chaotic_pfc.cli.run_all

Run every experiment in sequence.

Nested under chaotic-pfc run all. Previously the top-level run_all.py script, which shelled out to each numbered script via subprocess. The in-process version here is faster (no fork overhead, the Numba cache is shared across experiments) and makes the control flow much easier to follow.

Usage examples

Display every figure interactively:

chaotic-pfc run all

Save all figures to disk (keeps display for non-sweep experiments):

chaotic-pfc run all --save

Headless mode (implies --save):

chaotic-pfc run all --no-display

Skip the long Lyapunov sweep (~5 h); assumes the .npz checkpoints are already present, so plotting still works:

chaotic-pfc run all --no-display --skip-sweep

Run the sweep in quick mode (tiny grid, seconds) — useful for CI:

chaotic-pfc run all --no-display --quick-sweep

Run the sweep with adaptive Lyapunov early-stop (≈3-4× speedup, mean |Δλ| < 0.001 vs. the fixed-Nmap reference):

chaotic-pfc run all --no-display --adaptive

Tighten the adaptive tolerance for closer-to-reference accuracy:

chaotic-pfc run all --no-display --adaptive --tol 1e-4

Functions

add_parser(subparsers)	Register the run all subcommand.
run(args)	Execute run all.

chaotic_pfc.cli.run_all.add_parser(subparsers)

Register the run all subcommand.

Parameters:

subparsers (_SubParsersAction)

Return type:

None

chaotic_pfc.cli.run_all.run(args)

Execute run all.

Parameters:

args (Namespace)

Return type:

int