doc.txt

CAUSAL_LEARNER

def learn(self, 
	do_size=100, # ???
	do_conf=0.4, 
	ci_conf=0.1, 
	max_cond_vars=4, # DOC: max # of vars to condition (incrementally, through lim_neighbours = Order)
	post=True, trace=False, verbose=False):
	
def has_influence(src: str, # DOC: node to intervene on
	dst: list, # DOC: nodes to check whether src has influence on
	cond_node: list, # DOC: list of conditioning nodes
	env, # DOC: whole Bayesian network (with CPD)
	do_size=200, # ??? 
	alpha=0.05): # DOC: chi-square test confidence
	
def simulate(src: str, # DOC: node to intervene on
	dst: list, # DOC: nodes to check whether src has influence on
	env, # DOC: whole Bayesian network (with CPD)
	cond_evidence: dict = {}, # ???
	do_size=100): # ???
	
NETWORK

def do_evidence(self, 
	evidence=None, # DOC: {src: value, **cond_evidence}
	size=100, # DOC: same as do_size
	seed=12):
	
def _sample(self, 
	evidence: dict = None):