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(t) | 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  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]) | Attempt to create a valid degree sequence of length n using specified function sfunction(n,**kwds). |
| 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. |