summaryrefslogtreecommitdiff
path: root/src/sample_selection.cc
blob: 8616e098a0d9315737d5c4b497c1ad879faa25c8 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
/* -*- Mode: c++ -*- */
/***************************************************************************
 *            sample_selection.h
 *
 *  Mon Mar  4 23:58:12 CET 2019
 *  Copyright 2019 André Nusser
 *  andre.nusser@googlemail.com
 ****************************************************************************/

/*
 *  This file is part of DrumGizmo.
 *
 *  DrumGizmo is free software; you can redistribute it and/or modify
 *  it under the terms of the GNU Lesser General Public License as published by
 *  the Free Software Foundation; either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  DrumGizmo is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU Lesser General Public License for more details.
 *
 *  You should have received a copy of the GNU Lesser General Public License
 *  along with DrumGizmo; if not, write to the Free Software
 *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA.
 */
#include "sample_selection.h"

#include <hugin.hpp>

#include "powerlist.h"
#include "random.h"
#include "settings.h"

namespace
{

// Minimum sample set size.
// Smaller means wider 'velocity groups'.
// Limited by sample set size, ie. only kicks in if sample set size is smaller
// than this number.
std::size_t const MIN_SAMPLE_SET_SIZE = 26u;

float pow2(float f)
{
	return f*f;
}

} // end anonymous namespace

SampleSelection::SampleSelection(Settings& settings, Random& rand, const PowerList& powerlist)
	: settings(settings), rand(rand), powerlist(powerlist), alg(SelectionAlg::Old)
{
}

void SampleSelection::setSelectionAlg(SelectionAlg alg)
{
	this->alg = alg;
}

void SampleSelection::finalise()
{
	last.assign(powerlist.getPowerListItems().size(), 0);
}

const Sample* SampleSelection::get(level_t level, std::size_t pos)
{
	// TODO: switch objective to default at some point
	switch (alg)
	{
		case SelectionAlg::Objective:
			return getObjective(level, pos);
			break;
		case SelectionAlg::Old:
		default:
			return getOld(level, pos);
	}
}

const Sample* SampleSelection::getOld(level_t level, std::size_t pos)
{
	auto velocity_stddev = settings.velocity_stddev.load();

	const auto& samples = powerlist.getPowerListItems();
	if(!samples.size())
	{
		return nullptr; // No samples to choose from.
	}

	int retry = settings.sample_selection_retry_count.load();

	Sample* sample{nullptr};

	auto power_max = powerlist.getMaxPower();
	auto power_min = powerlist.getMinPower();
	float power_span = power_max - power_min;

	// Width is limited to at least 10. Fixes problem with instrument with a
	//  sample set smaller than MIN_SAMPLE_SET_SIZE.
	float width = std::max(samples.size(), MIN_SAMPLE_SET_SIZE);

	// Spread out at most ~2 samples away from center if all samples have a
	// uniform distribution over the power spectrum (which they probably don't).
	float mean_stepwidth = power_span / width;

	// Cut off mean value with stddev/2 in both ends in order to make room for
	//  downwards expansion on velocity 0 and upwards expansion on velocity 1.
	float mean = level * (power_span - mean_stepwidth) + (mean_stepwidth / 2.0);
	float stddev = velocity_stddev * mean_stepwidth;

	std::size_t index{0};
	float power{0.f};

	// note: loop is executed once + #retry
	do
	{
		--retry;

		// Select normal distributed value between
		//  (stddev/2) and (power_span-stddev/2)
		float lvl = rand.normalDistribution(mean, stddev);

		// Adjust this value to be in range
		//  (power_min+stddev/2) and (power_max-stddev/2)
		lvl += power_min;

		DEBUG(rand,
			  "level: %f, lvl: %f (mean: %.2f, stddev: %.2f, mean_stepwidth: %f, power_min: %f, power_max: %f)\n",
			  level, lvl, mean, stddev, mean_stepwidth, power_min, power_max);

		for (std::size_t i = 0; i < samples.size(); ++i)
		{
			auto const& item = samples[i];
			if (sample == nullptr || std::fabs(item.power - lvl) < std::fabs(power - lvl))
			{
				sample = item.sample;
				index = i;
				power = item.power;
			}
		}
	} while (lastsample == sample && retry >= 0);

	DEBUG(rand, "Chose sample with index: %d, power %f", (int)index, power);

	lastsample = sample;
	return sample;
}

const Sample* SampleSelection::getObjective(level_t level, std::size_t pos)
{
	auto velocity_stddev = settings.velocity_stddev.load();

	const auto& samples = powerlist.getPowerListItems();
	if(!samples.size())
	{
		return nullptr; // No samples to choose from.
	}

	auto power_max = powerlist.getMaxPower();
	auto power_min = powerlist.getMinPower();
	float power_span = power_max - power_min;

	// Width is limited to at least 10. Fixes problem with instrument with a
	// sample set smaller than MIN_SAMPLE_SET_SIZE.
	float width = std::max(samples.size(), MIN_SAMPLE_SET_SIZE);

	// Spread out at most ~2 samples away from center if all samples have a
	// uniform distribution over the power spectrum (which they probably don't).
	float mean_stepwidth = power_span / width;

	// Cut off mean value with stddev/2 in both ends in order to make room for
	// downwards expansion on velocity 0 and upwards expansion on velocity 1.
	float mean = level * (power_span - mean_stepwidth) + (mean_stepwidth / 2.0);
	float stddev = settings.enable_velocity_modifier.load() ? velocity_stddev * mean_stepwidth : 0.;

	std::size_t index_opt = 0;
	float power_opt{0.f};
	float value_opt{std::numeric_limits<float>::max()};
	// TODO: those are mostly for debugging at the moment
	float random_opt = 0.;
	float distance_opt = 0.;
	float recent_opt = 0.;

	// Select normal distributed value between
	// (stddev/2) and (power_span-stddev/2)
	float lvl = rand.normalDistribution(mean, stddev);

	// Adjust this value to be in range
	// (power_min+stddev/2) and (power_max-stddev/2)
	lvl += power_min;

	DEBUG(rand, "level: %f, lvl: %f (mean: %.2f, stddev: %.2f, mean_stepwidth: %f,"
		"power_min: %f, power_max: %f)\n", level, lvl, mean, stddev, mean_stepwidth,
		power_min, power_max);

	// TODO: expose parameters to GUI
	float alpha = 2.0;
	float beta = 1.0;
	float gamma = .5;

	// TODO: start with most promising power value and then stop when reaching far values
	// which cannot become opt anymore
	for (std::size_t i = 0; i < samples.size(); ++i)
	{
		auto const& item = samples[i];

		// compute objective function value
		auto random = rand.floatInRange(0.,1.);
		auto distance = item.power - lvl;
		auto recent = (float)settings.samplerate/std::max<std::size_t>(pos - last[i], 1);
		auto value = alpha*pow2(distance) + beta*pow2(recent) + gamma*random;

		if (value < value_opt)
		{
			index_opt = i;
			power_opt = item.power;
			value_opt = value;
			random_opt = random;
			distance_opt = distance;
			recent_opt = recent;
		}
	}

	DEBUG(rand, "Chose sample with index: %d, value: %f, power %f, random: %f, distance: %f, recent: %f", (int)index_opt, value_opt, power_opt, random_opt, distance_opt, recent_opt);

	last[index_opt] = pos;
	return samples[index_opt].sample;
}