library(tidyverse)
library(igraph)
library(sf)
temp_edgelist1 <- readr::read_csv(
here::here("data/migration_decision_making_syria.csv")) %>%
mutate(
group = str_extract(`Civilian Group`,
"^(.*?)(?=\\sof)")) %>%
dplyr::select(`Neighborhood of Syria`, group) %>%
rename(neighborhood_id = `Neighborhood of Syria`) %>%
tidyr::drop_na() %>%
igraph::graph_from_data_frame() %>%
igraph::set_vertex_attr(name = "type",
value = igraph::bipartite_mapping(.)$type) %>%
igraph::bipartite.projection(which = "false") %>%
igraph::get.data.frame("edges") %>%
dplyr::mutate(edge_type = "Population") %>%
dplyr::select(from, to, edge_type)
syrian_polygons <- readRDS(here::here("data/syria_merged.rds"))
syrian_polygons_matrix <- sf::st_intersects(syrian_polygons,
sparse = FALSE)
rownames(syrian_polygons_matrix) <- syrian_polygons$neighborhood_id
colnames(syrian_polygons_matrix) <- syrian_polygons$neighborhood_id
temp_edgelist2 <- syrian_polygons_matrix %>%
igraph::graph_from_adjacency_matrix(mode = "undirected") %>%
igraph::get.data.frame("edges") %>%
dplyr::mutate(edge_type = "Adjacency")
temp_edgelist3 <- readRDS(here::here("data/sum_matrix.rds")) %>%
igraph::graph_from_adjacency_matrix(mode = "undirected") %>%
igraph::get.data.frame("edges") %>%
dplyr::mutate(edge_type = "Adjacency/Population")
edgelist <- rbind(temp_edgelist1, temp_edgelist2, temp_edgelist3)
usethis::use_data(edgelist, overwrite = TRUE)
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