PLearn 0.1
plearn_exp.cc
Go to the documentation of this file.
00001 // -*- C++ -*-
00002 
00003 // plearn.cc
00004 // Copyright (C) 2002 Pascal Vincent, Julien Keable, Xavier Saint-Mleux, Rejean Ducharme
00005 //
00006 // Redistribution and use in source and binary forms, with or without
00007 // modification, are permitted provided that the following conditions are met:
00008 // 
00009 //  1. Redistributions of source code must retain the above copyright
00010 //     notice, this list of conditions and the following disclaimer.
00011 // 
00012 //  2. Redistributions in binary form must reproduce the above copyright
00013 //     notice, this list of conditions and the following disclaimer in the
00014 //     documentation and/or other materials provided with the distribution.
00015 // 
00016 //  3. The name of the authors may not be used to endorse or promote
00017 //     products derived from this software without specific prior written
00018 //     permission.
00019 // 
00020 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00021 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00022 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00023 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00024 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00025 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00026 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00027 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00028 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00029 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00030 // 
00031 // This file is part of the PLearn library. For more information on the PLearn
00032 // library, go to the PLearn Web site at www.plearn.org
00033 
00034 
00035 /* *******************************************************      
00036  * $Id: plearn_light.cc 3995 2005-08-25 13:58:23Z chapados $
00037  ******************************************************* */
00038 
00040 #include <commands/plearn_version.h>
00041 #include <commands/PLearnCommands/plearn_main.h>
00042 
00043 
00044 /*****************
00045  * Miscellaneous *
00046  *****************/
00047 // #include <plearn/db/UCISpecification.h>
00048 // #include <plearn/io/openUrl.h>
00049 // #include <plearn/math/ManualBinner.h>
00050 // #include <plearn/math/SoftHistogramBinner.h>
00051 // #include <plearn/misc/ShellScript.h>
00052 // #include <plearn/misc/RunObject.h>
00053 // #include <plearn_learners/misc/Grapher.h>
00054 // #include <plearn_learners/misc/VariableSelectionWithDirectedGradientDescent.h>
00055 #include <plearn_learners/testers/PTester.h>
00056 
00057 /***********
00058  * Command *
00059  ***********/
00060 #include <commands/PLearnCommands/VMatCommand.h>
00061 #include <commands/PLearnCommands/VMatViewCommand.h>
00062 // #include <commands/PLearnCommands/AutoRunCommand.h>
00063 // #include <commands/PLearnCommands/DiffCommand.h>
00064 // #include <commands/PLearnCommands/FieldConvertCommand.h>
00065 #include <commands/PLearnCommands/HelpCommand.h>
00066 // #include <commands/PLearnCommands/JulianDateCommand.h>
00067 // #include <commands/PLearnCommands/KolmogorovSmirnovCommand.h>
00068 #include <commands/PLearnCommands/LearnerCommand.h>
00069 // #include <commands/PLearnCommands/PairwiseDiffsCommand.h>
00070 #include <commands/PLearnCommands/ReadAndWriteCommand.h>
00071 #include <commands/PLearnCommands/RunCommand.h>
