library(agriME)

# Core accounting identities and formula definitions.
m <- marketing_metrics(
  producer_price = 1900,
  consumer_price = 3150,
  marketing_cost = 510,
  marketing_margin = 740,
  channel = "Channel A"
)
stopifnot(
  identical(m$channel, "Channel A"),
  isTRUE(all.equal(m$price_spread, 1250)),
  isTRUE(all.equal(m$price_spread_percent, 100 * 1250 / 3150)),
  isTRUE(all.equal(m$producer_share_percent, 100 * 1900 / 3150)),
  isTRUE(all.equal(m$acharya_efficiency, 1900 / 1250)),
  isTRUE(all.equal(m$shepherd_efficiency, 3150 / 510)),
  isTRUE(all.equal(m$conventional_efficiency, 1250 / 510)),
  isTRUE(all.equal(m$accounting_gap, 0))
)
stopifnot(
  isTRUE(all.equal(price_spread(1900, 3150), 1250)),
  isTRUE(all.equal(price_spread(1900, 3150, TRUE), 100 * 1250 / 3150)),
  isTRUE(all.equal(producers_share(1900, 3150), 100 * 1900 / 3150)),
  isTRUE(all.equal(
    marketing_efficiency(1900, 3150, 510, 740, "acharya"),
    1900 / 1250
  )),
  isTRUE(all.equal(
    marketing_efficiency(1900, 3150, 510, 740, "shepherd", "net_ratio"),
    3150 / 510 - 1
  ))
)

margin <- marketing_margin(2050, 2450, 140, 3150)
stopifnot(
  margin$gross_margin == 400,
  margin$net_margin == 260,
  isTRUE(all.equal(margin$net_margin_share_percent, 100 * 260 / 3150))
)

# Stage-level analysis and diagnostics.
data(tomato_channels)
channel_data <- as_market_channel(tomato_channels)
stopifnot(inherits(channel_data, "market_channel"))
stopifnot(nrow(validate_market_channel(channel_data)) == 0L)

fit <- analyse_channels(channel_data)
stopifnot(inherits(fit, "agriME_analysis"))
stopifnot(nrow(fit$summary) == 4L, nrow(fit$actors) == 10L)
stopifnot(all(abs(fit$summary$accounting_gap) < 1e-10))
direct <- fit$summary[fit$summary$channel == "Direct", ]
stopifnot(
  direct$producer_price == 2420,
  direct$consumer_price == 2600,
  direct$price_spread == 180
)

broken <- tomato_channels
broken$purchase_price[broken$channel == "Producer-Retailer" &
                        broken$stage == 2] <- 2200
diagnostics <- validate_market_channel(as_market_channel(broken))
stopifnot(any(diagnostics$code == "broken_price_link"))

rupee <- consumer_rupee(fit)
rupee_sum <- tapply(rupee$percent, rupee$channel, sum)
stopifnot(all(abs(rupee_sum - 100) < 1e-10))

# Ranking, uncertainty, sensitivity, targets, and loss adjustment.
ranking <- rank_channels(fit)
stopifnot(inherits(ranking, "agriME_ranking"))
stopifnot(ranking$channel[ranking$rank == 1] == "Direct")
stopifnot(abs(sum(attr(ranking, "weights")) - 1) < 1e-12)

data(market_observations)
set.seed(77)
old_seed <- .Random.seed
boot <- bootstrap_marketing_metrics(
  market_observations,
  marketing_margin = "marketing_margin",
  channel = "channel",
  weight = "volume_qtl",
  R = 30,
  seed = 123
)
stopifnot(identical(old_seed, .Random.seed))
stopifnot(inherits(boot, "agriME_bootstrap"))
stopifnot(nrow(boot$summary) == 24L)
stopifnot(all(boot$summary$conf_low <= boot$summary$conf_high, na.rm = TRUE))

sens <- marketing_sensitivity(
  1900, 3150, 510, 740,
  producer_change = c(0, 0.05),
  cost_change = c(-0.1, 0, 0.1)
)
stopifnot(inherits(sens, "agriME_sensitivity"), nrow(sens) == 6L)
target <- efficiency_target(
  target = 2,
  method = "acharya",
  solve_for = "marketing_cost",
  producer_price = 1900,
  marketing_margin = 740
)
stopifnot(isTRUE(all.equal(target$required_value, 210)))

loss <- loss_adjusted_margin(20, 28, 100, 92, 180, "lot")
stopifnot(
  loss$loss_quantity == 8,
  isTRUE(all.equal(loss$loss_percent, 8)),
  loss$net_margin_total == 396
)

# All base-graphics methods execute on a non-interactive device.
plot_file <- tempfile(fileext = ".pdf")
grDevices::pdf(plot_file)
plot(fit, type = "decomposition")
plot(fit, type = "efficiency")
plot(fit, type = "producer_share")
plot(ranking)
plot(boot, metric = "acharya_efficiency")
plot(sens, metric = "acharya_efficiency")
grDevices::dev.off()
stopifnot(file.exists(plot_file), file.info(plot_file)$size > 0)
unlink(plot_file)