;
#endif
}
else
{
#ifdef RUSAGE
struct rusage rus;
if (getrusage(RUSAGE_SELF, &rus) < 0)
{
c_num = -1;
}
else
{
c_num = (long long)rus.ru_utime.tv_sec * 1000000 +
rus.ru_utime.tv_usec +
(long long)rus.ru_stime.tv_sec * 1000000 +
rus.ru_stime.tv_usec;
}
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with RUSAGE flag.\n";
return &retval;
#endif
}
retval.type = T_NUMBER;
retval.u.number = c_num;
return &retval;
}
case 9: /* swap, object */
#if 0 /* can not swap while executing */
if (argc && (argv[0].type == T_OBJECT))
(void)swap(argv[0].u.ob);
#endif
retval = const1;
return &retval;
case 10: /* version, */
{
char buff[64];
(void)snprintf(buff, sizeof(buff), "%6.6s%02d %s %s", GAME_VERSION, PATCH_LEVEL, __DATE__, __TIME__);
retval.type = T_STRING;
retval.string_type = STRING_MSTRING;
retval.u.string = make_mstring(buff);
return &retval;
}
case 11: /* wizlist, wizname */
/*
* Prints information, will be changed
*/
retval = const1;
return &retval;
case 12: /* trace, bitmask */
{
int ot = -1;
extern struct object *current_interactive;
if (current_interactive && current_interactive->interactive)
{
if (argc && (argv[0].type == T_NUMBER))
{
ot = current_interactive->interactive->trace_level;
current_interactive->interactive->trace_level = argv[0].u.number;
}
}
retval.type = T_NUMBER;
retval.u.number = ot;
return &retval;
}
case 13: /* traceprefix, pathstart */
{
char *old = 0;
extern struct object *current_interactive;
if (current_interactive && current_interactive->interactive)
{
if (argc)
{
old = current_interactive->interactive->trace_prefix;
if (argv[0].type == T_STRING)
{
current_interactive->interactive->trace_prefix =
make_sstring(argv[0].u.string);
}
else
current_interactive->interactive->trace_prefix = 0;
}
}
if (old)
{
retval.type = T_STRING;
retval.string_type = STRING_SSTRING;
retval.u.string = old;
}
else
retval = const0;
return &retval;
}
case 14: /* call_out_info, */
{
extern struct vector *get_calls(struct object *);
if (argv[0].type != T_OBJECT)
break;
retval.type = T_POINTER;
retval.u.vec = get_calls(argv[0].u.ob);
return &retval;
}
case 15: /* inherit_list, object */
if (argc && (argv[0].type == T_OBJECT))
{
retval.type = T_POINTER;
retval.u.vec = inherit_list(argv[0].u.ob);
return &retval;
}
else
{
retval = const0;
return &retval;
}
case 16: /* load_average, */
retval.type = T_STRING;
retval.string_type = STRING_MSTRING;
retval.u.string = make_mstring(query_load_av());
return &retval;
case 17: /* shutdown, */
startshutdowngame(0);
retval = const1;
return &retval;
case 18: /* "object_info", num object */
{
struct object *ob;
char db_buff[1024], tdb[200];
int i;
if (argc < 2 || argv[0].type != T_NUMBER || argv[1].type != T_OBJECT)
break;
if (argv[0].u.number == 0)
{
int flags;
struct object *obj2;
if ( argv[1].type != T_OBJECT)
break;
ob = argv[1].u.ob;
flags = ob->flags;
(void)sprintf(db_buff,"O_ENABLE_COMMANDS : %s\nO_CLONE : %s\nO_DESTRUCTED : %s\nO_SWAPPED : %s\nO_ONCE_INTERACTIVE: %s\nO_CREATED : %s\n",
flags&O_ENABLE_COMMANDS ?"TRUE":"FALSE",
flags&O_CLONE ?"TRUE":"FALSE",
flags&O_DESTRUCTED ?"TRUE":"FALSE",
flags&O_SWAPPED ?"TRUE":"FALSE",
flags&O_ONCE_INTERACTIVE?"TRUE":"FALSE",
flags&O_CREATED ?"TRUE":"FALSE");
(void)sprintf(tdb,"time_of_ref : %d\n", ob->time_of_ref);
(void)strcat(db_buff, tdb);
(void)sprintf(tdb,"ref : %d\n", ob->ref);
(void)strcat(db_buff, tdb);
#ifdef DEBUG
(void)sprintf(tdb,"extra_ref : %d\n", ob->extra_ref);
(void)strcat(db_buff, tdb);
#endif
(void)sprintf(tdb,"swap_num : %d\n", ob->swap_num);
(void)strcat(db_buff, tdb);
(void)snprintf(tdb, sizeof(tdb), "name : '%s'\n", ob->name);
(void)strcat(db_buff, tdb);
(void)snprintf(tdb, sizeof(tdb), "next_all : OBJ(%s)\n",
ob->next_all?ob->next_all->name: "NULL");
(void)strcat(db_buff, tdb);
if (obj_list == ob)
{
(void)strcat(db_buff, "This object is the head of the object list.\n");
}
obj2 = obj_list;
i = 1;
do
if (obj2->next_all == ob)
{
(void)snprintf(tdb, sizeof(tdb), "Previous object in object list: OBJ(%s)\n",
obj2->name);
(void)strcat(db_buff, tdb);
(void)sprintf(tdb, "position in object list:%d\n",i);
(void)strcat(db_buff, tdb);
}
while (obj_list != (obj2 = obj2->next_all));
}
else if (argv[0].u.number == 1)
{
if (argv[1].type != T_OBJECT)
break;
ob = argv[1].u.ob;
(void)sprintf(db_buff,"program ref's %d\n", ob->prog->ref);
(void)snprintf(tdb, sizeof(tdb), "Name %s\n", ob->prog->name);
(void)strcat(db_buff, tdb);
(void)sprintf(tdb,"program size %d\n", ob->prog->program_size);
(void)strcat(db_buff, tdb);
(void)sprintf(tdb, "num func's %u (%u) \n", ob->prog->num_functions
,ob->prog->num_functions * (unsigned) sizeof(struct function));
(void)strcat(db_buff, tdb);
(void)sprintf(tdb,"sizeof rodata %d\n", ob->prog->rodata_size);
(void)strcat(db_buff, tdb);
(void)sprintf(tdb,"num vars %u (%u)\n", ob->prog->num_variables
,ob->prog->num_variables * (unsigned) sizeof(struct variable));
(void)strcat(db_buff, tdb);
(void)sprintf(tdb,"num inherits %u (%u)\n", ob->prog->num_inherited
,ob->prog->num_inherited * (unsigned) sizeof(struct inherit));
(void)strcat(db_buff, tdb);
(void)sprintf(tdb,"total size %d\n", ob->prog->total_size);
(void)strcat(db_buff, tdb);
}
else
{
(void)sprintf(db_buff, "Bad number argument to object_info: %lld\n",
argv[0].u.number);
}
retval.type = T_STRING;
retval.string_type = STRING_MSTRING;
retval.u.string = make_mstring(db_buff);
return &retval;
}
case 19: /* opcdump, 19 */
{
#ifdef OPCPROF
opcdump();
retval = const1;
return &retval;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with OPCPROF flag.\n";
return &retval;
#endif
}
case 20: /* send_udp, 20 host, port, msg */
{
#ifdef CATCH_UDP_PORT
extern udpsvc_t *udpsvc;
#endif
if (argc < 3 ||
argv[0].type != T_STRING ||
argv[1].type != T_NUMBER ||
argv[2].type != T_STRING)
break;
#ifdef CATCH_UDP_PORT
tmp = udpsvc_send(udpsvc, argv[0].u.string, argv[1].u.number, argv[2].u.string);
if (tmp)
retval = const1;
else
#endif
retval = const0;
return &retval;
}
case 21: /* mud_port, 21 */
{
extern int port_number;
retval.type = T_NUMBER;
retval.u.number = port_number;
return &retval;
}
case 22: /* udp_port, 22 */
{
#ifdef CATCH_UDP_PORT
extern int udp_port;
retval.u.number = udp_port;
#else
retval.u.number = -1;
#endif
retval.type = T_NUMBER;
return &retval;
}
case 23: /* set_wizard, object */
if (argc && (argv[0].type == T_OBJECT))
{
retval = const1;
return &retval;
}
else
{
retval = const0;
return &retval;
}
case 24: /* ob_flags, 24 ob */
{
if (argc && (argv[0].type == T_OBJECT))
{
retval.type = T_NUMBER;
retval.u.number = argv[0].u.ob->flags;
return &retval;
}
retval = const0;
return &retval;
}
case 25: /* get_variables, 25 object NULL/string */
{
struct svalue get_variables(struct object *);
struct svalue get_variable(struct object *, char *);
switch (argc)
{
case 1:
if ( argv[0].type != T_OBJECT)
{
retval = const0;
return &retval;
}
retval = get_variables(argv[0].u.ob);
return &retval;
case 2:
if ( argv[0].type != T_OBJECT || argv[1].type != T_STRING)
{
retval = const0;
return &retval;
}
retval = get_variable(argv[0].u.ob, argv[1].u.string);
return &retval;
case 3:
if ( argv[0].type == T_OBJECT && argv[1].type == T_STRING)
{
retval = get_variable(argv[0].u.ob, argv[1].u.string);
return &retval;
}
if ( argv[0].type == T_OBJECT)
{
retval = get_variables(argv[0].u.ob);
return &retval;
}
retval = const0;
return &retval;
default:
retval = const0;
return &retval;
}
}
case 26: /* get_eval_cost, 26 */
{
extern int eval_cost;
retval.type = T_NUMBER;
retval.u.number = eval_cost;
return &retval;
}
case 27: /* debug malloc, 27 */
{
retval = const1;
return &retval;
}
case 28: /* getprofile, 28 object */
{
int format = 0;
#ifndef PROFILE_LPC
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC flag.\n";
return &retval;
#else
if (argc < 1 || argv[0].type != T_OBJECT)
break;
if (argc >= 2 && argv[1].type == T_NUMBER)
format = argv[1].u.number;
if (format == 0) {
retval.type = T_POINTER;
retval.u.vec = allocate_array(argv[0].u.ob->prog->num_functions);
for (il = 0; il < (int)argv[0].u.ob->prog->num_functions; il++)
{
(void)snprintf(buff, sizeof(buff), "%016lld:%020lld: %s",
(long long)argv[0].u.ob->prog->functions[il].num_calls,
(long long)(argv[0].u.ob->prog->functions[il].time_spent * 1e6),
argv[0].u.ob->prog->functions[il].name);
retval.u.vec->item[il].type = T_STRING;
retval.u.vec->item[il].string_type = STRING_MSTRING;
retval.u.vec->item[il].u.string = make_mstring(buff);
}
} else if (format == 1) {
retval.type = T_POINTER;
retval.u.vec = allocate_array(argv[0].u.ob->prog->num_functions);
double now = current_cpu();
struct program *prog = argv[0].u.ob->prog;
for (il = 0; il < (int)prog->num_functions; il++)
{
struct function *func = prog->functions + il;
struct vector *res = allocate_array(7);
update_func_profile(func, now, 0.0, 0.0, 0);
res->item[0].type = T_STRING;
res->item[0].string_type = STRING_MSTRING;
res->item[0].u.string = make_mstring(func->name);
res->item[1].type = T_FLOAT;
res->item[1].u.real = func->time_spent * 1e6;
