Merge pull request #35 from agustin-recoba/feature/network_rename

Network -> DirectedNetwork class rename

Author: agustin-recoba

docs/reference/networkbehavior.rst

@@ -16,7 +16,7 @@ class defines the three parameters that are used to model the communication prop
    #. How fast a node can process a message. This is used to model the case where a node can only process a certain
       number of messages per time unit.
 
-To apply these properties to a network, simply set :attr:`Network.behavioral_properties` to an instance of
+To apply these properties to a network, simply set :attr:`NetworkType.behavioral_properties` to an instance of
 :class:`NetworkBehaviorModel`.
 
 

docs/reference/networkmixin.rst

@@ -11,7 +11,7 @@ PyDistSim uses the library :mod:`networkx` to represent graphs. :mod:`networkx`
 In order to extend the defined :class:`networkx.Graph` and :class:`networkx.DiGraph` in :mod:`networkx`, PyDistSim uses a mixin class.
 
 This mixin class is called NetworkMixin and is defined in the network module.
-For the development of the framework, we have used this mixin to define :class:`Network` and :class:`BidirectionalNetwork`,
+For the development of the framework, we have used this mixin to define :class:`DirectedNetwork` and :class:`BidirectionalNetwork`,
 which are subclasses of :class:`networkx.Graph` and :class:`networkx.DiGraph` respectively.
 
 In broad terms, these NetworkMixin subclasses are responsible for the following:
@@ -23,5 +23,5 @@ In broad terms, these NetworkMixin subclasses are responsible for the following:
 
 For class and method documentation refer to :class:`NetworkMixin`.
 
-.. inheritance-diagram:: Network BidirectionalNetwork
-   :caption: Inheritance diagram for Network and BidirectionalNetwork
+.. inheritance-diagram:: DirectedNetwork BidirectionalNetwork
+   :caption: Inheritance diagram for DirectedNetwork and BidirectionalNetwork

docs/reference/observers.rst

@@ -28,7 +28,7 @@ Standardize the use of observers in the framework, we implemented a mixin class
 can be used to add observer functionality to any class. The mixin class provides methods to add and remove observers,
 and to notify the observers of changes in the observable object.
 
-.. inheritance-diagram:: ObserverManagerMixin pydistsim.algorithm.BaseAlgorithm pydistsim.simulation.Simulation pydistsim.network.network.Network pydistsim.network.network.BidirectionalNetwork pydistsim.network.node.Node
+.. inheritance-diagram:: ObserverManagerMixin pydistsim.algorithm.BaseAlgorithm pydistsim.simulation.Simulation pydistsim.network.network.DirectedNetwork pydistsim.network.network.BidirectionalNetwork pydistsim.network.node.Node
    :top-classes: ObserverManagerMixin
    :parts: 1
    :caption: ObserverManagerMixin inheritance diagram

pydistsim/__init__.py

@@ -31,7 +31,12 @@
 from pydistsim.algorithm import NodeAlgorithm, StatusValues
 from pydistsim.benchmark import AlgorithmBenchmark
 from pydistsim.logging import disable_logger, enable_logger, logger
-from pydistsim.network import BidirectionalNetwork, Network, NetworkGenerator, Node
+from pydistsim.network import (
+    BidirectionalNetwork,
+    DirectedNetwork,
+    NetworkGenerator,
+    Node,
+)
 from pydistsim.simulation import Simulation
 
 __path__ = extend_path(__path__, __name__)  # @ReservedAssignment

pydistsim/algorithm/base_algorithm.py

@@ -88,7 +88,7 @@ class SomeAlgorithm(NodeAlgorithm):
         required_params = ('rp1',)
         default_params = {'dp1': 'dv1',}
 
-    >>> net = Network()
+    >>> net = DirectedNetwork()
     >>> alg = SomeAlgorithm(net, rp1='rv1')
     >>> alg.rp1
     'rv1'

pydistsim/benchmark.py

@@ -15,13 +15,13 @@
 from pydistsim.metrics import MetricCollector
 from pydistsim.network.behavior import NetworkBehaviorModel
 from pydistsim.network.generator import NetworkGenerator
-from pydistsim.network.network import BidirectionalNetwork, Network, NetworkType
+from pydistsim.network.network import BidirectionalNetwork, DirectedNetwork, NetworkType
 from pydistsim.simulation import AlgorithmsParam, Simulation
 
 
 def decide_directed_class(directed: bool):
     if directed:
-        return Network
+        return DirectedNetwork
     else:
         return BidirectionalNetwork
 

pydistsim/gui/drawing.py

@@ -366,7 +366,7 @@ def draw_current_state(
     Automatically determines the current algorithm and draws the network accordingly. This includes a mapping of
     node colors to the status of the nodes, as well as the messages in the network.
 
