def test_get_data(self):
# without renaming data should remain as is
experiment = basico.get_data_from_experiment(0, rename_headers=False)
self.assertEqual([
'# Time', 'Values[F16BP_obs]', 'Values[Glu_obs]',
'Values[Pyr_obs]', '[Glc(ext)]_0', 'Unnamed: 5'
], list(experiment.columns))
self.assertEqual((101, 6), experiment.shape)
# data should be renamed as expected, and unassigned columns dropped
experiment = basico.get_data_from_experiment(0, rename_headers=True)
self.assertEqual([
'Time', '[Fru1,6-P2]', '[Glc(int)]', '[pyruvate]', '[Glc(ext)]_0'
], list(experiment.columns))
self.assertEqual((101, 5), experiment.shape)
self.assertEqual(0, experiment.iloc[0][0])
self.assertEqual(2, experiment.iloc[100][0])
# now simulate
exp, sim = basico.get_simulation_results()
self.assertTrue(len(exp) == len(sim) == 2)
# ensure that simulations are different
self.assertGreater(
float(((sim[0][['Fru1,6-P2']] - sim[1][['Fru1,6-P2']])**2).sum()),
10)
def simulate_without_noise(self):
"""Simulate the PEtab problem.
This is an abstract method that should be implemented with a simulation
package. Examples of this are referenced in the class docstring.
:return:
Simulated data, as a PEtab measurements table, which should be
equivalent to replacing all values in the `petab.C.MEASUREMENT`
column of the measurements table (of the PEtab problem supplied to
the `__init__` method), with simulated values.
:rtype: pandas.DataFrame
"""
simulation_results = basico.get_simulation_results(
values_only=True, solution=self.evaluate())
return create_simulation_df(self.petab_problem.measurement_df,
simulation_results)
def evaluate_model(test_model, evaluation=default_evaluation, temp_dir=None, delete_temp_files=True,
sim_dfs=None, sol_dfs=None, temp_files=None):
"""evaluates the given test model and updates it with the calculated metrics and estimated parameters
:param test_model: the model to test
:type test_model: petab_select.Model
:param evaluation: optional function to evaluate the test model with. defaults to func:`.default_evaluation`
:type evaluation: () -> pandasDataFrame
:param temp_dir: optional temp directory to store the files in (otherwise the os temp dir will be used)
:type temp_dir: str or None
:param delete_temp_files: boolean indicating whether temp files should be deleted
:type delete_temp_files: bool
:param sim_dfs: optional array, in which simulation data frames will be returned
:type sim_dfs: [] or None
:param sol_dfs: optional array in which found parameters will be returned
:type sol_dfs: [] or None
:param temp_files: optional array that returns filenames of temp files created during the run
:type temp_files: [] or None
:return: COPASI objective value of the evaluation
:rtype: float
"""
# create petab problem
pp = test_model.to_petab()['petab_problem']
created_temp_dir = False
if temp_dir is None:
temp_dir = tempfile.mkdtemp()
created_temp_dir = True
if not os.path.exists(temp_dir):
os.makedirs(temp_dir, exist_ok=True)
model_id = test_model.model_id
files = core.write_problem_to(pp, temp_dir, model_id)
# load into basico
out_name = 'cps_{0}'.format(model_id)
cps_file = os.path.join(temp_dir, out_name + '.cps')
core.load_petab(files['problem'], temp_dir, out_name)
files = list(files.values())
files.append(cps_file)
files = files + basico.get_experiment_filenames()
# run parameter estimation
sol = evaluation()
if sol_dfs:
sol_dfs.append(sol)
simulation_results = basico.get_simulation_results(values_only=True, solution=sol)
basico.prune_simulation_results(simulation_results)
sim_df = basico.petab.create_simulation_df(pp.measurement_df, simulation_results)
if sim_dfs:
sim_dfs.append(sim_df)
# compute metrics
llh = basico.petab.petab_llh(pp, sim_df)
test_model.set_criterion(Criterion.LLH, llh)
task = basico.get_current_model().getTask("Parameter Estimation")
prob = task.getProblem()
obj = prob.getSolutionValue()
test_model.compute_criterion(Criterion.AIC)
test_model.compute_criterion(Criterion.AICC)
test_model.compute_criterion(Criterion.BIC)
# update estimated parameters
for param_id in test_model.parameters:
value = test_model.parameters[param_id]
if str(value) != 'estimate': # not isnan(value): # we only want to include what we estimated
continue
name = 'Values[{0}]'.format(param_id)
if name in sol.index:
test_model.estimated_parameters[param_id] = sol.loc[name].sol
# write result for testing
result_file = os.path.join(temp_dir, 'result_{0}.yaml'.format(model_id))
files.append(result_file)
test_model.to_yaml(result_file)
# delete temp files if needed
if delete_temp_files:
for file in files:
os.remove(file)
if created_temp_dir:
# since we created the temp dir, lets get rid of it
os.rmdir(temp_dir)
elif temp_files is not None:
# add temp files to the list of temp files:
temp_files = temp_files + files
return obj
def test_get_plotting_data(self):
exp, sim = basico.get_simulation_results()
self.assertTrue(len(exp) == len(sim))
exp, sim = basico.get_simulation_results(values_only=True)
self.assertListEqual(exp[0].Time.to_list(),
sim[0].reset_index().Time.to_list())
def test_current_solution(self):
result = basico.get_simulation_results()
self.assertTrue(len(result) == 2)
self.assertTrue(len(result[0]) == len(result[0]))
def test_get_plotting_data(self):
exp, sim = basico.get_simulation_results()
self.assertTrue(len(exp) == len(sim))