plotBasicNetwork.Rdtakes an object output from renderSurfaceFunction and a list of centroids and plots the centroid network over the rendering object
plotBasicNetwork( centroids, brain, weights = NA, edgecolors = -1, backgroundColor = "white", nodecolors = "blue", nodetype = "s", edgeContrast = c(0, 1), quantileTransformWeights = FALSE, lwd = 2, minRadius = 0, maxRadius = 3, radius = NA, showOnlyConnectedNodes = TRUE )
| centroids | input matrix of size N 3D points ( in rows ) by 3 ( in columns ), for N nodes. |
|---|---|
| brain | input rendering object which is output of renderSurfaceFunction. or a function derived from renderSurfaceFunction. |
| weights | edge weights, a symmetric matrix of size N. Weights should be non-negative. |
| edgecolors | a color(map) for edges. If a color map function, weights will be transformed
to the range [0,1], which is compatible with functions returned by |
| backgroundColor | background color. |
| nodecolors | a color or color vector for nodes. |
| nodetype | sphere or other node type supported by RGL. |
| edgeContrast | a vector of length 2, specifying the contrast range for edge colors.
Weights are normalized to the range [0,1].
The normalized weights can be rescaled with this parameter, eg |
| quantileTransformWeights | quantile transform the weights. |
| lwd | line width for drawing edges. |
| minRadius | minimum node radius. Ignored if the radius is specified explicitly with |
| maxRadius | maximum node radius. The node radius between |
| radius | a constant radius or vector of length nrow(centroids). If not specified, node radius is determined by the sum of edge weights connected to the node. |
| showOnlyConnectedNodes | boolean, if |
None
If edgecolors is not specified, a heat-like color palette is used. Weights
can be quantile transformed or clipped at a given quantile in order to improve
contrast.
If weights are not specified, only the nodes are plotted.
Avants BB, Duda JT, Cook PA
if (FALSE) { # more complete example mnit<-getANTsRData("mni") mnit<-antsImageRead(mnit) mnia<-getANTsRData("mnia") mnia<-antsImageRead(mnia) mnit<-thresholdImage( mnit, 1, max(mnit) ) mnit<-iMath(mnit,"FillHoles") mnit = thresholdImage(mnit, 1, 2 ) cnt<-getCentroids( mnia, clustparam = 0 ) aalcnt<-cnt[1:90,1:3] brain<-renderSurfaceFunction( surfimg =list( mnit ) , alphasurf=0.1 ,smoothsval = 1.5 ) testweights<-matrix( rep( 0, 90*90 ) ,nrow=90) testweights[31,37]<-1 # ant cingulate to hipp testweights[31,36]<-2 # ant cingulate to post cingulate testweights[11,65]<-3 # broca to angular plotBasicNetwork( centroids = aalcnt , brain , weights=testweights, edgecolors = "red" ) id<-rgl::par3d('userMatrix') rid<-rotate3d( id , -pi/2, 1, 0, 0 ) rid2<-rotate3d( id , pi/2, 0, 0, 1 ) rid3<-rotate3d( id , -pi/2, 0, 0, 1 ) rgl::par3d(userMatrix = id ) dd<-make3ViewPNG( rid, id, rid2, paste('network1',sep='') ) rgl::par3d(userMatrix = id ) # another example mni<-getANTsRData("mni") mni<-antsImageRead(mni) mnit<-thresholdImage( mni, 1, max(mni) ) mnit<-iMath(mnit,"FillHoles") mniseg = kmeansSegmentation( mni, 3 )$segmentation wmbkgd = thresholdImage( mniseg, 3, 3 ) %>% iMath( "GetLargestComponent" ) %>% iMath( "FillHoles" ) wmbkgd = smoothImage( iMath( wmbkgd, "MD", 1 ), 2.0 ) brain<-renderSurfaceFunction( surfimg =list( wmbkgd ) , alphasurf=0.8 ,smoothsval = 1.0 ) data( powers_areal_mni_itk ) coords = powers_areal_mni_itk[,1:3] id<-rgl::par3d('userMatrix') rid<-rotate3d( id , -pi/2, 1, 0, 0 ) rid2<-rotate3d( id , pi/2, 0, 0, 1 ) rid3<-rotate3d( id , -pi/2, 0, 0, 1 ) rgl::par3d(userMatrix = id ) handMat2 = t( matrix( c(-0.9998656511 , 0.01626961, 0.00198165 , 0 ,-0.0163816363, -0.99584705 ,-0.08955579 , 0, 0.0005163439, -0.08957647, 0.99597979 , 0, 0.0000000000, 0.00000000, 0.00000000 , 1), ncol = 4) ) loccolor = as.character( powers_areal_mni_itk$Color ) loccolor[ loccolor == "Peach" ] = "sienna1" loccolor[ loccolor == "Cyan" ] = "cyan" loccolor[ loccolor == "Orange" ] = "orange" loccolor[ loccolor == "Purple" ] = "darkorchid1" loccolor[ loccolor == "Pink" ] = "deeppink" loccolor[ loccolor == "Red" ] = "red" loccolor[ loccolor == "Gray" ] = "gray74" loccolor[ loccolor == "Teal" ] = "turquoise4" loccolor[ loccolor == "Blue" ] = "blue" loccolor[ loccolor == "Yellow" ] = "yellow" loccolor[ loccolor == "Black" ] = "black" loccolor[ loccolor == "Brown" ] = "brown" loccolor[ loccolor == "Pale blue" ] = "steelblue1" loccolor[ loccolor == "Green" ] = "green" tt = plotBasicNetwork( centroids = coords, brain, nodecolors = loccolor, radius=3 ) dd<-make3ViewPNG( handMat2, id, rid2, tempfile( fileext='.png' ) ) rgl::par3d(userMatrix = id ) }