Minor code quality changes

queueing_tool/graph/graph_generation.py

@@ -1,5 +1,4 @@
 import numbers
-import copy
 
 import networkx as nx
 import numpy as np
@@ -120,7 +119,6 @@ def generate_random_graph(nVertices=250, prob_loop=0.5, **kwargs):
     typically used for terminal edges.
     """
     g = minimal_random_graph(nVertices, **kwargs)
-    nNodes  = g.number_of_nodes()
     for v in g.nodes():
         e = (v, v)
         if not g.is_edge(e):
@@ -203,7 +201,6 @@ def minimal_random_graph(nVertices, seed=None, **kwargs):
         np.random.seed(seed)
 
     points = np.random.random((nVertices, 2)) * 10
-    nEdges = nVertices * (nVertices - 1) // 2
     edges  = []
 
     for k in range(nVertices-1):
@@ -219,7 +216,6 @@ def minimal_random_graph(nVertices, seed=None, **kwargs):
     g = nx.Graph()
 
     for n1, n2, d in edges:
-        max_space = d
         unionF.union(n1, n2)
         g.add_edge(n1, n2)
         if unionF.nClusters == 1:
@@ -292,17 +288,14 @@ def set_types_random(g, proportions=None, loop_proportions=None, seed=None,
     if loop_proportions is None:
         loop_proportions = {k : 1. / 4 for k in range(4)}
 
-    nEdges = g.number_of_edges()
     edges  = [e for e in g.edges() if e[0] != e[1]]
     loops  = [e for e in g.edges() if e[0] == e[1]]
     props  = list(proportions.values())
     lprops = list(loop_proportions.values())
 
     if not np.isclose(sum(props), 1.0):
-        msg = "proportions values must sum to one."
         raise ValueError("proportions values must sum to one.")
     if not np.isclose(sum(lprops), 1.0):
-        msg = "loop_proportions values must sum to one."
         raise ValueError("loop_proportions values must sum to one.")
 
     eTypes = {}

queueing_tool/graph/graph_preparation.py

@@ -1,12 +1,7 @@
-import numbers
-
 import networkx as nx
 import numpy as np
 
-from queueing_tool.graph.graph_functions  import (
-    graph2dict,
-    _test_graph
-)
+from queueing_tool.graph.graph_functions  import _test_graph
 from queueing_tool.graph.graph_wrapper import (
     adjacency2graph,
     QueueNetworkDiGraph

queueing_tool/graph/graph_wrapper.py

@@ -45,7 +45,7 @@ def _adjacency_adjust(adjacency, adjust, is_directed):
     """
 
     for v, adj in adjacency.items():
-        for u, properties in adj.items():
+        for properties in adj.values():
             if properties.get('edge_type') is None:
                 properties['edge_type'] = 1
 
@@ -155,8 +155,7 @@ def adjacency2graph(adjacency, edge_type=None, adjust=1, **kwargs):
     2: {},
     3: {0: {'edge_type': 1}}}
     """
-    import copy
-    dd = copy.deepcopy(adjacency)
+
     if isinstance(adjacency, np.ndarray):
         adjacency = _matrix2dict(adjacency)
     elif isinstance(adjacency, dict):
@@ -490,7 +489,6 @@ def lines_scatter_args(self, line_kwargs=None, scatter_kwargs=None, pos=None):
             'zorder': 0,
             'facecolors': None,
             'norm': None,
-            'antialiaseds': None,
             'offsets': None,
             'offset_position': 'screen',
             'hatch': None,

queueing_tool/network/queue_network.py

@@ -3,7 +3,6 @@
 import copy
 import array
 
-import networkx as nx
 import numpy as np
 from numpy.random import uniform
 
@@ -18,7 +17,7 @@
 except ImportError:
     HAS_MATPLOTLIB = False
 
-from queueing_tool.graph import _prepare_graph, QueueNetworkDiGraph
+from queueing_tool.graph import _prepare_graph
 from queueing_tool.queues import (
     NullQueue,
     QueueServer,
@@ -1320,7 +1319,6 @@ def _simulate_next_event(self, slow=True):
             e2  = q1._departures[0].desired_destination(self, q1.edge)
             q2  = self.edge2queue[e2]
             q2k = q2._key()
-            q2t = q2k[0]
 
             if q2.at_capacity() and e2 != e1:
                 q2.nBlocked += 1

queueing_tool/queues/queue_extentions.py

@@ -1,15 +1,12 @@
 import copy
 from heapq import heappush, heappop
 
-from numpy.random import randint, exponential
+from numpy.random import exponential
 from numpy import logical_or, infty
 import numpy as np
 
 from queueing_tool.queues.agents import Agent
-from queueing_tool.queues.queue_servers import (
-    QueueServer,
-    LossQueue
-)
+from queueing_tool.queues.queue_servers import LossQueue
 
 
 class ResourceAgent(Agent):
@@ -202,7 +199,7 @@ def _current_color(self, which=0):
 
