import re import pandas as pd # Function to extract caption from latex table def extract_caption(latex_table_content): caption_pattern = re.compile(r'\\caption{(.*?)}', re.DOTALL) caption_match = caption_pattern.search(latex_table_content) if caption_match: return caption_match.group(1).strip() return "No caption found" # Function to convert LaTeX table content to DataFrame def latex_table_to_dataframe(latex_table_content): table_data = [] rows = latex_table_content.split("\\\\") for row in rows: row = row.strip() if row: # Keep LaTeX formatting but split at '&' for each column cleaned_row = re.sub(r'\\[a-zA-Z]+\{[^}]*\}', '', row) # Removing LaTeX commands table_data.append(cleaned_row.split('&')) # Convert to DataFrame for easier statistical analysis df = pd.DataFrame(table_data) return df # Function to calculate statistics (mean, median, min, max) def calculate_statistics(df): # Convert all columns to numeric values (ignoring non-numeric columns) df_numeric = df.apply(pd.to_numeric, errors='coerce') # Calculate statistics mean_row = df_numeric.mean() median_row = df_numeric.median() min_row = df_numeric.min() max_row = df_numeric.max() return mean_row, median_row, min_row, max_row # Function to add the statistics row to the LaTeX table def add_statistics_to_latex_table(latex_table_content, mean_row, median_row, min_row, max_row): table_rows = latex_table_content.split("\\\\") # Create a formatted statistics row stats_row = "Mean & " + " & ".join([f"{value:.3f}" for value in mean_row]) + " \\\\" table_rows.append(stats_row) stats_row = "Median & " + " & ".join([f"{value:.3f}" for value in median_row]) + " \\\\" table_rows.append(stats_row) stats_row = "Min & " + " & ".join([f"{value:.3f}" for value in min_row]) + " \\\\" table_rows.append(stats_row) stats_row = "Max & " + " & ".join([f"{value:.3f}" for value in max_row]) + " \\\\" table_rows.append(stats_row) latex_table_with_stats = "\\\\\n".join(table_rows) # Add the caption and return the updated table caption = extract_caption(latex_table_content) updated_latex_table = latex_table_with_stats + "\n\\caption{" + caption + "}" return updated_latex_table # Function to process a list of LaTeX tables and add statistics rows def process_multiple_latex_tables(latex_tables): updated_tables = [] for latex_table in latex_tables: # Convert LaTeX table content to DataFrame df = latex_table_to_dataframe(latex_table) # Calculate statistics (mean, median, min, max) mean_row, median_row, min_row, max_row = calculate_statistics(df) # Add the statistics row to the original LaTeX table updated_latex_table = add_statistics_to_latex_table(latex_table, mean_row, median_row, min_row, max_row) updated_tables.append(updated_latex_table) return updated_tables latex_input_list = [ """ \begin{table*}[t!] \centering \resizebox{\textwidth}{!