[BUGFIX] Fix dense barycenter calculations #79
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added 8 commits
October 11, 2024 21:54
pbarbarant
changed the title
bthirion
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Oct 13, 2024
| @@ -181,6 +183,9 @@ def fit( | |||
| have the same number of features n_features. | |||
| geometry_embedding (np.array or torch.Tensor): Common geometry | |||
| embedding of all individuals and barycenter. | |||
| subject_weights (list of float, optional): Weights of each individual. | |||
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Naive question: is there really a usecase for this parameter ?
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Mostly for interpolation:
https://pythonot.github.io/auto_examples/gromov/plot_gromov_barycenter.html
In our fMRI application, all subjects are assigned the same weight. However other FUGW users might do fancier things...
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I removed it since there is no immediate usecase where it could be relevant for the end user.
| _, | ||
| _, | ||
| _, | ||
| ) = fugw_barycenter.fit( |
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AN old traidiotn of sklearn is that fit() return the object itself.
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I'd prefer to merge this PR first and open another one to fix this.
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Solves #58, #77 and #78.
Adds a new set of tests against POT and in the identity case. Fixes the barycenter weight mix-up issue in the dense case.
It might be worth opening another PR for the sparse case.