-    :param sim: Simulation or Network object
+    :param sim: Simulation or NetworkType object
     :param axes: matplotlib axes object
     :param clear: boolean to clear the axes before drawing
     :param tree_key: key in nodes memory (dictionary) where tree data is stored

pydistsim/network/__init__.py

@@ -7,7 +7,7 @@
 from pydistsim.network.generator import NetworkGenerator, NetworkGeneratorException
 from pydistsim.network.network import (
     BidirectionalNetwork,
-    Network,
+    DirectedNetwork,
     NetworkException,
     NetworkType,
 )

pydistsim/network/generator.py

@@ -6,7 +6,7 @@
 from numpy.random import rand
 
 from pydistsim.logging import logger
-from pydistsim.network.network import BidirectionalNetwork, Network
+from pydistsim.network.network import BidirectionalNetwork, DirectedNetwork
 from pydistsim.network.node import Node
 from pydistsim.network.rangenetwork import BidirectionalRangeNetwork, RangeNetwork
 
@@ -303,7 +303,7 @@ def generate_complete_network(cls, n: int, network_type: type[T] = None, directe
             >>> net1 = NetworkGenerator.generate_complete_network(5)
             <BidirectionalNetwork object with 5 nodes and 10 edges>
             >>> net2 = NetworkGenerator.generate_complete_network(5, directed_network=True)
-            <Network object with 5 nodes and 20 edges>
+            <DirectedNetwork object with 5 nodes and 20 edges>
             >>> net3 = NetworkGenerator.generate_complete_network(5, network_type=BidirectionalNetwork)
             <BidirectionalNetwork object with 5 nodes and 10 edges>
 
@@ -322,7 +322,7 @@ def generate_complete_network(cls, n: int, network_type: type[T] = None, directe
             directed_network = False
 
         if network_type is None:
-            network_type = Network if directed_network else BidirectionalNetwork
+            network_type = DirectedNetwork if directed_network else BidirectionalNetwork
 
         net = network_type()
         node_pos_list = cls.__get_ring_pos(n, net.environment)
@@ -349,7 +349,7 @@ def generate_ring_network(cls, n: int, network_type: type[T] = None, directed_ne
             >>> net = NetworkGenerator.generate_ring_network(6)
             <BidirectionalNetwork object with 6 nodes and 6 edges>
             >>> net = NetworkGenerator.generate_ring_network(6, directed_network=False)
-            <Network object with 6 nodes and 6 edges>
+            <DirectedNetwork object with 6 nodes and 6 edges>
 
         DO NOT instantiate the class, this is a class method.
 
@@ -366,7 +366,7 @@ def generate_ring_network(cls, n: int, network_type: type[T] = None, directed_ne
             directed_network = False
 
         if network_type is None:
-            network_type = Network if directed_network else BidirectionalNetwork
+            network_type = DirectedNetwork if directed_network else BidirectionalNetwork
 
         net = network_type()
         node_pos_list = cls.__get_ring_pos(n, net.environment)
@@ -409,7 +409,7 @@ def generate_star_network(cls, n: int, network_type: type[T] = None, directed_ne
             directed_network = False
 
         if network_type is None:
-            network_type = Network if directed_network else BidirectionalNetwork
+            network_type = DirectedNetwork if directed_network else BidirectionalNetwork
 
         net = network_type()
         node_pos_list = cls.__get_ring_pos(n - 1, net.environment)
@@ -447,7 +447,7 @@ def generate_hypercube_network(
             >>> net = NetworkGenerator.generate_hypercube_network(dimension=3)
             <BidirectionalNetwork object with 8 nodes and 12 edges>
             >>> net2 = NetworkGenerator.generate_hypercube_network(dimension=3, directed_network=True)
-            <Network object with 8 nodes and 24 edges>
+            <DirectedNetwork object with 8 nodes and 24 edges>
             >>> net3 = NetworkGenerator.generate_complete_network(n=8)
             <BidirectionalNetwork object with 8 nodes and 12 edges>
 
@@ -477,7 +477,7 @@ def generate_hypercube_network(
             directed_network = False
 
         if network_type is None:
-            network_type = Network if directed_network else BidirectionalNetwork
+            network_type = DirectedNetwork if directed_network else BidirectionalNetwork
 
         LABEL_KEY = "HYPERCUBE_LABEL"
 
@@ -616,7 +616,7 @@ def generate_mesh_network(
             directed_network = False
 
         if network_type is None:
-            network_type = Network if directed_network else BidirectionalNetwork
+            network_type = DirectedNetwork if directed_network else BidirectionalNetwork
 
         if a is None or b is None:
             if n is None:

pydistsim/network/network.py

@@ -34,7 +34,7 @@ class NetworkMixin(ObserverManagerMixin, with_typehint(Graph)):
     """
     Mixin to extend Graph and DiGraph. The result represents a network in a distributed simulation.
 
