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
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
|
package de.lmu.ifi.dbs.elki.data;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2014
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program 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 Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
import java.io.IOException;
import java.nio.ByteBuffer;
import de.lmu.ifi.dbs.elki.math.linearalgebra.Vector;
import de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayAdapter;
import de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil;
import de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.NumberArrayAdapter;
import de.lmu.ifi.dbs.elki.utilities.io.ByteArrayUtil;
import de.lmu.ifi.dbs.elki.utilities.io.ByteBufferSerializer;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
/**
* Vector type using {@code float[]} storage, thus needing approximately half as
* much memory as {@link DoubleVector}.
*
* @author Elke Achtert
*/
public class FloatVector extends AbstractNumberVector {
/**
* Static factory instance.
*/
public static final FloatVector.Factory FACTORY = new FloatVector.Factory();
/**
* Serializer for up to 127 dimensions.
*/
public static final ByteBufferSerializer<FloatVector> BYTE_SERIALIZER = new SmallSerializer();
/**
* Serializer for up to 2^15-1 dimensions.
*/
public static final ByteBufferSerializer<FloatVector> SHORT_SERIALIZER = new ShortSerializer();
/**
* Serializer using varint encoding.
*/
public static final ByteBufferSerializer<FloatVector> VARIABLE_SERIALIZER = new VariableSerializer();
/**
* Keeps the values of the float vector.
*/
private final float[] values;
/**
* Private constructor. NOT for public use.
*
* @param values Data values
* @param nocopy Flag to re-use the values array
*/
private FloatVector(float[] values, boolean nocopy) {
this.values = nocopy ? values : values.clone();
}
/**
* Create a FloatVector consisting of the given float values.
*
* @param values the values to be set as values of the float vector
*/
public FloatVector(float[] values) {
this.values = values.clone();
}
/**
* Expects a matrix of one column.
*
* @param columnMatrix a matrix of one column
*/
public FloatVector(Vector columnMatrix) {
final double[] src = columnMatrix.getArrayRef();
values = new float[src.length];
for(int i = 0; i < src.length; i++) {
values[i] = (float) src[i];
}
}
@Override
public int getDimensionality() {
return values.length;
}
@Deprecated
@Override
public Float getValue(int dimension) {
return values[dimension];
}
@Override
public double doubleValue(int dimension) {
return values[dimension];
}
@Override
public long longValue(int dimension) {
return (long) values[dimension];
}
@Override
public Vector getColumnVector() {
return new Vector(ArrayLikeUtil.toPrimitiveDoubleArray(values, ArrayLikeUtil.FLOATARRAYADAPTER));
}
@Override
public String toString() {
StringBuilder featureLine = new StringBuilder();
for(int i = 0; i < values.length; i++) {
featureLine.append(values[i]);
if(i + 1 < values.length) {
featureLine.append(ATTRIBUTE_SEPARATOR);
}
}
return featureLine.toString();
}
/**
* Factory for float vectors.
*
* @author Erich Schubert
*
* @apiviz.has FloatVector
*/
public static class Factory extends AbstractNumberVector.Factory<FloatVector> {
@Override
public <A> FloatVector newFeatureVector(A array, ArrayAdapter<? extends Number, A> adapter) {
int dim = adapter.size(array);
float[] values = new float[dim];
for(int i = 0; i < dim; i++) {
values[i] = adapter.get(array, i).floatValue();
}
return new FloatVector(values, true);
}
@Override
public <A> FloatVector newNumberVector(A array, NumberArrayAdapter<?, ? super A> adapter) {
int dim = adapter.size(array);
float[] values = new float[dim];
for(int i = 0; i < dim; i++) {
values[i] = adapter.getFloat(array, i);
}
return new FloatVector(values, true);
}
@Override
public ByteBufferSerializer<FloatVector> getDefaultSerializer() {
return VARIABLE_SERIALIZER;
}
@Override
public Class<? super FloatVector> getRestrictionClass() {
return FloatVector.class;
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractParameterizer {
@Override
protected FloatVector.Factory makeInstance() {
return FACTORY;
}
}
}
/**
* Serialization class for dense float vectors with up to 127 dimensions, by
* using a byte for storing the dimensionality.
