python-igraph API reference

List of all classes, functions and methods in python-igraph

module documentation

Undocumented

Function	`_indegree`	Returns the in-degrees in a list.
Function	`_outdegree`	Returns the out-degrees in a list.
Function	`_degree_distribution`	Calculates the degree distribution of the graph.
Function	`_pagerank`	Calculates the PageRank values of a graph.

def _indegree(graph, *args, **kwds):

Returns the in-degrees in a list.

See degree for possible arguments.

def _outdegree(graph, *args, **kwds):

Returns the out-degrees in a list.

See degree for possible arguments.

def _degree_distribution(graph, bin_width=1, *args, **kwds):

Calculates the degree distribution of the graph.

Unknown keyword arguments are directly passed to degree().

Parameters	graph	Undocumented
	bin_width	the bin width of the histogram
	args	Undocumented
	kwds	Undocumented
Returns	a histogram representing the degree distribution of the graph.

def _pagerank(graph, vertices=None, directed=True, damping=0.85, weights=None, arpack_options=None, implementation='prpack', niter=1000, eps=0.001):

Calculates the PageRank values of a graph.

Parameters	graph	Undocumented
	vertices	the indices of the vertices being queried. `None` means all of the vertices.
	directed	whether to consider directed paths.
	damping	the damping factor. 1-damping is the PageRank value for nodes with no incoming links. It is also the probability of resetting the random walk to a uniform distribution in each step.
	weights	edge weights to be used. Can be a sequence or iterable or even an edge attribute name.
	arpack_options	an `ARPACKOptions` object used to fine-tune the ARPACK eigenvector calculation. If omitted, the module-level variable called `arpack_options` is used. This argument is ignored if not the ARPACK implementation is used, see the implementation argument.
	implementation	which implementation to use to solve the PageRank eigenproblem. Possible values are: `"prpack"`: use the PRPACK library. This is a new implementation in igraph 0.7 `"arpack"`: use the ARPACK library. This implementation was used from version 0.5, until version 0.7. `"power"`: use a simple power method. This is the implementation that was used before igraph version 0.5.
	niter	The number of iterations to use in the power method implementation. It is ignored in the other implementations
	eps	The power method implementation will consider the calculation as complete if the difference of PageRank values between iterations change less than this value for every node. It is ignored by the other implementations.
Returns	a list with the Google PageRank values of the specified vertices.

API Documentation for python-igraph, generated by pydoctor 21.2.2.

igraph.structural