int main()
{
int n,m,ji,f,g;
int i,cas,ans;
yu();
scanf("%d",&cas);
for(i=0;i<cas;i++)
{
ji=0;
if(0 != i)
printf("\n");
while(scanf("%d%d",&n,&m),0 != n+m)
{
ji++;
ans=0;
for(f=1;f<n;f++)
{
for(g=f+1;g<n;g++)
{
if(0 == (add[f][g]+m)%muti[f][g])
ans++;
}
}
printf("Case %d: %d\n",ji,ans);
}
}
return 0;
}
int main()
{
int f,i;
while(scanf("%d",&nn)!=EOF)
{
group=nn;
n=2*group;
for(i=1;i<=nn;i++)
{
for(f=1;f<=nn;f++)
{
scanf("%d",&b[i][f]);
}
}
if(0 == pan())
{
printf("NO\n");
continue;
}
for(now=1;now<=31;now++)
{
chu();
for(i=1;i<=nn;i++)
{
for(f=i+1;f<=nn;f++)
{
if(i == f)
{
continue;
}
else if((i%2)==0 && (f%2)==0)
{
huo(i,f);
}
else if((i%2)==1 && (f%2)==1)
{
yu(i,f);
}
else
{
yihuo(i,f);
}
}
}
slove();
if(0 == check())
{
printf("NO\n");
break;
}
}
if(32 == now)
{
printf("YES\n");
}
}
return 0;
}
int main()
{
int s,t;
int u,v;
int i,f,cas;
scanf("%d",&cas);
for(i=0;i<cas;i++)
{
scanf("%d%d",&n,&d);
init();
for(f=0;f<n;f++)
scanf("%d",hei+f);
yu();
for(f=0;f<n-1;f++)
add(f+1,f,-1);
for(f=0;f<n-1;f++)
{
u=tem[f].id;
v=tem[f+1].id;
if(u < v)
add(u,v,d);
else
add(v,u,d);
}
if(tem[0].id < tem[n-1].id)
s=tem[0].id,t=tem[n-1].id;
else
s=tem[n-1].id,t=tem[0].id;
spfa(s);
printf("Case %d: %d\n",i+1,1==cycle?-1:dis[t]);
}
return 0;
}
sc_signed
bar()
{
sc_signed y(6);
sc_unsigned yu(6);
foo(y, yu);
sc_signed z(10);
sc_unsigned zu(10);
foo(z, zu);
sc_signed x(8);
sc_unsigned xu(8);
foo(x, xu);
return x + y + z;
}
int main()
{
yu();
while(scanf("%s%s",ch1,ch2)!=EOF)
{
if(1 == ex())
break;
chu();
fun();
cal();
print();
}
return 0;
}
void StandardModel<Two_scale>::set(const DoubleVector& y)
{
int i, j, k = 0;
for (i = 1; i <= 3; i++)
for (j = 1; j <= 3; j++) {
k++;
yu(i, j) = y.display(k);
yd(i, j) = y.display(k + 9);
ye(i, j) = y.display(k + 18);
}
k = 27;
for (i = 1; i <= 3; i++) {
k++;
g(i) = y.display(k);
}
}
void StandardModel<Two_scale>::setYukawaElement(yukawa k, int i, int j, double f)
{
switch (k) {
case YU:
yu(i, j) = f;
break;
case YD:
yd(i, j) = f;
break;
case YE:
ye(i, j) = f;
break;
default:
assert(false && "StandardModel<Two_scale>::setYukawaElement called with illegal k");
break;
}
}
int main()
{
int i,f;
while(scanf("%d%d%d%d",&n,&m,&x,&t)!=EOF)
{
chu();
for(i=1;i<=n;i++)
{
for(f=1;f<=m;f++)
{
scanf("%d",&sro[i][f]);
}
}
yu();
printf("%I64d\n",dp());
}
return 0;
}
int main()
{
int i,cas,f;
string ch;
scanf("%d",&cas);
for(i=0;i<cas;i++)
{
scanf("%d",&n);
M=(1<<n)-1;
chu();
for(f=1;f<=n;f++)
{
cin>>ch;
id[f]=ch;
scanf("%d%d",&deadline[f],&tt[f]);
}
yu();
spfa();
printf("%d\n",dis[M]);
print();
}
return 0;
}
int main(int argc, char *argv[]) {
Teuchos::GlobalMPISession mpiSession(&argc, &argv);
// This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
int iprint = argc - 1;
Teuchos::RCP<std::ostream> outStream;
Teuchos::oblackholestream bhs; // outputs nothing
if (iprint > 0)
outStream = Teuchos::rcp(&std::cout, false);
else
outStream = Teuchos::rcp(&bhs, false);
int errorFlag = 0;
// *** Example body.
