Combine data sets into a single complex tree

I’m have a issue merging 3 sets of data trees together and still maintaining consistent item/branch recall. I have spent about 3 hours playing with path mapper and tree frog, but can’t for the life of me get my head around how to do it (complex data trees are my nemesis!). I’m sure someone will be able to help wrangle this!

The image below (and gha file attached) show the 3 sets of data.
The tree structure of the master set is correct. I want to merge them so branch {0} of set A becomes {60;0;4} and branch {0} of set B becomes {60;0;5}. Extrapolating this further, branch {3} of set A would become {60;3;4}, or branch {4} of set B would become {60;4;5), etc.

The number of items in each branch of sets A & B will vary (there are about 450 master sets with corresponding sets A and B’s) and potentially may contain a Null (no curve).

Any assistance would be great, I’ve been looking at this way too long and can’t see the logic anymore!


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I don’t understand your description but wonder if you are aware of Match Tree?

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Merging the grafted trees shows that some branches (whose length = 1) exist only in the ‘master set’ and have no matching polylines in ‘set A’ or ‘set B’: (bottom right text panel)

Hi @Joseph_Oster & @HS_Kim ,

Thanks for getting back to me so quickly, I haven’ been able to get back to this problem until now. You are both so giving to the community in your help!

Both of your responses solve the issue in different ways. Joseph’s solution doesn’t do quite what i would have liked, however matching the structures may make it a lot easier to call the paths of data from separate trees.

The second option does it the way that I was hoping for, but in hindsight, may actually make it harder for me to recall the data that I want further through definition.

I can definitely move forward from here, once I decide on the best method of data recall.

thanks you so much from your help,

We both responded within a few minutes, yet you didn’t check back for two days? I really don’t understand that…

Any data tree that combines numbers and geometry will be more difficult to work with.

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P.S. Prune Tree the branches with length < 2.

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Hi Joseph,
When I raised the question it was 1am here in Tasmania, I posted and then went to bed :slight_smile:
I didn’t get back to it as the following two days were spent teaching at the university and I didn’t get a chance to jump back onto this project.

I think that your match tree method is actually the one that i’m going to employ as your comments about mixing data and geometry being harder is a definite concern. especially as there will always be 3 pieces of data in each branch of the master set, but the number of curves in the branches of sets A and B will vary between 0 and 13.

Thanks again for your help.
It’s 12:45am here, so i’m off to bed (again)