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:

modelModel: The model to plot. Not required when called from inside a modelcontext.
var_namesiterable of str, optional: Subset of variables to be plotted that identify a subgraph with respect to the entire model graph
formattingstr, optional: one of { “plain” }

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)