csharp typemap and examples

examples/undocumented/csharp_modular/Load.cs

@@ -0,0 +1,96 @@
+using System;
+using System.Collections.Generic;
+
+using org.shogun;
+using org.jblas;
+
+public class Load
+{
+	public static DoubleMatrix load_numbers(string filename)
+	{
+		DoubleMatrix result = null;
+		try
+		{
+			DoubleMatrix temp = DoubleMatrix.loadAsciiFile(filename);
+			result = temp.reshape(2, temp.Length / 2);
+		}
+		catch(java.io.IOException e)
+		{
+			Console.WriteLine("Unable to create matrix from " + filename + ": " + e.Message);
+			Environment.Exit(-1);
+		}
+		return result;
+	}
+	public static DoubleMatrix load_labels(string filename)
+	{
+		DoubleMatrix result = null;
+		try
+		{
+			DoubleMatrix temp = DoubleMatrix.loadAsciiFile(filename);
+			result = temp.reshape(1, temp.Length);
+		}
+		catch(java.io.IOException e)
+		{
+			Console.WriteLine("Unable to create matrix from " + filename + ": " + e.Message);
+			Environment.Exit(-1);
+		}
+		return result;
+	}
+	public static string[] load_dna(string filename)
+	{
+		List<string> list = new List<string>();
+		string[] result = null;
+		try
+		{
+			FileInputStream fstream = new FileInputStream(filename);
+			DataInputStream @in = new DataInputStream(fstream);
+			BufferedReader buffer = new BufferedReader(new InputStreamReader(@in));
+			string line;
+			while((line = buffer.readLine()) != null)
+			{
+				list.Add(line);
+			}
+			@in.close();
+			result = new string[list.Count];
+			for (int i = 0; i < list.Count; i++)
+			{
+				result[i] = (string)list[i];
+			}
+		}
+		catch(java.io.IOException e)
+		{
+			Console.WriteLine("Unable to create matrix from " + filename + ": " + e.Message);
+			Environment.Exit(-1);
+		}
+		return result;
+	}
+
+	public static string[] load_cubes(string filename)
+	{
+		List<string> list = new List<string>();
+		string[] result = null;
+		try
+		{
+			FileInputStream fstream = new FileInputStream(filename);
+			DataInputStream @in = new DataInputStream(fstream);
+			BufferedReader buffer = new BufferedReader(new InputStreamReader(@in));
+			string line;
+			while((line = buffer.readLine()) != null)
+			{
+				list.Add(line);
+			}
+			@in.close();
+			result = new string[list.Count];
+			for (int i = 0; i < list.Count; i++)
+			{
+				result[i] = (string)list[i];
+			}
+		}
+		catch(java.io.IOException e)
+		{
+			Console.WriteLine("Unable to create matrix from " + filename + ": " + e.Message);
+			Environment.Exit(-1);
+		}
+		return result;
+	}
+}

examples/undocumented/csharp_modular/MatrixTest.cs

@@ -0,0 +1,26 @@
+using System;
+
+using org.shogun;
+using org.jblas;
+
+public class MatrixTest
+{
+	static MatrixTest()
+	{
+// The library is specified in the 'DllImport' attribute for .NET:
+//		System.loadLibrary("modshogun");
+	}
+
+	static void Main(string[] argv)
+	{
+		modshogun.init_shogun();
+		Console.WriteLine("Test DoubleMatrix(jblas):");
+		RealFeatures x = new RealFeatures();
+		double[][] y = { new double[] { 1, 2 }, new double[] { 3, 4 }, new double[] { 5, 6 } };
+		DoubleMatrix A = new DoubleMatrix(y);
+		x.set_feature_matrix(A);
+		DoubleMatrix B = x.get_feature_matrix();
+		Console.WriteLine(B.ToString());
+		modshogun.exit_shogun();
+	}
+}

examples/undocumented/csharp_modular/VectorTest.cs

@@ -0,0 +1,25 @@
+using System;
+
+using org.shogun;
+using org.jblas;
+
+public class VectorTest
+{
+	static VectorTest()
+	{
+// The library is specified in the 'DllImport' attribute for .NET:
+//		System.loadLibrary("modshogun");
+	}
+
+	static void Main(string[] argv)
+	{
+		modshogun.init_shogun_with_defaults();
+
+		double[][] y = { new double[] { 1, 2, 3, 4 } };
+		DoubleMatrix A = new DoubleMatrix(y);
+		Labels x = new Labels(A);
+		DoubleMatrix B = x.get_labels();
+		Console.WriteLine(B.ToString());
+		modshogun.exit_shogun();
+	}
+}

