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/* Any copyright is dedicated to the Public Domain.
const { SmartTabGroupingManager } = ChromeUtils.importESModule(
"moz-src:///browser/components/tabbrowser/SmartTabGrouping.sys.mjs"
);
add_task(function test_average_similarity_single_candidate_single_anchor() {
const anchors = [[1, 0]];
const candidates = [[1, 0]];
const smartTabGroupingManager = new SmartTabGroupingManager();
const result = smartTabGroupingManager.getAverageSimilarity(
anchors,
candidates
);
Assert.equal(result.length, 1, "Should return one similarity score.");
Assert.equal(
result[0],
1,
"Cosine similarity should be 1 for identical vectors."
);
});
add_task(function test_average_similarity_single_candidate_multiple_anchor() {
const anchors = [
[1, 0],
[0, 1],
];
const candidates = [[1, 0]];
const smartTabGroupingManager = new SmartTabGroupingManager();
const result = smartTabGroupingManager.getAverageSimilarity(
anchors,
candidates
);
const expectedAverage = (1 + 0) / 2;
Assert.equal(result.length, 1, "Should return one similarity score.");
Assert.equal(
result[0],
expectedAverage,
"Average similarity should be about 0.5."
);
});
add_task(function test_average_similarity_multiple_candidate_single_anchor() {
const anchors = [[1, 0]];
const candidates = [
[1, 0],
[-1, 0],
];
const smartTabGroupingManager = new SmartTabGroupingManager();
const result = smartTabGroupingManager.getAverageSimilarity(
anchors,
candidates
);
Assert.equal(result.length, 2, "Should return two similarity scores.");
Assert.equal(result[0], 1, "First candidate similarity should be 1.");
Assert.equal(result[1], -1, "Second candidate similarity should be -1.");
});
add_task(
function test_average_similarity_multiple_candidates_multiple_anchors() {
const anchors = [
[1, 0],
[0, 1],
];
const candidates = [
[1, 1],
[1, -1],
];
const smartTabGroupingManager = new SmartTabGroupingManager();
const result = smartTabGroupingManager.getAverageSimilarity(
anchors,
candidates
);
// Expected values based on standard cosine similarity for normalized vectors.
Assert.equal(result.length, 2, "Should return two similarity scores.");
Assert.equal(
result[0].toPrecision(4),
0.7071,
"First candidate average similarity should be approx 0.7071."
);
Assert.equal(
result[1],
0,
"Second candidate average similarity should be 0."
);
}
);
add_task(function test_average_similarity_empty_candidates() {
const anchors = [
[1, 0],
[0, 1],
];
const candidates = [];
const smartTabGroupingManager = new SmartTabGroupingManager();
const result = smartTabGroupingManager.getAverageSimilarity(
anchors,
candidates
);
Assert.deepEqual(
result,
[],
"Empty candidate embeddings should return an empty array."
);
});
add_task(function test_average_similarity_multiple_candidate_empty_anchors() {
const anchors = [];
const candidates = [[1, 0]];
const smartTabGroupingManager = new SmartTabGroupingManager();
const result = smartTabGroupingManager.getAverageSimilarity(
anchors,
candidates
);
Assert.equal(
result.length,
1,
"One candidate should produce one similarity score."
);
Assert.ok(
isNaN(result[0]),
"Empty anchor embeddings should result in NaN (due to 0/0 division)."
);
});