accumulate(iterable[, func]) |
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arbitrary_element(iterable) |
Returns an arbitrary element of iterable without removing it. |
consume(iterator) |
Consume the iterator entirely. |
create_degree_sequence(n[, sfunction, max_tries]) |
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cumulative_distribution(distribution) |
Return normalized cumulative distribution from discrete distribution. |
cuthill_mckee_ordering(G[, heuristic]) |
Generate an ordering (permutation) of the graph nodes to make a sparse matrix. |
default_opener(filename) |
Opens filename using system’s default program. |
dict_to_numpy_array(d[, mapping]) |
Convert a dictionary of dictionaries to a numpy array with optional mapping. |
dict_to_numpy_array1(d[, mapping]) |
Convert a dictionary of numbers to a 1d numpy array with optional mapping. |
dict_to_numpy_array2(d[, mapping]) |
Convert a dictionary of dictionaries to a 2d numpy array with optional mapping. |
discrete_sequence(n[, distribution, ...]) |
Return sample sequence of length n from a given discrete distribution or discrete cumulative distribution. |
flatten(obj[, result]) |
Return flattened version of (possibly nested) iterable object. |
generate_unique_node() |
Generate a unique node label. |
groups(many_to_one) |
Converts a many-to-one mapping into a one-to-many mapping. |
is_iterator(obj) |
Returns True if and only if the given object is an iterator object. |
is_list_of_ints(intlist) |
Return True if list is a list of ints. |
is_string_like(obj) |
Check if obj is string. |
iterable(obj) |
Return True if obj is iterable with a well-defined len(). |
make_str(x) |
Return the string representation of t. |
nodes_or_number(which_args) |
Decorator to allow number of nodes or container of nodes. |
not_implemented_for(*graph_types) |
Decorator to mark algorithms as not implemented |
open_file(path_arg[, mode]) |
Decorator to ensure clean opening and closing of files. |
pairwise(iterable[, cyclic]) |
s -> (s0, s1), (s1, s2), (s2, s3), ... |
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. |
random_weighted_sample(mapping, k) |
Return k items without replacement from a weighted sample. |
reverse_cuthill_mckee_ordering(G[, heuristic]) |
Generate an ordering (permutation) of the graph nodes to make a sparse matrix. |
reversed(*args, **kwds) |
A context manager for temporarily reversing a directed graph in place. |
tee |
tee(iterable, n=2) –> tuple of n independent iterators. |
to_tuple(x) |
Converts lists to tuples. |
uniform_sequence(n) |
Return sample sequence of length n from a uniform distribution. |
weighted_choice(mapping) |
Return a single element from a weighted sample. |
zipf_rv(alpha[, xmin, seed]) |
Return a random value chosen from the Zipf distribution. |
zipf_sequence(n[, alpha, xmin]) |
Return a sample sequence of length n from a Zipf distribution with exponent parameter alpha and minimum value xmin. |