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Jun 26, 2025
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PyCMA Wrapper small grant completion #165

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PyCMA Wrapper small grant completion
mxpoch Jun 26, 2025
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fixed type in small_grants.md
mxpoch Jun 26, 2025
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51 changes: 26 additions & 25 deletions small_grants.md
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Expand Up @@ -162,31 +162,6 @@ will "go the extra mile" to teach the contributor how the package or mathematics

# List of Current Projects

## Wrap PyCMA into the Optimization.jl Interface (\$100)

***In progress:** being worked on by Maximilian Pochapski*

PyCMA is a very good global optimizer written in Python. It did very well in
early editions of the BlackboxOptimizationBenchmarking.jl tests (see for example
https://github.com/jonathanBieler/BlackBoxOptimizationBenchmarking.jl/tree/v0.1.0)
and thus it would be good to have available for users to call and for benchmarking new
global optimization algorithms against. The goal of this project is to use PythonCall.jl
to setup the wrapper subpackage OptimizationPyCMA.jl with the bells and whistles to make
such benchmarking and usage straightforward and simple.

**Information to Get Started**: See the issue https://github.com/SciML/Optimization.jl/issues/918
which has links to starter code. PythonCall.jl is a well-documented library for calling Python
code from Julia and thus its documentation is a good starting point as well.

**Related Issues**: https://github.com/SciML/Optimization.jl/issues/918

**Success Criteria**: Merged pull request which adds a new OptimizationPyCMA.jl to
the Optimization.jl repository.

**Recommended Skills**: Basic (undergrad-level) knowledge of calculus and Python

**Reviewers**: Chris Rackauckas

## Fix and Update the "Simple Handwritten PDEs as ODEs" Benchmark Set (\$200)

**In Progress**: Claimed by Arjit Seth from June 20, 2025, to July 20, 2025.
Expand Down Expand Up @@ -355,6 +330,32 @@ which SciML will help administer through the small grants program.

These are the previous SciML small grants projects which have successfully concluded and paid out.


## Wrap PyCMA into the Optimization.jl Interface (\$100)

*Completed by Maximilian Pochapski June 25th, 2025*

PyCMA is a very good global optimizer written in Python. It did very well in
early editions of the BlackboxOptimizationBenchmarking.jl tests (see for example
https://github.com/jonathanBieler/BlackBoxOptimizationBenchmarking.jl/tree/v0.1.0)
and thus it would be good to have available for users to call and for benchmarking new
global optimization algorithms against. The goal of this project is to use PythonCall.jl
to setup the wrapper subpackage OptimizationPyCMA.jl with the bells and whistles to make
such benchmarking and usage straightforward and simple.

**Information to Get Started**: See the issue https://github.com/SciML/Optimization.jl/issues/918
which has links to starter code. PythonCall.jl is a well-documented library for calling Python
code from Julia and thus its documentation is a good starting point as well.

**Related Issues**: https://github.com/SciML/Optimization.jl/issues/918

**Success Criteria**: Merged pull request which adds a new OptimizationPyCMA.jl to
the Optimization.jl repository.

**Recommended Skills**: Basic (undergrad-level) knowledge of calculus and Python

**Reviewers**: Chris Rackauckas

## Wrap `scipy.optimize` into the Optimization.jl Interface (\$300)

**Completed by Aditya Pandey on June 23rd, 2025**
Expand Down