add further c# examples

shogun-toolbox · Aug 29, 2011 · ace079d · ace079d
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diff --git a/examples/undocumented/csharp_modular/distance_euclidian_modular.cs b/examples/undocumented/csharp_modular/distance_euclidian_modular.cs
@@ -0,0 +1,30 @@
+using System;
+
+public class distance_euclidian_modular {
+	public static void Main() {
+		modshogun.init_shogun_with_defaults();
+
+		double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		RealFeatures feats_train = new RealFeatures(traindata_real);
+		RealFeatures feats_test = new RealFeatures(testdata_real);
+
+		EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train);
+
+		double[,] dm_train = distance.get_distance_matrix();
+		distance.init(feats_train, feats_test);
+		double[,] dm_test = distance.get_distance_matrix();
+
+		foreach(double item in dm_train) {
+			Console.Write(item);
+		}
+
+		foreach(double item in dm_test) {
+			Console.Write(item);
+		}
+
+		modshogun.exit_shogun();
+	}
+}
+
diff --git a/examples/undocumented/csharp_modular/distance_manhattenword_modular.cs b/examples/undocumented/csharp_modular/distance_manhattenword_modular.cs
@@ -0,0 +1,48 @@
+using System;
+
+public class distance_manhattenword_modular {
+	public static void Main() {
+
+		modshogun.init_shogun_with_defaults();
+		int order = 3;
+		int gap = 0;
+		bool reverse = false;
+
+		String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
+		String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
+		double[,] fm_test_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		StringCharFeatures charfeat = new StringCharFeatures(EAlphabet.DNA);
+		charfeat.set_features(fm_train_dna);
+		StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
+		feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
+		SortWordString preproc = new SortWordString();
+		preproc.init(feats_train);
+		feats_train.add_preprocessor(preproc);
+		feats_train.apply_preprocessor();
+
+		StringCharFeatures charfeat_test = new StringCharFeatures(EAlphabet.DNA);
+		charfeat_test.set_features(fm_test_dna);
+		StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
+		feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
+		feats_test.add_preprocessor(preproc);
+		feats_test.apply_preprocessor();
+
+		ManhattanWordDistance distance = new ManhattanWordDistance(feats_train, feats_train);
+
+		double[,] dm_train = distance.get_distance_matrix();
+		distance.init(feats_train, feats_test);
+		double[,] dm_test = distance.get_distance_matrix();
+
+		foreach(double item in dm_train) {
+			Console.Write(item);
+		}
+
+		foreach(double item in dm_test) {
+			Console.Write(item);
+		}
+
+		modshogun.exit_shogun();
+	}
+}
+
diff --git a/examples/undocumented/csharp_modular/distribution_linearhmm_modular.cs b/examples/undocumented/csharp_modular/distribution_linearhmm_modular.cs
@@ -0,0 +1,33 @@
+using System;
+
+public class distribution_linearhmm_modular {
+	public static void Main() {
+		bool reverse = false;
+		modshogun.init_shogun_with_defaults();
+		int order = 3;
+		int gap = 4;
+
+		String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
+
+		StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
+		StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
+		feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
+
+		LinearHMM hmm = new LinearHMM(feats);
+		hmm.train();
+
+		hmm.get_transition_probs();
+
+		int  num_examples = feats.get_num_vectors();
+		int num_param = hmm.get_num_model_parameters();
+		for (int i = 0; i < num_examples; i++)
+			for(int j = 0; j < num_param; j++) {
+			hmm.get_log_derivative(j, i);
+		}
+
+		double[] out_likelihood = hmm.get_log_likelihood();
+		double out_sample = hmm.get_log_likelihood_sample();
+
+		modshogun.exit_shogun();
+	}
+}
diff --git a/examples/undocumented/csharp_modular/kernel_anova_modular.cs b/examples/undocumented/csharp_modular/kernel_anova_modular.cs
@@ -0,0 +1,23 @@
+using System;
+
+public class kernel_anova_modular {
+	public static void Main() {
+		modshogun.init_shogun_with_defaults();
+		int cardinality = 2;
+		int size_cache = 5;
+
+		double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		RealFeatures feats_train = new RealFeatures(traindata_real);
+		RealFeatures feats_test = new RealFeatures(testdata_real);
+
+		ANOVAKernel kernel = new ANOVAKernel(feats_train, feats_train, cardinality, size_cache);
+
+		double[,] km_train = kernel.get_kernel_matrix();
+		kernel.init(feats_train, feats_test);
+		double[,] km_test = kernel.get_kernel_matrix();
+
+		modshogun.exit_shogun();
+	}
+}
diff --git a/examples/undocumented/csharp_modular/kernel_cauchy_modular.cs b/examples/undocumented/csharp_modular/kernel_cauchy_modular.cs
@@ -0,0 +1,50 @@
+using System;
+
+public class kernel_cauchy_modular {
+	public static void Main() {
+		modshogun.init_shogun_with_defaults();
+		double sigma = 1.0;
+
+		double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		RealFeatures feats_train = new RealFeatures(traindata_real);
+		RealFeatures feats_test = new RealFeatures(testdata_real);
+
+		EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train);
+
+		CauchyKernel kernel = new CauchyKernel(feats_train, feats_train, sigma, distance);
+
+		double[,] km_train = kernel.get_kernel_matrix();
+
+		kernel.init(feats_train, feats_test);
+		double[,] km_test=kernel.get_kernel_matrix();
+
+
+		//  Parse and Display km_train
