зеркало из https://github.com/microsoft/wpa.git
refactor: scaffolding (#225)
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@ -78,9 +78,41 @@ network_p2p_test <- function(
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## Set variables ---------------------------------------------------------
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TO_hrvar <- paste0("TieOrigin_", hrvar)
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TO_hrvar <- paste0("TieOrigin_", hrvar)
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TD_hrvar <- paste0("TieDestination_", hrvar)
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## Vertices data frame to provide meta-data ------------------------------
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vert_ft <-
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rbind(
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# TieOrigin
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edges %>%
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select(from) %>% # Single column
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unique() %>% # Remove duplications
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left_join(select(data, TieOrigin_PersonId, TO_hrvar),
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by = c("from" = "TieOrigin_PersonId")) %>%
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select(node = "from", !!sym(hrvar) := TO_hrvar),
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# TieDestination
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edges %>%
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select(to) %>% # Single column
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unique() %>% # Remove duplications
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left_join(select(data, TieDestination_PersonId, TD_hrvar),
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by = c("to" = "TieDestination_PersonId")) %>%
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select(node = "to", !!sym(hrvar) := TD_hrvar)
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)
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## Create 'igraph' object -----------------------------------------------
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g_raw <-
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igraph::graph_from_data_frame(edges,
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directed = TRUE, # Directed, but FALSE for visualization
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vertices = unique(vert_ft)) # remove duplicates
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## Assign weights --------------------------------------------------------
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g_raw$weight <- edges$weight
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## Main algorithm --------------------------------------------------------
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if(centrality == FALSE & community == FALSE){
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@ -91,6 +123,11 @@ network_p2p_test <- function(
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# Data -> Returns person dataset with HR attributes
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# Network -> Returns network object
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g <- g_raw %>% igraph::simplify()
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## Name of vertex attribute
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v_attr <- hrvar
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} else if(centrality %in% valid_cen & community == FALSE){
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@ -109,6 +146,56 @@ network_p2p_test <- function(
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# Network -> Returns network object with community attribute
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# TODO - modularise louvain and leiden?
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if(community == "louvain"){
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set.seed(seed = seed)
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## Convert to undirected
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g_ud <- igraph::as.undirected(g_raw)
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## Return a numeric vector of partitions / clusters / modules
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## Set a low resolution parameter to have fewer groups
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## weights = NULL means that if the graph as a `weight` edge attribute, this
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## will be used by default.
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lc <- igraph::cluster_louvain(g_ud, weights = NULL)
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## Add cluster
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g <-
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g_ud %>%
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# Add louvain partitions to graph object
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igraph::set_vertex_attr("cluster", value = as.character(igraph::membership(lc))) %>% # Return membership - diff from Leiden
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igraph::simplify()
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## Name of vertex attribute
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v_attr <- "cluster"
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} else if(community == "leiden"){
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# Check package installation
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check_pkg_installed(pkgname = "leiden")
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## Return a numeric vector of partitions / clusters / modules
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## Set a low resolution parameter to have fewer groups
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ld <- leiden::leiden(
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g_raw,
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resolution_parameter = res,
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seed = seed,
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weights = g_raw$weight) # create partitions
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## Add cluster
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g <-
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g_raw %>%
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# Add leiden partitions to graph object
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igraph::set_vertex_attr("cluster", value = as.character(ld)) %>%
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igraph::simplify()
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## Name of vertex attribute
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v_attr <- "cluster"
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}
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} else if(centrality %in% valid_cen & community %in% valid_com){
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# PLOT -> Returns basic plot with community AND vertices proportional to centrality
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@ -121,7 +208,7 @@ network_p2p_test <- function(
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} else {
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stop(
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"Invalid inputs to `centrality` or `community`".
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"Invalid inputs to `centrality` or `community`."
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)
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}
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