class members with the parameter names (#5042) (#5094)

* class members with the parameter names (#5042) * WeightedMajorityVote, Clustering, CrossValidation * GradientEval, MachineEval, MulticlassOVRE * SigmoidCalibra, SplittingStrat, TimeSeries * Cross Validation fix * removing m prefix
shogun-toolbox · Jul 15, 2020 · c964c9d · c964c9d
1 parent 6351bcb
commit c964c9d
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Showing 22 changed files with 103 additions and 33 deletions.
diff --git a/src/shogun/ensemble/WeightedMajorityVote.cpp b/src/shogun/ensemble/WeightedMajorityVote.cpp
@@ -103,5 +103,5 @@ void WeightedMajorityVote::init()
 
 void WeightedMajorityVote::register_parameters()
 {
-	SG_ADD(&m_weights, "weights", "Weights for the majority vote", ParameterProperties::HYPER);
+	SG_ADD(&m_weights, kWeights, "Weights for the majority vote", ParameterProperties::HYPER);
 }
diff --git a/src/shogun/ensemble/WeightedMajorityVote.h b/src/shogun/ensemble/WeightedMajorityVote.h
@@ -96,6 +96,10 @@ namespace shogun
 		private:
 			void init();
 			void register_parameters();
+		#ifndef SWIG
+		public:
+			static constexpr std::string_view kWeights = "weights";
+		#endif
 	};
 }
 

diff --git a/src/shogun/evaluation/ClusteringEvaluation.cpp b/src/shogun/evaluation/ClusteringEvaluation.cpp
@@ -19,7 +19,7 @@ using namespace std;
 ClusteringEvaluation::ClusteringEvaluation() : Evaluation()
 {
 	m_use_best_map = true;
-	SG_ADD(&m_use_best_map, "use_best_map",
+	SG_ADD(&m_use_best_map, kBestMap,
 		"Find best match between predicted labels and the ground truth");
 }
 

diff --git a/src/shogun/evaluation/ClusteringEvaluation.h b/src/shogun/evaluation/ClusteringEvaluation.h
@@ -69,6 +69,11 @@ class ClusteringEvaluation: public Evaluation
 	// A flag to find best match between predicted labels and the ground truth
 	// before evaluation
 	bool m_use_best_map;
+
+#ifndef SWIG
+public:
+	static constexpr std::string_view kBestMap = "use_best_map";
+#endif
 };
 
 } // namespace shogun

diff --git a/src/shogun/evaluation/CrossValidation.cpp b/src/shogun/evaluation/CrossValidation.cpp
@@ -51,7 +51,7 @@ void CrossValidation::init()
 {
 	m_num_runs = 1;
 
-	SG_ADD(&m_num_runs, "num_runs", "Number of repetitions");
+	SG_ADD(&m_num_runs, kNumRuns, "Number of repetitions");
 }
 
 std::shared_ptr<EvaluationResult> CrossValidation::evaluate_impl() const

diff --git a/src/shogun/evaluation/CrossValidation.h b/src/shogun/evaluation/CrossValidation.h
@@ -188,6 +188,11 @@ namespace shogun
 
 		/** number of evaluation runs for one fold */
 		int32_t m_num_runs;
+
+	#ifndef SWIG
+	public:
+		static constexpr std::string_view kNumRuns = "num_runs";
+	#endif
 	};
 }
 

diff --git a/src/shogun/evaluation/CrossValidationStorage.cpp b/src/shogun/evaluation/CrossValidationStorage.cpp
@@ -44,28 +44,28 @@ using namespace shogun;
 CrossValidationFoldStorage::CrossValidationFoldStorage() : EvaluationResult()
 {
 	SG_ADD(
-	    &m_current_run_index, "run_index", "The current run index of this fold",
+	    &m_current_run_index, kCurrentRunIndex, "The current run index of this fold",
 	    ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_current_fold_index, "fold_index", "The current fold index",
+	    &m_current_fold_index, kCurrentFoldIndex, "The current fold index",
 	    ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_trained_machine, "trained_machine",
+	    &m_trained_machine, kTrainedMachine,
 	    "The machine trained by this fold", ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_test_result, "predicted_labels",
+	    &m_test_result, kTestResult,
 	    "The test result of this fold", ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_test_true_result, "ground_truth_labels",
+	    &m_test_true_result, kTestTrueResult,
 	    "The true test result for this fold", ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_train_indices, "train_indices", "Indices used for training",
+	    &m_train_indices, kTrainIndices, "Indices used for training",
 	    ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_test_indices, "test_indices", "Indices used for testing",
+	    &m_test_indices, kTestIndices, "Indices used for testing",
 	    ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_evaluation_result, "evaluation_result", "Result of the evaluation",
+	    &m_evaluation_result, kEvalulationResult, "Result of the evaluation",
 	    ParameterProperties::HYPER);
 }
 
