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gridap / Gridap.jl

Grid-based approximation of partial differential equations in Julia
MIT License
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Implementing Explicit Runge Kutta Methods #952

Closed tamaratambyah closed 10 months ago

tamaratambyah commented 11 months ago

This is a clean version of PR#951 for explicit Runge Kutta.

In this PR, I have implemented multi-stage, explicit Runge Kutta method in EXRungeKutta.jl. This follows the format and structure of RungeKutta.jl and IMEXRungeKutta.jl.

I have added an additional operator TransientEXRungeKuttaFEOperator. However, I think this can be combined with TransientRungeKuttaFEOperator to have one operator which works for both explicit and diagonally implicit Runge Kutta (IMEX will probably still require its own operator).

@santiagobadia can you please review this PR

Thanks

santiagobadia commented 11 months ago

@tamaratambyah can you please modify https://github.com/gridap/Gridap.jl/blob/master/NEWS.md accordingly?

You have to add the new feature (explicit RK) in the unreleased part.

santiagobadia commented 11 months ago

@tamaratambyah the ODE tests are not passing.

Can you please check try to fix the errors?

codecov-commenter commented 10 months ago

Codecov Report

Attention: 33 lines in your changes are missing coverage. Please review.

Comparison is base (86e8101) 88.17% compared to head (99b40e1) 88.08%.

Files Patch % Lines
src/ODEs/TransientFETools/TransientFEOperators.jl 0.00% 32 Missing :warning:
src/ODEs/ODETools/EXRungeKutta.jl 98.38% 1 Missing :warning:

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Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #952 +/- ## ========================================== - Coverage 88.17% 88.08% -0.10% ========================================== Files 176 177 +1 Lines 20936 21053 +117 ========================================== + Hits 18460 18544 +84 - Misses 2476 2509 +33 ```

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