feat: RunningQuality - running SQI

pasada-lib/include/pd_signal.h

@@ -20,7 +20,19 @@ namespace pd_signal {
     void interp(std::vector<double>& y, std::vector<double>& x, std::vector<double>& xp, std::vector<double>& fp);
 
     /** resample to BEAT_LEN */
-    void resample(std::vector<double> &out, std::vector<double> x, int beat_len);
+    void resample(std::vector<double> &out, std::vector<double> &x, int beat_len);
+
+    /**
+     * normalized cross-correlation of the two signals of same length.
+     * normalization factor is <c>1 / sqrt(\sum_i x_i^2 * \sum_i y_i^2)</c>
+     */
+    double crossCorr(std::vector<double> &x, std::vector<double> &y);
+
+    /** clip 'val' to between 'a_min' and 'a_max'. */
+    double clip(double val, double a_min, double a_max);
+
+    /** two-dimensional mean of a collection of signals */
+    void mean(std::vector<double> &out, std::vector<std::vector<double> >& m);
 
 }
 

pasada-lib/pd_signal.cpp

@@ -5,6 +5,7 @@
 #include "include/pd_signal.h"
 #include <stdexcept>
 #include <algorithm>
+#include <iostream>
 
 namespace pd_signal {
 
@@ -86,7 +87,7 @@ void interp(std::vector<double>& y, std::vector<double>& x, std::vector<double>&
 }
 
 // resample to BEAT_LEN
-void resample(std::vector<double> &out, std::vector<double> x, int beat_len) {
+void resample(std::vector<double> &out, std::vector<double> &x, int beat_len) {
     std::vector<double> t;
     std::vector<double> i;
     linspace(t, 0, (double) x.size(), beat_len, false);
@@ -94,4 +95,41 @@ void resample(std::vector<double> &out, std::vector<double> x, int beat_len) {
     interp(out, t, i, x);
 }
 
+// normalized cross-correlation of the two signals of same length
+double crossCorr(std::vector<double> &x, std::vector<double> &y) {
+    if (x.size() != y.size()) throw std::invalid_argument("x.size() != y.size()");
+    double xs = 0.0, ys = 0.0, cs = 0.0;
+    for (size_t i = 0; i < x.size(); i++) {
+        xs += x[i] * x[i];
+        ys += y[i] * y[i];
+        cs += x[i] * y[i];
+    }
+    return cs / sqrt(xs * ys);
+}
+
+// clip 'val' to between 'a_min' and 'a_max'.
+double clip(double val, double a_min, double a_max) {
+    return std::min(std::max(val, a_min), a_max);
+}
+
+// two-dimensional mean of a collection of signals
+void mean(std::vector<double> &out, std::vector<std::vector<double> >& m) {
+    if (m.empty()) {
+        out.resize(0);
+        return;
+    }
+    const size_t sz = m[0].size();
+    out.resize(sz);
+    out.assign(sz, 0.0);
+    const size_t N = m.size();
+    for (size_t i = 0; i < N; i++) {
+        for (size_t j = 0; j < sz; j++) {
+            out[j] += m[i][j];
+        }
+    }
+    for (size_t j = 0; j < sz; j++) {
+        out[j] /= static_cast<double>(N);
+    }
+}
+
 }

pasada-lib/ssf_filter.cpp

@@ -17,7 +17,7 @@ static std::vector<double> make_ones(size_t sw) {
 SsfFilter::SsfFilter(size_t upslope_width) :
     sw(upslope_width),
     // Filt(N, shift, offset, taps)
-    f_delta_u(2, 0, 0, std::vector {1.0, -1.0}),
+    f_delta_u(2, 0, 0, std::vector<double> {1.0, -1.0}),
     f_window(upslope_width, 0, 0, make_ones(upslope_width))
 {}
 double SsfFilter::filter(double val) {