def test_autozi():
data = synthetic_iid(n_batches=1)
for disp_zi in ["gene", "gene-label"]:
autozivae = AUTOZI(
data,
dispersion=disp_zi,
zero_inflation=disp_zi,
)
autozivae.train(1, lr=1e-2)
autozivae.get_elbo(indices=autozivae.test_indices)
autozivae.get_reconstruction_error(indices=autozivae.test_indices)
autozivae.get_marginal_ll(indices=autozivae.test_indices)
autozivae.get_alphas_betas()
def test_autozi():
data = synthetic_iid(n_batches=1)
for disp_zi in ["gene", "gene-label"]:
autozivae = AUTOZI(
data,
dispersion=disp_zi,
zero_inflation=disp_zi,
)
autozivae.train(1, plan_kwargs=dict(lr=1e-2), check_val_every_n_epoch=1)
assert len(autozivae.history["elbo_train"]) == 1
assert len(autozivae.history["elbo_validation"]) == 1
autozivae.get_elbo(indices=autozivae.validation_indices)
autozivae.get_reconstruction_error(indices=autozivae.validation_indices)
autozivae.get_marginal_ll(indices=autozivae.validation_indices, n_mc_samples=3)
autozivae.get_alphas_betas()
def test_autozi():
data = synthetic_iid(n_batches=1)
for disp_zi in ["gene", "gene-label"]:
autozivae = AUTOZI(
data,
dispersion=disp_zi,
zero_inflation=disp_zi,
)
autozivae.train(1, lr=1e-2, frequency=1)
assert len(autozivae.history["elbo_train_set"]) == 2
assert len(autozivae.history["elbo_test_set"]) == 2
autozivae.get_elbo(indices=autozivae.test_indices)
autozivae.get_reconstruction_error(indices=autozivae.test_indices)
autozivae.get_marginal_ll(indices=autozivae.test_indices)
autozivae.get_alphas_betas()
def test_autozi():
data = synthetic_iid(n_batches=1, run_setup_anndata=False)
AUTOZI.setup_anndata(
data,
batch_key="batch",
labels_key="labels",
)
for disp_zi in ["gene", "gene-label"]:
autozivae = AUTOZI(
data,
dispersion=disp_zi,
zero_inflation=disp_zi,
)
autozivae.train(1,
plan_kwargs=dict(lr=1e-2),
check_val_every_n_epoch=1)
assert len(autozivae.history["elbo_train"]) == 1
assert len(autozivae.history["elbo_validation"]) == 1
autozivae.get_elbo(indices=autozivae.validation_indices)
autozivae.get_reconstruction_error(
indices=autozivae.validation_indices)
autozivae.get_marginal_ll(indices=autozivae.validation_indices,
n_mc_samples=3)
autozivae.get_alphas_betas()
# Model library size.
for disp_zi in ["gene", "gene-label"]:
autozivae = AUTOZI(
data,
dispersion=disp_zi,
zero_inflation=disp_zi,
use_observed_lib_size=False,
)
autozivae.train(1,
plan_kwargs=dict(lr=1e-2),
check_val_every_n_epoch=1)
assert hasattr(autozivae.module, "library_log_means") and hasattr(
autozivae.module, "library_log_vars")
assert len(autozivae.history["elbo_train"]) == 1
assert len(autozivae.history["elbo_validation"]) == 1
autozivae.get_elbo(indices=autozivae.validation_indices)
autozivae.get_reconstruction_error(
indices=autozivae.validation_indices)
autozivae.get_marginal_ll(indices=autozivae.validation_indices,
n_mc_samples=3)
autozivae.get_alphas_betas()