def test_exec_sed_task_negative_initial_time(self):
task = Task(
id='task',
model=Model(
id='model',
source=os.path.join(self.EXAMPLES_DIRNAME, 'S1_intro',
'bounce1.txt'),
language=ModelLanguage.Smoldyn.value,
),
simulation=UniformTimeCourseSimulation(
initial_time=-0.01,
output_start_time=-0.01,
output_end_time=0.09,
number_of_points=10,
algorithm=Algorithm(kisao_id='KISAO_0000057', )),
)
variables = [
Variable(id='time', symbol=Symbol.time.value, task=task),
Variable(id='red', target='molcount red', task=task),
Variable(id='green', target='molcount green', task=task),
]
results, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables)
self.assertEqual(set(results.keys()), set(['time', 'red', 'green']))
numpy.testing.assert_allclose(results['time'],
numpy.linspace(-0.01, 0.09, 11),
rtol=5e-6)
def test_create_actions_for_simulation(self):
# CVODE
simulation = UniformTimeCourseSimulation(
initial_time=0.,
output_start_time=10.,
output_end_time=20.,
number_of_points=10,
algorithm=Algorithm(kisao_id='KISAO_0000019',
changes=[
AlgorithmParameterChange(
kisao_id='KISAO_0000211',
new_value='1e-6'),
]),
)
actions, _ = create_actions_for_simulation(simulation)
self.assertEqual(actions, [
'generate_network({overwrite => 1})',
'simulate({t_start => 0.0, t_end => 20.0, n_steps => 20, method => "ode", atol => 1e-6})',
])
# Error handling: non-integer steps
simulation.output_end_time = 20.1
with self.assertRaisesRegex(NotImplementedError,
'must specify an integer number of steps'):
create_actions_for_simulation(simulation)
# Error handling: non-zero initial time
simulation.output_end_time = 20.0
simulation.initial_time = 5.
simulation.algorithm.kisao_id = 'KISAO_0000019'
create_actions_for_simulation(simulation)
simulation.initial_time = 5.
simulation.algorithm.kisao_id = 'KISAO_0000263'
with self.assertRaisesRegex(NotImplementedError, 'must be 0'):
create_actions_for_simulation(simulation)
# Error handling: unknown algorithm
simulation.algorithm.kisao_id = 'KISAO_0000448'
with self.assertRaisesRegex(AlgorithmCannotBeSubstitutedException,
'No algorithm can be substituted'):
create_actions_for_simulation(simulation)
# Error handling: unknown algorithm parameter
simulation.algorithm.kisao_id = 'KISAO_0000019'
simulation.algorithm.changes[0].kisao_id = 'KISAO_0000001'
with mock.patch.dict('os.environ',
{'ALGORITHM_SUBSTITUTION_POLICY': 'NONE'}):
with self.assertRaisesRegex(
NotImplementedError,
'is not supported. Parameter must have'):
create_actions_for_simulation(simulation)
with mock.patch.dict(
'os.environ',
{'ALGORITHM_SUBSTITUTION_POLICY': 'SIMILAR_VARIABLES'}):
with pytest.warns(BioSimulatorsWarning,
match='is not supported. Parameter must have'):
create_actions_for_simulation(simulation)
def test_add_simulation_to_task(self):
# CVODE
task = Task()
simulation = UniformTimeCourseSimulation(
initial_time=0.,
output_start_time=10.,
output_end_time=20.,
number_of_points=10,
algorithm=Algorithm(
kisao_id='KISAO_0000019',
changes=[
AlgorithmParameterChange(kisao_id='KISAO_0000211', new_value='1e-6'),
]
),
)
add_simulation_to_task(task, simulation)
self.assertEqual(task.actions, [
'generate_network({overwrite => 1})',
'simulate({t_start => 0.0, t_end => 20.0, n_steps => 20, method => "ode", atol => 1e-6})',
])
# Error handling: non-integer steps
simulation.output_end_time = 20.1
with self.assertRaisesRegex(NotImplementedError, 'must specify an integer number of steps'):
add_simulation_to_task(task, simulation)
# Error handling: non-zero initial time
simulation.output_end_time = 20.0
simulation.initial_time = 5.
simulation.algorithm.kisao_id = 'KISAO_0000019'
add_simulation_to_task(task, simulation)
simulation.initial_time = 5.
