First version of `symmip`, which adds tentative MIP support by tBuLi · Pull Request #370 · tBuLi/symfit

tBuLi · 2023-09-18T12:54:01Z

First version of symmip, a symbolic wrapper around MIP solvers. Currently only support the Gurobi API, but the code is setup in such a way that we can easily add other solvers.

Added as a seperate module, because merging it into the existing symfit infrastructure was less than obvious. In particular, the existing Models, objectives and minimizers are only very expensive boilerplate with no added value for MIPs, so for now I cut ties with this formalism. We can always still plug this MIP solver back into the Fit API if we have a good MIP API to begin with.

lesshaste · 2023-09-18T13:36:03Z

Highs would be wonderful to add as it is open source.

pckroon

Alright! I mostly like it. I do have some comments and questions though.

Can you explain what the problem is with Models and Objectives + MIP? As I see it it should be possible to hook at least Model into this, maybe as MIPModel (see also ODEModel). I agree (for now) to leave out Objectives.
What does this mean for Indexed in base symfit?
I'm missing tests and docs ;)

pckroon · 2023-09-19T09:11:37Z

examples/mip/bilinear.py

+
+mip = MIP(- objective, constraints=constraints)
+# For full control, we still need to access the model directly.
+mip.backend.model.Params.NonConvex = 2


Oh I don't like this at all...

Nope, it's horrible. The good news is that it is possible however, which means that we don't have to wrap everything even to get started. But we still need to think about a syntax to deal with this. Personally I think that it might be best if the backend class GurobiBackend accepts any options, which will then be passed on to gurobi without looking into it.

The example above would then become

backend = GurobiBackend(NonConvex=2) mip = MIP(- objective, constraints=constraints, backend=backend)

That looks like an excellent option

pckroon · 2023-09-19T09:11:53Z

examples/mip/bilinear.py

+mip.backend.model.Params.NonConvex = 2
+mip_result = mip.execute()
+
+print(mip_result)


Missing empty line

pckroon · 2023-09-19T09:12:59Z

examples/mip/bilinear.py

+# This example formulates and solves the following simple bilinear model:
+#  maximize    x
+#  subject to  x + y + z <= 10
+#              x * y <= 2         (bilinear inequality)
+#              x * z + y * z = 1  (bilinear equality)
+#              x, y, z non-negative (x integral in second version)


For my understanding, this is not a MIP, but just an almost-linear problem? In other words, there are no integer constraints. In other other words, you could solve this with the existing minimizers

Second note, I don't see the non-negative boundaries in the code below

examples/mip/mip1.py

pckroon · 2023-09-19T09:15:35Z

examples/mip/mip1.py

+    f"y={fit_result[y]}, "
+    f"z={fit_result[z]}"
+)
+print(fit_result)


Missing empty line

pckroon · 2023-09-19T09:32:02Z

symfit/symmip/backend/gurobi.py

+from symfit.core.argument import Parameter
+
+
+VTYPES = {'binary': 'B', 'integer': 'I', 'real': 'C',}


Should this be a GurobiBackend class variable?

symfit/symmip/backend/gurobi.py

pckroon · 2023-09-19T09:34:46Z

symfit/symmip/mip.py

+
+DummyModel = namedtuple('DummyModel', 'params')
+
+VTYPES = {'binary': 'B', 'integer': 'I', 'real': 'C',} # ToDo: Enum?


Seeing that this got duplicated here there has to be a better way

agreed. I've now somewhat fixed this: in mip.py we only specify which types of variables there are as a list, whereas the specific backends can (should) dictate how these are to be translated to vtypes.

pckroon · 2023-09-19T09:35:42Z

symfit/symmip/mip.py

+VTYPES = {'binary': 'B', 'integer': 'I', 'real': 'C',} # ToDo: Enum?
+
+
+class MIPBackend(Protocol):


Should the GurobiBackend be a subclass of this?

For now I went with a protocol because it allows for static typing and duck-typing. An ABC was not worth it (yet) because there was no code reuse. But maybe I will make a common base class now that we have two solvers, but I'll keep the protocol nonetheless.

I need to read up on what Protocol does.

pckroon · 2023-09-19T09:41:03Z

symfit/symmip/mip.py

+        free_symbols = reduce(operator.or_,
+                              (c.free_symbols for c in self.constraints),
+                              self.objective.free_symbols if self.objective else set())


Just taking the union of some sets of symbols! ;)

Oh right. I can see how this works now. At minimal this needs a comment. Also consider using set.union instead of operator.or_.

pckroon · 2023-09-19T09:57:03Z

Oh, and another question. I love the type annotations, but what does it mean for the minimum python version we can use/support?

…mmercial solver.

tBuLi · 2023-09-19T11:09:54Z

Highs would be wonderful to add as it is open source.

Thanks for the tip, I wasn't aware of that package! I agree that we should have an open solver (as a default). But I tried to include it and found the documentation lacking and moreover, couldn't get the examples to work for Highs. So I've now instead added a wrapper for SCIP and made that the default, and that seems to work beautifully! So thanks for pointing me in this direction.

tBuLi · 2023-09-19T13:13:46Z

Alright! I mostly like it. I do have some comments and questions though.

