Examples with DoubleMatrix2D cern.colt.matrix.DoubleMatrix2D used on opensource projects

Example 36 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class Formatter method demo1.

/**
 * Demonstrates how to use this class.
 */
public static void demo1() {
    // parameters
    double[][] values = { { 3, 0, -3.4, 0 }, { 5.1, 0, +3.0123456789, 0 }, { 16.37, 0.0, 2.5, 0 }, { -16.3, 0, -3.012345678E-4, -1 }, { 1236.3456789, 0, 7, -1.2 } };
    String[] formats = { "%G", "%1.10G", "%f", "%1.2f", "%0.2e", null };
    // now the processing
    int size = formats.length;
    DoubleMatrix2D matrix = cern.colt.matrix.DoubleFactory2D.dense.make(values);
    String[] strings = new String[size];
    String[] sourceCodes = new String[size];
    String[] htmlStrings = new String[size];
    String[] htmlSourceCodes = new String[size];
    for (int i = 0; i < size; i++) {
        String format = formats[i];
        strings[i] = new Formatter(format).toString(matrix);
        sourceCodes[i] = new Formatter(format).toSourceCode(matrix);
    // may not compile because of packages not included in the distribution
    // htmlStrings[i] = cern.colt.matrixpattern.Converting.toHTML(strings[i]);
    // htmlSourceCodes[i] = cern.colt.matrixpattern.Converting.toHTML(sourceCodes[i]);
    }
    System.out.println("original:\n" + new Formatter().toString(matrix));
    // may not compile because of packages not included in the distribution
    for (int i = 0; i < size; i++) {
    // System.out.println("\nhtmlString("+formats[i]+"):\n"+htmlStrings[i]);
    // System.out.println("\nhtmlSourceCode("+formats[i]+"):\n"+htmlSourceCodes[i]);
    }
    for (int i = 0; i < size; i++) {
        System.out.println("\nstring(" + formats[i] + "):\n" + strings[i]);
        System.out.println("\nsourceCode(" + formats[i] + "):\n" + sourceCodes[i]);
    }
}

Example 37 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class Formatter method toTitleString.

/**
 *Same as <tt>toTitleString</tt> except that additionally statistical aggregates (mean, median, sum, etc.) of rows and columns are printed.
 *Pass <tt>null</tt> to one or more parameters to indicate that the corresponding decoration element shall not appear in the string converted matrix.
 *
 *@param matrix The matrix to format.
 *@param rowNames The headers of all rows (to be put to the left of the matrix).
 *@param columnNames The headers of all columns (to be put to above the matrix).
 *@param rowAxisName The label of the y-axis.
 *@param columnAxisName The label of the x-axis.
 *@param title The overall title of the matrix to be formatted.
 *@param aggr the aggregation functions to be applied to columns and rows.
 *@return the matrix converted to a string.
 *@see hep.aida.bin.BinFunction1D
 *@see hep.aida.bin.BinFunctions1D
 */
public String toTitleString(DoubleMatrix2D matrix, String[] rowNames, String[] columnNames, String rowAxisName, String columnAxisName, String title, hep.aida.bin.BinFunction1D[] aggr) {
    if (matrix.size() == 0)
        return "Empty matrix";
    if (aggr == null || aggr.length == 0)
        return toTitleString(matrix, rowNames, columnNames, rowAxisName, columnAxisName, title);
    // hold row aggregations
    DoubleMatrix2D rowStats = matrix.like(matrix.rows(), aggr.length);
    // hold column aggregations
    DoubleMatrix2D colStats = matrix.like(aggr.length, matrix.columns());
    // aggregate an entire column at a time
    cern.colt.matrix.doublealgo.Statistic.aggregate(matrix, aggr, colStats);
    // aggregate an entire row at a time
    cern.colt.matrix.doublealgo.Statistic.aggregate(matrix.viewDice(), aggr, rowStats.viewDice());
    // turn into strings
    // tmp holds "matrix" plus "colStats" below (needed so that numbers in a columns can be decimal point aligned)
    DoubleMatrix2D tmp = matrix.like(matrix.rows() + aggr.length, matrix.columns());
    tmp.viewPart(0, 0, matrix.rows(), matrix.columns()).assign(matrix);
    tmp.viewPart(matrix.rows(), 0, aggr.length, matrix.columns()).assign(colStats);
    colStats = null;
    String[][] s1 = format(tmp);
    align(s1);
    tmp = null;
    String[][] s2 = format(rowStats);
    align(s2);
    rowStats = null;
    // copy strings into a large matrix holding the source matrix and all aggregations
    cern.colt.matrix.ObjectMatrix2D allStats = cern.colt.matrix.ObjectFactory2D.dense.make(matrix.rows() + aggr.length, matrix.columns() + aggr.length + 1);
    allStats.viewPart(0, 0, matrix.rows() + aggr.length, matrix.columns()).assign(s1);
    allStats.viewColumn(matrix.columns()).assign("|");
    allStats.viewPart(0, matrix.columns() + 1, matrix.rows(), aggr.length).assign(s2);
    s1 = null;
    s2 = null;
    // append a vertical "|" separator plus names of aggregation functions to line holding columnNames
    if (columnNames != null) {
        cern.colt.list.ObjectArrayList list = new cern.colt.list.ObjectArrayList(columnNames);
        list.add("|");
        // add names of aggregation functions
        for (int i = 0; i < aggr.length; i++) list.add(aggr[i].name());
        columnNames = new String[list.size()];
        list.toArray(columnNames);
    }
    // append names of aggregation functions to line holding rowNames
    if (rowNames != null) {
        cern.colt.list.ObjectArrayList list = new cern.colt.list.ObjectArrayList(rowNames);
        // add names of aggregation functions
        for (int i = 0; i < aggr.length; i++) list.add(aggr[i].name());
        rowNames = new String[list.size()];
        list.toArray(rowNames);
    }
    // turn large matrix into string
    String s = new cern.colt.matrix.objectalgo.Formatter().toTitleString(allStats, rowNames, columnNames, rowAxisName, columnAxisName, title);
    // insert a horizontal "----------------------" separation line above the column stats
    // determine insertion position and line width
    int last = s.length() + 1;
    int secondLast = last;
    int v = Math.max(0, rowAxisName == null ? 0 : rowAxisName.length() - matrix.rows() - aggr.length);
    for (int k = 0; k < aggr.length + 1 + v; k++) {
        // scan "aggr.length+1+v" lines backwards
        secondLast = last;
        last = s.lastIndexOf(rowSeparator, last - 1);
    }
    StringBuffer buf = new StringBuffer(s);
    buf.insert(secondLast, rowSeparator + repeat('-', secondLast - last - 1));
    return buf.toString();
}

