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Fix LLE warning mistake #295
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Maybe, check on |
To fix tests with corrections of #294, can you rebase your branch on the last master? |
It is already only performed during fit. But warnings can be easily suppressed globally, so it's ok as it is I guess. |
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Yes, let's leave it like that.
Thx @gabelstein !
* Basic K-means clustering example on remote-sensing/complex data * Speed up TimeDelayCovariances (#281) * complete test for time delay cov * update whatsnew * speedup TimeDelayCovariances removing a for loop * Update pyriemann/estimation.py Co-authored-by: Alexandre Gramfort <[email protected]> --------- Co-authored-by: Alexandre Gramfort <[email protected]> * clean imports in examples * improve equations (#282) * Remove warnings from examples and tests (#283) * remove warnings from examples and tests * correct flake8 * remove useless checks because requirements are sklearn version sup to 0.24 * remove useless imports * Use a unique function check_metric (#284) * improve checking of metric arguments * improve checking of metric arguments bis * improve error messages * last modifs * apply code review remarks * Enhance ajd module (#238) * Enhance ajd module * correct whatsnew * improve code * complete refs * mean ale supporting hpd matrices * remove support of hpd matrices for ajd_pham * last modifs * update version number * modify n_iter_max of ajd_pham * apply suggestions from code review Co-authored-by: Vasco Schiavo <[email protected]> * correct --------- Co-authored-by: Vasco Schiavo <[email protected]> * Use a unique function check_function (#285) * use a unique function check_function * complete doc * sort imports in tests * Correct example on covariance estimation (#286) * change range of window lengths * improve imports in examples * remove useless imports * add blank line * small improvements * Improve viz module (#287) * improve viz module * move plot_cov_ellipse into viz module * add plot_bihist in viz * add reference * garantee to have 0.5 value in bin edges * add matplotlib in requirements * complete whatsnew * correct indentation * add plot_scatter Co-authored-by: gcattan <[email protected]> * correct flake8 * ensure to draw line y=x --------- Co-authored-by: gcattan <[email protected]> * Improve conftest (#289) * Add class CrossSpectra (#288) * add class cross spectra * complete whatsnew * correct typo * improve doc * Create pypi-publish.yml (#290) * prepare release 0.6 (#291) * update release and year * Add LLE kernel option (#293) * Add kernel option and tests * Update whatsnew.rst * Update whatsnew.rst * Apply suggestions from code review Co-authored-by: Quentin Barthélemy <[email protected]> * lint * improve whatsnew * Apply suggestions from code review Co-authored-by: Quentin Barthélemy <[email protected]> * linting * add none kernel test * might needed for flake8 * Update embedding.py * Delete .idea/workspace.xml * Update test_embedding.py * Update test_embedding.py * Apply suggestions from code review Co-authored-by: Quentin Barthélemy <[email protected]> * change error * linting --------- Co-authored-by: Quentin Barthélemy <[email protected]> * Adding Euclidean Alignment as implemented in the paper * Organizing code * Organizing code * resolving comments * Adapting TLCenter * simplify code and complete doc * deleting 'euclidean.py' file * fixing flake8 errors * updating whatsnew file * move contrib to version 0.7 in whatsnew * remove warnings from test_embedding * Update testing.yml (#294) * Update testing.yml * Update testing.yml * Fix LLE warning mistake (#295) * Improve clustering module (#296) * improve clustering module * correct tests * improve clustering * Update pyriemann/clustering.py Co-authored-by: Alexandre Gramfort <[email protected]> * improve doc * improve doc again --------- Co-authored-by: Alexandre Gramfort <[email protected]> * Improve classification module (#297) * improve classification module * correct indentation * improve indentations for SVC * correct indentation again * imrpove regression module (#300) * improve tests (#301) * Enhance ajd_pham to process HPD matrices (#299) * enhance ajd_pham to process HPD matrices * update mean_ale doc and test to process HPD matrices * complete whatsnew * Add partial_fit function to Whitening for online applications (#277) * Add functionality to whiten covariance matrices in online applications * add partial_fit * complete whatsnew * update version added * Changes to partial_fit to get it working in online applications * fix errors, simplify code and allow dimension reduction * improve whatsnew --------- Co-authored-by: qbarthelemy <[email protected]> * improve tangentspace module (#304) * Improve channelselection module (#303) * improve channelselection module * Update pyriemann/channelselection.py Co-authored-by: gcattan <[email protected]> * last modifs --------- Co-authored-by: gcattan <[email protected]> * Improve embedding module (#302) * improve embedding module * Update pyriemann/embedding.py Co-authored-by: gcattan <[email protected]> * remove np.dot * simplify code for _get_affinity_matrix --------- Co-authored-by: gcattan <[email protected]> * Add get_weights (#305) * add get_weights * complete whatsnew * fix blank line * replace is_weight by use_weight * change extension of readme file * Refactored code and more in the pyRiemann style * Whatsnew remote sensing * small modifs on code * small fix on estimator + new strategy to visualize results in remote sensing examples * Flake8 * small modifs * PCA from sklearn * Better image processing API * transform pca_image into a private function * improve code and doc * Removed redundant RemoveMeanImage --------- Co-authored-by: Quentin Barthélemy <[email protected]> Co-authored-by: Alexandre Gramfort <[email protected]> Co-authored-by: Vasco Schiavo <[email protected]> Co-authored-by: gcattan <[email protected]> Co-authored-by: Gabriel Wagner vom Berg <[email protected]> Co-authored-by: brunalopes <[email protected]> Co-authored-by: Brent Gaisford <[email protected]>
Stupid error, obviously always printed
n_neighbors = n_matrices - 1
in the warning.Also, this warning clogs my console extremely on large comparisons. Maybe we could just not proint a warning @qbarthelemy ?
Or introduce some variable that suppresses it? But this would be more of a global thing, I guess.