Examples with DoubleMatrix1D cern.colt.matrix.DoubleMatrix1D used on opensource projects

Example 41 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tdq-studio-se by Talend.

the class Sorting method sort.

/**
 *Sorts the matrix slices into ascending order, according to the <i>natural ordering</i> of the matrix values in the given <tt>[row,column]</tt> position.
 *The returned view is backed by this matrix, so changes in the returned view are reflected in this matrix, and vice-versa.
 *To sort ranges use sub-ranging views. To sort by other dimensions, use dice views. To sort descending, use flip views ...
 *<p>
 *The algorithm compares two 2-d slices at a time, determinining whether one is smaller, equal or larger than the other.
 *Comparison is based on the cell <tt>[row,column]</tt> within a slice.
 *Let <tt>A</tt> and <tt>B</tt> be two 2-d slices. Then we have the following rules
 *<ul>
 *<li><tt>A &lt;  B  iff A.get(row,column) &lt;  B.get(row,column)</tt>
 *<li><tt>A == B iff A.get(row,column) == B.get(row,column)</tt>
 *<li><tt>A &gt;  B  iff A.get(row,column) &gt;  B.get(row,column)</tt>
 *</ul>
 *
 *@param matrix the matrix to be sorted.
 *@param row the index of the row inducing the order.
 *@param column the index of the column inducing the order.
 *@return a new matrix view having slices sorted by the values of the slice view <tt>matrix.viewRow(row).viewColumn(column)</tt>.
 *		<b>Note that the original matrix is left unaffected.</b>
 *@throws IndexOutOfBoundsException if <tt>row < 0 || row >= matrix.rows() || column < 0 || column >= matrix.columns()</tt>.
 */
public DoubleMatrix3D sort(DoubleMatrix3D matrix, int row, int column) {
    if (row < 0 || row >= matrix.rows())
        throw new IndexOutOfBoundsException("row=" + row + ", matrix=" + Formatter.shape(matrix));
    if (column < 0 || column >= matrix.columns())
        throw new IndexOutOfBoundsException("column=" + column + ", matrix=" + Formatter.shape(matrix));
    // indexes to reorder instead of matrix itself
    int[] sliceIndexes = new int[matrix.slices()];
    for (int i = sliceIndexes.length; --i >= 0; ) sliceIndexes[i] = i;
    final DoubleMatrix1D sliceView = matrix.viewRow(row).viewColumn(column);
    IntComparator comp = new IntComparator() {

        public int compare(int a, int b) {
            double av = sliceView.getQuick(a);
            double bv = sliceView.getQuick(b);
            // swap NaNs to the end
            if (av != av || bv != bv)
                return compareNaN(av, bv);
            return av < bv ? -1 : (av == bv ? 0 : 1);
        }
    };
    runSort(sliceIndexes, 0, sliceIndexes.length, comp);
    // take all rows and columns in the original order
    return matrix.viewSelection(sliceIndexes, null, null);
}

Example 42 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tdq-studio-se by Talend.

the class Sorting method zdemo1.

/**
 * Demonstrates advanced sorting.
 * Sorts by sum of row.
 */
public static void zdemo1() {
    Sorting sort = quickSort;
    DoubleMatrix2D matrix = DoubleFactory2D.dense.descending(4, 3);
    DoubleMatrix1DComparator comp = new DoubleMatrix1DComparator() {

        public int compare(DoubleMatrix1D a, DoubleMatrix1D b) {
            double as = a.zSum();
            double bs = b.zSum();
            return as < bs ? -1 : as == bs ? 0 : 1;
        }
    };
    System.out.println("unsorted:" + matrix);
    System.out.println("sorted  :" + sort.sort(matrix, comp));
}

Example 43 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tdq-studio-se by Talend.

the class Sorting method zdemo3.

/**
 * Demonstrates advanced sorting.
 * Sorts by sinus of cell values.
 */
public static void zdemo3() {
    Sorting sort = quickSort;
    double[] values = { 0.5, 1.5, 2.5, 3.5 };
    DoubleMatrix1D matrix = new DenseDoubleMatrix1D(values);
    cern.colt.function.DoubleComparator comp = new cern.colt.function.DoubleComparator() {

        public int compare(double a, double b) {
            double as = Math.sin(a);
            double bs = Math.sin(b);
            return as < bs ? -1 : as == bs ? 0 : 1;
        }
    };
    System.out.println("unsorted:" + matrix);
    DoubleMatrix1D sorted = sort.sort(matrix, comp);
    System.out.println("sorted  :" + sorted);
    // check whether it is really sorted
    sorted.assign(cern.jet.math.Functions.sin);
    /*
	sorted.assign(
		new cern.colt.function.DoubleFunction() {
			public double apply(double arg) { return Math.sin(arg); }
		}
	);
	*/
    System.out.println("sined  :" + sorted);
}

Example 44 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tdq-studio-se by Talend.

the class Sorting method zdemo4.

/**
 * Demonstrates applying functions.
 */
protected static void zdemo4() {
    double[] values1 = { 0, 1, 2, 3 };
    double[] values2 = { 0, 2, 4, 6 };
    DoubleMatrix1D matrix1 = new DenseDoubleMatrix1D(values1);
    DoubleMatrix1D matrix2 = new DenseDoubleMatrix1D(values2);
    System.out.println("m1:" + matrix1);
    System.out.println("m2:" + matrix2);
    matrix1.assign(matrix2, cern.jet.math.Functions.pow);
    /*
	matrix1.assign(matrix2,
		new cern.colt.function.DoubleDoubleFunction() {
			public double apply(double x, double y) { return Math.pow(x,y); }
		}
	);
	*/
    System.out.println("applied:" + matrix1);
}

Example 45 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tdq-studio-se by Talend.

the class Statistic method covariance.

/**
 * Constructs and returns the covariance matrix of the given matrix.
 * The covariance matrix is a square, symmetric matrix consisting of nothing but covariance coefficients.
 * The rows and the columns represent the variables, the cells represent covariance coefficients.
 * The diagonal cells (i.e. the covariance between a variable and itself) will equal the variances.
 * The covariance of two column vectors x and y is given by <tt>cov(x,y) = (1/n) * Sum((x[i]-mean(x)) * (y[i]-mean(y)))</tt>.
 * See the <A HREF="http://www.cquest.utoronto.ca/geog/ggr270y/notes/not05efg.html"> math definition</A>.
 * Compares two column vectors at a time. Use dice views to compare two row vectors at a time.
 *
 * @param matrix any matrix; a column holds the values of a given variable.
 * @return the covariance matrix (<tt>n x n, n=matrix.columns</tt>).
 */
public static DoubleMatrix2D covariance(DoubleMatrix2D matrix) {
    int rows = matrix.rows();
    int columns = matrix.columns();
    DoubleMatrix2D covariance = new cern.colt.matrix.impl.DenseDoubleMatrix2D(columns, columns);
    double[] sums = new double[columns];
    DoubleMatrix1D[] cols = new DoubleMatrix1D[columns];
    for (int i = columns; --i >= 0; ) {
        cols[i] = matrix.viewColumn(i);
        sums[i] = cols[i].zSum();
    }
    for (int i = columns; --i >= 0; ) {
        for (int j = i + 1; --j >= 0; ) {
            double sumOfProducts = cols[i].zDotProduct(cols[j]);
            double cov = (sumOfProducts - sums[i] * sums[j] / rows) / rows;
            covariance.setQuick(i, j, cov);
            // symmetric
            covariance.setQuick(j, i, cov);
        }
    }
    return covariance;
}