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…
Would it be feasible to post the model you were working on?
I would like to mention for that record that, although Janak was not able to post his model here due to its proprietary nature, we worked with him directly outside of the forum and were able to optimize that model to the point where it was quite viable, with calculation times that were constant and reasonably fast, and not dependent on the sizes of the dimensions that had previously been giving him trouble. This didn’t require the creation of any external models, just some know-how concerning the Quantrix calculation engine. If it’s possible to post (or submit by some more confidential means) a model that is representative of your approach, we may well be able adjust it to obtain satisfactory performance.