This file is indexed.

/usr/include/shogun/distance/CustomDistance.h is in libshogun-dev 3.2.0-7.3build4.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  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
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 1999-2009 Soeren Sonnenburg
 * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
 */

#ifndef _CUSTOMDISTANCE_H___
#define _CUSTOMDISTANCE_H___

#include <shogun/mathematics/Math.h>
#include <shogun/lib/common.h>
#include <shogun/distance/Distance.h>
#include <shogun/features/Features.h>

namespace shogun
{
/** @brief The Custom Distance allows for custom user provided distance matrices.
 *
 * For squared training matrices it allows to store only the upper triangle of
 * the distance to save memory: Full symmetric distance matrices can be stored as
 * is or can be internally converted into (or directly given in) upper triangle
 * representation. Also note that values are stored as 32bit floats.
 *
 */
class CCustomDistance: public CDistance
{
	public:
		/** default constructor */
		CCustomDistance();

		/** constructor
		 *
		 * compute custom distance from given distance matrix
		 * @param d distance matrix
		 */
		CCustomDistance(CDistance* d);

		/** constructor
		 * @param distance_matrix distance matrix
		 */
		CCustomDistance(const SGMatrix<float64_t> distance_matrix);

		/** constructor
		 *
		 * sets full distance matrix from full distance matrix
		 * (from double precision floats)
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		CCustomDistance(
			const float64_t* dm, int32_t rows, int32_t cols);

		/** constructor
		 *
		 * sets full distance matrix from full distance matrix
		 * (from single precision floats)
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		CCustomDistance(
			const float32_t* dm, int32_t rows, int32_t cols);

		virtual ~CCustomDistance();

		/** initialize distance with dummy features
		 *
		 * Distances always need feature objects assigned. As the custom distance
		 * does not really require this it creates some magic dummy features
		 * that only know about the number of vectors
		 *
		 * @param rows features of left-hand side
		 * @param cols features of right-hand side
		 * @return if initializing was successful
		 */
		virtual bool dummy_init(int32_t rows, int32_t cols);

		/** initialize distance
		 *
		 * @param l features of left-hand side
		 * @param r features of right-hand side
		 * @return if initializing was successful
		 */
		virtual bool init(CFeatures* l, CFeatures* r);

		/** clean up distance */
		virtual void cleanup();

		/** return what type of distance we are
		 *
		 * @return distance type CUSTOM
		 */
		virtual EDistanceType get_distance_type() { return D_CUSTOM; }

		/** return feature type the distance can deal with
		 *
		 * @return feature type ANY
		 */
		virtual EFeatureType get_feature_type() { return F_ANY; }

		/** return feature class the distance can deal with
		 *
		 * @return feature class ANY
		 */
		virtual EFeatureClass get_feature_class() { return C_ANY; }

		/** return the distance's name
		 *
		 * @return name Custom
		 */
		virtual const char* get_name() const { return "CustomDistance"; }

		/** set distance matrix (only elements from upper triangle)
		 * from elements of upper triangle (concat'd), including the
		 * main diagonal
		 *
		 * small variant for floats64's, triangle needs to have less than 2**32 elements
		 *
		 * @param dm distance matrix
		 * @param len denotes the size of the array and should match len=cols*(cols+1)/2
		 * @return if setting was successful
		 */
		bool set_triangle_distance_matrix_from_triangle(
			const float64_t* dm, int32_t len)
		{
			return set_triangle_distance_matrix_from_triangle_generic(dm, len);
		}

		/** set distance matrix (only elements from upper triangle)
		 * from elements of upper triangle (concat'd), including the
		 * main diagonal
		 *
		 * small variant for floats32's, triangle needs to have less than 2**32 elements
		 *
		 * @param dm distance matrix
		 * @param len denotes the size of the array and should match len=cols*(cols+1)/2
		 * @return if setting was successful
		 */
		bool set_triangle_distance_matrix_from_triangle(
			const float32_t* dm, int32_t len)
		{
			return set_triangle_distance_matrix_from_triangle_generic(dm, len);
		}

		/** set distance matrix (only elements from upper triangle)
		 * from elements of upper triangle (concat'd), including the
		 * main diagonal
		 *
		 * big variant, allowing the triangle to have more than 2**31-1 elements
		 *
		 * @param dm distance matrix
		 * @param len denotes the size of the array and should match len=cols*(cols+1)/2
		 * @return if setting was successful
		 */
		template <class T>
		bool set_triangle_distance_matrix_from_triangle_generic(
			const T* dm, int64_t len)
		{
			ASSERT(dm)
			ASSERT(len>0)

			int64_t cols = (int64_t) floor(-0.5 + CMath::sqrt(0.25+2*len));

			int64_t int32_max=2147483647;

