Add Dice.from_dist to approximate distributions via quantile slicing - #14
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`Dice.from_dist(dist, n=6, quantiles=None)` builds a dice that approximates a continuous distribution by slicing equiprobable quantiles. It is duck-typed on the inverse-CDF: works with scipy frozen dists (.ppf) and the stdlib statistics.NormalDist (.inv_cdf), so no new dependency is added. Includes notebook demos (NormalDist plus a numpy exponential showing the duck-typing) and tests covering equiprobability, normal symmetry, custom quantiles, mean tracking, and the error cases. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
# Conflicts: # dicekit/__init__.py # nbs/__init__.py
Configure shared Conductor scripts for the uv + marimo workflow: - setup: uv sync - run: marimo edit on the nbs/ folder, bound to $CONDUCTOR_PORT, headless - archive: make clean - run_mode: concurrent (per-workspace port, no shared local state) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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What
Adds
Dice.from_dist(dist, n=6, quantiles=None)— a classmethod that approximates a continuous distribution with aDiceby slicing equiprobable quantiles out of it.How
.ppf(scipy frozen distributions) or.inv_cdf(stdlibstatistics.NormalDist), raisingTypeErrorif neither is present. No new package dependency.n(default6): number of equiprobable faces, placed at the midpoint of each quantile bin —inv_cdf((i + 0.5) / n).quantiles: optional explicit sequence of probabilities in(0, 1)to slice at instead ofnmidpoints; faces stay equiprobable. Validated to be non-empty with everyqstrictly in(0, 1)(avoids±infon unbounded distributions), elseValueError.Notebook
Demo cells added in
nbs/__init__.py(source of truth): astatistics.NormalDistexample, the documented kwargs, and anumpyexponential example that doubles as a duck-typing showcase.dicekit/__init__.pyregenerated viamake build.Tests
8 new tests in
tests/test_basics.py: equiprobable faces, normal symmetry, monotonic midpoints, custom quantiles, duck-typed.ppfstub, mean tracking,TypeErroron bad object,ValueErroron bad quantiles.uv run pytest -q→ 34 passed.🤖 Generated with Claude Code