Chris@1187: /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
Chris@1187: 
Chris@1187: /*
Chris@1187:     Sonic Visualiser
Chris@1187:     An audio file viewer and annotation editor.
Chris@1187:     Centre for Digital Music, Queen Mary, University of London.
Chris@1188:     This file copyright 2006-2016 Chris Cannam and QMUL.
Chris@1187:     
Chris@1187:     This program is free software; you can redistribute it and/or
Chris@1187:     modify it under the terms of the GNU General Public License as
Chris@1187:     published by the Free Software Foundation; either version 2 of the
Chris@1187:     License, or (at your option) any later version.  See the file
Chris@1187:     COPYING included with this distribution for more information.
Chris@1187: */
Chris@1187: 
Chris@1187: #ifndef COLUMN_OP_H
Chris@1187: #define COLUMN_OP_H
Chris@1187: 
Chris@1187: #include "BaseTypes.h"
Chris@1187: 
Chris@1187: #include <cmath>
Chris@1187: 
Chris@1190: /**
Chris@1193:  * Display normalization types for columns in e.g. grid plots.
Chris@1193:  *
Chris@1193:  * Max1 means to normalize to max value = 1.0.
Chris@1193:  * Sum1 means to normalize to sum of values = 1.0.
Chris@1193:  *
Chris@1193:  * Hybrid means normalize to max = 1.0 and then multiply by
Chris@1193:  * log10 of the max value, to retain some difference between
Chris@1193:  * levels of neighbouring columns.
Chris@1193:  *
Chris@1193:  * Area normalization is handled separately.
Chris@1193:  */
Chris@1193: enum class ColumnNormalization {
Chris@1193:     None,
Chris@1193:     Max1,
Chris@1193:     Sum1,
Chris@1193:     Hybrid
Chris@1193: };
Chris@1193: 
Chris@1193: /**
Chris@1190:  * Class containing static functions for simple operations on data
Chris@1190:  * columns, for use by display layers.
Chris@1190:  */
Chris@1187: class ColumnOp
Chris@1187: {
Chris@1187: public:
Chris@1190:     /** 
Chris@1190:      * Column type. 
Chris@1190:      */
Chris@1187:     typedef std::vector<float> Column;
Chris@1187: 
Chris@1190:     /**
Chris@1195:      * Scale the given column using the given gain multiplier.
Chris@1195:      */
Chris@1197:     static Column applyGain(const Column &in, double gain) {
Chris@1195: 	
Chris@1197: 	if (gain == 1.0) {
Chris@1195: 	    return in;
Chris@1195: 	}
Chris@1195: 	Column out;
Chris@1195: 	out.reserve(in.size());
Chris@1195: 	for (auto v: in) {
Chris@1197: 	    out.push_back(float(v * gain));
Chris@1195: 	}
Chris@1195: 	return out;
Chris@1195:     }
Chris@1195: 
Chris@1195:     /**
Chris@1190:      * Scale an FFT output by half the FFT size.
Chris@1190:      */
Chris@1187:     static Column fftScale(const Column &in, int fftSize) {
Chris@1197:         return applyGain(in, 2.0 / fftSize);
Chris@1187:     }
Chris@1187: 
Chris@1190:     /**
Chris@1190:      * Determine whether an index points to a local peak.
Chris@1190:      */
Chris@1187:     static bool isPeak(const Column &in, int ix) {
Chris@1187: 	
Chris@1187: 	if (!in_range_for(in, ix-1)) return false;
Chris@1187: 	if (!in_range_for(in, ix+1)) return false;
Chris@1187: 	if (in[ix] < in[ix+1]) return false;
Chris@1187: 	if (in[ix] < in[ix-1]) return false;
Chris@1187: 	
Chris@1187: 	return true;
Chris@1187:     }
Chris@1187: 
Chris@1190:     /**
Chris@1190:      * Return a column containing only the local peak values (all
Chris@1190:      * others zero).
Chris@1190:      */
Chris@1187:     static Column peakPick(const Column &in) {
Chris@1187: 	
Chris@1187: 	std::vector<float> out(in.size(), 0.f);
Chris@1187: 	for (int i = 0; in_range_for(in, i); ++i) {
Chris@1187: 	    if (isPeak(in, i)) {
Chris@1187: 		out[i] = in[i];
Chris@1187: 	    }
Chris@1187: 	}
Chris@1187: 	
Chris@1187: 	return out;
Chris@1187:     }
Chris@1187: 
Chris@1190:     /**
Chris@1190:      * Return a column normalized from the input column according to
Chris@1190:      * the given normalization scheme.
