/** Plot reads identified versus index
*
* @ingroup plot_logic
* @param metrics run metrics
* @param lane lane number
* @param data output plot data
*/
void plot_sample_qc(const model::metrics::run_metrics& metrics,
const size_t lane,
model::plot::plot_data<model::plot::bar_point>& data)
throw(model::index_out_of_bounds_exception)
{
typedef model::plot::series<model::plot::bar_point> bar_series_t;
data.set_xlabel("Index Number");
data.set_ylabel("% Reads Identified (PF)");
data.assign(1, bar_series_t("% reads", "Green", bar_series_t::Bar));
data[0].add_option(constants::to_string(constants::Centered));
if(metrics.get_set<model::metrics::index_metric>().size() == 0)
{
if(metrics.run_info().is_indexed())
{
data.set_range(data.x_axis().min(),
1,
data.y_axis().min(),
5);
}
//data.clear(); // TODO: Remove below and uncomment this line
return;
}
const float max_height = populate_reads_identified(metrics.get_set<model::metrics::index_metric>(),
metrics.get_set<model::metrics::tile_metric>(),
lane,
data[0]);
auto_scale(data);
data.set_range(data.x_axis().min(),
static_cast<float>(data[0].size()+1),
data.y_axis().min(),
roundf(max_height+5));
}
void zoom_to_extents(void)
{
tool_dehover();
center(NULL);
auto_scale(NULL);
redraw();
tool_hover(canvas_to_coord(curr_pos.x, curr_pos.y));
}
void zoom_to_frame(void)
{
tool_dehover();
center(&active_frame_bbox);
auto_scale(&active_frame_bbox);
redraw();
tool_hover(canvas_to_coord(curr_pos.x, curr_pos.y));
}
/* Automatic scaling of the problem */
double __declspec(dllexport) WINAPI _auto_scale(lprec *lp)
{
double ret;
if (lp != NULL) {
freebuferror();
ret = auto_scale(lp);
}
else
ret = 0.0;
return(ret);
}
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);
}
main(int argc, char **argv)
#endif
{
char *stub;
ASL *asl;
FILE *nl;
lprec *lp;
ograd *og;
int ct, i, intmin, *is, j, j0, j1, k, nalt, rc;
short *basis, *lower;
real *LU, *c, lb, objadj, *rshift, *shift, t, ub, *x, *x0, *x1;
char buf[256];
typedef struct { char *msg; int code; } Sol_info;
static Sol_info solinfo[] = {
{ "optimal", 0 },
{ "integer programming failure", 502 },
{ "infeasible", 200 },
{ "unbounded", 300 },
{ "failure", 501 },
{ "bug", 500 }
};
sprintf(lp_solve_version+9, "%.*s", (int)sizeof(lp_solve_version)-10,
PATCHLEVEL);
sprintf(lp_solve_vversion, "%s, driver(20001002)", lp_solve_version);
asl = ASL_alloc(ASL_read_f);
stub = getstub(&argv, &Oinfo);
nl = jac0dim(stub, (fint)strlen(stub));
suf_declare(suftab, sizeof(suftab)/sizeof(SufDecl));
/* set A_vals to get the constraints column-wise */
A_vals = (real *)M1alloc(nzc*sizeof(real));
f_read(nl,0);
lp = make_lp(n_con, 0);
Oinfo.uinfo = (char *)lp;
if (getopts(argv, &Oinfo))
return 1;
i = n_var + n_con + 1;
x = (real*)M1alloc(i*sizeof(real)); /* scratch vector */
memset(x, 0, i*sizeof(real));
x0 = x++;
c = x + n_con;
/* supply objective */
objadj = 0;
if (--nobj >= 0 && nobj < n_obj) {
for(og = Ograd[nobj]; og; og = og->next)
c[og->varno] = og->coef;
if (objtype[nobj])
set_maxim(lp);
objadj = objconst(nobj);
}
/* supply columns and variable bounds */
LU = LUv;
intmin = n_var - (nbv + niv);
j1 = nalt = 0;
rshift = shift = 0;
for(i = 1; i <= n_var; i++, LU += 2) {
lb = LU[0];
ub = LU[1];
j0 = j1;
j1 = A_colstarts[i];
*x0 = *c++; /* cost coefficient */
if (lb <= negInfinity && ub < Infinity) {
/* negate this variable */
