Merge pull request #3 from IdeasLabUT/issue-1-fix

Fixes - including issue #1

.gitignore

@@ -59,3 +59,6 @@ dynetworkx/classes/test.py
 DyNetworkX.egg-info/
 tutorials/facebook-wall.txt.anon
 tutorials/execs.email.linesnum
+
+# venv
+.venv

README.rst → README.md

@@ -2,8 +2,7 @@ DyNetworkX
 ==========
 
 DyNetworkX is a Python package for the study of dynamic network analysis (DNA).
-DyNetworkX used to be a fork of `NetworkX <https://networkx.github.io/documentation/stable/index.html>`_
-package. Thus, implementation, documentation and the development of DyNetworkX is heavily
+DyNetworkX used to be a fork of [NetworkX](https://networkx.github.io/documentation/stable/index.html) package. Thus, implementation, documentation and the development of DyNetworkX is heavily
 influenced by NetworkX.
 
 **Documentation:** https://dynetworkx.readthedocs.io/
@@ -21,6 +20,13 @@ The audience for DyNetworkX includes mathematicians, physicists, biologists,
 computer scientists, and social scientists. Overall, everyone interested
 in analyzing dynamic networks.
 
+Install
+-------
+You can install the latest version of DyNetworkX using pip:
+```python
+pip install dynetworkx
+```
+
 Python
 ------
 
@@ -30,12 +36,12 @@ algorithms.  Python has a vibrant and growing ecosystem of packages that
 NetworkX uses to provide more features such as numerical linear algebra and
 drawing.  In order to make the most out of NetworkX you will want to know how
 to write basic programs in Python.  Among the many guides to Python, we
-recommend the `Python documentation <https://docs.python.org/3/>`_.
+recommend the [Python documentation](https://docs.python.org/3/).
 
 License
 -------
 
-Released under the 3-Clause BSD license (see `dydoc/source/license.rst`)::
+Released under the 3-Clause BSD license (see [LICENSE.txt](LICENSE.txt)):
 
    Copyright (C) 2018 IDEASLab @ The University of Toledo.
 

dynetworkx/classes/impulsedigraph.py

@@ -4,9 +4,8 @@
 from networkx.classes.digraph import DiGraph
 from networkx.classes.multidigraph import MultiDiGraph
 
-import dynetworkx as dnx
 from networkx.exception import NetworkXError
-from sortedcontainers import SortedList, SortedDict
+from sortedcontainers import SortedDict
 import random
 import math
 from timeit import default_timer as timer

dynetworkx/classes/impulsegraph.py

@@ -2,16 +2,14 @@
 from networkx.classes.graph import Graph
 from networkx.exception import NetworkXError
 from networkx.classes.multigraph import MultiGraph
-from networkx.classes.reportviews import NodeView, EdgeView, NodeDataView
-from sortedcontainers import SortedList, SortedDict
+from networkx.classes.reportviews import NodeDataView
+from sortedcontainers import SortedDict
 import random
 import math
 from timeit import default_timer as timer
 from sklearn.linear_model import LinearRegression
 from itertools import product
 
-from dynetworkx.classes.intervalgraph import IntervalGraph
-
 
 class ImpulseGraph(object):
     """Base class for undirected impulse graphs.

dynetworkx/classes/intervaldigraph.py

@@ -2,10 +2,9 @@
 from networkx.classes.digraph import DiGraph
 from networkx.classes.multidigraph import MultiDiGraph
 
-import dynetworkx as dnx
 from networkx.exception import NetworkXError
 from dynetworkx.classes.intervaltree import IntervalTree
-from sortedcontainers import SortedList, SortedDict
+from sortedcontainers import SortedDict
 import random
 import math
 from timeit import default_timer as timer

dynetworkx/classes/intervalgraph.py

@@ -3,7 +3,7 @@
 from networkx.exception import NetworkXError
 from dynetworkx.classes.intervaltree import IntervalTree
 from networkx.classes.multigraph import MultiGraph
-from networkx.classes.reportviews import NodeView, EdgeView, NodeDataView
+from networkx.classes.reportviews import NodeDataView
 from sortedcontainers import SortedList, SortedDict
 import random
 import math
@@ -775,7 +775,7 @@ def has_edge(self, u, v, begin=None, end=None, overlapping=True):
         True
 
         With specific overlapping interval:
-        
+
         >>> G.has_edge(1, 2, begin=2)
         True
         >>> G.has_edge(2, 4, begin=12)

dynetworkx/classes/intervaltree.py

@@ -1,5 +1,3 @@
-import networkx as nx
-from sortedcontainers import SortedDict, SortedList
 import operator
 
 class Node:

dynetworkx/classes/snapshotgraph.py

@@ -1,7 +1,7 @@
 from networkx.classes.graph import Graph
 import numpy as np
 from networkx import adjacency_matrix, from_numpy_array
-from sortedcontainers import SortedDict, SortedList
+from sortedcontainers import SortedDict
 import copy
 
 
@@ -733,7 +733,7 @@ def add_nodes_from(self, nbunch, sbunch=None, start=None, end=None, **attrs):
          [0 0 0 0 0 0 0]]
 
