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```
# Core Basic Analysis Parameters
# discourseGT
# MIT License
# Documentation
#' Run Graphical Analysis Core Parameters
#'
#' Analyzes the graphs with the core parameters, such as number of edges and nodes, density, average degree, centrality, and modularity
#'
#' @param ginp The prepared graph object from prepareGraphs function
#' @return Gives the edge and weighted edge counts, number of nodes, density, degree (averages), memberships, modularity, centrality, articulation points, and strong/weak plots as a list object
#' @examples
#' df <- sampleData1
#' prepNet <- tabulate_edges(df, iscsvfile = FALSE, silentNodes = 0)
#' baseNet <- prepareGraphs(prepNet, project_title = "Sample Data 1", weightedGraph = TRUE)
#'
#' coreNetAnalysis(baseNet)
#'
coreNetAnalysis <- function(ginp){
# Pulls a copy of the stored variable
g <- ginp$graph
weighted <- ginp$weightedGraph
# Edge Count
nedge <- igraph::ecount(g)
# Edge Weighted Count
if(weighted == TRUE){
nedge_weighted <- sum(ginp$weight_list)
} else if(weighted == FALSE){
nedge_weighted <- NULL
}
# Node Count
nnode <- igraph::gorder(g)
# Density (with self interactions not allowed, user prompt)
den <- igraph::edge_density(g,loops = FALSE)
# Degrees of all nodes
inoutdeg <- igraph::degree(g)
# Average degree (both directions)
degavg.directional <- mean(igraph::degree(g))
# Average degree based on first occurance
degavg <- (mean(igraph::degree(g))/2)
# Finding and plotting strong/weak clusters
strwkplotchk <- igraph::clusters(g, mode = "strong")$membership
# Creates a vector based on short walkthroughs to find communities
membershipvec <- igraph::cluster_walktrap(g)
# Finds unrestricted modularity of graph
submod <- igraph::modularity(membershipvec)
# Centrality of Network Members
central <- igraph::centr_degree(g, mode = c("total"), loops = FALSE, normalized = TRUE)
# Articulation Points List
# Articuation points or cut vertices are vertices whose removal increases the number of connected components in a graph.
artpoint <- igraph::articulation.points(g)
# Reciprocity
reciprocity <- igraph::reciprocity(ginp$graph, ignore.loops = TRUE)
# Return all values as single function
objectsReturned <- list(edge.count = nedge, weighted.edge.count = nedge_weighted, node.count = nnode, net.density = den,
degree.all = inoutdeg, avg.net.degree = degavg.directional, degavg.unidirectional = degavg,
all.com = strwkplotchk, membershipNet = membershipvec, modularity = submod, central = central, artpoint = artpoint, reciprocity = reciprocity)
return(objectsReturned)
}
```

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