diff base/ColumnOp.h @ 1206:659372323b45 tony-2.0-integration

Merge latest SV 3.0 branch code

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/base/ColumnOp.h	Fri Aug 19 15:58:57 2016 +0100
@@ -0,0 +1,216 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
+
+/*
+    Sonic Visualiser
+    An audio file viewer and annotation editor.
+    Centre for Digital Music, Queen Mary, University of London.
+    This file copyright 2006-2016 Chris Cannam and QMUL.
+    
+    This program is free software; you can redistribute it and/or
+    modify it under the terms of the GNU General Public License as
+    published by the Free Software Foundation; either version 2 of the
+    License, or (at your option) any later version.  See the file
+    COPYING included with this distribution for more information.
+*/
+
+#ifndef COLUMN_OP_H
+#define COLUMN_OP_H
+
+#include "BaseTypes.h"
+
+#include <cmath>
+
+/**
+ * Display normalization types for columns in e.g. grid plots.
+ *
+ * Max1 means to normalize to max value = 1.0.
+ * Sum1 means to normalize to sum of values = 1.0.
+ *
+ * Hybrid means normalize to max = 1.0 and then multiply by
+ * log10 of the max value, to retain some difference between
+ * levels of neighbouring columns.
+ *
+ * Area normalization is handled separately.
+ */
+enum class ColumnNormalization {
+    None,
+    Max1,
+    Sum1,
+    Hybrid
+};
+
+/**
+ * Class containing static functions for simple operations on data
+ * columns, for use by display layers.
+ */
+class ColumnOp
+{
+public:
+    /** 
+     * Column type. 
+     */
+    typedef std::vector<float> Column;
+
+    /**
+     * Scale the given column using the given gain multiplier.
+     */
+    static Column applyGain(const Column &in, double gain) {
+	
+	if (gain == 1.0) {
+	    return in;
+	}
+	Column out;
+	out.reserve(in.size());
+	for (auto v: in) {
+	    out.push_back(float(v * gain));
+	}
+	return out;
+    }
+
+    /**
+     * Scale an FFT output by half the FFT size.
+     */
+    static Column fftScale(const Column &in, int fftSize) {
+        return applyGain(in, 2.0 / fftSize);
+    }
+
+    /**
+     * Determine whether an index points to a local peak.
+     */
+    static bool isPeak(const Column &in, int ix) {
+	
+	if (!in_range_for(in, ix-1)) return false;
+	if (!in_range_for(in, ix+1)) return false;
+	if (in[ix] < in[ix+1]) return false;
+	if (in[ix] < in[ix-1]) return false;
+	
+	return true;
+    }
+
+    /**
+     * Return a column containing only the local peak values (all
+     * others zero).
+     */
+    static Column peakPick(const Column &in) {
+	
+	std::vector<float> out(in.size(), 0.f);
+	for (int i = 0; in_range_for(in, i); ++i) {
+	    if (isPeak(in, i)) {
+		out[i] = in[i];
+	    }
+	}
+	
+	return out;
+    }
+
+    /**
+     * Return a column normalized from the input column according to
+     * the given normalization scheme.
+     */
+    static Column normalize(const Column &in, ColumnNormalization n) {
+
+	if (n == ColumnNormalization::None) {
+	    return in;
+	}
+
+        float scale = 1.f;
+        
+        if (n == ColumnNormalization::Sum1) {
+
+            float sum = 0.f;
+
+            for (auto v: in) {
+                sum += v;
+            }
+
+            if (sum != 0.f) {
+                scale = 1.f / sum;
+            }
+        } else {
+        
+            float max = *max_element(in.begin(), in.end());
+
+            if (n == ColumnNormalization::Max1) {
+                if (max != 0.f) {
+                    scale = 1.f / max;
+                }
+            } else if (n == ColumnNormalization::Hybrid) {
+                if (max > 0.f) {
+                    scale = log10f(max + 1.f) / max;
+                }
+            }
+        }
+
+        return applyGain(in, scale);
+    }
+
+    /**
+     * Distribute the given column into a target vector of a different
+     * size, optionally using linear interpolation. The binfory vector
+     * contains a mapping from y coordinate (i.e. index into the
+     * target vector) to bin (i.e. index into the source column).
+     */
+    static Column distribute(const Column &in,
+			     int h,
+			     const std::vector<double> &binfory,
+			     int minbin,
+			     bool interpolate) {
+
+	std::vector<float> out(h, 0.f);
+	int bins = int(in.size());
+
+	for (int y = 0; y < h; ++y) {
+        
+	    double sy0 = binfory[y] - minbin;
+	    double sy1 = sy0 + 1;
+	    if (y+1 < h) {
+		sy1 = binfory[y+1] - minbin;
+	    }
+        
+	    if (interpolate && fabs(sy1 - sy0) < 1.0) {
+            
+		double centre = (sy0 + sy1) / 2;
+		double dist = (centre - 0.5) - rint(centre - 0.5);
+		int bin = int(centre);
+
+		int other = (dist < 0 ? (bin-1) : (bin+1));
+
+		if (bin < 0) bin = 0;
+		if (bin >= bins) bin = bins-1;
+
+		if (other < 0 || other >= bins) {
+		    other = bin;
+		}
+
+		double prop = 1.0 - fabs(dist);
+
+		double v0 = in[bin];
+		double v1 = in[other];
+                
+		out[y] = float(prop * v0 + (1.0 - prop) * v1);
+
+	    } else { // not interpolating this one
+
+		int by0 = int(sy0 + 0.0001);
+		int by1 = int(sy1 + 0.0001);
+		if (by1 < by0 + 1) by1 = by0 + 1;
+                if (by1 >= bins) by1 = by1 - 1;
+                
+		for (int bin = by0; bin < by1; ++bin) {
+
+		    float value = in[bin];
+
+		    if (bin == by0 || value > out[y]) {
+			out[y] = value;
+		    }
+		}
+	    }
+	}
+
+	return out;
+    }
+
+};
+
+#endif
+