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https://github.com/jneug/zeichenmaschine.git
synced 2026-04-14 06:33:34 +02:00
Weitere Tests eingefügt und verbessert
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@@ -16,6 +16,23 @@ class MLMatrixTest {
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this.info = info;
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}
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@ParameterizedTest
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@ValueSource( classes = {DoubleMatrix.class, MatrixFactory.ColtMatrix.class} )
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void get( Class<? extends MLMatrix> mType ) {
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MatrixFactory.matrixType = mType;
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MLMatrix M = MatrixFactory.create(new double[][]{
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{1, 2, 3},
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{4, 5, 6}
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});
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assertEquals(mType, M.getClass());
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assertEquals(1.0, M.get(0,0));
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assertEquals(4.0, M.get(1,0));
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assertEquals(6.0, M.get(1,2));
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}
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@ParameterizedTest
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@ValueSource( classes = {DoubleMatrix.class, MatrixFactory.ColtMatrix.class} )
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void initializeOne( Class<? extends MLMatrix> mType ) {
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@@ -20,8 +20,8 @@ class NeuralNetworkTest {
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@BeforeAll
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static void setupMatrixLibrary() {
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Constants.setSeed(1001);
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MatrixFactory.matrixType = MatrixFactory.ColtMatrix.class;
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//MatrixFactory.matrixType = DoubleMatrix.class;
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//MatrixFactory.matrixType = MatrixFactory.ColtMatrix.class;
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MatrixFactory.matrixType = DoubleMatrix.class;
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}
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/*@Test
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@@ -153,12 +153,11 @@ class NeuralNetworkTest {
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}
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private List<TestData> createTrainingSet( int trainingSetSize, CalcType operation ) {
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Random random = new Random();
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List<TestData> tuples = new ArrayList<>();
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for( int i = 0; i < trainingSetSize; i++ ) {
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double s1 = random.nextDouble() * 0.5;
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double s2 = random.nextDouble() * 0.5;
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double s1 = Constants.random() * 0.5;
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double s2 = Constants.random() * 0.5;
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switch( operation ) {
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case ADD:
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