tests/testthat/test-one_day.R

In IhsanKhaliq/ascotraceR: Simulate the Spread of Ascochyta Blight in Chickpea

# import and define data
seeding_rate <- as.integer(40)
primary_infection_foci <- data.table(x = 50,
                                     y = 50)

paddock <- CJ(x = 1:100,
              y = 1:100)

# initialise daily_vals
paddock[, c("new_gp",
            # Change in the number of growing points since last iteration
            "susceptible_gp",
            "exposed_gp",
            "infectious_gp") :=
          list(
            seeding_rate,
            fifelse(
              x == primary_infection_foci[, x] &
                y == primary_infection_foci[, y],
              seeding_rate - 1,
              seeding_rate
            ),
            0,
            fifelse(x == primary_infection_foci[, x] &
                      y == primary_infection_foci[, y], 1,
                    0)
          )]

max_gp_lim <- 15000
max_new_gp <- 350

spore_interception_parameter <-
  0.00006 * (max_gp_lim / max_new_gp)

max_gp <- max_gp_lim * (1 - exp(-0.138629 * seeding_rate))

# set the iteration date
od_t1_i_date <- as.POSIXct("1998-05-12", tz = "Australia/Perth")

daily_vals_list <-
  list(
    paddock = paddock,
    # data.table each row is a 1 x 1m coordinate
    i_date = od_t1_i_date,
    # day of the simulation (iterator)
    i_day = 1,
    day = yday(od_t1_i_date),
    # day of the year
    cdd = 0,
    # cumulative degree days
    cwh = 0,
    # cumulative wet hours
    cr = 0,
    # cumulative rainfall
    gp_standard = seeding_rate,
    # standard number of growing points for 1m^2 if not inhibited by infection (refUninfectiveGrowingPoints)
    new_gp = seeding_rate,
    # new number of growing points for current iteration (refNewGrowingPoints)
    infected_coords = primary_infection_foci,
    # data.frame
    exposed_gps = data.table() # data.table of infected growing points still in latent period and not sporilating (exposed_gp)
  )


# begin testing
set.seed(666)
test1 <- one_day(
  i_date = od_t1_i_date,
  daily_vals = daily_vals_list,
  weather_dat = newM_weather,
  gp_rr = 0.0065,
  max_gp = max_gp,
  spore_interception_parameter = spore_interception_parameter,
  spores_per_gp_per_wet_hour = 0.22
)


test_that("one_day single infection foci returns expected output", {
  expect_silent(test1[["paddock"]]) # This line is here due to https://github.com/Rdatatable/data.table/issues/869
  test1[["paddock"]]
  expect_is(test1, "list")
  expect_length(test1, 11)
  expect_equal(
    names(test1),
    c(
      "paddock",
      "i_date",
      "i_day",
      "day",
      "cdd",
      "cwh",
      "cr",
      "gp_standard",
      "new_gp",
      "infected_coords",
      "exposed_gps"
    )
  )
  expect_equal(test1[["i_date"]], od_t1_i_date)
  expect_equal(test1[["i_day"]], 1)
  expect_equal(test1[["day"]], 132)
  expect_equal(test1[["cdd"]], 18)
  expect_equal(test1[["cwh"]], 15)
  expect_equal(test1[["cr"]], 78.85)
  expect_equal(test1[["gp_standard"]], 45)
  expect_equal(test1[["new_gp"]], test1[["gp_standard"]] - seeding_rate)
  expect_equal(test1[["exposed_gps"]],
               data.table(
                 x = c(50, 50),
                 y = c(50, 51),
                 spores_per_packet = c(1, 1),
                 cdd_at_infection = c(18, 18)
               ))
  expect_s3_class(test1[["paddock"]], "data.table")
  expect_equal(
    colnames(test1[["paddock"]]),
    c("x",
      "y",
      "new_gp",
      "susceptible_gp",
      "exposed_gp",
      "infectious_gp"
    )
  )
  expect_equal(test1[["paddock"]][, unique(new_gp)],
               c(5, 4))
  expect_equal(test1[["paddock"]][, unique(susceptible_gp)],
               c(45, 43))
  expect_equal(test1[["paddock"]][, unique(exposed_gp)], c(0, 1),
               tolerance = 0.001)
  expect_equal(test1[["paddock"]][, unique(infectious_gp)], c(0, 1),
               tolerance = 0.001)
})

