dataset card

README.md

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+---
+license: mit
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- matplotlib
+- seaborn
+- data-visualization
+- rl-environment
+- verifiers
+- code
+size_categories:
+- n<1K
+---
+
+# matplotlib-tasks-v1
+
+Task dataset for a Matplotlib/Seaborn RL / eval environment, in the shape used by the
+[Prime Intellect Environments Hub](https://app.primeintellect.ai/dashboard/environments).
+
+27 plotting tasks over a fixed set of small datasets. The model builds the figure, then reads
+the answer back off the axes; the grade is an exact row comparison against a reference.
+Deterministic — no LLM judge, no external API, no network, **and no pixels**.
+
+| Category | Tasks | Covers |
+|---|---|---|
+| line_plots | 6 | ydata/xdata readback, multiple lines, legend texts, linestyle and marker, plotting a derived series |
+| axes_config | 6 | explicit limits, title and axis labels, explicit ticks, subplot grids, log scale, limits not filtering data |
+| bar_charts | 5 | heights, widths, `barh`, stacked bars via `bottom`, explicit tick labels |
+| statistical | 5 | histogram counts and edges, custom bin edges, scatter offsets, boxplot median and whiskers |
+| seaborn | 5 | `lineplot` passthrough, `barplot` group means, `barplot` with `estimator="sum"`, `scatterplot` collections, `histplot` patch heights |
+
+## ⚠ Why this dataset does not compare images
+
+Image comparison is the obvious way to grade a plot and the wrong one: it fails on font
+hinting, DPI, backend and antialiasing long before it tests whether the model plotted the right
+thing. Here the model builds the figure and the grade reads values back off the artists.
+
+That still leaves a determinism trap, and it was **measured** on matplotlib 3.11.1, not assumed:
+
+```
+ln.get_color()  ->  (0.1215…, 0.4666…, 0.7058…)   from the STYLE CYCLE — version-dependent
+ax.get_xlim()   ->  (-0.2, 4.2) after autoscale   depends on margin defaults
+ln.get_ydata()  ->  exactly what was passed in    stable
+hist counts     ->  computed from the data        stable
+ax.get_xlim()   ->  after ax.set_xlim(0, 10)      stable — the task set it
+```
+
+**Every task therefore grades only:** user-supplied data, computed values, and properties the
+task itself sets explicitly. Never a default colour, never an autoscaled limit, never an
+automatic tick location.
+
+## Fields
+
+| Field | Description |
+|---|---|
+| `task_id` | stable id, e.g. `mpl-017` |
+| `category` | one of the five above |
+| `prompt` | the natural-language instruction |
+| `data_description` | the preloaded variables, as shown to the model |
+| `data` | those variables as JSON, so the task is self-contained |
+| `expected_output` | `{"rows": [[...]]}` — the reference result |
+
+## Verification
+
+Every task is independently checked: it runs, is deterministic **across two freshly built
+figures**, returns a non-empty list of JSON-safe primitives — which catches an Artist or numpy
+scalar leaking out instead of a plain value — contains no NaN/inf, and survives the
+serialisation round-trip exactly. All 27 pass on matplotlib 3.11.1 / seaborn 0.13.2 with the
+Agg backend.
+
+Builder and verifier:
+[`build_tasks.py`](https://github.com/eltociear/my-molt-agent/blob/main/environments/matplotlib_env/build_tasks.py).