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context("fit_photosynthesis()")
library(photosynthesis)
test_that("'fit_photosynthesis()' accepts data.frames and tibbles", {
df1 = data.frame(
.A = c(10, 9.5, 8, 3.5, 2.5, 2.0, 1, 0.2),
.Q = c(1500, 750, 375, 125, 100, 75, 50, 25)
)
df2 = tibble::as_tibble(df1)
f1 = suppressMessages(fit_photosynthesis(.data = df1, .photo_fun = "aq_response"))
f2 = suppressMessages(fit_photosynthesis(.data = df2, .photo_fun = "aq_response"))
expect_equal(coef(f1), coef(f2))
})
test_that(".vars argument renames variables", {
df1 = data.frame(
.A = c(10, 9.5, 8, 3.5, 2.5, 2.0, 1, 0.2),
.Q = c(1500, 750, 375, 125, 100, 75, 50, 25)
)
df2 = dplyr::rename(df1, Photo = .A)
df3 = dplyr::rename(df1, PPFD = .Q)
df4 = dplyr::rename(df1, Photo = .A, PPFD = .Q)
expect_error({fit_photosynthesis(.data = df2, .photo_fun = "aq_response")})
expect_error({fit_photosynthesis(.data = df3, .photo_fun = "aq_response")})
expect_error({fit_photosynthesis(.data = df4, .photo_fun = "aq_response")})
f1 = suppressMessages(
fit_photosynthesis(.data = df2, .photo_fun = "aq_response",
.vars = list(.A = Photo))
)
f2 = suppressMessages(fit_photosynthesis(.data = df3, .photo_fun = "aq_response",
.vars = list(.Q = PPFD))
)
f3 = suppressMessages(
fit_photosynthesis(.data = df4, .photo_fun = "aq_response",
.vars = list(.A = Photo, .Q = PPFD))
)
expect_equal(coef(f1), coef(f2))
expect_equal(coef(f2), coef(f3))
expect_error({fit_photosynthesis(.data = df2, .photo_fun = "aq_response",
.vars = list(.A = foo))})
expect_error({fit_photosynthesis(.data = df3, .photo_fun = "aq_response",
.vars = list(.Q = bar))})
f4 = suppressMessages(
fit_photosynthesis(.data = dplyr::mutate(df4, A1 = Photo),
.photo_fun = "aq_response",
.vars = list(.A = Photo, .Q = PPFD))
)
expect_equal(coef(f3), coef(f4))
})
df1 = data.frame(
.A = c(10, 9.5, 8, 3.5, 2.5, 2.0, 1, 0.2),
.Q = c(1500, 750, 375, 125, 100, 75, 50, 25)
)
fit = fit_photosynthesis(
.data = df1,
.photo_fun = "aq_response",
.model = "marshall_biscoe_1980"
)
test_that("marshall_biscoe_1980 output", {
expect_is(object = fit, class = "nls")
})
fit = fit_photosynthesis(
.data = df1,
.photo_fun = "aq_response",
.model = "photoinhibition"
)
test_that("photoinhibition output", {
expect_is(object = fit, class = "nls")
})
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