positions <- as.matrix(french_cities[1:10, c("th_longitude", "th_latitude")])
distances <- french_cities_distances[1:10, 1:10] / 1000 ## convert to km
production <- rep(1, 10)
attractiveness <- log(french_cities$area[1:10])
all_flows <- grid_blvim(distances, production, seq(1.05, 1.45, by = 0.1),
seq(1, 3, by = 0.5) / 400,
attractiveness,
bipartite = FALSE,
epsilon = 0.1, iter_max = 1000,
)
all_flows_df <- sim_df(all_flows)
## default display: Shannon diversity
ggplot2::autoplot(all_flows_df)
## iterations
ggplot2::autoplot(all_flows_df, iterations)
## we leverage non standard evaluation to compute a different diversity
ggplot2::autoplot(all_flows_df, diversity(sim, "RW"))
## or to refer to columns of the data frame, either default ones
ggplot2::autoplot(all_flows_df, converged)
ggplot2::autoplot(all_flows_df, iterations)
## or added ones
all_flows_df["Nystuen & Dacey"] <- diversity(sim_column(all_flows_df), "ND")
ggplot2::autoplot(all_flows_df, `Nystuen & Dacey`)
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