Example 38 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class Formatter method toString.

/**
 * Returns a string representation of the given matrix.
 * @param matrix the matrix to convert.
 */
public String toString(DoubleMatrix1D matrix) {
    DoubleMatrix2D easy = matrix.like2D(1, matrix.size());
    easy.viewRow(0).assign(matrix);
    return toString(easy);
}

Example 39 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class Sorting method zdemo5.

/**
 * Demonstrates sorting with precomputation of aggregates (median and sum of logarithms).
 */
public static void zdemo5(int rows, int columns, boolean print) {
    Sorting sort = quickSort;
    // for reliable benchmarks, call this method twice: once with small dummy parameters to "warm up" the jitter, then with your real work-load
    System.out.println("\n\n");
    System.out.print("now initializing... ");
    cern.colt.Timer timer = new cern.colt.Timer().start();
    final cern.jet.math.Functions F = cern.jet.math.Functions.functions;
    DoubleMatrix2D A = cern.colt.matrix.DoubleFactory2D.dense.make(rows, columns);
    // initialize randomly
    A.assign(new cern.jet.random.engine.DRand());
    timer.stop().display();
    // also benchmark copying in its several implementation flavours
    DoubleMatrix2D B = A.like();
    timer.reset().start();
    System.out.print("now copying... ");
    B.assign(A);
    timer.stop().display();
    timer.reset().start();
    System.out.print("now copying subrange... ");
    B.viewPart(0, 0, rows, columns).assign(A.viewPart(0, 0, rows, columns));
    timer.stop().display();
    // System.out.println(A);
    timer.reset().start();
    System.out.print("now copying selected... ");
    B.viewSelection(null, null).assign(A.viewSelection(null, null));
    timer.stop().display();
    System.out.print("now sorting - quick version with precomputation... ");
    timer.reset().start();
    // THE QUICK VERSION (takes some 10 secs)
    A = sort.sort(A, hep.aida.bin.BinFunctions1D.median);
    // A = sort.sort(A,hep.aida.bin.BinFunctions1D.sumLog);
    timer.stop().display();
    // so we just show the first 5 rows
    if (print) {
        int r = Math.min(rows, 5);
        hep.aida.bin.BinFunction1D[] funs = { hep.aida.bin.BinFunctions1D.median, hep.aida.bin.BinFunctions1D.sumLog, hep.aida.bin.BinFunctions1D.geometricMean };
        String[] rowNames = new String[r];
        String[] columnNames = new String[columns];
        for (int i = columns; --i >= 0; ) columnNames[i] = Integer.toString(i);
        for (int i = r; --i >= 0; ) rowNames[i] = Integer.toString(i);
        System.out.println("first part of sorted result = \n" + new cern.colt.matrix.doublealgo.Formatter("%G").toTitleString(A.viewPart(0, 0, r, columns), rowNames, columnNames, null, null, null, funs));
    }
    System.out.print("now sorting - slow version... ");
    A = B;
    cern.colt.matrix.doublealgo.DoubleMatrix1DComparator fun = new cern.colt.matrix.doublealgo.DoubleMatrix1DComparator() {

        public int compare(DoubleMatrix1D x, DoubleMatrix1D y) {
            double a = cern.colt.matrix.doublealgo.Statistic.bin(x).median();
            double b = cern.colt.matrix.doublealgo.Statistic.bin(y).median();
            // double b = y.aggregate(F.plus,F.log);
            return a < b ? -1 : (a == b) ? 0 : 1;
        }
    };
    timer.reset().start();
    A = sort.sort(A, fun);
    timer.stop().display();
}

Example 40 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class Sorting method zdemo2.

/**
 * Demonstrates advanced sorting.
 * Sorts by sum of slice.
 */
public static void zdemo2() {
    Sorting sort = quickSort;
    DoubleMatrix3D matrix = DoubleFactory3D.dense.descending(4, 3, 2);
    DoubleMatrix2DComparator comp = new DoubleMatrix2DComparator() {

        public int compare(DoubleMatrix2D a, DoubleMatrix2D 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));
}