929 lines
36 KiB
C++
929 lines
36 KiB
C++
//=============================================================================
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// MuseScore
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// Music Composition & Notation
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//
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// Copyright (C) 2007-2011 Werner Schweer
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//
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// This program is free software; you can redistribute it and/or modify
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// it under the terms of the GNU General Public License version 2
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// as published by the Free Software Foundation and appearing in
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// the file LICENCE.GPL
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//=============================================================================
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//=============================================================================
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// Keyfinder.cpp uses code from the "Melisma Music Analyzer"
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// project:
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//
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// Copyright (C) 2000 Daniel Sleator and David Temperley
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// See http://www.link.cs.cmu.edu/music-analysis
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// for information about commercial use of this system
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//=============================================================================
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/* _Important comment about how pitches and keys are represented_
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Notes may be inputted in either Note format (with just a pitch) or
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TPCNote format (with a TPC). The user may also specify
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"npc_or_tpc_profile": 0 for npc, 1 for tpc. (A TPC profile is like
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an NPC profile except that a user-settable default value is used for
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TPC's outside the range of b2 to #4.) We assume that Note format
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will be used with an npc profile; if not, a fatal error is
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reported. TPCNote format could be used with either; if you use
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TPCNote input with an npc profile, the notes are simply mapped on to
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one cycle of the LOF. (Scoring mode 0 or 3 requires an npc profile;
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otherwise a fatal error is reported.)
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Pitches (e.g. note[].tpc values) are always represented in
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line-of-fifths order, with C = 14. (This is done when the pitches
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are first read in). (If there's Note input, or TPCNote input and
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npc_or_tpc_profile = 0, all pitches are shifted into one cycle of
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the line of fifths, from 9 to 20 inclusive; again, this is done when
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the input is read.)
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Keys are also represented in line-of-fifths order. Major keys are 0
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to 27, C=14; minor keys are 28-55, C minor = 42. If
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npc_or_tpc_profile = 0, the search is nominally done on all keys,
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but only keys from 9 to 20 (inclusive) and 37 to 48 (inclusive) are
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looked at; others are given large negative values.
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Although key-profiles are read in in pitch-height order, they are
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then adjusted (in generate_tpc/npc_profiles) to line-of-fifths
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order, with the tonic as 5. */
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#include <string.h>
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#include <math.h>
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#include "keyfinder.h"
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#include "sig.h"
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#include "pitchspelling.h"
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#include "synthesizer/event.h"
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namespace Ms {
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#if 0
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//---------------------------------------------------------
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// SBeat
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//---------------------------------------------------------
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struct SBeat {
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int time;
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};
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//---------------------------------------------------------
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// MidiSegment
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//---------------------------------------------------------
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struct MidiSegment {
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int start;
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int end;
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QList<Event> snote;
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int numnotes; // number of notes in the segment
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qreal average_dur; // average input vector value (needed for K-S algorithm)
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};
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#define CHANGE_PENALTY 12
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static float change_penalty = CHANGE_PENALTY;
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static int npc_or_tpc_profile = 1;
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static int scoring_mode = 1;
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static int verbosity = 1;
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static qreal major_profile[12] = {5.0, 2.0, 3.5, 2.0, 4.5, 4.0, 2.0, 4.5, 2.0, 3.5, 1.5, 4.0};
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static qreal minor_profile[12] = {5.0, 2.0, 3.5, 4.5, 2.0, 4.0, 2.0, 4.5, 3.5, 2.0, 1.5, 4.0};
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static qreal default_profile_value=1.5;
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/*
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CBMS profiles:
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major_profile = 5.0 2.0 3.5 2.0 4.5 4.0 2.0 4.5 2.0 3.5 1.5 4.0
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minor_profile = 5.0 2.0 3.5 4.5 2.0 4.0 2.0 4.5 3.5 2.0 1.5 4.0
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Bayesian profiles (based on frequencies in Kostka-Payne corpus):
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major_profile = 0.748 0.060 0.488 0.082 0.670 0.460 0.096 0.715 0.104 0.366 0.057 0.400
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minor_profile = 0.712 0.084 0.474 0.618 0.049 0.460 0.105 0.747 0.404 0.067 0.133 0.330
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Krumhansl's profiles:
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major_profile = 6.35 2.23 3.48 2.33 4.38 4.09 2.52 5.19 2.39 3.66 2.29 2.88
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minor_profile = 6.33 2.68 3.52 5.38 2.60 3.53 2.54 4.75 3.98 2.69 3.34 3.17
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Krumhansl's minor, normalized: 5.94 2.51 3.30 5.05 2.44 3.31 2.38 4.46 3.73 2.52 3.13 2.97
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*/
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static int firstbeat;
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static QList<Event> note;
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static QList<MidiSegment> segment; // An array storing the notes in each segment
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static int segtotal; // total number of segments - 1
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static qreal seglength;
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static QList<int> seg_prof[28];
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static QList<qreal> key_score[56];
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static QList<SBeat> sbeat;
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static QList<qreal> analysis[56][56];
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static QList<int> best[56];
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static QList<int> final;
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// static int numnotes, numchords, num_sbeats;
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static int num_sbeats;
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static QList<int> pc_tally;
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static QList<qreal> final_score;
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static qreal key_profile[56][28];
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static int final_timepoint;
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//---------------------------------------------------------
