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8 months ago Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:
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Unfortunately, Gurobi dropped support for 9.5.2, and because it depends upon a license file, gurobipy 9.5.2 is officially broken without a manually added license. Previously, we had been prevented from upgrading to 10.x because of a bug noted in #266. I've recreated that bug with gurobipy 10.0.0, but tests pass in 10.0.1 to 10.0.3. I've also requested gurobi release a 9.5.3 with an updated limited-size license.
This PR will also fix #303
Support email to gurobi
> As noted [here](https://support.gurobi.com/hc/en-us/articles/19487474933521-How-do-I-resolve-the-error-License-expired-2023-10-25-), the size-limited license with gurobipy 9.5.2 distributed via pip expired this year, disabling that release. > > Our lab maintains an open-source modeling package that includes the option to use gurobipy as a backed for a step. However, gurobipy 10.x was released shortly thereafter, and is backwards-incompatible with some of the functions they used. A researcher PR'd that capability in, but updating their code every time gurobi releases a new major version, which apparently moves quickly, is too much of a maintenance burden long-term. > > In addition, this makes our library (some of the gurobi features) unavailable on python 3.11, since 9.5.2 doesn't have cp311 wheels. > > The technical solution on gurobi's end is simple: update the license in the 9.x branch, release an update, and build wheels for python 3.11. Gurobi enforcing upgrades couples our development cycle to yours unneccessarily. > > Alternatively, we could walk all of our developers through the license process (complicated by the fact that some are no longer in academia) in order to be able to support gurobipy 9.x. That seems like an option with a lot of email exchanges every time someone wants to debug an argument, run tests, or reproduce a low-dimensional experiment.Recreated bug when running tests:
``` ./test/test_optimizers.py::test_fit[optimizer11] Failed: [undefined]AttributeError: 'gurobipy.MVar' object has no attribute '__cindex__' data_derivative_1d = (array([ 2., 4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24., 26., 28., 30., 32., 34., ...., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.])) optimizer = MIOSR() @pytest.mark.parametrize( "optimizer", [ STLSQ(), SSR(), SSR(criteria="model_residual"), FROLS(), SR3(), ConstrainedSR3(), StableLinearSR3(), TrappingSR3(), Lasso(fit_intercept=False), ElasticNet(fit_intercept=False), DummyLinearModel(), MIOSR(), ], ) def test_fit(data_derivative_1d, optimizer): x, x_dot = data_derivative_1d if len(x.shape) == 1: x = x.reshape(-1, 1) opt = WrappedOptimizer(optimizer, unbias=False) > opt.fit(x, x_dot) test/test_optimizers.py:113: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pysindy/optimizers/base.py:190: in fit self._reduce(x_normed, y, **reduce_kws) pysindy/optimizers/wrapped_optimizer.py:38: in _reduce self.optimizer.fit(x, y) env/lib/python3.10/site-packages/sklearn/multioutput.py:216: in fit self.estimators_ = Parallel(n_jobs=self.n_jobs)( env/lib/python3.10/site-packages/sklearn/utils/parallel.py:63: in __call__ return super().__call__(iterable_with_config) env/lib/python3.10/site-packages/joblib/parallel.py:1085: in __call__ if self.dispatch_one_batch(iterator): env/lib/python3.10/site-packages/joblib/parallel.py:901: in dispatch_one_batch self._dispatch(tasks) env/lib/python3.10/site-packages/joblib/parallel.py:819: in _dispatch job = self._backend.apply_async(batch, callback=cb) env/lib/python3.10/site-packages/joblib/_parallel_backends.py:208: in apply_async result = ImmediateResult(func) env/lib/python3.10/site-packages/joblib/_parallel_backends.py:597: in __init__ self.results = batch() env/lib/python3.10/site-packages/joblib/parallel.py:288: in __call__ return [func(*args, **kwargs) env/lib/python3.10/site-packages/joblib/parallel.py:288: in