res->item[2].type = T_FLOAT;
res->item[2].u.real = func->tot_time_spent * 1e6;
res->item[3].type = T_FLOAT;
res->item[3].u.real = func->num_calls;
res->item[4].type = T_FLOAT;
res->item[4].u.real = func->avg_time * 1e6;
res->item[5].type = T_FLOAT;
res->item[5].u.real = func->avg_tot_time * 1e6;
res->item[6].type = T_FLOAT;
res->item[6].u.real = func->avg_calls;
retval.u.vec->item[il].type = T_POINTER;
retval.u.vec->item[il].u.vec = res;
}
} else {
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Unknown format.\n";
}
return &retval;
#endif
}
case 29: /* get_avg_response, 29 */
{
extern int get_msecs_response(int);
extern int msr_point;
int sum, num, tmp;
if (msr_point >=0)
{
sum = 0;
num = 0;
for (il = 0; il < 100; il++)
{
if ((tmp = get_msecs_response(il)) >=0)
{
sum += tmp;
num++;
}
}
retval.type = T_NUMBER;
retval.u.number = (num > 0) ? sum / num : 0;
return &retval;
}
break;
}
case 30: /* destruct, 30 */
case 31: /* destroy, 31 */
{
extern void destruct_object(struct object *);
if (argc && argv[0].type == T_OBJECT &&
!(argv[0].u.ob->flags & O_DESTRUCTED))
destruct_object(argv[0].u.ob);
break;
}
case 32: /* update snoops, 31 */
#ifdef SUPER_SNOOP
update_snoop_file();
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with SUPER_SNOOP flag.\n";
#endif
break;
case 33: /* call_warnings, int 0 = off, 1 = on */
if (argc && (argv[0].type == T_STRING))
{
if (strcmp(argv[0].u.string, "on") == 0)
call_warnings++;
else
call_warnings = call_warnings > 0 ? call_warnings - 1 : 0;
retval.type = T_NUMBER;
retval.u.number = call_warnings;
return &retval;
}
else
{
retval.type = T_NUMBER;
retval.u.number = -1;
return &retval;
}
case 34: /* dump objects */
{
FILE *ufile;
struct object *ob;
if ((ufile = fopen(OBJECT_DUMP_FILE, "w")) == NULL)
{
retval.type = T_NUMBER;
retval.u.number = -1;
return &retval;
}
fputs("Array (size), Mapping (size), String (size), Objs, Ints, Floats, Inventory, Callouts, Environment, Name\n", ufile);
ob = obj_list;
do
{
mem_variables(ufile, ob);
}
while (obj_list != (ob = ob->next_all));
(void)fclose(ufile);
break;
}
case 35: /* query_debug_ob */
if (!argc || argv[0].type != T_OBJECT)
break;
retval.type = T_NUMBER;
retval.u.number = argv[0].u.ob->debug_flags;
return &retval;
case 36: /* set_debug_ob */
if (!argc || argv[0].type != T_OBJECT || argv[1].type != T_NUMBER)
break;
retval.type = T_NUMBER;
retval.u.number = argv[0].u.ob->debug_flags;
argv[0].u.ob->debug_flags = argv[1].u.number;
return &retval;
case 37: /* set_swap */
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Obsolete function.\n";
return &retval;
case 38: /* query_swap */
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Obsolete function.\n";
return &retval;
case 39: /* query_debug_prog */
if (!argc || argv[0].type != T_OBJECT)
break;
retval.type = T_NUMBER;
retval.u.number = argv[0].u.ob->prog->debug_flags;
return &retval;
case 40: /* set_debug_prog */
if (argc < 2 || argv[0].type != T_OBJECT || argv[1].type != T_NUMBER)
break;
retval.type = T_NUMBER;
retval.u.number = argv[0].u.ob->prog->debug_flags;
argv[0].u.ob->prog->debug_flags = argv[1].u.number;
return &retval;
#ifdef FUNCDEBUG
case 41:
dumpfuncs();
retval = const0;
return &retval;
#endif
case 42: /* inhibitcallouts */
if (argc && (argv[0].type == T_STRING))
{
extern int inhibitcallouts;
int old;
old = inhibitcallouts;
if (strcmp(argv[0].u.string, "on") == 0)
inhibitcallouts = 1;
else
inhibitcallouts = 0;
retval.type = T_NUMBER;
retval.u.number = old;
return &retval;
}
else
{
retval.type = T_NUMBER;
retval.u.number = -1;
return &retval;
}
case 43: /* inhibitcallouts */
if (argc && (argv[0].type == T_STRING))
{
extern int warnobsoleteflag;
int old;
old = warnobsoleteflag;
if (strcmp(argv[0].u.string, "on") == 0)
warnobsoleteflag = 1;
else
warnobsoleteflag = 0;
retval.type = T_NUMBER;
retval.u.number = old;
return &retval;
}
else
{
retval.type = T_NUMBER;
retval.u.number = -1;
return &retval;
}
case 44: /* shared_strings */
#ifdef DEBUG
dump_sstrings();
retval = const0;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with DEBUG flag.\n";
#endif
return &retval;
case 45: /* dump_alarms */
{
int c;
FILE *ufile;
if ((ufile = fopen(ALARM_DUMP_FILE, "w")) == NULL)
{
retval.type = T_NUMBER;
retval.u.number = -1;
return &retval;
}
c = dump_callouts(ufile);
fclose(ufile);
retval.type = T_NUMBER;
retval.u.number = c;
return &retval;
}
#ifdef PROFILE_LPC
case 46: /* top_ten_cpu */
{
#define NUMBER_OF_TOP_TEN 100
struct program *p[NUMBER_OF_TOP_TEN];
struct program *prog;
struct vector *v;
int i, j;
double now = current_cpu();
for(i = 0; i < NUMBER_OF_TOP_TEN; i++)
p[i] = (struct program *)0L;
prog = prog_list;
do
{
update_prog_profile(prog, now, 0.0, 0.0);
for(i = NUMBER_OF_TOP_TEN-1; i >= 0; i--)
{
if ( p[i] && (prog->cpu_avg <= p[i]->cpu_avg))
break;
}
if (i < (NUMBER_OF_TOP_TEN - 1))
for (j = 0; j <= i; j++)
if (strcmp(p[j]->name,prog->name) == 0)
{
i = NUMBER_OF_TOP_TEN-1;
break;
}
if (i < (NUMBER_OF_TOP_TEN - 1))
{
j = NUMBER_OF_TOP_TEN - 2;
while(j > i)
{
p[j + 1] = p[j];
j--;
}
p[i + 1] = prog;
}
} while (prog_list != (prog = prog->next_all));
v = make_cpu_array2(NUMBER_OF_TOP_TEN, p);
if (v)
{
retval.type = T_POINTER;
retval.u.vec = v;
return &retval;
}
break;
#undef NUMBER_OF_TOP_TEN
}
#else
case 46:
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC flag.\n";
return &retval;
#endif
case 47: /* object_cpu_avg object */
{
#if defined(PROFILE_LPC)
if (argc < 1 || (argv[0].type != T_OBJECT))
break;
update_prog_profile(argv[0].u.ob->prog, current_cpu(), 0.0, 0.0);
retval.type = T_FLOAT;
retval.u.number =argv[0].u.ob->prog->cpu_avg * 1e6;
return &retval;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC flag.\n";
return &retval;
#endif
}
case 48: /* getprofile_avg, 28 object */
{
#if defined(PROFILE_LPC)
if (argc < 1 || argv[0].type != T_OBJECT)
break;
retval.type = T_POINTER;
retval.u.vec = allocate_array(argv[0].u.ob->prog->num_functions);
double now = current_cpu();
struct program *prog = argv[0].u.ob->prog;
for (il = 0; il < (int)prog->num_functions; il++)
{
struct function *func = prog->functions + il;
struct vector *res = allocate_array(3);
update_func_profile(func, now, 0.0, 0.0, 0);
res->item[0].type = T_STRING;
res->item[0].string_type = STRING_MSTRING;
res->item[0].u.string = make_mstring(func->name);
res->item[1].type = T_FLOAT;
res->item[1].u.real = func->avg_time * 1e6;
res->item[2].type = T_FLOAT;
res->item[2].u.real = func->avg_calls;
retval.u.vec->item[il].type = T_POINTER;
retval.u.vec->item[il].u.vec = res;
}
return &retval;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC flag.\n";
return &retval;
#endif
}
case 49: /* profile_timebase */
{
#if defined(PROFILE_LPC)
if (argc < 1) { /* Return current value */
retval.type = T_FLOAT;
retval.u.real = get_profile_timebase();
return &retval;
}
/* Update using old timebase */
double now = current_cpu();
struct program *prog = prog_list;
do
{
update_prog_profile(prog, now, 0.0, 0.0);
for (int i = 0; i < prog->num_functions; i++)
{
struct function *func = prog->functions + i;
update_func_profile(func, now, 0.0, 0.0, 0);
}
} while (prog_list != (prog = prog->next_all));
/* Set the new value */
if (argv[0].type == T_NUMBER && argv[0].u.number > 0)
set_profile_timebase(argv[0].u.number);
else if (argv[0].type == T_FLOAT && argv[0].u.real > 1e-3)
set_profile_timebase(argv[0].u.real);
else
break;
retval = const1;
return &retval;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC flag.\n";
return &retval;
#endif
}
case 50:
{
#ifdef PROFILE_LPC
extern int trace_calls;
extern FILE *trace_calls_file;
if (argc < 1 || argv[0].type != T_NUMBER)
break;
if (!trace_calls && argv[0].u.number) {
if ((trace_calls_file = fopen(TRACE_CALLS_FILE, "w")) == 0)
break;
setvbuf(trace_calls_file, 0, _IOFBF, 1<<20); /* Set a 1MB buffer */
trace_calls = 1;
} else if (trace_calls && !argv[0].u.number) {
fclose(trace_calls_file);
trace_calls_file = 0;
trace_calls = 0;
}
retval = const1;
return &retval;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC.\n";
return &retval;
#endif
}
case 51:
{
#if defined(PROFILE_LPC)
long long num_top, criteria, num_items = 0;
double now = current_cpu(), crit_val;
struct program *prog;
struct {
struct program *prog;
double crit_val;
unsigned short func_index;
} *result;
if (argc < 2 ||
argv[0].type != T_NUMBER ||
argv[1].type != T_NUMBER)
break;
num_top = argv[0].u.number;
criteria = argv[1].u.number;
if (num_top < 0 || num_top > 1000) {
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "The number of itmes must be >= 0 and <= 1000.";
break;
}
if (criteria < 0 || criteria > 9) {
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "The criteria must be >= 0 and <= 9.";
break;
}
if (num_top == 0) {
retval.type = T_POINTER;
retval.u.vec = allocate_array(0);
return &retval;
}
result = xalloc(sizeof(*result) * (num_top + 1));
memset(result, 0, sizeof(*result) * (num_top + 1));
prog = prog_list;
do
{
update_prog_profile(prog, now, 0.0, 0.0);
