test_that("with phenotype, with superpops", {
expect_equal(1 + 1, 2) # Prevents testthat warning for empty test
if (!plinkr::is_on_ci()) return()
if (!is_gcae_script_fixed()) return()
remove_gcaer_tempfolder()
# This test goes through the full workflow.
# It is not broken up into small pieces, as each 'small piece'
# takes multiple seconds to run.
#
# 1. Setup
# 2. Train
# 3. Project
# 4. Plot
# 1. Setup
Sys.time()
gcae_options <- create_gcae_options()
gcae_setup <- create_test_gcae_setup(
superpops = get_gcaer_filename("gcae_input_files_1_labels.csv")
)
# 2. Train, approx 31 secs
Sys.time()
train_filenames <- gcae_train(
gcae_setup = gcae_setup,
epochs = 1,
save_interval = 1,
verbose = TRUE
)
expect_true(all(file.exists(train_filenames)))
# 3. Project, takes approx 22 secs
Sys.time()
project_filenames <- gcae_project(
gcae_setup = gcae_setup,
gcae_options = gcae_options,
verbose = TRUE
)
Sys.time()
project_results <- parse_project_files(project_filenames)
expect_equal(
names(project_results),
c("losses_from_project_table", "genotype_concordances_table")
)
# 4. Plot
Sys.time()
plot_filenames <- gcae_plot( # Takes approx 18 secs
gcae_setup = gcae_setup,
gcae_options = gcae_options,
verbose = TRUE
)
Sys.time()
expect_true(all(file.exists(plot_filenames)))
# 5. Evaluate
gcae_evaluate( # Takes approx 19 secs
gcae_setup = gcae_setup,
gcae_options = gcae_options,
metrics = "f1_score_3",
epoch = 1,
verbose = TRUE
)
Sys.time()
})
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