def test_hdf5_load(self):
hdf5_summary = "celltype_summary.hdf5"
orig_ast = Astir(self.expr, self.marker_dict)
orig_ast.fit_type(max_epochs=5, n_init=1, n_init_epochs=1)
orig_ast.fit_state(max_epochs=5, n_init=1, n_init_epochs=1)
orig_ast.save_models(hdf5_summary)
new_ast = Astir()
new_ast.load_model(hdf5_summary)
orig_type_run_info = orig_ast.get_type_run_info()
orig_state_run_info = orig_ast.get_state_run_info()
new_type_run_info = new_ast.get_type_run_info()
new_state_run_info = new_ast.get_state_run_info()
for key, val in orig_type_run_info.items():
if val != new_type_run_info[key]:
raise AssertionError(
"variable " + key +
" is different in original model and loaded model")
for key, val in orig_state_run_info.items():
if val != new_state_run_info[key]:
raise AssertionError(
"variable " + key +
" is different in original model and loaded model")
orig_type_losses = orig_ast.get_type_losses()
orig_state_losses = orig_ast.get_state_losses()
new_type_losses = new_ast.get_type_losses()
new_state_losses = new_ast.get_state_losses()
if not (all(orig_type_losses == new_type_losses)
and all(orig_state_losses == new_state_losses)):
raise AssertionError(
"loss is different in original model and loaded model")
def test_cellstate_diff_seed_diff_result(self):
"""Test whether the loss after one epoch one two different models
with the different random seed have different losses after one epoch
"""
warnings.filterwarnings("ignore", category=UserWarning)
model1 = Astir(
input_expr=self.expr,
marker_dict=self.marker_dict,
design=None,
random_seed=42,
)
model2 = Astir(
input_expr=self.expr,
marker_dict=self.marker_dict,
design=None,
random_seed=1234,
)
model1.fit_state(max_epochs=5)
model1_loss = model1.get_state_losses()
model2.fit_state(max_epochs=5)
model2_loss = model2.get_state_losses()
self.assertFalse(np.abs(model1_loss - model2_loss)[-1] < 1e-6)