Nothing
## ----include=FALSE------------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE,
comment = "#>",
out.width = "100%",
dpi = 96,
fig.align = "center")
## ----'setup', echo=TRUE-------------------------------------------------------
# Setup ----
library("chessboard")
library("ggplot2")
library("patchwork")
## ----'ggplot-theme', echo=FALSE-----------------------------------------------
## Custom ggplot2 theme ----
custom_theme <- function() {
theme_light() +
theme(plot.title = element_text(face = "bold", family = "serif", size = 18),
plot.caption = element_text(face = "italic", family = "serif"),
axis.title = element_blank(),
axis.text = element_text(family = "serif"))
}
## ----'cb-network', eval=TRUE, fig.height=8, fig.width=5, echo=FALSE, fig.cap="Figure 1. Network as a chessboard", out.width='60%'----
sites <- expand.grid("transect" = 1:3, "quadrat" = 1:5)
nodes <- create_node_labels(data = sites,
transect = "transect",
quadrat = "quadrat")
gg_chessboard(nodes)
## ----echo = FALSE, out.width = "100%", fig.cap = "Figure 2. Workflow and main features of `chessboard`", fig.align = 'center'----
knitr::include_graphics("figures/diagramme.png")
## ----'map-adour-river', echo=FALSE, fig.height=9, fig.width=10, out.width='80%', fig.cap='Figure 3. Location of the French river L\'Adour'----
knitr::include_graphics("figures/map-adour-river.png")
## ----'import-adour-river', echo=FALSE-----------------------------------------
## Import the spatial layer of Adour river ----
path_to_file <- system.file("extdata", "adour_lambert93.gpkg",
package = "chessboard")
adour_river <- sf::st_read(path_to_file, quiet = TRUE)
## ----'import-adour-sites', echo=FALSE-----------------------------------------
## Import sites data ----
path_to_file <- system.file("extdata", "adour_survey_sampling.csv",
package = "chessboard")
nodes <- read.csv(path_to_file)
## Convert data.frame to sf object ----
nodes_sf <- sf::st_as_sf(nodes, coords = c("longitude", "latitude"),
crs = "epsg:2154")
## ----'map-adour-sites', fig.height=9, fig.width=12, out.width='80%', echo=FALSE, fig.cap='Figure 4. Survey sampling along the river L\'Adour'----
ggplot() +
geom_sf(data = adour_river, col = "steelblue") +
geom_sf(data = nodes_sf, shape = 19, size = 2) +
labs(caption = "RGF93 / Lambert-93 Projection") +
custom_theme() +
geom_segment(aes(x = 454180, xend = 440170, y = 6216290, yend = 6263320),
arrow = arrow(length = unit(0.75, 'cm'), type = 'closed'),
linewidth = 2.25) +
geom_text(aes(x = 334500, y = 6285000), label = "River", hjust = 0,
color = "steelblue", fontface = "bold", size = 6,
family = "serif") +
geom_text(aes(x = 414950, y = 6312200), label = "Location 3", hjust = -0.20,
color = "black", fontface = "bold", size = 6, family = "serif") +
geom_text(aes(x = 474655, y = 6236708), label = "Location 1",
color = "black", fontface = "bold", size = 6, family = "serif") +
geom_text(aes(x = 467250, y = 6287620), label = "Location 2",
color = "black", fontface = "bold", size = 6, family = "serif")
## ----'import-data', echo=TRUE-------------------------------------------------
# Import data ----
path_to_file <- system.file("extdata", "adour_survey_sampling.csv",
package = "chessboard")
sampling <- read.csv(path_to_file)
dim(sampling)
## ----'head-of-data', echo=TRUE------------------------------------------------
# First rows ----
head(sampling, 10)
## ----'tail-of-data', echo=TRUE------------------------------------------------
# Last rows ----
tail(sampling, 10)
## ----'select-data'------------------------------------------------------------
# Select the first location ----
sampling <- sampling[sampling$"location" == 1, ]
dim(sampling)
## ----'create-nodes-labels'----------------------------------------------------
# Create node labels ----
nodes <- create_node_labels(data = sampling,
location = "location",
transect = "transect",
quadrat = "quadrat")
nodes
## ----'plot-sampling-units', fig.height=8, fig.width=5, echo=TRUE, out.width='60%', fig.cap='Figure 5. Sampling survey as a chessboard'----
# Visualize chessboard ----
gg_chessboard(nodes)
## ----'get-node-labels'--------------------------------------------------------
# Extract node labels ----
get_node_list(nodes)
## ----'method-pawn'------------------------------------------------------------
# Explore pawn method to find neighbors ----
neighbors_pawn <- pawn(nodes = nodes,
focus = "2-3",
degree = 1,
directed = FALSE,
reverse = FALSE)
neighbors_pawn
## ----'nb-pawn', fig.height=8, fig.width=5, echo=TRUE, fig.cap="Figure 6. Detected neighbors (pawn method)", out.width='50%'----
gg_chessboard(nodes) +
geom_node(nodes, focus = "2-3") +
geom_neighbors(nodes, neighbors_pawn)
## ----'cb-pawn', fig.height=4.3, fig.width=12, echo=FALSE, fig.cap="Figure 7. Pawn movements", out.width='100%'----
demo_sites <- expand.grid("transect" = 1:9, "quadrat" = 1:9)
demo_nodes <- create_node_labels(data = demo_sites,
transect = "transect",
