## Tests for swcEcon package — all self-contained, < 10 seconds total

library(testthat)
library(swcEcon)

# ============================================================
# 1. calc_bcr
# ============================================================
test_that("calc_bcr returns correct class and BCR > 1 for viable project", {
  r <- calc_bcr(investment = 20, annual_benefit = 6,
                annual_omc = 0.8, life = 20, discount_rate = 0.12)
  expect_s3_class(r, "swcEcon_bcr")
  expect_gt(r$bcr, 1.0)
  expect_true(r$pv_benefits > r$pv_costs)
})

test_that("calc_bcr BCR < 1 for non-viable project", {
  r <- calc_bcr(investment = 100, annual_benefit = 1,
                annual_omc = 0, life = 5, discount_rate = 0.12)
  expect_lt(r$bcr, 1.0)
})

test_that("calc_bcr benefit_lag reduces BCR", {
  r0 <- calc_bcr(20, 6, 0.8, 20, 0.12, benefit_lag = 0)
  r2 <- calc_bcr(20, 6, 0.8, 20, 0.12, benefit_lag = 2)
  expect_lt(r2$bcr, r0$bcr)
})

test_that("calc_bcr residual_value increases BCR", {
  r0 <- calc_bcr(20, 6, 0.8, 20, 0.12)
  r1 <- calc_bcr(20, 6, 0.8, 20, 0.12, residual_value = 5)
  expect_gt(r1$bcr, r0$bcr)
})

test_that("calc_bcr stops on non-positive investment", {
  expect_error(calc_bcr(-5, 6), "positive")
})

test_that("calc_bcr stops on invalid discount rate", {
  expect_error(calc_bcr(20, 6, discount_rate = 1.5), "proportion")
})

test_that("calc_bcr vector benefits work", {
  bv <- c(3, 4, 5, 6, 7, 6, 6, 6, 6, 6,
          6, 6, 6, 6, 6, 6, 6, 6, 6, 6)
  r  <- calc_bcr(20, bv, life = 20)
  expect_s3_class(r, "swcEcon_bcr")
  expect_length(r$bcr, 1L)
})

# ============================================================
# 2. calc_npv
# ============================================================
test_that("calc_npv positive for viable project", {
  r <- calc_npv(20, 6, 0.8, 20, 0.12)
  expect_s3_class(r, "swcEcon_npv")
  expect_gt(r$npv, 0)
  expect_equal(ncol(r$cashflows), 6L)
  expect_equal(nrow(r$cashflows), 20L)
})

test_that("calc_npv negative for unviable project", {
  r <- calc_npv(200, 1, 0, 5, 0.12)
  expect_lt(r$npv, 0)
})

# ============================================================
# 3. calc_irr
# ============================================================
test_that("calc_irr exceeds 12% for good project", {
  r <- calc_irr(20, 6, 0.8, 20)
  expect_true(r$converged)
  expect_gt(r$irr_pct, 12)
})

test_that("calc_irr converged = FALSE when no root", {
  r <- calc_irr(1000, 1, 0, 5)
  expect_false(isTRUE(r$converged))
})

test_that("calc_irr IRR decreases with higher investment", {
  r1 <- calc_irr(20, 6, 0.8, 20)
  r2 <- calc_irr(40, 6, 0.8, 20)
  if (r1$converged && r2$converged)
    expect_gt(r1$irr, r2$irr)
})

# ============================================================
# 4. calc_pbp
# ============================================================
test_that("calc_pbp correct class and finite result", {
  r <- calc_pbp(20, 6, 0.8, 20, 0.12)
  expect_s3_class(r, "swcEcon_pbp")
  expect_true(is.finite(r$simple_pbp))
  expect_gt(r$discounted_pbp, r$simple_pbp)
})

test_that("calc_pbp short PBP gives adoption message", {
  r <- calc_pbp(10, 8, 0, 20)
  expect_true(grepl("likely", r$adoption, ignore.case = TRUE))
})

# ============================================================
# 5. calc_mrr
# ============================================================
test_that("calc_mrr correct MRR for positive case", {
  r <- calc_mrr(nb_with = 18000, nb_without = 11000,
                cost_with = 16000, cost_without = 11500)
  expect_s3_class(r, "swcEcon_mrr")
  expect_equal(r$mrr, round((18000-11000)/(16000-11500)*100, 2))
})

test_that("calc_mrr recommends when MRR > min_mrr", {
  r <- calc_mrr(18000, 11000, 16000, 11500, min_mrr = 100)
  expect_true(grepl("Recommend", r$recommendation))
})

test_that("calc_mrr does not recommend when MRR < min_mrr", {
  r <- calc_mrr(12000, 11000, 16000, 11500, min_mrr = 100)
  expect_true(grepl("not recommend|Do not", r$recommendation, ignore.case = TRUE))
})

test_that("calc_mrr zero marginal cost with positive benefit dominates", {
  r <- calc_mrr(15000, 11000, 11500, 11500)
  expect_true(is.infinite(r$mrr) || grepl("Dominates", r$recommendation))
})

