plot
/plot
Draw standard PNG and SVG plots from saved results without simulating - sweep curves or two-parameter heatmaps with target bounds, the power distribution of a run, signed bar charts and histograms. Use it to show study or run results.
- Author
- JunLin615 ↗
- Repository
- os-optics-kit ↗
- Licence
- MIT
- Last repository change
- 11.11.2026
Assessment and security
- Files in this package
- 1
- Scripts
- 0
- HTML comments
- 0
- URLs in SKILL.md
- 0
No signals detected. Repository changed on 11.11.2026, without references to retired models or APIs.
MIT, open: use and modify while retaining author attribution.
What it does and when to use it
Draw standard PNG and SVG plots from saved results without simulating - sweep curves or two-parameter heatmaps with target bounds, the power distribution of a run, signed bar charts and histograms. Use it to show study or run results.
Original author description
Draw standard PNG and SVG plots from saved results without simulating - sweep curves or two-parameter heatmaps with target bounds, the power distribution of a run, signed bar charts and histograms. Use it to show study or run results.
How it works
- When to use
- When not to use
- Inputs
- Outputs
- Minimal example
- Limits
- Version
SKILL.md preview
---
name: plot
description: Draw standard PNG and SVG plots from saved results without simulating - sweep curves or two-parameter heatmaps with target bounds, the power distribution of a run, signed bar charts and histograms. Use it to show study or run results.
version: 0.3.0
command: os-optics-kit plot
requires: os-optics>=0.13,<0.14; os-optics-kit[plot]
kind: tool
---
# plot
## When to use
- Show a target against a swept parameter (`sweep`), every sample marked by its outcome.
- Show where a run's power went (`power`).
- Plot your own labelled values (`bars`) or a value distribution with bounds (`histogram`).
## When not to use
- 3D views or ray pictures: use `os-optics view RUN`.
- Numbers for a decision: read `summary`, `compare` or the study's `summary.json`.
## Inputs
- `sweep STUDY_DIR --y COLUMN`: COLUMN is `target:<id>`, `derived:<name>` or `param:<name>`.
- `power RUN_DIR`.
- `bars DATA.json`: `{"labels", "values", "unit", "title", "ylabel"?}`.
- `histogram DATA.json`: `{"values", "unit", "title", "xlabel"?, "bounds"?: {"minimum", "maximum"}, "bins"?}`.
- `--out DIR` (default: `plots/` in the study, or next to the run), `--name STEM`.
- `--theme presentation|report|FILE` and `--set KEY=VALUE` (theme keys: `language=zh-CN`, `background=dark`,
`font_scale=1.3`, `size=4k`, `title=false`, `units={"mm": "um"}`; `os-optics-kit present settings` lists
them). For a set of figures with a gallery, use `present`.
## Outputs
`<name>.png` and `<name>.svg`, each captioned with the data file (relative path and sha256 prefix), the
engine build and the catalog release. With `--theme presentation` that record goes to
`<name>.provenance.txt` and the caption to `<name>.caption.txt`, keeping the figure clean. Stdout: one JSON document with the written paths and point counts.
Exit 0 written, 4 invalid input or missing matplotlib (`PLOT_EXTRA_MISSING`).
## Minimal example
```
python -m pip install "os-optics-kit[plot]"
os-optics project example --kind focus > project.json
os-optics project run project.json --out-dir run
os-optics-kit plot power run
```
After a `sweep` into `study`: `os-optics-kit plot sweep study --y target:spot_radius`.
## Limits
- Samples without an exact value are drawn as hollow markers below the lowest value, never as values.
- `bars` and `histogram` plot the given numbers only; units come from the data file.
## Version
0.3.0 (os-optics-kit 0.3.0): presentation themes (`--theme`, `--set`), verified with os-optics 0.13.0.
0.2.0 (os-optics-kit 0.2.0), verified with os-optics 0.13.0, matplotlib 3.11 and catalog release
2026-10-28.1.
Versions
| Repository | Score | Licence |
|---|---|---|
| This page · JunLin615/os-optics-kit | 100 | MIT |
| wenhaochai/claude-plugins | 100 | MIT |
| liouhai/plot-is-all-you-need | 100 | MIT |
| saigauthamr/fiction-craft-skills | 90 | Apache-2.0 |
Database snapshot: 13.11.2026 · package version 661c9854f325 (SHA-256 digest of the entire package)
Downloads in the last 30 days: 0 · ranking
Report a problem with this skill: harmful content, incorrect descriptions or an author’s removal request.
Similar skills
- 100charts
Draw a static chart, graph or plot as a PNG with seaborn in the house style (the shared palette, DM Sans, the slides' type sizes): bar, line, scatter, histogram, box, heatmap, small multiples. The default for any chart: use it whenever a chart, graph or plot is to be created… - 100data-charts
Analyze tabular data and render charts (bar, line, scatter, pie, histogram) to PNG/SVG with pandas + matplotlib. Use whenever the user wants to plot, chart, graph, or visualize data from a CSV/JSON/Excel file or inline numbers. - 100visualization
Create publication-quality scientific figures and plots using Python (matplotlib, seaborn, plotly). Supports bar charts, scatter plots, heatmaps, box plots, violin plots, survival curves, network graphs, and more. Use when user asks to plot data, create figures, make charts,… - 100boardplot-chart
Draw consulting-grade charts, tables and maps as SVG or PNG with Boardplot, or build Boardplot React chart components. Use when the user requests a chart, graph, table exhibit, map or chart component. - 95plotly
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards.… - 100ggnet
Generate charts with GGNet, the grammar-of-graphics plotting library for .NET/Blazor (C#, fluent DSL, SVG output). Use when creating, editing, or debugging plots in a C#/.NET/Blazor codebase that references GGNet — chart, plot, graph, dashboard, sparkline, histogram, heatmap,…