pymc.model_graph.model_to_networkx#
- pymc.model_graph.model_to_networkx(model=None, *, var_names=None, formatting='plain')[source]#
Produce a networkx Digraph from a PyMC model.
Requires networkx, which may be installed most easily with:
conda install networkx
Alternatively, you may install using pip with:
pip install networkx
See https://networkx.org/documentation/stable/ for more information.
- Parameters:
Examples
How to plot the graph of the model.
import numpy as np from pymc import HalfCauchy, Model, Normal, model_to_networkx J = 8 y = np.array([28, 8, -3, 7, -1, 1, 18, 12]) sigma = np.array([15, 10, 16, 11, 9, 11, 10, 18]) with Model() as schools: eta = Normal("eta", 0, 1, shape=J) mu = Normal("mu", 0, sigma=1e6) tau = HalfCauchy("tau", 25) theta = mu + tau * eta obs = Normal("obs", theta, sigma=sigma, observed=y) model_to_networkx(schools)