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Implement predict in ensembles #972

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merged 4 commits into from
Oct 5, 2022
Merged

Implement predict in ensembles #972

merged 4 commits into from
Oct 5, 2022

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Mr-Geekman
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@Mr-Geekman Mr-Geekman commented Oct 3, 2022

Before submitting (must do checklist)

  • Did you read the contribution guide?
  • Did you update the docs? We use Numpy format for all the methods and classes.
  • Did you write any new necessary tests?
  • Did you update the CHANGELOG?

Proposed Changes

Look #959.

Closing issues

Closes #959.

@Mr-Geekman Mr-Geekman self-assigned this Oct 3, 2022
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github-actions bot commented Oct 3, 2022

🚀 Deployed on https://deploy-preview-972--etna-docs.netlify.app

@github-actions github-actions bot temporarily deployed to pull request October 3, 2022 16:04 Inactive
tests/test_ensembles/test_stacking_ensemble.py Outdated Show resolved Hide resolved
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tests/test_ensembles/test_voting_ensemble.py Show resolved Hide resolved
tests/test_ensembles/test_voting_ensemble.py Show resolved Hide resolved
def test_forecast_calls_vote(example_tsds: TSDataset, naive_pipeline_1: Pipeline, naive_pipeline_2: Pipeline):
ensemble = VotingEnsemble(pipelines=[naive_pipeline_1, naive_pipeline_2])
ensemble.fit(ts=example_tsds)
ensemble._vote = MagicMock()
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Do we actually need MagicMock here, why not just Mock?

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I just use MagicMock everywhere. Should I replace it with Mock?

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As i understand MagicMock is useful testing the magic methods, but here we don't need it

@github-actions github-actions bot temporarily deployed to pull request October 4, 2022 15:45 Inactive
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codecov-commenter commented Oct 4, 2022

Codecov Report

❗ No coverage uploaded for pull request base (inference@e1399fb). Click here to learn what that means.
The diff coverage is n/a.

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@alex-hse-repository alex-hse-repository merged commit 70c7b0b into inference Oct 5, 2022
@Mr-Geekman Mr-Geekman mentioned this pull request Oct 26, 2022
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3 participants