Move FEEC assembly kernels into kernel folders

[max-models]

Stack: part 12 of 14, based on #724 (merge that first), next: #723. Full order: #709 → #708 → #711 → #712 → #705 → #713 → #714 → #718 → #720 → #721 → #724 → #725 → #723 → #722.

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Solves the following issue(s):

Solves #411, tracked in #650. The FEEC assembly kernels are the last entry kernels that were still called as PyccelKernel(getattr(module, name)) from shared modules. They now follow the folder rule of CUDA_STRATEGY.md, like the pusher, accumulation and geometry kernels. This is a pure restructuring: no numerical change.

Core changes:

• One folder per kernel: the 16 entry kernels of feec/mass_kernels.py and feec/basis_projection_kernels.py each move into feec/kernels/<name>/, which holds <name>_kernels.py and an __init__.py declaring <name> = Kernel.from_folder(__name__, structs=CUDA_STRUCTS, missing_cuda="fallback"). There is no .cu file, because none of these kernels has a CUDA port yet. Both old modules are removed.
  • From mass_kernels.py: kernel_{1,2,3}d_mat, kernel_{1,2,3}d_vec, kernel_{1,2,3}d_eval, kernel_3d_matrixfree, kernel_3d_diag, surface_kernel_3d_mat, surface_kernel_3d_vec
  • From basis_projection_kernels.py: assemble_dofs_for_weighted_basisfuns_{1,2,3}d
• The function bodies are unchanged. I checked this with an AST comparison of all 16 functions against devel. Each file imports only what it uses (numpy as np and/or shape).
• Call sites in feec/mass.py, feec/boundary_mass.py and feec/basis_projection_ops.py import the kernels. For kernels that depend on the dimension, they pick the right one from a small module-level dict (_MAT_KERNELS[ldim], _EVAL_KERNELS, _MATRIXFREE_KERNELS, _DIAG_KERNELS, _ASSEMBLY_KERNELS) instead of getattr on a module. The direct pyccel calls of mass_kernels.kernel_3d_vec in L2Projector also go through the Kernel now.
• missing_cuda="fallback": on the CuPy backend these kernels keep the behaviour of the former PyccelKernel calls: they run on host copies of the arrays, with a warning the first time. With the default ("raise"), FEEC setups that currently assemble mass matrices on CuPy would start to fail. When a kernel is ported, its port removes the fallback for that kernel.
• collect_kernel_files() picks up the new files with no change, since their names contain kernels. It now lists 142 files, 17 of them under feec/kernels.
• Tests: test_catalog_signatures expects 17 kernels in feec.kernels (was 1). feec.kernels was already in test_cuda_parity.PACKAGES, so the new folders get the signature check and the folder-declaration check.

Model-specific changes:

None.

Documentation changes:

• feec/kernels/__init__.py: the docstring lists the assembly kernels and the fallback.
• CUDA_STRATEGY.md:
  • a checklist entry for this PR
  • the kernel count in "Current state"
  • a short section "FEEC assembly kernels (Put each kernel into its own folder and file #411)" saying that these kernels are now ready for CUDA ports (add <name>_cuda.cu and parity cases, then drop the fallback)

Testing (macOS, no GPU; pyccel kernels compiled in the worktree with GNU/Fortran; GPU tests not run; following the agreed scope, I ran only a few directly relevant tests, and CI covers the rest):

• feec/tests/test_mass_reassembly.py: 2 passed
• feec/tests/test_basis_ops.py::test_some_basis_ops and ::test_transposed_update_weights_drops_zero_blocks: passed
• feec/tests/test_boundary_integrals.py -k "unit_cube_constant or hcurl_per_face": 12 passed
• feec/tests/test_utilities_kernels.py, pic/tests/test_kernel_backends.py::test_catalog_signatures, pic/tests/test_cuda_parity.py::test_folders_declare_their_kernels: passed
• An ad-hoc script (not committed) on Colella with 6×5×4 elements and degree (2,3,2):
  • Matrix-free M0–M3 dot agree with the assembled operators to about 1e-15 relative (kernel_3d_matrixfree against kernel_3d_mat).
  • Matrix-free and assembled diagonal() agree exactly (kernel_3d_diag).
  • L2Projector.get_dofs (kernel_3d_vec) and eval_quad (kernel_3d_eval) run.

Not run locally: the full test suites, test_mass_matrices.py (32³ and 48³ grids, slow) and MPI runs. No MPI code changed.

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