00072 #include <commands/PLearnCommands/ServerCommand.h>
00073 // #include <commands/PLearnCommands/TestDependenciesCommand.h>
00074 // #include <commands/PLearnCommands/TestDependencyCommand.h>
00075 
00076 // * extra stuff from Boost to generate help *
00077 // #include <commands/PLearnCommands/HTMLHelpCommand.h>
00078 
00079 // //#include <commands/PLearnCommands/TxtmatCommand.h>
00080 #include <commands/PLearnCommands/VerifyGradientCommand.h>
00081 #include <commands/PLearnCommands/ExtractOptionCommand.h>
00082 
00083 // /**************
00084 //  * Dictionary *
00085 //  **************/
00086 // #include <plearn/dict/Dictionary.h>
00087 // #include <plearn/dict/FileDictionary.h>
00088 // #include <plearn/dict/VecDictionary.h>
00089 // #include <plearn/dict/ConditionalDictionary.h>
00090 
00091 // /****************
00092 //  * HyperCommand *
00093 //  ****************/
00094 #include <plearn_learners/hyper/HyperOptimize.h>
00095 #include <plearn_learners/hyper/HyperRetrain.h>
00096 #include <plearn_learners/hyper/HyperSetOption.h>
00097 
00098 // /**********
00099 //  * Kernel *
00100 //  **********/
00101 // #include <plearn/ker/AdditiveNormalizationKernel.h>
00102 // #include <plearn/ker/DistanceKernel.h>
00103 // #include <plearn/ker/DotProductKernel.h>
00104 // #include <plearn/ker/EpanechnikovKernel.h>
00105 // #include <plearn/ker/GaussianKernel.h>
00106 // #include <plearn/ker/GeodesicDistanceKernel.h>
00107 // #include <plearn/ker/IIDNoiseKernel.h>
00108 // #include <plearn/ker/NegOutputCostFunction.h>
00109 // #include <plearn/ker/NeuralNetworkARDKernel.h>
00110 // #include <plearn/ker/PolynomialKernel.h>
00111 // #include <plearn/ker/RationalQuadraticARDKernel.h>
00112 // #include <plearn/ker/SquaredExponentialARDKernel.h>
00113 // #include <plearn/ker/SummationKernel.h>
00114 // #include <plearn/ker/ThresholdedKernel.h>
00115 // #include <plearn/ker/VMatKernel.h>
00116 
00117 // /*************
00118 //  * Optimizer *
00119 //  *************/
00120 // #include <plearn/opt/AdaptGradientOptimizer.h>
00121 // #include <plearn/opt/ConjGradientOptimizer.h>
00122 #include <plearn/opt/GradientOptimizer.h>
00123 #include <plearn/opt/EXPERIMENTAL/AutoScaledGradientOptimizer.h>
00124 
00125 // /****************
00126 //  * OptionOracle *
00127 //  ****************/
00128 // #include <plearn_learners/hyper/CartesianProductOracle.h>
00129 #include <plearn_learners/hyper/EarlyStoppingOracle.h>
00130 #include <plearn_learners/hyper/ExplicitListOracle.h>
00131 // #include <plearn_learners/hyper/OptimizeOptionOracle.h>
00132 
00133 // /************
00134 //  * PLearner *
00135 //  ************/
00136 
00137 // // Unsupervised preprocessing
00138 // #include <plearn_learners/unsupervised/UniformizeLearner.h>
00139 #include <plearn_learners/unsupervised/NormalizationLearner.h>
00140 
00141 // // Classifiers
00142 // #include <plearn_learners/classifiers/BinaryStump.h>
00143 // #include <plearn_learners/classifiers/ClassifierFromConditionalPDistribution.h>
00144 // #include <plearn_learners/classifiers/ClassifierFromDensity.h>
00145 // #include <plearn_learners/classifiers/KNNClassifier.h>
00146 // //#include <plearn_learners/classifiers/SVMClassificationTorch.h>
00147 // #include <plearn_learners/classifiers/MultiInstanceNNet.h>
00148 // //#include <plearn_learners/classifiers/OverlappingAdaBoost.h> // Does not currently compile.
