Mercurial > hg > svcore
view base/ColumnOp.h @ 1385:b061b9f8fca5
Debug notes, tidying
author | Chris Cannam |
---|---|
date | Thu, 23 Feb 2017 09:22:56 +0000 |
parents | dd190086db73 |
children | 9ef1cc26024c |
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 2006-2016 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 <vector> /** * 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 downward by half the FFT size. */ static Column fftScale(const Column &in, int fftSize); /** * Determine whether an index points to a local peak. */ static bool isPeak(const Column &in, int ix) { if (!in_range_for(in, ix)) { return false; } if (ix == 0) { return in[0] >= in[1]; } if (!in_range_for(in, ix+1)) { return in[ix] > in[ix-1]; } 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); /** * Return a column normalized from the input column according to * the given normalization scheme. * * Note that the sum or max (as appropriate) used for * normalisation will be calculated from the absolute values of * the column elements, should any of them be negative. */ static Column normalize(const Column &in, ColumnNormalization n); /** * 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). The * source column ("in") may be a partial column; it's assumed to * contain enough bins to span the destination range, starting * with the bin of index minbin. */ static Column distribute(const Column &in, int h, const std::vector<double> &binfory, int minbin, bool interpolate); }; #endif