Installing pySkyNetΒΆ

Note

Python dependencies : numpy, pandas
For plotting : matplotlib, we recommend you use seaborn
The anaconda python distribution contains all the necessary libraries for all platforms.
As pySkyNet is a poor man’s wrapper of SkyNet it performs system calls to SkyNet.
SkyNet can be installed from here: http://ccpforge.cse.rl.ac.uk/gf/project/skynet/
pySkyNet takes care of writing the files needed in the correct format and reading in the predictions from the files once printed by SkyNet and returning them to the user.

This means that the only configuration that is needed is setting the folders where pySkNet and SkyNet will read and write.

First clone the pySkyNet repository:

$ git clone https://github.com/cbonnett/SkyNet_wrapper.git

Then create a system variable SKYNETPATH to an exciting folder where you want to store SkyNet training, validation, predictions, configuration and prediction files.

Bash shell:

$ export SKYNETPATH=/path/where/you/want/to/store/skynet/data/

c-shell:

$ setenv SKYNETPATH /path/where/you/want/to/store/skynet/data/

Once the $SKYNETPATH is set, in the pySkyNet repo you run:

$ python src/install.py
This will create 4 subfolders in $SKYNETPATH:
  • $SKYNETPATH/train_valid

    This folder will contain the training and validation files.

  • $SKYNETPATH/config_files

    This folder contains the configuration files used by SkyNet

  • $SKYNETPATH/network

    This folder contains the learned weight files. This folder will also contain the predictions of the training and validation samples

  • $SKYNETPATH/predictions

    In this folder all the predictions are printed.

Note

All these folders can be set when instantiating SkyNetRegressor or SkyNetClassifier class:

sn_reg = SkyNetRegressor(id=’identification’,input_root=’/my/folder/inputs’)