00149 
00150 // // Generic
00151 // #include <plearn_learners/generic/AddCostToLearner.h>
00152 // #include <plearn_learners/generic/AddLayersNNet.h>
00153 // #include <plearn_learners/generic/BestAveragingPLearner.h>
00154 // //#include <plearn_learners/generic/DistRepNNet.h>
00155 // #include <plearn_learners/generic/NNet.h>
00156 // #include <plearn_learners/generic/SelectInputSubsetLearner.h>
00157 #include <plearn_learners/generic/ChainedLearners.h>
00158 // #include <plearn_learners/generic/StackedLearner.h>
00159 // #include <plearn_learners/generic/TestingLearner.h>
00160 // #include <plearn_learners/generic/VPLPreprocessedLearner.h>
00161 // #include <plearn_learners/generic/VPLPreprocessedLearner2.h>
00162 // #include <plearn_learners/generic/VPLCombinedLearner.h>
00163 
00164 // // Hyper
00165 #include <plearn_learners/hyper/HyperLearner.h>
00166 
00167 // // Meta
00168 // #include <plearn_learners/meta/AdaBoost.h>
00169 // #include <plearn_learners/meta/BaggingLearner.h>
00170 
00171 // // Regressors
00172 // #include <plearn_learners/regressors/ConstantRegressor.h>
00173 // #include <plearn_learners/regressors/GaussianProcessRegressor.h>
00174 // #include <plearn_learners/regressors/KernelRidgeRegressor.h>
00175 // #include <plearn_learners/regressors/KNNRegressor.h>
00176 // #include <plearn_learners/regressors/RankLearner.h>
00177 // #include <plearn_learners/regressors/RegressorFromDistribution.h>
00178 
00179 // // PDistribution
00180 // #include <plearn_learners/distributions/SpiralDistribution.h>
00181 // #include <plearn_learners/distributions/UniformDistribution.h>
00182 
00183 // // Nearest-Neighbors
00184 // #include <plearn_learners/nearest_neighbors/BallTreeNearestNeighbors.h>
00185 // #include <plearn_learners/nearest_neighbors/ExhaustiveNearestNeighbors.h>
00186 // #include <plearn_learners/nearest_neighbors/GenericNearestNeighbors.h>
00187 
00188 // // Experimental
00189 // #include <plearn_learners_experimental/DeepFeatureExtractorNNet.h>
00190 
00191 // // Online
00192 // #include <plearn_learners/online/BackConvolution2DModule.h>
00193 // #include <plearn_learners/online/ClassErrorCostModule.h>
00194 // #include <plearn_learners/online/CombiningCostsModule.h>
00195 // #include <plearn_learners/online/Convolution2DModule.h>
00196 // #include <plearn_learners/online/CostModule.h>
00197 // #include <plearn_learners/online/DeepBeliefNet.h>
00198 // #include <plearn_learners/online/GradNNetLayerModule.h>
00199 // #include <plearn_learners/online/ModulesLearner.h>
00200 // #include <plearn_learners/online/ModuleStackModule.h>
00201 // #include <plearn_learners/online/NLLCostModule.h>
00202 // #include <plearn_learners/online/OnlineLearningModule.h>
00203 // #include <plearn_learners/online/ProcessInputCostModule.h>
00204 // #include <plearn_learners/online/RBMBinomialLayer.h>
00205 // #include <plearn_learners/online/RBMClassificationModule.h>
00206 // #include <plearn_learners/online/RBMConnection.h>
00207 // #include <plearn_learners/online/RBMConv2DConnection.h>
00208 // #include <plearn_learners/online/RBMGaussianLayer.h>
00209 // #include <plearn_learners/online/RBMLayer.h>
00210 // #include <plearn_learners/online/RBMMatrixConnection.h>
00211 // #include <plearn_learners/online/RBMMatrixTransposeConnection.h>
00212 // #include <plearn_learners/online/RBMMixedConnection.h>
00213 // #include <plearn_learners/online/RBMMixedLayer.h>
00214 // #include <plearn_learners/online/RBMMultinomialLayer.h>
00215 // #include <plearn_learners/online/RBMTruncExpLayer.h>
00216 // #include <plearn_learners/online/SoftmaxModule.h>
00217 // #include <plearn_learners/online/SquaredErrorCostModule.h>
00218 // #include <plearn_learners/online/StackedAutoassociatorsNet.h>
00219 // #include <plearn_learners/online/Subsampling2DModule.h>
00220 // #include <plearn_learners/online/Supersampling2DModule.h>
00221 // #include <plearn_learners/online/TanhModule.h>
00222 
00223 // /************
00224 //  * Splitter *
00225 //  ************/
00226 // #include <plearn/vmat/BinSplitter.h>
00227 // #include <plearn/vmat/BootstrapSplitter.h>
00228 // #include <plearn/vmat/ClassSeparationSplitter.h>
00229 // #include <plearn/vmat/ConcatSetsSplitter.h>
00230 // #include <plearn/vmat/DBSplitter.h>
00231 #include <plearn/vmat/ExplicitSplitter.h>
00232 // #include <plearn/vmat/FilterSplitter.h>
00233 #include <plearn/vmat/FractionSplitter.h>
00234 // #include <plearn/vmat/KFoldSplitter.h>
00235 #include <plearn/vmat/NoSplitSplitter.h>
00236 // #include <plearn/vmat/MultiTaskSeparationSplitter.h>
00237 // #include <plearn/vmat/RepeatSplitter.h>
00238 // #include <plearn/vmat/SourceVMatrixSplitter.h>
00239 // #include <plearn/vmat/StackedSplitter.h>
00240 // #include <plearn/vmat/TestInTrainSplitter.h>
00241 // #include <plearn/vmat/ToBagSplitter.h>
00242 #include <plearn/vmat/TrainTestSplitter.h>
00243 // #include <plearn/vmat/TrainValidTestSplitter.h>
00244 
00245 // /************
00246 //  * Variable *
00247 //  ************/
00248 // #include <plearn/var/MatrixElementsVariable.h>
00249 
00250 // /*********************
00251 //  * VecStatsCollector *
00252 //  *********************/
00253 // #include <plearn/math/LiftStatsCollector.h>
00254 
00255 // /***********
00256 //  * VMatrix *
00257 //  ***********/
00258 // #include <plearn/vmat/AddMissingVMatrix.h>
00259 // #include <plearn/vmat/AppendNeighborsVMatrix.h>
00260 // #include <plearn/vmat/AsciiVMatrix.h>
00261 #include <plearn/vmat/AutoVMatrix.h>
00262 // #include <plearn/vmat/BootstrapVMatrix.h>
00263 // #include <plearn/vmat/CenteredVMatrix.h>
00264 // #include <plearn/vmat/ClassSubsetVMatrix.h>
00265 // #include <plearn/vmat/CompactVMatrix.h>
00266 #include <plearn/vmat/CompactFileVMatrix.h>
00267 // #include <plearn/vmat/CompressedVMatrix.h>
00268 // #include <plearn/vmat/CumVMatrix.h>
00269 // #include <plearn/vmat/DatedJoinVMatrix.h>
00270 // // #include <plearn/vmat/DictionaryVMatrix.h>
00271 // #include <plearn/vmat/DisregardRowsVMatrix.h>
00272 // #include <plearn/vmat/ExtractNNetParamsVMatrix.h>
00273 #include <plearn/vmat/FilteredVMatrix.h>
00274 // #include <plearn/vmat/FinancePreprocVMatrix.h>
00275 // #include <plearn/vmat/GaussianizeVMatrix.h>
00276 // #include <plearn/vmat/GeneralizedOneHotVMatrix.h>
00277 // #include <plearn/vmat/GetInputVMatrix.h>
00278 // #include <plearn/vmat/GramVMatrix.h>
00279 // #include <plearn/vmat/IndexedVMatrix.h>
00280 // #include <plearn/vmat/JulianizeVMatrix.h>
00281 // #include <plearn/vmat/KNNVMatrix.h>
00282 // #include <plearn/vmat/KNNImputationVMatrix.h>
00283 // // Commented out because triggers WordNet, which does not work really fine yet.
