networkit.viz

class networkit.viz.GraphLayoutAlgorithm

Bases: object

Abstract base class for graph drawing algorithms.

getCoordinates()

Computes approximation (in parallel) of the Spanning Edge Centrality.

Returns

List of coordinates for each node.

Return type

list(tuple(float, float))

numEdgeCrossings()

Computes approximation (in parallel) of the Spanning Edge Centrality.

Returns

Number of edge crossings.

Return type

int

run()

Executes the graph layout algorithm.

Returns

self

Return type

networkit.viz.GraphLayoutAlgorithm

writeGraphToGML(path)

Writes the graph and its layout to a .gml file at the specified path.

Parameters

path (str) – Path where the graph file should be created.

writeKinemage(path)

Writes the graph and its layout to a file at the specified path.

Parameters

path (str) – Path where the graph file should be created.

class networkit.viz.MaxentStress(G, dim, k, coordinates=list(), tolerance=1e-5, linearSolverType=networkit.viz.LinearSolverType.LAMG, fastComputation=False, graphDistance=networkit.viz.GraphDistance.EDGE_WEIGHT)

Bases: networkit.viz.GraphLayoutAlgorithm

Implementation of MaxentStress by Gansner et al. using a Laplacian system solver. @see Gansner, Emden R., Yifan Hu, and Steve North. “A maxent-stress model for graph layout.” Visualization and Computer Graphics, IEEE Transactions on 19, no. 6 (2013): 927-940.

Parameter graphDistance can be one of the following:

• networkit.viz.GraphDistance.EdgeWeight

• networkit.viz.GraphDistance.AlgebraicDistance

Parameter linearSolverType can be one of the following:

• networkit.viz.LinearSolverType.LAMG

• networkit.viz.LinearSolverType.CONJUGATE_GRADIENT_IDENTITY_PRECONDITIONER

• networkit.viz.LinearSolverType.CONJUGATE_GRADIENT_DIAGONAL_PRECONDITIONER

Parameters

• G (networkit.Graph) – The (connected) graph to be handled.

• dim (int) – Number of dimensions.

• k (int) – Node distance to take into account for computation. The higher k, the longer computation takes to complete.

• coordinates (list(tuple(float, float)), optional) – Fixed coordinates. Default: list()

• tolerance (float, optional) – The tolerance of the solver. Default: 1e-5

• linearSolverType (networkit.viz.LinearSolverType, optional) – The type of linear solver. Default: networkit.viz.LinearSolverType.LAMG

• fastComputation (bool, optional) – Decides whether or not slightly faster computation should be employed, leading to slightly worse results. Default: False

• graphDistance (networkit.viz.GraphDistance, optional) – Decides what type of graph distance should be utilised. Default: networkit.community.GraphDistance.EdgeWeight

computeScalingFactor()

Computes a scalar s s.t. \(\sum_{u,v \in V} w_{uv} (s ||x_u - x_v|| - d_{uv}||)^2\) is minimized.

fullStressMeasure()

Computes the full stress measure of the computed layout with run().

getApproxEntropyTerm()

Returns entropy term value.

Returns

The parameter value.

Return type

float

getRhs()

Returns rhs value.

Returns

The parameter value.

Return type

float

getSolveTime()

Returns solve time value.

Returns

The parameter value.

Return type

float

ldme()

Computes the ldme.

maxentMeasure()

Computes the maxent stress measure for the computed layout with run().

meanDistanceError()

Computes mean distance error.

scaleLayout()

Scale the layout computed by run() by a scalar s to minimize \(\sum_{u,v \in V} w_{uv} (s ||x_u - x_v|| - d_{uv}||)^2\).

setAlpha(alpha)

Set parameter alpha.

Parameters

alpha (float) – New parameter value.

setAlphaReduction(alphaReduction)

Set parameter alphaReduction.

Parameters

alphaReduction (float) – New parameter value.

setConvergenceThreshold(convThreshold)

Set parameter convThreshold.

Parameters

convThreshold (float) – New parameter value.

setFinalAlpha(finalAlpha)

Set parameter finalAlpha.

Parameters

finalAlpha (float) – New parameter value.

setQ(q)

Set parameter q.

Parameters

q (float) – New parameter value.

class networkit.viz.PivotMDS(dim, numberOfPivots)

Bases: networkit.viz.GraphLayoutAlgorithm

Implementation of PivotMDS proposed by Brandes and Pich.

Parameters

• G (networkit.Graph) – The graph to be handled by the algorithm.

• dim (int) – Number of dimensions.

• numberOfPivots (int) – Number of pivots for the algorithm.