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Refactor test for KMeans empty cluster reinitialization to use distinct data points and remove redundant assertion

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This commit is contained in:
Palash Tyagi 2025-07-13 01:49:15 +01:00
parent 7c7c8c2a16
commit 1bdcf1b113
1 changed files with 6 additions and 11 deletions
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17
src/compute/models/k_means.rs
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@ -328,13 +328,12 @@ mod tests {
// Two distinct groups of points, but we ask for 3 clusters. // Two distinct groups of points, but we ask for 3 clusters.
// This should cause one cluster to be empty and re-initialized. // This should cause one cluster to be empty and re-initialized.
let data = vec![ let data = vec![
1.0, 1.0, 0.0, 0.0, // Single point cluster
1.1, 1.1, 10.0, 10.0,
1.2, 1.2, 10.1, 10.1,
// Large gap to ensure distinct clusters 10.2, 10.2,
100.0, 100.0, 10.3, 10.3,
100.1, 100.1, 10.4, 10.4,
100.2, 100.2,
]; ];
let x = FloatMatrix::from_rows_vec(data, 6, 2); let x = FloatMatrix::from_rows_vec(data, 6, 2);
let k = 3; // Request 3 clusters for 2 natural groups let k = 3; // Request 3 clusters for 2 natural groups
@ -362,10 +361,6 @@ mod tests {
counts[label] += 1; counts[label] += 1;
} }
// The crucial assertion: After re-initialization, no cluster should remain empty.
// This verifies that the "furthest point" logic successfully re-assigned a point
// to the previously empty cluster.
assert!(counts.iter().all(|&c| c > 0));
// The crucial assertion: After re-initialization, no cluster should remain empty. // The crucial assertion: After re-initialization, no cluster should remain empty.
// This verifies that the "furthest point" logic successfully re-assigned a point // This verifies that the "furthest point" logic successfully re-assigned a point