Broken FEEC projections on polar domains#576
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- Remove polar_mapping and use_logical_sol options - Change the analytical solution - Avoid Laplacian() for right hand side - Add disk radius as parse argument
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| f_with_det = lambda eta1, eta2: f_log(eta1, eta2) * np.sqrt(F.metric_det(eta1, eta2)) | ||
| return derham_h.V0.integral(f_with_det) | ||
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| def l2_norm_of(f_log): |
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Why is this necessary? Can you not use mass matrices instead?
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As discussed, I'll look into this next week. If no "quick" solution is found, we can keep this code as it works (and is also somewhat instructive).
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| from scipy.sparse.linalg import LinearOperator as SparseLinearOperator | ||
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| class SparseCurlAsOperator(LinearOperator): |
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Is this class worth keeping in the library? It's only used in the maxwell_2d.py example, and I'd argue that one could remove the scipy option from that file. Either way, I think one could use a MatrixFreeLinearOperator in the example instead, for example like so:
lambda_strong = lambda x : array_to_psydac(strong_curl_sp @ x.toarray(), W2.coeff_space)
weak_curl_sp = sp_inv(M1.tosparse()) @ strong_curl_sp.T @ M2.tosparse()
lambda_weak = lambda x : array_to_psydac(weak_curl_sp @ x.toarray(), W1.coeff_space)
if scipy:
step_faraday_2d = MatrixFreeLinearOperator(W1.coeff_space, W2.coeff_space, lambda_strong)
step_ampere_2d = MatrixFreeLinearOperator(W2.coeff_space, W1.coeff_space, lambda_weak)
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June 9, 2026 14:38
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This PR introduces broken FEEC projections for C0 and C1 sequences (conga_projections.py) in 2D. The formulas for the projections can be found here on pages 19-23.
Added projections
C0PolarProjection_V0,C0PolarProjection_V1,C0PolarProjection_V2onto C0 sequence, and analogously onto C1 sequence.dotmethods of the projections are implemented for parallel execution for arbitrary domain decompositions in the angular and/or radial dimensions.Added unit tests for the projections checking:
tosparsemethods against reference matrix operatorsdotandtosparsemethodsPoisson example
Example of run:
mpirun -n 2 python poisson_2d.py -S -n 16 24 -d 2 2 -t disk -D 0.2 -m 'C0conga'Exact solution, approximate solution and error plot:
Example of run:
mpirun -n 2 python maxwell_2d.py -S -n 16 20 -d 2 2 -T 1 -D 0.2 -s 1Plot of exact solution and approximate solution at final time T = 1: