Machine learning tools for the Geoscience Australia uncover project.
Before you start, make sure your system has the following packages installed,
- gdal (libgdal-dev)
- openmpi
- hdf5
We strongly recommend using a virtual environment.
To install, simply run setup.py
:
$ python setup.py install
or install with pip
:
$ pip install git+https://github.com/GeoscienceAustralia/uncover-ml.git@release
The python requirements should automatically be built and installed.
In order to use the cubist regressor, you need to first make sure cubist is installed. This is easy with our simple installation script, invoke it with:
$ ./makecubist <installation-path>
Once cubist is installed, it will add a configuration file to the script, if you like, you can test that it's been installed in the correct place by checking the contents of uncover-ml/cubist_config.py, its presence indicates that the installation completed successfully.
Next you need to rerun the setup script with:
$ python setup.py install
Which will ensure the cubist_config has been added successfully. Now you should be able to use the cubist regressor in the pipeline file.
See the usage documentation.
Please see The PBS Readme .
This software is jointly developed by NICTA and Geoscience Australia. For a list of features still to be implemented, see the issue tracker.
- Home Page
- http://github.com/GeoscienceAustralia/uncover-ml
- Documentation
- http://GeoscienceAustralia.github.io/uncover-ml
- Issue tracking
- https://github.com/GeoscienceAustralia/uncover-ml/issues
For bugs, questions and discussions, please use Github Issues.