optimized imports

bamt/builders/builders_base.py

@@ -1,19 +1,18 @@
 import itertools
+from typing import Dict, List, Optional, Tuple, Callable, TypedDict, Sequence, Union
+
+from pandas import DataFrame
 
+from bamt.log import logger_builder
+from bamt.nodes.conditional_gaussian_node import ConditionalGaussianNode
+from bamt.nodes.conditional_logit_node import ConditionalLogitNode
+from bamt.nodes.conditional_mixture_gaussian_node import ConditionalMixtureGaussianNode
 from bamt.nodes.discrete_node import DiscreteNode
 from bamt.nodes.gaussian_node import GaussianNode
-from bamt.nodes.conditional_logit_node import ConditionalLogitNode
 from bamt.nodes.logit_node import LogitNode
 from bamt.nodes.mixture_gaussian_node import MixtureGaussianNode
-from bamt.nodes.conditional_mixture_gaussian_node import ConditionalMixtureGaussianNode
-from bamt.nodes.conditional_gaussian_node import ConditionalGaussianNode
-
-from bamt.log import logger_builder
-from pandas import DataFrame
 from bamt.utils import GraphUtils as gru
 
-from typing import Dict, List, Optional, Tuple, Callable, TypedDict, Sequence, Union
-
 
 class ParamDict(TypedDict, total=False):
     init_edges: Optional[Sequence[str]]

bamt/builders/composite_builder.py

@@ -1,32 +1,30 @@
 from datetime import timedelta
-
-from pandas import DataFrame
-from sklearn import preprocessing
-import bamt.preprocessors as pp
-
-from bamt.builders.builders_base import VerticesDefiner, EdgesDefiner
-from bamt.log import logger_builder
-from bamt.nodes.discrete_node import DiscreteNode
-from bamt.nodes.gaussian_node import GaussianNode
-from bamt.utils.composite_utils import CompositeGeneticOperators
-from bamt.utils.composite_utils.CompositeModel import CompositeModel, CompositeNode
-from bamt.nodes.composite_discrete_node import CompositeDiscreteNode
-from bamt.nodes.composite_continuous_node import CompositeContinuousNode
-from bamt.utils import EvoUtils as evo
+from typing import Dict, Optional, List, Tuple, Callable
 
 from golem.core.adapter import DirectAdapter
 from golem.core.dag.verification_rules import has_no_cycle, has_no_self_cycled_nodes
+from golem.core.log import Log
 from golem.core.optimisers.genetic.gp_optimizer import EvoGraphOptimizer
 from golem.core.optimisers.genetic.gp_params import GPAlgorithmParameters
 from golem.core.optimisers.genetic.operators.crossover import CrossoverTypesEnum
 from golem.core.optimisers.genetic.operators.inheritance import GeneticSchemeTypesEnum
+from golem.core.optimisers.genetic.operators.selection import SelectionTypesEnum
 from golem.core.optimisers.objective import Objective, ObjectiveEvaluate
 from golem.core.optimisers.optimization_parameters import GraphRequirements
 from golem.core.optimisers.optimizer import GraphGenerationParams
-from golem.core.optimisers.genetic.operators.selection import SelectionTypesEnum
-from golem.core.log import Log
+from pandas import DataFrame
+from sklearn import preprocessing
 
-from typing import Dict, Optional, List, Tuple, Callable
+import bamt.preprocessors as pp
+from bamt.builders.builders_base import VerticesDefiner, EdgesDefiner
+from bamt.log import logger_builder
+from bamt.nodes.composite_continuous_node import CompositeContinuousNode
+from bamt.nodes.composite_discrete_node import CompositeDiscreteNode
+from bamt.nodes.discrete_node import DiscreteNode
+from bamt.nodes.gaussian_node import GaussianNode
+from bamt.utils import EvoUtils as evo
+from bamt.utils.composite_utils import CompositeGeneticOperators
+from bamt.utils.composite_utils.CompositeModel import CompositeModel, CompositeNode
 
 
 class CompositeDefiner(VerticesDefiner, EdgesDefiner):

bamt/builders/evo_builder.py

@@ -1,23 +1,21 @@
 from datetime import timedelta
-
-from pandas import DataFrame
-
-from bamt.builders.builders_base import BaseDefiner
-from bamt.utils import EvoUtils as evo
+from typing import Dict, Optional, List, Tuple
 
 from golem.core.adapter import DirectAdapter
 from golem.core.dag.verification_rules import has_no_cycle, has_no_self_cycled_nodes
+from golem.core.log import Log
 from golem.core.optimisers.genetic.gp_optimizer import EvoGraphOptimizer
 from golem.core.optimisers.genetic.gp_params import GPAlgorithmParameters
 from golem.core.optimisers.genetic.operators.crossover import CrossoverTypesEnum
 from golem.core.optimisers.genetic.operators.inheritance import GeneticSchemeTypesEnum
+from golem.core.optimisers.genetic.operators.selection import SelectionTypesEnum
 from golem.core.optimisers.objective import Objective, ObjectiveEvaluate
 from golem.core.optimisers.optimization_parameters import GraphRequirements
 from golem.core.optimisers.optimizer import GraphGenerationParams
-from golem.core.optimisers.genetic.operators.selection import SelectionTypesEnum
-from golem.core.log import Log
+from pandas import DataFrame
 
