bloc.plotting.trajectory_dashboard#

General-purpose Trajectory Dashboard (Bloc analysis toolbox).

A standalone Dash/Plotly app that reads the cached scenarios of a running Bloc GUI (via its REST API) and plots every reactor trajectory in (temperature, residence-time) space. Clicking a trajectory drives the open GUI to load that scenario (the scenario-focus channel), and the clicked path is highlighted with a gold halo.

It is config-agnostic: the title is taken from the loaded YAML’s name (e.g. SPRING_A3 Stability Map) and it plots whatever scenarios the GUI exposes.

Single-user by design: the app keeps its rows/focus/theme in one server-side state dict, so it serves ONE local analyst next to ONE GUI. Opening it from two browsers would share focus/theme; that trade-off is deliberate (no session plumbing) — don’t expose it beyond localhost.

Launch it together with the GUI via the CLI:

bloc <config>.yaml --trajectories      # starts the GUI *and* this dashboard

or standalone against an already-running GUI:

python -m bloc.plotting.trajectory_dashboard --gui http://127.0.0.1:8050

──────────────────────────────────────────────────────────────────────────── WHAT THIS DASHBOARD CLASSIFIES — carbon-species dominance, hardcoded ──────────────────────────────────────────────────────────────────────────── The coloured trajectories + isolines are carbon-specific. To generalise to other species or metrics, edit only the block marked CLASSIFIER below:

categories + colours → CATEGORY_COLORS, from bloc.plotting.stability_map.

mass vs mole fraction → classify_series() uses mass fractions (bloc.chem.carbon_dominance.category_mass_fractions → gas.Y). For mole fractions, sum gas.X over each category’s species instead (or add a category_mole_fractions helper in carbon_dominance).

isoline scalar → currently solid-carbon yield %. Swap for any per-point scalar (e.g. a temperature, a conversion, a selectivity).

Everything below the classifier (figure assembly, click→focus) is species-agnostic.

Functions#

`classify_series`(gas, category_map, series)	Recompute per-point (dominant category, isoline scalar) for one trajectory.
`fetch_trajectories`(gui)	Fetch every cached scenario from the GUI API and classify each trajectory.
`build_figure`(rows, listing[, highlight_id, theme])	One Plotly figure: segment-coloured trajectories + scalar isolines.
`build_app`(gui)	Build the Dash app that reads `gui` and drives it on click.
`main`([argv])

Module Contents#

bloc.plotting.trajectory_dashboard.classify_series(gas, category_map, series)#

Recompute per-point (dominant category, isoline scalar) for one trajectory.

Returns arrays aligned by sample: T_C (°C), tau (s), cat (str), scalar (%, the isoline metric). X carries full mole fractions; Y is derived by Cantera from (T, P, X).

GENERALISE HERE: category_mass_fractions uses mass fractions (gas.Y). For a mole-based map, sum gas.X over each category’s species instead.

bloc.plotting.trajectory_dashboard.fetch_trajectories(gui)#

Fetch every cached scenario from the GUI API and classify each trajectory.

Returns (rows, listing). Raises on a non-reachable GUI.

bloc.plotting.trajectory_dashboard.build_figure(rows, listing, highlight_id=None, theme='light')#

One Plotly figure: segment-coloured trajectories + scalar isolines.

Each trajectory contributes 2-point segments to a per-category trace; every point carries customdata = scenario id so a click resolves the scenario. highlight_id draws the currently-overlaid scenario with a gold halo. theme (light/dark) selects the Plotly template + line ink.

bloc.plotting.trajectory_dashboard.build_app(gui)#: Build the Dash app that reads gui and drives it on click.

bloc.plotting.trajectory_dashboard.main(argv=None)#