# ============================================================
# 6. calc_mbcr
# ============================================================
test_that("calc_mbcr correct value", {
  r <- calc_mbcr(total_benefit = 80, operating_cost = 12,
                 capital_cost = 20)
  expect_s3_class(r, "swcEcon_mbcr")
  expect_equal(r$mbcr, round((80 - 12) / 20, 4))
})

# ============================================================
# 7. calc_soil_loss_cost
# ============================================================
test_that("calc_soil_loss_cost correct structure", {
  r <- calc_soil_loss_cost(R = 720, K = 0.25, LS = 4.2,
                            C_pre = 0.35, C_post = 0.18,
                            P_pre = 1.0, P_post = 0.5,
                            area_ha = 500)
  expect_s3_class(r, "swcEcon_soil")
  expect_true(r$soil_loss_pre > r$soil_loss_post)
  expect_true(r$pct_reduction > 0)
  expect_true(r$annual_benefit_inr > 0)
})

test_that("calc_soil_loss_cost uses usle_india_soils data", {
  data(usle_india_soils, package = "swcEcon")
  K <- usle_india_soils[usle_india_soils$soil_series == "Vertisols", "k_mean"]
  r <- calc_soil_loss_cost(R = 650, K = K, LS = 3.5,
                            C_pre = 0.3, C_post = 0.15, area_ha = 200)
  expect_s3_class(r, "swcEcon_soil")
})

# ============================================================
# 8. calc_nutrient_cost
# ============================================================
test_that("calc_nutrient_cost returns positive costs", {
  r <- calc_nutrient_cost(soil_loss_t_ha = 12, area_ha = 200)
  expect_true(r$total_cost_inr > 0)
  expect_equal(r$total_cost_inr,
               r$cost_n_inr + r$cost_p_inr + r$cost_k_inr)
})

# ============================================================
# 9. calc_water_value
# ============================================================
test_that("calc_water_value returns correct class and positive benefit", {
  r <- calc_water_value(area_ha = 500, rainfall_mm = 720,
                         rc_pre = 0.35, rc_post = 0.20)
  expect_s3_class(r, "swcEcon_water")
  expect_gt(r$annual_benefit_inr, 0)
  expect_gte(r$runoff_reduced_m3, 0)
})

test_that("calc_water_value uses rainfall_erosivity_india data", {
  data(rainfall_erosivity_india, package = "swcEcon")
  rf <- rainfall_erosivity_india[
    rainfall_erosivity_india$district == "Pune", "annual_rf_mm"]
  r  <- calc_water_value(500, rf)
  expect_s3_class(r, "swcEcon_water")
})

# ============================================================
# 10. calc_irrigation_benefit
# ============================================================
test_that("calc_irrigation_benefit positive net benefit", {
  r <- calc_irrigation_benefit(80, 1.6, 18000, 8000)
  expect_gt(r$net_benefit_inr, 0)
  expect_equal(r$gross_benefit_inr - r$additional_cost_inr,
               r$net_benefit_inr)
})

# ============================================================
# 11. calc_employment
# ============================================================
test_that("calc_employment correct EGR", {
  r <- calc_employment(45000, 50, 250)
  expect_equal(r$egr_days_per_lakh, 45000 / 50)
  expect_true(is.character(r$mgnregs_60pct_norm))
})

# ============================================================
# 12. sensitivity_analysis
# ============================================================
test_that("sensitivity_analysis returns correct structure", {
  r <- sensitivity_analysis(20, 6, 0.8, 20, 0.12)
  expect_s3_class(r, "swcEcon_sens")
  expect_equal(nrow(r$scenarios), 8L)
  expect_true(all(c("scenario","bcr","npv","robust") %in%
                    names(r$scenarios)))
})

test_that("sensitivity_analysis base case BCR matches calc_bcr", {
  r    <- sensitivity_analysis(20, 6, 0.8, 20, 0.12)
  base <- calc_bcr(20, 6, 0.8, 20, 0.12)$bcr
  expect_equal(r$scenarios$bcr[1L], round(base, 3))
})

