[jira] Updated: (MATH-326) getLInfNorm() uses wrong formula in both ArrayRealVector and OpenMapRealVector (in different ways)

["Phil Steitz (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MATH-326?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Phil Steitz updated MATH-326:
-----------------------------

    Fix Version/s: 2.1

> getLInfNorm() uses wrong formula in both ArrayRealVector and OpenMapRealVector (in different ways)
> --------------------------------------------------------------------------------------------------
>
>                 Key: MATH-326
>                 URL: https://issues.apache.org/jira/browse/MATH-326
>             Project: Commons Math
>          Issue Type: Bug
>    Affects Versions: 2.0
>         Environment: all
>            Reporter: Jake Mannix
>             Fix For: 2.1
>
>
> the L_infinity norm of a finite dimensional vector is just the max of the absolute value of its entries.
> The current implementation in ArrayRealVector has a typo:
> {code}
>     public double getLInfNorm() {
>         double max = 0;
>         for (double a : data) {
>             max += Math.max(max, Math.abs(a));
>         }
>         return max;
>     }
> {code}
> the += should just be an =.
> There is sadly a unit test assuring us that this is the correct behavior (effectively a regression-only test, not a test for correctness).
> Worse, the implementation in OpenMapRealVector is not even positive semi-definite:
> {code}   
>     public double getLInfNorm() {
>         double max = 0;
>         Iterator iter = entries.iterator();
>         while (iter.hasNext()) {
>             iter.advance();
>             max += iter.value();
>         }
>         return max;
>     }
> {code}
> I would suggest that this method be moved up to the AbstractRealVector superclass and implemented using the sparseIterator():
> {code}
>   public double getLInfNorm() {
>     double norm = 0;
>     Iterator<Entry> it = sparseIterator();
>     Entry e;
>     while(it.hasNext() && (e = it.next()) != null) {
>       norm = Math.max(norm, Math.abs(e.getValue()));
>     }
>     return norm;
>   }
> {code}
> Unit tests with negative valued vectors would be helpful to check for this kind of thing in the future.

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