view base/LogRange.cpp @ 875:3e6ed8a8577b tonioni

Use a sparse time-value model only for outputs with fixed bin count of 1, not for those with unknown bin count.
(Precursor to using more than one model for outputs with unknown bin count)

/* -*- 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 Chris Cannam.
    
    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.
*/

#include "LogRange.h"
#include "system/System.h"

#include <algorithm>
#include <iostream>
#include <cmath>

void
LogRange::mapRange(float &min, float &max, float logthresh)
{
    if (min > max) std::swap(min, max);
    if (max == min) max = min + 1;

//    SVDEBUG << "LogRange::mapRange: min = " << min << ", max = " << max << endl;

    if (min >= 0.f) {

        max = log10f(max); // we know max != 0

        if (min == 0.f) min = std::min(logthresh, max);
        else min = log10f(min);

//        SVDEBUG << "LogRange::mapRange: positive: min = " << min << ", max = " << max << endl;

    } else if (max <= 0.f) {
        
        min = log10f(-min); // we know min != 0
        
        if (max == 0.f) max = std::min(logthresh, min);
        else max = log10f(-max);
        
        std::swap(min, max);
        
//        SVDEBUG << "LogRange::mapRange: negative: min = " << min << ", max = " << max << endl;

    } else {
        
        // min < 0 and max > 0
        
        max = log10f(std::max(max, -min));
        min = std::min(logthresh, max);

//        SVDEBUG << "LogRange::mapRange: spanning: min = " << min << ", max = " << max << endl;
    }

    if (min == max) min = max - 1;
}        

float
LogRange::map(float value, float thresh)
{
    if (value == 0.f) return thresh;
    return log10f(fabsf(value));
}

float
LogRange::unmap(float value)
{
    return powf(10.0, value);
}

static float
sd(const std::vector<float> &values, size_t start, size_t n)
{
    float sum = 0.f, mean = 0.f, variance = 0.f;
    for (size_t i = 0; i < n; ++i) {
        sum += values[start + i];
    }
    mean = sum / n;
    for (size_t i = 0; i < n; ++i) {
        float diff = values[start + i] - mean;
        variance += diff * diff;
    }
    variance = variance / n;
    return sqrtf(variance);
}

bool
LogRange::useLogScale(std::vector<float> values)
{
    // Principle: Partition the data into two sets around the median;
    // calculate the standard deviation of each set; if the two SDs
    // are very different, it's likely that a log scale would be good.

    if (values.size() < 4) return false;
    std::sort(values.begin(), values.end());
    size_t mi = values.size() / 2;

    float sd0 = sd(values, 0, mi);
    float sd1 = sd(values, mi, values.size() - mi);

    SVDEBUG << "LogRange::useLogScale: sd0 = "
              << sd0 << ", sd1 = " << sd1 << endl;

    if (sd0 == 0 || sd1 == 0) return false;

    // I wonder what method of determining "one sd much bigger than
    // the other" would be appropriate here...
    if (std::max(sd0, sd1) / std::min(sd0, sd1) > 10.f) return true;
    else return false;
}