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@PBrblt PBrblt commented Jun 30, 2022

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@anujanegi
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@PBrblt Thanks for adding your method!
can you also test your method by adding it to test_estimators.py.
Additionally, you can also think of adding NLL as a testcase in the above file. Can also add it for benchmarking in benchmark.py, you might have to be careful with the arguments that you pass/use, for eg. active set is not calculated in benchmark.py, I would suggest calculating it inside the NLL function by calling _get_active().

PBrblt and others added 2 commits July 5, 2022 12:29
First attempt at including the new method/metric to the benchmark
@anujanegi anujanegi marked this pull request as ready for review July 6, 2022 08:23
anujanegi and others added 2 commits July 6, 2022 10:24
In addition improved some part of the code.
@anujanegi anujanegi requested a review from agramfort July 11, 2022 12:51
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@PBrblt @anujanegi can you make the CIs green before considering a merge ? 🙏

@anujanegi
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anujanegi commented Jul 18, 2022

@PBrblt I updated the test cases to take less time to run.
Can you check you method, all tests fail. The estimates returned are filled with Nan values.

(iterative_L1_typeII, 0.1, 1e-1, 5e-1, "full"),
(iterative_L2_typeII, 0.1, 1e-1, 1e-1, "full"),
(gamma_map, 0.2, 1e-1, 5e-1, "full"),
(lemur, 0.2, 1e-1, 5e-1, "diag"),
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rtol and atol values are chosen by you @PBrblt

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3 participants