try {
std::string filename = "input.xml";
Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp( new Teuchos::ParameterList() );
Teuchos::updateParametersFromXmlFile( filename, parlist.ptr() );
RealT V_th = parlist->get("Thermal Voltage", 0.02585);
RealT lo_Vsrc = parlist->get("Source Voltage Lower Bound", 0.0);
RealT up_Vsrc = parlist->get("Source Voltage Upper Bound", 1.0);
RealT step_Vsrc = parlist->get("Source Voltage Step", 1.e-2);
RealT true_Is = parlist->get("True Saturation Current", 1.e-12);
RealT true_Rs = parlist->get("True Saturation Resistance", 0.25);
RealT init_Is = parlist->get("Initial Saturation Current", 1.e-12);
RealT init_Rs = parlist->get("Initial Saturation Resistance", 0.25);
RealT lo_Is = parlist->get("Saturation Current Lower Bound", 1.e-16);
RealT up_Is = parlist->get("Saturation Current Upper Bound", 1.e-1);
RealT lo_Rs = parlist->get("Saturation Resistance Lower Bound", 1.e-2);
RealT up_Rs = parlist->get("Saturation Resistance Upper Bound", 30.0);
// bool use_lambertw = parlist->get("Use Analytical Solution",true);
bool use_scale = parlist->get("Use Scaling For Epsilon-Active Sets",true);
bool use_sqp = parlist->get("Use SQP", true);
// bool use_linesearch = parlist->get("Use Line Search", true);
// bool datatype = parlist->get("Get Data From Input File",false);
// bool use_adjoint = parlist->get("Use Adjoint Gradient Computation",false);
// int use_hessvec = parlist->get("Use Hessian-Vector Implementation",1); // 0 - FD, 1 - exact, 2 - GN
// bool plot = parlist->get("Generate Plot Data",false);
// RealT noise = parlist->get("Measurement Noise",0.0);
EqualityConstraint_DiodeCircuit<RealT> con(V_th,lo_Vsrc,up_Vsrc,step_Vsrc);
RealT alpha = 1.e-4; // regularization parameter (unused)
int ns = 101; // number of Vsrc components
int nz = 2; // number of optimization variables
Objective_DiodeCircuit<RealT> obj(alpha,ns,nz);
// Initialize iteration vectors.
Teuchos::RCP<std::vector<RealT> > z_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) );
Teuchos::RCP<std::vector<RealT> > yz_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) );
Teuchos::RCP<std::vector<RealT> > soln_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) );
(*z_rcp)[0] = init_Is;
(*z_rcp)[1] = init_Rs;
(*yz_rcp)[0] = init_Is;
(*yz_rcp)[1] = init_Rs;
(*soln_rcp)[0] = true_Is;
(*soln_rcp)[1] = true_Rs;
ROL::StdVector<RealT> z(z_rcp);
ROL::StdVector<RealT> yz(yz_rcp);
ROL::StdVector<RealT> soln(soln_rcp);
Teuchos::RCP<ROL::Vector<RealT> > zp = Teuchos::rcp(&z,false);
Teuchos::RCP<ROL::Vector<RealT> > yzp = Teuchos::rcp(&yz,false);
Teuchos::RCP<std::vector<RealT> > u_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) );
Teuchos::RCP<std::vector<RealT> > yu_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) );
std::ifstream input_file("measurements.dat");
RealT temp, temp_scale;
for (int i=0; i<ns; i++) {
input_file >> temp;
input_file >> temp;
temp_scale = pow(10,int(log10(temp)));
(*u_rcp)[i] = temp_scale*(RealT)rand()/(RealT)RAND_MAX;
(*yu_rcp)[i] = temp_scale*(RealT)rand()/(RealT)RAND_MAX;
}
input_file.close();
ROL::StdVector<RealT> u(u_rcp);
ROL::StdVector<RealT> yu(yu_rcp);
Teuchos::RCP<ROL::Vector<RealT> > up = Teuchos::rcp(&u,false);
Teuchos::RCP<ROL::Vector<RealT> > yup = Teuchos::rcp(&yu,false);
Teuchos::RCP<std::vector<RealT> > jv_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 1.0) );
ROL::StdVector<RealT> jv(jv_rcp);
Teuchos::RCP<ROL::Vector<RealT> > jvp = Teuchos::rcp(&jv,false);
ROL::Vector_SimOpt<RealT> x(up,zp);
ROL::Vector_SimOpt<RealT> y(yup,yzp);
// Check derivatives
obj.checkGradient(x,x,y,true,*outStream);
obj.checkHessVec(x,x,y,true,*outStream);
con.checkApplyJacobian(x,y,jv,true,*outStream);
con.checkApplyAdjointJacobian(x,yu,jv,x,true,*outStream);
con.checkApplyAdjointHessian(x,yu,y,x,true,*outStream);
// Check consistency of Jacobians and adjoint Jacobians.
