test_that("fit_vant_hoff recovers approximately correct thermodynamic parameters", {
  # Simulate Kc from known deltaH/deltaS via the van't Hoff relationship
  set.seed(7)
  deltaH_true <- 15   # kJ/mol (endothermic)
  deltaS_true <- 55   # J/(mol K)
  R_gas <- 8.314e-3   # kJ/(mol K)
  temperature_K <- c(298, 308, 318, 328)
  logKc <- deltaS_true / (R_gas * 1000) - deltaH_true / (R_gas * temperature_K) +
    stats::rnorm(4, 0, 0.01)
  Kc <- exp(logKc)

  res <- fit_vant_hoff(temperature_K, Kc)
  expect_equal(res$deltaH_kJmol, deltaH_true, tolerance = 0.5)
  expect_equal(res$deltaS_Jmolk, deltaS_true, tolerance = 2)
  expect_equal(nrow(res$table), 4)
})

test_that("fit_vant_hoff errors with too few points", {
  expect_error(fit_vant_hoff(c(298, 308), c(1.8, 2.3)), "at least 3")
})

test_that("fit_confint returns a tidy data frame for a langmuir fit", {
  Ce <- c(2, 5, 10, 20, 35, 50, 70)
  qe <- c(0.8, 1.6, 2.3, 3.0, 3.6, 4.0, 4.4)
  fit <- fit_langmuir(Ce, qe)
  ci <- fit_confint(fit)
  expect_equal(nrow(ci), 2)
  expect_true(all(c("parameter", "estimate", "lower", "upper") %in% names(ci)))
  expect_true(all(ci$lower <= ci$estimate & ci$estimate <= ci$upper))
})

test_that("fit_confint works for an lm-based fit (intraparticle)", {
  t <- c(5, 15, 30, 60, 120, 240)
  qt <- c(1.2, 2.1, 2.9, 3.6, 4.0, 4.2)
  fit <- fit_intraparticle(t, qt)
  ci <- fit_confint(fit)
  expect_equal(nrow(ci), 2)
})