examples/undocumented/csharp_modular/check.sh

@@ -0,0 +1,36 @@
+#!/bin/bash
+if [ -z "${JAVA}" ]
+then
+	JAVAC=javac
+	JAVA=java
+fi
+
+args=$#
+if [ $args -gt 1 ]; then
+echo "Usage: ./check.sh   check all examples.
+        ./check.sh name.cs  check one example."
+exit 0
+fi
+
+export CLASSPATH=/usr/share/java/jblas.jar:../../../src/interfaces/java_modular/shogun.jar:.
+export LD_LIBRARY_PATH=../../../src/shogun:../../../src/interfaces/java_modular
+
+if [ $args -eq 0 ]; then
+  ${JAVAC} Load.cs
+  ${JAVAC} $(ls *.cs | sed 's/Load.cs//')
+
+  for filename in *.class
+  do
+   [ "$filename" = "Load.class" ] && continue
+   echo "running ${filename%.class} .."
+   ${JAVA} ${filename%.class} >/dev/null
+  done
+fi
+
+if [ $args -eq 1 ]; then
+  arg=("$@")
+  ${JAVAC} Load.cs
+  ${JAVAC} ${arg[0]}
+  ${JAVA} ${arg[0]%.cs} >/dev/null
+fi
+

examples/undocumented/csharp_modular/classifier_averaged_perceptron_modular.cs

@@ -0,0 +1,54 @@
+using System.Collections;
+
+using org.shogun;
+using org.jblas;
+
+public class classifier_averaged_perceptron_modular
+{
+	static classifier_averaged_perceptron_modular()
+	{
+// The library is specified in the 'DllImport' attribute for .NET:
+//		System.loadLibrary("modshogun");
+	}
+
+	public ArrayList parameter_list = new ArrayList(2);
+	public classifier_averaged_perceptron_modular()
+	{
+		parameter_list.Add(Arrays.asList(new double?(10), new int?(1000)));
+		parameter_list.Add(Arrays.asList(new double?(10), new int?(10)));
+	}
+	public virtual Serializable run(IList para)
+	{
+		modshogun.init_shogun_with_defaults();
+		double learn_rate = (double)((double?)para[0]);
+		int max_iter = (int)((int?)para[1]);
+
+		DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
+		RealFeatures feats_train = new RealFeatures();
+		feats_train.set_feature_matrix(traindata_real);
+		RealFeatures feats_test = new RealFeatures();
+		feats_test.set_feature_matrix(testdata_real);
+		Labels labels = new Labels(trainlab);
+		AveragedPerceptron perceptron = new AveragedPerceptron(feats_train, labels);
+		perceptron.set_learn_rate(learn_rate);
+		perceptron.set_max_iter(max_iter);
+		perceptron.train();
+
+		perceptron.set_features(feats_test);
+		DoubleMatrix out_labels = perceptron.apply().get_labels();
+		ArrayList result = new ArrayList();
+		result.Add(perceptron);
+		result.Add(out_labels);
+
+		modshogun.exit_shogun();
+		return result;
+	}
+	static void Main(string[] argv)
+	{
+		classifier_averaged_perceptron_modular x = new classifier_averaged_perceptron_modular();
+		x.run((IList)x.parameter_list[0]);
+	}
+}

