Source code for netrd.reconstruction.base

[docs]class BaseReconstructor: r"""Base class for graph reconstruction algorithms. The basic usage of a graph reconstruction algorithm is as follows: >>> reconstructor = ReconstructionAlgorithm() >>> G =, <some_params>) >>> # or alternately, G = reconstructor.results['graph'] Here, `TS` is an :math:`N \times L` numpy array consisting of :math:`L` observations for each of :math:`N` sensors. This constrains the graphs to have integer-valued nodes. The ``results`` dict object, in addition to containing the graph object, may also contain objects created as a side effect of reconstructing the network, which may be useful for debugging or considering goodness of fit. What is returned will vary between reconstruction algorithms. """ def __init__(self): self.results = {}
[docs] def fit(self, TS, **kwargs): """Reconstruct a graph from time series TS. Parameters ---------- TS (np.ndarray): Array consisting of $L$ observations from $N$ sensors. Returns ------- G (nx.Graph): A reconstructed graph with $N$ nodes. """ G = nx.Graph() # reconstruct the graph self.results['graph'] = G # and store it in self.results # self.results[..] = .. # also store other values if needed return G