Can you explain what the problem is with Models and Objectives + MIP? As I see it it should be possible to hook at least Model into this, maybe as MIPModel (see also ODEModel). I agree (for now) to leave out Objectives.

Great question. The main issue is that in order to translate the symbolic definition into a MIP model, I actually need to interact directly with the symbolic definition and use a custom code printer to translate it into the target MIP backend. I found that with our existing models it is actually quite hard to get back to the symbolic expressions, because they are more designed to be easily called with data and parameters. Moreover, with the existing Model classes there is no control over the Printer being used; it is always the default one that sympy offers.

So my idea here was the following: within the symmip module I will make a new Model class, which has way less boilerplate code and allows direct control over the printing. Moreover, I will use the lessons from both symfit and the slymfit brainstorm session to make sure this model can also be dropped back into symfit eventually.

What does this mean for Indexed in base symfit?

A bit similar to the previous answer, I think that starting from scratch in a new submodule in a context that is full of indexed symbols will be a good opportunity to learn some best practices for dealing wit these objects, that can then be back ported into symfit.

I'm missing tests and docs ;)

Yeah it definitely still needs some work ;).

Oh, and another question. I love the type annotations, but what does it mean for the minimum python version we can use/support?

I'm pretty sure that everything from >3.5 should be okay with this, so I don't expect any problems but let's keep our eyes open.

pckroon · 2023-09-19T13:39:26Z

Alright, thanks for the explanation. If I understand it Model + Minimizer determine the Printer? Or even just Minimizer? Following this line of thought, does that mean everything should remain as symbolic as possible, right up until the Minimizer touches it? This also has implications for Objectives --- symbolical objectives have been on my wish list for a while.

I think it's a good idea to fix this in code symfit Models now that we (you) know better, similar for Indexed*.

I think its fine to do some trial-and-error prototyping in a submodule like you do here, but I'd strongly prefer the final PR simply improving the symfit classes. This will also have the benefit of being able to use the tests to make sure you're not missing old use cases. I also think it'll result in less work since you'll be able to build on the existing framework. And where that doesn't fit, just break/adapt the old framework.

Can you do MIPODEModels? If no, your design is not good enough yet :D

…s which are not in model.

pckroon · 2023-09-28T08:49:26Z

symfit/core/argument.py


    def __new__(cls, name=None, value=1.0, min=None, max=None, fixed=False, **kwargs):
+        if 'binary' in kwargs:
+            kwargs['integer'] = kwargs['real'] = kwargs['nonnegative'] = True


Suggested change

kwargs['integer'] = kwargs['real'] = kwargs['nonnegative'] = True

kwargs['integer'] = True

kwargs['real'] = True

kwargs['nonnegative'] = True

symfit/core/argument.py

Co-authored-by: Peter C Kroon <pckroon@users.noreply.github.com>

First version of symmip, which adds tentative Gurobi support

21f402e

tBuLi added the WIP Work in Progress label Sep 18, 2023

Added non-trivial example, improved model output.

02a2359

pckroon requested changes Sep 19, 2023

View reviewed changes

Added SCIPOpt backend and made it the default, since this is a non-co…

8854846

…mmercial solver.

tBuLi added 11 commits September 25, 2023 10:46

Fixed parameter bounds, can now be arrays

4530c47

Updated examples, added test for array parameter bounds

6f0833f

Added simple mip test that can be compared with a Fit.

af962d1

Updated key2str function

920a1b6

Added MIP bilinear test. Also, we now allow constraints to have param…

8881b65

…s which are not in model.

Added some try/except clauses since MIP backends are an optional extra.

9c66409

Added symmip workflow and installation instruction.

e863bdd

Added SCIPOptSuite installation to symmip workflow

a409437

Added download statistics badges.

8e46208

Added tr/except clauses such that mip is an optional import.

19c263d

Fixed mistake in multiscenario example

77dd0bd

pckroon requested changes Sep 28, 2023

View reviewed changes

tBuLi and others added 5 commits October 3, 2023 11:01

Update symfit/core/argument.py

6fa3e04

Co-authored-by: Peter C Kroon <pckroon@users.noreply.github.com>

Support explicit indicing by ints in objectives and constraits.

edee7ef

Merge branch 'symmip' of github.com:tBuLi/symfit into symmip

6450a20

Removed numpy import in sudoku_alt

ea86ffe

Fixed kwargs preperation for non-indexed parameters.

c060e80

		from symfit.core.argument import Parameter


		VTYPES = {'binary': 'B', 'integer': 'I', 'real': 'C',}


		DummyModel = namedtuple('DummyModel', 'params')

		VTYPES = {'binary': 'B', 'integer': 'I', 'real': 'C',} # ToDo: Enum?

		VTYPES = {'binary': 'B', 'integer': 'I', 'real': 'C',} # ToDo: Enum?


		class MIPBackend(Protocol):

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pckroon commented Sep 19, 2023

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tBuLi commented Sep 19, 2023

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tBuLi commented Sep 18, 2023 •

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