Mercurial > hg > svcore
view base/ColumnOp.cpp @ 1376:d9511f9e04d7 dev/refactor-piper-related
Introduce some POD structs for describing an external server application and the desired libraries to load from it, and disambiguating between empty list request and invalid list request. This allows for overriding PiperVampPluginFactory behaviour for using a PluginScan to populate the list request.
author | Lucas Thompson <lucas.thompson@qmul.ac.uk> |
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date | Fri, 10 Feb 2017 11:15:19 +0000 |
parents | 47ee4706055c |
children | 9ef1cc26024c |
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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 2006-2016 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. */ #include "ColumnOp.h" #include <cmath> #include <algorithm> #include <iostream> #include "base/Debug.h" using namespace std; ColumnOp::Column ColumnOp::fftScale(const Column &in, int fftSize) { return applyGain(in, 2.0 / fftSize); } ColumnOp::Column ColumnOp::peakPick(const Column &in) { 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; } ColumnOp::Column ColumnOp::normalize(const Column &in, ColumnNormalization n) { if (n == ColumnNormalization::None || in.empty()) { return in; } float scale = 1.f; if (n == ColumnNormalization::Sum1) { float sum = 0.f; for (auto v: in) { sum += fabsf(v); } if (sum != 0.f) { scale = 1.f / sum; } } else { float max = 0.f; for (auto v: in) { v = fabsf(v); if (v > max) { max = v; } } 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); } ColumnOp::Column ColumnOp::distribute(const Column &in, int h, const vector<double> &binfory, int minbin, bool interpolate) { vector<float> out(h, 0.f); int bins = int(in.size()); if (interpolate) { // If the bins are all closer together than the target y // coordinate increments, then we don't want to interpolate // after all. But because the binfory mapping isn't // necessarily linear, just checking e.g. whether bins > h is // not enough -- the bins could still be spaced more widely at // either end of the scale. We are prepared to assume however // that if the bins are closer at both ends of the scale, they // aren't going to diverge mysteriously in the middle. if (h > 1 && fabs(binfory[1] - binfory[0]) >= 1.0 && fabs(binfory[h-1] - binfory[h-2]) >= 1.0) { interpolate = false; } } for (int y = 0; y < h; ++y) { if (interpolate) { double sy = binfory[y] - minbin - 0.5; double syf = floor(sy); int mainbin = int(syf); int other = mainbin; if (sy > syf) { other = mainbin + 1; } else if (sy < syf) { other = mainbin - 1; } if (mainbin < 0) { mainbin = 0; } if (mainbin >= bins) { mainbin = bins - 1; } if (other < 0) { other = 0; } if (other >= bins) { other = bins - 1; } double prop = 1.0 - fabs(sy - syf); double v0 = in[mainbin]; double v1 = in[other]; out[y] = float(prop * v0 + (1.0 - prop) * v1); } else { double sy0 = binfory[y] - minbin; double sy1; if (y+1 < h) { sy1 = binfory[y+1] - minbin; } else { sy1 = bins; } int by0 = int(sy0 + 0.0001); int by1 = int(sy1 + 0.0001); if (by0 < 0 || by0 >= bins || by1 > bins) { SVCERR << "ERROR: bin index out of range in ColumnOp::distribute: by0 = " << by0 << ", by1 = " << by1 << ", sy0 = " << sy0 << ", sy1 = " << sy1 << ", y = " << y << ", binfory[y] = " << binfory[y] << ", minbin = " << minbin << ", bins = " << bins << endl; continue; } for (int bin = by0; bin == by0 || bin < by1; ++bin) { float value = in[bin]; if (bin == by0 || value > out[y]) { out[y] = value; } } } } return out; }