Initial quality measures implementation.

1 files changed, 75 insertions, 0 deletions

diff --git a/measures.cpp b/measures.cpp
new file mode 100644
index 0000000..dff8494
--- /dev/null
+++ b/measures.cpp
@@ -0,0 +1,75 @@
+#include "mp.h"
+
+#include <cassert>
+#include <cmath>
+
+double mp::stress(const arma::mat &Dp, const arma::mat &Dq)
+{
+    assert(Dp.n_rows == Dp.n_cols);
+    assert(Dq.n_rows == Dq.n_cols);
+    assert(Dp.n_rows == Dq.n_rows);
+
+    arma::uword n = Dp.n_rows;
+    double sigma = 0, s = 0;
+    for (arma::uword i = 0; i < n; i++)
+        for (arma::uword j = i + 1; j < n; j++) {
+            double delta = Dp(i, j);
+            double d     = Dq(i, j);
+            sigma += (delta - d) * (delta - d) / delta;
+            s += delta;
+        }
+
+    return sigma / s;
+}
+
+arma::vec mp::klDivergence(const arma::mat &P, const arma::mat &Q)
+{
+    arma::vec diver(P.n_rows);
+    mp::klDivergence(P, Q, diver);
+    return diver;
+}
+
+void mp::klDivergence(const arma::mat &P, const arma::mat &Q, arma::vec diver)
+{
+    assert(P.n_rows == P.n_cols);
+    assert(Q.n_rows == Q.n_cols);
+    assert(P.n_rows == Q.n_cols);
+    assert(diver.n_elem == P.n_rows);
+
+    arma::uword n = P.n_rows;
+    for (arma::uword i = 0; i < n; i++)
+        diver(i) = klDivergence(P.row(i), Q.row(i));
+}
+
+double mp::klDivergence(const arma::rowvec &pi, const arma::rowvec &qi)
+{
+    return arma::accu(removeJ % (pi % arma::log(pi / qi)));
+}
+
+arma::mat mp::d2p(const arma::mat &D, const arma::vec &sigmas)
+{
+    arma::mat P(D.n_rows, D.n_cols);
+    mp::relevance(D, sigmas, P);
+    return P;
+}
+
+void mp::d2p(const arma::mat &D, const arma::vec &sigmas, arma::mat &P)
+{
+    /*
+     * WARNING: assumes D and sigmas are already squared
+     */
+
+    assert(D.n_rows == D.n_cols);
+    assert(P.n_rows == P.n_cols);
+    assert(D.n_rows == P.n_rows);
+
+    arma::uword n = D.n_rows;
+    for (arma::uword i = 0; i < n; i++) {
+        double den = -1; // k == i must be skipped
+        for (arma::uword k = 0; k < n; k++)
+            den += exp(-D(i, k) / sigmas(i));
+
+        for (arma::uword j = 0; j < n; j++)
+            P(i, j) = exp(-D(i, j) / sigmas(i)) / den;
+    }
+}
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