MVP run:
python -m src.experiments --help
# Usage: python -m src.experiments [OPTIONS]
# Options:
# --d INTEGER Amount of variables
# --n INTEGER Sample size
# --s INTEGER Expected number of edges in the simulated
# DAG
# --graph_type [ER|SF|BP] ER: Erdos-Renyi, SF: Scale Free, BP:
# BiPartite [default: ER]
# --sem_type [mim|mlp|gp|gp-add] mim: Index Model, mlp: Multi-Layered
# Perceptron, gp: Gaussian Process, gp-add:
# Additive Gaussian Process [default: mim]
# --epochs INTEGER [default: 100]
# --batch_size INTEGER [default: 256]
# --seed INTEGER
# --nt-h_tol FLOAT MINIMUM h value for NOTEARS.
# --nt-rho_max FLOAT MAXIMUM value for rho in dual ascent
# NOTEARS.
# --help Show this message and exit.
Required packages:
numpy
scipy
scikit-learn
pytorch-lightning
igraph
wandb
click
matplotlib
tabulate