GRBlogtools

Extract information from Gurobi log files and generate pandas DataFrames or Excel worksheets for further processing. Also includes a wrapper for out-of-the-box interactive visualizations using the plotting library Plotly.

Installation

python -m pip install grblogtools

It is recommended to prepend the pip install command with python -m to ensure that the package is installed using the correct Python version currently active in your environment. See CHANGELOG for added, removed or fixed functionality.

Usage

First, you need a set of Gurobi log files to compare, e.g.,

• results from several model instances
• comparisons of different parameter settings
• performance variability experiments involving multiple random seed runs
• ...

You may also use the provided grblogtools.ipynb notebook with the example data set to get started. Additionally, there is a Gurobi TechTalk demonstrating how to use grblogtools (YouTube).

Pandas/Plotly

1. parse log files:

   import grblogtools as glt
   
   summary, timelines, rootlp = glt.get_dataframe(["run1/*.log", "run2/*.log"], timelines=True)

   Depending on your requirements, you may need to filter or modify the resulting DataFrames.

2. draw interactive charts, preferably in a Jupyter Notebook:

   • final results from the individual runs:

   glt.plot(summary, type="box")

   • progress charts for the individual runs:

   glt.plot(timelines, y="Gap", color="Log", type="line")

   These are just examples using the Plotly Python library - of course, any other plotting library of your choice can be used to work with these DataFrames.

Excel

Convert your log files to Excel worksheets right on the command-line:

python -m grblogtools myrun.xlsx data/*.log

List all available options and how to use the command-line tool:

python -m grblogtools --help