Added more decomposition methods to the matrices

Author: staticbeagle

README.md

@@ -36,12 +36,12 @@ Maven
 <dependency>
     <groupId>com.wildbitsfoundry</groupId>
     <artifactId>etk4j</artifactId>
-    <version>2.2.0</version>
+    <version>2.2.1</version>
 </dependency>
 ```
 Gradle
 ```bash
-implementation 'com.wildbitsfoundry:etk4j:2.2.0'
+implementation 'com.wildbitsfoundry:etk4j:2.2.1'
 ```
 
 Requirements

pom.xml

@@ -2,7 +2,7 @@
     <modelVersion>4.0.0</modelVersion>
     <groupId>com.wildbitsfoundry</groupId>
     <artifactId>etk4j</artifactId>
-    <version>2.2.0</version>
+    <version>2.2.1</version>
     <name>Engineering Toolkit for Java</name>
     <description>Tools and implementation of mathematical methods or backing math for engineering problems and
         applications.

src/main/java/com/wildbitsfoundry/etk4j/math/linearalgebra/ComplexMatrixDense.java

@@ -126,6 +126,29 @@ public ComplexCholeskyDecompositionDense Chol() {
         return new ComplexCholeskyDecompositionDense(this);
     }
 
+    public ComplexSingularValueDecompositionDense SVD() {
+        return new ComplexSingularValueDecompositionDense(this);
+    }
+
+    /**
+     * Eigenvalue decomposition. The {@link Matrix} is balanced ({@link MatrixDense#balance()}) prior to the decomposition.
+     *
+     * @return The {@link EigenvalueDecompositionDense} of the {@code Matrix}.
+     */
+    public ComplexEigenvalueDecompositionDense eig() {
+        return new ComplexEigenvalueDecompositionDense(this);
+    }
+
+    /**
+     * Schur Decomposition of the {@code Matrix}.
+     *
+     * @return The {@link SchurDecompositionDense} of the {@code Matrix}.
+     * @see <a href="https://en.wikipedia.org/wiki/Schur_decomposition">Schur Decomposition</a>
+     */
+    public ComplexSchurDecompositionDense Schur() {
+        return new ComplexSchurDecompositionDense(this);
+    }
+
     public Complex[] getArray() {
         return this.data;
     }
@@ -514,10 +537,6 @@ public ComplexMatrixDense balance() {
         return new ComplexMatrixDense(data, rows, cols);
     }
 
-    public ComplexSingularValueDecompositionDense SVD() {
-        return new ComplexSingularValueDecompositionDense(this);
-    }
-
     public ComplexMatrixDense pinv() {
         int rows = this.rows;
         int cols = this.cols;

src/main/java/com/wildbitsfoundry/etk4j/math/linearalgebra/MatrixDense.java

@@ -530,6 +530,16 @@ public CholeskyDecompositionDense Chol() {
     public SingularValueDecompositionDense SVD() {
         return new SingularValueDecompositionDense(this);
     }
+
+    /**
+     * Schur Decomposition of the {@code Matrix}.
+     *
+     * @return The {@link SchurDecompositionDense} of the {@code Matrix}.
+     * @see <a href="https://en.wikipedia.org/wiki/Schur_decomposition">Schur Decomposition</a>
+     */
+    public SchurDecompositionDense Schur() {
+        return new SchurDecompositionDense(this);
+    }
     // endregion
 
     /***

src/main/java/com/wildbitsfoundry/etk4j/math/linearalgebra/MatrixSparse.java

@@ -216,6 +216,9 @@ public MatrixSparse solve(MatrixSparse b) {
      */
     public MatrixSparse solve(double[] b) {
         double[][] matrix = new double[b.length][1];
+        for(int i = 0; i < b.length; i++) {
+            matrix[i][0] = b[i];
+        }
         return solve(from2DArray(matrix));
     }
 

src/test/java/com/wildbitsfoundry/etk4j/math/linearalgebra/MatrixSparseTest.java

@@ -127,6 +127,20 @@ public void testLUDecomposition() {
                 solution.get(1, 0), solution.get(2, 0)}, 1e-12);
     }
 
+    @Test
+    public void testSolveArrayRHS() {
+        double[][] matrix = {
+                {1, 4, 7},
+                {2, 5, 8},
+                {3, 6, 10},
+        };
+        MatrixSparse sparseCSC = MatrixSparse.from2DArray(matrix, ConstantsETK.DOUBLE_EPS);
+        double[] b = {1, 2, 0};
+        MatrixSparse solution = sparseCSC.solve(b);
+        assertArrayEquals(new double[]{-2, 6.000000000000005, -3.0000000000000027}, new double[]{solution.get(0, 0),
+                solution.get(1, 0), solution.get(2, 0)}, 1e-12);
+    }
+
     @Test
     public void testLUDecompositionSparseMatrixRHS() {
         double[][] matrix = {