con.checkAdjointConsistencyJacobian_1(jv,yu,u,z,true,*outStream);
con.checkAdjointConsistencyJacobian_2(jv,yz,u,z,true,*outStream);
// Check consistency of solves.
con.checkSolve(u,z,jv,true,*outStream);
con.checkInverseJacobian_1(jv,yu,u,z,true,*outStream);
con.checkInverseAdjointJacobian_1(yu,jv,u,z,true,*outStream);
// Initialize reduced objective function.
Teuchos::RCP<std::vector<RealT> > p_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) );
ROL::StdVector<RealT> p(p_rcp);
Teuchos::RCP<ROL::Vector<RealT> > pp = Teuchos::rcp(&p,false);
Teuchos::RCP<ROL::Objective_SimOpt<RealT> > pobj = Teuchos::rcp(&obj,false);
Teuchos::RCP<ROL::EqualityConstraint_SimOpt<RealT> > pcon = Teuchos::rcp(&con,false);
ROL::Reduced_Objective_SimOpt<RealT> robj(pobj,pcon,up,pp);
// Check derivatives.
*outStream << "Derivatives of reduced objective" << std::endl;
robj.checkGradient(z,z,yz,true,*outStream);
robj.checkHessVec(z,z,yz,true,*outStream);
// Bound constraints
RealT tol = 1.e-12;
Teuchos::RCP<std::vector<RealT> > g0_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) );;
ROL::StdVector<RealT> g0p(g0_rcp);
robj.gradient(g0p,z,tol);
*outStream << std::scientific << "Initial gradient = " << (*g0_rcp)[0] << " " << (*g0_rcp)[1] << "\n";
*outStream << std::scientific << "Norm of Gradient = " << g0p.norm() << "\n";
// Define scaling for epsilon-active sets (used in inequality constraints)
RealT scale;
if(use_scale){ scale = 1.0e-2/g0p.norm();}
else{ scale = 1.0;}
*outStream << std::scientific << "Scaling: " << scale << "\n";
/// Define constraints on Is and Rs
BoundConstraint_DiodeCircuit<RealT> bcon(scale,lo_Is,up_Is,lo_Rs,up_Rs);
//bcon.deactivate();
// Optimization
*outStream << "\n Initial guess " << (*z_rcp)[0] << " " << (*z_rcp)[1] << std::endl;
if (!use_sqp){
// Trust Region
ROL::Algorithm<RealT> algo_tr("Trust Region",*parlist);
std::clock_t timer_tr = std::clock();
algo_tr.run(z,robj,bcon,true,*outStream);
*outStream << "\n Solution " << (*z_rcp)[0] << " " << (*z_rcp)[1] << "\n" << std::endl;
*outStream << "Trust-Region required " << (std::clock()-timer_tr)/(RealT)CLOCKS_PER_SEC
<< " seconds.\n";
}
else{
// SQP.