for (int i = 0; i < prog->num_functions; i++)
{
struct function *func = prog->functions + i;
update_func_profile(func, now, 0.0, 0.0, 0);
crit_val = get_top_func_criteria(func, criteria);
if (num_items == num_top &&
result[num_items - 1].crit_val >= crit_val)
continue;
if (num_items == 0 || (num_items < num_top &&
result[num_items - 1].crit_val >= crit_val)) {
result[num_items].prog = prog;
result[num_items].func_index = i;
result[num_items].crit_val = crit_val;
num_items++;
} else {
int insert = num_items;
while (insert > 0 &&
result[insert - 1].crit_val < crit_val)
insert--;
memmove(&result[insert + 1], &result[insert],
sizeof(*result) * (num_items - insert));
result[insert].prog = prog;
result[insert].func_index = i;
result[insert].crit_val = crit_val;
if (num_items < num_top)
num_items++;
}
}
} while ((prog = prog->next_all) != prog_list);
retval.type = T_POINTER;
retval.u.vec = allocate_array(num_items);
for (int i = 0; i < num_items; i++) {
struct vector *val = allocate_array(9);
prog = result[i].prog;
struct function *func = &prog->functions[result[i].func_index];
crit_val = result[i].crit_val;
val->item[0].type = T_STRING;
val->item[0].string_type = STRING_MSTRING;
val->item[0].u.string = make_mstring(prog->name);
val->item[1].type = T_STRING;
val->item[1].string_type = STRING_SSTRING;
val->item[1].u.string = func->name;
reference_sstring(func->name);
val->item[2].type = T_FLOAT;
val->item[2].u.real = crit_val;
val->item[3].type = T_FLOAT;
val->item[3].u.real = func->time_spent;
val->item[4].type = T_FLOAT;
val->item[4].u.real = func->avg_time;
val->item[5].type = T_FLOAT;
val->item[5].u.real = func->tot_time_spent;
val->item[6].type = T_FLOAT;
val->item[6].u.real = func->avg_tot_time;
val->item[7].type = T_FLOAT;
val->item[7].u.real = func->num_calls;
val->item[8].type = T_FLOAT;
val->item[8].u.real = func->avg_calls;
retval.u.vec->item[i].type = T_POINTER;
retval.u.vec->item[i].u.vec = val;
}
free(result);
return &retval;
#else
retval.type = T_STRING;
retval.string_type = STRING_CSTRING;
retval.u.string = "Only valid if GD compiled with PROFILE_LPC.\n";
return &retval;
#endif
}
}
retval = const0;
return &retval;
}
int StateConstraints::fireVectorSize(const PetriNet& net,
const MarkVal* m0,
const VarVal*) const{
assert(nPlaces == net.numberOfPlaces());
assert(nVars == net.numberOfVariables());
// Create linary problem
lprec* lp;
lp = make_lp(0, net.numberOfTransitions()); // One variable for each entry in the firing vector
assert(lp);
if(!lp) return false;
// Set verbosity
set_verbose(lp, IMPORTANT);
// Set transition names (not strictly needed)
for(size_t i = 0; i < net.numberOfTransitions(); i++)
set_col_name(lp, i+1, const_cast<char*>(net.transitionNames()[i].c_str()));
// Start adding rows
set_add_rowmode(lp, TRUE);
REAL row[net.numberOfTransitions() + 1];
for(size_t p = 0; p < nPlaces; p++){
// Set row zero
memset(row, 0, sizeof(REAL) * net.numberOfTransitions() + 1);
for(size_t t = 0; t < net.numberOfTransitions(); t++){
int d = net.outArc(t, p) - net.inArc(p, t);
row[1+t] = d;
}
if(pcs[p].min == pcs[p].max &&
pcs[p].max != CONSTRAINT_INFTY){
double target = pcs[p].min - m0[p];
add_constraint(lp, row, EQ, target);
}else{
// There's always a min, even zero is interesting
double target = pcs[p].min - m0[p];
add_constraint(lp, row, GE, target);
if(pcs[p].max != CONSTRAINT_INFTY){
double target = pcs[p].max - m0[p];
add_constraint(lp, row, LE, target);
}
}
}
// Finished adding rows
set_add_rowmode(lp, FALSE);
// Create objective
memset(row, 0, sizeof(REAL) * net.numberOfTransitions() + 1);
for(size_t t = 0; t < net.numberOfTransitions(); t++)
row[1+t] = 1; // The sum the components in the firing vector
// Set objective
set_obj_fn(lp, row);
// Minimize the objective
set_minim(lp);
// Set variables as integer variables
for(size_t i = 0; i < net.numberOfTransitions(); i++)
set_int(lp, 1+i, TRUE);
// Attempt to solve the problem
int result = solve(lp);
// Limit on traps to test
size_t traplimit = nPlaces * OVER_APPROX_TRAP_FACTOR;
// Try to add a minimal trap constraint
while((result == OPTIMAL) && traplimit-- < 0){
memset(row, 0, sizeof(REAL) * net.numberOfTransitions() + 1);
// Get the firing vector
get_variables(lp, row);
// Compute the resulting marking
MarkVal rMark[net.numberOfPlaces()];
for(size_t p = 0; p < nPlaces; p++){
rMark[p] = m0[p];
for(size_t t = 0; t < net.numberOfTransitions(); t++)
rMark[p] += (net.outArc(t, p) - net.inArc(p, t)) * (int)row[t];
}
// Find an M-trap
BitField trap(minimalTrap(net, m0, rMark));
//Break if there's no trap
if(trap.none()) break;
// Compute the new equation
for(size_t t = 0; t < net.numberOfTransitions(); t++){
row[1+t] = 0;
for(size_t p = 0; p < nPlaces; p++)
if(trap.test(p))
row[1+t] += net.outArc(t, p) - net.inArc(p, t);
}
// Add a new row with target as greater than equal to 1
set_add_rowmode(lp, TRUE);
add_constraint(lp, row, GE, 1);
set_add_rowmode(lp, FALSE);
// Attempt to solve the again
result = solve(lp);
}
int retval = 0;
if(result != INFEASIBLE){
get_variables(lp, row);
for(size_t t = 0; t < net.numberOfTransitions(); t++)
retval += (int)row[t];
}
// Delete the linear problem
delete_lp(lp);
lp = NULL;
// Return true, if it was infeasible
return retval;
}
/** \brief Compute search direction using cholesky method (m > n).
*
*/
void compute_searchdir_chol_thin(problem_data_t *pdat, variables_t *vars,
double t, dmatrix *B, dmatrix *BB,
double *tm1, double *bDA, double *d3)
{
int i, m, n;
double bDb, bDbinv;
dmatrix *matX1, *matX2;
double lambda, tinv;
double *g, *h, *z, *expz, *expmz, *ac, *ar, *b, *d1, *d2, *Aw;
double *x, *v, *w, *u, *dx, *dv, *dw, *du, *gv, *gw, *gu, *gx;
get_problem_data(pdat, &matX1, &matX2, &ac, &ar, &b, &lambda);
get_variables(vars, &x, &v, &w, &u, &dx, &dv, &dw, &du, &gx, &gv,
&gw, &gu, &g, &h, &z, &expz, &expmz, &d1, &d2, &Aw);
m = matX1->m;
n = matX1->n;
tinv = 1.0 / t;
/* bDb, Db */
bDb = 0.0;
for (i = 0; i < m; i++)
{
tm1[i] = h[i] * b[i]; /* tm1 = Db */
bDb += b[i] * tm1[i];
}
bDbinv = 1.0 / bDb;
/* bDA */
dmat_yATx(matX1, tm1, bDA);
dmat_copy(matX1, B); /* B = A */
dmat_ysqrtx(m, h, tm1); /* tm1 = D^{1/2} */
/* B = D^{1/2}*B */
dmat_diagscale(B, tm1, FALSE, NULL, FALSE);
/* BB = A^T*D*A */
dmat_B_ATA(B, BB); /* BB = B^T*B */
for (i = 0; i < n; i++)
{
double q1, q2, q3, ui, wi, gr2;
ui = u[i];
wi = w[i];
q1 = 1.0 / (ui + wi);
q2 = 1.0 / (ui - wi);
q3 = ui * ui + wi * wi;
gw[i] -= (q1 - q2) * tinv; /* A'*g - (q1-q2) */
gu[i] = lambda - (q1 + q2) * tinv; /* lambda - (q1+q2) */
d1[i] = (q1 * q1 + q2 * q2) * tinv;
d2[i] = (q1 * q1 - q2 * q2) * tinv;
d3[i] = 2 / q3 * tinv;
/* dw = (bDA'*gv-bDb*gr2); */
gr2 = gw[i] + 2 * gu[i] * ui * wi / q3;
dw[i] = bDA[i] * gv[0] * bDbinv - gr2;
}
/* dw = (bDb*S-bDA'*bDA)\(bDA'*gv-bDb*gr2);
= (S-1/bDb)*bDA'*bDA)\(bDA'*(gv/bDb)-gr2); */
dmat_diagadd(BB, d3);
dmat_A_axxTpA(-bDbinv, bDA, BB);
dmat_posv(BB, dw);
/* dv = (-bDA*dw-gv)/bDb; */
dv[0] = -(dmat_dot(n, bDA, dw) + gv[0]) / bDb;
/* du = -(gu+d2.*dw)./d1; */
for (i = 0; i < n; i++)
du[i] = -(gu[i] + d2[i] * dw[i]) / d1[i];
}
//Execute function
int LPSolveClass::Execute()
{
/*
std::cout << "---------------------------------\n";
std::cout << "objective function\n";
for (unsigned int i = 0; i < coefficients.size(); i++)
std::cout << coefficients[i] << "\t";
std::cout << "\nConstant Value = " << obj_const << std::endl;
std::cout << "---------------------------------\n";
std::cout << "Equality Constraints\n";
for (unsigned int i = 0; i < A_equ.size(); i++){
//std::cout << "Row index = " << i << "\t\t";
for (unsigned int j = 0; j < A_equ[i].size(); j++)
std::cout << A_equ[i][j] << "\t";
std::cout << "\n";
}
std::cout << "b\n";
for (unsigned int i = 0; i < b_equ.size(); i++)
std::cout << b_equ[i] << "\t";
std::cout << "\n";
std::cout << "---------------------------------\n";
std::cout << "InEquality Constraints\n";
for (unsigned int i = 0; i < A_inequ.size(); i++){
//std::cout << "Row index = " << i << "\t\t";
for (unsigned int j = 0; j < A_inequ[i].size(); j++)
std::cout << A_inequ[i][j] << "\t";
std::cout << "\n";
}
std::cout << "b\n";
for (unsigned int i = 0; i < b_inequ.size(); i++)
std::cout << b_inequ[i] << "\t";
std::cout << "\n";
*/
lprec *lp;
int Ncol = coefficients.size(), *colno = NULL, j, ret = 0;
REAL *row = NULL;
/* We will build the model row by row
So we start with creating a model with 0 rows and n columns */
lp = make_lp(0, Ncol);
if (lp == NULL)
ret = 1;/* couldn't construct a new model... */
if (ret == 0){
//let us name our variables
std::string s = "x";
for (int i = 0; i < Ncol; i++){
std::stringstream out;
out << i;
s = s + out.str();
char *cpy = new char[s.size()+1] ;
strcpy(cpy, s.c_str());
set_col_name(lp, i+1, cpy);
}
/* create space large enough for one row */
colno = (int *) malloc(Ncol * sizeof(*colno));
row = (REAL *) malloc(Ncol * sizeof(*row));
if ((colno == NULL) || (row == NULL))
ret = 2;
}
set_add_rowmode(lp, TRUE);
//add the equation constraints
if (ret == 0){
