Coat Similarity Conflict Checking Heuristic Scorer
Weighted exact similarity of independently aligned armorial attributes; not legal conflict, image recognition or grant clearance.
Description
An annotation-based conflict score can weight exact agreement in chosen attributes.
An annotation-based conflict score can weight exact agreement in chosen attributes.1
The weights define a heuristic and do not establish legal conflict or visual indistinguishability.
When to use Coat Similarity Conflict Checking Heuristic Scorer
Use this tool to calculate or review the supplied observations under the stated rules. Establish the source tradition, viewing frame, coordinate units and independently annotated features.
How to use Coat Similarity Conflict Checking Heuristic Scorer and understand its results
- Establish the source tradition, viewing frame, coordinate units and independently annotated features.
- Enter candidateAnnotatedAttributes, referenceAnnotatedAttributes, callerWeights, using the field meanings and rules below, then run the tool.
- Read result.weightedExactSimilarity, result.differentIndices, using the output meanings and calculation rules below.
- Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| candidateAnnotatedAttributes | Candidate annotated attributes | list of string | Required |
| referenceAnnotatedAttributes | Reference annotated attributes | list of string | Required |
| callerWeights | Caller weights | list of number | Required |
Use nonempty aligned candidate attributes, reference attributes and nonnegative finite weights whose sum is positive. Add weights only where the two strings are exactly equal, then divide by total weight. Also return zero-based differing positions, including mismatches whose weight is zero.
similarity=Σ_i weight_i×indicator(candidate_i=reference_i)/Σ_i weight_i Use the matching field units and the exact boundary, ordering and reference rules above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Calculated observation or reference | object |
| result.weightedExactSimilarity | weighted Exact Similarity | number |
| result.differentIndices | different Indices; zero-based positions in the relevant supplied record or adjacent-pair list | list |
{
"input": {
"candidateAnnotatedAttributes": [
"or",
"lion"
],
"referenceAnnotatedAttributes": [
"or",
"eagle"
],
"callerWeights": [
3,
1
]
},
"output": {
"result": {
"weightedExactSimilarity": 0.75,
"differentIndices": [
1
]
}
}
}Limitations and assumptions
Attributes and weights are caller-selected and case-sensitive. The score is a fraction, not a legal conflict threshold, visual distance or proof of identity.
Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above. Extremely large composite outputs are rejected.
Alternative or Complementary methods
For a related step, use Crest Above Helmet Uniqueness Conflict Checker: A crest identifier can be compared with an explicitly supplied registry. For a complementary comparison, use Difference Subtle Change Sufficiency Rater: A subtlety reference can relate a measured coordinate to a calibrated response.
References
Similar or alternative tools
- Crest Above Helmet Uniqueness Conflict Checker
A crest identifier can be compared with an explicitly supplied registry.
- Difference Subtle Change Sufficiency Rater
A subtlety reference can relate a measured coordinate to a calibrated response.