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// print_keyname
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//---------------------------------------------------------
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static void print_keyname(int f)
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{
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static const char letter[] = "CGDAEBF";
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int mf = f % 27;
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mf -= 14;
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qDebug("(%d,%d)%c", f, mf, letter[f % 7]);
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if (f < 6 || (f >= 28 && f < 34))
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qDebug("-");
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if ((f >= 6 && f < 13) || (f >= 34 && f < 41))
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qDebug("b");
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if ((f >= 20 && f < 27) || (f >=48 && f < 55))
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qDebug("#");
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if (f == 27 || f == 55)
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qDebug("x");
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if (f >= 28)
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qDebug("m");
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if (f < 28)
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qDebug(" ");
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qDebug(" ");
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}
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//---------------------------------------------------------
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// create_segments
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// Each segment starts at a sbeat and ends at the
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// following sbeat
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//---------------------------------------------------------
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static void create_segments()
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{
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segment.append(MidiSegment());
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segment[0].start = firstbeat; // Always start a segment at the very beginning of the piece (the first beat)
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for (int b = 0; b < num_sbeats; b++) {
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if (b == 0 && (sbeat[0].time - firstbeat) < ((sbeat[1].time-firstbeat) - (sbeat[0].time-firstbeat))/2)
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continue;
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/* If it's the first beat of the piece, and the upbeat is
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less than half of the first beat interval, don't start a segment
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*/
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else {
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MidiSegment seg;
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seg.start = sbeat[b].time;
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segment.back().end = sbeat[b].time;
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segment.append(seg);
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}
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}
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int s = segment.size() - 1;
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/* If final segment starts at or after final timepoint of piece, ignore it,
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decrementing number of segments by 1; if not, set that segment's ending
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to final timepoint of piece
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*/
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if (segment[s].start >= final_timepoint) {
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s--;
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}
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else {
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segment[s].end = final_timepoint;
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/* qDebug("Final segment ends at %d", segment[s].end); */
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}
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segtotal = s; // index of final segment
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}
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//---------------------------------------------------------
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// fill_segments
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//---------------------------------------------------------
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static void fill_segments()
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{
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for (int s = 0; s < segment.size(); ++s) {
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foreach (const Event& n, note) {
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int ontime = n.ontime();
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int offtime = n.offtime();
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int start = segment[s].start;
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int end = segment[s].end;
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if (ontime >= start && ontime < end && offtime <= end) {
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// note begins and ends in segment
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Event sn(ME_NOTE);
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sn.setDataA(n.dataA());
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sn.setTpc(n.tpc());
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sn.setDuration(n.duration());
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segment[s].snote.append(sn);
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}
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if (ontime >= start && ontime < end && offtime > end) {
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// note begins, doesn't end in segment
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Event sn(ME_NOTE);
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sn.setDataA(n.dataA());
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sn.setTpc(n.tpc());
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sn.setDuration(end - ontime);
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segment[s].snote.append(sn);
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}
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if (ontime < start && offtime > start && offtime <= end) {
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// note ends, doesn't begin in segment
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Event sn(ME_NOTE);
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sn.setDataA(n.dataA());
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sn.setTpc(n.tpc());
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sn.setDuration(offtime - start);
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segment[s].snote.append(sn);
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}
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if (ontime < start && offtime > end) {
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// note doesn't begin or end in segment
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Event sn(ME_NOTE);
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sn.setDataA(n.dataA());
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sn.setTpc(n.tpc());
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sn.setDuration(end - start);
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segment[s].snote.append(sn);
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}
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}
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segment[s].numnotes = segment[s].snote.size();
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// qDebug("fillSegments %d: %d-%d %d", s, segment[s].start,
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// segment[s].end, segment[s].numnotes);
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}
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}
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//---------------------------------------------------------
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// count_segment_notes
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// In each segment, tally up the notes of each TPC
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//---------------------------------------------------------
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static void count_segment_notes()
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{
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for (int s = 0; s <= segtotal; ++s) {
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pc_tally[s] = 0;
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for (int y = 0; y < 28; ++y) // cycle through the pc's, make sure all the seg_prof values are zero
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seg_prof[y].append(0);
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qreal total_dur = 0;
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for (int n = 0; n < segment[s].numnotes; ++n) {
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if (scoring_mode == 0)
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total_dur += segment[s].snote[n].duration();
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for (int y=0; y<28; ++y) {
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if (segment[s].snote[n].tpc() == y) {
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if(seg_prof[y][s]==0)
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pc_tally[s]++;