# ============================================================
# 13. calc_switching_value
# ============================================================
test_that("calc_switching_value returns positive values for viable project", {
  r <- calc_switching_value(20, 6, 0.8, 20, 0.12)
  expect_s3_class(r, "swcEcon_sv")
  expect_gt(r$sv_cost_pct, 0)
  expect_gt(r$sv_benefit_pct, 0)
})

# ============================================================
# 14. monte_carlo_swc
# ============================================================
test_that("monte_carlo_swc returns correct structure", {
  mc <- monte_carlo_swc(inv_mean = 20, ben_mean = 6,
                         omc_mean = 0.8, n_sim = 200, seed = 42)
  expect_s3_class(mc, "swcEcon_mc")
  expect_length(mc$bcr_sim, 200L)
  expect_gte(mc$p_bcr_gt1, 0)
  expect_lte(mc$p_bcr_gt1, 1)
})

test_that("monte_carlo_swc reproducible with seed", {
  mc1 <- monte_carlo_swc(20, 6, 0.8, n_sim = 100, seed = 99)
  mc2 <- monte_carlo_swc(20, 6, 0.8, n_sim = 100, seed = 99)
  expect_equal(mc1$bcr_sim, mc2$bcr_sim)
})

# ============================================================
# 15. run_swc_pipeline
# ============================================================
test_that("run_swc_pipeline returns correct class", {
  pl <- suppressMessages(
    run_swc_pipeline(20, 6, 0.8, 20, 0.12,
                     include_sensitivity = FALSE,
                     include_monte_carlo = FALSE))
  expect_s3_class(pl, "swcEcon_pipeline")
  expect_s3_class(pl$summary, "data.frame")
  expect_true(nrow(pl$summary) > 0)
  expect_true(all(c("indicator","value","status") %in%
                    names(pl$summary)))
})

# ============================================================
# 16. generate_swc_report
# ============================================================
test_that("generate_swc_report creates valid HTML file", {
  pl  <- suppressMessages(
    run_swc_pipeline(20, 6, 0.8, include_sensitivity = FALSE))
  tmp <- tempfile(fileext = ".html")
  on.exit(unlink(tmp))
  generate_swc_report(pl, output_file = tmp, author = "test")
  expect_true(file.exists(tmp))
  expect_gt(file.size(tmp), 3000L)
  html <- paste(readLines(tmp, warn = FALSE), collapse = "\n")
  expect_true(grepl("<!DOCTYPE html>", html, fixed = TRUE))
  expect_true(grepl("swcEcon", html, fixed = TRUE))
})

test_that("generate_swc_report stops on wrong class", {
  expect_error(generate_swc_report(list(a = 1)), "swcEcon_pipeline")
})

# ============================================================
# 17. Datasets
# ============================================================
test_that("swc_benchmarks has correct dimensions and values", {
  data(swc_benchmarks, package = "swcEcon")
  expect_equal(nrow(swc_benchmarks), 10L)
  expect_equal(ncol(swc_benchmarks), 10L)
  expect_true(all(swc_benchmarks$bcr_min >= 1.0))
  expect_true(all(swc_benchmarks$bcr_max > swc_benchmarks$bcr_min))
})

test_that("usle_india_soils has 8 soil orders and valid K values", {
  data(usle_india_soils, package = "swcEcon")
  expect_equal(nrow(usle_india_soils), 8L)
  expect_true(all(usle_india_soils$k_mean > 0))
  expect_true(all(usle_india_soils$k_mean <= 0.65))
})

test_that("rainfall_erosivity_india has 20 districts", {
  data(rainfall_erosivity_india, package = "swcEcon")
  expect_equal(nrow(rainfall_erosivity_india), 20L)
  expect_true(all(rainfall_erosivity_india$r_factor > 0))
})

test_that("swc_cost_norms has 18 measures with valid costs", {
  data(swc_cost_norms, package = "swcEcon")
  expect_equal(nrow(swc_cost_norms), 18L)
  expect_true(all(swc_cost_norms$norm_2024_inr > swc_cost_norms$norm_2015_inr))
})

test_that("watershed_projects has 50 rows and computed BCR column", {
  data(watershed_projects, package = "swcEcon")
  expect_equal(nrow(watershed_projects), 50L)
  expect_true("bcr" %in% names(watershed_projects))
  expect_true(all(!is.na(watershed_projects$bcr)))
})

test_that("farmer_adoption has 120 rows and valid adoption column", {
  data(farmer_adoption, package = "swcEcon")
  expect_equal(nrow(farmer_adoption), 120L)
  expect_true(all(farmer_adoption$adopted_swc %in% c(0L, 1L)))
  expect_true(sum(is.na(farmer_adoption$yield_post_kharif)) ==
              sum(farmer_adoption$adopted_swc == 0L))
})