simulation.algorithm.kisao_id = 'KISAO_0000263'
with self.assertRaisesRegex(NotImplementedError, 'must be 0'):
add_simulation_to_task(task, simulation)
# Error handling: unknown algorithm
simulation.algorithm.kisao_id = 'KISAO_0000001'
with self.assertRaisesRegex(NotImplementedError, 'is not supported. Algorithm must have'):
add_simulation_to_task(task, simulation)
# Error handling: unknown algorithm parameter
simulation.algorithm.kisao_id = 'KISAO_0000019'
simulation.algorithm.changes[0].kisao_id = 'KISAO_0000001'
with self.assertRaisesRegex(NotImplementedError, 'is not supported. Parameter must have'):
add_simulation_to_task(task, simulation)
def test_gen_algorithms_from_specs(self):
algs = gen_algorithms_from_specs(
os.path.join(os.path.dirname(__file__), '..', 'fixtures',
'tellurium.json'))
self.assertEqual(len(algs), 5)
self.assertTrue(algs['KISAO_0000086'].is_equal(
Algorithm(
kisao_id='KISAO_0000086',
changes=[
AlgorithmParameterChange(kisao_id='KISAO_0000107',
new_value='true'),
AlgorithmParameterChange(kisao_id='KISAO_0000485',
new_value='1e-12'),
AlgorithmParameterChange(kisao_id='KISAO_0000467',
new_value='1.0'),
],
), ))
def test_does_simulator_have_capabilities_to_execute_sed_document(self):
specs = get_simulator_specs('tellurium', 'latest')
doc = SedDocument(tasks=[
Task(model=Model(language=ModelLanguage.SBML.value, ),
simulation=UniformTimeCourseSimulation(
algorithm=Algorithm(kisao_id='KISAO_0000019',
changes=[
AlgorithmParameterChange(
kisao_id='KISAO_0000209')
])))
])
self.assertTrue(
does_simulator_have_capabilities_to_execute_sed_document(
doc,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
doc2 = copy.deepcopy(doc)
doc2.tasks.append(
RepeatedTask(
sub_tasks=[SubTask(task=copy.deepcopy(doc2.tasks[0]))], ))
self.assertTrue(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
doc2 = copy.deepcopy(doc)
doc2.tasks.append(
RepeatedTask(
sub_tasks=[SubTask(task=copy.deepcopy(doc2.tasks[0]))], ))
doc2.tasks[1].sub_tasks[
0].task.model.language = ModelLanguage.CellML.value
self.assertFalse(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
doc2 = copy.deepcopy(doc)
doc2.tasks[0].model.language = ModelLanguage.CellML.value
self.assertFalse(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
doc2 = copy.deepcopy(doc)
doc2.tasks[0].model.language = 'urn:sedml:language:unknown'
self.assertFalse(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
doc2 = copy.deepcopy(doc)
doc2.tasks[0].simulation.algorithm.kisao_id = 'KISAO_0000088'
self.assertFalse(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
doc2 = copy.deepcopy(doc)
doc2.tasks[0].simulation.algorithm.kisao_id = 'KISAO_0000088'
self.assertTrue(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.
SAME_VARIABLES))
doc2 = copy.deepcopy(doc)
doc2.tasks[0].simulation.algorithm.kisao_id = 'KISAO_0000560'
self.assertTrue(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.
SAME_VARIABLES))
doc2 = copy.deepcopy(doc)
doc2.tasks[0].simulation.algorithm.changes[
0].kisao_id = 'KISAO_0000019'
self.assertFalse(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
specs = get_simulator_specs('pysces', 'latest')
doc2 = copy.deepcopy(doc)
doc2.tasks[0].simulation = OneStepSimulation(algorithm=Algorithm(
kisao_id='KISAO_0000019'))
self.assertFalse(
does_simulator_have_capabilities_to_execute_sed_document(
doc2,
specs,
alg_substitution_policy=AlgorithmSubstitutionPolicy.SAME_METHOD
))
def test_exec_sedml_docs_in_archive_without_log(self):
archive = CombineArchive(contents=[
CombineArchiveContent(
location='sim.sedml',
format='http://identifiers.org/combine.specifications/sed-ml',
),
CombineArchiveContent(
location='model.xml',
format='http://identifiers.org/combine.specifications/sbml',
),
], )
sed_doc = SedDocument()
model = Model(id='model_1',
source='model.xml',
language=ModelLanguage.SBML.value)
sed_doc.models.append(model)
sim = UniformTimeCourseSimulation(
id='sim_1',
initial_time=0.,
output_start_time=0.,
output_end_time=10.,
number_of_points=10,
algorithm=Algorithm(kisao_id='KISAO_0000019'))
sed_doc.simulations.append(sim)
task = Task(id='task_1', model=model, simulation=sim)
sed_doc.tasks.append(task)
sed_doc.data_generators.append(
DataGenerator(
id='data_gen_1',
variables=[
Variable(