}{% \begin{tabular}{|l|c|c|c||c|c|c|c|c||c|c|c|} \hline Method & \multicolumn{3}{c||}{Default} & \multicolumn{5}{c||}{Best} & \multicolumn{3}{c|}{Oracle} \\ \cline{2-13} & F1 & Precision & Recall & F1 & Precision & Recall & Precision (F1 max) & Recall (F1 max) & F1 & Precision & Recall \\ \hline BinSeg & 0.524 & 0.481 & 0.693 & 0.653 & 1.000 & 1.000 & 0.961 & 0.562 & 0.764 & 1.000 & 1.000 \\ BOCPD & 0.256 & 0.177 & 0.791 & 0.591 & 0.621 & 0.918 & 0.592 & 0.681 & 0.710 & 0.789 & 0.946 \\ CPNP & 0.284 & 0.187 & 0.785 & 0.292 & 0.193 & 0.999 & 0.193 & 0.793 & 0.305 & 0.203 & 0.999 \\ KCPA & 0.516 & 0.497 & 0.676 & 0.516 & 0.497 & 0.795 & 0.497 & 0.676 & 0.557 & 0.516 & 0.801 \\ MongoDB & 0.428 & 0.339 & 0.746 & 0.432 & 0.343 & 0.769 & 0.343 & 0.744 & 0.464 & 0.374 & 0.773 \\ PELT & 0.451 & 0.382 & 0.722 & 0.451 & 0.382 & 1.000 & 0.382 & 0.722 & 0.525 & 0.458 & 1.000 \\ RFPOP & 0.248 & 0.158 & 0.817 & 0.248 & 0.158 & 0.866 & 0.158 & 0.817 & 0.256 & 0.164 & 0.866 \\ pelt & 0.451 & 0.382 & 0.722 & 0.451 & 0.382 & 1.000 & 0.382 & 0.722 & 0.525 & 0.458 & 1.000 \\ WBS & 0.170 & 0.107 & 0.804 & 0.305 & 0.215 & 1.000 & 0.215 & 0.775 & 0.346 & 0.247 & 1.000 \\ zero & 0.648 & 1.000 & 0.545 & 0.648 & 1.000 & 0.545 & 1.000 & 0.545 & 0.648 & 1.000 & 0.545 \\ \hline \end{tabular}%% } \caption{Performance Metrics for Methods over 195 average-aggregated datasets} \end{table*} """ ] # latex_input_list = [ # """ # \begin{table*}[t!] # \centering # \resizebox{\textwidth}{!}{% # \begin{tabular}{|l|c|c|c||c|c|c|c|c||c|c|c|} # \hline # Method & \multicolumn{3}{c||}{Default} & \multicolumn{5}{c||}{Best} & \multicolumn{3}{c|}{Oracle} \\ # \cline{2-13} # & F1 & Precision & Recall & F1 & Precision & Recall & Precision (F1 max) & Recall (F1 max) & F1 & Precision & Recall \\ # \hline # BinSeg & 0.524 & 0.481 & 0.693 & 0.653 & 1.000 & 1.000 & 0.961 & 0.562 & 0.764 & 1.000 & 1.000 \\ # BOCPD & 0.256 & 0.177 & 0.791 & 0.591 & 0.621 & 0.918 & 0.592 & 0.681 & 0.710 & 0.789 & 0.946 \\ # CPNP & 0.284 & 0.187 & 0.785 & 0.292 & 0.193 & 0.999 & 0.193 & 0.793 & 0.305 & 0.203 & 0.999 \\ # KCPA & 0.516 & 0.497 & 0.676 & 0.516 & 0.497 & 0.795 & 0.497 & 0.676 & 0.557 & 0.516 & 0.801 \\ # MongoDB & 0.428 & 0.339 & 0.746 & 0.432 & 0.343 & 0.769 & 0.343 & 0.744 & 0.464 & 0.374 & 0.773 \\ # PELT & 0.451 & 0.382 & 0.722 & 0.451 & 0.382 & 1.000 & 0.382 & 0.722 & 0.525 & 0.458 & 1.000 \\ # RFPOP & 0.248 & 0.158 & 0.817 & 0.248 & 0.158 & 0.866 & 0.158 & 0.817 & 0.256 & 0.164 & 0.866 \\ # pelt & 0.451 & 0.382 & 0.722 & 0.451 & 0.382 & 1.000 & 0.382 & 0.722 & 0.525 & 0.458 & 1.000 \\ # WBS & 0.170 & 0.107 & 0.804 & 0.305 & 0.215 & 1.000 & 0.215 & 0.775 & 0.346 & 0.247 & 1.000 \\ # zero & 0.648 & 1.000 & 0.545 & 0.648 & 1.000 & 0.545 & 1.000 & 0.545 & 0.648 & 1.000 & 0.545 \\ # \hline # \end{tabular}%% # } # \caption{Performance Metrics for Methods over 195 average-aggregated datasets} # \end{table*} # """ # , # """ # \begin{table*}[t!] # \centering # \resizebox{\textwidth}{!}{% # \begin{tabular}{|l|c|c|c||c|c|c|c|c||c|c|c|} # \hline # Method & \multicolumn{3}{c||}{Default} & \multicolumn{5}{c||}{Best} & \multicolumn{3}{c|}{Oracle} \\ # \cline{2-13} # & F1 & Precision & Recall & F1 & Precision & Recall & Precision (F1 max) & Recall (F1 max) & F1 & Precision & Recall \\ # \hline # Mozilla \& BinSeg & 0.746 & 0.951 & 0.679 & 0.802 & 1.000 & 0.958 & 0.895 & 0.792 & 0.929 & 1.000 & 0.958 \\ # Mozilla \& BOCPD & 0.772 & 0.867 & 0.771 & 0.797 & 0.981 & 0.889 & 0.935 & 0.754 & 0.906 & 0.996 & 0.909 \\ # Mozilla \& CPNP & 0.768 & 0.860 & 0.769 & 0.787 & 0.880 & 0.957 & 0.764 & 0.884 & 0.895 & 0.908 & 0.957 \\ # Mozilla \& KCPA & 0.725 & 0.939 & 0.664 & 0.767 & 0.942 & 0.774 & 0.875 & 0.765 & 0.820 & 0.965 & 0.782 \\ # Mozilla \& MongoDB & 0.761 & 0.916 & 0.726 & 0.769 & 0.923 & 0.747 & 0.904 & 0.742 & 0.787 & 0.929 & 0.751 \\ # Mozilla \& PELT & 0.769 & 0.943 & 0.709 & 0.784 & 0.943 & 0.958 & 0.880 & 0.781 & 0.927 & 0.972 & 0.958 \\ # Mozilla \& RFPOP & 0.772 & 0.850 & 0.793 & 0.778 & 0.850 & 0.841 & 0.840 & 0.809 & 0.808 & 0.864 & 0.841 \\ # Mozilla \& WBS & 0.782 & 0.866 & 0.786 & 0.784 & 0.896 & 0.958 & 0.869 & 0.789 & 0.881 & 0.908 & 0.958 \\ # Mozilla \& Zero & 0.648 & 1.000 & 0.545 & 0.648 & 1.000 & 0.545 & 1.000 & 0.545 & 0.648 & 1.000 & 0.545 \\ # \hline # \end{tabular}%% # } # \caption{Performance Metrics for Methods over 195 average-aggregated datasets merged with Mozilla method results} # \end{table*} # """ # , # """ # \begin{table*}[t!] # \centering # \resizebox{\textwidth}{!}{% # \begin{tabular}{|l|c|c|c||c|c|c|c|c||c|c|c|} # \hline # Method & \multicolumn{3}{c||}{Default} & \multicolumn{5}{c||}{Best} & \multicolumn{3}{c|}{Oracle} \\ # \cline{2-13} # & F1 & Precision & Recall & F1 & Precision & Recall & Precision (F1 max) & Recall (F1 max) & F1 & Precision & Recall \\ # \hline # Mozilla \& BinSeg \& BOCPD & 0.771 & 0.863 & 0.772 & 0.804 & 0.981 & 0.958 & 0.892 & 0.797 & 0.933 & 0.996 & 0.958 \\ # Mozilla \& BinSeg \& KCPA & 0.745 & 0.926 & 0.694 & 0.793 & 0.942 & 0.958 & 0.880 & 0.792 & 0.910 & 0.966 & 0.958 \\ # Mozilla \& BinSeg \& MongoDB & 0.771 & 0.916 & 0.736 & 0.804 & 0.923 & 0.958 & 0.892 & 0.795 & 0.903 & 0.934 & 0.958 \\ # Mozilla \& Bineg \& PELT & 0.767 & 0.932 & 0.714 & 0.802 & 0.943 & 0.958 & 0.895 & 0.792 & 0.929 & 0.972 & 0.958 \\ # Mozilla \& KCPA & 0.725 & 0.939 & 0.664 & 0.767 & 0.942 & 0.774 & 0.875 & 0.765 & 0.820 & 0.965 & 0.782 \\ # MozillA \& KCPA \& BOCPD & 0.770 & 0.863 & 0.771 & 0.788 & 0.934 & 0.894 & 0.866 & 0.793 & 0.892 & 0.966 & 0.913 \\ # Mozilla \& MongoDB \& BOCPD & 0.775 & 0.857 & 0.781 & 0.800 & 0.920 & 0.892 & 0.906 & 0.779 & 0.885 & 0.933 & 0.913 \\ # Mozilla \& MongoDB \& KCPA & 0.768 & 0.897 & 0.746 & 0.776 & 0.904 & 0.781 & 0.895 & 0.756 & 0.807 & 0.914 & 0.789 \\ # Mozilla \& MongoDB \& PELT & 0.779 & 0.910 & 0.749 & 0.790 & 0.911 & 0.958 & 0.887 & 0.780 & 0.905 & 0.929 & 0.958 \\ # Mozilla \& PELT BOCPD & 0.771 & 0.865 & 0.771 & 0.795 & 0.941 & 0.958 & 0.923 & 0.759 & 0.930 & 0.972 & 0.958 \\ # Mozilla \& PELT \& KCPA & 0.757 & 0.920 & 0.712 & 0.783 & 0.923 & 0.958 & 0.876 & 0.784 & 0.910 & 0.945 & 0.958 \\ # \hline # \end{tabular}%% # } # \caption{Performance Metrics for Methods over 195 average-aggregated datasets merged with Mozilla method results (two CPDs/testing all combinations)} # \end{table*} # """ # , # """ # \begin{table*}[t!] # \centering # \resizebox{\textwidth}{!}{% # \begin{tabular}{|l|c|c|c||c|c|c|c|c||c|c|c|} # \hline # Method & \multicolumn{3}{c||}{Default} & \multicolumn{5}{c||}{Best} & \multicolumn{3}{c|}{Oracle} \\ # \cline{2-13} # & F1 & Precision & Recall & F1 & Precision & Recall & Precision (F1 max) & Recall (F1 max) & F1 & Precision & Recall \\ # \hline # Mozilla \& BinSeg \& BOCPD \& KCPA & 0.770 & 0.860 & 0.772 & 0.737 & 0.926 & 0.687 & 0.926 & 0.687 & 0.737 & 0.926 & 0.687 \\ # Mozilla \& BinSeg \& BOCPD \& MongoDB & 0.775 & 0.857 & 0.781 & 0.780 & 0.910 & 0.748 & 0.910 & 0.748 & 0.780 & 0.910 & 0.748 \\ # Mozilla \& BinSeg \& BOCPD \& PELT & 0.771 & 0.863 & 0.772 & 0.768 & 0.936 & 0.714 & 0.936 & 0.714 & 0.768 & 0.936 & 0.714 \\ # Mozilla \& BinSeg \& KCPA \& MongoDB & 0.769 & 0.897 & 0.747 & 0.765 & 0.896 & 0.742 & 0.896 & 0.742 & 0.765 & 0.896 & 0.742 \\ # Mozilla \& BinSeg \& KCPA \& PELT & 0.756 & 0.913 & 0.716 & 0.755 & 0.918 & 0.712 & 0.918 & 0.712 & 0.755 & 0.918 & 0.712 \\ # Mozilla \& BinSeg \& MongoDB \& PELT & 0.781 & 0.910 & 0.750 & 0.774 & 0.904 & 0.744 & 0.904 & 0.744 & 0.774 & 0.904 & 0.744 \\ # Mozilla \& BOCPD \& MongoDB \& PELT & 0.775 & 0.857 & 0.781 & 0.777 & 0.902 & 0.749 & 0.902 & 0.749 & 0.777 & 0.902 & 0.749 \\ # Mozilla \& KCPA \& BinSeg \& BOCPD & 0.770 & 0.860 & 0.772 & 0.737 & 0.926 & 0.687 & 0.926 & 0.687 & 0.737 & 0.926 & 0.687 \\ # Mozilla \& KCPA \& BOCPD \& MongoDB & 0.773 & 0.854 & 0.781 & 0.768 & 0.892 & 0.748 & 0.892 & 0.748 & 0.768 & 0.892 & 0.748 \\ # Mozilla \& KCPA \& BOCPD \& PELT & 0.770 & 0.863 & 0.771 & 0.755 & 0.914 & 0.716 & 0.914 & 0.716 & 0.755 & 0.914 & 0.716 \\ # Mozilla \& KCPA \& MongoDB \& PELT & 0.770 & 0.895 & 0.750 & 0.767 & 0.891 & 0.746 & 0.891 & 0.746 & 0.767 & 0.891 & 0.746 \\ # \hline # \end{tabular}%% # } # \caption{Performance Metrics for Methods over 195 average-aggregated datasets merged with Mozilla method results (three CPD methods/testing only Best combinations)} # \end{table*} # """ # , # """ # \begin{table*}[t!] # \centering # \resizebox{\textwidth}{!}{% # \begin{tabular}{|l|c|c|c||c|c|c|c|c||c|c|c|} # \hline # Method & \multicolumn{3}{c||}{Default} & \multicolumn{5}{c||}{Best} & \multicolumn{3}{c|}{Oracle} \\ # \cline{2-13} # & F1 & Precision & Recall & F1 & Precision & Recall & Precision (F1 max) & Recall (F1 max) & F1 & Precision & Recall \\ # \hline # mozilla \& Binseg \& BOCPD \& KCPA \& Mongodb & 0.773 & 0.854 & 0.781 & 0.768 & 0.892 & 0.748 & 0.892 & 0.748 & 0.768 & 0.892 & 0.748 \\ # mozilla \& BinSeg \& BOCPD \& KCPA \& PELT & 0.770 & 0.860 & 0.772 & 0.755 & 0.914 & 0.716 & 0.914 & 0.716 & 0.755 & 0.914 & 0.716 \\ # mozilla \& BinSeg \& BOCPD \& MongoDB \& PELT & 0.775 & 0.857 & 0.781 & 0.777 & 0.902 & 0.749 & 0.902 & 0.749 & 0.777 & 0.902 & 0.749 \\ # mozilla \& KCPA \& MongoDB \& PELT \& BinSeg & 0.770 & 0.895 & 0.750 & 0.767 & 0.891 & 0.746 & 0.891 & 0.746 & 0.767 & 0.891 & 0.746 \\ # mozilla \& KCPA \& MongoDB \& PELT \& BOCPD & 0.773 & 0.854 & 0.781 & 0.769 & 0.890 & 0.749 & 0.890 & 0.749 & 0.769 & 0.890 & 0.749 \\ # mozilla \& PELT \& BinSeg \& BOCPD \& KCPA \& MongoDB & 0.773 & 0.854 & 0.781 & 0.769 & 0.890 & 0.749 & 0.890 & 0.749 & 0.769 & 0.890 & 0.749 \\ # \hline # \end{tabular}%% # } # \caption{Performance Metrics for Methods over 195 average-aggregated datasets merged with Mozilla method results (four or five CPD methods/testing only Best combinations)} # \end{table*} # """ # ] # Process the list of latex tables and add the statistics rows updated_latex_tables = process_multiple_latex_tables(latex_input_list) # Print the updated LaTeX tables with statistics rows for updated_table in updated_latex_tables: print("###################") print(updated_table)