quadrat = "quadrat")
demo_focus <- "5-5"
pawn_1 <-
gg_chessboard(demo_nodes, "A. Undirected network", "") +
geom_node(demo_nodes, demo_focus) +
geom_neighbors(demo_nodes, pawn(demo_nodes, demo_focus, degree = 4,
directed = FALSE, reverse = FALSE))
pawn_2 <-
gg_chessboard(demo_nodes, "B. Directed network", "") +
geom_node(demo_nodes, demo_focus) +
geom_neighbors(demo_nodes, pawn(demo_nodes, demo_focus, degree = 4,
directed = TRUE, reverse = FALSE))
pawn_3 <-
gg_chessboard(demo_nodes, "C. Directed network (reverse)", "") +
geom_node(demo_nodes, demo_focus) +
geom_neighbors(demo_nodes, pawn(demo_nodes, demo_focus, degree = 4,
directed = TRUE, reverse = TRUE))
(pawn_1 | pawn_2 | pawn_3)
## ----'cb-bishop', eval=TRUE, fig.height=4.3, fig.width=12, echo=FALSE, fig.cap="Figure 8. Bishop movements", out.width='100%'----
demo_sites <- expand.grid("transect" = 1:9, "quadrat" = 1:9)
demo_nodes <- create_node_labels(data = demo_sites,
transect = "transect",
quadrat = "quadrat")
demo_focus <- "5-5"
bishop_1 <-
gg_chessboard(demo_nodes, "A. Undirected network", "") +
geom_node(demo_nodes, demo_focus) +
geom_neighbors(demo_nodes, bishop(demo_nodes, demo_focus, degree = 4,
directed = FALSE, reverse = FALSE))
bishop_2 <-
gg_chessboard(demo_nodes, "B. Directed network", "") +
geom_node(demo_nodes, demo_focus) +
geom_neighbors(demo_nodes, bishop(demo_nodes, demo_focus, degree = 4,
directed = TRUE, reverse = FALSE))
bishop_3 <-
gg_chessboard(demo_nodes, "C. Directed network (reverse)", "") +
geom_node(demo_nodes, demo_focus) +
geom_neighbors(demo_nodes, bishop(demo_nodes, demo_focus, degree = 4,
directed = TRUE, reverse = TRUE))
(bishop_1 | bishop_2 | bishop_3)
## ----'create-edges-list-pawn'-------------------------------------------------
# Create edge list ----
edges_pawn <- create_edge_list(nodes = nodes,
method = "pawn",
degree = 1,
directed = TRUE,
reverse = FALSE,
self = FALSE)
edges_pawn
## ----'df-to-sf'---------------------------------------------------------------
# Convert nodes to sf object ----
nodes_sf <- sf::st_as_sf(nodes, coords = c("longitude", "latitude"),
crs = "epsg:2154")
head(nodes_sf)
## ----'edges-list-to-sf'-------------------------------------------------------
# Convert edge list to sf ----
edges_pawn_sf <- edges_to_sf(edges = edges_pawn,
sites = nodes_sf)
edges_pawn_sf
## ----'map-edges-list-pawn', fig.height=8, fig.width=6.5, echo=TRUE, fig.cap="Figure 9. Edge list (pawn method)", out.width='80%'----
# Map of nodes and edges ----
ggplot(nodes_sf) +
geom_sf(size = 12) +
geom_sf(data = edges_pawn_sf) +
theme_light()
## ----'create-edges-list-bishop'-----------------------------------------------
# Create edge list (Bishop method) ----
edges_bishop <- create_edge_list(nodes = nodes,
method = "bishop",
degree = 1,
directed = TRUE,
reverse = FALSE,
self = FALSE)
edges_bishop
# Merge Pawn and Bishop edges ----
edges <- append_edge_lists(edges_pawn, edges_bishop)
# Convert edges to spatial layer ----
edges_sf <- edges_to_sf(edges, nodes_sf)
## ----'map-edges-list-pawn-bishop', fig.height=8, fig.width=6.5, echo=TRUE, fig.cap="Figure 10. Edges list (combined methods)", out.width='80%'----
# Map of nodes and edges ----
ggplot(nodes_sf) +
geom_sf(size = 12) +
geom_sf(data = edges_sf) +
theme_light()
## ----'connectivity-matrix'----------------------------------------------------
# Create connectivity matrix ----
conn_matrix <- connectivity_matrix(edges)
conn_matrix
## ----'plot-connectivity-matrix', fig.height=8, fig.width=8, fig.cap="Figure 11. Connectivity matrix", out.width='80%'----
# Visualize connectivity matrix ----
gg_matrix(conn_matrix)
## ----'connectivity-matrix-to-df'----------------------------------------------
# Convert connectivity matrix to edge list ----
matrix_to_edge_list(conn_matrix)
## ----'transform-crs'----------------------------------------------------------
# Convert edges to spatial layer ----
edges_sf <- edges_to_sf(edges, nodes_sf)
# Project the CRS ----
edges_sf_lonlat <- sf::st_transform(edges_sf, crs = "epsg:4326")
# Check ----
edges_sf
edges_sf_lonlat
## ----'export-sf', eval=FALSE--------------------------------------------------
# # Export layer as a GeoPackage ----
# sf::st_write(edges_sf, "edge_list.gpkg")
## ----'change-theme', fig.height=8, fig.width=8, fig.cap="Figure 12. Custom connectivity matrix", out.width='80%'----
# Change default ggplot2 theme ----
gg_matrix(conn_matrix) +
theme_bw() +
theme(legend.position = "none")
## ----'to-igraph'--------------------------------------------------------------
# Convert edge list to igraph object ----
igraph_obj <- igraph::graph_from_data_frame(d = edges,
directed = TRUE,
vertices = nodes)
# Check -----
class(igraph_obj)
print(igraph_obj)
## ----'plot-igraph', fig.height=8, fig.width=8, fig.cap="Figure 13. Network visualization w/ `igraph`", out.width='80%'----
# Plot the network w/ igraph ----
plot(igraph_obj)
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