Warning
This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.
Utilities¶
Helper Functions¶
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
| is_string_like(obj) | Check if obj is string. |
| flatten(obj[, result]) | Return flattened version of (possibly nested) iterable object. |
| iterable(obj) | Return True if obj is iterable with a well-defined len(). |
| is_list_of_ints(intlist) | Return True if list is a list of ints. |
| make_str(x) | Return the string representation of t. |
| cumulative_sum(numbers) | Yield cumulative sum of numbers. |
| generate_unique_node() | Generate a unique node label. |
| default_opener(filename) | Opens \(filename\) using system’s default program. |
Data Structures and Algorithms¶
Union-find data structure.
| UnionFind.union(*objects) | Find the sets containing the objects and merge them all. |
Random Sequence Generators¶
Utilities for generating random numbers, random sequences, and random selections.
| create_degree_sequence(n[, sfunction, max_tries]) | |
| pareto_sequence(n[, exponent]) | Return sample sequence of length n from a Pareto distribution. |
| powerlaw_sequence(n[, exponent]) | Return sample sequence of length n from a power law distribution. |
| uniform_sequence(n) | Return sample sequence of length n from a uniform distribution. |
| cumulative_distribution(distribution) | Return normalized cumulative distribution from discrete distribution. |
| discrete_sequence(n[, distribution, ...]) | Return sample sequence of length n from a given discrete distribution or discrete cumulative distribution. |
| zipf_sequence(n[, alpha, xmin]) | Return a sample sequence of length n from a Zipf distribution with |
| zipf_rv(alpha[, xmin, seed]) | Return a random value chosen from the Zipf distribution. |
| random_weighted_sample(mapping, k) | Return k items without replacement from a weighted sample. |
| weighted_choice(mapping) | Return a single element from a weighted sample. |
Cuthill-Mckee Ordering¶
Cuthill-McKee ordering of graph nodes to produce sparse matrices
| cuthill_mckee_ordering(G[, heuristic]) | Generate an ordering (permutation) of the graph nodes to make a sparse matrix. |
| reverse_cuthill_mckee_ordering(G[, heuristic]) | Generate an ordering (permutation) of the graph nodes to make a sparse matrix. |