/* makes building the model faster if it is done rows by row */
if (A_equ.size() > 0){
for (unsigned int i = 0; i < A_equ.size(); i++){//loop over the rows of equality constraints
for (unsigned int j = 0; j < A_equ[i].size(); j++){//loop over the columns of equality constraints
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = A_equ[i][j];
}
/* add the row to lpsolve */
if(!add_constraintex(lp, A_equ[i].size(), row, colno, EQ, b_equ[i]))
ret = 2;
}
}
}
//add the inequality constraints
if (ret == 0){
/* makes building the model faster if it is done rows by row */
if (A_inequ.size() > 0){
for (unsigned int i = 0; i < A_inequ.size(); i++){//loop over the rows of inequality constraints
for (unsigned int j = 0; j < A_inequ[i].size(); j++){//loop over the columns of inequality constraints
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = A_inequ[i][j];
}
/* add the row to lpsolve */
if(!add_constraintex(lp, A_inequ[i].size(), row, colno, LE, b_inequ[i]))
ret = 3;
}
}
}
//add the const constraint
if (ret == 0){
if (b_const.size()>0){
for (unsigned int i = 0; i < b_const.size(); i++){
if (b_const[i] > 0){
for (unsigned int j = 0; j < b_const.size(); j++){
if (i == j){
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = 1.0;
}
else{
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = 0.0;
}
}
if(!add_constraintex(lp, b_const.size(), row, colno, EQ, b_const[i]))
ret = 4;
}
}
}
}
//set the variables to be integer
if (ret == 0){
for (int i = 0; i < Ncol; i++)
set_int(lp, i+1, TRUE);
}
/* rowmode should be turned off again when done building the model */
set_add_rowmode(lp, FALSE);
//add the objective function
if (ret == 0){
//set the objective function
for (unsigned int i = 0; i < coefficients.size(); i++){
colno[i] = i+1;
row[i] = coefficients[i];
}
//set the objective in lpsolve
if(!set_obj_fnex(lp, coefficients.size(), row, colno))
ret = 4;
}
//set the objective to minimize
if (ret == 0){
set_minim(lp);
/* just out of curioucity, now show the model in lp format on screen */
/* this only works if this is a console application. If not, use write_lp and a filename */
write_LP(lp, stdout);
/* I only want to see important messages on screen while solving */
set_verbose(lp, IMPORTANT);
/* Now let lpsolve calculate a solution */
ret = solve(lp);
if(ret == OPTIMAL)
ret = 0;
else
ret = 5;
}
//get some results
if (ret == 0){
/* a solution is calculated, now lets get some results */
/* objective value */
std::cout << "Objective value: " << get_objective(lp) << std::endl;
/* variable values */
get_variables(lp, row);
/* variable values */
variables.resize(Ncol);
for(j = 0; j < Ncol; j++)
variables[j] = row[j];
/* we are done now */
}
else{
std::cout << "The optimal value can't be solved for linear programming, please check the constraints!!\n";
exit(1);
}
std::cout << "print the result\t # of line segments is \n";
for (int i = 0; i < Ncol; i++)
std::cout << "index = " << i << "\t# = " << variables[i] << std::endl;
/* free allocated memory */
if(row != NULL)
free(row);
if(colno != NULL)
free(colno);
/* clean up such that all used memory by lpsolve is freed */
if (lp != NULL)
delete_lp(lp);
return ret;
}
/*
* updates autos list
*/
void update_autos()
{
gchar command[1000];
/* remove all previous GDB variables for autos */
GList *iter = autos;
while (iter)
{
variable *var = (variable*)iter->data;
sprintf(command, "-var-delete %s", var->internal->str);
exec_sync_command(command, TRUE, NULL);
iter = iter->next;
}
g_list_foreach(autos, (GFunc)variable_free, NULL);
g_list_free(autos);
autos = NULL;
/* add current autos to the list */
GList *unevaluated = NULL;
const char *gdb_commands[] = { "-stack-list-arguments 0 0 0", "-stack-list-locals 0" };
int i, size = sizeof (gdb_commands) / sizeof(char*);
for (i = 0; i < size; i++)
{
gchar *record = NULL;
result_class rc = exec_sync_command(gdb_commands[i], TRUE, &record);
if (RC_DONE != rc)
break;
gchar *pos = record;
while ((pos = strstr(pos, "name=\"")))
{
pos += strlen("name=\"");
*(strchr(pos, '\"')) = '\0';
variable *var = variable_new(pos, i ? VT_LOCAL : VT_ARGUMENT);
/* create new gdb variable */
gchar *create_record = NULL;
gchar *escaped = g_strescape(pos, NULL);
sprintf(command, "-var-create - * \"%s\"", escaped);
g_free(escaped);
/* form new variable */
if (RC_DONE == exec_sync_command(command, TRUE, &create_record))
{
gchar *intname = strstr(create_record, "name=\"") + strlen ("name=\"");
*strchr(intname, '\"') = '\0';
var->evaluated = TRUE;
g_string_assign(var->internal, intname);
autos = g_list_append(autos, var);
g_free(create_record);
}
else
{
var->evaluated = FALSE;
g_string_assign(var->internal, "");
unevaluated = g_list_append(unevaluated, var);
}
pos += strlen(pos) + 1;
}
g_free(record);
}
/* get values for the autos (without incorrect variables) */
get_variables(autos);
/* add incorrect variables */
autos = g_list_concat(autos, unevaluated);
}
int demo()
{
lprec *lp;
int Ncol, *colno = NULL, j, ret = 0;
REAL *row = NULL;
/* We will build the model row by row
So we start with creating a model with 0 rows and 2 columns */
Ncol = 2; /* there are two variables in the model */
lp = make_lp(0, Ncol);
if(lp == NULL)
ret = 1; /* couldn't construct a new model... */
if(ret == 0) {
/* let us name our variables. Not required, but can be useful for debugging */
set_col_name(lp, 1, "x");
set_col_name(lp, 2, "y");
/* create space large enough for one row */
colno = (int *) malloc(Ncol * sizeof(*colno));
row = (REAL *) malloc(Ncol * sizeof(*row));
if((colno == NULL) || (row == NULL))
ret = 2;
}
if(ret == 0) {
set_add_rowmode(lp, TRUE); /* makes building the model faster if it is done rows by row */
/* construct first row (120 x + 210 y <= 15000) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 120;
colno[j] = 2; /* second column */
row[j++] = 210;
/* add the row to lpsolve */
if(!add_constraintex(lp, j, row, colno, LE, 15000))
ret = 3;
}
if(ret == 0) {
/* construct second row (110 x + 30 y <= 4000) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 110;
colno[j] = 2; /* second column */
row[j++] = 30;
/* add the row to lpsolve */
if(!add_constraintex(lp, j, row, colno, LE, 4000))
ret = 3;
}
if(ret == 0) {
/* construct third row (x + y <= 75) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 1;
colno[j] = 2; /* second column */
row[j++] = 1;
/* add the row to lpsolve */
if(!add_constraintex(lp, j, row, colno, LE, 75))
ret = 3;
}
if(ret == 0) {
set_add_rowmode(lp, FALSE); /* rowmode should be turned off again when done building the model */
/* set the objective function (143 x + 60 y) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 143;
colno[j] = 2; /* second column */
row[j++] = 60;
/* set the objective in lpsolve */
if(!set_obj_fnex(lp, j, row, colno))
ret = 4;
}
if(ret == 0) {
/* set the object direction to maximize */
set_maxim(lp);
/* just out of curioucity, now show the model in lp format on screen */
/* this only works if this is a console application. If not, use write_lp and a filename */
write_LP(lp, stdout);
/* write_lp(lp, "model.lp"); */
/* I only want to see important messages on screen while solving */
set_verbose(lp, IMPORTANT);
/* Now let lpsolve calculate a solution */
ret = solve(lp);
if(ret == OPTIMAL)
ret = 0;
else
ret = 5;
}
if(ret == 0) {
/* a solution is calculated, now lets get some results */
/* objective value */
printf("Objective value: %f\n", get_objective(lp));
/* variable values */
get_variables(lp, row);
for(j = 0; j < Ncol; j++)
printf("%s: %f\n", get_col_name(lp, j + 1), row[j]);
/* we are done now */
}
/* free allocated memory */
if(row != NULL)
free(row);
if(colno != NULL)
free(colno);
if(lp != NULL) {
/* clean up such that all used memory by lpsolve is freed */
delete_lp(lp);
}
return(ret);
}
int calculate (IN int nCols /* variables in the model */,
IN int nRows,
IN double** rows,
IN double* rights,
IN double* objectives,
OUT int* answer,
IN int verbose)
{
lprec *lp;
int result = 0;
char *str = NULL;
int *colno = NULL;
double *row = NULL;
/* We will build the model row by row
* So we start with creating a model
* with 0 rows and 2 columns
*/
if ( !(lp = make_lp (0, nCols)) )
{
/* couldn't construct a new model... */
result = 1;
goto RESULT;
}
if ( !(str = (char*) malloc ((log10 (nCols) + 10) * sizeof (*str))) )
{
result = 2;
goto RESULT;
}
/* let us name our variables. Not required,
* but can be useful for debugging
*/
for ( int i = 1; i <= nCols; ++i )
{
str[0] = 't';
_itoa (i, str + 1, 10);
set_col_name (lp, i, str);
// set_int (lp, i, TRUE);
}
/* create space large enough for one row */
colno = (int *) malloc (nCols * sizeof (*colno));
row = (double*) malloc (nCols * sizeof (*row));
if ( (colno == NULL) || (row == NULL) )
{
result = 2;
goto RESULT;
}
for ( int j = 0; j < nCols; ++j )
{ colno[j] = j + 1; /* (j + 1) column */ }
/* makes building the model faster if it is done rows by row */
set_add_rowmode (lp, TRUE);
for ( int i = 0; i < nRows; ++i )
{
// /* construct j row */
