From 3e37d31d228ae8f8d80239ef40766304d04ac27b Mon Sep 17 00:00:00 2001
From: noah <noah@theschricks.com>
Date: Sat, 30 Apr 2022 16:03:21 -0500
Subject: [PATCH] Graph laplacian and reursive newman modularity

---
 Schrick-Noah_CG-Analysis.R | 81 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 81 insertions(+)

diff --git a/Schrick-Noah_CG-Analysis.R b/Schrick-Noah_CG-Analysis.R
index c6dc7f3..a4dbbd2 100644
--- a/Schrick-Noah_CG-Analysis.R
+++ b/Schrick-Noah_CG-Analysis.R
@@ -11,8 +11,24 @@ setwd(dirname(rstudioapi::getActiveDocumentContext()$path))
 source("./CG_Files/manual_import.R")
 
 car <- import_networks(1)
+car.netname <- "Vehicle Maintenance"
 hipaa <- import_networks(2)
+hipaa.netname <- "HIPAA Compliance"
 pci <- import_networks(3)
+pci.netname <- "PCI Compliance"
+
+# Get basic network attributes
+car.adj <- get.adjacency(car)
+car.deg <- rowSums(as.matrix(car.adj)) # degree
+car.n <- length(V(car))
+
+hipaa.adj <- get.adjacency(hipaa)
+hipaa.deg <- rowSums(as.matrix(hipaa.adj)) # degree
+hipaa.n <- length(V(hipaa))
+
+pci.adj <- get.adjacency(pci)
+pci.deg <- rowSums(as.matrix(pci.adj)) # degree
+pci.n <- length(V(pci))
 
 ################################ Centralities ################################
 source("centralities.R")
@@ -29,8 +45,73 @@ pci.pr <- page.rank(pci)
 
 ### K-path
 car.kpe <- geokpath(car, V(car), "out")
+hipaa.kpe <- geokpath(hipaa, V(hipaa), "out")
+pci.kpe <- geokpath(pci, V(pci), "out")
 
 
+############## Clustering
+source("self_newman_mod.R")
+
+### Laplacian
+car.Lap <- diag(car.deg) - car.adj # L = D-A
+hipaa.Lap <- diag(hipaa.deg) - hipaa.adj
+pci.Lap <- diag(pci.deg) - pci.adj
+
+# get eigvals and vecs
+car.eigs <- eigen(car.Lap)$vectors[,car.n-1]
+car.eig_val <- eigen(car.Lap)$values[car.n-1]
+names(car.eigs) <- names(V(car))
+car.l_clusters <- ifelse(car.eigs>0,1,-1)
+
+hipaa.eigs <- eigen(hipaa.Lap)$vectors[,hipaa.n-1]
+hipaa.eig_val <- eigen(hipaa.Lap)$values[hipaa.n-1]
+names(hipaa.eigs) <- names(V(hipaa))
+hipaa.l_clusters <- ifelse(hipaa.eigs>0,1,-1)
+
+pci.eigs <- eigen(pci.Lap)$vectors[,pci.n-1]
+pci.eig_val <- eigen(pci.Lap)$values[pci.n-1]
+names(pci.eigs) <- names(V(pci))
+pci.l_clusters <- ifelse(pci.eigs>0,1,-1)
+
+### Recursive Newmann
+car.modularity <- fastgreedy.community(car,merges=TRUE, modularity=TRUE, membership=TRUE)
+car.membership.ids <- unique(car.modularity$membership)
+cat(paste('Number of detected communities in the car network =',length(car.membership.ids)))
+cat("community sizes: ")
+sapply(membership.ids,function(x) {sum(x==car.modularity$membership)})
+cat("modularity: ")
+max(car.modularity$modularity)
+V(car)$color=car.modularity$membership
+plot(car,vertex.size=10,
+     vertex.label=NA,vertex.color=V(car)$color,
+     main=paste(car.netname, " Recursive Newman Modularity"))
+
+
+hipaa.modularity <- fastgreedy.community(hipaa,merges=TRUE, modularity=TRUE, membership=TRUE)
+hipaa.membership.ids <- unique(hipaa.modularity$membership)
+cat(paste('Number of detected communities in the HIPAA network =',length(hipaa.membership.ids)))
+cat("community sizes: ")
+sapply(membership.ids,function(x) {sum(x==hipaa.modularity$membership)})
+cat("modularity: ")
+max(hipaa.modularity$modularity)
+V(hipaa)$color=hipaa.modularity$membership
+plot(hipaa,vertex.size=10,
+     vertex.label=NA,vertex.color=V(hipaa)$color,
+     main=paste(hipaa.netname, " Recursive Newman Modularity"))
+
+
+pci.modularity <- fastgreedy.community(pci,merges=TRUE, modularity=TRUE, membership=TRUE)
+pci.membership.ids <- unique(pci.modularity$membership)
+cat(paste('Number of detected communities in the PCI network =',length(pci.membership.ids)))
+cat("community sizes: ")
+sapply(membership.ids,function(x) {sum(x==pci.modularity$membership)})
+cat("modularity: ")
+max(pci.modularity$modularity)
+V(pci)$color=pci.modularity$membership
+plot(pci,vertex.size=10,
+     vertex.label=NA,vertex.color=V(pci)$color,
+     main=paste(pci.netname, " Recursive Newman Modularity"))
+
 ############# Other- Tmp work
 min_cut(car,"0", "2490")
 min_cut(hipaa,"0","2320")