         """
-        
+
         if sbunch and (start or end):
             raise ValueError('Either sbunch or (start and end) can be specified.')
         elif sbunch:

dynetworkx/tests/inputoutput_text/impulsegraph_save_to_text_default_test.txt

@@ -1,4 +1,4 @@
+3 4 5.0 weight=1.0
 1 2 3.0
 2 3 4.0
-3 4 5.0 weight=1.0
 6 7 8.0 weight=2.0

dynetworkx/tests/inputoutput_text/impulsegraph_save_to_text_delimiter_test.txt

@@ -1,4 +1,4 @@
+3	4	5.0	weight=1.0
 1	2	3.0
 2	3	4.0
-3	4	5.0	weight=1.0
 6	7	8.0	weight=2.0

dynetworkx/tests/inputoutput_text/intervalgraph_save_to_text_default_test.txt

@@ -1,4 +1,4 @@
 1 2 3 4.0
+13 14 15 16.0 weight=2.0
 5 6 7 8.0
 9 10 11 12.0 weight=1.0
-13 14 15 16.0 weight=2.0

dynetworkx/tests/inputoutput_text/intervalgraph_save_to_text_delimiter_test.txt

@@ -1,4 +1,4 @@
 1	2	3	4.0
+13	14	15	16.0	weight=2.0
 5	6	7	8.0
 9	10	11	12.0	weight=1.0
-13	14	15	16.0	weight=2.0

dynetworkx/tests/test_impulsedigraph.py

@@ -1,5 +1,4 @@
 import dynetworkx as dnx
-import networkx as nx
 
 
 def test_impulsedigraph_init_default():

dynetworkx/tests/test_impulsegraph.py

@@ -1,8 +1,6 @@
 import dynetworkx as dnx
 import networkx as nx
-from networkx import from_numpy_matrix, from_numpy_array
 import os
-import numpy as np
 
 current_dir = os.path.dirname(__file__)
 

dynetworkx/tests/test_intervaldigraph.py

@@ -1,5 +1,4 @@
 import dynetworkx as dnx
-import networkx as nx
 
 
 def test_intervaldigraph_init():

dynetworkx/tests/test_snapshotgraph.py

@@ -1,6 +1,6 @@
 import dynetworkx as dnx
 import networkx as nx
-from networkx import from_numpy_matrix, from_numpy_array
+from networkx import from_numpy_array
 import os
 import numpy as np
 
@@ -320,7 +320,7 @@ def test_snapshotgraph_load_from_text_multi():
     desired.insert(from_numpy_array(
         np.array([[0, 1, 1, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0],
                   [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 1, 0]])), start=0, end=3)
-    desired.insert(from_numpy_matrix(
+    desired.insert(from_numpy_array(
         np.array([[0, 1, 1, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0],
                   [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 1, 0]])), start=3, end=10)
 

requirements.txt

@@ -1,3 +1,2 @@
--r requirements/default.txt
--r requirements/test.txt
--r requirements/dynetworkx.txt
+-r requirements/dynetworkx.txt
+-r requirements/test.txt

requirements/README.md

@@ -2,7 +2,7 @@
 
 ## Index
 
-- [`default.txt`](default.txt)
+- [`dynetworkx.txt`](dynetworkx.txt)
   Default requirements
 - [`extras.txt`](extras.txt)
   Optional requirements
@@ -16,12 +16,12 @@
 ### Installing requirements
 
 ```bash
-$ pip install -U -r requirements/default.txt
+$ pip install -U -r requirements/dynetworkx.txt
 ```
 
 ### Running the tests
 
 ```bash
-$ pip install -U -r requirements/default.txt
+$ pip install -U -r requirements/dynetworkx.txt
 $ pip install -U -r requirements/test.txt
 ```

requirements/dynetworkx.txt

@@ -1,5 +1,4 @@
 networkx>=2.0
 sortedcontainers
 numpy
-timeit
-sklearn
+scikit-learn

setup.py

@@ -1,22 +1,32 @@
+from os import path
+
 from setuptools import setup
 
+pwd = path.abspath(path.dirname(__file__))
+with open(path.join(pwd, "README.md"), "r", encoding="utf-8") as fh:
+    long_description = fh.read()
+
 setup(
-    name='DyNetworkX',
-    version='0.3.2',
-    author='Makan Arastuie',
-    author_email='[email protected]',
-    packages=['dynetworkx',
-              'dynetworkx.algorithms',
-              'dynetworkx.classes',
-              'dynetworkx.tests',
-              ],
-    license='Released under the 3-Clause BSD license.',
-    url='https://github.com/IdeasLabUT/dynetworkx',
-    description='DyNetworkX is a Python package for the study of dynamic network analysis.',
-    long_description=open('README.rst').read(),
-    install_requires=['networkx',
-                      'sortedcontainers',
-                      'numpy',
-                      ],
-    python_requires='>=3.4',
+    name="dynetworkx",
+    version="0.4.2",
+    author="Makan Arastuie",
+    author_email="[email protected]",
+    packages=[
+        "dynetworkx",
+        "dynetworkx.algorithms",
+        "dynetworkx.classes",
+        "dynetworkx.tests",
+    ],
+    license="Released under the 3-Clause BSD license.",
+    url="https://github.com/IdeasLabUT/dynetworkx",
+    description="DyNetworkX is a Python package for the study of dynamic network analysis.",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    install_requires=[
+        "networkx>=2.0",
+        "sortedcontainers",
+        "numpy",
+        "scikit-learn",
+    ],
+    python_requires=">=3.4",
 )