Weighted random choice picks among options by probability so the common case dominates and surprises stay rare

Weighted-random-choice picks among options with unequal probabilities — for example one sample 70% of the time, another 20%, silence 10%. Unlike a flat random pick, weighting lets you make the common case dominate while keeping surprises rare-but-present. It applies to choosing samples, notes, or which transform to apply, and is the tool for controlled unpredictability: you shape the distribution so most results are the expected material and the occasional outlier adds interest without derailing the groove.

Examples

// Strudel: wchoose favors the first option wchoose([s(“bd”),0.7],[s(”~”),0.2],[s(“cp”),0.1])

Assessment

How does weighted-random-choice differ from a flat random pick, and give a weighting that keeps surprises rare but present.