Chris@1190:      */
Chris@1193:     static Column normalize(const Column &in, ColumnNormalization n) {
Chris@1187: 
Chris@1193: 	if (n == ColumnNormalization::None) {
Chris@1187: 	    return in;
Chris@1187: 	}
Chris@1187: 
Chris@1193:         float scale = 1.f;
Chris@1193:         
Chris@1193:         if (n == ColumnNormalization::Sum1) {
Chris@1193: 
Chris@1193:             float sum = 0.f;
Chris@1193: 
Chris@1193:             for (auto v: in) {
Chris@1193:                 sum += v;
Chris@1193:             }
Chris@1193: 
Chris@1193:             if (sum != 0.f) {
Chris@1193:                 scale = 1.f / sum;
Chris@1193:             }
Chris@1193:         } else {
Chris@1193:         
Chris@1193:             float max = *max_element(in.begin(), in.end());
Chris@1193: 
Chris@1193:             if (n == ColumnNormalization::Max1) {
Chris@1193:                 if (max != 0.f) {
Chris@1193:                     scale = 1.f / max;
Chris@1193:                 }
Chris@1193:             } else if (n == ColumnNormalization::Hybrid) {
Chris@1193:                 if (max > 0.f) {
Chris@1193:                     scale = log10f(max + 1.f) / max;
Chris@1193:                 }
Chris@1193:             }
Chris@1193:         }
Chris@1187: 
Chris@1197:         return applyGain(in, scale);
Chris@1187:     }
Chris@1187: 
Chris@1190:     /**
Chris@1190:      * Distribute the given column into a target vector of a different
Chris@1190:      * size, optionally using linear interpolation. The binfory vector
Chris@1190:      * contains a mapping from y coordinate (i.e. index into the
Chris@1190:      * target vector) to bin (i.e. index into the source column).
Chris@1190:      */
Chris@1187:     static Column distribute(const Column &in,
Chris@1187: 			     int h,
Chris@1187: 			     const std::vector<double> &binfory,
Chris@1187: 			     int minbin,
Chris@1187: 			     bool interpolate) {
Chris@1198: 
Chris@1187: 	std::vector<float> out(h, 0.f);
Chris@1187: 	int bins = int(in.size());
Chris@1187: 
Chris@1187: 	for (int y = 0; y < h; ++y) {
Chris@1187:         
Chris@1187: 	    double sy0 = binfory[y] - minbin;
Chris@1187: 	    double sy1 = sy0 + 1;
Chris@1187: 	    if (y+1 < h) {
Chris@1187: 		sy1 = binfory[y+1] - minbin;
Chris@1187: 	    }
Chris@1187:         
Chris@1187: 	    if (interpolate && fabs(sy1 - sy0) < 1.0) {
Chris@1187:             
Chris@1187: 		double centre = (sy0 + sy1) / 2;
Chris@1187: 		double dist = (centre - 0.5) - rint(centre - 0.5);
Chris@1187: 		int bin = int(centre);
Chris@1187: 
Chris@1187: 		int other = (dist < 0 ? (bin-1) : (bin+1));
Chris@1187: 
Chris@1187: 		if (bin < 0) bin = 0;
Chris@1187: 		if (bin >= bins) bin = bins-1;
Chris@1187: 
Chris@1187: 		if (other < 0 || other >= bins) {
Chris@1187: 		    other = bin;
Chris@1187: 		}
Chris@1187: 
Chris@1187: 		double prop = 1.0 - fabs(dist);
Chris@1187: 
Chris@1187: 		double v0 = in[bin];
Chris@1187: 		double v1 = in[other];
Chris@1187:                 
Chris@1187: 		out[y] = float(prop * v0 + (1.0 - prop) * v1);
Chris@1187: 
Chris@1187: 	    } else { // not interpolating this one
Chris@1187: 
Chris@1187: 		int by0 = int(sy0 + 0.0001);
Chris@1187: 		int by1 = int(sy1 + 0.0001);
Chris@1187: 		if (by1 < by0 + 1) by1 = by0 + 1;
Chris@1198:                 if (by1 >= bins) by1 = by1 - 1;
Chris@1198:                 
Chris@1187: 		for (int bin = by0; bin < by1; ++bin) {
Chris@1187: 
Chris@1187: 		    float value = in[bin];
Chris@1187: 
Chris@1201: 		    if (bin == by0 || value > out[y]) {
Chris@1187: 			out[y] = value;
Chris@1187: 		    }
Chris@1187: 		}
Chris@1187: 	    }
Chris@1187: 	}
Chris@1187: 
Chris@1187: 	return out;
Chris@1187:     }
Chris@1187: 
Chris@1187: };
Chris@1187: 
Chris@1187: #endif
Chris@1187: