The Quintessential PGM

This is a demonstration of a very common structure found in graphical models. It has been rendered using Daft’s default settings for all the parameters and it shows off how much beauty is baked in by default.

import daft

# Instantiate the PGM.
pgm = daft.PGM()

# Hierarchical parameters.
pgm.add_node("alpha", r"$\alpha$", 0.5, 2, fixed=True)
pgm.add_node("beta", r"$\beta$", 1.5, 2)

# Latent variable.
pgm.add_node("w", r"$w_n$", 1, 1)

# Data.
pgm.add_node("x", r"$x_n$", 2, 1, observed=True)

# Add in the edges.
pgm.add_edge("alpha", "beta")
pgm.add_edge("beta", "w")
pgm.add_edge("w", "x")
pgm.add_edge("beta", "x")

# And a plate.
pgm.add_plate([0.5, 0.5, 2, 1], label=r"$n = 1, \cdots, N$", shift=-0.1)

# Render and save.
pgm.render()

<matplotlib.axes._axes.Axes at 0x7fd546ffbbd0>