tests/testthat/_snaps/check_enough_data.md

In cmu-delphi/epipredict: Basic epidemiology forecasting methods

check_enough_data works on pooled data

Code
  epi_recipe(toy_epi_df) %>% check_enough_data(x, y, min_observations = 2 * n + 1,
  drop_na = FALSE) %>% prep(toy_epi_df)
Condition
  Error in `check_enough_data_core()`:
  ! The following columns don't have enough data to train: x and y.

Code
  epi_recipe(toy_epi_df) %>% check_enough_data(x, y, min_observations = 2 * n - 1,
  drop_na = TRUE) %>% prep(toy_epi_df)
Condition
  Error in `check_enough_data_core()`:
  ! The following columns don't have enough data to train: x.

check_enough_data works on unpooled data

Code
  epi_recipe(toy_epi_df) %>% check_enough_data(x, y, min_observations = n + 1,
  epi_keys = "geo_value", drop_na = FALSE) %>% prep(toy_epi_df)
Condition
  Error in `check_enough_data_core()`:
  ! The following columns don't have enough data to train: x and y.

Code
  epi_recipe(toy_epi_df) %>% check_enough_data(x, y, min_observations = 2 * n - 3,
  epi_keys = "geo_value", drop_na = TRUE) %>% prep(toy_epi_df)
Condition
  Error in `check_enough_data_core()`:
  ! The following columns don't have enough data to train: x and y.

check_enough_data only checks train data when skip = FALSE

Code
  forecaster %>% predict(new_data = toy_test_data %>% filter(time_value >
    "2020-01-08"))
Condition
  Error in `check_enough_data_core()`:
  ! The following columns don't have enough data to predict: x.

check_enough_data works with all_predictors() downstream of constructed terms

Code
  epi_recipe(toy_epi_df) %>% step_epi_lag(x, lag = c(1, 2)) %>% check_enough_data(
    all_predictors(), y, min_observations = 2 * n - 4) %>% prep(toy_epi_df)
Condition
  Error in `check_enough_data_core()`:
  ! The following columns don't have enough data to train: no single column, but the combination of lag_1_x, lag_2_x, y.

cmu-delphi/epipredict documentation built on June 14, 2025, 2:41 a.m.