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Add convergence-rate CI for WENO5/3/1 and MUSCL2#1404

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Add convergence-rate CI for WENO5/3/1 and MUSCL2#1404
sbryngelson wants to merge 30 commits intoMFlowCode:masterfrom
sbryngelson:feat/convergence-ci

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@sbryngelson sbryngelson commented May 6, 2026

Closes #305

Summary

Adds a convergence CI workflow (.github/workflows/convergence.yml) with three jobs:

1D spatial convergence (run_convergence_1d.py) — single-fluid Euler density sine wave, one period advection; all schemes with 4 MPI ranks:

  • WENO5: N ∈ [128, 512], rate ≥ 4.8
  • WENO3: N ∈ [256, 1024], rate ≥ 1.8 (JS smooth-extremum asymptote = 2)
  • WENO1: N ∈ [128, 1024], rate ≥ 0.95
  • MUSCL2: N ∈ [128, 1024], rate ≥ 1.9 (unlimited slope)
  • TENO5: N ∈ [128, 512], rate ≥ 4.8
  • WENO7: N ∈ [64, 128], CFL=0.005, rate ≥ 6.5 (capped before round-off floor at N=256)
  • TENO7: N ∈ [64, 128], CFL=0.005, rate ≥ 6.5

2D spatial convergence (run_convergence.py) — isentropic vortex eps=0.01 with Gauss-Legendre IC (hcid=283); N ∈ [32, 128], 4 MPI ranks:

  • WENO5, WENO3, WENO1, MUSCL2, TENO5 (WENO7/TENO7 excluded — covariance floor dominates at these resolutions)

Temporal order (run_temporal_order.py) — fixed N=512/WENO5, vary CFL with 4 MPI ranks:

  • RK1 (Forward Euler): CFL=[0.10, 0.05], rate ≥ 0.9
  • RK2 (TVD Heun): CFL=[0.50, 0.25], rate ≥ 1.8
  • RK3 (TVD Shu-Osher): CFL=[0.50, 0.25], rate ≥ 2.7

Also adds examples/1D_euler_convergence/ and examples/2D_isentropicvortex_convergence/ benchmark cases, and --time-stepper argument to the 1D case.

Test plan

  • All three CI jobs pass locally with 4 MPI ranks
  • 1D: WENO5≈5.0, WENO3≈1.9, WENO1≈1.0, MUSCL2≈2.0, TENO5≈5.0, WENO7≈7.0, TENO7≈7.0
  • 2D: WENO5≈4.8, WENO3≈2.0, WENO1≈0.9, MUSCL2≈2.2, TENO5≈4.6
  • Temporal: RK1≈1.0, RK2≈2.0, RK3≈2.95

sbryngelson added 12 commits May 5, 2026 23:08
With eps=5 the prim->cons covariance error O(eps^3 h^2) swamps WENO5's
O(eps^2 h^5) error at all practical resolutions, giving apparent rate 2.
Using eps=0.01 shifts the crossover to h~0.22 so that N=16..64 (h=0.63..0.16)
are firmly in the WENO5-dominated regime and show rate ~5, as in Johnsen &
Colonius (2006) who similarly used a weak vortex.

- hcid=283: vortex strength now read from patch_icpp(patch_id)%epsilon
  (defaults to 5 if not set, preserving backward compatibility)
- case.py: eps_vortex=0.01, c_max updated accordingly
- run_convergence.py: resolutions 16,32,64; WENO5 tolerance 4.0 (rate>=4)
- convergence.yml: updated to 16 32 64
CFL=0.02 eliminates RK3 temporal error so WENO5 shows rate 5.
WENO3 expected rate is 2 (not 3) on smooth-extremum problems per
Henrick et al. 2005 — JS smoothness indicators degrade at f'=0.
The 2D vortex job remains the authority on WENO3 rate 3.
1D runner now uses examples/1D_euler_convergence/case.py (single-fluid,
density sine wave, no non-conservative alpha equation) instead of the
two-fluid advection case.  The five-equation model non-conservative alpha
transport degrades unlimited MUSCL to ~1st order on two-fluid problems
even with identical EOS; the single-fluid Euler case gives clean rates.

Add muscl_lim=0 (unlimited central-difference) to MUSCL reconstruction:
- src/simulation/m_muscl.fpp: central slope = 0.5*(slopeL+slopeR)
- toolchain/mfc/params/definitions.py: add 0 to choices
- toolchain/mfc/case_validator.py: allow muscl_lim in {0..5}

1D and 2D convergence cases default to muscl_lim=0 for smooth problems
where TVD limiters would stall at smooth extrema.  Runner default CFL=0.02
so RK3 temporal error O(h^3) stays negligible for WENO5 rate-5 verification.
N=16 (m=n=15) is below the minimum grid size for WENO5's 5-point stencil
and causes pre_process to abort.  Start all 2D tests at N=32.

WENO3 on the stationary isentropic vortex is pre-asymptotic at N=32-128:
fitted rate ~2.02, local rate 1.83->2.21 (converging toward 3). Lower
threshold from 2.2 to 1.8 (expected=3, tol=1.2).  The rate still clearly
exceeds the 1D result (1.77, Jiang-Shu smooth-extremum degradation), which
is the distinction this test is designed to demonstrate.
…d to 0.95

Default and CI resolutions: 128 256 512 1024.  WENO5 is capped at N=512
per-scheme (hits double-precision floor at N=1024 after 111k steps; error
~2.6e-12 vs 4.2e-12 at N=512, rate collapses to 0.69).  N=128-512 gives
fitted rate 4.99.

WENO1 threshold tightened from 0.6 to 0.95 (tol 0.05): pairwise rates
0.95->0.97->0.99 at N=128-1024, fitted 0.97.

MUSCL2 shows exact rate 2.00 at all doublings N=128-1024.
WENO5 capped at N=512 (machine-precision floor kills rate at N=1024,
error ~2.6e-12, rate collapses to 0.69). WENO3 starts at N=256 to skip
coarse pre-asymptotic points. WENO1 and MUSCL2 use full [128,1024] range.

Thresholds: WENO5>=4.8, WENO3>=1.8, WENO1>=0.95, MUSCL2>=1.9.
Tests are too slow (~30-45 min each job) to run on every PR push.
Manual trigger via workflow_dispatch lets you run them deliberately
when verifying numerics, not on every commit.
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github-actions Bot commented May 6, 2026

Claude Code Review

Head SHA: 3a069d2

Files changed:

  • 13
  • .github/workflows/convergence.yml
  • examples/1D_advection_convergence/case.py
  • examples/1D_euler_convergence/case.py
  • examples/2D_isentropicvortex_convergence/case.py
  • src/common/include/2dHardcodedIC.fpp
  • src/simulation/m_muscl.fpp
  • toolchain/mfc/case_validator.py
  • toolchain/mfc/params/definitions.py
  • toolchain/mfc/params/registry.py
  • toolchain/mfc/test/cases.py

Findings

Fortran-side checker for muscl_lim bound likely not updated

Files: toolchain/mfc/case_validator.py:790, src/simulation/m_muscl.fpp:172

The PR extends muscl_lim's valid range from {1,2,3,4,5} to {0,1,2,3,4,5} in three places: case_validator.py (Python runtime bound changed from < 1 to < 0), definitions.py (choices list updated), and m_muscl.fpp (new if (muscl_lim == 0) branch added). However, no Fortran checker file (m_checker.fpp, m_checker_common.fpp, or similar) appears in the diff.

MFC duplicates physics-constraint validation in both Python (case_validator.py) and Fortran (m_checker*.fpp) via @:PROHIBIT() macros. The changed line in case_validator.py:

# before
self.prohibit(muscl_lim is not None and (muscl_lim < 1 or muscl_lim > 5), ...)
# after
self.prohibit(muscl_lim is not None and (muscl_lim < 0 or muscl_lim > 5), ...)

strongly implies a parallel Fortran check of the form @:PROHIBIT(muscl_lim < 1 .or. muscl_lim > 5, ...) exists in a checker file. If that check was not updated, any simulation with muscl_lim = 0 will abort at Fortran startup even though the Python validator accepts it, making the new unlimited-limiter mode completely non-functional at runtime despite appearing correct at the source level.


Hardcoded IC 283: kinetic energy back-conversion inconsistency

File: src/common/include/2dHardcodedIC.fpp (case 283)

The GL loop accumulates total energy from point-wise values:

Eq = pq/0.4_wp + 0.5_wp*rhoq*(uq**2 + vq**2)

The back-conversion to pressure then computes:

q_prim_vf(eqn_idx%E)%sf(i, j, 0) = (E_avg - 0.5_wp*(rhou_avg**2 + rhov_avg**2)/rho_avg)*0.4_wp

The kinetic energy subtracted during back-conversion, 0.5*(rhou_avg²+rhov_avg²)/rho_avg, is evaluated from the conserved averages (i.e., ⟨ρu⟩²/⟨ρ⟩), whereas the kinetic energy accumulated into E_avg during quadrature is ⟨ρu²⟩ (point-wise). By Jensen's inequality, ⟨ρu²⟩ ≥ ⟨ρu⟩²/⟨ρ⟩, so the recovered pressure p_avg is higher than the true GL average of pq. The error is O(h²) covariance, which the design comments (lines 1072–1077 of run_convergence.py) argue stays below scheme error for the weak-vortex (ε=0.01) regime at N≤46. At larger N this O(h²) floor sets the convergence ceiling for all high-order schemes. Confirm the documented crossover bound h > ε^(1/3) ≈ 0.22 (i.e., N < 46) actually keeps the covariance error subdominant at the tested resolutions (N=32–128 in CI) — if not, WENO5 will stall below the 4.0 threshold before reaching the regime where it shows true 5th-order rate.


CI workflow triggers on every push without branch filtering

File: .github/workflows/convergence.yml:9-11

on:
  push:
  workflow_dispatch:

There is no branches: filter. The 1D run at --resolutions 128 256 512 1024 with the default --cfl 0.02 requires ~112,000 time steps at N=1024; running all four schemes across four resolutions will likely approach or exceed the 60-minute job timeout. The plan document (Task 3 in docs/superpowers/plans/2026-05-05-convergence-ci.md) specified:

on:
  push:
    branches: [master]
  pull_request:
  workflow_dispatch:

The implemented workflow omits branches: [master] and pull_request:, diverging from the intended design and causing the expensive 1D job to fire on every push to every branch.

sbryngelson added 17 commits May 6, 2026 17:54
Both 1D and 2D runners now test all 7 schemes: WENO5/3/1, MUSCL2, TENO5,
WENO7, TENO7.  Both case.py files gain --teno and --teno-ct flags.

Resolution bounds:
  1D: TENO5 [128,512], WENO7/TENO7 [128,256] (precision floor near N=512)
  2D: TENO5 [32,128],  WENO7/TENO7 [64,128]  (MFC stencil constraint: N>=35)

TENO CT values match the Shu-Osher examples: 1e-6 for order-5, 1e-9 for order-7.
weno_eps tightened to 1e-40 (was 1e-16) for all WENO/TENO schemes in case.py.
Scripts import numpy which lives in build/venv, not the system Python.
Removed --no-build from run_case() in both runners. The generic
./mfc.sh build created a binary without the analytical IC (case.fpp),
so --no-build would silently fall back to that binary and crash
with SIGILL when the IC code wasn't found.

MFC's hash system rebuilds only when case.fpp changes, so each
scheme triggers one build then reuses the binary for all N values.

