baseCode - 0.2.5

Clover coverage report - baseCode - 0.2.5

Coverage timestamp: Tue Apr 12 2005 11:31:58 EDT

FRAMES NO FRAMES

file stats:	LOC:	92		Methods:	5
	NCLOC:	42		Classes:	1

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Source file

Conditionals

Statements

Methods

TOTAL

MatrixRowStats.java

100%

80%

96.9%

 package baseCode.math;
 
 import baseCode.dataStructure.matrix.DenseDoubleMatrix2DNamed;
 import cern.colt.list.DoubleArrayList;
 
 /**
  * Convenience functions for getting row statistics from matrices.
  * <p>
  * Copyright (c) 2004
  * </p>
  * <p>
  * Institution:: Columbia University
  * </p>
  * 
  * @author Paul Pavlidis
  * @version $Id: MatrixRowStats.java,v 1.11 2004/07/27 03:18:58 pavlidis Exp $
  * @todo Have min() and max() throw an EmptyMatrixException -- this exception class does not yet exist and needs to be
  *       defined somewhere.
  */
 public class MatrixRowStats {
 
    private MatrixRowStats() { /* keep us from instantiating this */
    }
 
    /**
     * Calculates the sum of squares for each row of a matrix
     * 
     * @param M DenseDoubleMatrix2DNamed
     * @return DoubleArrayList
     */
    public static DoubleArrayList sumOfSquares( DenseDoubleMatrix2DNamed M ) {
       DoubleArrayList r = new DoubleArrayList();
 
       for ( int i = 0; i < M.rows(); i++ ) {
          DoubleArrayList row = new DoubleArrayList( M.getRow( i ) );
          r.add( DescriptiveWithMissing.sumOfSquares( row ) );
       }
 
       return r;
    }
 
    /**
     * Calculates the means of a matrix's rows.
     * 
     * @param M DenseDoubleMatrix2DNamed
     * @return DoubleArrayList
     */
    public static DoubleArrayList means( DenseDoubleMatrix2DNamed M ) {
       DoubleArrayList r = new DoubleArrayList();
       for ( int i = 0; i < M.rows(); i++ ) {
          r.add( DescriptiveWithMissing
                .mean( new DoubleArrayList( M.getRow( i ) ) ) );
       }
       return r;
    }
 
    /**
     * Calculate the sums of a matrix's rows.
     * 
     * @param M DenseDoubleMatrix2DNamed
     * @return DoubleArrayList
     * @todo calls new a lot.
     */
    public static DoubleArrayList sums( DenseDoubleMatrix2DNamed M ) {
       DoubleArrayList r = new DoubleArrayList();
       for ( int i = 0; i < M.rows(); i++ ) {
          r.add( DescriptiveWithMissing
                .sum( new DoubleArrayList( M.getRow( i ) ) ) );
       }
       return r;
    }
 
    /**
     * Calculates the sample standard deviation of each row of a matrix
     * 
     * @param M DenseDoubleMatrix2DNamed
     * @return DoubleArrayList
     */
    public static DoubleArrayList sampleStandardDeviations(
          DenseDoubleMatrix2DNamed M ) {
       DoubleArrayList r = new DoubleArrayList();
       for ( int i = 0; i < M.rows(); i++ ) {
          DoubleArrayList row = new DoubleArrayList( M.getRow( i ) );
          double mean = DescriptiveWithMissing.mean( row );
          r
                .add( Math.sqrt( DescriptiveWithMissing.sampleVariance( row,
                      mean ) ) );
       }
       return r;
    }
 
 }

1		package baseCode.math;
2
3		import baseCode.dataStructure.matrix.DenseDoubleMatrix2DNamed;
4		import cern.colt.list.DoubleArrayList;
5
6		/**
7		* Convenience functions for getting row statistics from matrices.
8		* <p>
9		* Copyright (c) 2004
10		* </p>
11		* <p>
12		* Institution:: Columbia University
13		* </p>
14		*
15		* @author Paul Pavlidis
16		* @version $Id: MatrixRowStats.java,v 1.11 2004/07/27 03:18:58 pavlidis Exp $
17		* @todo Have min() and max() throw an EmptyMatrixException -- this exception class does not yet exist and needs to be
18		* defined somewhere.
19		*/
20		public class MatrixRowStats {
21
22	0	private MatrixRowStats() { /* keep us from instantiating this */
23		}
24
25		/**
26		* Calculates the sum of squares for each row of a matrix
27		*
28		* @param M DenseDoubleMatrix2DNamed
29		* @return DoubleArrayList
30		*/
31	2	public static DoubleArrayList sumOfSquares( DenseDoubleMatrix2DNamed M ) {
32	2	DoubleArrayList r = new DoubleArrayList();
33
34	2	for ( int i = 0; i < M.rows(); i++ ) {
35	60	DoubleArrayList row = new DoubleArrayList( M.getRow( i ) );
36	60	r.add( DescriptiveWithMissing.sumOfSquares( row ) );
37		}
38
39	2	return r;
40		}
41
42		/**
43		* Calculates the means of a matrix's rows.
44		*
45		* @param M DenseDoubleMatrix2DNamed
46		* @return DoubleArrayList
47		*/
48	1	public static DoubleArrayList means( DenseDoubleMatrix2DNamed M ) {
49	1	DoubleArrayList r = new DoubleArrayList();
50	1	for ( int i = 0; i < M.rows(); i++ ) {
51	30	r.add( DescriptiveWithMissing
52		.mean( new DoubleArrayList( M.getRow( i ) ) ) );
53		}
54	1	return r;
55		}
56
57		/**
58		* Calculate the sums of a matrix's rows.
59		*
60		* @param M DenseDoubleMatrix2DNamed
61		* @return DoubleArrayList
62		* @todo calls new a lot.
63		*/
64	1	public static DoubleArrayList sums( DenseDoubleMatrix2DNamed M ) {
65	1	DoubleArrayList r = new DoubleArrayList();
66	1	for ( int i = 0; i < M.rows(); i++ ) {
67	30	r.add( DescriptiveWithMissing
68		.sum( new DoubleArrayList( M.getRow( i ) ) ) );
69		}
70	1	return r;
71		}
72
73		/**
74		* Calculates the sample standard deviation of each row of a matrix
75		*
76		* @param M DenseDoubleMatrix2DNamed
77		* @return DoubleArrayList
78		*/
79	1	public static DoubleArrayList sampleStandardDeviations(
80		DenseDoubleMatrix2DNamed M ) {
81	1	DoubleArrayList r = new DoubleArrayList();
82	1	for ( int i = 0; i < M.rows(); i++ ) {
83	30	DoubleArrayList row = new DoubleArrayList( M.getRow( i ) );
84	30	double mean = DescriptiveWithMissing.mean( row );
85	30	r
86		.add( Math.sqrt( DescriptiveWithMissing.sampleVariance( row,
87		mean ) ) );
88		}
89	1	return r;
90		}
91
92		}