-from typing import Dict, Optional, List, Tuple
+from bamt.builders.builders_base import BaseDefiner
+from bamt.utils import EvoUtils as evo
 
 
 class EvoDefiner(BaseDefiner):

bamt/builders/hc_builder.py

@@ -1,15 +1,14 @@
+from typing import Dict, List, Optional, Tuple, Callable, Union
+
+from pandas import DataFrame
 from pgmpy.base import DAG
 from pgmpy.estimators import HillClimbSearch
 
 from bamt.builders.builders_base import ParamDict, BaseDefiner
-from bamt.redef_HC import hc as hc_method
-
 from bamt.log import logger_builder
-from pandas import DataFrame
+from bamt.redef_HC import hc as hc_method
 from bamt.utils import GraphUtils as gru
 
-from typing import Dict, List, Optional, Tuple, Callable, Union
-
 
 class HillClimbDefiner(BaseDefiner):
     """

bamt/external/pyBN/classes/_tests/test_bayesnet.py

@@ -33,13 +33,13 @@
 """
 __author__ = """Nicholas Cullen <[email protected]>"""
 
+import os
 import unittest
+from os.path import dirname
+
 from external.pyBN.classes.bayesnet import BayesNet
 from external.pyBN.readwrite.read import read_bn
 
-import os
-from os.path import dirname
-
 
 class BayesNetTestCase(unittest.TestCase):
     def setUp(self):

bamt/external/pyBN/classes/bayesnet.py

@@ -39,6 +39,7 @@
 from copy import deepcopy
 
 import numpy as np
+
 from bamt.external.pyBN.utils.class_equivalence import are_class_equivalent
 from bamt.external.pyBN.utils.graph import topsort
 

bamt/external/pyBN/utils/_tests/test_independence_tests.py

@@ -7,11 +7,11 @@
 """
 __author__ = """Nicholas Cullen <[email protected]>"""
 
-import unittest
 import os
+import unittest
 from os.path import dirname
-import numpy as np
 
+import numpy as np
 from external.pyBN.independence.constraint_tests import mi_test
 
 

bamt/external/pyBN/utils/_tests/test_markov_blanket.py

@@ -7,14 +7,12 @@
 
 __author__ = """Nicholas Cullen <[email protected]>"""
 
-import unittest
 import os
+import unittest
 from os.path import dirname
-import numpy as np
-import pandas as pd
 
-from external.pyBN.readwrite.read import read_bn
 from external.pyBN.independence.markov_blanket import markov_blanket
+from external.pyBN.readwrite.read import read_bn
 
 
 class ConstraintTestsTestCase(unittest.TestCase):

bamt/external/pyBN/utils/_tests/test_orient_edges.py

@@ -7,11 +7,11 @@
 """
 __author__ = """Nicholas Cullen <[email protected]>"""
 
-import unittest
 import os
+import unittest
 from os.path import dirname
-import numpy as np
 
+import numpy as np
 from external.pyBN.structure_learn.orient_edges import orient_edges_gs, orient_edges_pc
 
 

bamt/external/pyBN/utils/_tests/test_random_sample.py

@@ -7,13 +7,13 @@
 """
 __author__ = """Nicholas Cullen <[email protected]>"""
 
-import unittest
 import os
+import unittest
 from os.path import dirname
-import numpy as np
 
-from external.pyBN.utils.random_sample import random_sample
+import numpy as np
 from external.pyBN.readwrite.read import read_bn
+from external.pyBN.utils.random_sample import random_sample
 
 
 class RandomSampleTestCase(unittest.TestCase):

bamt/external/pyitlib/DiscreteRandomVariableUtils.py

@@ -1,7 +1,8 @@
 import warnings
+
 import numpy as np
-import sklearn.preprocessing
 import pandas as pd
+import sklearn.preprocessing
 
 NONE_REPLACEMENT = -32768
 

bamt/log.py

@@ -1,8 +1,9 @@
 import logging.config
 import os
-from bamt.config import config
 import warnings
 