-    The Network classes (:class:`Network` and :class:`BidirectionalNetwork`) extend the Graph class and provides additional functionality
+    The Network classes (:class:`DirectedNetwork` and :class:`BidirectionalNetwork`) extend the Graph class and provides additional functionality
     for managing nodes and network properties.
 
     :param environment: The environment in which the network operates. If not provided, a new Environment instance will be created.
@@ -64,7 +64,7 @@ def __init__(
 
     @staticmethod
     def to_directed_class():
-        return Network
+        return DirectedNetwork
 
     @staticmethod
     def to_undirected_class():
@@ -269,14 +269,14 @@ def subnetwork(
         edges: None | Iterable[tuple[Node, Node]] = None,
     ):
         """
-        Returns a Network instance with the specified nodes and edges.
+        Returns a NetworkType instance with the specified nodes and edges.
 
         :param nbunch: A list of nodes to include in the subnetwork.
         :type nbunch: list[Node]
         :param edges: A list of edges to include in the subnetwork. Defaults to None.
         :type edges: Iterable[tuple[Node, Node]], optional
-        :return: A Network instance representing the subnetwork.
-        :rtype: Network
+        :return: A NetworkType instance representing the subnetwork.
+        :rtype: NetworkType
         """
 
         return self.__deepcopy__({}, nodes, edges)
@@ -649,7 +649,7 @@ def validate_params(self, params: dict):
                             assert sensor.probabilityFunction.scale == value
 
 
-class Network(NetworkMixin, DiGraph):
+class DirectedNetwork(NetworkMixin, DiGraph):
     """
     A directed graph representing a network in a distributed simulation.
     """
@@ -661,5 +661,5 @@ class BidirectionalNetwork(NetworkMixin, Graph):
     """
 
 
-NetworkType = Network | BidirectionalNetwork
+NetworkType = DirectedNetwork | BidirectionalNetwork
 "A network in a distributed simulation."

pydistsim/network/node.py

@@ -49,7 +49,7 @@ class Node(ObserverManagerMixin):
     Represents a node in a network.
 
     :param network: Optional network object to which the node belongs.
-    :type network: Network, optional
+    :type network: NetworkType, optional
     :param commRange: Communication range of the node.
     :type commRange: int, optional
     :param sensors: Tuple of sensor types or names.

pydistsim/network/rangenetwork.py

@@ -7,7 +7,7 @@
 
 from pydistsim.logging import logger
 from pydistsim.network.environment import Environment
-from pydistsim.network.network import BidirectionalNetwork, Network
+from pydistsim.network.network import BidirectionalNetwork, DirectedNetwork
 from pydistsim.utils.helpers import with_typehint
 
 if TYPE_CHECKING:
@@ -36,7 +36,7 @@ def in_comm_range(self, network: "RangeNetworkType", node1: "Node", node2: "Node
         are within communication range.
 
         :param network: The network in which the nodes are connected.
-        :type network: Network
+        :type network: RangeNetworkType
         :param node1: The first node.
         :type node1: Node
         :param node2: The second node.
@@ -65,7 +65,7 @@ def in_comm_range(self, network: "RangeNetworkType", node1: "Node", node2: "Node
         positioned so that their distance is smaller than the communication range.
 
         :param network: The network in which the nodes are connected.
-        :type network: Network
+        :type network: RangeNetworkType
         :param node1: The first node.
         :type node1: Node
         :param node2: The second node.
@@ -99,7 +99,7 @@ def in_comm_range(self, network: "RangeNetworkType", node1: "Node", node2: "Node
         communication range.
 
         :param network: The network in which the nodes are connected.
-        :type network: Network
+        :type network: RangeNetworkType
         :param node1: The first node.
         :type node1: Node
         :param node2: The second node.
@@ -129,7 +129,7 @@ def in_comm_range(self, network: "RangeNetworkType", node1: "Node", node2: "Node
         probability of connection.
 