*
* @author Erich Schubert
*
* @apiviz.uses FloatVector - - «serializes»
*/
public static class SmallSerializer implements ByteBufferSerializer<FloatVector> {
@Override
public FloatVector fromByteBuffer(ByteBuffer buffer) throws IOException {
final byte dimensionality = buffer.get();
assert (buffer.remaining() >= ByteArrayUtil.SIZE_FLOAT * dimensionality);
final float[] values = new float[dimensionality];
for(int i = 0; i < dimensionality; i++) {
values[i] = buffer.getFloat();
}
return new FloatVector(values, true);
}
@Override
public void toByteBuffer(ByteBuffer buffer, FloatVector vec) throws IOException {
assert (vec.values.length < Byte.MAX_VALUE) : "This serializer only supports a maximum dimensionality of " + Byte.MAX_VALUE + "!";
assert (buffer.remaining() >= ByteArrayUtil.SIZE_FLOAT * vec.values.length);
buffer.put((byte) vec.values.length);
for(int i = 0; i < vec.values.length; i++) {
buffer.putFloat(vec.values[i]);
}
}
@Override
public int getByteSize(FloatVector vec) {
assert (vec.values.length < Byte.MAX_VALUE) : "This serializer only supports a maximum dimensionality of " + Byte.MAX_VALUE + "!";
return ByteArrayUtil.SIZE_BYTE + ByteArrayUtil.SIZE_FLOAT * vec.getDimensionality();
}
}
/**
* Serialization class for dense float vectors with up to
* {@link Short#MAX_VALUE} dimensions, by using a short for storing the
* dimensionality.
*
* @author Erich Schubert
*
* @apiviz.uses FloatVector - - «serializes»
*/
public static class ShortSerializer implements ByteBufferSerializer<FloatVector> {
@Override
public FloatVector fromByteBuffer(ByteBuffer buffer) throws IOException {
final short dimensionality = buffer.getShort();
assert (buffer.remaining() >= ByteArrayUtil.SIZE_FLOAT * dimensionality);
final float[] values = new float[dimensionality];
for(int i = 0; i < dimensionality; i++) {
values[i] = buffer.getFloat();
}
return new FloatVector(values, true);
}
@Override
public void toByteBuffer(ByteBuffer buffer, FloatVector vec) throws IOException {
assert (vec.values.length < Short.MAX_VALUE) : "This serializer only supports a maximum dimensionality of " + Short.MAX_VALUE + "!";
assert (buffer.remaining() >= ByteArrayUtil.SIZE_FLOAT * vec.values.length);
buffer.putShort((short) vec.values.length);
for(int i = 0; i < vec.values.length; i++) {
buffer.putFloat(vec.values[i]);
}
}
@Override
public int getByteSize(FloatVector vec) {
assert (vec.values.length < Short.MAX_VALUE) : "This serializer only supports a maximum dimensionality of " + Short.MAX_VALUE + "!";
return ByteArrayUtil.SIZE_SHORT + ByteArrayUtil.SIZE_FLOAT * vec.getDimensionality();
}
}
/**
* Serialization class for variable dimensionality by using VarInt encoding.
*
* @author Erich Schubert
*
* @apiviz.uses FloatVector - - «serializes»
*/
public static class VariableSerializer implements ByteBufferSerializer<FloatVector> {
@Override
public FloatVector fromByteBuffer(ByteBuffer buffer) throws IOException {
final int dimensionality = ByteArrayUtil.readUnsignedVarint(buffer);
assert (buffer.remaining() >= ByteArrayUtil.SIZE_FLOAT * dimensionality);
final float[] values = new float[dimensionality];
for(int i = 0; i < dimensionality; i++) {
values[i] = buffer.getFloat();
}
return new FloatVector(values, true);
}
@Override
public void toByteBuffer(ByteBuffer buffer, FloatVector vec) throws IOException {
assert (vec.values.length < Short.MAX_VALUE) : "This serializer only supports a maximum dimensionality of " + Short.MAX_VALUE + "!";
assert (buffer.remaining() >= ByteArrayUtil.SIZE_FLOAT * vec.values.length);
ByteArrayUtil.writeUnsignedVarint(buffer, vec.values.length);
for(int i = 0; i < vec.values.length; i++) {
buffer.putFloat(vec.values[i]);
}
}
@Override
public int getByteSize(FloatVector vec) {
assert (vec.values.length < Short.MAX_VALUE) : "This serializer only supports a maximum dimensionality of " + Short.MAX_VALUE + "!";
return ByteArrayUtil.getUnsignedVarintSize(vec.values.length) + ByteArrayUtil.SIZE_FLOAT * vec.values.length;
}
}
}
|