@@ -92,13 +92,13 @@ CrossValidationStorage::CrossValidationStorage() : EvaluationResult()
 	m_num_folds = 0;
 
 	SG_ADD(
-	    &m_num_runs, "num_runs", "The total number of cross-validation runs",
+	    &m_num_runs, kNumRuns, "The total number of cross-validation runs",
 	    ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_num_folds, "num_folds", "The total number of cross-validation folds",
+	    &m_num_folds, kNumFold, "The total number of cross-validation folds",
 	    ParameterProperties::HYPER);
 	SG_ADD(
-	    &m_original_labels, "labels",
+	    &m_original_labels, kOriginalLabels,
 	    "The labels used for this cross-validation",
 	    ParameterProperties::HYPER);
 	this->watch_param(

diff --git a/src/shogun/evaluation/CrossValidationStorage.h b/src/shogun/evaluation/CrossValidationStorage.h
@@ -103,6 +103,18 @@ namespace shogun
 
 		/** Evaluation result for this fold */
 		float64_t m_evaluation_result{};
+
+	#ifndef SWIG
+	public:
+		static constexpr std::string_view kCurrentRunIndex = "run_index";
+		static constexpr std::string_view kCurrentFoldIndex = "fold_index";
+		static constexpr std::string_view kTrainedMachine = "trained_machine";
+		static constexpr std::string_view kTestResult = "predicted_labels";
+		static constexpr std::string_view kTestTrueResult = "ground_truth_labels";
+		static constexpr std::string_view kTrainIndices = "train_indices";
+		static constexpr std::string_view kTestIndices = "test_indices";
+		static constexpr std::string_view kEvalulationResult = "evaluation_result";
+	#endif
 	};
 
 	/**
@@ -156,6 +168,13 @@ namespace shogun
 
 		/** Vector with all the folds results */
 		std::vector<std::shared_ptr<EvaluationResult>> m_folds_results;
+
+	#ifndef SWIG
+	public:
+		static constexpr std::string_view kNumRuns = "num_runs";
+		static constexpr std::string_view kNumFold = "num_folds";
+		static constexpr std::string_view kOriginalLabels = "labels";
+	#endif
 	};
 }
 

diff --git a/src/shogun/evaluation/GradientEvaluation.cpp b/src/shogun/evaluation/GradientEvaluation.cpp
@@ -29,7 +29,7 @@ void GradientEvaluation::init()
 	m_diff=NULL;
 
 	SG_ADD(
-	    &m_diff, "differentiable_function", "Differentiable function",
+	    &m_diff, kDifferentiableFunction, "Differentiable function",
 	    ParameterProperties::HYPER);
 }
 

diff --git a/src/shogun/evaluation/GradientEvaluation.h b/src/shogun/evaluation/GradientEvaluation.h
@@ -86,6 +86,10 @@ class GradientEvaluation: public MachineEvaluation
 
 	/** parameter dictionary of differentiable function */
 	mutable std::map<Parameters::value_type, std::shared_ptr<SGObject>> m_parameter_dictionary; 
+#ifndef SWIG
+public:
+	static constexpr std::string_view kDifferentiableFunction = "differentiable_function";
+#endif
 };
 }
 #endif /* CGRADIENTEVALUATION_H_ */
diff --git a/src/shogun/evaluation/MachineEvaluation.cpp b/src/shogun/evaluation/MachineEvaluation.cpp
@@ -61,12 +61,12 @@ void MachineEvaluation::init()
 	m_cancel_computation = false;
 	m_pause_computation_flag = false;
 
