Optimized imports

bamt/core/graph/dag.py

@@ -1,6 +1,7 @@
-from .graph import Graph
 from networkx import DiGraph
 
+from .graph import Graph
+
 
 class DirectedAcyclicGraph(Graph):
  def __init__(self):

bamt/core/graph/graph.py

@@ -1,4 +1,4 @@
-from abc import ABC, abstractmethod
+from abc import ABC
 
 
 class Graph(ABC):

bamt/core/node_models/__init__.py

@@ -1,4 +1,4 @@
-from continuous_distribution import ContinuousDistribution
 from classifier import Classifier
+from continuous_distribution import ContinuousDistribution
 from empirical_distribution import EmpiricalDistribution
 from regressor import Regressor

bamt/core/node_models/classifier.py

@@ -1,7 +1,7 @@
-from .prediction_model import PredictionModel
-
 import numpy as np
 
+from .prediction_model import PredictionModel
+
 
 class Classifier(PredictionModel):
  def __init__(self, classifier=None, **parameters):

bamt/core/node_models/continuous_distribution.py

@@ -1,9 +1,12 @@
+from enum import Enum
+from typing import Tuple, Optional, List, Type, Dict
+
 import numpy as np
 from scipy import stats
-from scipy.stats import rv_continuous
 from scipy.special import kl_div
-from typing import Tuple, Optional, List, Type, Dict
-from enum import Enum
+from scipy.stats import rv_continuous
+
+from .distribution import Distribution
 
 # Get all continuous distributions from scipy.stats
 _CONTINUOUS_DISTRIBUTIONS = [
@@ -24,7 +27,7 @@ class DistributionPool(Enum):
 
 
 # noinspection PyPep8Naming
-class ContinuousDistribution:
+class ContinuousDistribution(Distribution):
  """
  Class for continuous distributions.
  This class is a wrapper for continuous distributions from `scipy.stats` module,

bamt/core/node_models/empirical_distribution.py

@@ -1,5 +1,7 @@
-import numpy as np
 from typing import Optional, Union, List
+
+import numpy as np
+
 from distribution import Distribution
 
 

bamt/core/node_models/regressor.py

@@ -1,7 +1,7 @@
-from .prediction_model import PredictionModel
-
 import numpy as np
 
+from .prediction_model import PredictionModel
+
 
 class Regressor(PredictionModel):
  def __init__(self, regressor=None, **parameters):

bamt/core/nodes/child_nodes/__init__.py

@@ -1,2 +1,2 @@
-from conditional_discrete_node import ConditionalDiscreteNode
 from conditional_continuous_node import ConditionalContinuousNode
+from conditional_discrete_node import ConditionalDiscreteNode

bamt/core/nodes/root_nodes/continuous_node.py

@@ -1,7 +1,9 @@
+from typing import Optional
+
 import numpy as np
-from .root_node import RootNode
+
 from bamt.core.node_models import ContinuousDistribution
-from typing import List, Optional
+from .root_node import RootNode
 
 
 class ContinuousNode(RootNode):

bamt/core/nodes/root_nodes/discrete_node.py

@@ -1,7 +1,7 @@
 from typing import Optional
 
-from .root_node import RootNode
 from bamt.core.node_models import EmpiricalDistribution
+from .root_node import RootNode
 
 
 class DiscreteNode(RootNode):