1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
|
"""
Miscellaneous Helpers for NetworkX.
These are not imported into the base networkx namespace but
can be accessed, for example, as
>>> import networkx
>>> networkx.utils.is_string_like('spam')
True
"""
# Copyright (C) 2004-2015 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
import collections
import sys
import uuid
from itertools import tee
# itertools.accumulate is only available on Python 3.2 or later.
#
# Once support for Python versions less than 3.2 is dropped, this code should
# be removed.
try:
from itertools import accumulate
except ImportError:
import operator
# The code for this function is from the Python 3.5 documentation,
# distributed under the PSF license:
# <https://docs.python.org/3.5/library/itertools.html#itertools.accumulate>
def accumulate(iterable, func=operator.add):
it = iter(iterable)
try:
total = next(it)
except StopIteration:
return
yield total
for element in it:
total = func(total, element)
yield total
__author__ = '\n'.join(['Aric Hagberg (hagberg@lanl.gov)',
'Dan Schult(dschult@colgate.edu)',
'Ben Edwards(bedwards@cs.unm.edu)'])
### some cookbook stuff
# used in deciding whether something is a bunch of nodes, edges, etc.
# see G.add_nodes and others in Graph Class in networkx/base.py
def is_string_like(obj): # from John Hunter, types-free version
"""Check if obj is string."""
try:
obj + ''
except (TypeError, ValueError):
return False
return True
def iterable(obj):
""" Return True if obj is iterable with a well-defined len()."""
if hasattr(obj,"__iter__"): return True
try:
len(obj)
except:
return False
return True
def flatten(obj, result=None):
""" Return flattened version of (possibly nested) iterable object. """
if not iterable(obj) or is_string_like(obj):
return obj
if result is None:
result = []
for item in obj:
if not iterable(item) or is_string_like(item):
result.append(item)
else:
flatten(item, result)
return obj.__class__(result)
def is_list_of_ints( intlist ):
""" Return True if list is a list of ints. """
if not isinstance(intlist,list): return False
for i in intlist:
if not isinstance(i,int): return False
return True
PY2 = sys.version_info[0] == 2
if PY2:
def make_str(x):
"""Return the string representation of t."""
if isinstance(x, unicode):
return x
else:
# Note, this will not work unless x is ascii-encoded.
# That is good, since we should be working with unicode anyway.
# Essentially, unless we are reading a file, we demand that users
# convert any encoded strings to unicode before using the library.
#
# Also, the str() is necessary to convert integers, etc.
# unicode(3) works, but unicode(3, 'unicode-escape') wants a buffer.
#
return unicode(str(x), 'unicode-escape')
else:
def make_str(x):
"""Return the string representation of t."""
return str(x)
def generate_unique_node():
""" Generate a unique node label."""
return str(uuid.uuid1())
def default_opener(filename):
"""Opens `filename` using system's default program.
Parameters
----------
filename : str
The path of the file to be opened.
"""
from subprocess import call
cmds = {'darwin': ['open'],
'linux2': ['xdg-open'],
'win32': ['cmd.exe', '/C', 'start', '']}
cmd = cmds[sys.platform] + [filename]
call(cmd)
def dict_to_numpy_array(d,mapping=None):
"""Convert a dictionary of dictionaries to a numpy array
with optional mapping."""
try:
return dict_to_numpy_array2(d, mapping)
except (AttributeError, TypeError):
# AttributeError is when no mapping was provided and v.keys() fails.
# TypeError is when a mapping was provided and d[k1][k2] fails.
return dict_to_numpy_array1(d,mapping)
def dict_to_numpy_array2(d,mapping=None):
"""Convert a dictionary of dictionaries to a 2d numpy array
with optional mapping.
"""
import numpy
if mapping is None:
s=set(d.keys())
for k,v in d.items():
s.update(v.keys())
mapping=dict(zip(s,range(len(s))))
n=len(mapping)
a = numpy.zeros((n, n))
for k1, i in mapping.items():
for k2, j in mapping.items():
try:
a[i,j]=d[k1][k2]
except KeyError:
pass
return a
def dict_to_numpy_array1(d,mapping=None):
"""Convert a dictionary of numbers to a 1d numpy array
with optional mapping.
"""
import numpy
if mapping is None:
s = set(d.keys())
mapping = dict(zip(s,range(len(s))))
n = len(mapping)
a = numpy.zeros(n)
for k1,i in mapping.items():
i = mapping[k1]
a[i] = d[k1]
return a
def is_iterator(obj):
"""Returns ``True`` if and only if the given object is an iterator
object.
"""
has_next_attr = hasattr(obj, '__next__') or hasattr(obj, 'next')
return iter(obj) is obj and has_next_attr
def arbitrary_element(iterable):
"""Returns an arbitrary element of ``iterable`` without removing it.
This is most useful for "peeking" at an arbitrary element of a set,
but can be used for any list, dictionary, etc., as well::
>>> arbitrary_element({3, 2, 1})
1
>>> arbitrary_element('hello')
'h'
This function raises a :exc:`ValueError` if ``iterable`` is an
iterator (because the current implementation of this function would
consume an element from the iterator)::
>>> iterator = iter([1, 2, 3])
>>> arbitrary_element(iterator)
Traceback (most recent call last):
...
ValueError: cannot return an arbitrary item from an iterator
"""
if is_iterator(iterable):
raise ValueError('cannot return an arbitrary item from an iterator')
# Another possible implementation is `for x in iterable: return x`.
return next(iter(iterable))
# Recipe from the itertools documentation.
def consume(iterator):
"Consume the iterator entirely."
# Feed the entire iterator into a zero-length deque.
collections.deque(iterator, maxlen=0)
# Recipe from the itertools documentation.
def pairwise(iterable):
"s -> (s0, s1), (s1, s2), (s2, s3), ..."
a, b = tee(iterable)
next(b, None)
return zip(a, b)
|