// for ( int j = 0; j < nCols; ++j )
// { row[j] = ??? ; }
/* (210 * t2 + 156 * t3 == 0.0178) */
/* (230 * t2 + 160 * t3 == 0.0176) */
/* add the row to lp_solve */
if ( !add_constraintex (lp, nCols, rows[i], colno, EQ, rights[i]) )
{
result = 3;
goto RESULT;
}
}
/* rowmode should be turned off again when done building the model */
set_add_rowmode (lp, FALSE);
// /* set the objective function */
// for ( int j = 0; j < nCols; ++j )
// { row[j] = objectives[j]; }
/* (t1 + t2 + t3 + t4) */
/* set the objective in lp_solve */
if ( !set_obj_fnex (lp, nCols, objectives, colno) )
{
result = 4;
goto RESULT;
}
/* set the object direction to maximize */
set_minim (lp);
if ( verbose )
{
/* just out of curioucity, now show the model in lp format on screen */
/* this only works if this is a console application. If not, use write_lp and a filename */
write_LP (lp, stdout);
/* write_lp(lp, "model.lp"); */
}
/* I only want to see important messages on screen while solving */
set_verbose (lp, IMPORTANT);
/* Now let lpsolve calculate a solution */
result = solve (lp);
if ( result == OPTIMAL )
{ result = 0; }
else
{
result = 5;
goto RESULT;
}
/* a solution is calculated,
* now lets get some results
*/
if ( verbose )
{
/* objective value */
printf ("Objective value: %f\n", get_objective (lp));
}
/* variable values */
get_variables (lp, row);
for ( int j = 0; j < nCols; j++ )
{
if ( verbose )
printf ("%s: %f\n", get_col_name (lp, j + 1), row[j]);
answer[j] = row[j];
}
/* we are done now */
RESULT:;
/* free allocated memory */
if ( str != NULL )free (str);
if ( row != NULL ) free (row);
if ( colno != NULL ) free (colno);
if ( lp != NULL )
{
/* clean up such that all used memory by lpsolve is freed */
delete_lp (lp);
}
return result;
}
double solve_constraints(int this_task)
{
lprec *lp;
int numVar = 0, *var = NULL, ret = 0, i, j, k, var_count;
double *coeff = NULL, lhs,rhs, obj;
char col_name[10];
/* Creating a model */
for(i = 1;i < this_task; i++)
numVar+=i;
lp = make_lp(0, numVar);
if(lp == NULL)
ret = 1; /* Couldn't construct a new model */
if(ret == 0) {
var_count = 1;
for(i = 1 ; i < this_task; i++){
for(j = i+1 ; j <= this_task; j++)
{
sprintf(col_name, "%dNNP%d_%d", this_task, i, j);
set_col_name(lp, var_count, col_name);
var_count++;
}
}
/* create space large enough for one row(i.e. equation) */
var = (int *) malloc(numVar * sizeof(*var));
coeff = (double *) malloc(numVar * sizeof(*coeff));
if((var == NULL) || (coeff == NULL))
ret = 2;
}
/* add the equations to lpsolve */
if(ret == 0) {
set_add_rowmode(lp, TRUE);
/* --------------------adding EQN-D-------------------- */
for(j = 2;j <= this_task;j++){
var_count = 0;
for(i = 1; i < j; i++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = 1;
var_count++;
}
lhs= 0;
for(i = 1; i < j; i++)
lhs+= nnp_min[i][j];
lhs*= floor(R[this_task]/task[j].p);
rhs = 0;
for(i = 1; i < j; i++)
rhs += nnp_max[i][j];
rhs *= ceil(R[this_task]/task[j].p);
if(!add_constraintex(lp, var_count, coeff, var, GE, lhs))
ret = 3;
if(!add_constraintex(lp, var_count, coeff, var, LE, rhs))
ret = 3;
}
}
if(ret == 0) {
/* --------------------adding EQN-E-------------------- */
for(k = 2;k <= this_task;k++)
{
var_count = 0;
for(j = 2; j <= k; j++){
for(i = 1; i < j; i++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = 1;
var_count++;
}
}
rhs = 0;
for(i = 1; i < k; i++)
rhs += ceil(R[this_task]/task[i].p);
if(!add_constraintex(lp, var_count, coeff, var, LE,rhs))
ret = 3;
}
}
if(ret == 0) {
/* ------------------adding EQN-G & H------------------ */
for(j = 2; j <= this_task ; j++){
for(i = 1; i < j; i++){
lhs= floor(R[this_task]/task[j].p) * nnp_min[i][j];
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[0] = get_nameindex(lp, col_name, FALSE);
coeff[0] = 1;
if(!add_constraintex(lp, 1, coeff, var, GE, lhs))
ret = 3;
rhs = min(ceil(R[this_task]/task[i].p), ceil(R[this_task]/task[j].p) * ceil(R[j]/task[i].p), ceil(R[this_task]/task[j].p) * nnp_max[i][j]);
if(!add_constraintex(lp, 1, coeff, var, LE,rhs))
ret = 3;
}
}
}
if(ret == 0) {
/* --------------------adding EQN-I-------------------- */
for(i = 1; i < this_task; i++){
var_count = 0;
for(j = i+1; j <= this_task; j++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = 1;
var_count++;
}
rhs = ceil(R[this_task]/task[i].p);
if(!add_constraintex(lp, var_count, coeff, var, LE,rhs))
ret = 3;
}
}
set_add_rowmode(lp, FALSE);
if(ret == 0) {
/* -----------------set the objective----------------- */
var_count = 0;
for(i = 1 ; i < this_task; i++){
for(j = i+1 ; j<= this_task; j++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = get_f(this_task, i, j);
var_count++;
}
}
if(!set_obj_fnex(lp, var_count, coeff, var))
ret = 4;
set_maxim(lp);
write_LP(lp, stdout);
set_verbose(lp, IMPORTANT);
ret = solve(lp);
if(ret == OPTIMAL)
ret = 0;
else
ret = 5;
}
if(ret == 0) {
obj = get_objective(lp);
/* Displaying calculated values */
/* variable values */
printf("\nVariable values:\n");
get_variables(lp, coeff);
printf("\n");
for(j = 0; j < numVar; j++)
printf("%s: %f\n", get_col_name(lp, j + 1), coeff[j]);
/* objective value */
printf("\nObjective value: %f\n\n", obj);
}
printf("LP ERROR = %d\n\n", ret);
/* free allocated memory */
if(coeff != NULL)
free(coeff);
if(var != NULL)
free(var);
if(lp != NULL)
delete_lp(lp);
return ret == 0 ? obj : 0;
}
/*
* updates watches list
*/
void update_watches()
{
gchar command[1000];
/* delete all GDB variables */
GList *iter = watches;
while (iter)
{
variable *var = (variable*)iter->data;
if (var->internal->len)
{
sprintf(command, "-var-delete %s", var->internal->str);
exec_sync_command(command, TRUE, NULL);
}
/* reset all variables fields */
variable_reset(var);
iter = iter->next;
}
/* create GDB variables, adding successfully created
variables to the list then passed for updatind */
GList *updating = NULL;
iter = watches;
while (iter)
{
variable *var = (variable*)iter->data;
/* try to create variable */
gchar *record = NULL;
gchar *escaped = g_strescape(var->name->str, NULL);
sprintf(command, "-var-create - * \"%s\"", escaped);
g_free(escaped);
if (RC_DONE != exec_sync_command(command, TRUE, &record))
{
/* do not include to updating list, move to next watch */
var->evaluated = FALSE;
g_string_assign(var->internal, "");
g_free(record);
iter = iter->next;
continue;
}
/* find and assign internal name */
gchar *pos = strstr(record, "name=\"") + strlen("name=\"");
*strchr(pos, '\"') = '\0';
g_string_assign(var->internal, pos);
g_free(record);
var->evaluated = TRUE;
/* add to updating list */
updating = g_list_append(updating, var);
iter = iter->next;
}
/* update watches */
get_variables(updating);
/* free updating list */
g_list_free(updating);
}
/** \brief Compute search direction using pcg method.
*
*/
void compute_searchdir_pcg(problem_data_t * pdat, variables_t * vars,
double t, double s, double gap, pcg_status_t * pcgstat,
adata_t * adata, mdata_t * mdata, double *precond,
double *tmp_m1, double *A2h, double *tmp_x1)
{
int i, m, n, nz;
double *p0, *p1, *p2, *p3;
double normg, pcgtol, pcgmaxi, multfact;
dmatrix *matX1, *matX2;
double lambda, tinv;
double *g, *h, *z, *expz, *expmz, *ac, *ar, *b, *d1, *d2, *Aw;
double *x, *v, *w, *u, *dx, *dv, *dw, *du, *gv, *gw, *gu, *gx;
static double pcgtol_factor = 1.0;
get_problem_data(pdat, &matX1, &matX2, &ac, &ar, &b, &lambda);
get_variables(vars, &x, &v, &w, &u, &dx, &dv, &dw, &du, &gx, &gv,
&gw, &gu, &g, &h, &z, &expz, &expmz, &d1, &d2, &Aw);
m = matX1->m;
n = matX1->n;
nz = matX1->nz;
tinv = 1.0 / t;
p0 = &precond[0];
p1 = &precond[1];
p2 = &precond[1+n];
p3 = &precond[1+n+n];
/* dmat_vset(n+n+1, 0, dx); */
dmat_yATx(matX2, h, A2h); /* A2h = A2'*h */
multfact = 0.0;
if (ac != NULL)
{
/* h.*ac */
dmat_elemprod(m, h, ac, tmp_m1);
dmat_vset(n, 0, tmp_x1);
dmat_yAmpqTx(matX1, NULL, NULL, tmp_m1, tmp_x1);
dmat_elemprod(n, ar, tmp_x1, tmp_x1);
for (i = 0; i < m; i++)
{
multfact += h[i] * ac[i] * ac[i];
}
}
p0[0] = 0;
for (i = 0; i < m; i++)
{
p0[0] += b[i] * b[i] * h[i];
}
/* complete forming gradient and d1, d2, precond */
for (i = 0; i < n; i++)
{
double q1, q2, d3, div;
q1 = 1.0 / (u[i] + w[i]);
q2 = 1.0 / (u[i] - w[i]);
gw[i] -= (q1 - q2) * tinv; /* A'*g - (q1-q2) */
gu[i] = lambda - (q1 + q2) * tinv; /* lambda - (q1+q2) */
d1[i] = (q1 * q1 + q2 * q2) * tinv;
d2[i] = (q1 * q1 - q2 * q2) * tinv;
if (ac != NULL)
{
d3 = A2h[i] + d1[i] + multfact*ar[i]*ar[i] - 2*tmp_x1[i];
}
else
{
d3 = A2h[i] + d1[i];
}
div = 1 / (d3 * d1[i] - d2[i] * d2[i]);
p1[i] = d1[i] * div;
p2[i] = d2[i] * div;
p3[i] = d3 * div;
}
normg = dmat_norm2(n+n+1, gx);
pcgtol = min(1e-1, 0.3*gap/min(1.0,normg));
/*
pcgtol = min(1e-1, 0.3*gap/min(1.0,sqrt(normg)));
*/
pcgmaxi = MAX_PCG_ITER;
if (s < 1e-5)
{
pcgtol_factor *= 0.5;
}
else
{
pcgtol_factor = 1.0;
}
pcgtol = pcgtol*pcgtol_factor;
dmat_waxpby(n+n+1, -1, gx, 0, NULL, tmp_x1);
pcg(dx, pcgstat, afun, adata, mfun, mdata, tmp_x1, pcgtol, pcgmaxi, n+n+1);
}
/** \brief Compute search direction using cholesky method (m < n).
