def main():
t1 = time.time()
graph_iter = generate_graphs(**config.generator_dictionary)
graphs = list(graph_iter)
for graph in graphs:
Node_Name_Rule.graph_semantics_apply(graph,config.node_semantics)
Edge_Semantics_Rule.graph_semantics_apply(graph,config.edge_semantics)
inference_obj = Inference()
result_graphs, result_posterior, result_loglik, result_dict = inference_obj.p_graph_given_d(graphs,config.options)
edges_of_interest = result_config.edges_of_interest
filename_base = "hidden_structure_results"
filename = filename_utility(filename_base)
filename = os.path.join("results",filename)
for idx,g in enumerate(result_graphs):
for edge in edges_of_interest:
if edge in g.edges():
edges_of_interest[edge]+=result_posterior[idx]
with open(filename,'wb') as f:
np.savez(f,posterior=result_posterior,loglik=result_loglik,init_dict=result_dict)
elapsed= time.time() - t1
print(elapsed)
def main():
t1 = time.time()
graph_iter = generate_graphs(**config.generator_dictionary)
graphs = list(graph_iter)
for graph in graphs:
Node_Name_Rule.graph_semantics_apply(graph, config.node_semantics)
Edge_Semantics_Rule.graph_semantics_apply(graph, config.edge_semantics)
inference_obj = Inference()
result_graphs, result_posterior, result_loglik, result_dict = inference_obj.p_graph_given_d(
graphs, config.options)
edges_of_interest = result_config.edges_of_interest
filename_base = "hidden_structure_results"
filename = filename_utility(filename_base)
filename = os.path.join("results", filename)
for idx, g in enumerate(result_graphs):
for edge in edges_of_interest:
if edge in g.edges():
edges_of_interest[edge] += result_posterior[idx]
with open(filename, 'wb') as f:
np.savez(f,
posterior=result_posterior,
loglik=result_loglik,
init_dict=result_dict)
elapsed = time.time() - t1
print(elapsed)
def main():
t1 = time.time()
graph_iter = generate_graphs(**config.generator_dictionary)
graphs = list(graph_iter)
for graph in graphs:
Node_Name_Rule.graph_semantics_apply(graph, config.node_semantics)
Edge_Semantics_Rule.graph_semantics_apply(graph, config.edge_semantics)
# num_conditions = 4
# options = [config.options]*num_conditions
# for i in range(num_conditions):
# options[i]["data_sets"] = cond_to_data(config.conds[i,:])
num_conditions = 3
options = [config.options] * num_conditions
for i in range(num_conditions):
options[i]["data_sets"] = cond_to_data(config.lesser_conds[i, :])
options[i]["parallel"] = True
result_graphs = [None] * num_conditions
result_posteriors = [None] * num_conditions
result_logliks = [None] * num_conditions
result_dicts = [None] * num_conditions
result_params = [None] * num_conditions
inference_obj = Inference()
for i in range(num_conditions):
result_graphs[i], result_posteriors[i], result_logliks[
i], result_dicts[i], result_params[
i] = inference_obj.p_graph_given_d(graphs, options[i])
# no longer valid edges_of_interest code
# edges_of_interest = result_config.edges_of_interest
# for idx,g in enumerate(result_graphs):
# for edge in edges_of_interest:
# if edge in g.edges():
# edges_of_interest[edge]+=result_posteriors[idx]
result_graphs_strings = [
json_graph_list_dumps(g_list) for g_list in result_graphs
]
filename_base = "hidden_structure_results"
filename = filename_utility(filename_base)
filename = os.path.join("results", filename)
with open(filename, 'wb') as f:
np.savez(f,
g_list_strings=result_graphs_strings,
posterior=result_posteriors,
loglik=result_logliks,
init_dict=result_dicts,
params=result_params)
elapsed = time.time() - t1
print(elapsed)
def main():
t1 = time.time()
graph_iter = generate_graphs(**config.generator_dictionary)
graphs = list(graph_iter)
for graph in graphs:
Node_Name_Rule.graph_semantics_apply(graph,config.node_semantics)
Edge_Semantics_Rule.graph_semantics_apply(graph,config.edge_semantics)
# num_conditions = 4
# options = [config.options]*num_conditions
# for i in range(num_conditions):
# options[i]["data_sets"] = cond_to_data(config.conds[i,:])
num_conditions = 3
options = [config.options]*num_conditions
for i in range(num_conditions):
options[i]["data_sets"] = cond_to_data(config.lesser_conds[i,:])
options[i]["parallel"] = True
result_graphs = [None]*num_conditions
result_posteriors = [None]*num_conditions
result_logliks = [None]*num_conditions
result_dicts = [None]*num_conditions
result_params = [None]*num_conditions
inference_obj = Inference()
for i in range(num_conditions):
result_graphs[i], result_posteriors[i], result_logliks[i], result_dicts[i], result_params[i] = inference_obj.p_graph_given_d(graphs,options[i])
# no longer valid edges_of_interest code
# edges_of_interest = result_config.edges_of_interest
# for idx,g in enumerate(result_graphs):
# for edge in edges_of_interest:
# if edge in g.edges():
# edges_of_interest[edge]+=result_posteriors[idx]
result_graphs_strings = [json_graph_list_dumps(g_list) for g_list in result_graphs]
filename_base = "hidden_structure_results"
filename = filename_utility(filename_base)
filename = os.path.join("results",filename)
with open(filename,'wb') as f:
np.savez(f,
g_list_strings = result_graphs_strings,
posterior = result_posteriors,
loglik = result_logliks,
init_dict = result_dicts,
params = result_params)
elapsed= time.time() - t1
print(elapsed)
