R Under development (unstable) (2026-08-25 r90448 ucrt) -- "Unsuffered Consequences"
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> 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()
null device 
          1 
> stopifnot(file.exists(plot_file), file.info(plot_file)$size > 0)
> unlink(plot_file)
> 
> 
> proc.time()
   user  system elapsed 
   0.40    0.06    0.45