double prodai(int k, double a);
double fac(int x);
+// Numerical integration using Simpson's rule
+template<class T>
+double simpson_integrate(const T &evaluator, double from, double to, double step)
+{
+ int n = int((to - from) / step + 0.5);
+ double h = (to - from) / n;
+ double sum = evaluator(from);
+
+ for (int i = 1; i < n; i += 2) {
+ sum += 4.0 * evaluator(from + i * h);
+ }
+ for (int i = 2; i < n; i += 2) {
+ sum += 2.0 * evaluator(from + i * h);
+ }
+ sum += evaluator(to);
+
+ return (h/3.0) * sum;
+}
+
// probability of match ending k-a (k>a) when winnerR - loserR = RD
//
// +inf
// is already divided by 455.
double prob_score_real(int k, double a, double prodai, double kfac, double rd_norm)
{
- double nom = prodai * pow(2.0, -rd_norm * a);
- double denom = kfac * pow(1.0 + pow(2.0, -rd_norm), k+a);
+ double nom = prodai * pow(2.0, rd_norm * a);
+ double denom = kfac * pow(1.0 + pow(2.0, rd_norm), k+a);
return nom/denom;
}
// Set the last parameter to 1.0 if player 1 won, or -1.0 if player 2 won.
// In the latter case, ProbScore will be given (r1-r2) instead of (r2-r1).
//
-static inline double evaluate_int_point(int k, double a, double prodai_precompute, double kfac_precompute, double r1, double mu2, double sigma2, double winfac, double x);
+class ProbScoreEvaluator {
+private:
+ int k;
+ double a;
+ double prodai_precompute, kfac_precompute, r1, mu2, sigma2, winfac;
+
+public:
+ ProbScoreEvaluator(int k, double a, double prodai_precompute, double kfac_precompute, double r1, double mu2, double sigma2, double winfac)
+ : k(k), a(a), prodai_precompute(prodai_precompute), kfac_precompute(kfac_precompute), r1(r1), mu2(mu2), sigma2(sigma2), winfac(winfac) {}
+ inline double operator() (double x) const
+ {
+ double probscore = prob_score_real(k, a, prodai_precompute, kfac_precompute, (x - r1)*winfac);
+ double z = (x - mu2)/sigma2;
+ double gaussian = exp(-(z*z/2.0));
+ return probscore * gaussian;
+ }
+};
double opponent_rating_pdf(int k, double a, double r1, double mu2, double sigma2, double winfac)
{
double kfac_precompute = fac(k-1);
winfac /= rating_constant;
- int n = int(3000.0 / int_step_size + 0.5);
- double h = 3000.0 / double(n);
- double sum = evaluate_int_point(k, a, prodai_precompute, kfac_precompute, r1, mu2, sigma2, winfac, 0.0);
-
- for (int i = 1; i < n; i += 2) {
- sum += 4.0 * evaluate_int_point(k, a, prodai_precompute, kfac_precompute, r1, mu2, sigma2, winfac, i * h);
- }
- for (int i = 2; i < n; i += 2) {
- sum += 2.0 * evaluate_int_point(k, a, prodai_precompute, kfac_precompute, r1, mu2, sigma2, winfac, i * h);
- }
- sum += evaluate_int_point(k, a, prodai_precompute, kfac_precompute, r1, mu2, sigma2, winfac, 3000.0);
-
- return (h/3.0) * sum;
-}
-
-static inline double evaluate_int_point(int k, double a, double prodai_precompute, double kfac_precompute, double r1, double mu2, double sigma2, double winfac, double x)
-{
- double probscore = prob_score_real(k, a, prodai_precompute, kfac_precompute, (r1 - x)*winfac);
- double z = (x - mu2)/sigma2;
- double gaussian = exp(-(z*z/2.0));
- return probscore * gaussian;
+ return simpson_integrate(ProbScoreEvaluator(k, a, prodai_precompute, kfac_precompute, r1, mu2, sigma2, winfac), 0.0, 3000.0, int_step_size);
}
// normalize the curve so we know that A ~= 1
compute_new_rating(mu1, sigma1, mu2, sigma2, k, i, newmu1, newsigma1);
compute_new_rating(mu2, sigma2, mu1, sigma1, i, k, newmu2, newsigma2);
printf("%u-%u,%f,%+f,%+f\n",
- k, i, prob_score(k, i, mu1-mu2), newmu1-mu1, newmu2-mu2);
+ k, i, prob_score(k, i, mu2-mu1), newmu1-mu1, newmu2-mu2);
}
for (int i = k; i --> 0; ) {
double newmu1, newmu2, newsigma1, newsigma2;
compute_new_rating(mu1, sigma1, mu2, sigma2, i, k, newmu1, newsigma1);
compute_new_rating(mu2, sigma2, mu1, sigma1, k, i, newmu2, newsigma2);
printf("%u-%u,%f,%+f,%+f\n",
- i, k, prob_score(k, i, mu2-mu1), newmu1-mu1, newmu2-mu2);
+ i, k, prob_score(k, i, mu1-mu2), newmu1-mu1, newmu2-mu2);
}
}
}