add support for user-provided decompositions #842
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ctdunc
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Puhhhhhhh. I misunderstood this MR a bit at the start. Not the smartest bear in the woods.
I'm not an expert with decompositions, and am not sure what general users want from this functionality. I will need to look into how SCIP handles them before I can check if everything correct.
In the meantime: More tests and comments are needed. I am against adding such functionality without making it extremely clear to users what it does. This is just a draft though, so I guess speed isn't a concern right now.
| decomp.scip_decomp = scip_decomp | ||
| return decomp | ||
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| def isOriginal(self): |
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We're trying to make sure new functionality isn't added without having tests. So for all available functions you're adding please put them into a simple test (one test can cover multiple functions)
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Will add more tests & docs when I get a moment, sorry. This one got put on the backburner due to other stuff at work.
For our use case, we have a modeling layer on top of PySCIPOpt that basically uses dataframe-like syntax to create groups of constraints using a table that characterizes our variables. So the goal is to break .groupby statements into subproblems where each of the groups can be solved ~in parallel. We have some combinatorial constraints as well, so decompositions seem like a natural place to reduce the number of combinations to check.
| def isOriginal(self): | ||
| return SCIPdecompIsOriginal(self.scip_decomp) | ||
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| def getAreaScore(self): |
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As this isn't standard knowledge (or at least I don't know it), if you can add a one line comment for what the function does then please do. This really helps out users and means they don't need to go through SCIP itself for answers.
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This extends to most functions below
this commit will add support for user-provided decompositions as dicts of
{var: label},{cons:label}pairs.still needs testing & examples, but opening a draft so maintainers can follow along if you have time.