KilianGRIHAULTBARREIRO
commented
6 months ago New version :
splnr_plot_cost_4 <- function(df, col_names = NULL,
legendTitle = "Cost",
plotTitle = "",
paletteName = "YlGnBu") {
gg <- ggplot2::ggplot() +
ggplot2::coord_sf(xlim = sf::st_bbox(df)$xlim, ylim = sf::st_bbox(df)$ylim) +
ggplot2::labs(subtitle = plotTitle, fill = legendTitle)
# If col_names is NULL, use all columns in the data
if (is.null(col_names)) {
stop("Please specify the column(s) of data to display.")
}
# Replace NA with 0 in selected columns for binary data
df <- dplyr::mutate_all(df, ~replace_na(.,0))
# Create a new binary column indicating the presence of any non-missing value in selected columns for binary data
is_binary <- all(sapply(col_names, function(col_name) all(df[[col_name]] %in% c(0, 1))))
if (is_binary) {
df$UnionColumn <- apply(df[, col_names, drop = FALSE], 1, function(x) as.numeric(any(x == 1, na.rm = TRUE)))
gg <- gg +
ggplot2::geom_sf(data = df, ggplot2::aes(fill = UnionColumn),
colour = "grey80", size = 0.1, show.legend = TRUE) +
ggplot2::scale_fill_gradient(low = "#c6dbef", high = "#3182bd", limits = c(0, 1))
} else {
for (col_name in col_names) {
gg <- gg +
ggplot2::geom_sf(data = df, ggplot2::aes(fill = !!rlang::sym(col_name)),
colour = "grey80", size = 0.1, show.legend = TRUE) +
ggplot2::scale_fill_gradientn(
colors = rev(RColorBrewer::brewer.pal(100, paletteName)),
limits = NULL
)
}
}
return(gg)
}
jaseeverett
We want to make the function
splnr_plot_costmore generic to handle multi-columns binary and continuous data.