data_extraction_transformation/scripts/one_time_use_scripts/make_diagrams_per_compound.py [26:97]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - sig_id = dataf['signature_id'].unique()[0] machine_platform = dataf['machine_platform'].unique()[0] machine_platform_general = categorize_platform(machine_platform) framework_id = dataf['framework_id'].unique()[0] repository_name = dataf['repository_name'].unique()[0] test = dataf['test'].unique()[0] application = dataf['application'].unique()[0] suite = dataf['suite'].unique()[0] option_collection_hash = dataf['option_collection_hash'].unique()[0] TP = len(dataf[dataf['alert_summary_status_general'] == "TP"]) FN = len(dataf[dataf['alert_summary_status_general'] == "FN"]) FP = len(dataf[dataf['alert_summary_status_general'] == "FP"]) SP = len(dataf[dataf['alert_summary_status_general'] == "SP"]) sample_df = dataf.copy() sample_df['push_timestamp'] = pd.to_datetime(sample_df['push_timestamp']) sample_df.set_index('push_timestamp', inplace=True) # Sorting to maintain order sample_df.sort_index(inplace=True) # Define color mapping color_mapping = { 'TP': 'green', 'FP': 'red', 'SP': 'grey', 'TN': 'blue' } # Plotting plt.figure(figsize=(20, 10)) # Plot all values as a scatter plot for better alignment plt.scatter(sample_df.index, sample_df['value'], color=[color_mapping.get(status, 'black') for status in sample_df['alert_summary_status_general']], alpha=0.6, label="Measurements") # Draw vertical lines for change points (TP, FP, SP) for status in ['TP', 'FP', 'SP']: change_points = sample_df[sample_df['alert_summary_status_general'] == status].index for cp in change_points: plt.axvline(x=cp, color=color_mapping[status], linestyle='--', alpha=0.6) plt.title('Time Series Plot') plt.xlabel('Date') plt.ylabel(f'Test measurement values associated with signature ID {sig_id}') plt.grid(axis='y') # Set limits plt.xlim(sample_df.index.min(), sample_df.index.max()) plt.ylim(bottom=0, top=sample_df['value'].max() * 1.2) # Slightly above max for visibility # X-axis formatting plt.xticks(pd.date_range(start=sample_df.index.min(), end=sample_df.index.max(), freq='W-MON'), rotation=45) plt.gca().xaxis.set_major_formatter(plt.matplotlib.dates.DateFormatter('%Y-%m-%d')) # Add text box for metadata text_content = f"Framework ID: {framework_id}\n" \ f"Repository: {repository_name}\n" \ f"Platform (general): {machine_platform_general}\n" \ f"Platform: {machine_platform}\n" \ f"Test: {test}\n" \ f"Suite: {suite}\n" \ f"Application: {application}\n" \ f"TP count: {TP}\n" \ f"FP count: {FP}\n" \ f"FN count: {FN}\n" \ f"SP count: {SP}" plt.text(0.98, 0.98, text_content, ha='right', va='top', transform=plt.gca().transAxes, fontsize=12, family='monospace', bbox=dict(facecolor='white', alpha=0.7, edgecolor='black', boxstyle='round,pad=0.5')) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - data_extraction_transformation/scripts/one_time_use_scripts/make_diagrams_per_dtw_analysis.py [17:88]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - sig_id = dataf['signature_id'].unique()[0] machine_platform = dataf['machine_platform'].unique()[0] machine_platform_general = categorize_platform(machine_platform) framework_id = dataf['framework_id'].unique()[0] repository_name = dataf['repository_name'].unique()[0] test = dataf['test'].unique()[0] application = dataf['application'].unique()[0] suite = dataf['suite'].unique()[0] option_collection_hash = dataf['option_collection_hash'].unique()[0] TP = len(dataf[dataf['alert_summary_status_general'] == "TP"]) FN = len(dataf[dataf['alert_summary_status_general'] == "FN"]) FP = len(dataf[dataf['alert_summary_status_general'] == "FP"]) SP = len(dataf[dataf['alert_summary_status_general'] == "SP"]) sample_df = dataf.copy() sample_df['push_timestamp'] = pd.to_datetime(sample_df['push_timestamp']) sample_df.set_index('push_timestamp', inplace=True) # Sorting to maintain order sample_df.sort_index(inplace=True) # Define color mapping color_mapping = { 'TP': 'green', 'FP': 'red', 'SP': 'grey', 'TN': 'blue' } # Plotting plt.figure(figsize=(20, 10)) # Plot all values as a scatter plot for better alignment plt.scatter(sample_df.index, sample_df['value'], color=[color_mapping.get(status, 'black') for status in sample_df['alert_summary_status_general']], alpha=0.6, label="Measurements") # Draw vertical lines for change points (TP, FP, SP) for status in ['TP', 'FP', 'SP']: change_points = sample_df[sample_df['alert_summary_status_general'] == status].index for cp in change_points: plt.axvline(x=cp, color=color_mapping[status], linestyle='--', alpha=0.6) plt.title('Time Series Plot') plt.xlabel('Date') plt.ylabel(f'Test measurement values associated with signature ID {sig_id}') plt.grid(axis='y') # Set limits plt.xlim(sample_df.index.min(), sample_df.index.max()) plt.ylim(bottom=0, top=sample_df['value'].max() * 1.2) # Slightly above max for visibility # X-axis formatting plt.xticks(pd.date_range(start=sample_df.index.min(), end=sample_df.index.max(), freq='W-MON'), rotation=45) plt.gca().xaxis.set_major_formatter(plt.matplotlib.dates.DateFormatter('%Y-%m-%d')) # Add text box for metadata text_content = f"Framework ID: {framework_id}\n" \ f"Repository: {repository_name}\n" \ f"Platform (general): {machine_platform_general}\n" \ f"Platform: {machine_platform}\n" \ f"Test: {test}\n" \ f"Suite: {suite}\n" \ f"Application: {application}\n" \ f"TP count: {TP}\n" \ f"FP count: {FP}\n" \ f"FN count: {FN}\n" \ f"SP count: {SP}" plt.text(0.98, 0.98, text_content, ha='right', va='top', transform=plt.gca().transAxes, fontsize=12, family='monospace', bbox=dict(facecolor='white', alpha=0.7, edgecolor='black', boxstyle='round,pad=0.5')) - 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