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feat: Optimize COVER #27

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Merged
Pringled merged 1 commit into from
Jan 30, 2026
Merged

feat: Optimize COVER #27

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9 changes: 5 additions & 4 deletions src/pyversity/strategies/cover.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,16 +80,17 @@ def cover(
transposed_similarity_matrix = similarity_matrix.T

# Initialize selection state
accumulated_coverage = np.zeros(similarity_matrix.shape[0], dtype=np.float32)
selected_mask = np.zeros(similarity_matrix.shape[0], dtype=bool)
num_items = similarity_matrix.shape[0]
accumulated_coverage = np.zeros(num_items, dtype=np.float32)
selected_mask = np.zeros(num_items, dtype=bool)
selected_indices = np.empty(top_k, dtype=np.int32)
marginal_gains = np.empty(top_k, dtype=np.float32)

for step in range(top_k):
# Compute coverage gains using concave transformation
concave_before = np.power(accumulated_coverage, gamma)
concave_before_sum = float(np.power(accumulated_coverage, gamma).sum())
concave_after = np.power(transposed_similarity_matrix + accumulated_coverage[None, :], gamma)
coverage_gains = (concave_after - concave_before[None, :]).sum(axis=1)
coverage_gains = concave_after.sum(axis=1) - concave_before_sum

# Combine relevance and coverage gains
candidate_scores = theta * relevance_scores + (1.0 - theta) * coverage_gains
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