int
trapped(int n, int inc)
{
int i, j, k;
int c, l, ct;
ct = 0;
l = n + 7 * inc;
for (i = n + inc; i != l; i += inc) {
odds(0, 0, 0);
c = abs(i - l);
if (board[i] * inc > 0) {
for (j = c; j < 13; j++)
if (board[i + inc * j] * inc < -1) {
if (j < 7)
odds(j, 0, 1);
for (k = 1; k < 7 && k < j; k++)
if (j - k < 7)
odds(k, j - k, 1);
}
ct += abs(board[i]) * (36 - count());
}
}
return (ct / 5);
}
int
freemen(int b)
{
int i, inc, lim;
odds(0, 0, 0);
if (board[b] == 0)
return (0);
inc = (b == 0 ? 1 : -1);
lim = (b == 0 ? 7 : 18);
for (i = b + inc; i != lim; i += inc)
if (board[i] * inc < -1)
odds(abs(b - i), 0, abs(board[b]));
if (abs(board[b]) == 1)
return ((36 - count()) / 5);
return (count() / 5);
}
int main() {
int cards[3];
while(scanf("%d %d %d", cards, cards+1, cards+2) == 3) {
if(DEBUG)
printf("%d %d %d\n", cards[0], cards[1], cards[2]);
if(odds(cards) < 0.50) {
printf("NO\n");
} else {
printf("YES\n");
}
}
return 0;
}
double log_odds(const valarray<bool>& v) {
return log(odds(v));
}
extern "C" void glm_gibbs(double * rZ, double * rxo, double * rlam, int * rmodelprior, double * rpriorprob, double * rbeta1, double * rbeta2, int * rburnin, int * rniter, int * rscalemixture, double * ralpha, int * rno, int * rna, int * rp, double * B_mcmc, double * prob_mcmc, int * gamma_mcmc, double * phi_mcmc, double * lam_mcmc, double * B_rb, double * prob_rb, double * intercept_mcmc, double * xo_scale)
{
GetRNGstate();
//MCMC Variables//
int burnin=*rburnin;
int niter=*rniter;
//Dimensions//
int p=*rp;
int no=*rno;
int na=*rna;
//Phi Variables//
double phi=1.0;
//Yo Variables//
std::vector<double> Z(rZ, rZ+no);
std::vector<double> xo(rxo, rxo+no*p);
standardize_xo(xo,xo_scale,no,p);
std::vector<double> xoyo(p);
double yobar=0;
std::vector<double> xoxo(p*p);
dgemm_( &transT, &transN, &p, &p, &no, &unity, &*xo.begin(), &no, &*xo.begin(), &no, &inputscale0, &*xoxo.begin(), &p );
//Construct Xa//
std::vector<double> xa(p*(p+1)/2); //Triangular Packed Storage
std::vector<double> d(p);
chol_xa(xa,xoxo,d,p);
//Reserve Memory for Submatrices//
std::vector<double> xog; xog.reserve(no*p);
std::vector<double> xogyo; xogyo.reserve(p);
std::vector<double> xogxog_Lamg; xogxog_Lamg.reserve(p*p);
std::vector<double> xag; xag.reserve(na*p);
//Ya Variables//
std::vector<double> xaya(p);
//Beta Variables//
double intercept=0;
std::vector<double> Bols(p);
std::vector<double> B(p,0.0);
std::vector<double> Bg; Bg.reserve(p);
//Lambda Variables//
int scalemixture=*rscalemixture;
double alpha=*ralpha;
std::vector<double> lam(rlam,rlam+p);
std::vector<double> lamg; lamg.reserve(p); //vector instead of diagonal pxp matrix
//Gamma Variables//
std::vector<int> gamma(p,1);
int p_gamma=std::accumulate(gamma.begin(),gamma.end(),0);
bool gamma_diff=true;
int modelprior=*rmodelprior;
//Probability Variables//
std::vector<double> prob(p);
std::vector<double> odds(p);
std::vector<double> priorprob(rpriorprob,rpriorprob+p);
//Theta Variables//
double theta=0.5;
double beta1=*rbeta1;
double beta2=*rbeta2;
//Store Initial Values//
std::copy(B.begin(),B.end(),B_mcmc);
std::copy(prob.begin(),prob.end(),prob_mcmc);
std::copy(gamma.begin(),gamma.end(),gamma_mcmc);
std::copy(lam.begin(),lam.end(),lam_mcmc);
//Run Gibbs Sampler//
for (int t = 1; t < niter; ++t)
{
//Form Submatrices//
if(p_gamma) submatrices_uncollapsed(gamma_diff,B,xog,xag,lamg,Bg,gamma,lam,xo,xa,p_gamma,p,no,na);
//Draw xoyo//
draw_xoyo(Z,xoyo,yobar,xo,xog,Bg,phi,no,p,p_gamma,intercept);
//Draw xaya//
draw_uncollapsed_xaya(xaya,xa,xag,Bg,phi,na,p,p_gamma);
//Compute Probabilities//
if(modelprior==1)
{
bernoulli_probabilities(prob,odds,Bols,d,xoyo,xaya,priorprob,lam,phi);
}else if(modelprior==2)
{
betabinomial_probabilities(prob,odds,Bols,d,xoyo,xaya,theta,lam,phi);
}else
{
uniform_probabilities(prob,odds,Bols,d,xoyo,xaya,lam,phi);
}
//Draw Gamma//
draw_gamma(gamma,p_gamma,prob);
//Draw Theta//
if(modelprior==2) theta=Rf_rbeta(beta1+p_gamma,p-p_gamma+beta2);
//Draw Beta//
draw_beta(gamma,B,Bols,d,lam,phi);
//Draw Intercept//
intercept=yobar+sqrt(1/(no*phi))*Rf_rnorm(0,1);
//Draw Lambda//
if(scalemixture) draw_lambda_t(lam,gamma,alpha,B,phi);
//Store Draws//
intercept_mcmc[t]=intercept;
std::copy(gamma.begin(),gamma.end(),(gamma_mcmc+p*t));
std::copy(prob.begin(),prob.end(),(prob_mcmc+p*t));
std::copy(B.begin(),B.end(),(B_mcmc+p*t));
std::copy(lam.begin(),lam.end(),(lam_mcmc+p*t));
//Rao Blackwell//
if(t>=burnin) rao_blackwell(B_rb,prob_rb,B,prob,burnin,niter);
//Has Gamma Changed?//
gamma_diff=gamma_change(gamma_mcmc,t,p);
}
PutRNGstate();
}
