Default attraction parameter.
Default repulsion parameter.
Default edge weight increment parameter.
Default maximum number of iterations.
Default initial step size.
Default minimum step size.
Default step size reduction.
Default required number of quality value improvements.
Attraction parameter.
Repulsion parameter.
Edge weight increment parameter.
Maximum number of iterations.
Initial step size.
Minimum step size.
Step size reduction.
Required number of quality value improvements.
Random number generator.
Initializes a VOS layout algorithm with a specified attraction parameter, repulsion parameter, and edge weight increment parameter.
Attraction parameter
Repulsion parameter
Edge weight increment parameter
Returns the attraction parameter.
Attraction parameter
Returns the repulsion parameter.
Repulsion parameter
Returns the edge weight increment parameter.
Edge weight increment parameter
Sets the attraction parameter.
Attraction parameter
Sets the repulsion parameter.
Repulsion parameter
Sets the edge weight increment parameter.
Edge weight increment parameter
Calculates the quality of a layout using the VOS quality function.
The VOS quality function is given by
1 / attraction * sum(a[i][j] * d(x[i], x[j]) ^
attraction) - 1 / repulsion * sum(d(x[i], x[j]) ^
repulsion),
where a[i][j] is the weight of the edge between nodes i and j and
x[i] = (x[i][1], x[i][2]) are the coordinates of node i. The function
d(x[i], x[j]) is the Euclidean distance between nodes i and j. The
sum is taken over all pairs of nodes i and j with j < i. The
attraction parameter must be greater than the repulsion parameter. The
lower the value of the VOS quality function, the higher the quality of the
layout.
Quality of the layout
Initializes a gradient descent VOS layout algorithm.
Random number generator
Initializes a gradient descent VOS layout algorithm for a specified attraction parameter, repulsion parameter, and edge weight increment parameter.
Attraction parameter
Repulsion parameter
Edge weight increment parameter
Random number generator
Initializes a gradient descent VOS layout algorithm for a specified attraction parameter, repulsion parameter, edge weight increment parameter, maximum number of iterations, initial step size, minimum step size, step size reduction, and required number of quality value improvements.
Attraction parameter
Repulsion parameter
Edge weight increment parameter
Maximum number of iterations
Initial step size
Minimum step size
Step size reduction
Required number of quality value improvements
Random number generator
Clones the algorithm.
Cloned algorithm
Returns the maximum number of iterations.
Maximum number of iterations
Returns the initial step size.
Initial step size
Returns the minimum step size.
Minimum step size
Returns the step size reduction.
Step size reduction
Returns the required number of quality value improvements.
Required number of quality value improvements
Sets the maximum number of iterations.
Maximum number of iterations
Sets the initial step size.
Initial step size
Sets the minimum step size.
Minimum step size
Sets the step size reduction.
Step size reduction
Sets the required number of quality value improvements.
Required number of quality value improvements
Constructs a gradient descent VOS layout algorithm.
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Gradient descent VOS layout algorithm.