Python Module and Conda Environment

This module was created to accompany the MGDrivE project, although its codebase is totally independent to allow as much modularity as possible. This is not only convenient in terms of the code, but it also provides a clear-cut separation between designing and running experiments, and analyzing the results.

import MoNeT_MGDrivE as monet
# Define the experiment's path
type = float
experimentString = "E_090_050_010_025"
path = "/Users/sanchez.hmsc/Desktop/ParserDataset/"
aggregationDictionary = monet.generateAggregationDictionary(
    ["W", "H", "R", "B"],
    [
        [0, 0, 1, 2, 3],
        [1, 4, 4, 5, 6],
        [2, 5, 7, 7, 8],
        [3, 6, 8, 9, 9]
    ]
)
# Get the filenames lists
filenames = monet.readExperimentFilenames(path + experimentString)
# Load a single node (Auxiliary function)
nodeIndex = 0
nodeData = monet.loadNodeData(
    filenames.get("male")[nodeIndex],
    filenames.get("female")[nodeIndex],
    dataType=float
)

The creation of this package is ongoing, and is currently being thoroughly tested against previous scattered scripts developed in Mathematica. It can be installed through pip with the following command:

pip install MoNeT_MGDrivE

For more information and releases please take a look at our pypi website.

Authors

Sarafina Smith, Víctor Ferman, Sabrina Wong, Héctor M. Sánchez C.