view base/LogRange.cpp @ 1671:82d03c9661f9 single-point

Rework isReady()/getCompletion() on models. Previously the new overhauled models were implementing getCompletion() but inheriting a version of isReady() (from the Model base) that didn't call it, referring only to isOK(). So they were reporting completion as soon as they had begun. Instead hoist getCompletion() to abstract base and call it from Model::isReady().
author Chris Cannam
date Wed, 27 Mar 2019 13:15:16 +0000
parents 7e3532d56abb
children
line wrap: on
line source
/* -*- 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(double &min, double &max, double logthresh)
{
    static double eps = 1e-10;
    
    // ensure that max > min:
    if (min > max) std::swap(min, max);
    if (max == min) max = min + 1;

    if (min >= 0.0) {

        // and max > min, so we know min >= 0 and max > 0
        
        max = log10(max);

        if (min == 0.0) min = std::min(logthresh, max);
        else min = log10(min);

    } else if (max <= 0.0) {

        // and max > min, so we know min < 0 and max <= 0
        
        min = log10(-min);

        if (max == 0.0) max = std::min(logthresh, min);
        else max = log10(-max);
        
        std::swap(min, max);

    } else {
        
        // min < 0 and max > 0
        
        max = log10(std::max(max, -min));
        min = std::min(logthresh, max);
    }

    if (fabs(max - min) < eps) min = max - 1;
}        

double
LogRange::map(double value, double thresh)
{
    if (value == 0.0) return thresh;
    return log10(fabs(value));
}

double
LogRange::unmap(double value)
{
    return pow(10.0, value);
}

static double
sd(const std::vector<double> &values, int start, int n)
{
    double sum = 0.0, mean = 0.0, variance = 0.0;
    for (int i = 0; i < n; ++i) {
        sum += values[start + i];
    }
    mean = sum / n;
    for (int i = 0; i < n; ++i) {
        double diff = values[start + i] - mean;
        variance += diff * diff;
    }
    variance = variance / n;
    return sqrt(variance);
}

bool
LogRange::shouldUseLogScale(std::vector<double> 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.

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

    double sd0 = sd(values, 0, mi);
    double sd1 = sd(values, mi, n - 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.) return true;
    else return false;
}