Resolve scikit-learn conflict #177
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tsj5
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Pin sklearn to known-good version Need to pin scipy version as well
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Merging at request of @odunbar |
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177: Resolve scikit-learn conflict r=tsj5 a=tsj5 # PULL REQUEST ## Purpose and Content This PR fixes the problems encountered by `@szy21` in #175. The purpose of that PR was to update the Manifest for the examples (Project/Manifest for CES itself is unchanged). This PR uses `@szy21` 's updates and in addition pins the versions of scipy and scikit-learn installed through Conda.jl to avoid an incompatibility in libstdc++ (documented in #176). ## Benefits and Risks **Benefits**: Resolves #176. `@szy21's` original PR resolves #174. **Risks**: Introduces maintenance requirement of having to remember we've pinned the versions of some dependencies going forward; since these are python dependencies this information isn't in Project.toml, so we might forget about this in the future when we want/need to update scikit-learn. This is a very minor risk, as the functionality from sk-learn that we currently use is mature. ## Linked Issues - Closes #174, #176 ## PR Checklist - [X] This PR has a corresponding issue OR is linked to an SDI. - [X] I have followed CliMA's codebase [contribution](https://clima.github.io/ClimateMachine.jl/latest/Contributing/) and [style](https://clima.github.io/ClimateMachine.jl/latest/DevDocs/CodeStyle/) guidelines OR N/A. - [X] I have followed CliMA's [documentation policy](https://github.com/CliMA/policies/wiki/Documentation-Policy). - [X] I have checked all issues and PRs and I certify that this PR does not duplicate an open PR. - [X] I linted my code on my local machine prior to submission: N/A. - [X] Unit tests: N/A. - [X] Code used in an integration test. - [X] All tests ran successfully on my local machine. - [X] All classes, modules, and function contain docstrings: N/A. - [X] Documentation has been added/updated: N/A. Co-authored-by: szy21 <pkuszy@gmail.com>
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177: Resolve scikit-learn conflict r=tsj5 a=tsj5 # PULL REQUEST ## Purpose and Content This PR fixes the problems encountered by `@szy21` in #175. The purpose of that PR was to update the Manifest for the examples (Project/Manifest for CES itself is unchanged). This PR uses `@szy21` 's updates and in addition pins the versions of scipy and scikit-learn installed through Conda.jl to avoid an incompatibility in libstdc++ (documented in #176). ## Benefits and Risks **Benefits**: Resolves #176. `@szy21's` original PR resolves #174. **Risks**: Introduces maintenance requirement of having to remember we've pinned the versions of some dependencies going forward; since these are python dependencies this information isn't in Project.toml, so we might forget about this in the future when we want/need to update scikit-learn. This is a very minor risk, as the functionality from sk-learn that we currently use is mature. ## Linked Issues - Closes #174, #176 ## PR Checklist - [X] This PR has a corresponding issue OR is linked to an SDI. - [X] I have followed CliMA's codebase [contribution](https://clima.github.io/ClimateMachine.jl/latest/Contributing/) and [style](https://clima.github.io/ClimateMachine.jl/latest/DevDocs/CodeStyle/) guidelines OR N/A. - [X] I have followed CliMA's [documentation policy](https://github.com/CliMA/policies/wiki/Documentation-Policy). - [X] I have checked all issues and PRs and I certify that this PR does not duplicate an open PR. - [X] I linted my code on my local machine prior to submission: N/A. - [X] Unit tests: N/A. - [X] Code used in an integration test. - [X] All tests ran successfully on my local machine. - [X] All classes, modules, and function contain docstrings: N/A. - [X] Documentation has been added/updated: N/A. Co-authored-by: szy21 <pkuszy@gmail.com>
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Sep 1, 2022
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I think Caltech HPC was down for maintenance yesterday which perhaps is why bors (buildkite in particular) timed out |
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177: Resolve scikit-learn conflict r=odunbar a=tsj5 # PULL REQUEST ## Purpose and Content This PR fixes the problems encountered by `@szy21` in #175. The purpose of that PR was to update the Manifest for the examples (Project/Manifest for CES itself is unchanged). This PR uses `@szy21` 's updates and in addition pins the versions of scipy and scikit-learn installed through Conda.jl to avoid an incompatibility in libstdc++ (documented in #176). ## Benefits and Risks **Benefits**: Resolves #176. `@szy21's` original PR resolves #174. **Risks**: Introduces maintenance requirement of having to remember we've pinned the versions of some dependencies going forward; since these are python dependencies this information isn't in Project.toml, so we might forget about this in the future when we want/need to update scikit-learn. This is a very minor risk, as the functionality from sk-learn that we currently use is mature. ## Linked Issues - Closes #174, #176 ## PR Checklist - [X] This PR has a corresponding issue OR is linked to an SDI. - [X] I have followed CliMA's codebase [contribution](https://clima.github.io/ClimateMachine.jl/latest/Contributing/) and [style](https://clima.github.io/ClimateMachine.jl/latest/DevDocs/CodeStyle/) guidelines OR N/A. - [X] I have followed CliMA's [documentation policy](https://github.com/CliMA/policies/wiki/Documentation-Policy). - [X] I have checked all issues and PRs and I certify that this PR does not duplicate an open PR. - [X] I linted my code on my local machine prior to submission: N/A. - [X] Unit tests: N/A. - [X] Code used in an integration test. - [X] All tests ran successfully on my local machine. - [X] All classes, modules, and function contain docstrings: N/A. - [X] Documentation has been added/updated: N/A. Co-authored-by: szy21 <pkuszy@gmail.com>
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Test on linux failed due to known issue #169. Merging this PR under the expectation that this intermittent failure will be fixed in a future PR addressing that issue.
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PULL REQUEST
Purpose and Content
This PR fixes the problems encountered by @szy21 in #175. The purpose of that PR was to update the Manifest for the examples (Project/Manifest for CES itself is unchanged). This PR uses @szy21 's updates and in addition pins the versions of scipy and scikit-learn installed through Conda.jl to avoid an incompatibility in libstdc++ (documented in #176).
Benefits and Risks
Benefits: Resolves #176. @szy21's original PR resolves #174.
Risks: Introduces maintenance requirement of having to remember we've pinned the versions of some dependencies going forward; since these are python dependencies this information isn't in Project.toml, so we might forget about this in the future when we want/need to update scikit-learn. This is a very minor risk, as the functionality from sk-learn that we currently use is mature.
Linked Issues
PR Checklist