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Artemis aims to get rid of all the boring, bureaucratic coding (plotting, file management, organizing experiments, etc) involved in machine learning projects, so you can get to the good stuff quickly.

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Artemis

The deer represents dull, repetitive coding tasks, and Artemis represents Artemis.  As you can see, once Artemis comes along, the future is not bright for dull, repetitive coding tasks.

Artemis is a collection of tools that make it easier to run experiments in Python. These include:

  • An easy-to-use system for making live plots, to monitor variables in a running experiment.
  • A browser-based plotter for displaying live plots.
  • A framework for defining experiments and logging their results (text output and figures) so that they can be reviewed later and replicated easily.
  • A system for downloading/caching files, to a local directory, so the same code can work on different machines.

For examples of how to use artemis, read the Artemis Documentation

Installation

Note: Artemis was build for Python 2.7. The Master branch now supports Python 3, so if you want to use on Python 3, you can directly install from master: pip install git+http://github.com/QUVA-Lab/artemis.git#egg=artemis. A more official release supporting Python 3 is coming soon.

To use artemis from within your project, use the following to install Artemis and its dependencies: (You probably want to do this in a virtualenv with the latest version of pip - run virtualenv venv; source venv/bin/activate; pip install --upgrade pip; to make one and enter it).

Option 1: Simple install:

pip install artemis-ml

Option 2: Install as source.

pip install -e git+http://github.com/QUVA-Lab/artemis.git#egg=artemis 

This will install it in (virtual env or system python root)/src/artemis. You can edit the code and submit pull requests to our git repo. To install with the optional remote plotting mode enabled, add the [remote_plotting] option, as in: pip install -e git+http://github.com/QUVA-Lab/artemis.git#egg=artemis[remote_plotting]

(Note, this doesn't work if you have Anaconda installed, as it does not work with the -e option). Use pip install artemis-ml in this case instead.

Verifying that it works

To verify that the plotting works, run:

python -m artemis.plotting.demo_dbplot

A bunch of plots should come up and start updating live.

Note: During installation, the settings file .artemisrc is created in your home directory. In it you can specify the plotting backend to use, and other settings.

Now that you have Artemis installed, see this Tutorial on how to use Artemis to organize your experiments.

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Artemis aims to get rid of all the boring, bureaucratic coding (plotting, file management, organizing experiments, etc) involved in machine learning projects, so you can get to the good stuff quickly.

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