{"action":"created","comment":{"url":"https://api.github.com/repos/mne-tools/mne-python/pulls/comments/32948318","id":32948318,"diff_hunk":"@@ -435,6 +436,8 @@ def tf_mixed_norm(evoked, forward, noise_cov, alpha_space, alpha_time,\n         and right window length.\n     return_residual : bool\n         If True, the residual is returned as an Evoked instance.\n+    log_objective : bool\n+        If True, the cost function is evaluated in every 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can remove it and compute the cost function all the time","created_at":"2015-06-22T15:40:39Z","updated_at":"2015-06-22T15:40:39Z","html_url":"https://github.com/mne-tools/mne-python/pull/2217#discussion_r32948318","pull_request_url":"https://api.github.com/repos/mne-tools/mne-python/pulls/2217","_links":{"self":{"href":"https://api.github.com/repos/mne-tools/mne-python/pulls/comments/32948318"},"html":{"href":"https://github.com/mne-tools/mne-python/pull/2217#discussion_r32948318"},"pull_request":{"href":"https://api.github.com/repos/mne-tools/mne-python/pulls/2217"}}},"pull_request":{"url":"https://api.github.com/repos/mne-tools/mne-python/pulls/2217","id":38007847,"html_url":"https://github.com/mne-tools/mne-python/pull/2217","diff_url":"https://github.com/mne-tools/mne-python/pull/2217.diff","patch_url":"https://github.com/mne-tools/mne-python/pull/2217.patch","issue_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2217","number":2217,"state":"open","locked":false,"title":"MRG: TFMxNE using BCD and active 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with active set approach, which is having \"same\" source estimate much 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