             color    = [i * tmp / 0.9 for i in self.colors['edge_loop_color']]
             color[3] = 0.0
-  
+
         elif which == 2:
             color = self.colors['vertex_pen_color']
         else:

queueing_tool/queues/queue_servers.py

@@ -763,19 +763,19 @@ def simulate(self, n=1, t=None, nA=None, nD=None):
         """
         if t is None and nD is None and nA is None:
             for k in range(n):
-                tmp = self.next_event()
+                self.next_event()
         elif t is not None:
             then = self._current_t + t
             while self._current_t < then and self._time < infty:
-                tmp = self.next_event()
+                self.next_event()
         elif nD is not None:
             nDepartures = self.nDepartures + nD
             while self.nDepartures < nDepartures and self._time < infty:
-                tmp = self.next_event()
+                self.next_event()
         elif nA is not None:
             nArrivals = self._oArrivals + nA
             while self._oArrivals < nArrivals and self._time < infty:
-                tmp = self.next_event()
+                self.next_event()
 
 
     def __deepcopy__(self, memo):
@@ -966,7 +966,7 @@ def _add_arrival(self, agent=None):
             else:
                 self.data[agent.agent_id].append([agent._time, 0, 0, 0, 0])
 
-    def delay_service(self):
+    def delay_service(self, *args, **kwargs):
         pass
 
     def next_event_description(self):

tests/test_graph_generation.py

@@ -1,8 +1,4 @@
 import unittest
-try:
-    import unittest.mock as mock
-except ImportError:
-    import mock
 
 from numpy.random import randint
 import networkx as nx
@@ -45,8 +41,8 @@ def test_graph2dict(self):
 
 
     def test_add_edge_lengths(self):
-        g   = qt.generate_pagerank_graph(10)
-        g2  = qt.add_edge_lengths(g)
+        g = qt.generate_pagerank_graph(10)
+        g = qt.add_edge_lengths(g)
 
         edge_props = set()
         for key in g.edge_properties():
@@ -79,12 +75,6 @@ def test_adjacency2graph_matrix_adjacency(self):
         g   = qt.adjacency2graph(adj, edge_type=ety, adjust=2)
         ans = qt.graph2dict(g)
 
-        expected_response = {
-            0: {1: {'edge_type': 5}},
-            1: {2: {'edge_type': 9}, 3: {'edge_type': 0}},
-            2: {0: {'edge_type': 1}},
-            3: {}
-        }
         self.assertTrue(ans == self.expected_response1)
 
 

tests/test_network.py

@@ -100,7 +100,7 @@ def test_QueueNetwork_blocking(self):
             5: qt.ResourceQueue,
             6: qt.QueueServer
         }
-                 
+
         q_arg = {
             3: {'net_size': g.number_of_edges()},
             4: {'nServers': 500},
@@ -210,7 +210,7 @@ def test_QueueNetwork_drawing_animation_error(self):
     def test_QueueNetwork_init_error(self):
         g  = qt.generate_pagerank_graph(7)
         with self.assertRaises(TypeError):
-            qn = qt.QueueNetwork(g, blocking=2)
+            qt.QueueNetwork(g, blocking=2)
 
     def test_QueueNetwork_get_agent_data(self):
 

tests/test_qndigraph.py

@@ -1,12 +1,10 @@
 import os
-import sys
 import unittest
 try:
     import unittest.mock as mock
 except ImportError:
     import mock
 
-from numpy.random import randint
 import networkx as nx
 import numpy as np
 

tests/test_queue_server.py

@@ -1,9 +1,4 @@
-import os
 import unittest
-try:
-    import unittest.mock as mock
-except ImportError:
-    import mock
 
 import networkx as nx
 import numpy as np
@@ -49,7 +44,7 @@ def test_QueueServer_set_nServers_errors(self):
             q.set_nServers(0)
 
     def test_QueueServer_set_inactive(self):
-        
+
         q   = qt.QueueServer()
         q.set_active()
 
@@ -203,7 +198,6 @@ def test_LossQueue_blocking(self):
             else :
                 q.simulate(n=1)
 
-        tmp = np.ones(5)
         self.assertTrue( ans.all() )
 
 

tests/test_statistical_properties.py

@@ -87,7 +87,6 @@ def test_QueueServer_Littleslaw(self):
         q.clear()
 
         ind  = data[:,2] > 0
-        souj = data[ind, 2] - data[ind, 0]
         wait = data[ind, 1] - data[ind, 0]
         ans  = np.mean(wait) * self.lam - np.mean(data[:, 3]) * self.rho
 
@@ -135,9 +134,8 @@ def test_poisson_random_measure(self):
         # Poisson random variables using a chi-squared test (testing the
         # composite null hypothesis). It does not look for independence of the
         # random variables.
+        # This test should fail some percentage of the time
 
-        # This test should fail about
-
         rate  = lambda t: 0.5 + 4 * np.sin(np.pi * t / 12)**2
         arr_f = lambda t: qt.poisson_random_measure(rate, 4.5, t)