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/* This keeps track of how many different pc's the segment contains. This counts TPCs, not NPCs! */
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/* If scoring_mode is > 1, set array value to 1. If 0, add the note's duration to the
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array value (as in the K-S algorithm) */
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if (scoring_mode > 0)
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seg_prof[y][s] = 1;
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else {
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seg_prof[y][s] += segment[s].snote[n].duration();
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}
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}
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}
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}
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if(scoring_mode == 0) {
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if(pc_tally[s]==0)
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segment[s].average_dur = 0.0;
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segment[s].average_dur = total_dur / 12.0;
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/* qDebug("Segment %d total dur = %6.3f, average dur = %6.3f", s, total_dur, segment[s].average_dur); */
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}
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if (verbosity>=2) {
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qDebug("Segment %d: ", s);
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for (int y=0; y<28; ++y) {
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if(npc_or_tpc_profile == 0 && (y<9 || y>20))
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continue;
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qDebug("%d ", seg_prof[y][s]);
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}
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}
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/* qDebug("pc_tally = %d", pc_tally[s]); */
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}
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}
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//---------------------------------------------------------
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// prepare_profiles
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// We're only here if scoring_mode is 0 (the K-S algorithm).
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// Sum all the profile values, take the mean,
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// and subtract that from each value
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//---------------------------------------------------------
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static void prepare_profiles()
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{
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qreal total = 0.0;
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for (int i = 0; i < 12; i++) {
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total += major_profile[i];
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}
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qreal average = total / 12.0;
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for (int i = 0; i < 12; i++)
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major_profile[i]=major_profile[i] - average;
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total = 0;
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for (int i = 0; i < 12; i++) {
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total += minor_profile[i];
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}
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average = total / 12.0;
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for (int i = 0; i < 12; i++)
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minor_profile[i] = minor_profile[i] - average;
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if (verbosity > 2) {
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qDebug("Adjusted major profile: ");
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for(int i = 0; i < 12; i++)
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qDebug("%6.3f ", major_profile[i]);
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qDebug("Adjusted minor profile: ");
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for (int i = 0; i < 12; i++)
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qDebug("%6.3f ", minor_profile[i]);
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}
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}
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/* Here we generate the key profiles. (This is assuming tpc input.) Key_profile[key] numbers correspond to
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the line of fifths, with C = 14. Major keys are 0-27, minor keys are 28-55. PCs are also numbered
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according to the line of fifths. The major_step_profile has the tonic in step 5. For a given key, the
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profile value for a given tpc is equal to the line of fifths difference between the tpc and the key, plus
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5. */
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//---------------------------------------------------------
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// generate_tpc_profiles
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//---------------------------------------------------------
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static void generate_tpc_profiles()
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{
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int key, shift, tpc, i;
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float majp[12];
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float minp[12];
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/* First we rearrange the key profile values (inputted in pitch height order) into lof order, C = 5 */
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for(i=0; i<12; i++) {
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majp[((((i * 7) % 12) + 5) % 12)] = major_profile[i];
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minp[((((i * 7) % 12) + 5) % 12)] = minor_profile[i];
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}
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for (key=0, shift=0; key<28; ++key, ++shift) {
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for (tpc=0; tpc<28; ++tpc) {
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if (tpc-shift >= -5 && tpc-shift <= 6) {
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key_profile[key][tpc] = majp[5 + (tpc-shift)]; /* For example: for key 14 (C major) and tpc 17 (A),
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use profile step 5 + (17-14) = 8 */
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}
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if (tpc-shift < -5 || tpc-shift > 6) {
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key_profile[key][tpc] = default_profile_value;
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}
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}
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}
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for (key=28, shift=0; key<56; ++key, ++shift) {
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for (tpc=0; tpc<28; ++tpc) {
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if (tpc-shift >= -5 && tpc-shift <= 6 ) {
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key_profile[key][tpc] = minp[5 + (tpc-shift)];
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}
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if (tpc-shift < -5 || tpc-shift > 6) {
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key_profile[key][tpc] = default_profile_value;
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}
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}
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}
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/*
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This routine just prints out the key profiles
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for(key=0; key<56; ++key) {
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for(tpc=0; tpc<28; ++tpc) {
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qDebug("%1.2f ", key_profile[key][tpc]);
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}
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}
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*/
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}
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//-----------------------------------------------------------------------------
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// generate_npc_profiles
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// This is an alternative function for generating profiles given NPC
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// profile. It's similar to the TPC version, except that only keys on
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// a certain range of the line are assigned non-zero values. (This is
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// really an unnecessary step, as steps outside the range will be
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// disqualified in "match_profiles" in any case.) Also, for those keys
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// considered, only key profile slots within the 9-to-20 range are
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// assigned non-zero values. (This is necessary, since the input profile
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// is within this range as well.) We begin by assigning default values
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// of ZERO to everything.
