test_that("biogas energy chain is computed correctly", {
  bg <- biogas_economics(feedstock = 1000, total_solids = 0.1,
                         volatile_solids = 0.8, biogas_yield = 0.5,
                         methane_share = 0.6, electrical_efficiency = 0.4,
                         own_use = 0, energy_price = 5, capex = 1e6,
                         om_rate = 0, leakage = 0, years = 10)
  vs <- 1000 * 0.1 * 0.8 * 1000
  expect_equal(bg$annual[["biogas_m3"]], vs * 0.5)
  expect_equal(bg$annual[["energy_sold"]], vs * 0.5 * 0.6 * 9.97 * 0.4)
  cf <- bg$cashflows
  expect_equal(bg$appraisal[["npv"]],
               sum(cf$net / 1.1^cf$year))
  irr <- bg$appraisal[["irr"]]
  expect_lt(abs(sum(cf$net / (1 + irr)^cf$year)), 1e-3)
  g <- biogas_economics(1000, 0.1, 0.8, 0.5, use = "gas", own_use = 0,
                        energy_price = 30, capex = 1e6, leakage = 0)
  expect_equal(g$annual[["energy_sold"]], vs * 0.5 * 0.6)
  expect_output(print(bg), "NPV")
  expect_error(biogas_economics(1, 2, 0.8, 0.5, energy_price = 1, capex = 1))
})

test_that("leakage and baseline methane enter the GHG balance", {
  a <- biogas_economics(1000, 0.1, 0.8, 0.5, energy_price = 5, capex = 1,
                        leakage = 0, baseline_ch4 = 10)
  b <- biogas_economics(1000, 0.1, 0.8, 0.5, energy_price = 5, capex = 1,
                        leakage = 0.05, baseline_ch4 = 10)
  expect_equal(a$annual[["ghg_avoided_t"]], 1000 * 10 / 1000 * 28)
  expect_lt(b$annual[["ghg_avoided_t"]], a$annual[["ghg_avoided_t"]])
})

test_that("nutrient recovery value is correct", {
  nr <- nutrient_recovery_value(c(10, 20),
                                rbind(c(N = 10, P2O5 = 5, K2O = 0),
                                      c(N = 2, P2O5 = 1, K2O = 4)),
                                equivalence = c(N = 0.5, P2O5 = 1, K2O = 1),
                                price = c(N = 10, P2O5 = 20, K2O = 5),
                                input_nutrients = c(N = 500, P2O5 = 100,
                                                    K2O = 80))
  expect_equal(nr$by_product$value, c(10 * (10 * 0.5 * 10 + 5 * 20),
                                      20 * (2 * 0.5 * 10 + 1 * 20 + 4 * 5)))
  expect_equal(nr$total, sum(nr$by_product$value))
  expect_equal(nr$by_nutrient$recovery_rate, c(140 / 500, 70 / 100, 1))
  expect_error(nutrient_recovery_value(1, c(Z = 1), c(Z = 1), c(Z = 1)))
  expect_output(print(nr), "Total value")
})

test_that("circularity index scales and ranks", {
  d <- data.frame(u = c("a", "b", "c"), x = c(0, 0.5, 1), w = c(1, 0.5, 0))
  ci <- circularity_index(d, "u", c("x", "w"), c(TRUE, FALSE))
  expect_equal(ci$x_score, c(0, 0.5, 1))
  expect_equal(ci$w_score, c(0, 0.5, 1))
  expect_equal(ci$rank, c(3, 2, 1))
  ct <- circularity_index(d, "u", c("x", "w"), c(TRUE, FALSE),
                          method = "target", targets = c(0.5, 0.25))
  expect_equal(ct$x_score, c(0, 1, 1))
  expect_equal(ct$w_score, c(0.25, 0.5, 1))
  expect_error(circularity_index(d, "u", "x", TRUE, method = "target"))
})