         :param network: The network in which the nodes are connected.
-        :type network: Network
+        :type network: RangeNetworkType
         :param node1: The first node.
         :type node1: Node
         :param node2: The second node.
@@ -147,7 +147,7 @@ def in_comm_range(self, network: "RangeNetworkType", node1: "Node", node2: "Node
         return False
 
 
-class RangeNetworkMixin(with_typehint(Network)):
+class RangeNetworkMixin(with_typehint(DirectedNetwork)):
     """
     Mixin to define a type of network that decides which nodes are connected based on their
     communication range.
@@ -295,7 +295,7 @@ def modify_avg_degree(self, value):
         logger.trace("Modified degree to {}", self.avg_degree())
 
 
-class RangeNetwork(RangeNetworkMixin, Network):
+class RangeNetwork(RangeNetworkMixin, DirectedNetwork):
     """
     Type of network that decides which nodes are connected based on their communication range.
 

pydistsim/tests/test_network.py

@@ -8,7 +8,7 @@
     BidirectionalNetwork,
     BidirectionalRangeNetwork,
     CompleteRangeType,
-    Network,
+    DirectedNetwork,
     NetworkException,
     NetworkType,
     Node,

pydistsim/tests/test_npickle.py

@@ -2,7 +2,7 @@
 import unittest
 
 from pydistsim.demo_algorithms.broadcast import Flood
-from pydistsim.network import Network, NetworkGenerator, NetworkType
+from pydistsim.network import DirectedNetwork, NetworkGenerator, NetworkType
 from pydistsim.utils.npickle import read_npickle, write_npickle
 
 
@@ -23,7 +23,7 @@ def setUp(self):
 
     def test_write_read(self):
         for i, (size, net) in enumerate(self.nets):
-            net: Network
+            net: DirectedNetwork
             with self.subTest(net=net):
                 try:
                     write_npickle(net, f"net_test_{i}.tar.gz")

pydistsim/tests/test_restrictions.py

@@ -3,7 +3,7 @@
 from pydistsim.message import Message
 from pydistsim.network import NetworkGenerator
 from pydistsim.network.behavior import NetworkBehaviorModel
-from pydistsim.network.network import Network
+from pydistsim.network.network import DirectedNetwork
 from pydistsim.restrictions.communication import (
     BidirectionalLinks,
     MessageOrdering,
@@ -81,7 +81,7 @@ def test_MessageOrdering(self):
         assert not MessageOrdering.check(net)
 
     def test_ReciprocalCommunication(self):
-        net = Network()  # directed graph
+        net = DirectedNetwork()  # directed graph
         n1, n2, n3 = net.add_node(), net.add_node(), net.add_node()
 
         net.add_edge(n1, n2)
@@ -217,7 +217,7 @@ def test_Connectivity(self):
         net = NetworkGenerator(10, enforce_connected=True).generate_random_network()
         assert Connectivity.check(net)
 
-        net = Network()
+        net = DirectedNetwork()
         net.add_node()
         net.add_node()
         assert not Connectivity.check(net)
@@ -238,7 +238,7 @@ def test_UniqueInitiator(self):
         assert UniqueInitiator.check(net)
 
     def test_CompleteGraph(self):
-        net = Network()
+        net = DirectedNetwork()
 
         nodes = [net.add_node() for _ in range(10)]
         for i, n1 in enumerate(nodes):
@@ -252,7 +252,7 @@ def test_CompleteGraph(self):
         assert not CompleteGraph.check(net)
 
     def test_CycleGraph(self):
-        net = Network()
+        net = DirectedNetwork()
         LEN = 10
         nodes = [net.add_node() for _ in range(LEN)]
         for i, n1 in enumerate(nodes):
@@ -261,7 +261,7 @@ def test_CycleGraph(self):
 
         assert CycleGraph.check(net)
 
-        net = Network()
+        net = DirectedNetwork()
         nodes = [net.add_node() for _ in range(LEN)]
         for i, n1 in enumerate(nodes[:-2]):
             n2 = nodes[(i + 1) % LEN]
@@ -270,7 +270,7 @@ def test_CycleGraph(self):
         assert not CycleGraph.check(net)
 
     def test_TreeGraph(self):
-        net = Network()
+        net = DirectedNetwork()
         n1, n2, n3, n4, n5 = net.add_node(), net.add_node(), net.add_node(), net.add_node(), net.add_node()
 
         net.add_edge(n1, n2), net.add_edge(n1, n3), net.add_edge(n2, n4), net.add_edge(n2, n5)
@@ -280,7 +280,7 @@ def test_TreeGraph(self):
         assert not TreeGraph.check(net)
 
     def test_StarGraph(self):
-        net = Network()
+        net = DirectedNetwork()
         n1, n2, n3, n4, n5 = net.add_node(), net.add_node(), net.add_node(), net.add_node(), net.add_node()
 
         net.add_edge(n1, n2), net.add_edge(n1, n3), net.add_edge(n1, n4)