			if (cols> int32_max)
				SG_ERROR("Matrix larger than %d x %d\n", int32_max)

			if (cols*(cols+1)/2 != len)
			{
				SG_ERROR("dm should be a vector containing a lower triangle matrix, with len=cols*(cols+1)/2 elements\n")
				return false;
			}

			cleanup_custom();
			SG_DEBUG("using custom distance of size %dx%d\n", cols,cols)

			dmatrix= SG_MALLOC(float32_t, len);

			upper_diagonal=true;
			num_rows=cols;
			num_cols=cols;

			for (int64_t i=0; i<len; i++)
				dmatrix[i]=dm[i];

			dummy_init(num_rows, num_cols);
			return true;
		}

		/** set distance matrix (only elements from upper triangle)
		 * from squared matrix
		 *
		 * for float64's
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		inline bool set_triangle_distance_matrix_from_full(
			const float64_t* dm, int32_t rows, int32_t cols)
		{
			return set_triangle_distance_matrix_from_full_generic(dm, rows, cols);
		}

		/** set distance matrix (only elements from upper triangle)
		 * from squared matrix
		 *
		 * for float32's
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		inline bool set_triangle_distance_matrix_from_full(
			const float32_t* dm, int32_t rows, int32_t cols)
		{
			return set_triangle_distance_matrix_from_full_generic(dm, rows, cols);
		}

		/** set distance matrix (only elements from upper triangle)
		 * from squared matrix
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		template <class T>
		bool set_triangle_distance_matrix_from_full_generic(
			const T* dm, int32_t rows, int32_t cols)
		{
			ASSERT(rows==cols)

			cleanup_custom();
			SG_DEBUG("using custom distance of size %dx%d\n", cols,cols)

			dmatrix= SG_MALLOC(float32_t, int64_t(cols)*(cols+1)/2);

			upper_diagonal=true;
			num_rows=cols;
			num_cols=cols;

			for (int64_t row=0; row<num_rows; row++)
			{
				for (int64_t col=row; col<num_cols; col++)
				{
					int64_t idx=row * num_cols - row*(row+1)/2 + col;
					dmatrix[idx]= (float32_t) dm[col*num_rows+row];
				}
			}
			dummy_init(rows, cols);
			return true;
		}

		/** set full distance matrix from full distance matrix
		 *
		 * for float64's
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		bool set_full_distance_matrix_from_full(
			const float64_t* dm, int32_t rows, int32_t cols)
		{
			return set_full_distance_matrix_from_full_generic(dm, rows, cols);
		}

		/** set full distance matrix from full distance matrix
		 *
		 * for float32's
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		bool set_full_distance_matrix_from_full(
			const float32_t* dm, int32_t rows, int32_t cols)
		{
			return set_full_distance_matrix_from_full_generic(dm, rows, cols);
		}

		/** set full distance matrix from full distance matrix
		 *
		 * @param dm distance matrix
		 * @param rows number of rows in matrix
		 * @param cols number of cols in matrix
		 * @return if setting was successful
		 */
		template <class T>
		bool set_full_distance_matrix_from_full_generic(const T* dm, int32_t rows, int32_t cols)
		{
			cleanup_custom();
			SG_DEBUG("using custom distance of size %dx%d\n", rows,cols)

			dmatrix=SG_MALLOC(float32_t, rows*cols);

			upper_diagonal=false;
			num_rows=rows;
			num_cols=cols;

			for (int32_t row=0; row<num_rows; row++)
			{
				for (int32_t col=0; col<num_cols; col++)
				{
					dmatrix[row * num_cols + col]=dm[col*num_rows+row];
				}
			}

			dummy_init(rows, cols);
			return true;
		}

		/** get number of vectors of lhs features
		 *
		 * @return number of vectors of left-hand side
		 */
		virtual int32_t get_num_vec_lhs()
		{
			return num_rows;
		}

		/** get number of vectors of rhs features
		 *
		 * @return number of vectors of right-hand side
		 */
		virtual int32_t get_num_vec_rhs()
		{
			return num_cols;
		}

		/** test whether features have been assigned to lhs and rhs
		 *
		 * @return true if features are assigned
		 */
		virtual bool has_features()
		{
			return (num_rows>0) && (num_cols>0);
		}

	protected:
		/** compute distance function
		 *
		 * @param row row
		 * @param col col
		 * @return computed distance function
		 */
		virtual float64_t compute(int32_t row, int32_t col);

	private:
		void init();

		/** only cleanup stuff specific to Custom distance */
		void cleanup_custom();

	protected:
		/** distance matrix */
		float32_t* dmatrix;
		/** number of rows */
		int32_t num_rows;
		/** number of columns */
		int32_t num_cols;
		/** upper diagonal */
		bool upper_diagonal;
};

}
#endif /* _CUSTOMKERNEL_H__ */