-	SG_ADD(&m_machine, "machine", "Used learning machine");
-	SG_ADD(&m_features, "features", "Used features");
-	SG_ADD(&m_labels, "labels", "Used labels");
-	SG_ADD(&m_splitting_strategy, "splitting_strategy",
+	SG_ADD(&m_machine, kMachine, "Used learning machine");
+	SG_ADD(&m_features, kFeatures, "Used features");
+	SG_ADD(&m_labels, kLabels, "Used labels");
+	SG_ADD(&m_splitting_strategy, kSplittingStrategy,
 			"Used splitting strategy");
-	SG_ADD(&m_evaluation_criterion, "evaluation_criterion",
+	SG_ADD(&m_evaluation_criterion, kEvaluationCriterion,
 			"Used evaluation criterion");
 }
 

diff --git a/src/shogun/evaluation/MachineEvaluation.h b/src/shogun/evaluation/MachineEvaluation.h
@@ -104,6 +104,14 @@ namespace shogun
 
 		/** Criterion for evaluation */
 		std::shared_ptr<Evaluation> m_evaluation_criterion;
+	#ifndef SWIG
+	public:
+		static constexpr std::string_view kMachine = "machine";
+		static constexpr std::string_view kFeatures = "features";
+		static constexpr std::string_view kLabels = "labels";
+		static constexpr std::string_view kSplittingStrategy = "splitting_strategy";
+		static constexpr std::string_view kEvaluationCriterion = "evaluation_criterion";
+	#endif
 	};
 
 } /* namespace shogun */

diff --git a/src/shogun/evaluation/MulticlassOVREvaluation.cpp b/src/shogun/evaluation/MulticlassOVREvaluation.cpp
@@ -20,7 +20,7 @@ MulticlassOVREvaluation::MulticlassOVREvaluation() :
 MulticlassOVREvaluation::MulticlassOVREvaluation(const std::shared_ptr<BinaryClassEvaluation>& binary_evaluation) :
 	Evaluation(), m_binary_evaluation(nullptr), m_graph_results(nullptr), m_num_graph_results(0)
 {
-    SG_ADD((std::shared_ptr<Evaluation>*)&m_binary_evaluation, "binary_evaluation", "binary evaluator")
+    SG_ADD((std::shared_ptr<Evaluation>*)&m_binary_evaluation, kBinaryEvaluation, "binary evaluator")
 }
 
 MulticlassOVREvaluation::~MulticlassOVREvaluation()

diff --git a/src/shogun/evaluation/MulticlassOVREvaluation.h b/src/shogun/evaluation/MulticlassOVREvaluation.h
@@ -80,6 +80,10 @@ class MulticlassOVREvaluation: public Evaluation
 
 	/** number of graph results */
 	int32_t m_num_graph_results;
+#ifndef SWIG
+public:
+	static constexpr std::string_view kBinaryEvaluation = "binary_evaluation";
+#endif
 
 };
 

diff --git a/src/shogun/evaluation/SigmoidCalibration.cpp b/src/shogun/evaluation/SigmoidCalibration.cpp
@@ -28,19 +28,19 @@ void SigmoidCalibration::init()
 	m_epsilon = 1E-5;
 
 	SG_ADD(
-	    &m_sigmoid_as, "m_sigmoid_as",
+	    &m_sigmoid_as, kSigmoidAs,
 	    "Vector of paramter A of sigmoid for each class.");
 	SG_ADD(
-	    &m_sigmoid_bs, "m_sigmoid_bs",
+	    &m_sigmoid_bs, kSigmoidBs,
 	    "Vector of paramter B of sigmoid for each class.");
 	SG_ADD(
-	    &m_maxiter, "m_maxiter", "Maximum number of iteration for search.");
+	    &m_maxiter, kMaxiter, "Maximum number of iteration for search.");
 	SG_ADD(
-	    &m_minstep, "m_minstep", "Minimum step taken in line search.");
+	    &m_minstep, kMinstep, "Minimum step taken in line search.");
 	SG_ADD(
-	    &m_sigma, "m_sigma",
+	    &m_sigma, kSigma,
 	    "Positive parameter to ensure positive semi-definite Hessian.");
-	SG_ADD(&m_epsilon, "m_epsilon", "Stopping criteria.");
+	SG_ADD(&m_epsilon, kEpsilon, "Stopping criteria.");
 }
 
 void SigmoidCalibration::set_maxiter(index_t maxiter)

