Changing a value only for the currently selected filter category

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Hi – a question that has some similarities to one asked in the previous post “Addressing cells programmatically”.

I am writing a simple script to replicate an excel-style goal-seek functionality. The script is to work on a matrix with a filter category (‘PhaseName’). The idea is to change the value of a particular item ‘Decline Rate’ (incrementing it up or down), depending on the value returned by the model. Only the value of ‘decline rate’ for the ‘PhaseName’ currently selected in the filter should be changed, however.

I can use the .itemIndex property of the .getFilterItem method to obtain the index number of the currently selected ‘PhaseName’, and can get the particular value for the ‘Decline Rate’ of the currently selected ‘PhaseName’ as follows:

int current = |Phase Details|.getFilterItem(|Phase Details::PhaseName|).itemIndex

|Phase Details::Combined Peak.Decline Rate|.values[current].value


However, it appears that using values with an index number in this way is a read-only property – one can’t set this to a new value.

In the earlier post “Addressing cells programmatically”, I found a useful code snippet from dom, achieving something similar by creating an ArrayList based on all of the different values of the item being changed, changing only that value corresponding to the currently selected filter category, and then writing the ArrayList back to the item. In my case, this would work as follows:

def ArrayList<Item> declines = |Phase Details::Combined Peak.Decline Rate|.values

declines.set(current, |Phase Details::Combined Peak.Decline Rate|.values[current].value-increment)

|Phase Details::Combined Peak.Decline Rate|.values = declines

This does in fact work – but it seems an inordinately complicated way of doing something that users must surely want to do all the time. Is anyone able to suggest a better way of doing this?

On a related note, since when the model is complete, the filter category “PhaseName” will have several hundred ‘phases’ in it, I have a related question on the model.ensureCalculated() method. With only a few phases, calculation times for this model are generally under a second – so if the goal-seek algorithm I have put together takes 6-10 iterations to find an answer, and must calcuate each time, while it is slow, it is not unbearable. Once several hundered phases have been added to the model, a full recalc will almost certainly take well over 10 seconds, meaning 6-10 iterations will become painfully slow – frustrating since in this case, only one of those several hundred phases actually needs to be calculated. Is there any method that can be called that will calculate the model only for the currently selected phase, rather than for all of them? This would seem like an essential ability for anyone with a large, complex model…

Many thanks.


Just a quick note to add to Ben’s response – it’s true, the team at Quantrix were able to give me some very useful pointers to model optimization that really did make all the difference in terms of being able to do iterative algorithms like this. What I learned as a result was that EnsureCalculated method actually does do only the ‘lazy’ recalc that is done by default using the UI – the problem, for me at least, was the number of cells being inadvertently dirtied during the execution of my code.

While I had a few issues in my model like use of the indirect function, which was contributing to the wide-scale dirtying of the model and thus slowing down calc times in general, the biggest problem with speed during iteration stemmed the issue identified at the start of the forum – the limitations of the scripting API in enabling changes to an item only for the currently selected item filter category, not across all items.

Using the method I described in the original post meant I was inadvertently dirtying huge swathes of the model, by changing an entire array of cells to update only one value. By switching to a method using the <matrix>.getSelection method Luca referred to, combined with optimizing other parts of the model, I was able to get calc times not only to be acceptable, but also to be independent of the sizes of the dimensions of the model.

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