def get_combined_texts_uniform_k()

in evaluation_pipeline/evaluation.py [0:0]

• 9 lines of code
• 6 McCabe index (conditional complexity)

def get_combined_texts_uniform_k(df, k):
    # Identify retrieval columns and sort them numerically
    retrieval_cols = sorted(
        [col for col in df.columns if 'retrieval_' in col and '_combined_text' in col],
        key=lambda x: int(x.split('_')[1])
    )
    
    # Extract relevant retrieval columns as a NumPy array
    retrieval_matrix = df[retrieval_cols].to_numpy()

    # Slice the matrix up to `k` columns for all rows
    sliced_matrix = retrieval_matrix[:, :k]

    # Convert to a list of lists
    result = sliced_matrix.tolist()
    return result