//Teuchos::RCP<std::vector<RealT> > gz_rcp = Teuchos::rcp( new std::vector<RealT> (nz, 0.0) );
//ROL::StdVector<RealT> gz(gz_rcp);
//Teuchos::RCP<ROL::Vector<RealT> > gzp = Teuchos::rcp(&gz,false);
Teuchos::RCP<std::vector<RealT> > gu_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) );
ROL::StdVector<RealT> gu(gu_rcp);
Teuchos::RCP<ROL::Vector<RealT> > gup = Teuchos::rcp(&gu,false);
//ROL::Vector_SimOpt<RealT> g(gup,gzp);
ROL::Vector_SimOpt<RealT> g(gup,zp);
Teuchos::RCP<std::vector<RealT> > c_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) );
Teuchos::RCP<std::vector<RealT> > l_rcp = Teuchos::rcp( new std::vector<RealT> (ns, 0.0) );
ROL::StdVector<RealT> c(c_rcp);
ROL::StdVector<RealT> l(l_rcp);
ROL::Algorithm<RealT> algo_cs("Composite Step",*parlist);
//x.zero();
std::clock_t timer_cs = std::clock();
algo_cs.run(x,g,l,c,obj,con,true,*outStream);
*outStream << "\n Solution " << (*z_rcp)[0] << " " << (*z_rcp)[1] << "\n" << std::endl;
*outStream << "Composite Step required " << (std::clock()-timer_cs)/(RealT)CLOCKS_PER_SEC
<< " seconds.\n";
}
soln.axpy(-1.0, z);
*outStream << "Norm of error: " << soln.norm() << std::endl;
if (soln.norm() > 1e4*ROL::ROL_EPSILON) {
errorFlag = 1;
}
}
catch (std::logic_error err) {
*outStream << err.what() << "\n";
errorFlag = -1000;
}; // end try
if (errorFlag != 0)
std::cout << "End Result: TEST FAILED\n";
else
std::cout << "End Result: TEST PASSED\n";
return 0;
}
void testMat()
{
int k=FreqSys(1,1)/FreqSys(1,2);
//cout<<k<<endl;
math::matrix<double> yu(4,4);
for (int i=0;i<4;i++)
{
yu(0,i)=i+1;
yu(i,0)=i+1;
if (i==1)
{
yu(1,1)=5;yu(1,i+1)=9;yu(1,i+2)=10;
yu(1+i,1)=9;yu(i+2,1)=10;
}
yu(2,2)=22;yu(2,3)=20;
yu(3,2)=20;
yu(3,3)=37;
}
//cout<<yu<<endl;
math::matrix<double> yk(4,4);
math::matrix<double> ol(4,1);
math::matrix<double>* yyy=new math::matrix<double>[2];
for (int i=0;i<4;i++)
{
for (int j=0;j<1;j++)
{
ol(i,j)=(i+1.2)+j*0.2;
}
//math::matrix<double> ols(4,1);
}
yyy[0]=ol;
math::matrix<double>I(2,2);
//cout<<yu<<endl;
//cout<<InsertZeroCol(yu,0,1);
for (int i=0;i<2;i++)
{
I(i,i)=12.0;
}
//cout<<Kronecker(yu,I,2);
}
int main(int argc, char *argv[]) {
Teuchos::GlobalMPISession mpiSession(&argc, &argv);
// This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
int iprint = argc - 1;
Teuchos::RCP<std::ostream> outStream;
Teuchos::oblackholestream bhs; // outputs nothing
if (iprint > 0)
outStream = Teuchos::rcp(&std::cout, false);
else
outStream = Teuchos::rcp(&bhs, false);
int errorFlag = 0;
// *** Example body.
try {
// Initialize full objective function.
int nx = 256; // Set spatial discretization.
RealT alpha = 1.e-3; // Set penalty parameter.
RealT nu = 1e-2; // Viscosity parameter.
Objective_BurgersControl<RealT> obj(alpha,nx);
// Initialize equality constraints
EqualityConstraint_BurgersControl<RealT> con(nx,nu);
Teuchos::ParameterList list;
list.sublist("SimOpt").sublist("Solve").set("Residual Tolerance",1.e2*ROL::ROL_EPSILON);
con.setSolveParameters(list);
// Initialize iteration vectors.
Teuchos::RCP<std::vector<RealT> > z_rcp = Teuchos::rcp( new std::vector<RealT> (nx+2, 1.0) );
Teuchos::RCP<std::vector<RealT> > gz_rcp = Teuchos::rcp( new std::vector<RealT> (nx+2, 1.0) );
Teuchos::RCP<std::vector<RealT> > yz_rcp = Teuchos::rcp( new std::vector<RealT> (nx+2, 1.0) );
for (int i=0; i<nx+2; i++) {
(*z_rcp)[i] = (RealT)rand()/(RealT)RAND_MAX;
(*yz_rcp)[i] = (RealT)rand()/(RealT)RAND_MAX;
}
ROL::StdVector<RealT> z(z_rcp);
ROL::StdVector<RealT> gz(gz_rcp);
ROL::StdVector<RealT> yz(yz_rcp);