00284 // //#include <plearn/vmat/LemmatizeVMatrix.h>
00285 // #include <plearn/vmat/LocalNeighborsDifferencesVMatrix.h>
00286 // #include <plearn/vmat/LocallyPrecomputedVMatrix.h>
00287 // #include <plearn/vmat/MeanImputationVMatrix.h>
00288 // //#include <plearn/vmat/MixUnlabeledNeighbourVMatrix.h>
00289 // #include <plearn/vmat/MultiInstanceVMatrix.h>
00290 // #include <plearn/vmat/MultiTargetOneHotVMatrix.h>
00291 // #include <plearn/vmat/MultiToUniInstanceSelectRandomVMatrix.h>
00292 // #include <plearn/vmat/OneHotVMatrix.h>
00293 // #include <plearn/vmat/PLearnerOutputVMatrix.h>
00294 // #include <plearn/vmat/PairsVMatrix.h>
00295 // #include <plearn/vmat/PrecomputedVMatrix.h>
00296 // #include <plearn/vmat/ProcessDatasetVMatrix.h>
00297 #include <plearn/vmat/ProcessingVMatrix.h>
00298 // #include <plearn/vmat/ProcessSymbolicSequenceVMatrix.h>
00299 // #include <plearn/vmat/RandomSamplesVMatrix.h>
00300 // #include <plearn/vmat/RandomSamplesFromVMatrix.h>
00301 // #include <plearn/vmat/RankedVMatrix.h>
00302 #include <plearn/vmat/RegularGridVMatrix.h>
00303 // #include <plearn/vmat/RemoveDuplicateVMatrix.h>
00304 // #include <plearn/vmat/ReorderByMissingVMatrix.h>
00305 // //#include <plearn/vmat/SelectAttributsSequenceVMatrix.h>
00306 // #include <plearn/vmat/SelectRowsMultiInstanceVMatrix.h>
00307 // #include <plearn/vmat/ShuffleColumnsVMatrix.h>
00308 // #include <plearn/vmat/SortRowsVMatrix.h>
00309 // #include <plearn/vmat/SparseVMatrix.h>
00310 // #include <plearn/vmat/SplitWiseValidationVMatrix.h>
00311 // #include <plearn/vmat/SubInputVMatrix.h>
00312 // #include <plearn/vmat/TemporaryDiskVMatrix.h>
00313 // #include <plearn/vmat/TemporaryFileVMatrix.h>
00314 // #include <plearn/vmat/TextFilesVMatrix.h>
00315 // #include <plearn/vmat/ThresholdVMatrix.h>
00316 // #include <plearn/vmat/TransposeVMatrix.h>
00317 // #include <plearn/vmat/UCIDataVMatrix.h>
00318 // #include <plearn/vmat/UniformizeVMatrix.h>
00319 // #include <plearn/vmat/VariableDeletionVMatrix.h>
00320 // #include <plearn/vmat/ViewSplitterVMatrix.h>
00321 // #include <plearn/vmat/VMatrixFromDistribution.h>
00322 
00323 
00324 
00325 // **** Require LAPACK and BLAS
00326 
00327 // Unsupervised/KernelProjection
00328 // #include <plearn_learners/unsupervised/Isomap.h>
00329 // #include <plearn_learners/unsupervised/KernelPCA.h>
00330 // #include <plearn_learners/unsupervised/LLE.h>
00331 #include <plearn_learners/unsupervised/PCA.h>
00332 // #include <plearn_learners/unsupervised/SpectralClustering.h>
00333 
00334 // Kernels
00335 // #include <plearn/ker/LLEKernel.h>
00336 // #include <plearn/ker/ReconstructionWeightsKernel.h>
00337 
00338 // Regressors
00339 // #include <plearn_learners/regressors/LinearRegressor.h>
00340 // #include <plearn_learners/regressors/PLS.h>
00341 
00342 // PDistribution
00343 // #include <plearn_learners/distributions/GaussianDistribution.h>
00344 // #include <plearn_learners/distributions/GaussMix.h>
00345 // #include <plearn_learners/distributions/RandomGaussMix.h>
00346 #include <plearn_learners/distributions/ParzenWindow.h>
00347 // #include <plearn_learners/distributions/ManifoldParzen2.h>
00348 
00349 // Experimental
00350 // #include <plearn_learners_experimental/LinearInductiveTransferClassifier.h>
00351 
00352 // SurfaceTemplate
00353 // #include <plearn_learners_experimental/SurfaceTemplate/SurfaceTemplateLearner.h>
00354 
00355 // ***************************************************
00356 // ***   New EXPERIMENTAL stuff
00357 
00358 #include <plearn/var/EXPERIMENTAL/SumVarianceOfLinearTransformedBernoullis.h>