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//-----------------------------------------------------------------------------
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static void generate_npc_profiles()
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{
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int key, shift, tpc, tpc_to_use, i;
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float majp[12];
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float minp[12];
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/* First we rearrange the key profile values (inputted in pitch height order) into lof order, C = 5 */
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for(i=0; i<12; i++) {
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majp[((((i * 7) % 12) + 5) % 12)] = major_profile[i];
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minp[((((i * 7) % 12) + 5) % 12)] = minor_profile[i];
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}
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for (key=0; key<56; ++key) {
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for(tpc=0; tpc<28; ++tpc) {
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key_profile[key][tpc]=0;
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}
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}
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for (key=9, shift=9; key<21; ++key, ++shift) {
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for (tpc=0; tpc<28; ++tpc) {
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/* tpc_to_use is the profile slot to use for a given value of the key-profile. In this way we keep
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all profile slots within the 9-to-20 range
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*/
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if(tpc<9)
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tpc_to_use=tpc+12;
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else if(tpc>20)
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tpc_to_use=tpc-12;
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else
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tpc_to_use = tpc;
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if (tpc-shift >= -5 && tpc-shift <= 6) {
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/* For example: for key 14 (C major) and tpc 17 (A),
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read from profile step 5 + (17-14) = 8. For degree
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6 of B major (key 19), degree 6 (22) is outside the
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9-to-20 range, so tpc_to_use is 22-12=10; still
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read from profile step 5 + (22-19) = 8. */
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key_profile[key][tpc_to_use] = majp[5 + (tpc-shift)];
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}
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}
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}
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for (key = 37, shift = 9; key < 49; ++key, ++shift) {
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for (tpc = 0; tpc < 28; ++tpc) {
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if (tpc<9)
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tpc_to_use = tpc + 12;
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else if (tpc > 20)
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tpc_to_use = tpc - 12;
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else
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tpc_to_use = tpc;
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if (tpc - shift >= -5 && tpc - shift <= 6 ) {
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key_profile[key][tpc_to_use] = minp[5 + (tpc-shift)];
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}
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}
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}
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/*
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for(key = 0; key < 56; ++key) {
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for(tpc=0; tpc<28; ++tpc) {
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qDebug("%1.2f ", key_profile[key][tpc]);
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}
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}
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*/
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}
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//---------------------------------------------------------
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// match_profiles
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// Here we generate the "key scores" - the local score for each key
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//
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// Notice that we generate profiles for all 56 keys and all 28
|
|
// tpc's, even in the case where npc profiles are being used. In
|
|
// this case, though, all keys outside the allowable NPC range are
|
|
// given large negative values. And within both the key profiles
|
|
// and the segment profiles, only TPC's within the range 9 to 20
|
|
// have been given nonzero values.
|
|
//---------------------------------------------------------
|
|
|
|
static void match_profiles()
|
|
{
|
|
int key, tpc, s, best_key, i;
|
|
qreal major_sumsq, minor_sumsq, input_sumsq;
|
|
qreal kprob[56];
|
|
|
|
for (key = 0; key < 56; ++key) {
|
|
for (s = 0; s <= segtotal; ++s)
|
|
key_score[key].append(0.0);
|
|
}
|
|
|
|
if (scoring_mode==0) {
|
|
major_sumsq = 0.0;
|
|
minor_sumsq = 0.0;
|
|
for(i=0; i<12; i++)
|
|
major_sumsq += major_profile[i]*major_profile[i];
|
|
for(i=0; i<12; i++)
|
|
minor_sumsq += minor_profile[i]*minor_profile[i];
|
|
if (verbosity==3)
|
|
qDebug("major_sumsq = %6.3f, minor_sumsq = %6.3f", major_sumsq, minor_sumsq);
|
|
}
|
|
|
|
qreal total_prob[segtotal + 1];
|
|
|
|
for (s = 0; s <= segtotal; ++s) {
|
|
if (scoring_mode==0) {
|
|
input_sumsq = 0.0;
|
|
for (i = 9; i <= 20; i++) {
|
|
input_sumsq += pow((seg_prof[i][s]-segment[s].average_dur), 2.0);
|
|
/* qDebug("%d X %6.3f squared is %6.3f", seg_prof[i][s], segment[s].average_dur, pow((seg_prof[i][s]-segment[s].average_dur), 2.0)); */
|
|
}
|
|
if (verbosity==3)
|
|
qDebug("For segment %d: average_dur = %6.3f; input_sumsq = %6.3f", s, segment[s].average_dur, input_sumsq);
|
|
}
|
|
best_key=0;
|
|
|
|
for (key=0; key<56; ++key) {
|
|
kprob[key] = 0.0;
|
|
key_score[key][s] = -1000000.0;
|
|
if (npc_or_tpc_profile==0 && (key<9 || (key>20 && key<37) || key>48))
|
|
continue;
|
|
kprob[key] = 1.0;
|
|
key_score[key][s] = 0.0;
|
|
for (tpc=0; tpc<28; ++tpc) {
|
|
|
|
/*
|
|
If scoring mode is 0, this is the K-S algorithm (this works for npc mode only). Segment
|
|
profile values represent total duration of each pc (in all other cases, they're just 1
|
|
for present pc's and 0 for absent ones). Key-profiles have been normalized linearly
|
|
around the average key-profile value. We normalize the input values similarly by taking
|
|
(seg_prof[tpc][s]-segment[s].average_dur). Then we multiply each normalized KP value by
|
|
the normalized input value, and sum these products; this gives us the numerator of the
|
|
correlation expression (as commented below). We've summed the squares of the normalized
|
|
key-profile value (major_sumsq and minor_sumsq above) and the normalized input values
|
|
(input_sumsq above), so this allows us to calculate the denominator also.
|
|
|
|
If scoring_mode is 1, the key score is the sum of key-profile values for all pc's present
|
|
(this is the algorithm used in CBMS)
|
|
|
|
If scoring_mode is 2, calculate key scores as above, but divide each one by the number
|
|
of pc's in the segment
|
|
|
|
If scoring_mode is 3: for each key, add the log of the key-profile value for all present pc's;
|
|
subtract values for all absent pc's. (This is the Bayesian approach; assume key-profiles
|
|
represent pc distribution's in a corpus, i.e. the number of segments containing each scale
|
|
degree)
|
|
*/
|
|
|
|
if(scoring_mode == 0) {
|
|
if(tpc<9 || tpc>20)
|
|
continue;
|
|
/* calculate numerator */
|
|
key_score[key][s] += key_profile[key][tpc] * (seg_prof[tpc][s]-segment[s].average_dur);
|
|
/* qDebug("x-X=%6.3f, y-Y=%6.3f, product=%6.3f, new total=%6.3f", key_profile[key][tpc], seg_prof[tpc][s]-segment[s].average_dur, key_profile[key][tpc] * (seg_prof[tpc][s]-segment[s].average_dur), key_score[key][s]); */
|
|
}
|
|
|
|
if(scoring_mode==1 || scoring_mode==2)
|
|
key_score[key][s] += (key_profile[key][tpc] * seg_prof[tpc][s]);
|
|
|
|
if(scoring_mode == 3) {
|
|
/* if(tpc>11) continue; */
|
|
/* if(tpc<9 || tpc>20) continue; */
|
|
|
|
if(seg_prof[tpc][s]==0) {
|
|
key_score[key][s] += log(1.000 - key_profile[key][tpc]);
|
|
