Source code for netrd.dynamics.base

import numpy as np

[docs]class BaseDynamics: """Base class for all dynamics processes. The basic usage is as follows: >>> ground_truth = nx.read_edgelist("ground_truth.txt") >>> dynamics_model = Dynamics() >>> synthetic_TS = dynamics_model.simulate(ground_truth, <some_params>) >>> # G = Reconstructor().fit(synthetic_TS) This produces a numpy array of time series data. """ def __init__(self): self.results = {}
[docs] def simulate(self, G, L): r"""Simulate dynamics on a ground truth network. The results dictionary stores the ground truth network as `'ground_truth'`. Parameters ---------- G (nx.Graph) the input (ground-truth) graph with :math:`N` nodes. L (int) the length of the desired time series. Returns ------- TS (np.ndarray) an :math`N \times L` array of synthetic time series data. """ N = G.number_of_nodes() self.results['ground_truth'] = G self.results['TS'] = np.ones((N, L)) return self.results['TS']