id='var_1',
target=
"/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Trim']",
target_namespaces={
'sbml': 'http://www.sbml.org/sbml/level2/version4'
},
task=task)
],
math='var_1',
))
sed_doc.data_generators.append(
DataGenerator(
id='data_gen_2',
variables=[
Variable(
id='var_2',
target=
"/sbml:sbml/sbml:model/sbml:listOfSpecies/sbml:species[@id='Clb']",
target_namespaces={
'sbml': 'http://www.sbml.org/sbml/level2/version4'
},
task=task)
],
math='var_2',
))
report = Report(id='output_1')
sed_doc.outputs.append(report)
report.data_sets.append(
DataSet(id='data_set_1',
label='data_set_1',
data_generator=sed_doc.data_generators[0]))
report.data_sets.append(
DataSet(id='data_set_2',
label='data_set_2',
data_generator=sed_doc.data_generators[1]))
archive_dirname = os.path.join(self.tmp_dir, 'archive')
os.makedirs(archive_dirname)
shutil.copyfile(
os.path.join(os.path.dirname(__file__), '..', 'fixtures',
'BIOMD0000000297.xml'),
os.path.join(archive_dirname, 'model.xml'))
SedmlSimulationWriter().run(sed_doc,
os.path.join(archive_dirname, 'sim.sedml'))
archive_filename = os.path.join(self.tmp_dir, 'archive.omex')
CombineArchiveWriter().run(archive, archive_dirname, archive_filename)
def sed_task_executer(task, variables, log=None, config=None):
if log:
log.algorithm = task.simulation.algorithm.kisao_id
log.simulator_details = {
'attrib': 'value',
}
return VariableResults({
'var_1':
numpy.linspace(0., 10., task.simulation.number_of_points + 1),
'var_2':
numpy.linspace(10., 20., task.simulation.number_of_points + 1),
}), log
def sed_task_executer_error(task, variables, log=None, config=None):
raise ValueError('Big error')
out_dir = os.path.join(self.tmp_dir, 'outputs')
config = get_config()
config.REPORT_FORMATS = []
config.VIZ_FORMATS = []
config.COLLECT_COMBINE_ARCHIVE_RESULTS = True
config.LOG = True
# with log
sed_doc_executer = functools.partial(sedml_exec.exec_sed_doc,
sed_task_executer)
results, log = exec.exec_sedml_docs_in_archive(
sed_doc_executer,
archive_filename,
out_dir,
apply_xml_model_changes=False,
config=config)
self.assertEqual(set(results.keys()), set(['sim.sedml']))
self.assertEqual(set(results['sim.sedml'].keys()), set(['output_1']))
self.assertEqual(set(results['sim.sedml']['output_1'].keys()),
set(['data_set_1', 'data_set_2']))
numpy.testing.assert_allclose(
results['sim.sedml']['output_1']['data_set_1'],
numpy.linspace(0., 10., 11))
numpy.testing.assert_allclose(
results['sim.sedml']['output_1']['data_set_2'],
numpy.linspace(10., 20., 11))
self.assertEqual(log.exception, None)
self.assertEqual(
log.sed_documents['sim.sedml'].tasks['task_1'].algorithm,
task.simulation.algorithm.kisao_id)
self.assertEqual(
log.sed_documents['sim.sedml'].tasks['task_1'].simulator_details,
{'attrib': 'value'})
sed_doc_executer = functools.partial(sedml_exec.exec_sed_doc,
sed_task_executer_error)
results, log = exec.exec_sedml_docs_in_archive(
sed_doc_executer,
archive_filename,
out_dir,
apply_xml_model_changes=False,
config=config)
self.assertIsInstance(log.exception, CombineArchiveExecutionError)
config.DEBUG = True
sed_doc_executer = functools.partial(sedml_exec.exec_sed_doc,
sed_task_executer_error)
with self.assertRaisesRegex(ValueError, 'Big error'):
exec.exec_sedml_docs_in_archive(sed_doc_executer,
archive_filename,
out_dir,
apply_xml_model_changes=False,
config=config)
# without log
config.COLLECT_COMBINE_ARCHIVE_RESULTS = False
config.LOG = False
config.DEBUG = False
sed_doc_executer = functools.partial(sedml_exec.exec_sed_doc,
sed_task_executer)
results, log = exec.exec_sedml_docs_in_archive(
sed_doc_executer,
archive_filename,
out_dir,
apply_xml_model_changes=False,
config=config)
self.assertEqual(results, None)
self.assertEqual(log, None)
sed_doc_executer = functools.partial(sedml_exec.exec_sed_doc,
sed_task_executer_error)
with self.assertRaisesRegex(CombineArchiveExecutionError, 'Big error'):
exec.exec_sedml_docs_in_archive(sed_doc_executer,
archive_filename,
out_dir,
apply_xml_model_changes=False,
config=config)
config.DEBUG = True
sed_doc_executer = functools.partial(sedml_exec.exec_sed_doc,
sed_task_executer_error)
with self.assertRaisesRegex(ValueError, 'Big error'):
exec.exec_sedml_docs_in_archive(sed_doc_executer,
archive_filename,
out_dir,
