Errors Array
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Errors Array has 21 facts recorded in Dontopedia across 1 reference, with 3 live disagreements.
Mostly:has element at(5), element at index(5), has element(4)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (5)
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.
affectsAffects(1)
- Issue 1
ex:issue-1
assignsAssigns(1)
- Code Test
ex:code-test
hasParameterHas Parameter(1)
- Incremental Improvements Function
ex:incremental-improvements-function
modifiesModifies(1)
- For Loop Improvements
ex:for-loop-improvements
usesSampleDataUses Sample Data(1)
- Code Test
ex:code-test
Other facts (21)
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 |
|---|---|---|
| Has Element at | 10 | [1] |
| Has Element at | 20 | [1] |
| Has Element at | 30 | [1] |
| Has Element at | 40 | [1] |
| Has Element at | 50 | [1] |
| Element at Index | 10 | [1] |
| Element at Index | 20 | [1] |
| Element at Index | 30 | [1] |
| Element at Index | 40 | [1] |
| Element at Index | 50 | [1] |
| Has Element | 20 | [1] |
| Has Element | 30 | [1] |
| Has Element | 40 | [1] |
| Has Element | 50 | [1] |
| Rdf:type | Numpy Array | [1] |
| Has Initial Value | 10 | [1] |
| Has Length | 5 | [1] |
| Element Type | Number | [1] |
| Used in | Code Test | [1] |
| Is Used in | Code Test | [1] |
| Is Modified by | For Loop Improvements | [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/3c07262c-005c-4dd9-9b36-cade8afcedea- full textbeam-chunktext/plain1 KB
doc:beam/3c07262c-005c-4dd9-9b36-cade8afcedeaShow excerpt
# Apply incremental improvements for improvement in improvements: # Reduce training errors errors = errors - improvement return errors # Test the function errors = np.array([10, 20, 30, 40, 50]) result = in…
See also
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