pflow.xyz valid

pflow.xyz

Visual Petri net editor with an embeddable, dependency-free ES module

For agents: Visual Petri net editor and dependency-free ES modules (ODE solver, simulation, plotting), with a full guide and model-format docs for embedding in projects.

petri netsvisual editorode solverjavascript modulediscrete simulation

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-25T03:11:15.514Z. Cached copy · Source on pflow.xyz

# pflow.xyz

> Visual Petri net editor with an embeddable, dependency-free ES module
> library for discrete simulation and continuous (ODE) analysis. All modules
> are served from this origin with `Access-Control-Allow-Origin: *` — import
> them directly from any ad-hoc HTML page, no build step, no npm. ODE
> semantics are behaviorally identical to go-pflow (enforced by a parity
> test suite).

Models are JSON-LD (`@context: https://pflow.xyz/schema`): `places` and
`transitions` are objects keyed by id, `arcs` is an array of
`{source, target, weight}`. `initial`, `capacity`, and `weight` are vectors
(one entry per token color); capacity 0 means unbounded; an explicit 0
weight component means "this color is not involved".

## Docs

- [Full guide](https://pflow.xyz/llms-full.txt): model format, copy-paste
  recipes for solving/plotting/embedding, discrete simulation, related services
- [JSON-LD schema](https://pflow.xyz/schema): the @context served as JSON-LD
- [Book](https://book.pflow.xyz): Petri nets as a universal abstraction

## Modules

- [petri-solver.js](https://pflow.xyz/petri-solver.js): mass-action ODE
  solver (Tsit5, adaptive) + SVGPlotter interactive charts
- [petri-sim.js](https://pflow.xyz/petri-sim.js): discrete firing semantics,
  pure functions
- [petri-colors.js](https://pflow.xyz/petri-colors.js): colored-net unfolding
- [petri-view.js](https://pflow.xyz/petri-view.js): the full `<petri-view>`
  editor web component (with tabbed ODE analysis workbench)
- [petri-view.css](https://pflow.xyz/petri-view.css): editor styles, light +
  dark themes
- [petri-learn.js](https://pflow.xyz/petri-learn.js): differentiable fitting
  for Petri-net ODE models — forward + reverse-mode (adjoint) sensitivities,
  MSE/relative loss gradients, Adam / Nelder-Mead / coordinate-descent,
  `fitRates` convenience
- [petri-ssa.js](https://pflow.xyz/petri-ssa.js): portable Gillespie SSA
  (discrete-stochastic simulation) — byte-exact with go-pflow, pflow-rs and
  pflow-jl via a fixed PRNG (SplitMix64 → xoshiro256**) and a ported log;
  `simulate(model, {horizon, samples, realizations, seed})` → ensemble
  mean/stddev/final per place
- [petri-sde.js](https://pflow.xyz/petri-sde.js): chemical Langevin SDE —
  continuous state with the net's own intrinsic firing noise (Euler-Maruyama
  over the same propensities/stoichiometry `petri-ssa.js` compiles);
  `simulateSDE(model, {horizon, samples, realizations, seed})` → same shape
  as `simulate`, plus `diverged`/`reason`/`caveats` when the model gates
  (read arc, inhibitor, reached capacity — no continuous analogue). Not yet
  byte-exact cross-language the way SSA is.

**Which one for which question**: `petri-solver.js` refuses (rather than
silently mismodeling) a net with a read arc, inhibitor, reached capacity or
guard — use `petri-ssa.js` (or `petri-sde.js`, same refusal) for those, or
whenever token counts are small enough that variance is the answer, not
noise around it; `petri-sde.js` sits between the two
…

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