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call igraph in R or leidenalg via reticulate depending on methods #1
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@TomKellyGenetics
TomKellyGenetics committed Nov 5, 2020
1 parent e4d8650 commit fdf03f0
Showing 1 changed file with 91 additions and 71 deletions.
162 changes: 91 additions & 71 deletions R/leiden.R
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Original file line number Diff line number Diff line change
Expand Up @@ -166,10 +166,9 @@ leiden.matrix <- function(object,
# test performance for computing matrix to graph in R
# other option is to passing snn_graph to Python

#compute partitions
#compute partitions
partition <- find_partition(snn_graph, partition_type = partition_type,
initial_membership = initial_membership ,
initial_membership = initial_membership,
weights = weights,
node_sizes = node_sizes,
resolution_parameter = resolution_parameter,
Expand Down Expand Up @@ -287,89 +286,110 @@ leiden.igraph <- function(object,
object <- as.undirected(object, mode = "each")
}
}
call_igraph <- !is_directed(snn_graph) && !is_bipartite(object) && legacy == FALSE && partition_type == "CPMVertexPartition" || partition_type == "ModularityVertexPartition"

call_igraph <- !is_directed(object) && !is_bipartite(object) && legacy == FALSE && partition_type == "CPMVertexPartition" || partition_type == "ModularityVertexPartition"

#import python modules with reticulate
numpy <- reticulate::import("numpy", delay_load = TRUE)
leidenalg <- import("leidenalg", delay_load = TRUE)
ig <- import("igraph", delay_load = TRUE)
if(call_igraph == TRUE){
#call igraph implementation
if(partition_type == "CPMVertexPartition"){
objective_function <- "cpm"
}
if(partition_type == "ModularityVertexPartition"){
objective_function <- "modularity"
}

##convert to python numpy.ndarray, then a list
if(!is_named(object)){
vertices <- as.list(as.character(V(object)))
#compute partitions with igraph in C
partition <- membership(cluster_leiden(graph,
objective_function = objective_function,
weights = weights,
resolution_parameter = resolution_parameter,
initial_membership = initial_membership,
n_iterations = n_iterations,
vertex_weights = NULL
))
} else {
vertices <- as.list(names(V(object)))
}
#call python reticulate implementation

edges <- as_edgelist(object)
dim(edges)
edgelist <- list(rep(NA, nrow(edges)))
for(ii in 1:nrow(edges)){
edgelist[[ii]] <- as.character(edges[ii,])
}
#import python modules with reticulate
numpy <- reticulate::import("numpy", delay_load = TRUE)
leidenalg <- import("leidenalg", delay_load = TRUE)
ig <- import("igraph", delay_load = TRUE)

snn_graph <- ig$Graph()
snn_graph$add_vertices(r_to_py(vertices))
snn_graph$add_edges(r_to_py(edgelist))
##convert to python numpy.ndarray, then a list
if(!is_named(object)){
vertices <- as.list(as.character(V(object)))
} else {
vertices <- as.list(names(V(object)))
}

#compute weights if weighted graph given
if(is_weighted(object)){
#assign weights to edges (without dependancy on igraph)
weights <- r_to_py(edge_attr(object)$weight)
snn_graph$es$set_attribute_values('weight', weights)
}
edges <- as_edgelist(object)
dim(edges)
edgelist <- list(rep(NA, nrow(edges)))
for(ii in 1:nrow(edges)){
edgelist[[ii]] <- as.character(edges[ii,])
}

if(length(partition_type) > 1) partition_type <- partition_type[1]
if(is_bipartite(object) && partition_type == "ModularityVertexPartition"){
partition_type <- "ModularityVertexPartition.Bipartite"
}
if(partition_type == "ModularityVertexPartition.Bipartite"){
if(is.null(vertex_attr(object, "type"))){
if(bipartite_mapping(object)$res){
packageStartupMessage("computing bipartite partitions")
object <- set_vertex_attr(object, "type", value = bipartite_mapping(object)$type)
partition_type <- "ModularityVertexPartition.Bipartite"
} else {
packageStartupMessage("cannot compute bipartite types, defaulting to partition type ModularityVertexPartition")
partition_type <- "ModularityVertexPartition"
snn_graph <- ig$Graph()
snn_graph$add_vertices(r_to_py(vertices))
snn_graph$add_edges(r_to_py(edgelist))

