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Added testing template.
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R/test-step_naomit2.R

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library(dplyr)
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library(epiprocess)
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library(parsnip)
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library(workflows)
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# Random generated dataset
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set.seed(100)
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x <- tibble(geo_value = rep("nowhere",200),
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time_value = as.Date("2021-01-01") + 0:199,
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case_rate = rpois(100,20) + 1:200,
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death_rate = rpois(100,10) + 1:200) %>%
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as_epi_df()
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slm_fit <- function(recipe, data = x) {
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workflow() %>%
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add_recipe(recipe) %>%
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add_model(linear_reg()) %>%
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fit(data = data)
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}
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# Tests
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test_that("Check that epi_ahead shifts properly", {
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r1 <- epi_recipe(x) %>%
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step_epi_ahead(death_rate, ahead = 7) %>%
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step_epi_lag(death_rate, lag = -7) %>%
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step_naomit(all_predictors()) %>%
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step_naomit(all_outcomes(), skip = TRUE)
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slm_fit1 <- slm_fit(r1)
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slope_ahead <- slm_fit1$fit$fit$fit$coefficients[[2]]
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expect_equal(slope_ahead,1)
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})
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test_that("Check that epi_lag shifts properly", {
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r2 <- epi_recipe(x) %>%
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step_epi_ahead(death_rate, ahead = -7) %>%
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step_epi_lag(death_rate, lag = 7) %>%
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step_naomit(all_predictors()) %>%
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step_naomit(all_outcomes(), skip = TRUE)
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slm_fit2 <- slm_fit(r2)
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slope_lag <- slm_fit2$fit$fit$fit$coefficients[[2]]
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expect_equal(slope_lag,1)
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})
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test_that("Check for non-integer values", {
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r3 <- epi_recipe(x) %>%
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step_epi_ahead(death_rate, ahead = 3.6) %>%
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step_epi_lag(death_rate, lag = 1.9)
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expect_error(
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slm_fit(r3)
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)
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})
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test_that("Check for duplicate values", {
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r4 <- epi_recipe(x) %>%
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step_epi_ahead(death_rate, ahead = 7) %>%
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step_epi_lag(death_rate, lag = 7) %>%
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step_epi_lag(death_rate, lag = 7)
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expect_error(
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slm_fit(r4)
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)
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})

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