processing

`dsstools.processing`

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/.

`Layouter`

`create_layout(graph, seed=None, **kwargs)`

Create position dictionary according to set layout engine.

Parameters:

Name	Type	Description	Default
`seed`			`None`
`graph`	`DiGraph`	Graph object	required
`seed`	`int`	Set a default seed (default None)	`None`

Returns: Dictionary of node and positions.

`read_from_file(filename, **kwargs)`

Reads position from JSON file under filepath.

The following structure for the JSON is expected, where each key contains an array of length 2 containing the coordinates. Coordinates should be in the range [-1,1]:

{
    "domain1": [-0.1467271130230262, 0.25512246449304427],
    "domain2": [-0.3683594304205127, 0.34942480334119136],
}

This structure is generated through dsstools.Layouter().write_to_file().

Parameters:

Name	Type	Description	Default
`filename`	`Union[Path]`	Path to file to be read.	required
`graph`	`DiGraph`		required

Returns:

Type	Description
`dict`	Dictionary of nodes and positions.

`read_from_graph(graph, pos_name=('x', 'y'))`

Read positions from node attributes in the graph.

This is relevant when importing from Pajek or GEXF files where the positions are already set with another tool. Imported values are normalized onto [-1,1] in all directions.

Parameters:

Name	Type	Description	Default
`graph`	`Graph`	Graph object including the node attributes.	required
`pos_name`	`tuple`	Node attribute names to look for. These depend on the imported file format.	`('x', 'y')`

Returns:

Type	Description
	Dictionary of positions per Node.

`read_or_create_layout(filepath, graph, seed, overwrite=False, **kwargs)`

Read positions from file. If non-existant create pos and write to file.

Parameters:

Name	Type	Description	Default
`filename`	`Union[str, Path]`	Filename to read positions from	required
`graph`	`Graph`	Graph object to update	required
`overwrite`	`bool`	Overwrite existing file (default False)	`False`

Returns:

Type	Description
`dict`	Dictionary of positions per Node. Will return an empty dict if creation
`dict`	failed.

`SpringLayouter`

Bases: Layouter

`create_layout(graph, seed=None, pos=None, **kwargs)`

Create position dictionary according to set layout engine.

Parameters:

Name	Type	Description	Default
`graph`	`DiGraph`	Graph object	required
`seed`	`int`	Set a default seed (default None)	`None`
`pos`		Pre-populated positions	`None`

Returns:

Type	Description
`dict`	Dictionary of node and positions.

`calculate_betweenness_centrality(graph, **kwargs)`

Updates the nodes in the graph with betweenness centrality.

Parameters:

Name	Type	Description	Default
`graph`	`Graph`	nx.DiGraph The graph to calculate on.	required
`**kwargs`		All arguments passed onto nx.betweenness_centrality (see https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.centrality.betweenness_centrality.html#betweenness-centrality)	`{}`

Returns:

Type	Description
	Graph including the closeness centrality.

`calculate_closeness_centrality(graph, **kwargs)`

Updates the nodes in the graph with closeness centrality.

Parameters:

Name	Type	Description	Default
`graph`	`Graph`	nx.DiGraph The graph to calculate on.	required
`**kwargs`		All arguments passed onto nx.closeness_centrality (see https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.centrality.closeness_centrality.html#closeness-centrality)	`{}`

Returns:

Type	Description
	Graph including the betweenness centrality.