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Refactor StructureEstimator save_results and adjacency_matrix methods

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Filippo Martini 4 years ago
parent 6ba5762d02
commit 028e6f6b22
13 changed files with 140 additions and 99 deletions
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  1. 3
      .idea/.gitignore
  2. 8
      .idea/PyCTBN.iml
  3. 6
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  8. BIN
      CTBN_project_dominio.pdf
  9. 18
      PyCTBN/PyCTBN/estimators/structure_estimator.py
  10. 1
      PyCTBN/PyCTBN/structure_graph/sample_path.py
  11. 1
      PyCTBN/PyCTBN/utility/json_importer.py
  12. 19
      PyCTBN/tests/estimators/test_structure_estimator.py
  13. 41
      basic_main.py

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CTBN_project_dominio.pdf
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18
PyCTBN/PyCTBN/estimators/structure_estimator.py
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@ -90,17 +90,14 @@ class StructureEstimator(object):
list_without_test_parent.remove(parent_label)
return map(list, itertools.combinations(list_without_test_parent, size))
def save_results(self) -> None:
"""Save the estimated Structure to a .json file in the path where the data are loaded from.
The file is named as the input dataset but the `results_` word is appended to the results file.
def save_results(self, file_path: str) -> None:
"""Save the estimated Structure to a .json file in file_path.
:param file_path: the path including the file name with .json extension
:type file_path: string
"""
res = json_graph.node_link_data(self._complete_graph)
name = self._sample_path._importer.file_path.rsplit('/', 1)[-1]
name = name.split('.', 1)[0]
name += '_' + str(self._sample_path._importer.dataset_id())
name += '.json'
file_name = 'results_' + name
with open(file_name, 'w') as f:
with open(file_path, 'w') as f:
json.dump(res, f)
@ -120,14 +117,13 @@ class StructureEstimator(object):
"""
pass
def adjacency_matrix(self) -> np.ndarray:
"""Converts the estimated structure ``_complete_graph`` to a boolean adjacency matrix representation.
:return: The adjacency matrix of the graph ``_complete_graph``
:rtype: numpy.ndArray
"""
return nx.adj_matrix(self._complete_graph).toarray().astype(bool)
return nx.adj_matrix(self._complete_graph, self._nodes).toarray().astype(bool)
def spurious_edges(self) -> typing.List:
"""Return the spurious edges present in the estimated structure, if a prior net structure is present in

1
PyCTBN/PyCTBN/structure_graph/sample_path.py
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@ -10,6 +10,7 @@ from ..utility.abstract_importer import AbstractImporter
MESSAGE_HAS_TO_CONTAIN_EXCEPTION = 'The importer object has to contain the all processed data!'
class SamplePath(object):
"""Aggregates all the informations about the trajectories, the real structure of the sampled net and variables
cardinalites. Has the task of creating the objects ``Trajectory`` and ``Structure`` that will

1
PyCTBN/PyCTBN/utility/json_importer.py
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@ -131,7 +131,6 @@ class JsonImporter(AbstractImporter):
:rtype: List
"""
dataframe = pd.DataFrame
#print(raw_data)
smps = raw_data[indx][trajectories_key]
df_samples_list = [dataframe(sample) for sample in smps]
return df_samples_list

19
PyCTBN/tests/estimators/test_structure_estimator.py
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@ -24,6 +24,7 @@ class TestStructureEstimator(unittest.TestCase):
cls.s1 = SamplePath(cls.importer)
cls.s1.build_trajectories()
cls.s1.build_structure()
cls.real_net_structure = nx.DiGraph(cls.s1.structure.edges)
def test_init(self):
exp_alfa = 0.1
@ -50,7 +51,6 @@ class TestStructureEstimator(unittest.TestCase):
no_self_loops.remove(node)
for n2 in no_self_loops:
self.assertIn((node, n2), cg.edges)
#se1.save_plot_estimated_structure_graph()
def test_build_removable_edges_matrix(self):
exp_alfa = 0.1
@ -84,18 +84,12 @@ class TestStructureEstimator(unittest.TestCase):
print("Execution Time: ", exec_time)
for ed in self.s1.structure.edges:
self.assertIn(tuple(ed), se1._complete_graph.edges)
#print("Spurious Edges:", se1.spurious_edges())
#se1.save_plot_estimated_structure_graph()
def test_save_results(self):
se1 = StructureConstraintBasedEstimator(self.s1, 0.1, 0.1)
se1.ctpc_algorithm()
se1.save_results()
name = self.s1._importer.file_path.rsplit('/', 1)[-1]
name = name.split('.', 1)[0]
name += '_' + str(self.s1._importer.dataset_id())
name += '.json'
file_name = 'results_' + name
file_name = './PyCTBN/tests/estimators/test_save.json'
se1.save_results(file_name)
with open(file_name) as f:
js_graph = json.load(f)
result_graph = nx.json_graph.node_link_graph(js_graph)
@ -105,13 +99,16 @@ class TestStructureEstimator(unittest.TestCase):
def test_adjacency_matrix(self):
se1 = StructureConstraintBasedEstimator(self.s1, 0.1, 0.1)
se1.ctpc_algorithm()
adj_matrix = nx.adj_matrix(se1._complete_graph).toarray().astype(bool)
adj_matrix = nx.adj_matrix(self.real_net_structure, self.s1.structure.nodes_labels).toarray().astype(bool)
self.assertTrue(np.array_equal(adj_matrix, se1.adjacency_matrix()))
def test_save_plot_estimated_graph(self):
se1 = StructureConstraintBasedEstimator(self.s1, 0.1, 0.1)
edges = se1.estimate_structure(disable_multiprocessing=True)
se1.save_plot_estimated_structure_graph('./networks_and_trajectories_ternary_data_3.png')
file_name = './PyCTBN/tests/estimators/test_plot.png'
se1.save_plot_estimated_structure_graph(file_name)
os.remove(file_name)
if __name__ == '__main__':

41
basic_main.py
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import glob
import os
import sys
sys.path.append("./PyCTBN/")
import structure_graph.network_graph as ng
import structure_graph.sample_path as sp
import structure_graph.set_of_cims as sofc
import estimators.parameters_estimator as pe
import utility.json_importer as ji
def main():
read_files = glob.glob(os.path.join('./data', "*.json")) #Take all json files in this dir
#import data
importer = ji.JsonImporter(read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name')
#Create a SamplePath Obj
s1 = sp.SamplePath(importer)
#Build The trajectries and the structural infos
s1.build_trajectories()
s1.build_structure()
#From The Structure Object build the Graph
g = ng.NetworkGraph(s1.structure)
#Select a node you want to estimate the parameters
node = g.nodes[1]
#Init the graph specifically for THIS node
g.fast_init(node)
#Use SamplePath and Grpah to create a ParametersEstimator Object
p1 = pe.ParametersEstimator(s1, g)
#Init the peEst specifically for THIS node
p1.fast_init(node)
#Compute the parameters
sofc1 = p1.compute_parameters_for_node(node)
#The est CIMS are inside the resultant SetOfCIms Obj
print(sofc1.actual_cims)
if __name__ == "__main__":
main()