+		Console.Write("km_train:\n");
+		int numRows = km_train.GetLength(0);
+		int numCols = km_train.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_train[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		//  Parse and Display km_test
+		Console.Write("\nkm_test:\n");
+		numRows = km_test.GetLength(0);
+		numCols = km_test.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_test[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		modshogun.exit_shogun();
+	}
+}
diff --git a/examples/undocumented/csharp_modular/kernel_chi2_modular.cs b/examples/undocumented/csharp_modular/kernel_chi2_modular.cs
@@ -0,0 +1,49 @@
+using System;
+
+public class kernel_chi2_modular {
+	public static void Main() {
+		modshogun.init_shogun_with_defaults();
+		double width = 1.4;
+		int size_cache = 10;
+
+		double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		RealFeatures feats_train = new RealFeatures(traindata_real);
+		RealFeatures feats_test = new RealFeatures(testdata_real);
+
+		Chi2Kernel kernel = new Chi2Kernel(feats_train, feats_train, width, size_cache);
+
+		double[,] km_train = kernel.get_kernel_matrix();
+
+		kernel.init(feats_train, feats_test);
+		double[,] km_test=kernel.get_kernel_matrix();
+
+		//  Parse and Display km_train
+		Console.Write("km_train:\n");
+		int numRows = km_train.GetLength(0);
+		int numCols = km_train.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_train[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		//  Parse and Display km_test
+		Console.Write("\nkm_test:\n");
+		numRows = km_test.GetLength(0);
+		numCols = km_test.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_test[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		modshogun.exit_shogun();
+	}
+}
+
diff --git a/examples/undocumented/csharp_modular/kernel_circular_modular.cs b/examples/undocumented/csharp_modular/kernel_circular_modular.cs
@@ -0,0 +1,50 @@
+using System;
+
+public class kernel_circular_modular {
+	public static void Main() {
+		modshogun.init_shogun_with_defaults();
+		double sigma = 1.0;
+
+		double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		RealFeatures feats_train = new RealFeatures(traindata_real);
+		RealFeatures feats_test = new RealFeatures(testdata_real);
+
+		EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train);
+
+		CircularKernel kernel = new CircularKernel(feats_train, feats_train, sigma, distance);
+
+		double[,] km_train = kernel.get_kernel_matrix();
+
+		kernel.init(feats_train, feats_test);
+		double[,] km_test=kernel.get_kernel_matrix();
+
+
+		//  Parse and Display km_train
+		Console.Write("km_train:\n");
+		int numRows = km_train.GetLength(0);
+		int numCols = km_train.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_train[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		//  Parse and Display km_test
+		Console.Write("\nkm_test:\n");
+		numRows = km_test.GetLength(0);
+		numCols = km_test.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_test[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		modshogun.exit_shogun();
+	}
+}
diff --git a/examples/undocumented/csharp_modular/kernel_const_modular.cs b/examples/undocumented/csharp_modular/kernel_const_modular.cs
@@ -0,0 +1,45 @@
+using System;
+
+public class kernel_const_modular {
+	public static void Main() {
+		modshogun.init_shogun_with_defaults();
+		double c = 23;
+
+		DummyFeatures feats_train = new DummyFeatures(10);
+		DummyFeatures feats_test = new DummyFeatures(17);
+
+		ConstKernel kernel = new ConstKernel(feats_train, feats_train, c);
+
+		double[,] km_train = kernel.get_kernel_matrix();
+
+		kernel.init(feats_train, feats_test);
+		double[,] km_test=kernel.get_kernel_matrix();
+
+		//  Parse and Display km_train
+		Console.Write("km_train:\n");
+		int numRows = km_train.GetLength(0);
+		int numCols = km_train.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_train[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		//  Parse and Display km_test
+		Console.Write("\nkm_test:\n");
+		numRows = km_test.GetLength(0);
+		numCols = km_test.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_test[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		modshogun.exit_shogun();
+	}
+}
+
diff --git a/examples/undocumented/csharp_modular/kernel_diag_modular.cs b/examples/undocumented/csharp_modular/kernel_diag_modular.cs
@@ -0,0 +1,45 @@
+using System;
+
+public class kernel_diag_modular {
+	public static void Main() {
+		modshogun.init_shogun_with_defaults();
+		double diag = 23;
+
+		DummyFeatures feats_train = new DummyFeatures(10);
+		DummyFeatures feats_test = new DummyFeatures(17);
+
+		ConstKernel kernel = new ConstKernel(feats_train, feats_train, diag);
+
+		double[,] km_train = kernel.get_kernel_matrix();
+
+		kernel.init(feats_train, feats_test);
+		double[,] km_test=kernel.get_kernel_matrix();
+
+		//  Parse and Display km_train
+		Console.Write("km_train:\n");
+		int numRows = km_train.GetLength(0);
+		int numCols = km_train.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_train[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		//  Parse and Display km_test
+		Console.Write("\nkm_test:\n");
+		numRows = km_test.GetLength(0);
+		numCols = km_test.GetLength(1);
+
+		for(int i = 0; i < numRows; i++){
+			for(int j = 0; j < numCols; j++){
+				Console.Write(km_test[i,j] +" ");
+			}
+			Console.Write("\n");
+		}
+
+		modshogun.exit_shogun();
+	}
+}
+