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Utilities for networkx package
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These are not imported into the base networkx namespace but
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can be accessed, for example, as
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>>> networkx.utils.is_string_like('spam')
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__author__ = """Aric Hagberg (hagberg@lanl.gov)\nDan Schult(dschult@colgate.edu)"""
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# Aric Hagberg <hagberg@lanl.gov>
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# Dan Schult <dschult@colgate.edu>
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# Pieter Swart <swart@lanl.gov>
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# Distributed under the terms of the GNU Lesser General Public License
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# http://www.gnu.org/copyleft/lesser.html
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# All rights reserved.
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### some cookbook stuff
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# used in deciding whether something is a bunch of nodes, edges, etc.
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# see G.add_nodes and others in Graph Class in networkx/base.py
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def is_singleton(obj):
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""" Is string_like or not iterable. """
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"""Is string_like or not iterable."""
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return hasattr(obj,"capitalize") or not hasattr(obj,"__iter__")
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def is_string_like(obj): # from John Hunter, types-free version
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def flatten(obj, result=None):
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""" Return flattened version of (possibly nested) iterable obj. """
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""" Return flattened version of (possibly nested) iterable object. """
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if not iterable(obj) or is_string_like(obj):
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flatten(item, result)
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return obj.__class__(result)
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def iterable_to_string(obj, sep=''):
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Return string obtained by concatenating the string representation
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of each element of an iterable obj, with an optional internal string
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return sep.join([str(i) for i in obj])
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def is_list_of_ints( intlist ):
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""" Return True if list is a list of ints. """
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if not isinstance(intlist,list): return False
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# some helpers for choosing random sequences from distributions
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# uses pygsl: pygsl.sourceforge.org, but not all its functionality.
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# note: gsl's default number generator is the same as Python's
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def gsl_pareto_sequence(n,exponent=1.0,scale=1.0,seed=None):
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Return sample sequence of length n from a Pareto distribution.
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print "Import error: not able to import pygsl"
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random._inst = random.Random()
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seed=random.randint(1,2**32-1)
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return rng.pareto(exponent,scale,n)
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def gsl_powerlaw_sequence(n,exponent=2.0,scale=1.0,seed=None):
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Return sample sequence of length n from a power law distribution.
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print "Import error: not able to import pygsl"
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random._inst = random.Random()
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seed=random.randint(1,2**32-1)
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return rng.pareto(exponent-1,scale,n)
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def gsl_poisson_sequence(n,mu=1.0,seed=None):
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Return sample sequence of length n from a Poisson distribution.
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print "Import error: not able to import pygsl"
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random._inst = random.Random()
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seed=random.randint(1,2**32-1)
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return rng.poisson(mu,n)
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def gsl_uniform_sequence(n,seed=None):
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Return sample sequence of length n from a uniform distribution.
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print "Import error: not able to import pygsl"
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random._inst = random.Random()
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seed=random.randint(1,2**32-1)
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return rng.uniform(n)
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# The same helpers for choosing random sequences from distributions
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# uses Python's random module
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# http://www.python.org/doc/current/lib/module-random.html
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# choose from CDF
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seq=[bisect.bisect_left(cdf,s)-1 for s in inputseq]
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"""Union-find data structure.
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Each unionFind instance X maintains a family of disjoint sets of
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hashable objects, supporting the following two methods:
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- X[item] returns a name for the set containing the given item.
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Each set is named by an arbitrarily-chosen one of its members; as
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long as the set remains unchanged it will keep the same name. If
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the item is not yet part of a set in X, a new singleton set is
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- X.union(item1, item2, ...) merges the sets containing each item
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into a single larger set. If any item is not yet part of a set
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in X, it is added to X as one of the members of the merged set.
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Union-find data structure. Based on Josiah Carlson's code,
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http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/215912
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with significant additional changes by D. Eppstein.
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http://www.ics.uci.edu/~eppstein/PADS/UnionFind.py
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"""Create a new empty union-find structure."""
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def __getitem__(self, object):
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"""Find and return the name of the set containing the object."""
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# check for previously unknown object
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if object not in self.parents:
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self.parents[object] = object
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self.weights[object] = 1
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# find path of objects leading to the root
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root = self.parents[object]
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while root != path[-1]:
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root = self.parents[root]
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# compress the path and return
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for ancestor in path:
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self.parents[ancestor] = root
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"""Iterate through all items ever found or unioned by this structure."""
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return iter(self.parents)
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def union(self, *objects):
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"""Find the sets containing the objects and merge them all."""
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roots = [self[x] for x in objects]
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heaviest = max([(self.weights[r],r) for r in roots])[1]
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self.weights[heaviest] += self.weights[r]
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self.parents[r] = heaviest
added
removed
networkx/utils.py