*
*/
void compute_searchdir_chol_fat(problem_data_t *pdat, variables_t *vars,
double t, dmatrix *B, dmatrix *BB,
double *tm1, double *bDA,
double *d3inv, double *tmp31, double *tmp32)
{
int i, m, n;
double bDb;
dmatrix *matX1, *matX2;
double lambda, tinv;
double *g, *h, *z, *expz, *expmz, *ac, *ar, *b, *d1, *d2, *Aw;
double *x, *v, *w, *u, *dx, *dv, *dw, *du, *gv, *gw, *gu, *gx;
get_problem_data(pdat, &matX1, &matX2, &ac, &ar, &b, &lambda);
get_variables(vars, &x, &v, &w, &u, &dx, &dv, &dw, &du, &gx, &gv,
&gw, &gu, &g, &h, &z, &expz, &expmz, &d1, &d2, &Aw);
m = matX1->m;
n = matX1->n;
tinv = 1.0 / t;
/* bDb, Db */
bDb = 0.0;
for (i = 0; i < m; i++)
{
tm1[i] = h[i] * b[i]; /* tm1 = Db */
bDb += b[i] * tm1[i];
}
/* bDA, D_inv */
dmat_yATx(matX1, tm1, bDA);
dmat_copy(matX1, B); /* B = A */
dmat_yinvx(m, h, tm1); /* tm1 = D_inv */
for (i = 0; i < n; i++)
{
double ui, wi, q1, q2, q3, gr2;
ui = u[i];
wi = w[i];
q1 = 1.0 / (ui + wi);
q2 = 1.0 / (ui - wi);
q3 = ui * ui + wi * wi;
gw[i] -= (q1 - q2) * tinv; /* A'*g - (q1-q2) */
gu[i] = lambda - (q1 + q2)*tinv; /* lambda - (q1+q2) */
d1[i] = (q1 * q1 + q2 * q2) * tinv;
d2[i] = (q1 * q1 - q2 * q2) * tinv;
gr2 = gw[i] + 2 * gu[i] * ui * wi / q3;
d3inv[i] = t * q3 / 2; /* en = d3^{-1} */
/* temporary use of tmp31 */
tmp31[i] = sqrt(d3inv[i]);
/* store temporary values in dw, du */
dw[i] = d3inv[i] * bDA[i]; /* dw := d3inv.*bDA */
du[i] = d3inv[i] * gr2; /* du := d3inv.*gr2 */
}
/* B = B*D3^{1/2} */
dmat_diagscale(B, NULL, FALSE, tmp31, FALSE);
/* S = BB = ... */
/* BB = A*D3_inv*A^T */
dmat_B_AAT(B, BB); /* BB = B*B^T */
/* BB = D_inv + A*D3_inv*A^T */
dmat_diagadd(BB, tm1);
/* SMW */
dmat_yAx(matX1, dw, tm1);
dmat_posv(BB, tm1);
dmat_yATx(matX1, tm1, tmp31);
dmat_elemprod(n, d3inv, tmp31, tmp31);
dmat_waxpby(n, -1, tmp31, 1, dw, tmp31);
dmat_yAx(matX1, du, tm1);
dmat_potrs(BB, tm1);
dmat_yATx(matX1, tm1, tmp32);
dmat_elemprod(n, d3inv, tmp32, tmp32);
dmat_waxpby(n, -1, tmp32, 1, du, tmp32);
dv[0] = (-gv[0] + dmat_dot(n,bDA,tmp32)) / (bDb - dmat_dot(n,bDA,tmp31));
/* dw = ... */
dmat_waxpby(n, -dv[0], tmp31, -1, tmp32, dw);
/* du = -(gu+d2.*dw)./d1; */
for (i = 0; i < n; i++)
du[i] = -(gu[i] + d2[i] * dw[i]) / d1[i];
}
vector<PathPoint *> LPPath :: findPath(vertex *curr) {
lprec *lp;
int numDropoff = 0;
int numDropped = 0;
int numPickup = 0;
//find pairs for each dropoff point
for(int i = 0; i < points.size(); i++) {
if(points[i]->type == 1) {
bool foundPair = false;
for(int j = 0; j < points.size(); j++) {
if(j != i && points[j]->pairIndex == points[i]->pairIndex) {
pairIndex[i] = j;
foundPair = true;
break;
}
}
//sometimes, there's an error and the pair cannot be found
//in that case, print out some debugging information
if(!foundPair) {
cout << i << ":" << points[i]->pairIndex << " ";
for(int j = 0; j < points.size(); j++) {
cout << points[j]->type << ":" << points[j]->pairIndex << " ";
}
cout << endl;
}
}
}
//occasionally we encounter a model that takes hours or days to solve
//we set a timeout on the solve function, and then advance to the next iteration
//as the iteration increases, we introduce more randomness into the model
// (this is done via the getNonZero function)
for(int iteration = 0; ; iteration += 10) {
//calculate cost matrix
for(int i = 0; i < points.size(); i++) {
PathPoint *ipoint = points[i];
if(ipoint->type == 0) numPickup++;
else if(ipoint->type == 1) numDropoff++;
else if(ipoint->type == 2) numDropped++;
//from this point to itself
costMatrix[i + 1][i] = getNonZero(0, iteration);
//from this point to every other point
for(int j = 0; j < points.size(); j++) {
if(i != j)
costMatrix[i + 1][j] = getNonZero(length(ipoint, points[j]), iteration);
}
//from the current location to this point
costMatrix[0][i] = getNonZero(taxiPath->shortestPath(curr, ipoint->vert), iteration);
}
//calculate m matrix
//first, we have to find earliest and latest
//the current location must occur at time zero
latest[0] = 0;
for(int i = 0; i < points.size(); i++) {
if(points[i]->type == 0 || points[i]->type == 2) {
//this is a pickup or stand-alone dropoff point
//the earliest time occurs when we go directly
// from the current location to here
//the latest time is set by the pickup constraint
earliest[i] = costMatrix[0][i];
latest[i + 1] = points[i]->remaining;
} else if(points[i]->type == 1) {
//this is a dropoff point
//the earliest time occurs when we go directly
// to the pickup point, then here
//the latest time occurs when we get to the pickup
// point the latest, and then here the latest
// (stretch both pickup and service constraints)
earliest[i] = costMatrix[0][pairIndex[i]] + costMatrix[pairIndex[i] + 1][i];
latest[i + 1] = points[pairIndex[i]]->remaining + points[i]->remaining;
}
}
//calculate m
double test;
for(int i = 0; i < points.size() + 1; i++) {
for(int j = 0; j < points.size(); j++) {
test = latest[i] + costMatrix[i][j] - earliest[j];
if(test > 0) m[i][j] = test;
else m[i][j] = 0;
}
}
//find the number of binary columns
//each x_ij determines whether or not the taxi will move
// from i to j
//in the comments below these movements will be referred
// to as route segments (_from_ i _to_ j)
int ncol = (points.size() + 1) * points.size();
//find the total number of columns
//besides the binary ones, there are ones for the time
// at which the taxi will reach a point (B_i)
int ncol_total = ncol + points.size() + 1;
//create the lp instance
lp = make_lp(0, ncol_total);
//colno and row are used to define the constraints, and
// later row will store the result from lpsolve
//colno identifies the variable (column), and row identifies
// the constants (multiplied by the variable); then, a
// separate value determines the number of variables
// that will be read (since we are using a sparse matrix -
// otherwise we wouldn't need colno)
//note**: column numbers are labeled starting from 1, not 0
int *colno = new int[ncol_total];
REAL *row = new REAL[ncol_total];
//since we're going to be adding constraints equation
// by equation, we set add row mode to make it faster
set_add_rowmode(lp, TRUE);
//disable most output from lpsolve
set_verbose(lp, CRITICAL);
//set timeout of three seconds so we don't spend forever on this model
set_timeout(lp, 3);
//set up the binary constraints
for(int i = 0; i < ncol; i++) {
set_binary(lp, i + 1, TRUE);
}
//constraints 1 to 3
//these have one constraint per point
for(int i = 0; i < points.size(); i++) {
//1. the total number of route segments to here will
// be equal to one
for(int j = 0; j < points.size() + 1; j++) {
colno[j] = j * points.size() + i + 1;
row[j] = 1;
}
add_constraintex(lp, points.size() + 1, row, colno, EQ, 1);
//2. there will be no route segment from here to itself
colno[0] = (i + 1) * points.size() + i + 1;
row[0] = 1;
add_constraintex(lp, 1, row, colno, EQ, 0);
//3. the total number of route segments from here will
// be less than or equal to one (since the last point in
// the route will be zero)
for(int j = 0; j < points.size(); j++) {
colno[j] = (i + 1) * points.size() + j + 1;
row[j] = 1;
}
add_constraintex(lp, points.size(), row, colno, LE, 1);
}
//4. there will be exactly one route segment from the
// current location
for(int i = 0; i < points.size(); i++) {
colno[i] = i + 1;
row[i] = 1;
}
add_constraintex(lp, points.size(), row, colno, EQ, 1);
//5. the relative time that the taxi reaches the current
// location is zero
colno[0] = ncol + 1;
row[0] = 1;
add_constraintex(lp, 1, row, colno, EQ, 0);
//6. defined for each route segment (i, j)
//if the segment (i, j) exists, then the time B_j
// the taxi reaches j will be greater than
// B_i + time(i, j)
// (time is interchangeable with distance)
//in other words,
// B_j >= ( B_i + time(i, j) ) * x_ij
//
//**but that's non-linear (since B_i * x_ij)
//to achieve the if statement, we subtract a large
// number M from the right and M * x_ij on the left
//the equation becomes:
// B_j - B_i - M*x_ij >= time(i, j) - M
//
//m_ij that we found earlier is suitable for M, since
// if x_ij = 0 the equation reduces to
// B_j - B_i >= time(i, j) - M
// >> M >= B_i + time(i, j) - B_j
// we used the maximum possible value for B_i (latest[i])
// and the minimim for B_j (earliest[j]), so everything
// is good :)
for(int i = 0; i < points.size() + 1; i++) {
for(int j = 0; j < points.size(); j++) {
colno[0] = ncol + 1 + i;
colno[1] = ncol + 1 + j + 1; //make sure to add an extra 1 because we're not including current location
colno[2] = i * points.size() + j + 1;
double constant = costMatrix[i][j] - m[i][j];
//only use positive constants or it seems to explode
if(constant >= 0) {
row[0] = -1;
row[1] = 1;
row[2] = -m[i][j];
add_constraintex(lp, 3, row, colno, GE, constant);
} else {
row[0] = 1;
row[1] = -1;
row[2] = m[i][j];
add_constraintex(lp, 3, row, colno, LE, -constant);
}
}
}
//constraints 7, 8, and 9
