np.random.choice
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-07.)
np.random.choice has 7 facts recorded in Dontopedia across 3 references, with 1 live disagreement.
Mostly:rdf:type(2), has parameter(1), belongs to list(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (2)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
callsCalls(1)
- Search Lambda
ex:search-lambda
generatedByGenerated by(1)
- Documents
ex:documents
Other facts (6)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Numpy Function | [1] |
| Rdf:type | Function | [2] |
| Has Parameter | Size Parameter | [1] |
| Belongs to List | Np Random Module | [1] |
| Has Argument | Binary Options | [2] |
| Library | Numpy | [3] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (3)
ctx:claims/beam/3d2ebcc2-edde-456b-8a3a-1cb1f7bd0026- full textbeam-chunktext/plain1 KB
doc:beam/3d2ebcc2-edde-456b-8a3a-1cb1f7bd0026Show excerpt
# Example usage engine = { 'search': lambda x: np.random.choice([0, 1], size=x.shape[0]) } metrics = test_sparse_retrieval_engine(engine) print(f"Average Duration: {metrics['average_duration']:.4f} seconds") print(f"Average Throughput: …
ctx:claims/beam/059dfa3d-8d94-4bfc-bbe2-1c2228c8c6fe- full textbeam-chunktext/plain1 KB
doc:beam/059dfa3d-8d94-4bfc-bbe2-1c2228c8c6feShow excerpt
total_duration += timer.duration total_throughput += num_queries / timer.duration latencies.append(timer.duration) # Assuming results is a binary array indicating relevance precision = precision_scor…
ctx:claims/beam/7f086001-95b5-4788-b203-dee071ab04fa- full textbeam-chunktext/plain1 KB
doc:beam/7f086001-95b5-4788-b203-dee071ab04faShow excerpt
Returns: tuple: Tuple containing distances and indices of the nearest neighbors. """ return self.index.search(query_embedding, k) # Example usage if __name__ == "__main__": # Create instances of the modu…
See also
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.