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https://issues.apache.org/jira/browse/MATH-1558?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17217562#comment-17217562
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Sam Ritchie commented on MATH-1558:
-----------------------------------

[~erans] does that all make sense? Happy to explain further if you like, or 
chat if there's a good chat system y'all use.

> MidpointIntegrator doesn't implement the midpoint method correctly
> ------------------------------------------------------------------
>
>                 Key: MATH-1558
>                 URL: https://issues.apache.org/jira/browse/MATH-1558
>             Project: Commons Math
>          Issue Type: Bug
>    Affects Versions: 3.6.1
>            Reporter: Sam Ritchie
>            Priority: Major
>              Labels: integration, midpoint
>         Attachments: midpoint.patch
>
>
> Hi all,
> I've been reading through the implementation of {{MidpointIntegrator}}, and 
> I've discovered an issue with the algorithm as implemented.
> The midpoint method generates an estimate for the definite integral of {{f}} 
> between {{a}} and {{b}} by
>  * subdividing {{(a, b)}} into {{n}} intervals
>  * estimating the area of each interval as a rectangle {{(b-a)/n}} wide and 
> as tall as the midpoint of the interval - ie, {{((b-a)/n) * f((a + b) / 2)}}
>  * adding up all estimates.
> The {{MidpointIntegrator}} implementation here sticks to n = powers of 2 for 
> this reason, stated in the comments:
> ?? The interval is divided equally into 2^n sections rather than an arbitrary 
> m sections because this configuration can best utilize the already computed 
> values.??
>  
> *Here is the* *problem:* the midpoint method can't reuse values if you split 
> an interval in half. It can only reuse previous values if you split the 
> interval into 3; ie, use 3^n sections, not 2^n.
> What's actually implemented in `MidpointIntegrator` is a left Riemann sum 
> without the leftmost point. Or, identically, a right Riemann sum without the 
> rightmost point: [https://en.wikipedia.org/wiki/Riemann_sum]
> This matters because the error of a (left, right) Riemann sum is proportional 
> to 1/n, while the error of the midpoint method is proportional to 1/n^2... a 
> big difference.
> h2. Explanation
> The idea behind the midpoint method's point reuse is that if you triple the 
> number of integral slices, one of the midpoints with n slices will overlap 
> with the n/3 slice evaluation:
> {noformat}
> n = 1 |--------x--------|
> n = 3 |--x--|--x--|--x–-|
> {noformat}
> You can incrementally update the n=1 estimate by
>  * sampling the points at (1/6) and (5/6) of the way across the n=1 interval
>  * adding them to the n=1 estimate
>  * scaling this sum down by 3, to scale down the widths of the rectangles
> For values of n != 1, the same trick applies... just sample the 1/6, 5/6 
> point for every slice in the n/3 evaluation.
> What happens when you try and scale from n => 2n? The old function 
> evaluations all fall on the _boundaries_ between the new cells, and can't be 
> reused:
> {noformat}
> n = 1 |-------x-------|
> n = 2 |---x---|---x---|
> n = 4 |-x-|-x-|-x-|-x-|
> {noformat}
> The implementation of "stage" in MidpointIntegrator is combining them like 
> this:
> {noformat}
> n = 1 |-------x-------|
> n = 2 |---x---x---x---|
> n = 4 |-x-x-x-x-x-x-x-|
> {noformat}
> which is actually:
>  * tripling the number of integration slices at each step, not doubling, and
>  * moving the function evaluation points out of the midpoint.
> In fact, what "stage" is actually doing is calculating a left Riemann sum, 
> just without the left-most point.
> Here are the evaluation points for a left Riemann sum for comparison:
> {noformat}
> n = 2 x-------x--------
> n = 4 x---x---x---x----
> n = 8 x-x-x-x-x-x-x-x--
> {noformat}
> Here's the code from "stage" implementing this:
> {code}
> // number of new points in this stage... 2^n points at this stage, so we
> // have 2^n-1 points.
> final long np = 1L << (n - 1);
> double sum = 0;
> // spacing between adjacent new points
> final double spacing = diffMaxMin / np;
> // the first new point}}}}
> double x = min + 0.5 * spacing;}}}}
> for (long i = 0; i < np; i++) {}}}}
>     sum += computeObjectiveValue(x);
>     x += spacing;}}}}
> }
> // add the new sum to previously calculated result
> return 0.5 * (previousStageResult + sum * spacing);
> {code}
> h2. Suggested Resolution 
> To keep the exact same results, I think the only solution is to remove the 
> incorrect incremental "stage"; or convert it to the algorithm that implements 
> the correct incremental increase by 3, and then _don't_ call it by default.
> Everything does work wonderfully if you expand n by a factor of 3 each time. 
> Press discusses this trick in Numerical Recipes, section 4.4 (p136): 
> [http://phys.uri.edu/nigh/NumRec/bookfpdf/f4-4.pdf] and notes that the 
> savings you get still make it more efficient than NOT reusing function 
> evaluations and implementing a correct scale-by-2 each time.
> Happy to provide more information if I can be helpful!
>  



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