- Timestamp:
- 07/21/11 16:40:10 (13 years ago)
- File:
-
- 1 edited
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trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs
r6583 r6584 190 190 191 191 #region persistence 192 // not implemented yet 192 [Storable] 193 public double KDTreeApproxF { 194 get { return kdTree.approxf; } 195 set { kdTree.approxf = value; } 196 } 197 [Storable] 198 public double[] KDTreeBoxMax { 199 get { return kdTree.boxmax; } 200 set { kdTree.boxmax = value; } 201 } 202 [Storable] 203 public double[] KDTreeBoxMin { 204 get { return kdTree.boxmin; } 205 set { kdTree.boxmin = value; } 206 } 207 [Storable] 208 public double[] KDTreeBuf { 209 get { return kdTree.buf; } 210 set { kdTree.buf = value; } 211 } 212 [Storable] 213 public double[] KDTreeCurBoxMax { 214 get { return kdTree.curboxmax; } 215 set { kdTree.curboxmax = value; } 216 } 217 [Storable] 218 public double[] KDTreeCurBoxMin { 219 get { return kdTree.curboxmin; } 220 set { kdTree.curboxmin = value; } 221 } 222 [Storable] 223 public double KDTreeCurDist { 224 get { return kdTree.curdist; } 225 set { kdTree.curdist = value; } 226 } 227 [Storable] 228 public int KDTreeDebugCounter { 229 get { return kdTree.debugcounter; } 230 set { kdTree.debugcounter = value; } 231 } 232 [Storable] 233 public int KDTreeDistMatrixType { 234 get { return kdTree.distmatrixtype; } 235 set { kdTree.distmatrixtype = value; } 236 } 237 [Storable] 238 public int[] KDTreeIdx { 239 get { return kdTree.idx; } 240 set { kdTree.idx = value; } 241 } 242 [Storable] 243 public int KDTreeKCur { 244 get { return kdTree.kcur; } 245 set { kdTree.kcur = value; } 246 } 247 [Storable] 248 public int KDTreeKNeeded { 249 get { return kdTree.kneeded; } 250 set { kdTree.kneeded = value; } 251 } 252 [Storable] 253 public int KDTreeN { 254 get { return kdTree.n; } 255 set { kdTree.n = value; } 256 } 257 [Storable] 258 public int[] KDTreeNodes { 259 get { return kdTree.nodes; } 260 set { kdTree.nodes = value; } 261 } 262 [Storable] 263 public int KDTreeNormType { 264 get { return kdTree.normtype; } 265 set { kdTree.normtype = value; } 266 } 267 [Storable] 268 public int KDTreeNX { 269 get { return kdTree.nx; } 270 set { kdTree.nx = value; } 271 } 272 [Storable] 273 public int KDTreeNY { 274 get { return kdTree.ny; } 275 set { kdTree.ny = value; } 276 } 277 [Storable] 278 public double[] KDTreeR { 279 get { return kdTree.r; } 280 set { kdTree.r = value; } 281 } 282 [Storable] 283 public double KDTreeRNeeded { 284 get { return kdTree.rneeded; } 285 set { kdTree.rneeded = value; } 286 } 287 [Storable] 288 public bool KDTreeSelfMatch { 289 get { return kdTree.selfmatch; } 290 set { kdTree.selfmatch = value; } 291 } 292 [Storable] 293 public double[] KDTreeSplits { 294 get { return kdTree.splits; } 295 set { kdTree.splits = value; } 296 } 297 [Storable] 298 public int[] KDTreeTags { 299 get { return kdTree.tags; } 300 set { kdTree.tags = value; } 301 } 302 [Storable] 303 public double[] KDTreeX { 304 get { return kdTree.x; } 305 set { kdTree.x = value; } 306 } 307 [Storable] 308 public double[,] KDTreeXY { 309 get { return kdTree.xy; } 310 set { kdTree.xy = value; } 311 } 193 312 #endregion 194 313 }
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