00359 #include <plearn/var/EXPERIMENTAL/SumVarianceOfLinearTransformedCategoricals.h>
00360 #include <plearn/var/EXPERIMENTAL/SumEntropyOfBernoullis.h>
00361 #include <plearn/var/EXPERIMENTAL/SumEntropyOfCategoricals.h>
00362 #include <plearn/var/EXPERIMENTAL/LinearCombinationOfScalarVariables.h>
00363 #include <plearn/var/EXPERIMENTAL/SaltPepperNoiseVariable.h>
00364 
00365 // includes Pascal's gradient hack
00366 #include <plearn_learners/generic/EXPERIMENTAL/NatGradNNet.h>
00367 
00368 
00369 // Stuff used for DeepReconstructorNet experiments
00370 #include <plearn/var/Variable.h>
00371 #include <plearn/var/SquareVariable.h>
00372 #include <plearn/math/TVec_impl.h>
00373 #include <plearn/var/EXPERIMENTAL/MultiMaxVariable.h>
00374 #include <plearn/var/SoftmaxVariable.h>
00375 #include <plearn/var/SumSquareVariable.h>
00376 #include <plearn/var/Func.h>
00377 #include <plearn/var/EXPERIMENTAL/DoubleProductVariable.h>
00378 #include <plearn/var/EXPERIMENTAL/TransposedDoubleProductVariable.h>
00379 #include <plearn/var/EXPERIMENTAL/ProbabilityPairsVariable.h>
00380 #include <plearn/var/EXPERIMENTAL/ProbabilityPairsInverseVariable.h>
00381 #include <plearn/var/EXPERIMENTAL/SoftSoftMaxVariable.h>
00382 #include <plearn/var/EXPERIMENTAL/LogSoftSoftMaxVariable.h>
00383 #include <plearn_learners/generic/EXPERIMENTAL/DeepReconstructorNet.h>
00384 #include <plearn/var/SourceVariable.h>
00385 #include <plearn/var/ConcatColumnsVariable.h>
00386 #include <plearn/var/ConcatRowsVariable.h>
00387 #include <plearn/var/ExpVariable.h>
00388 #include <plearn/var/LogVariable.h>
00389 #include <plearn/var/SigmoidVariable.h>
00390 #include <plearn/var/ProductTransposeVariable.h>
00391 #include <plearn/var/NegCrossEntropySigmoidVariable.h>
00392 #include <plearn/var/LogSoftmaxVariable.h>
00393 #include <plearn/var/ClassificationLossVariable.h>
00394 #include <plearn/var/EXPERIMENTAL/MultiSampleVariable.h>
00395 #include <plearn/var/EXPERIMENTAL/RandomForcedValuesVariable.h>
00396 #include <plearn/var/EXPERIMENTAL/BernoulliSampleVariable.h>
00397 #include <plearn/var/EXPERIMENTAL/TimesConstantScalarVariable2.h>
00398 #include <plearn/var/PlusConstantVariable.h>
00399 #include <plearn/var/TimesConstantVariable.h>
00400 
00401 // Stuff used for transformationLearner experiments
00402 #include <plearn_learners/distributions/EXPERIMENTAL/TransformationLearner.h>
00403 
00404 // Stuff used for local Gaussian classifier and for knn with PartsDistanceKernel
00405 #include <plearn_learners/classifiers/KNNClassifier.h>
00406 #include <plearn/ker/EXPERIMENTAL/PartsDistanceKernel.h>
00407 #include <plearn_learners/classifiers/EXPERIMENTAL/LocalGaussianClassifier.h>
00408 
00409 // Stuff used for DiverseComponentAnalysis
00410 #include <plearn_learners/unsupervised/EXPERIMENTAL/DiverseComponentAnalysis.h>
00411 
00412 // Stuff used for DenoisingRecurrentNet
00413 #include <plearn_learners_experimental/DenoisingRecurrentNet.h>
00414 
00415 using namespace PLearn;
00416 
00417 int main(int argc, char** argv)
00418 {
00419     return plearn_main( argc, argv, 
00420                         PLEARN_MAJOR_VERSION, 
00421                         PLEARN_MINOR_VERSION, 
00422                         PLEARN_FIXLEVEL       );
00423 }
00424 
00425 
00426 /*
00427   Local Variables:
00428   mode:c++
00429   c-basic-offset:4
00430   c-file-style:"stroustrup"
00431   c-file-offsets:((innamespace . 0)(inline-open . 0))
00432   indent-tabs-mode:nil
00433   fill-column:79
00434   End:
00435 */
00436 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines