Merge branch 'development' into mengxuan/duststoppingtime

Author: mxchen39

.github/workflows/rocm-diskgalaxy-container.yml

@@ -23,8 +23,15 @@ env:
   IS_INTERNAL_PR: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.repo.full_name == github.repository }}
 
 jobs:
+  check_changes:
+    uses: ./.github/workflows/check_changes.yml
+    with:
+      workflow_file: '.github/workflows/rocm-diskgalaxy-container.yml'
+
   build-and-push:
     runs-on: ubuntu-latest
+    needs: check_changes
+    if: needs.check_changes.outputs.has_non_docs_changes == 'true'
 
     steps:
       - name: Checkout

docs/markdown/parameters.md

@@ -26,6 +26,8 @@ These parameters are read in the `AMRSimulation<problem_t>::readParameters()` fu
 | derived_vars                | String        | A list of the names of derived variables that should be included in the plotfile and Ascent outputs.                                                                                                            |
 | regrid_interval             | Integer       | The number of timesteps between AMR regridding.                                                                                                                                                                 |
 | density_floor               | Float         | The minimum density value allowed in the simulation. Enforced through EnforceLimits.                                                                                                                            |
+| density_floor_expr          | String        | Optional AMReX parser expression for a spatially varying density floor. Variables: x, y, z, base_density_floor. When set, this overrides the constant floor.                                             |
+| debug_density_floor_plot    | Boolean (0/1) | If set to 1, adds a derived field `density_floor_dbg` to plotfiles to visualize the spatially varying density floor. Default: 0 (disabled).                                                                 |
 | temperature_floor           | Float         | The minimum temperature value allowed in the simulation. Enforced through EnforceLimits.                                                                                                                        |
 | max_walltime                | String        | The maximum walltime for the simulation in the format DD:HH:SS (days/hours/seconds). After 90% of this walltime elapses, the simulation will automatically stop and exit.                                       |
 | dt_cutoff                   | Float         | Timestep drop detector threshold. If the timestep drops below dt_cutoff \* current_time, the simulation aborts with an error message. This helps detect numerical instabilities early. Default: 0.0 (disabled). |

extern/AMReX-Hydro

@@ -0,0 +1,27 @@
+# Hydrostatic exponential atmosphere density floor unit test inputs
+
+# *****************************************************************
+# Problem size and geometry
+# *****************************************************************
+geometry.prob_lo     =  0.0  0.0  0.0
+geometry.prob_hi     =  1.0  1.0  1.0
+quokka.bc = ext_dir periodic periodic
+
+# *****************************************************************
+# VERBOSITY
+# *****************************************************************
+amr.v              = 0       # verbosity in Amr
+
+# *****************************************************************
+# Resolution and refinement
+# *****************************************************************
+amr.n_cell          = 8 8 8
+amr.max_level       = 0     # number of levels = max_level + 1
+amr.blocking_factor = 1     # grid size must be divisible by this
+
+do_reflux = 0
+do_subcycle = 0
+
+density_floor = 1.0
+atmosphere_scale_height = 0.25
+density_floor_expr = "1.0e-2*base_density_floor*exp(-x/0.25)"

extern/amrex

@@ -0,0 +1,39 @@
+# *****************************************************************
+# Problem size and geometry
+# *****************************************************************
+geometry.prob_lo     =  -5.0  -5.0  -5.0 
+geometry.prob_hi     =   5.0   5.0   5.0
+geometry.is_periodic =   1     1     1
+
+# *****************************************************************
+# VERBOSITY
+# *****************************************************************
+amr.v = 1
+
+# *****************************************************************
+# Resolution and refinement
+# *****************************************************************
+amr.n_cell = 32 32 8
+amr.max_level = 0
+amr.max_grid_size = 32
+amr.blocking_factor_x = 32
+amr.blocking_factor_y = 32
+amr.blocking_factor_z = 8
+
+do_reflux = 0
+do_subcycle = 0
+
+plotfile_interval = 10
+plotfile_prefix = balsara_vortex_plt
+checkpoint_interval = -1
+cfl = 0.3
+max_timesteps = 10000
+
+hydro.rk_integrator_order = 2
+hydro.reconstruction_order = 5
+hydro.use_dual_energy = 0
+
+setup.vortex_Mach = 0.1
+setup.vortex_b_magn = 0.1
+setup.advection = 1
+setup.num_orbits = 3

extern/fmt

@@ -32,6 +32,13 @@ class FitResult:
     sse: float
 
 
+@dataclass
+class ConvergenceRun:
+    label: str
+    data: Sequence[ConvergenceDatum]
+    fit: FitResult
+
+
 def read_convergence_csv(path: Path) -> List[ConvergenceDatum]:
     if not path.exists():
         raise FileNotFoundError(f"Could not find convergence file: {path}")
@@ -161,39 +168,32 @@ def geometric_space(x_min: float, x_max: float, num: int) -> List[float]:
     return [math.exp(log_min + (log_max - log_min) * i / (num - 1)) for i in range(num)]
 
