text: import numpy as np
  
  
  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 = {}
  
      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']
  