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Some packages in Manifest are outdated #174

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szy21 opened this issue Aug 19, 2022 · 0 comments · Fixed by #177
Closed

Some packages in Manifest are outdated #174

szy21 opened this issue Aug 19, 2022 · 0 comments · Fixed by #177
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szy21 commented Aug 19, 2022

Some packages in Manifest.toml under examples are outdated, such as EnsembleKalmanProcesses. It leads to an error when running the Lorenz example:

LoadError: MethodError: no method matching ParameterDistribution(::Vector{Dict{String, Any}})
Closest candidates are:
  ParameterDistribution(::Union{Array{PDType}, PDType}, ::Union{Array{CType}, Array, CType}, ::Union{Array{ST}, ST}) where {PDType<:ParameterDistributionType, CType<:EnsembleKalmanProcesses.ParameterDistributions.ConstraintType, ST<:AbstractString} at ~/.julia/packages/EnsembleKalmanProcesses/OjLuD/src/ParameterDistributions.jl:167
Stacktrace:
 [1] top-level scope
   @ /central/home/zhaoyi/CalibrateEmulateSample.jl/examples/Lorenz/Lorenz_example.jl:123
 [2] include(fname::String)
   @ Base.MainInclude ./client.jl:451
 [3] top-level scope
   @ REPL[2]:1
in expression starting at /central/home/zhaoyi/CalibrateEmulateSample.jl/examples/Lorenz/Lorenz_example.jl:108
@szy21 szy21 self-assigned this Aug 19, 2022
@szy21 szy21 mentioned this issue Aug 19, 2022
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@tsj5 tsj5 mentioned this issue Aug 31, 2022
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bors bot added a commit that referenced this issue Aug 31, 2022
@bors @szy21
Merge #177
fcad052 
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>
bors bot added a commit that referenced this issue Aug 31, 2022
@bors @szy21
Merge #177
14436b1 
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>
bors bot added a commit that referenced this issue Sep 1, 2022
@bors @szy21
Merge #177
b8e8b67 
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>
@bors bors bot closed this as completed in 5eb0701 Sep 2, 2022
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