diff --git a/src/shogun/evaluation/SigmoidCalibration.h b/src/shogun/evaluation/SigmoidCalibration.h
@@ -139,6 +139,15 @@ namespace shogun
 		float64_t m_sigma;
 		/** Stopping criteria of search */
 		float64_t m_epsilon;
+	#ifndef SWIG
+	public:
+		static constexpr std::string_view kSigmoidAs = "sigmoid_as";
+		static constexpr std::string_view kSigmoidBs = "sigmoid_bs";
+		static constexpr std::string_view kMaxiter = "maxiter";
+		static constexpr std::string_view kMinstep = "minstep";
+		static constexpr std::string_view kSigma = "sigma";
+		static constexpr std::string_view kEpsilon = "epsilon";
+	#endif
 	};
 }
 #endif
diff --git a/src/shogun/evaluation/SplittingStrategy.cpp b/src/shogun/evaluation/SplittingStrategy.cpp
@@ -50,13 +50,13 @@ void SplittingStrategy::init()
 	m_is_filled=false;
 	m_num_subsets=0;
 
-	SG_ADD(&m_labels, "labels", "Labels for subsets");
+	SG_ADD(&m_labels, kLabels, "Labels for subsets");
 	SG_ADD(
-	    &m_subset_indices, "subset_indices", "Set of sets of subset indices");
+	    &m_subset_indices, kSubsetIndices, "Set of sets of subset indices");
 	SG_ADD(
-	    &m_is_filled, "is_filled", "Whether ther are index sets");
+	    &m_is_filled, kIsFilled, "Whether ther are index sets");
 	SG_ADD(
-	    &m_num_subsets, "num_subsets", "Number of index sets");
+	    &m_num_subsets, kSumSubsets, "Number of index sets");
 }
 
 SplittingStrategy::~SplittingStrategy()

diff --git a/src/shogun/evaluation/SplittingStrategy.h b/src/shogun/evaluation/SplittingStrategy.h
@@ -106,6 +106,13 @@ class SplittingStrategy: public SGObject
 	/** flag to check whether there is a set of index sets stored. If not,
 	 * call build_subsets() */
 	bool m_is_filled;
+#ifndef SWIG
+public:
+	static constexpr std::string_view kLabels = "labels";
+	static constexpr std::string_view kSubsetIndices = "subset_indices";
+	static constexpr std::string_view kIsFilled = "is_filled";
+	static constexpr std::string_view kSumSubsets = "num_subsets";
+#endif
 };
 }
 

diff --git a/src/shogun/evaluation/TimeSeriesSplitting.cpp b/src/shogun/evaluation/TimeSeriesSplitting.cpp
@@ -53,7 +53,7 @@ TimeSeriesSplitting::TimeSeriesSplitting(std::shared_ptr<Labels> labels, index_t
 void TimeSeriesSplitting::init()
 {
 	m_min_subset_size = 1;
-	SG_ADD(&m_min_subset_size, "min_subset_size",
+	SG_ADD(&m_min_subset_size, kMinSubsetSize,
 			"The minimum subset size for test set");
 }
 

diff --git a/src/shogun/evaluation/TimeSeriesSplitting.h b/src/shogun/evaluation/TimeSeriesSplitting.h
@@ -90,6 +90,11 @@ namespace shogun
 
 	private:
 		void init();
+
+	#ifndef SWIG
+	public:
+		static constexpr std::string_view kMinSubsetSize = "min_subset_size";
+	#endif
 	};
 }
 

diff --git a/src/shogun/neuralnets/DeepAutoencoder.cpp b/src/shogun/neuralnets/DeepAutoencoder.cpp
@@ -321,6 +321,5 @@ void DeepAutoencoder::init()
 	    "Pre-training L1 regularization coeff");
 	SG_ADD(&m_do_pretrain, "do_pretrain",
 	    "Whether to pretrain with relevant parameters");
-
 	SG_ADD(&m_sigma, "m_sigma", "Initialization Sigma");
 }
diff --git a/src/shogun/neuralnets/DeepAutoencoder.h b/src/shogun/neuralnets/DeepAutoencoder.h
@@ -276,6 +276,7 @@ class DeepAutoencoder : public Autoencoder
 	/** Standard deviation of the gaussian used to initialize the
 	 * parameters */
 	float64_t m_sigma;
+
 };
 }
 #endif