CATS Log Processing

This project is a Python framework for processing logs generated by the CATS ABox Abduction Solver and visualizing the processed data as graphs.

The framework allows users to:

• process experiment logs generated by different abduction algorithms,
• compute aggregated statistics (e.g., explanations over time, memory usage, consistency checks),
• export processed data into CSV files,
• generate graphs in PNG and PDF formats.

Project structure

main.py

The main script of the project.

It is used to configure which logs should be processed, select the algorithms, set input and output directories, run the log processing, and generate graphs.

config.py

Contains the project configuration.

This file defines the available algorithms, default paths, and plotting settings such as colours, markers, and figure size.

process_logs.py

Processes raw log files produced by the CATS solver.

It reads the logs produced by CATS, extracts relevant statistics, computes averages and aggregated metrics, and exports the processed data into CSV files.

plot_logs.py

Creates graphs from the processed CSV files.

It reads the exported CSV files and generates line plots and grid figures that can be saved as PNG or PDF.

generic_funcs.py

Contains helper functions used throughout the project.

These functions handle common tasks such as creating directories and working with file names.