incense 0.0.2

Interactively retrieve data from sacred experiments.

Incense

Though automated logging of machine learning experiments results is crucial, it does not replace manual interpretation. Incense is a toolbox to facilitate manual interpretation of experiments that are logged using sacred. It lets you find and evaluate experiments directly in Jupyter notebooks. Incense lets you query the database for experiments by id, name or any hyperparmeter value. For each found experiment, configuration, artifacts and metrics can be displayed. The artifacts are rendered according to their type, e.g. a PNG image is displayed as an image, while a CSV file gets transformed to a pandas DataFrame. Metrics are by default transformed into pandas Series, which allows for flexible plotting. Together with sacred and incense, Jupyter notebooks offer the perfect solution for interpreting experiments as they allow for a combination of code that reproducibly displays the experiment’s results, as well as text that contains the interpretation.

Installation

To use incense you need the newest development version of sacred, so that content-types of artifacts are automatically detected. Therefore, you first have to install sacred from github and then install incense from PyPI.

pip install git+https://github.com/IDSIA/sacred.git
pip install incense

Documentation

demo.ipynb demonstrates the basic functionality of incense.