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
|
/* -*- 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"
#include <algorithm>
namespace
{
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)
{
}
void SampleSelection::finalise()
{
last.assign(powerlist.getPowerListItems().size(), 0);
}
// FIXME: For the position, weird hacks via the powerlist are necessary. Refactor!
// FIXME: bad variable naming
const Sample* SampleSelection::get(level_t level, float position, std::size_t pos)
{
const auto& samples = powerlist.getPowerListItems();
if(!samples.size())
{
return nullptr; // No samples to choose from.
}
std::size_t index_opt = 0;
float power_opt{0.f};
float pos_opt{0.f};
float value_opt{std::numeric_limits<float>::max()};
// the following three values are mostly for debugging
float random_opt = 0.;
float close_opt = 0.;
float diverse_opt = 0.;
float closepos_opt = 0.;
// Note the magic values in front of the settings factors.
const float f_close = 4.*settings.sample_selection_f_close.load();
const float f_diverse = (1./2.)*settings.sample_selection_f_diverse.load();
const float f_random = (1./3.)*settings.sample_selection_f_random.load();
const float f_position = 1000.; // FIXME: get from settings
float power_range = powerlist.getMaxPower() - powerlist.getMinPower();
// If all power values are the same then power_range is invalid but we want
// to avoid division by zero.
if (power_range == 0.) { power_range = 1.0; }
// start with most promising power value and then stop when reaching far values
// which cannot become opt anymore
auto closest_it = std::lower_bound(samples.begin(), samples.end(), level);
std::size_t up_index = std::distance(samples.begin(), closest_it);
std::size_t down_index = (up_index == 0 ? 0 : up_index - 1);
float up_value_lb;
if (up_index < samples.size()) {
auto const close_up = (samples[up_index].power-level)/power_range;
up_value_lb = f_close*pow2(close_up);
}
else {
--up_index;
up_value_lb = std::numeric_limits<float>::max();
}
auto const close_down = (samples[down_index].power-level)/power_range;
float down_value_lb = (up_index != 0 ? f_close*pow2(close_down) : std::numeric_limits<float>::max());
std::size_t count = 0;
do
{
DEBUG(rand, "%d %d", (int)up_index, (int)down_index);
assert(down_index <= up_index);
std::size_t current_index;
if (up_value_lb < down_value_lb)
{
current_index = up_index;
if (up_index != samples.size()-1)
{
++up_index;
up_value_lb = f_close*pow2((samples[up_index].power-level)/power_range);
}
else
{
up_value_lb = std::numeric_limits<float>::max();
}
}
else
{
current_index = down_index;
if (down_index != 0)
{
--down_index;
down_value_lb = f_close*pow2((samples[down_index].power-level)/power_range);
}
else
{
down_value_lb = std::numeric_limits<float>::max();
}
}
auto random = rand.floatInRange(0.,1.);
auto close = (samples[current_index].power - level)/power_range;
auto diverse = 1./(1. + (float)(pos - last[current_index])/settings.samplerate);
auto closepos = samples[current_index].sample->getPosition() - position;
// note that the value below for close and closepos is actually the weighted squared l2 distance in 2d
auto value = f_close*pow2(close) + f_position*pow2(closepos) + f_diverse*diverse + f_random*random;
if (value < value_opt)
{
index_opt = current_index;
power_opt = samples[current_index].power;
pos_opt = samples[current_index].sample->getPosition();
value_opt = value;
random_opt = random;
close_opt = close;
diverse_opt = diverse;
closepos_opt = closepos;
}
++count;
}
while (up_value_lb <= value_opt || down_value_lb <= value_opt);
DEBUG(rand, "Chose sample with index: %d, value: %f, power: %f, position: %f, random: %f, close: %f, diverse: %f, closepos: %f, count: %d", (int)index_opt, value_opt, power_opt, pos_opt, random_opt, close_opt, diverse_opt, closepos_opt, (int)count);
last[index_opt] = pos;
return samples[index_opt].sample;
}
|
