annotate base/ColumnOp.h @ 1247:8f076d02569a piper

Make SVDEBUG always write to a log file -- formerly this was disabled in NDEBUG builds. I think there's little use to that, it just means that we keep adding more cerr debug output because we aren't getting the log we need. And SVDEBUG logging is not usually used in tight loops, I don't think the performance overhead is too serious.

Also update the About box.

/* -*- 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