Numpy Random Uniform
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Numpy Random Uniform has 3 facts recorded in Dontopedia across 1 reference.
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.
assignedByAssigned by(1)
- Precision Variable
ex:precision-variable
usesUses(1)
- Random Angle Generation
ex:random-angle-generation
Other facts (3)
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 | Function Call | [1] |
| Lower Bound | 0.85 | [1] |
| Upper Bound | 0.95 | [1] |
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 (1)
ctx:claims/beam/c8578409-db7a-4511-babf-7af22c569322- full textbeam-chunktext/plain1 KB
doc:beam/c8578409-db7a-4511-babf-7af22c569322Show excerpt
For each combination of weights, evaluate the performance using your test queries and measure the intent precision. ### Example Implementation Here's an example of how you might structure your experiments: ```python import itertools impo…
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.