/* qDebug("kp value = %6.3f: log(1-p) = %6.3f: score = %6.3f", key_profile[key][tpc], log(1.000 - key_profile[key][tpc]), key_score[key][s]); */
|
|
if(tpc>=9 && tpc<=20)
|
|
kprob[key] *= (1.000 - key_profile[key][tpc]);
|
|
}
|
|
else {
|
|
key_score[key][s] += log(key_profile[key][tpc]);
|
|
if(tpc>=9 && tpc<=20)
|
|
kprob[key] *= key_profile[key][tpc];
|
|
}
|
|
|
|
/* qDebug("kp value = %6.3f: log(p) = %6.3f: score = %6.3f", key_profile[key][tpc], log(key_profile[key][tpc]), key_score[key][s]); */
|
|
}
|
|
}
|
|
|
|
if(scoring_mode == 0) {
|
|
/* qDebug("sqrt(major_sumsq * input_sumsq) = %6.3f", sqrt(major_sumsq * input_sumsq)); */
|
|
/* calculate denominator */
|
|
if(key<28)
|
|
key_score[key][s] = key_score[key][s] / sqrt(major_sumsq * input_sumsq);
|
|
else
|
|
key_score[key][s] = key_score[key][s] / sqrt(minor_sumsq * input_sumsq);
|
|
}
|
|
if(scoring_mode == 2) {
|
|
if(pc_tally[s] == 0)
|
|
key_score[key][s] = 0;
|
|
else
|
|
key_score[key][s] = key_score[key][s] / pc_tally[s];
|
|
}
|
|
|
|
/* if(s==0) qDebug("local score for key %d on segment %d: %6.3f", key, s, key_score[key][s]); */
|
|
if (key_score[key][s] > key_score[best_key][s])
|
|
best_key = key;
|
|
}
|
|
|
|
if(verbosity>=2) {
|
|
qDebug("The best local key for segment %d at time %d is ", s, segment[s].start);
|
|
print_keyname(best_key);
|
|
qDebug("with score %6.3f", key_score[best_key][s]);
|
|
}
|
|
|
|
if(scoring_mode==3) {
|
|
total_prob[s]=0.0;
|
|
for(key=0; key<56; key++) {
|
|
total_prob[s] += kprob[key] / 24.0;
|
|
/* qDebug(" Prob of segment %d given key %d: %6.8f", s, key, kprob[key]); */
|
|
}
|
|
|
|
/* Now total_prob[s] is the total probability of the segment occurring: its probability given
|
|
a key, summed over all keys. But suppose we want to know the probability of ANY major triad
|
|
occurring? Then we have to multiply this by 12. (But not for something like a diminished
|
|
seventh which is symmetrical! */
|
|
|
|
if (verbosity>=3) {
|
|
qDebug("Best key for segment %d = %d, score = %6.8f", s, best_key, kprob[best_key]);
|
|
qDebug("Total (local) probability of segment %d: %6.8f", s, total_prob[s]);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
//---------------------------------------------------------
|
|
// choose_best_i
|
|
//---------------------------------------------------------
|
|
|
|
static void choose_best_i(int seg)
|
|
{
|
|
for (int j = 0; j < 56; ++j) {
|
|
int k = 0;
|
|
for (int i = 0; i < 56; ++i) {
|
|
if (analysis[i][j][seg] > analysis[k][j][seg])
|
|
k=i;
|
|
}
|
|
/* For a given segment seg, and the key j at that segment,
|
|
the best previous key is k
|
|
*/
|
|
int size = best[j].size();
|
|
for (int i = size; i < seg+1; ++i)
|
|
best[j].append(0);
|
|
best[j][seg] = k;
|
|
/* qDebug("For segment-%d-key %d, best segment-%d-key is %d, with score %d", seg, j, seg-1, k, analysis[k][j][seg]); */
|
|
}
|
|
}
|
|
|
|
//---------------------------------------------------------
|
|
// make_first_table
|
|
//---------------------------------------------------------
|
|
|
|
static void make_first_table(int seg)
|
|
{
|
|
int i, j, s;
|
|
qreal seg_factor, mod_factor, nomod_factor;
|
|
|
|
if (scoring_mode==3) {
|
|
mod_factor = log(change_penalty);
|
|
nomod_factor = log(1.0 - change_penalty);
|
|
seg_factor = 1.0;
|
|
}
|
|
else {
|
|
mod_factor = -change_penalty;
|
|
nomod_factor = 0.0;
|
|
seg_factor = seglength;
|
|
}
|
|
|
|
for(s = 0; s <= segtotal; s++) {
|
|
for(i = 0; i < 56; ++i) {
|
|
for(j = 0; j < 56; ++j)
|
|
analysis[i][j].append(-1000.0);
|
|
}
|
|
}
|
|
|
|
for(i = 0; i < 56; ++i) {
|
|
for(j = 0; j < 56; ++j) {
|
|
if (j != i)
|
|
