Created
April 17, 2025 20:52
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Solution Fragmentation tests using prioritizr testing data
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| # load packages | |
| library(prioritizr) | |
| library(prioritizrdata) | |
| library(terra) | |
| # import planning unit data | |
| wa_pu <- get_wa_pu() | |
| # preview data | |
| print(wa_pu) | |
| wa_pu[!is.na(wa_pu)] <- 1 | |
| # import feature data | |
| wa_features <- get_wa_features() | |
| # calculate budget | |
| budget <- terra::global(wa_pu, "sum", na.rm = TRUE)[[1]] * 0.3 | |
| # create problem | |
| p1 <- | |
| problem(wa_pu, features = wa_features) %>% | |
| add_relative_targets(0.2) %>% | |
| add_proportion_decisions() %>% | |
| add_default_solver(gap = 0.1, verbose = FALSE) | |
| # Minimum shortfall | |
| s1 <- solve(p1 |> add_min_shortfall_objective(budget) ) | |
| names(s1) <- "minshort" | |
| # Repeat all but with binary decisions - max cov | |
| s2 <- solve(p1 |> add_min_shortfall_objective(budget) |> add_binary_decisions() ) | |
| names(s2) <- "minshort_binary" | |
| # --- # | |
| # For ambitious targets | |
| p2 <- p1 |> | |
| add_loglinear_targets(10, 0.9, 1000, 0.2) | |
| # Minimum shortfall | |
| s3 <- solve(p2 |> add_min_shortfall_objective(budget) ) | |
| names(s3) <- "minshort_loglinear" | |
| # Repeat all but with binary decisions | |
| s4 <- solve(p2 |> add_min_shortfall_objective(budget) |> add_binary_decisions() ) | |
| names(s4) <- "minshort_loglinear_binary" | |
| # Plot all next to each other | |
| plot(c(s1,s2, s3,s4)) |
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