Teuchos::RCP<ROL::Vector<RealT> > zp = Teuchos::rcp(&z,false);
Teuchos::RCP<ROL::Vector<RealT> > gzp = Teuchos::rcp(&z,false);
Teuchos::RCP<ROL::Vector<RealT> > yzp = Teuchos::rcp(&yz,false);
Teuchos::RCP<std::vector<RealT> > u_rcp = Teuchos::rcp( new std::vector<RealT> (nx, 1.0) );
Teuchos::RCP<std::vector<RealT> > gu_rcp = Teuchos::rcp( new std::vector<RealT> (nx, 1.0) );
Teuchos::RCP<std::vector<RealT> > yu_rcp = Teuchos::rcp( new std::vector<RealT> (nx, 1.0) );
for (int i=0; i<nx; i++) {
(*u_rcp)[i] = (RealT)rand()/(RealT)RAND_MAX;
(*yu_rcp)[i] = (RealT)rand()/(RealT)RAND_MAX;
}
ROL::StdVector<RealT> u(u_rcp);
ROL::StdVector<RealT> gu(gu_rcp);
ROL::StdVector<RealT> yu(yu_rcp);
Teuchos::RCP<ROL::Vector<RealT> > up = Teuchos::rcp(&u,false);
Teuchos::RCP<ROL::Vector<RealT> > gup = Teuchos::rcp(&u,false);
Teuchos::RCP<ROL::Vector<RealT> > yup = Teuchos::rcp(&yu,false);
Teuchos::RCP<std::vector<RealT> > c_rcp = Teuchos::rcp( new std::vector<RealT> (nx, 1.0) );
Teuchos::RCP<std::vector<RealT> > l_rcp = Teuchos::rcp( new std::vector<RealT> (nx, 1.0) );
ROL::StdVector<RealT> c(c_rcp);
ROL::StdVector<RealT> l(l_rcp);
ROL::Vector_SimOpt<RealT> x(up,zp);
ROL::Vector_SimOpt<RealT> g(gup,gzp);
ROL::Vector_SimOpt<RealT> y(yup,yzp);
// Check derivatives.
obj.checkGradient(x,x,y,true,*outStream);
obj.checkHessVec(x,x,y,true,*outStream);
con.checkApplyJacobian(x,y,c,true,*outStream);
con.checkApplyAdjointJacobian(x,yu,c,x,true,*outStream);
con.checkApplyAdjointHessian(x,yu,y,x,true,*outStream);
// Initialize reduced objective function.
Teuchos::RCP<std::vector<RealT> > p_rcp = Teuchos::rcp( new std::vector<RealT> (nx, 1.0) );
ROL::StdVector<RealT> p(p_rcp);
Teuchos::RCP<ROL::Vector<RealT> > pp = Teuchos::rcp(&p,false);
Teuchos::RCP<ROL::Objective_SimOpt<RealT> > pobj = Teuchos::rcp(&obj,false);
Teuchos::RCP<ROL::EqualityConstraint_SimOpt<RealT> > pcon = Teuchos::rcp(&con,false);
ROL::Reduced_Objective_SimOpt<RealT> robj(pobj,pcon,up,pp);
// Check derivatives.
robj.checkGradient(z,z,yz,true,*outStream);
robj.checkHessVec(z,z,yz,true,*outStream);
// Get parameter list.
std::string filename = "input.xml";
Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp( new Teuchos::ParameterList() );
Teuchos::updateParametersFromXmlFile( filename, parlist.ptr() );
parlist->sublist("Status Test").set("Gradient Tolerance",1.e-14);
parlist->sublist("Status Test").set("Constraint Tolerance",1.e-14);
parlist->sublist("Status Test").set("Step Tolerance",1.e-16);
parlist->sublist("Status Test").set("Iteration Limit",1000);
// Declare ROL algorithm pointer.
Teuchos::RCP<ROL::Algorithm<RealT> > algo;
// Run optimization with Composite Step.
algo = Teuchos::rcp(new ROL::Algorithm<RealT>("Composite Step",*parlist,false));
RealT zerotol = std::sqrt(ROL::ROL_EPSILON);
z.zero();
con.solve(c,u,z,zerotol);
c.zero(); l.zero();
algo->run(x, g, l, c, obj, con, true, *outStream);
Teuchos::RCP<ROL::Vector<RealT> > zCS = z.clone();
zCS->set(z);
// Run Optimization with Trust-Region algorithm.
algo = Teuchos::rcp(new ROL::Algorithm<RealT>("Trust Region",*parlist,false));
z.zero();
algo->run(z,robj,true,*outStream);
// Check solutions.
Teuchos::RCP<ROL::Vector<RealT> > err = z.clone();
err->set(*zCS); err->axpy(-1.,z);
errorFlag += ((err->norm()) > 1.e-8) ? 1 : 0;
}
catch (std::logic_error err) {
*outStream << err.what() << "\n";
errorFlag = -1000;
}; // end try
if (errorFlag != 0)
std::cout << "End Result: TEST FAILED\n";
else
std::cout << "End Result: TEST PASSED\n";
return 0;
}
