def __init__(self,dataset,model_name,num_obs_vars,m='0',r1='1', lbp_iters=3000):
# TODO: experiment with different values of fastinf
self.dataset = dataset
self.fd = FastinfDiscretizer(self.dataset, model_name)
self.res_fname = config.get_fastinf_res_file(dataset,model_name,m,r1)
# TODO: experiment with different amounts of smoothing
# amount of smoothing is correlated with fastinf slowness, values [0,1)
self.smoothing = 0.5
self.cache_fname = config.get_fastinf_cache_file(dataset,model_name,m,r1,self.smoothing)
if os.path.exists(self.cache_fname):
with open(self.cache_fname) as f:
print("Loading fastinf cache from file")
self.cache = cPickle.load(f)
else:
self.cache = {}
self.cmd = config.fastinf_bin+" -i %s -m 0 -Is %f -Imm %d"%(self.res_fname, self.smoothing, lbp_iters)
self.num_obs_vars = num_obs_vars
self.tt = TicToc().tic()
self.process = pexpect.spawn(self.cmd)
self.blacklist = []
marginals = self.get_marginals()
print("FastinfModel: Computed initial marginals in %.3f sec"%self.tt.qtoc())
