-
graphs.py: basic Graph and DiGraph classes
-
graphical_models.py: currently supports on Bayesian Networks with Discrete variables. The
BayesNet
class is a subclass ofDiGraph
-
visualize.py: using networkx_interface.py and the graphviz module, makes diagrams of BayesNets
-
sampling.py: defines gibbs sampling functions
-
counting.py: useful combinatorics functions and some sampling procedures
-
util.py: other helper functions (e.g.
load_or_run()
which wraps precomputing/saving/loading numpy arrays) -
models.py: functions to create special cases of Graphs or BayesNets
-
generators.py: create evidence-generators for sampling
Because of the way packages are set up here, from the project directory run python -m scripts.script_name
without .py
. For example:
$ python -m scripts.make_mixing_time_movie