+from bamt.config import config
+
 log_file_path = config.get(
     "LOG", "log_conf_loc", fallback="log_conf_path is not defined"
 )

bamt/mi_entropy_gauss.py

@@ -1,17 +1,15 @@
-import os
+import math
 import sys
-import inspect
-
-
 from copy import copy
-import math
 from typing import List
+
 import numpy as np
 import pandas as pd
+
 from bamt.external.pyBN.utils.independence_tests import mutual_information, entropy
 from bamt.preprocess.discretization import get_nodes_type
-from bamt.preprocess.numpy_pandas import loc_to_DataFrame
 from bamt.preprocess.graph import edges_to_dict
+from bamt.preprocess.numpy_pandas import loc_to_DataFrame
 
 
 def query_filter(data: pd.DataFrame, columns: List, values: List):

bamt/networks/base.py

@@ -1,36 +1,33 @@
+import json
+import os
 import random
 import re
-import networkx as nx
+from typing import Dict, Tuple, List, Callable, Optional, Type, Union, Any, Sequence
+
 import matplotlib
 import matplotlib.pyplot as plt
-import pandas as pd
+import networkx as nx
 import numpy as np
-import json
-import os
-
-from sklearn.preprocessing import LabelEncoder
-from tqdm import tqdm
+import pandas as pd
 from joblib import Parallel, delayed
+from pgmpy.estimators import K2Score
 from pyvis.network import Network
+from sklearn.preprocessing import LabelEncoder
+from tqdm import tqdm
+
+import bamt.builders as builders
+from bamt.builders.builders_base import ParamDict
+from bamt.builders.evo_builder import EvoStructureBuilder
+from bamt.builders.hc_builder import HCStructureBuilder
+from bamt.config import config
 from bamt.external.pyitlib.DiscreteRandomVariableUtils import (
     information_mutual,
     information_mutual_conditional,
     entropy_conditional,
 )
-from pgmpy.estimators import K2Score
-
-from bamt.builders.builders_base import ParamDict
-from bamt.builders.hc_builder import HCStructureBuilder
-from bamt.builders.evo_builder import EvoStructureBuilder
 from bamt.log import logger_network
-from bamt.config import config
-
 from bamt.nodes.base import BaseNode
 
-import bamt.builders as builders
-
-from typing import Dict, Tuple, List, Callable, Optional, Type, Union, Any, Sequence
-
 STORAGE = config.get(
     "NODES", "models_storage", fallback="models_storage is not defined"
 )

bamt/networks/composite_bn.py

@@ -1,11 +1,12 @@
 import re
+from typing import Optional, Dict
 
-from bamt.networks.base import BaseNetwork
 import pandas as pd
-from typing import Optional, Dict
+
 from bamt.builders.composite_builder import CompositeStructureBuilder, CompositeDefiner
-from bamt.utils.composite_utils.MLUtils import MlModels
 from bamt.log import logger_network
+from bamt.networks.base import BaseNetwork
+from bamt.utils.composite_utils.MLUtils import MlModels
 
 
 class CompositeBN(BaseNetwork):

bamt/networks/hybrid_bn.py

@@ -1,7 +1,7 @@
-from .base import BaseNetwork
-
 from typing import Dict
 
+from .base import BaseNetwork
+
 
 class HybridBN(BaseNetwork):
     """

bamt/nodes/base.py

@@ -1,9 +1,8 @@
-from bamt.config import config
-
+import os
+import pickle
 from typing import Union
 
-import pickle
-import os
+from bamt.config import config
 
 STORAGE = config.get(
     "NODES", "models_storage", fallback="models_storage is not defined"

bamt/nodes/composite_continuous_node.py

@@ -1,8 +1,9 @@
-from .gaussian_node import GaussianNode
-from .schema import GaussianParams, HybcprobParams
+from typing import Optional, Union
 
 from sklearn import linear_model
-from typing import Optional, Union
+
+from .gaussian_node import GaussianNode
+from .schema import GaussianParams, HybcprobParams
 
 NodeInfo = Union[GaussianParams, HybcprobParams]
 

bamt/nodes/composite_discrete_node.py

@@ -1,7 +1,8 @@
-from .logit_node import LogitNode
+from typing import Optional
 
 from sklearn import linear_model
-from typing import Optional
+
+from .logit_node import LogitNode
 
 
 class CompositeDiscreteNode(LogitNode):

bamt/nodes/conditional_gaussian_node.py

@@ -1,20 +1,18 @@
-import numpy as np
 import itertools
-
+import math
 import pickle
-import joblib
 import random
-import math
-
-from .base import BaseNode
-from .schema import CondGaussParams
-
-from bamt.log import logger_nodes
+from typing import Dict, Optional, List, Union
 
+import joblib
+import numpy as np
+from pandas import DataFrame
 from sklearn import linear_model
 from sklearn.metrics import mean_squared_error as mse
-from pandas import DataFrame
-from typing import Dict, Optional, List, Union
+
+from bamt.log import logger_nodes
+from .base import BaseNode
+from .schema import CondGaussParams
 
 
 class ConditionalGaussianNode(BaseNode):