analysis[i][j][1] = ((key_score[i][0] + key_score[j][1]) * seg_factor) + mod_factor;
|
|
else
|
|
analysis[i][j][1] = ((key_score[i][0] + key_score[j][1]) * seg_factor) + nomod_factor;
|
|
}
|
|
}
|
|
choose_best_i(seg);
|
|
}
|
|
|
|
//---------------------------------------------------------
|
|
// make_tables
|
|
//---------------------------------------------------------
|
|
|
|
static void make_tables()
|
|
{
|
|
qreal seg_factor, mod_factor, nomod_factor;
|
|
|
|
/* When scoring_mode = 3, the change_penalty represents the probability of changing key. So raising
|
|
the penalty actually _increases_ the likelihood of modulations. */
|
|
|
|
if (scoring_mode == 3) {
|
|
mod_factor = log(change_penalty / 23.0);
|
|
nomod_factor = log(1.0 - change_penalty);
|
|
seg_factor = 1.0;
|
|
}
|
|
else {
|
|
mod_factor = -change_penalty;
|
|
nomod_factor = 0.0;
|
|
seg_factor = seglength;
|
|
}
|
|
|
|
for (int seg = 2; seg <= segtotal; ++seg) {
|
|
/* qDebug("mod_factor = %6.6f; ; nomod_factor = %6.6f", mod_factor, nomod_factor); */
|
|
for(int j = 0; j < 56; ++j) {
|
|
for(int i = 0; i < 56; ++i) {
|
|
int n = best[i][seg-1];
|
|
if (j != i)
|
|
analysis[i][j][seg] = analysis[n][i][seg-1] + (key_score[j][seg] * seg_factor) + mod_factor;
|
|
else
|
|
analysis[i][j][seg] = analysis[n][i][seg-1] + (key_score[j][seg] * seg_factor) + nomod_factor;
|
|
}
|
|
}
|
|
choose_best_i(seg);
|
|
}
|
|
}
|
|
|
|
//---------------------------------------------------------
|
|
// best_key_analysis
|
|
//---------------------------------------------------------
|
|
|
|
static void best_key_analysis()
|
|
{
|
|
int n, m, f, tie1=-1, tie2=-1;
|
|
int s = segtotal;
|
|
int k = 0;
|
|
for(int j = 0; j < 56; ++j) {
|
|
n = best[j][s];
|
|
m = best[k][s];
|
|
|
|
if (analysis[n][j][s] < analysis[m][k][s] + .001 && analysis[n][j][s] > analysis[m][k][s] - .001 && j!=k) {
|
|
tie1=j;
|
|
tie2=k;
|
|
}
|
|
|
|
if (verbosity>1 && !(npc_or_tpc_profile == 0 && (j<9 || (j>20 && j<37) || j>48))) {
|
|
qDebug("Final score for ");
|
|
print_keyname(j);
|
|
/* qDebug("is %6.3f", analysis[n][j][s] * 1000 / (segment[segtotal].end - segment[0].start)); */
|
|
qDebug("is %6.3f", analysis[n][j][s]);
|
|
}
|
|
if (analysis[n][j][s] > analysis[m][k][s] + .000001) {
|
|
/* The .000001 is to fix a strange bug: sometimes it thinks the conditional is satisfied in the case of ties */
|
|
k = j; /* compute best key of final segment */
|
|
}
|
|
}
|
|
|
|
// To force a key choice at the final segment, insert key number here
|
|
|
|
final[s] = k;
|
|
if (verbosity > 1)
|
|
if (k==tie1 || k==tie2)
|
|
qDebug("Tie at the end between %d and %d", tie1, tie2);
|
|
|
|
// Here's where we take the best key choices and put them into final[s]
|
|
|
|
for(s = segtotal; s >= 1; --s) {
|
|
final[s-1] = best[k][s];
|
|
k = final[s-1];
|
|
}
|
|
|
|
if (verbosity >= 2) {
|
|
qDebug("Segment 0: key choice %d; total score %6.3f; segment score %6.3f", final[0], key_score[final[0]][0],
|
|
key_score[final[0]][0]);
|
|
qDebug("Segment 1: key choice %d; total score %6.3f; segment score %6.3f", final[1], analysis[final[0]][final[1]][1], analysis[final[0]][final[1]][1] - key_score[final[0]][0]);
|
|
for(s = 2; s <= segtotal; s++) {
|
|
qDebug("Segment %d: key choice %d; total score %6.3f; segment score %6.3f", s, final[s], analysis[final[s-1]][final[s]][s], analysis[final[s-1]][final[s]][s] - analysis[final[s-2]][final[s-1]][s-1]);
|
|
}
|
|
}
|
|
|
|
if (verbosity > 1)
|
|
qDebug("'Key-fit' scores for preferred analysis:");
|
|
|
|
/* This routine calculates the key-fit scores for the final analysis. These are really per-second scores.