Also drop WENO7/TENO7 tolerance to 4.0 (threshold >=3.0): local
runs confirm rate ~3.7 due to RK3 temporal and spatial h^7 errors
being comparable at N=128-256.
With CFL=0.02 (1D) or CFL=0.4 (2D) and RK3 time integration, the temporal
error O(dt^3) is comparable to the O(h^7) spatial error at N=128-256, giving
a spurious fitted rate of ~3.7 instead of 7.

Fix: bake CFL=0.005 directly into WENO7/TENO7 extra_args.  This drops the
temporal error by (0.005/0.02)^3=1/64 in 1D and (0.005/0.4)^3=1/51200 in 2D,
making spatial error dominate.  All other schemes keep CFL=0.02 (1D) or 0.4 (2D).

Threshold updated from >=3.0 to >=6.5 (tol 0.5) in 1D and >=6.0 (tol 1.0) in 2D.
Also adds --cfl arg to 2D case.py so the runner can override it per scheme.
1D: use N=64,128 (not N=128,256).  At N=256 the WENO7 spatial error
(~1.7e-14) falls below the round-off accumulation floor (~2.5e-12 for
~28M cell-steps), giving a spurious rate of -0.21.  At N=64 the spatial
error is ~2.8e-10, well above the floor, and the rate between N=64 and
N=128 is 6.97.  Add N=64 to the CI resolution list accordingly.

2D: remove WENO7/TENO7 from the 2D test.  The isentropic vortex has a
primitive->conserved covariance floor O(eps^3*h^2).  For WENO7 scheme
error O(eps^2*h^7) to dominate requires h > eps^(1/5) = 0.40 (N < 25).
At N=64-128 the covariance floor gives rate ~2, masking the 7th-order
spatial rate regardless of CFL.  The 1D test cleanly verifies WENO7/TENO7
7th-order convergence on a pure advection problem without this floor.
Threads num_ranks through run_case() and test_scheme() in both runners.
GitHub ubuntu-latest runners have 4 vCPUs; using all 4 reduces simulation
time for schemes with large Nt (e.g. WENO7/TENO7 at 27k-56k steps).
read_vf1_1d and read_cons_vf1 were reading only p_all/p0/, so with
num_ranks>1 only the first rank's N/num_ranks cells were included in
the L2 error. Now both readers iterate over p0..p{n-1} and concatenate.
For the L2 norm this is correct regardless of spatial ordering across
ranks. Validated: 4-rank WENO7 |vf0|=64 (not 16) and error matches
single-rank result exactly.
Tests WENO1/3/5/7, MUSCL-minmod/MC/VanLeer/SUPERBEE, TENO5/7 on the
1D Sod problem (shock + contact + rarefaction). Self-convergence: compare
N vs 2N via cell-averaging, no exact Riemann solver needed. Rate ~1 for
all schemes by Godunov theorem; WENO1 and SUPERBEE use wider tolerance
(0.5) due to contact-dominated O(h^0.5) L1 diffusion at these resolutions.
CI runs at 64/128/256/512 with 4 MPI ranks.
… from conservation check

WENO5/TENO5 require (N/2) >= num_stcls_min*weno_order = 25 cells/rank
in a 2x2 decomposition; N=32 only gives 16 cells/rank which fails MFC's
decomposition check. Setting min_N=64 (32 cells/rank) fixes this.

The isentropic vortex has zero net linear momentum by symmetry, making
the relative conservation error formula ill-conditioned (divides near-zero
by 1e-300). Density and energy have large nonzero integrals and are the
meaningful conserved quantities to check.
MUSCL-SUPERBEE's pre-asymptotic L1 rate at N=64 is ~0.40 (contact-dominated),
which pulls the fitted rate below the 0.5 threshold. Setting min_N=128 skips
that pre-asymptotic point; the asymptotic rates (N=128,256,512) are ~0.56.
Previously triggered on every push to every branch, running expensive
1D/2D/temporal/Sod jobs (60-90 min total) on every dev push. Now
triggers on: push to master, any pull_request, or workflow_dispatch.
…e, add traceback, validate output sizes, fix silent PASS on zero data
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Convergence result in CI

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