#compute weights if weighted graph given
if(is_weighted(object)){
#assign weights to edges (without dependancy on igraph)
weights <- r_to_py(edge_attr(object)$weight)
snn_graph$es$set_attribute_values('weight', weights)
}

if(length(partition_type) > 1) partition_type <- partition_type[1]
if(is_bipartite(object) && partition_type == "ModularityVertexPartition"){
partition_type <- "ModularityVertexPartition.Bipartite"
}
if(partition_type == "ModularityVertexPartition.Bipartite"){
if(is.null(vertex_attr(object, "type"))){
if(bipartite_mapping(object)$res){
packageStartupMessage("computing bipartite partitions")
object <- set_vertex_attr(object, "type", value = bipartite_mapping(object)$type)
partition_type <- "ModularityVertexPartition.Bipartite"
} else {
packageStartupMessage("cannot compute bipartite types, defaulting to partition type ModularityVertexPartition")
partition_type <- "ModularityVertexPartition"
}
}
}
}
if(is_bipartite(object) && partition_type == "CPMVertexPartition"){
partition_type <- "CPMVertexPartition.Bipartite"
}
if(partition_type == "CPMVertexPartition.Bipartite"){
if(is.null(vertex_attr(object, "type"))){
if(bipartite_mapping(object)$res){
packageStartupMessage("computing bipartite partitions")
object <- set_vertex_attr(object, "type", value = bipartite_mapping(object)$type)
partition_type <- "CPMVertexPartition.Bipartite"
} else {
packageStartupMessage("cannot compute bipartite types, defaulting to partition type CPMVertexPartition")
partition_type <- "CPMVertexPartition"
if(is_bipartite(object) && partition_type == "CPMVertexPartition"){
partition_type <- "CPMVertexPartition.Bipartite"
}
if(partition_type == "CPMVertexPartition.Bipartite"){
if(is.null(vertex_attr(object, "type"))){
if(bipartite_mapping(object)$res){
packageStartupMessage("computing bipartite partitions")
object <- set_vertex_attr(object, "type", value = bipartite_mapping(object)$type)
partition_type <- "CPMVertexPartition.Bipartite"
} else {
packageStartupMessage("cannot compute bipartite types, defaulting to partition type CPMVertexPartition")
partition_type <- "CPMVertexPartition"
}
}
}
}

if(!is.null(vertex_attr(object, "type")) || is_bipartite(object)){
type <- as.integer(V(object)$type)
snn_graph$vs$set_attribute_values('type', r_to_py(as.integer(type)))
}
if(!is.null(vertex_attr(object, "type")) || is_bipartite(object)){
type <- as.integer(V(object)$type)
snn_graph$vs$set_attribute_values('type', r_to_py(as.integer(type)))
}

# from here is the same as method for matrix
# would be better to refactor to call from matrix methof
# from here is the same as method for matrix
# would be better to refactor to call from matrix methof

#compute partitions with reticulate
partition <- find_partition(snn_graph, partition_type = partition_type,
initial_membership = initial_membership ,
weights = weights,
node_sizes = node_sizes,
resolution_parameter = resolution_parameter,
seed = seed,
n_iterations = n_iterations,
degree_as_node_size = degree_as_node_size
)
#compute partitions with reticulate
partition <- find_partition(snn_graph, partition_type = partition_type,
initial_membership = initial_membership,
weights = weights,
node_sizes = node_sizes,
resolution_parameter = resolution_parameter,
seed = seed,
n_iterations = n_iterations,
degree_as_node_size = degree_as_node_size
)
}
partition
}

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