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()