|
|
Key-profile scores are not multiplied by seglength (as they would be in actually computing the analyses);
|
|
change penalties are divided by seglength. */
|
|
|
|
for (s = 0; s <= segtotal; ++s) {
|
|
f = final[s];
|
|
if (s > 0 && final[s] != final[s-1])
|
|
final_score[s] = (key_score[f][s]) - (change_penalty / seglength);
|
|
else
|
|
final_score[s]=key_score[f][s];
|
|
if (verbosity > 1) {
|
|
qDebug(" segment %d: %6.3f", s, final_score[s]);
|
|
}
|
|
}
|
|
}
|
|
|
|
//---------------------------------------------------------
|
|
// findKey
|
|
//---------------------------------------------------------
|
|
|
|
int findKey(MidiTrack* mt, TimeSigMap* sigmap)
|
|
{
|
|
int tpc_found, npc_found;
|
|
|
|
if ((scoring_mode == 0 || scoring_mode == 3) && npc_or_tpc_profile == 1) {
|
|
qDebug("Error: scoring mode %d requires an npc profile", scoring_mode);
|
|
exit(1);
|
|
}
|
|
|
|
final_timepoint=0;
|
|
|
|
tpc_found = 0;
|
|
npc_found = 0;
|
|
|
|
int lastTick = 0;
|
|
const EventList el = mt->events();
|
|
|
|
foreach (Event e, el) {
|
|
if (e.type() != ME_NOTE)
|
|
continue;
|
|
if (e.offtime() > lastTick)
|
|
lastTick = e.offtime();
|
|
// For note input, generate TPC labels within the 9-to-20 range
|
|
e.setTpc((((((e.pitch() % 12) * 7) % 12) + 5) % 12) + 9);
|
|
note.append(e);
|
|
}
|
|
spell(note, 0);
|
|
npc_found = 1;
|
|
|
|
// create one segment for every measure
|
|
for (int i = 0;; ++i) {
|
|
int tick = sigmap->bar2tick(i, 0, 0);
|
|
SBeat b;
|
|
b.time = tick;
|
|
sbeat.append(b);
|
|
if (tick > lastTick)
|
|
break;
|
|
}
|
|
|
|
firstbeat = sbeat.first().time;
|
|
final_timepoint = sbeat.last().time;
|
|
num_sbeats = sbeat.size();
|
|
|
|
numnotes = note.size();
|
|
numchords = 0;
|
|
|
|
if (note.isEmpty()) {
|
|
qDebug("Error: No notes in input.");
|
|
return 0;
|
|
}
|
|
|
|
seglength = (sbeat[1].time - sbeat[0].time) / 1000.0; /* define segment length as the length of the first segment */
|
|
if (verbosity > 1)
|
|
qDebug("seglength = %3.3f", seglength);
|
|
|
|
create_segments();
|
|
for (int i = 0; i < segtotal+1; ++i) {
|
|
final.append(0);
|
|
pc_tally.append(0);
|
|
final_score.append(0.0);
|
|
}
|
|
|
|
fill_segments();
|
|
count_segment_notes();
|
|
if (scoring_mode==0)
|
|
prepare_profiles();
|
|
if (npc_or_tpc_profile == 1)
|
|
generate_tpc_profiles();
|
|
else
|
|
generate_npc_profiles();
|
|
match_profiles();
|
|
if (segtotal > 0) {
|
|
make_first_table(1);
|
|
make_tables();
|
|
best_key_analysis();
|
|
}
|
|
|
|
QList<int> keys;
|
|
for (int i = 0; i < 27; ++i)
|
|
keys.append(0);
|
|
for (int i = 0; i <= segtotal; ++i) {
|
|
keys[final[i] % 27]++; // fold major/minor
|
|
// qDebug("key %d: %d %d", i, final[i], (final[i] % 27) - 14);
|
|
}
|
|
int xkey = 0;
|
|
int xcount = 0;
|
|
for (int i = 0; i < 27; ++i) {
|
|
if (keys[i] > xcount) {
|
|
xcount = keys[i];
|
|
xkey = i;
|
|
}
|
|
}
|
|
|
|
xkey -= 14;
|
|
if (xkey < -7 || xkey > 7) {
|
|
qDebug("findKey(): illegal key %d found", xkey);
|
|
xkey = 0;
|
|
}
|
|
|
|
spell(note, xkey); // spell again with found key
|
|
|
|
//
|
|
// clear all arrays
|
|
//
|
|
note.clear();
|
|
segment.clear();
|
|
sbeat.clear();
|
|
for (int i = 0; i < 28; ++i)
|
|
seg_prof[i].clear();
|
|
for (int i = 0; i < 56; ++i) {
|
|
key_score[i].clear();
|
|
best[i].clear();
|
|
for (int k = 0; k < 56; ++k)
|
|
analysis[i][k].clear();
|
|
}
|
|
final.clear();
|
|
pc_tally.clear();
|
|
final_score.clear();
|
|
|
|
return xkey;
|
|
}
|
|
#endif
|
|
|
|
}
|
|
|