unimib-thesis-mad
/
PyCTBN
Archived
1
0
Fork 0
Code Releases Activity

Example Multiprocessing

Browse Source
master
Pietro 4 years ago
parent bc09738b00
commit db79fc5b70
1 changed files with 7 additions and 2 deletions
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Show Stats Download Patch File Download Diff File
  1. 9
      example.py

9
example.py
Unescape View File

@ -6,6 +6,11 @@ from PyCTBN.PyCTBN.structure_graph.structure import Structure
from PyCTBN.PyCTBN.structure_graph.sample_path import SamplePath from PyCTBN.PyCTBN.structure_graph.sample_path import SamplePath
from PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator import StructureConstraintBasedEstimator from PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator import StructureConstraintBasedEstimator
"""
if __name__ == "__main__":
trajectories = tg.multi_trajectory(t_ends = [100, 100, 100])
"""
# Network Generation # Network Generation
labels = ["X", "Y", "Z"] labels = ["X", "Y", "Z"]
card = 3 card = 3
@ -20,7 +25,7 @@ ng.generate_cims(cim_min, cim_max)
print(ng.dyn_str) print(ng.dyn_str)
e1 = JsonExporter(ng.variables, ng.dyn_str, ng.dyn_cims) e1 = JsonExporter(ng.variables, ng.dyn_str, ng.dyn_cims)
tg = TrajectoryGenerator(variables = ng.variables, dyn_str = ng.dyn_str, dyn_cims = ng.dyn_cims) tg = TrajectoryGenerator(variables = ng.variables, dyn_str = ng.dyn_str, dyn_cims = ng.dyn_cims)
sigma = tg.CTBN_Sample(max_tr = 10) sigma = tg.CTBN_Sample(max_tr = 100)
e1.add_trajectory(tg.to_json()) e1.add_trajectory(tg.to_json())
e1.out_json("example.json") e1.out_json("example.json")
@ -35,6 +40,6 @@ s1.build_structure()
se1 = StructureConstraintBasedEstimator(sample_path=s1, exp_test_alfa=0.1, chi_test_alfa=0.1, se1 = StructureConstraintBasedEstimator(sample_path=s1, exp_test_alfa=0.1, chi_test_alfa=0.1,
known_edges=[], thumb_threshold=25) known_edges=[], thumb_threshold=25)
edges = se1.estimate_structure(True) edges = se1.estimate_structure(True)
se1.save_plot_estimated_structure_graph('./result.png') # se1.save_plot_estimated_structure_graph('./result1.png')
print(se1.adjacency_matrix()) print(se1.adjacency_matrix())
print(edges) print(edges)