for(int i = 0; i < points.size(); i++) {
if(points[i]->type == 1) {
//dropoff point
//make sure to add an extra 1 because we're not including current location
colno[0] = ncol + 1 + i + 1;
colno[1] = ncol + 1 + pairIndex[i] + 1;
row[0] = 1;
row[1] = -1;
//constraints on L_i (= B_i - B_pickup[i])
//7. L_i >= time(pickup[i], i)
add_constraintex(lp, 2, row, colno, GE, costMatrix[pairIndex[i] + 1][i]);
//8. L_i <= remaining service constraint
add_constraintex(lp, 2, row, colno, LE, points[i]->remaining);
} else if(points[i]->type == 0 || points[i]->type == 2) {
//pickup or stand-alone dropoff point
colno[0] = ncol + 1 + i + 1;
row[0] = 1;
//9. B_i <= remaining pickup constraint
add_constraintex(lp, 1, row, colno, LE, points[i]->remaining);
}
}
//10. this used to enforce that all varibles be
// non-negative, but it seems to be working now
// (lpsolve makes variables non-negative unless
// explicitly stated in a constraint)
for(int i = ncol; i < ncol_total; i++) {
colno[0] = i + 1;
row[0] = 1;
//add_constraintex(lp, 1, row, colno, GE, 0);
}
//disable rowmode because we're done building model
set_add_rowmode(lp, FALSE);
//objective function: minimize sum( time(i, j) * x_ij )
//we maximize the negative though
// (we could change to set_minim(lp), but it's the same thing)
for(int i = 0; i < points.size() + 1; i++) {
for(int j = 0; j < points.size(); j++) {
colno[i * points.size() + j] = i * points.size() + j + 1;;
row[i * points.size() + j] = -costMatrix[i][j];
}
}
set_obj_fnex(lp, ncol, row, colno);
set_maxim(lp); //maximize the objective function
struct timeval solveStartTime;
struct timeval solveEndTime;
gettimeofday(&solveStartTime, NULL);
int ret = solve(lp);
gettimeofday(&solveEndTime, NULL);
long tS = solveStartTime.tv_sec*1000000 + (solveStartTime.tv_usec);
long tE = solveEndTime.tv_sec*1000000 + (solveEndTime.tv_usec);
long solveTime = tE - tS;
if(iteration == 0 && ret != TIMEOUT) {
lpTotalTime += solveTime;
if(solveTime > lpMaxTime) lpMaxTime = solveTime;
lpNum++;
cout << "lptimestatus: " << lpTotalTime / lpNum << " " << lpMaxTime << " " << lpNum << " " << solveTime << endl;
}
//if we didn't get the optimal solution, don't continue
if(ret != OPTIMAL) {
delete colno;
delete row;
delete_lp(lp);
bestList.clear();
if(ret == TIMEOUT) {
//if we timed out, then we need to try again
cout << "timed out on iteration " << iteration << ", advancing..." << endl;
continue;
} else {
return bestList;
}
}
get_variables(lp, row); //store variables in our row array
//extract the ordering of the points from the x_ij in the row
//at the same time, we calculate the route's distance
int previous = 0;
minTour = 0;
for(int i = 0; i < points.size(); i++) {
for(int j = 0; j < points.size(); j++) {
if(row[previous * points.size() + j] == 1) {
minTour += costMatrix[previous][j];
bestList.push_back(points[j]);
previous = j + 1;
break;
}
}
}
delete colno;
delete row;
delete_lp(lp);
//sometimes errors occur, probably because M was
// too large and double-precision isn't accurate
// enough
//in these cases, since they're rare enough, we
// assume that the model was infeasible
if(bestList.size() != points.size()) {
bestList.clear();
minTour = numeric_limits<double>::max();
return bestList;
}
return bestList;
}
}
int main(int argc, char* argv[]) {
if(argc != 2) {
std::cout << "Usage: " << argv[0] << " /path/to/lua/script.lua" << std::endl;
exit(1);
}
std::cout.unsetf(std::ios::floatfield);
std::cout.precision(5);
std::cout << std::fixed;
std::cout << "==================== SETUP ====================" << std::endl;
// TODO: detect unusual currency bases for accurate profit calculation
auto config = std::make_shared<LuaScript>(argv[1]);
std::cout << "Simulating a maximum of " << config->steps() << " steps" << std::endl;
std::cout << config->optimizations() << " optimizations per in sample" << std::endl;
auto charts = Chart::load_from_string(config->charts());
auto ts = std::make_unique<TickSource>(config->csv_path());
auto vars = Variable::load_from_string(config->variables());
auto optimizer = std::make_unique<Optimizer>(vars);
ts->fill_charts(charts);
ts->advance_charts_to_next_sunday(charts);
int step_number = 1;
int weeks_in_sample = std::stoi(config->in_sample_time());
int weeks_out_of_sample = std::stoi(config->out_of_sample_time());
std::vector<float> optimization_scores;
std::vector<float> execution_scores;
// ----- MAIN LOOP -------------------------------------------------------------------------
for(;;) {
// ----- FIND IN AND OUT OF SAMPLE START AND END POINTS ----------------------------
// in_sample_record_end is just out_of_sample_record_start - 1
unsigned long in_sample_record_start = ts->next_record_id();
unsigned long out_of_sample_record_start = 0;
unsigned long out_of_sample_record_end = 0;
bool tick_is_sunday = true;
bool on_sunday = true;
int sundays_seen = 0;
for(auto tick = ts->next(); tick; tick = ts->next()) {
tick_is_sunday = tick->is_sunday();
if(!on_sunday && tick_is_sunday) {
on_sunday = true;
sundays_seen++;
} else if(on_sunday && !tick_is_sunday) {
on_sunday = false;
}
if(sundays_seen == weeks_in_sample) {
out_of_sample_record_start = ts->next_record_id() - 1;
break;
}
}
if(!out_of_sample_record_start) {
bail("ran out of tick source when searching for out of sample start");
}
sundays_seen = 0;
on_sunday = true;
for(auto tick = ts->next(); tick; tick = ts->next()) {
tick_is_sunday = tick->is_sunday();
if(!on_sunday && tick_is_sunday) {
on_sunday = true;
sundays_seen++;
} else if(on_sunday && !tick_is_sunday) {
on_sunday = false;
}
if(sundays_seen == weeks_out_of_sample) {
// stop on the tick before the current tick
out_of_sample_record_end = ts->next_record_id() - 2;
break;
}
}
if(!out_of_sample_record_end) {
bail("ran out of tick source when searching for out of sample end");
}
std::cout << "In sample: " << ts->peek_at(in_sample_record_start)->show()
<< " through " << ts->peek_at(out_of_sample_record_start - 1)->show()
<< std::endl;
std::cout << "Out of sample: " << ts->peek_at(out_of_sample_record_start)->show()
<< " through " << ts->peek_at(out_of_sample_record_end)->show()
<< std::endl;
// ----- OPTIMIZE ON IN SAMPLE PERIOD ----------------------------------------------
auto subset = ts->subset(in_sample_record_start, out_of_sample_record_start - 1);
auto winner = optimizer->optimize_variables_on(config, charts, subset);
// optimizer->print_scores();
// ----- IF OPTIMIZATION SUCCEEDED, EXECUTE ON OUT OF SAMPLE PERIOD ----------------
if(winner->get_score() < config->minimum_optimization_score()) {
bail("Failed to find a variables above the cutoff");
}
optimization_scores.push_back(winner->get_score());
std::cout << "==================== EXECUTING ON ====================" << std::endl;
std::cout << "Winning variables!" << std::endl;
std::cout << "Score: " << winner->get_score() << std::endl;
for(auto var: winner->get_variables()) {
std::cout << "\t" << var->get_name() << " -> " << var->show() << std::endl;
}
auto new_vars = winner->get_variables();
auto new_config = config;
auto new_charts = charts;
auto oos = ts->subset(out_of_sample_record_start, out_of_sample_record_end);
Simulation sim(new_config, new_charts, new_vars);
sim.run(oos);
std::cout << "Execution score: " << sim.get_score() << std::endl;
std::cout << "% profitable: " << sim.percentage_of_profitable_trades()
<< "%" << std::endl;
std::cout << "Average trade duration: " << sim.average_trade_duration() << std::endl;
std::cout << "Worst DD: " << sim.get_worst_drawdown() << "%" << std::endl;
std::cout << "Equity high: " << sim.get_equity_high() << std::endl;
std::cout << "Equity low: " << sim.get_equity_low() << std::endl;
std::cout << "Trades: " << sim.get_trade_count() << std::endl;
std::cout << "Winners: " << sim.get_winning_trade_count() << std::endl;
std::cout << "Losers: " << sim.get_losing_trade_count() << std::endl;
std::cout << "Best: " << sim.best_winning_trade()->profit() << std::endl;
std::cout << "Worst: " << sim.worst_losing_trade()->profit() << std::endl;
// ----- IF EXECUTION SUCCEEDED, RECORD RESULTS ------------------------------------
if(sim.get_score() < config->minimum_execution_score()) {
bail("Failed at optimization step");
}
execution_scores.push_back(sim.get_score());
// ----- EXIT IF WE'RE AT MAX STEPS ------------------------------------------------
step_number++;
if(step_number > config->steps()) {
std::cout << "Reached max steps, breaking" << std::endl;
break;
}
// ----- ADVANCE CHARTS TO NEXT IN SAMPLE START ------------------------------------
ts->seek_to_record(in_sample_record_start);
ts->advance_charts_to_next_sunday(charts);
}
std::cout << "==================== RESULTS ====================" << std::endl;
// ----- SHOW PROFIT FOR EACH PERIOD -------------------------------------------------------
std::cout << "Scores:" << std::endl;
