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author | Chris Cannam |
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date | Thu, 20 Sep 2018 11:45:11 +0100 |
parents | 7e3532d56abb |
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/* -*- 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; }