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From "Jake Mannix (JIRA)" <j...@apache.org>
Subject [jira] Updated: (MATH-312) RealVector interface could use some iterators (dense and sparse) and generic map() and collect() methods.
Date Thu, 29 Oct 2009 07:48:59 GMT

     [ https://issues.apache.org/jira/browse/MATH-312?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Jake Mannix updated MATH-312:
-----------------------------

    Attachment: MATH-312.patch

Initial patch - sorry about my formatting, I haven't got checkstyle quite playing nice enough
to just reformat all the time correctly for me.

This patch has an AbstractRealVector which implements the iterators and map functions, as
well as faster iterators in ArrayRealVector and OpenMapRealVector.

> RealVector interface could use some iterators (dense and sparse) and generic map() and
collect() methods.
> ---------------------------------------------------------------------------------------------------------
>
>                 Key: MATH-312
>                 URL: https://issues.apache.org/jira/browse/MATH-312
>             Project: Commons Math
>          Issue Type: New Feature
>    Affects Versions: 2.0
>         Environment: all
>            Reporter: Jake Mannix
>             Fix For: 2.1
>
>         Attachments: MATH-312.patch
>
>
> As discussed on the [math] list, there are other projects out there which would love
to get a chance to standardize on using commons-math for things like linear algebra primitives,
as it would build a common base to build upon.  But to do that, some well-known and used techniques
for dealing with vectors, for one thing, are missing.  Most glaringly is the treatment of
sparse vectors: giving no Iterator for non-default values means external clients lose the
advantage of sparseness - only internal methods can skip around.  
> Extending the RealVector interface with sparse (and dense) iterator methods would fix
this: 
> {code}
>   double getDefaultValue();
>   Iterator<RealVector.Entry> iterator();
>   Iterator<RealVector.Entry> nonDefaultIterator();
> {code} 
> but there is another way to deal with vector data as well: instead of passing iterators
around, and worrying about all the lovely ConcurrentModification and unsupported "remove"
methods (which aren't the end of the world), we can instead expose generic map functions:
> {code}
>   RealVector map(UnivariateRealFunction f);
>   RealVector mapToSelf(UnivariateRealFunction f);
> {code}
> where RealVector mapToSelf(UnivariateRealFunction), which applies the function to the
vector's entries (checking whether the function preserves the default value up front allows
it to chose between the sparse or dense iterator), and map just applies mapToSelf to a copy.
> This doesn't exhaust all possible places where Iterators could be used helpfully (there's
also combining two vectors together via a {code}map(BinaryRealFunction, RealVector other){code}
which could be specialized nonlinear forms of addition or subtraction, and {code}double collect(UnivariateRealFunction,
BinaryRealFunction){code} which uses the iterates over all of the entries, applying the first
unary function to each entry, and then applying the binary function to combine this value
with the previous accumulated value - with "pow(2)", and "+" as the two functions, you get
L2 norm, with "abs()" and "+", you get L1 norm, etc...)

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