for(unsigned long i = 0; i < optimization_scores.size(); i++) {
std::cout << i + 1 << " - ";
std::cout << "Opti: " << optimization_scores[i];
std::cout << " - ";
std::cout << "Exec: " << execution_scores[i];
std::cout << std::endl;
}
// ----- SHOW WALK FORWARD EFFICIENCY ------------------------------------------------------
float optimization_total = sum_vector(optimization_scores);
float execution_total = sum_vector(execution_scores);
float efficiency = execution_total / optimization_total;
std::cout << "Optimization total: " << optimization_total << " - ";
std::cout << "Execution total: " << execution_total << " - ";
std::cout << "WFA efficiency: " << efficiency << "% - Verdict: ";
if(efficiency < 0.5) {
std::cout << "FAIL";
} else if(efficiency >= 0.5 && efficiency < 1.0) {
std::cout << "ACCEPTABLE";
} else if(efficiency >= 1.0 && efficiency <= 1.5) {
std::cout << "GREAT";
} else {
std::cout << "TOO GOOD - SUSPICIOUS";
}
std::cout << std::endl;
// ----- SHOW PROFIT FACTOR ----------------------------------------------------------------
float gross_profit = 0.0;
float gross_loss = 0.0;
for(auto score: execution_scores) {
if(score >= 0.0)
gross_profit += score;
else
gross_loss += score;
}
gross_loss = std::abs(gross_loss);
float profit_factor = gross_profit / gross_loss;
std::cout << "Gross profit: " << gross_profit << " - ";
std::cout << "Gross loss: " << gross_loss << " - ";
std::cout << "Profit factor: " << profit_factor << " - Verdict: ";
if(profit_factor < 1.5) {
std::cout << "FAIL";
} else if(profit_factor >= 1.5 && profit_factor < 2.0) {
std::cout << "ACCEPTABLE";
} else if(profit_factor >= 2.0 && profit_factor <= 3.0) {
std::cout << "GREAT";
} else {
std::cout << "TOO GOOD - SUSPICIOUS";
}
std::cout << std::endl;
// ----- SHOW FINAL SCORE ------------------------------------------------------------------
// TODO: final score should be some function of two or more of the following:
// execution_total, WFA efficiency, max drawdown, profit factor, % profitable
std::cout << "Final score: " << execution_total << " - Minimum score: "
<< config->minimum_overall_score() << " - Verdict: ";
std::cout << (execution_total >= config->minimum_overall_score() ? "PASS" : "FAIL") << std::endl;
std::cout << "==================== SHUTDOWN ====================" << std::endl;
return 0;
}
int l1_logreg_train(dmatrix *X, double *b, double lambda, train_opts to,
double *initial_x, double *initial_t, double *sol,
int *total_ntiter, int *total_pcgiter)
{
/* problem data */
problem_data_t prob;
variables_t vars;
dmatrix *matX1; /* matX1 = diag(b)*X_std */
dmatrix *matX2; /* matX2 = X_std.^2 (only for pcg) */
double *ac, *ar;
double *avg_x, *std_x;
int m, n, ntiter, pcgiter, status;
double pobj, dobj, gap;
double t, s, maxAnu;
double *g, *h, *z, *expz, *expmz;
double *x, *v, *w, *u;
double *dx, *dv, *dw, *du;
double *gv, *gw, *gu, *gx;
double *d1, *d2, *Aw;
/* pcg variables */
pcg_status_t pcgstat;
adata_t adata;
mdata_t mdata;
double *precond;
/* temporary variables */
double *tm1, *tn1, *tn2, *tn3, *tn4, *tx1;
/* temporary variables for dense case (cholesky) */
dmatrix *B; /* m x n (or m x n) */
dmatrix *BB; /* n x n (or m x m) */
char format_buf[PRINT_BUF_SIZE];
#if INTERNAL_PLOT
dmatrix *internal_plot;
dmat_new_dense(&internal_plot, 3, MAX_NT_ITER);
memset(internal_plot->val,0,sizeof(double)*3*MAX_NT_ITER);
/* row 1: cum_nt_iter, row 2: cum_pcg_iter, row 3: duality gap */
#endif
p2func_progress print_progress = NULL;
/*
* INITIALIZATION
*/
s = 1.0;
pobj = DBL_MAX;
dobj = -DBL_MAX;
pcgiter = 0;
matX1 = NULL;
matX2 = NULL;
init_pcg_status(&pcgstat);
dmat_duplicate(X, &matX1);
dmat_copy(X, matX1);
m = matX1->m;
n = matX1->n;
if (to.sflag == TRUE)
{
/* standardize_data not only standardizes the data,
but also multiplies diag(b). */
standardize_data(matX1, b, &avg_x, &std_x, &ac, &ar);
}
else
{
/* matX1 = diag(b)*X */
dmat_diagscale(matX1, b, FALSE, NULL, TRUE);
avg_x = std_x = ac = ar = NULL;
}
if (matX1->nz >= 0) /* only for pcg */
{
dmat_elemAA(matX1, &matX2);
}
else
{
matX2 = NULL;
}
set_problem_data(&prob, matX1, matX2, ac, ar, b, lambda, avg_x, std_x);
create_variables(&vars, m, n);
get_variables(&vars, &x, &v, &w, &u, &dx, &dv, &dw, &du, &gx, &gv,
&gw, &gu, &g, &h, &z, &expz, &expmz, &d1, &d2, &Aw);
allocate_temporaries(m, n, (matX1->nz >= 0),
&tm1, &tn1, &tn2, &tn3, &tn4, &tx1, &precond, &B, &BB);
if (initial_x == NULL)
{
dmat_vset(1, 0.0, v);
dmat_vset(n, 0.0, w);
dmat_vset(n, 1.0, u);
dmat_vset(n+n+1, 0, dx);
t = min(max(1.0, 1.0 / lambda), 2.0 * n / ABSTOL);
}
else
{
dmat_vcopy(n+n+1, initial_x, x);
dmat_vset(n+n+1, 0, dx);
t = *initial_t;
}
set_adata(&adata, matX1, ac, ar, b, h, d1, d2);
set_mdata(&mdata, m, n, precond);
/* select printing function and format according to
verbose level and method type (pcg/direct) */
if (to.verbose_level>=2) init_progress((matX1->nz >= 0), to.verbose_level,
format_buf, &print_progress);
/*** MAIN LOOP ************************************************************/
for (ntiter = 0; ntiter < MAX_NT_ITER; ntiter++)
{
/*
* Sets v as the optimal value of the intercept.
*/
dmat_yAmpqx(matX1, ac, ar, w, Aw);
optimize_intercept(v, z, expz, expmz, tm1, b, Aw, m);
/*
* Constructs dual feasible point nu.
*/
fprimes(m, expz, expmz, g, h);
/* partially computes the gradient of phi.
the rest part of the gradient will be completed while computing
the search direction. */
gv[0] = dmat_dot(m, b, g); /* gv = b'*g */
dmat_yAmpqTx(matX1, ac, ar, g, gw); /* gw = A'*g */
dmat_waxpby(m, -1, g, 0, NULL, tm1); /* nu = -g */
maxAnu = dmat_norminf(n, gw); /* max(A'*nu) */
if (maxAnu > lambda)
dmat_waxpby(m, lambda / maxAnu, tm1, 0.0, NULL, tm1);
/*
* Evaluates duality gap.
*/
pobj = logistic_loss2(m,z,expz,expmz)/m + lambda*dmat_norm1(n,w);
dobj = max(nentropy(m, tm1) / m, dobj);
gap = pobj - dobj;
#if INTERNAL_PLOT
internal_plot->val[0*MAX_NT_ITER+ntiter] = (double)ntiter;
internal_plot->val[1*MAX_NT_ITER+ntiter] = (double)pcgiter;
internal_plot->val[2*MAX_NT_ITER+ntiter] = gap;
#endif
if (to.verbose_level>=2)
{
(*print_progress)(format_buf, ntiter, gap, pobj, dobj, s, t,
pcgstat.flag, pcgstat.relres, pcgstat.iter);
}
/*
* Quits if gap < tolerance.
*/
if (gap < to.tolerance ) /***********************************************/
{
if (sol != NULL)
{
/* trim solution */
int i;
double lambda_threshold;
lambda_threshold = to.ktolerance*lambda;
sol[0] = x[0];
for (i = 0; i < n; i++)
{
sol[i+1] = (fabs(gw[i])>lambda_threshold)? x[i+1] : 0.0;
}
/* if standardized, sol = coeff/std */
if (to.sflag == TRUE && to.cflag == FALSE)
{
dmat_elemdivi(n, sol+1, std_x, sol+1);
sol[0] -= dmat_dot(n, avg_x, sol+1);
}
}
if (initial_x != NULL)
{
dmat_vcopy(n+n+1, x, initial_x);
*initial_t = t;
}
if (total_pcgiter) *total_pcgiter = pcgiter;
if (total_ntiter ) *total_ntiter = ntiter;
/* free memory */
free_variables(&vars);
free_temporaries(tm1, tn1, tn2, tn3, tn4, tx1, precond, B, BB);
free_problem_data(&prob);
#if INTERNAL_PLOT
write_mm_matrix("internal_plot",internal_plot,"",TYPE_G);
#endif
return STATUS_SOLUTION_FOUND;
} /********************************************************************/
/*
* Updates t
*/
if (s >= 0.5)
{
t = max(min(2.0 * n * MU / gap, MU * t), t);
}
else if (s < 1e-5)
{
t = 1.1*t;
}
/*
* Computes search direction.
*/
if (matX1->nz >= 0)
{
/* pcg */
compute_searchdir_pcg(&prob, &vars, t, s, gap, &pcgstat, &adata,
&mdata, precond, tm1, tn1, tx1);
pcgiter += pcgstat.iter;
}
else
{
/* direct */
if (n > m)
{
/* direct method for n > m, SMW */
compute_searchdir_chol_fat(&prob, &vars, t, B, BB,
tm1, tn1, tn2, tn3, tn4);
}
else
{
/* direct method for n <= m */
compute_searchdir_chol_thin(&prob, &vars, t, B, BB,
tm1, tn1, tn2);
}
}
/*
* Backtracking linesearch & update x = (v,w,u) and z.
*/
s = backtracking_linesearch(&prob, &vars, t, tm1, tx1);
if (s < 0) break; /* BLS error */
}
/*** END OF MAIN LOOP *****************************************************/
/* Abnormal termination */
if (s < 0)
{
status = STATUS_MAX_LS_ITER_EXCEEDED;
}
else /* if (ntiter == MAX_NT_ITER) */
{
status = STATUS_MAX_NT_ITER_EXCEEDED;
}
if (sol != NULL)
{
/* trim solution */
int i;
double lambda_threshold;
lambda_threshold = to.ktolerance*lambda;
sol[0] = x[0];
for (i = 0; i < n; i++)
{
sol[i+1] = (fabs(gw[i])>lambda_threshold)? x[i+1] : 0.0;
}
/* if standardized, sol = coeff/std */
if (to.sflag == TRUE && to.cflag == FALSE)
{
dmat_elemdivi(n, sol+1, std_x, sol+1);
sol[0] -= dmat_dot(n, avg_x, sol+1);
}
}
if (initial_x != NULL)
{
dmat_vcopy(n+n+1, x, initial_x);
*initial_t = t;
}
if (total_pcgiter) *total_pcgiter = pcgiter;
if (total_ntiter ) *total_ntiter = ntiter;
/* free memory */
free_variables(&vars);
free_temporaries(tm1, tn1, tn2, tn3, tn4, tx1, precond, B, BB);
free_problem_data(&prob);
#if INTERNAL_PLOT
write_mm_matrix("internal_plot",internal_plot,"",TYPE_G);
#endif
return status;
}