Closed danielcohenlive closed 2 days ago
This pull request was exported from Phabricator. Differential Revision: D62325402
Attention: Patch coverage is 99.47644%
with 1 line
in your changes missing coverage. Please review.
Project coverage is 95.72%. Comparing base (
d66814a
) to head (c6ce3c2
).
Files with missing lines | Patch % | Lines |
---|---|---|
ax/analysis/plotly/predicted_effects.py | 98.57% | 1 Missing :warning: |
:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.
This pull request was exported from Phabricator. Differential Revision: D62325402
This pull request was exported from Phabricator. Differential Revision: D62325402
This pull request was exported from Phabricator. Differential Revision: D62325402
This pull request was exported from Phabricator. Differential Revision: D62325402
This pull request was exported from Phabricator. Differential Revision: D62325402
This pull request was exported from Phabricator. Differential Revision: D62325402
This pull request was exported from Phabricator. Differential Revision: D62325402
This pull request has been merged in facebook/Ax@0d05f21353fc151223fdee64335870f99c6d1d44.
This pull request was exported from Phabricator. Differential Revision: D62325402
Summary: This replicated the functionality of
ax.plot.scatter.plot_fitted
. It will show predicted effects for all trials with data and the most recently created non abandoned trial (which may have data also). The intent is to use it for a candidate trial which has just been generated, which will be the case in scheduler. But in the event the most recent trial is not a candidate, it should still work.To come:
Differential Revision: D62325402