 
-def make_plot(
-    data: Sequence[ConvergenceDatum],
-    fit: FitResult,
-    output_path: Path,
-) -> None:
+def make_plot(runs: Sequence[ConvergenceRun], output_path: Path) -> None:
     import matplotlib
 
     matplotlib.use("Agg")
 
     import matplotlib.pyplot as plt
 
-    nx_values = [item.nx for item in data]
-    error_values = [item.error for item in data]
-
-    nx_min = min(nx_values)
-    nx_max = max(nx_values)
-    nx_plot = geometric_space(nx_min, nx_max, 200)
-
-    model_values = []
-    asymptotic_values = []
-    for nx in nx_plot:
-        asymptotic = fit.amplitude * (nx ** (-fit.order))
-        model_values.append(math.sqrt(asymptotic * asymptotic + fit.floor * fit.floor))
-        asymptotic_values.append(asymptotic)
-
     fig, ax = plt.subplots(figsize=(6.0, 4.0))
-    ax.loglog(nx_values, error_values, "o", label="Simulation data")
-    ax.loglog(nx_plot, model_values, "-", label="Power law + floor fit")
-    ax.loglog(nx_plot, asymptotic_values, "--", label="Asymptotic power law")
-
-    x_lo, x_hi = ax.get_xlim()
-    ax.axhline(fit.floor, color="gray", linestyle="--", label="Roundoff floor")
-    ax.set_xlim(x_lo, x_hi)
+    color_cycle = plt.rcParams["axes.prop_cycle"].by_key()["color"]
+    for run_index, run in enumerate(runs):
+        color = color_cycle[run_index % len(color_cycle)]
+        nx_values = [item.nx for item in run.data]
+        error_values = [item.error for item in run.data]
+
+        nx_plot = geometric_space(min(nx_values), max(nx_values), 200)
+        model_values = []
+        asymptotic_values = []
+        for nx in nx_plot:
+            asymptotic = run.fit.amplitude * (nx ** (-run.fit.order))
+            model_values.append(math.sqrt(asymptotic * asymptotic + run.fit.floor * run.fit.floor))
+            asymptotic_values.append(asymptotic)
+
+        ax.loglog(nx_values, error_values, "o", color=color, label="_nolegend_")
+        ax.loglog(nx_plot, model_values, "-", color=color, label=f"{run.label} fit")
+        ax.loglog(nx_plot, asymptotic_values, "--", color=color, label="_nolegend_")
+        ax.axhline(run.fit.floor, color=color, linestyle=":", alpha=0.5, label="_nolegend_")
 
     ax.set_xlabel("Cells per wavelength (N_x)")
     ax.set_ylabel("L1 error norm")
@@ -211,8 +211,15 @@ def main() -> None:
     parser.add_argument(
         "--csv",
         type=Path,
-        default=Path("tests") / "hydro_wave_convergence.csv",
-        help="Path to the hydro wave convergence CSV file (default: tests/hydro_wave_convergence.csv).",
+        action="append",
+        default=[],
+        help="Path to a hydro wave convergence CSV file (repeatable).",
+    )
+    parser.add_argument(
+        "--label",
+        action="append",
+        default=[],
+        help="Optional label for a CSV file (repeatable, matches --csv order).",
     )
     parser.add_argument(
         "--output",
@@ -227,29 +234,38 @@ def main() -> None:
     )
     args = parser.parse_args()
 
-    data = read_convergence_csv(args.csv)
-    fit = fit_power_law_with_floor(data)
-    orders = compute_observed_orders(data)
+    csv_paths = args.csv or [Path("tests") / "hydro_wave_convergence.csv"]
+    if args.label and len(args.label) != len(csv_paths):
+        raise ValueError("Provide the same number of --label entries as --csv entries.")
+
+    labels = args.label or [path.stem for path in csv_paths]
+    runs: List[ConvergenceRun] = []
+
+    for label, csv_path in zip(labels, csv_paths):
+        data = read_convergence_csv(csv_path)
+        fit = fit_power_law_with_floor(data)
+        orders = compute_observed_orders(data)
+        runs.append(ConvergenceRun(label=label, data=data, fit=fit))
 
-    print("Hydro wave convergence statistics:\n")
-    print(f"{'nx':>8} {'dx':>14} {'error':>16}")
-    for row in data:
-        print(f"{row.nx:8d} {row.dx:14.6e} {row.error:16.6e}")
+        print(f"Hydro wave convergence statistics for {label} ({csv_path}):\n")
+        print(f"{'nx':>8} {'dx':>14} {'error':>16}")
+        for row in data:
+            print(f"{row.nx:8d} {row.dx:14.6e} {row.error:16.6e}")
 
-    print("\nObserved refinement ratios and orders (successive levels):")
-    print(f"{'nx':>8} {'ratio':>10} {'order':>10}")
-    for nx, ratio, order in orders:
-        print(f"{nx:8d} {ratio:10.3f} {order:10.3f}")
+        print("\nObserved refinement ratios and orders (successive levels):")
+        print(f"{'nx':>8} {'ratio':>10} {'order':>10}")
+        for nx, ratio, order in orders:
+            print(f"{nx:8d} {ratio:10.3f} {order:10.3f}")
 
-    print("\nPower-law + floor fit parameters:")
-    print(f"  amplitude (A): {fit.amplitude:.6e}")
-    print(f"  order (p):     {fit.order:.3f}")
-    print(f"  floor (f):     {fit.floor:.6e}")
+        print("\nPower-law + floor fit parameters:")
+        print(f"  amplitude (A): {fit.amplitude:.6e}")
+        print(f"  order (p):     {fit.order:.3f}")
+        print(f"  floor (f):     {fit.floor:.6e}\n")
 
     if args.no_plot:
         print("\nSkipping plot generation (per --no-plot).")
     else:
-        make_plot(data, fit, args.output)
+        make_plot(runs, args.output)
         print(f"\nSaved log-log plot to {args.output}")