Visualization Tools

TRINITY’s plotting code lives outside the installed trinity package, under paper/methods/figures/, with two entry points:

Published paper figures are regenerated from the bundled paper/methods/data/*.npz files by a single entry point:
```
python paper/methods/make_figures.py            # all published figures
python paper/methods/make_figures.py teaser     # one figure (prefix match)
```
Output lands in paper/plots/. The figure scripts it drives live under paper/methods/figures/ (with shared infrastructure in paper/_lib/); see Published Paper Figures below.
Exploratory / personal scripts — the broader catalogue below — live under scratch/. They are not part of the installed package and are run directly, writing to fig/{folder_name}/.

Each script is a thin wrapper around the Output Reader API API: it loads one or more simulations, extracts a few time series, and renders them with a shared Matplotlib style sheet, paper/_lib/trinity.mplstyle. The scripts double as worked examples of how to drive the reader API from user code.

Common features

Most plotting scripts share a common parser (paper/_lib/cli.py): they accept a folder of simulations through -F and auto-discover the individual runs underneath, so a single invocation can render either one simulation or a full (mCloud × SFE) grid. Core density is selected through -n/--nCore, figure output is redirected through -o, and the shared style sheet keeps figures from different scripts visually consistent. Phase, cloud- edge, and collapse markers are drawn via --show-* flags.

Usage examples

# All runs in a folder (auto-discovers the mCloud/SFE grid)
python paper/methods/figures/paper_feedback.py -F /path/to/outputs/sweep_test

# Filter by core density
python paper/methods/figures/paper_feedback.py -F /path/to/outputs --nCore 1e4

# Custom output directory
python paper/methods/figures/paper_feedback.py -F /path/to/outputs -o /path/to/figures

# Single run from an explicit path
python paper/methods/figures/paper_feedback.py /path/to/dictionary.jsonl

Published Paper Figures

These are driven by paper/methods/make_figures.py from the bundled paper/methods/data/*.npz files and rendered into paper/plots/. Each row maps a short name (usable as a prefix on the command line) to its script and bundle:

Name	Script (`paper/methods/figures/`)	Figure
`density`	`paper_densityProfile.py`	Density-profile ingredients (uniform, \(r^{-1}\), \(r^{-2}\), Bonnor-Ebert) plus the phase timeline.
`teaser`	`paper_teaser.py`	Three-panel teaser: \(R_b\)/\(v_b\), feedback-force decomposition, and the \(Q_i\) photon budget.
`radiusComparison`	`paper_radiusComparison.py`	\(R(t)\) comparison of TRINITY against WARPFIELD and the analytic scaling laws (Weaver, Spitzer, momentum).
`rcloud_smoothing`	`paper_rcloud_smoothing.py`	Cloud-edge density-smoothing schematic with before/after LSODA trajectories.

The remaining paper/methods/figures/ script, paper_feedback.py (Force Budget Plots below), and the scratch/ catalogue are run directly rather than through make_figures.py.

Force Budget Plots

paper_feedback.py

(Lives under paper/methods/figures/; run directly.) Stacked-area plot showing the relative importance of feedback forces as fractions of the total:

Gravity (black)
Driving pressure F_drive (blue): the bubble’s driving term (the larger of bubble pressure and \(P_{\rm HII}\)), with the wind, SN, and \(P_{\rm HII}\) contributions overlaid as hatching inside the band (wind purple, SN tan, \(P_{\rm HII}\) red)
Radiation (teal): direct and reprocessed radiation pressure
PISM (white): external ISM pressure

Configuration

Most scripts share a common parser (paper/_lib/cli.py), which provides:

# Input (use a folder OR a single dictionary.jsonl path)
data                  Positional path to one dictionary.jsonl (optional)
-F, --folder PATH     Folder of simulation subfolders to auto-discover

# Filtering
-n, --nCore VALUE     Filter by core density (e.g., "1e4")
--mCloud VALUES       Filter by cloud mass (one or more)
--sfe VALUES          Filter by star-formation efficiency (one or more)

# Output / styling
-o, --output-dir PATH Directory to save figures (default: fig/)
--palette NAME        Colour palette
--info                Print discovered runs and exit

# Marker overlays
--show-phase          Energy/transition/momentum phase boundaries
--show-rcloud         Cloud-edge crossing
--show-rcloud-horizontal  Horizontal R_cloud line (on radius-on-y plots)
--show-collapse       Collapse onset
--show-noPHII         Overlay the no-PHII companion run
--show-all-markers    Enable all of the above

Output

Standalone scripts (run directly) save their figures to the fig/{folder_name}/ directory as PDF files; the make_figures.py entry point instead collects the published figures in paper/plots/. Standalone filenames include a parameter tag built from the (mCloud, SFE, nCore) combination actually plotted, so runs with different parameters never overwrite each other:

fig/
└── sweep_test/
    ├── feedback_M1e7_sfe020_n1e4.pdf            # single run
    ├── feedback_M1e5-1e8_sfe001-080_n1e4.pdf    # grid of runs
    └── ...