test2 <- one_day(
  i_date = od_t1_i_date,
  daily_vals = test1,
  # add to test1 daily vals
  weather_dat = newM_weather,
  gp_rr = 0.0065,
  max_gp = max_gp,
  spore_interception_parameter = spore_interception_parameter,
  spores_per_gp_per_wet_hour = 0.22
)

test_that("one_day test2 repeat using test1 single infection foci returns expected output",
          {
            expect_silent(test2[["paddock"]]) # This line is here due to https://github.com/Rdatatable/data.table/issues/869
            test2[["paddock"]]
            expect_is(test2, "list")
            expect_length(test2, 11)
            expect_equal(
              names(test2),
              c(
                "paddock",
                "i_date",
                "i_day",
                "day",
                "cdd",
                "cwh",
                "cr",
                "gp_standard",
                "new_gp",
                "infected_coords",
                "exposed_gps"
              )
            )
            expect_equal(test2[["i_date"]], od_t1_i_date)
            expect_equal(test2[["i_day"]], 1)
            expect_equal(test2[["day"]], 132)
            expect_equal(test2[["cdd"]], sum(18, 18))
            expect_equal(test2[["cwh"]], sum(15, 15))
            expect_equal(test2[["cr"]], sum(78.85, 78.85))
            expect_equal(test2[["gp_standard"]], sum(45, 5),
                         tolerance = 0.001)
            expect_equal(test2[["new_gp"]], 5)
            expect_equal(test2[["exposed_gps"]],
                         data.table(
                           x = c(50, 50),
                           y = c(50, 51),
                           spores_per_packet = c(1, 1),
                           cdd_at_infection = c(18, 18)
                         ))
            expect_s3_class(test2[["paddock"]], "data.table")
            expect_equal(
              colnames(test2[["paddock"]]),
              c("x",
                "y",
                "new_gp",
                "susceptible_gp",
                "exposed_gp",
                "infectious_gp"
              )
            )
            expect_equal(test2[["paddock"]][, unique(new_gp)],
                         5)
            expect_equal(test2[["paddock"]][, unique(susceptible_gp)],
                         c(50, 48))
            expect_equal(test2[["paddock"]][, unique(exposed_gp)], c(0,1),
                         tolerance = 0.001)
            expect_equal(test2[["paddock"]][, unique(infectious_gp)],
                         c(0, 1), tolerance = 0.001)
          })

# update cumulative degree days to past threshold
test2[["cdd"]] <- 201

test3 <- one_day(
  i_date = od_t1_i_date,
  daily_vals = test2,
  # add to test1 daily vals
  weather_dat = newM_weather,
  gp_rr = 0.0065,
  max_gp = max_gp,
  spore_interception_parameter = spore_interception_parameter,
  spores_per_gp_per_wet_hour = 0.22
)

test_that("one_day test3 adds to cumulative degree days and passes latent period",
          {
            expect_silent(test3[["paddock"]])
            test3[["paddock"]]
            expect_is(test3, "list")
            expect_length(test3, 11)
            expect_equal(
              names(test3),
              c(
                "paddock",
                "i_date",
                "i_day",
                "day",
                "cdd",
                "cwh",
                "cr",
                "gp_standard",
                "new_gp",
                "infected_coords",
                "exposed_gps"
              )
            )
            expect_equal(test3[["i_date"]], od_t1_i_date)
            expect_equal(test3[["i_day"]], 1)
            expect_equal(test3[["day"]], 132)
            expect_equal(test3[["cdd"]], 219)
            expect_equal(test3[["cwh"]], 15 + 15 + 15)
            expect_equal(test3[["cr"]], 78.85 + 78.85 + 78.85)
            expect_equal(test3[["gp_standard"]], sum(45,
                                                     5,
                                                     5))
            expect_equal(test3[["new_gp"]], 5)
            expect_equal(
              test3[["exposed_gps"]],
              data.table(
                data.table(
                  x = c(50),
                  y = c(50),
                  spores_per_packet = c(1),
                  cdd_at_infection = c(219)
                )
              )
            )
            expect_s3_class(test3[["paddock"]], "data.table")

            expect_equal(test3[["paddock"]][, unique(new_gp)],
                         c(5,6))
            expect_equal(test3[["paddock"]][, unique(susceptible_gp)],
                         c(55, 52))
            expect_equal(test3[["paddock"]][, unique(exposed_gp)], c(0, 1),
                         tolerance = 0.001)
            expect_equal(test3[["paddock"]][, unique(infectious_gp)],
                         c(0, 2, 1), tolerance = 0.1)
          })