examples/undocumented/csharp_modular/classifier_domainadaptationsvm_modular.cs

@@ -0,0 +1,39 @@
+using org.shogun;
+using org.jblas;
+// This Java 'import static' statement cannot be converted to .NET:
+import static org.shogun.EAlphabet.DNA;
+
+public class classifier_domainadaptationsvm_modular
+{
+	static classifier_domainadaptationsvm_modular()
+	{
+// The library is specified in the 'DllImport' attribute for .NET:
+//		System.loadLibrary("modshogun");
+	}
+
+	static void Main(string[] argv)
+	{
+		modshogun.init_shogun_with_defaults();
+		int degree = 3;
+		int C = 1;
+
+		string[] fm_train_dna = {"CGCACGTACGTAGCTCGAT", "CGACGTAGTCGTAGTCGTA", "CGACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGACCACAGTTATATAGTA", "CGACGTAGTCGTAGTCGTA", "CGACGTAGTTTTTTTCGTA", "CGACGTAGTCGTAGCCCCA", "CAAAAAAAAAAAAAAAATA", "CGACGGGGGGGGGGGCGTA"};
+		string[] fm_test_dna = {"AGCACGTACGTAGCTCGAT", "AGACGTAGTCGTAGTCGTA", "CAACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGAACACAGTTATATAGTA", "CGACCTAGTCGTAGTCGTA", "CGACGTGGGGTTTTTCGTA", "CGACGTAGTCCCAGCCCCA", "CAAAAAAAAAAAACCAATA", "CGACGGCCGGGGGGGCGTA"};
+
+		StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
+		StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
+
+		WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
+		double[][] label_train_dna = { new double[] { -1, -1, -1, -1, -1, 1, 1, 1, 1, 1 } };
+		Labels labels = new Labels(new DoubleMatrix(label_train_dna));
+
+		SVMLight svm = new SVMLight(C, kernel, labels);
+		svm.train();
+
+		DomainAdaptationSVM dasvm = new DomainAdaptationSVM(C, kernel, labels, svm, 1.0);
+		dasvm.train();
+
+		DoubleMatrix @out = dasvm.apply(feats_test).get_labels();
+		modshogun.exit_shogun();
+	}
+}

examples/undocumented/csharp_modular/classifier_gaussiannaivebayes_modular.cs

@@ -0,0 +1,36 @@
+using System;
+
+using org.shogun;
+using org.jblas;
+
+public class classifier_gaussiannaivebayes_modular
+{
+	static classifier_gaussiannaivebayes_modular()
+	{
+// The library is specified in the 'DllImport' attribute for .NET:
+//		System.loadLibrary("modshogun");
+	}
+
+	static void Main(string[] argv)
+	{
+		modshogun.init_shogun_with_defaults();
+
+		DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		DoubleMatrix trainlab = Load.load_labels("../data/label_train_multiclass.dat");
+
+		RealFeatures feats_train = new RealFeatures();
+		feats_train.set_feature_matrix(traindata_real);
+		RealFeatures feats_test = new RealFeatures();
+		feats_test.set_feature_matrix(testdata_real);
+		Labels labels = new Labels(trainlab);
+
+		GaussianNaiveBayes gnb = new GaussianNaiveBayes(feats_train, labels);
+		gnb.train();
+		DoubleMatrix out_labels = gnb.apply(feats_test).get_labels();
+		Console.WriteLine(out_labels.ToString());
+
+		modshogun.exit_shogun();
+	}
+}

examples/undocumented/csharp_modular/classifier_gmnpsvm_modular.cs

@@ -0,0 +1,44 @@
+using System;
+
+using org.shogun;
+using org.jblas;
+
+public class classifier_gmnpsvm_modular
+{
+	static classifier_gmnpsvm_modular()
+	{
+// The library is specified in the 'DllImport' attribute for .NET:
+//		System.loadLibrary("modshogun");
+	}
+
+	static void Main(string[] argv)
+	{
+		modshogun.init_shogun_with_defaults();
+		double width = 2.1;
+		double epsilon = 1e-5;
+		double C = 1.0;
+
+		DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
+		DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
+
+		DoubleMatrix trainlab = Load.load_labels("../data/label_train_multiclass.dat");
+
+		RealFeatures feats_train = new RealFeatures();
+		feats_train.set_feature_matrix(traindata_real);
+		RealFeatures feats_test = new RealFeatures();
+		feats_test.set_feature_matrix(testdata_real);
+
+		GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
+
+		Labels labels = new Labels(trainlab);
+
+		GMNPSVM svm = new GMNPSVM(C, kernel, labels);
+		svm.set_epsilon(epsilon);
+		svm.train();
+		kernel.init(feats_train, feats_test);
+		DoubleMatrix out_labels = svm.apply(feats_test).get_labels();
+		Console.WriteLine(out_labels.ToString());
+
+		modshogun.exit_shogun();
+	}
+}