Merge 6f38b5b into d613a52

.travis.yml

@@ -5,6 +5,8 @@ python:
   - 2.7
   - 3.4
   - 3.5
+  - 3.6
+  - 3.7
 cache: pip
 env:
   global:
@@ -30,6 +32,6 @@ before_script:
   - "sh -e /etc/init.d/xvfb start"
   - sleep 3 # give xvfb some time to start
 script:
-  - py.test --cov=queueing_tool --cov-report term-missing --doctest-modules
+  - pytest --cov=queueing_tool --cov-report term-missing --doctest-modules -k "not slow"
 after_success:
   - coveralls

README.rst

@@ -37,7 +37,7 @@ Installation
 ------------
 
 
-**Prerequisites:** Queueing-tool runs on Python 2.7 and 3.4-3.5 and it
+**Prerequisites:** Queueing-tool runs on Python 2.7 and 3.4-3.7 and it
 requires `networkx <http://networkx.readthedocs.org/en/stable/>`__ and
 `numpy <http://www.numpy.org/>`__. If you want to plot, you will need
 to install `matplotlib <http://matplotlib.org/>`__ as well.
@@ -73,7 +73,7 @@ The issue tracker is at https://github.com/djordon/queueing-tool/issues. Please
 Copyright and license
 ---------------------
 
-Code and documentation Copyright 2014-2016 Daniel Jordon. Code released
+Code and documentation Copyright 2014-2019 Daniel Jordon. Code released
 under the `MIT
 license <https://github.com/djordon/queueing-tool/blob/master/LICENSE.txt>`__.
 

VERSION

@@ -1 +1 @@
-1.2.2
+1.3.0

queueing_tool/__init__.py

@@ -1,20 +1,24 @@
 from __future__ import absolute_import
 
-from queueing_tool.queues import *
-import queueing_tool.queues as queues
+from queueing_tool.common import *
+import queueing_tool.common as common
+
+from queueing_tool.graph import *
+import queueing_tool.graph as graph
 
 from queueing_tool.network import *
 import queueing_tool.network as network
 
-from queueing_tool.graph import *
-import queueing_tool.graph as graph
+from queueing_tool.queues import *
+import queueing_tool.queues as queues
+
 
 __all__ = []
-__version__ = '1.2.2'
+__version__ = '1.3.0'
 
-__all__.extend(['__version__'])
-__all__.extend(queues.__all__)
-__all__.extend(network.__all__)
+__all__.extend(['__version__', 'EdgeID', 'AgentID'])
 __all__.extend(graph.__all__)
+__all__.extend(network.__all__)
+__all__.extend(queues.__all__)
 
 # del queues, network, generation, graph

queueing_tool/common.py

@@ -0,0 +1,12 @@
+import collections
+
+
+EdgeID = collections.namedtuple(
+    typename='EdgeID',
+    field_names=['source', 'target', 'edge_index', 'edge_type']
+)
+
+AgentID = collections.namedtuple(
+    typename='AgentID',
+    field_names=['edge_index', 'agent_qid']
+)

queueing_tool/graph/__init__.py

@@ -7,6 +7,7 @@
     generate_pagerank_graph
     generate_transition_matrix
     graph2dict
+    matrix2dict
     minimal_random_graph
     set_types_rank
     set_types_random
@@ -15,7 +16,8 @@
 """
 
 from queueing_tool.graph.graph_functions import (
-    graph2dict
+    graph2dict,
+    matrix2dict
 )
 from queueing_tool.graph.graph_generation import (
     generate_random_graph,
@@ -42,6 +44,7 @@
     'generate_pagerank_graph',
     'generate_transition_matrix',
     'graph2dict',
+    'matrix2dict',
     'minimal_random_graph',
     'set_types_rank',
     'set_types_random',

queueing_tool/graph/graph_functions.py

@@ -86,3 +86,56 @@ def graph2dict(g, return_dict_of_dict=True):
         return dict_of_dicts
     else:
         return {k: list(val.keys()) for k, val in dict_of_dicts.items()}
+
+
+def matrix2dict(matrix, graph):
+    """Takes an adjacency matrix and returns an adjacency list.
+
+    Parameters
+    ----------
+    graph : :any:`networkx.DiGraph`, :any:`networkx.Graph`, etc.
+        Any object that networkx can turn into a
+        :any:`DiGraph<networkx.DiGraph>`.
+    matrix : :class:`~numpy.ndarray`
+        An matrix related to an adjacency list. The ``matrix[i, j]``
+        represents some relationship between the vertex ``i`` and the
+        vertex ``j``.
+
+    Returns
+    -------
+    adj : dict
+        An adjacency representation of the matrix for the graph.
+
+    Examples
+    --------
+    >>> import queueing_tool as qt
+    >>> import networkx as nx
+    >>> adj = {0: [1, 2], 1: [0], 2: [0, 3], 3: [2]}
+    >>> g = nx.DiGraph(adj)
+    >>> mat = qt.generate_transition_matrix(g, seed=123)
+    >>> mat                     # doctest: +ELLIPSIS
+    ...                         # doctest: +NORMALIZE_WHITESPACE
+    array([[ 0.        ,  0.70707071,  0.29292929,  0.        ],
+           [ 1.        ,  0.        ,  0.        ,  0.        ],
+           [ 0.29113924,  0.        ,  0.        ,  0.70886076],
+           [ 0.        ,  0.        ,  1.        ,  0.        ]])
+    >>> qt.matrix2dict(mat, g)  # doctest: +ELLIPSIS
+    ...                         # doctest: +NORMALIZE_WHITESPACE
+    {0: {1: 0.707..., 2: 0.292...},
+     1: {0: 1.0},
+     2: {0: 0.291..., 3: 0.708...},
+     3: {2: 1.0}}
+    """
+    num_columns, num_rows = matrix.shape
+
+    if num_columns != num_rows or num_columns != graph.number_of_nodes():
+        msg = "Matrix has wrong shape, must be {} x {}"
+        non = graph.number_of_nodes()
+        raise ValueError(msg.format(non, non))
+
+    result = {}
+    adjacency_graph = graph2dict(graph, return_dict_of_dict=False)
+    for source, adjacents in adjacency_graph.items():
+        result[source] = {dest: matrix[source, dest] for dest in adjacents}
+
+    return result