calculateDescriptors: Generalized descriptor calculation

Description Usage Arguments Details Value Author(s) Examples

View source: R/calculateDescriptors.R

Description

The method calculates multiple descriptors for a list of graphs.

Usage

1

Arguments

graphs

either a list of or a single graphNEL object.

...

descriptors to calculate and arguments to pass, see ‘Details’.

labels

whether or not the columns of the resulting data frame should be named using the getLabels() method.

log

whether or not informative messages about the progress of the calculation should be printed

Details

calculateDescriptors() calls each function specified in ‘...’ for every graph in the given list and creates a data frame containing the calculated data. You can specify the functions either as strings (such as “totalAdjacency”) or using the numbers from the following table (e.g., 2001). For convenience, the multiples of 1000 denote entire groups of descriptors.

1000 --- all of 1xxx
1001 wiener
1002 harary
1003 balabanJ
1004 meanDistanceDeviation
1005 compactness
1006 productOfRowSums
1007 hyperDistancePathIndex
1008 dobrynin
2000 --- all of 2xxx
2001 totalAdjacency
2002 zagreb1
2003 zagreb2
2004 modifiedZagreb
2005 augmentedZagreb
2006 variableZagreb
2007 randic
2008 complexityIndexB
2009 normalizedEdgeComplexity
2010 atomBondConnectivity
2011 geometricArithmetic1
2012 geometricArithmetic2
2013 geometricArithmetic3
2014 narumiKatayama
3000 --- all of 3xxx
3001 topologicalInfoContent
3002 bonchev1
3003 bonchev2
3004 bertz
3005 radialCentric
3006 vertexDegree
3007 balabanlike1
3008 balabanlike2
3009 graphVertexComplexity
3010 informationBondIndex
3011 edgeEqualityMIC
3012 edgeMagnitudeMIC
3013 symmetryIndex
3014 bonchev3
3015 graphDistanceComplexity
3016 distanceDegreeMIC
3017 distanceDegreeEquality
3018 distanceDegreeCompactness
3019 informationLayerIndex
4000 --- all of 4xxx
4001 mediumArticulation
4002 efficiency
4003 graphIndexComplexity
4004 offdiagonal
4005 spanningTreeSensitivity
4006 distanceDegreeCentric
4007 distanceCodeCentric
5000 --- all of 5xxx
5001 infoTheoreticGCM: vertcent, exp
5002 infoTheoreticGCM: vertcent, lin
5003 infoTheoreticGCM: sphere, exp
5004 infoTheoreticGCM: sphere, lin
5005 infoTheoreticGCM: pathlength, exp
5006 infoTheoreticGCM: pathlength, lin
5007 infoTheoreticGCM: degree, exp
5008 infoTheoreticGCM: degree, lin
5009 infoTheoreticLabeledV1: exp
5010 infoTheoreticLabeledV1: lin
5011 infoTheoreticLabeledV2
5012 infoTheoreticLabeledE: exp
5013 infoTheoreticLabeledE: lin
6000 --- all of 6xxx
6001 eigenvalueBased: adjacencyMatrix, s=1
6002 eigenvalueBased: adjacencyMatrix, s=2
6003 eigenvalueBased: laplaceMatrix, s=1
6004 eigenvalueBased: laplaceMatrix, s=2
6005 eigenvalueBased: distanceMatrix, s=1
6006 eigenvalueBased: distanceMatrix, s=2
6007 eigenvalueBased: distancePathMatrix, s=1
6008 eigenvalueBased: distancePathMatrix, s=2
6009 eigenvalueBased: augmentedMatrix, s=1
6010 eigenvalueBased: augmentedMatrix, s=2
6011 eigenvalueBased: extendedAdjacencyMatrix, s=1
6012 eigenvalueBased: extendedAdjacencyMatrix, s=2
6013 eigenvalueBased: vertConnectMatrix, s=1
6014 eigenvalueBased: vertConnectMatrix, s=2
6015 eigenvalueBased: randomWalkMatrix, s=1
6016 eigenvalueBased: randomWalkMatrix, s=2
6017 eigenvalueBased: weightStrucFuncMatrix_lin, s=1
6018 eigenvalueBased: weightStrucFuncMatrix_lin, s=2
6019 eigenvalueBased: weightStrucFuncMatrix_exp, s=1
6020 eigenvalueBased: weightStrucFuncMatrix_exp, s=2
6021 energy
6022 laplacianEnergy
6023 estrada
6024 laplacianEstrada
6025 spectralRadius
7000 --- all of 7xxx
7001 oneEdgeDeletedSubgraphComplexity
7002 twoEdgesDeletedSubgraphComplexity
7003 globalClusteringCoeff
8000 --- all of 8xxx
8001 connectivityID
8002 minConnectivityID
8003 primeID
8004 bondOrderID
8005 balabanID
8006 minBalabanID
8007 weightedID
8008 huXuID

The arguments to these functions, such as the distance matrix or the list of vertex degrees, will be automatically supplied and reused. After each function (or group of functions), regardless of whether it was referred to by name or by its assigned number, you may optionally pass extra arguments as a list, but note that this will not override the calculated arguments. If you wish to pass the same extra arguments to multiple functions, you can concatenate the latter to a vector.

When functions are given by name, an “@NAME” suffix can be used to give the column a different name in the output data frame. This is needed when you want to calculate a descriptor more than once with varying arguments.

If log is TRUE, a progress message is printed to the standard output connection for each graph in the list.

Value

A data frame where rows and columns represent the input graphs and the desired descriptors, respectively. The rows will be named according to the graph list; the column names are the names of the called functions if labels is FALSE, otherwise the label expressions as returned by getLabels() (and found in the vignette).

Author(s)

Michael Schutte

Examples

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library(RBGL)
set.seed(123)
g <- randomGraph(1:8, 1:5, 0.36, weights=FALSE)

calculateDescriptors(g, 1000, 2002, 2003)

calculateDescriptors(g, "randic", "offdiagonal", 7000, labels=TRUE)

# these will give the same results (although named differently):
calculateDescriptors(g, c(6011, 6013), list(s=3))
calculateDescriptors(g,
  "eigenvalueBased@ea", list(matrix_function="extendedAdjacencyMatrix", s=3),
  "eigenvalueBased@vc", list(matrix_function="vertConnectMatrix", s=3))

QuACN documentation built on May 2, 2019, 5:46 p.m.