nalt++;
lb = -ub;
ub = -LU[0];
for(j = j0; j < j1; j++)
x[A_rownos[j]] = -A_vals[j];
*x0 = -*x0;
add_column(lp, x0);
if (lb)
goto shift_check;
}
else {
for(j = j0; j < j1; j++)
x[A_rownos[j]] = A_vals[j];
add_column(lp, x0);
if (lb <= negInfinity) {
nalt++;
if (i > intmin)
set_int(lp, lp->columns, TRUE);
/* split free variable */
*x0 = -*x0;
for(j = j0; j < j1; j++)
x[A_rownos[j]] *= -1.;
add_column(lp,x0);
}
else if (lb) {
shift_check:
if (lb > 0)
set_lowbo(lp, lp->columns, lb);
else {
if (!rshift) {
rshift = (real*)M1zapalloc(
(n_var+n_con)*sizeof(real));
shift = rshift + n_con - 1;
}
shift[i] = lb;
for(j = j0; j < j1; j++) {
k = A_rownos[j];
rshift[k] += lb*x[k];
}
if (ub < Infinity)
ub -= lb;
objadj += lb**x0;
}
}
if (ub < Infinity)
set_upbo(lp, lp->columns, ub);
}
for(j = j0; j < j1; j++)
x[A_rownos[j]] = 0;
if (i > intmin)
set_int(lp, lp->columns, TRUE);
}
if (objadj) {
/* add a fixed variable to adjust the objective value */
*x0 = objadj;
add_column(lp, x0);
set_lowbo(lp, i, 1.);
set_upbo(lp, i, 1.);
}
/* supply constraint rhs */
LU = LUrhs;
for(i = 1; i <= n_con; i++, LU += 2) {
t = LU[0];
if (t == LU[1])
ct = EQ;
else if (t <= negInfinity) {
t = LU[1];
if (t >= Infinity) {
/* This is possible only with effort: */
/* one must turn presolve off and */
/* explicitly specify a constraint */
/* with infinite bounds. */
fprintf(Stderr,
"Sorry, can't handle free rows.\n");
exit(1);
}
ct = LE;
}
else
ct = GE;
set_constr_type(lp, i, ct);
set_rh(lp, i, rshift ? t - *rshift++ : t);
if (ct == GE && LU[1] < Infinity)
lp->orig_upbo[i] = LU[1] - t;
}
if (prlp)
print_lp(lp);
if (scaling)
auto_scale(lp);
/* Unfortunately, there seems to be no way to suggest */
/* a starting basis to lp_solve; thus we must ignore */
/* any incoming .sstatus values. */
rc = solve(lp);
if (rc < 0 || rc > 5)
rc = 5;
solve_result_num = solinfo[rc].code;
i = sprintf(buf, "%s: %s", Oinfo.bsname, solinfo[rc].msg);
if (rc == OPTIMAL)
i += sprintf(buf+i, ", objective %.*g", obj_prec(),
lp->best_solution[0]);
i += sprintf(buf+i,"\n%d simplex iterations", lp->total_iter);
if (lp->max_level > 1 || lp->total_nodes > 1)
sprintf(buf+i, "\n%d branch & bound nodes: depth %d",
lp->total_nodes, lp->max_level);
/* Prepare to report solution: deal with split free variables. */
x1 = lp->best_solution+lp->rows+1;
if (nalt || shift) {
x = x0;
LU = LUv;
for(i = 0; i < n_var; i++, LU += 2) {
if (LU[0] > negInfinity)
x[i] = *x1++;
else if (LU[1] < Infinity)
x[i] = -*x1++;
else {
x[i] = x1[0] - x1[1];
x1 += 2;
}
if (shift)
x[i] += *++shift;
}
}
else
x = x1;
if (solinfo[rc].code < 500 && !(nbv + niv)) {
/* return .sstatus values */
basis = lp->basis;
lower = lp->lower;
is = M1alloc((n_var + n_con)*sizeof(int));
suf_iput("sstatus", ASL_Sufkind_con, is);
for(i = 0; i < n_con; i++) {
j = *++lower;
*is++ = *++basis ? 1 : j ? 3 : 4;
}
suf_iput("sstatus", ASL_Sufkind_var, is);
LU = LUv;
for(i = 0; i < n_var; i++, LU += 2) {
j0 = *++basis;
j1 = *++lower;
if (LU[0] > negInfinity)
j = j0 ? 1 : j1 ? 3 : 4;
else if (LU[1] < Infinity)
j = j0 ? 1 : j1 ? 4 : 3;
else {
++lower;
j = *++basis || j0;
}
*is++ = j;
}
}
write_sol(buf, x, lp->duals+1, &Oinfo);
/* The following calls would only be needed */
/* if execution were to continue... */
delete_lp(lp);
ASL_free(&asl);
return 0;
}
void init_canvas(void)
{
center(NULL);
auto_scale(NULL);
}
