multiple_cutoffs.R

library(accessibility)
library(ggplot2)

data_dir <- system.file("extdata", package = "accessibility")
travel_matrix <- readRDS(file.path(data_dir, "travel_matrix.rds"))
land_use_data <- readRDS(file.path(data_dir, "land_use_data.rds"))

access <- cumulative_cutoff(
  travel_matrix,
  land_use_data,
  cutoff = 1:120,
  opportunity = "jobs",
  travel_cost = "travel_time"
)
access

# ideally we'd have to weigh by each origin population here, but you get the
# point

avg_access <- access[, .(avg_access = mean(jobs)), by = cutoff]
total_jobs <- sum(land_use_data$jobs)

ggplot(avg_access) +
  geom_line(aes(cutoff, avg_access)) +
  scale_y_continuous(
    labels = scales::label_percent(scale = 100 / total_jobs)
  ) +
  labs(
    x = "Travel time cutoff",
    y = "Avg. accessibility\n(% of total jobs in the study area)"
  )