apply_xml_model_changes=False,
config=config)
def test_exec_sed_task_with_changes(self):
task = Task(
id='task',
model=Model(
id='model',
source=os.path.join(os.path.dirname(__file__), 'fixtures',
'lotvolt.txt'),
language=ModelLanguage.Smoldyn.value,
),
simulation=UniformTimeCourseSimulation(
initial_time=0.,
output_start_time=0.,
output_end_time=0.1,
number_of_points=10,
algorithm=Algorithm(kisao_id='KISAO_0000057',
changes=[
AlgorithmParameterChange(
kisao_id='KISAO_0000488',
new_value='10'),
])),
)
model = task.model
sim = task.simulation
variable_ids = ['rabbit', 'fox']
variables = []
for variable_id in variable_ids:
variables.append(
Variable(id=variable_id,
target='molcount ' + variable_id,
task=task))
preprocessed_task = smoldyn.biosimulators.combine.preprocess_sed_task(
task, variables)
results, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
with self.assertRaises(AssertionError):
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results[variable_id][0:int(sim.number_of_points / 2 + 1)],
results[variable_id][-int(sim.number_of_points / 2 + 1):])
# check simulation is repeatable
preprocessed_task = smoldyn.biosimulators.combine.preprocess_sed_task(
task, variables)
results2, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
for variable_id in variable_ids:
numpy.testing.assert_allclose(results2[variable_id],
results[variable_id])
# check simulation is repeatable in two steps
sim.output_end_time = sim.output_end_time / 2
sim.number_of_points = int(sim.number_of_points / 2)
model.changes = []
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='fixmolcount ' + variable_id,
new_value=None))
preprocessed_task = smoldyn.biosimulators.combine.preprocess_sed_task(
task, variables)
model.changes = []
results2, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results2[variable_id],
results[variable_id][0:sim.number_of_points + 1])
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='fixmolcount ' + variable_id,
new_value=results2[variable_id][-1]))
results3, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results3[variable_id],
results[variable_id][-(sim.number_of_points + 1):])
# check model change modifies simulation
model.changes = []
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='fixmolcount ' + variable_id,
new_value=None))
preprocessed_task = smoldyn.biosimulators.combine.preprocess_sed_task(
task, variables)
model.changes = []
results2, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results2[variable_id],
results[variable_id][0:sim.number_of_points + 1])
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='fixmolcount ' + variable_id,
new_value=results2[variable_id][-1] + 1))
results3, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
with self.assertRaises(AssertionError):
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results3[variable_id],
results[variable_id][-(sim.number_of_points + 1):])
# check model change modifies simulation
model.changes = []
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='killmol ' + variable_id,
new_value=None))
preprocessed_task = smoldyn.biosimulators.combine.preprocess_sed_task(
task, variables)
model.changes = []
results2, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results2[variable_id],
results[variable_id][0:sim.number_of_points + 1])
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='killmol ' + variable_id,
new_value=0))
results3, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
with self.assertRaises(AssertionError):
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results3[variable_id],
results[variable_id][-(sim.number_of_points + 1):])
# preprocessing-time change
model.changes = []
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='define K_1', new_value=10))
results2, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables)
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results2[variable_id],
results[variable_id][0:sim.number_of_points + 1])
model.changes = []
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='define K_1', new_value=10))
preprocessed_task = smoldyn.biosimulators.combine.preprocess_sed_task(
task, variables)
with self.assertRaisesRegex(
NotImplementedError,
'can only be changed during simulation preprocessing'):
smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
model.changes = []
results2, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results2[variable_id],
results[variable_id][0:sim.number_of_points + 1])
model.changes = []
for variable_id in variable_ids:
model.changes.append(
ModelAttributeChange(target='define K_1', new_value=0))
preprocessed_task = smoldyn.biosimulators.combine.preprocess_sed_task(
task, variables)
model.changes = []
results2, _ = smoldyn.biosimulators.combine.exec_sed_task(
task, variables, preprocessed_task=preprocessed_task)
with self.assertRaises(AssertionError):
for variable_id in variable_ids:
numpy.testing.assert_allclose(
results2[variable_id],
results[variable_id][0:sim.number_of_points + 1])
def test_exec_sed_task(self):
task = Task(
id='task',
model=Model(
id='model',
source=os.path.join(self.EXAMPLES_DIRNAME, 'S1_intro',
'bounce1.txt'),
language=ModelLanguage.Smoldyn.value,
),
simulation=UniformTimeCourseSimulation(
initial_time=0.,
output_start_time=0.1,
output_end_time=0.2,
number_of_points=10,
algorithm=Algorithm(kisao_id='KISAO_0000057',
changes=[
AlgorithmParameterChange(
kisao_id='KISAO_0000488',
new_value='10'),
])),
)
variables = [
Variable(id='time', symbol=Symbol.time.value, task=task),
Variable(id='red', target='molcount red', task=task),
Variable(id='green', target='molcount green', task=task),
]
results, log = smoldyn.biosimulators.combine.exec_sed_task(
task, variables)
self.assertEqual(set(results.keys()), set(['time', 'red', 'green']))
numpy.testing.assert_allclose(results['time'],
numpy.linspace(0.1, 0.2, 11))
for result in results.values():
self.assertEqual(result.shape, (11, ))
self.assertFalse(numpy.any(numpy.isnan(result)))
self.assertEqual(log.algorithm, 'KISAO_0000057')
self.assertEqual(
log.simulator_details, {
'class': 'smoldyn.Simulation',
'instanceAttributes': {
'setRandomSeed': 10
},
'method': 'run',
'methodArguments': {
'start': 0.,
'stop': 0.2,
'dt': 0.01,
},
})
task.simulation.algorithm.changes.append(
AlgorithmParameterChange('KISAO_0000254', '5'))
results, log = smoldyn.biosimulators.combine.exec_sed_task(
task, variables)
self.assertEqual(
log.simulator_details, {
'class': 'smoldyn.Simulation',
'instanceAttributes': {
'setRandomSeed': 10
},
'method': 'run',
'methodArguments': {
'start': 0.,
'stop': 0.2,
'dt': 0.01,
'accuracy': 5.,
},
})
task.simulation.algorithm.kisao_id = 'KISAO_0000437'
with self.assertRaises(NotImplementedError):
smoldyn.biosimulators.combine.exec_sed_task(task, variables)
def _build_combine_archive(self):
task = Task(
id='task',
model=Model(
id='model',
source='bounce1.txt',
language=ModelLanguage.Smoldyn.value,
),
simulation=UniformTimeCourseSimulation(
id='sim',
initial_time=0.,
output_start_time=0.1,
output_end_time=0.2,
number_of_points=10,
algorithm=Algorithm(kisao_id='KISAO_0000057',
changes=[
AlgorithmParameterChange(
kisao_id='KISAO_0000488',
new_value='10'),
])),
)
variables = [
Variable(id='time', symbol=Symbol.time.value, task=task),
Variable(id='red', target='molcount red', task=task),
Variable(id='green', target='molcount green', task=task),
]
doc = SedDocument(
models=[task.model],
simulations=[task.simulation],
tasks=[task],
data_generators=[
DataGenerator(
id='data_gen_time',
variables=[
Variable(id='var_time',
symbol=Symbol.time.value,
task=task)
],
math='var_time',
),
DataGenerator(
id='data_gen_red',
variables=[
Variable(id='var_red',
target='molcount red',
task=task)
],
math='var_red',
),
DataGenerator(
id='data_gen_green',
variables=[
Variable(id='var_green',
target='molcount green',
task=task)
],
math='var_green',
),
],
)
doc.outputs.append(
Report(id='report',
data_sets=[
DataSet(id='data_set_time',
label='time',
data_generator=doc.data_generators[0]),
DataSet(id='data_set_red',
label='red',
data_generator=doc.data_generators[1]),
DataSet(id='data_set_green',
label='green',
data_generator=doc.data_generators[2]),
]))
archive_dirname = os.path.join(self.dirname, 'archive')
os.makedirs(archive_dirname)
shutil.copyfile(
os.path.join(self.EXAMPLES_DIRNAME, 'S1_intro', 'bounce1.txt'),
os.path.join(archive_dirname, 'bounce1.txt'))
sim_filename = os.path.join(archive_dirname, 'sim_1.sedml')
SedmlSimulationWriter().run(doc, sim_filename)
archive = CombineArchive(contents=[
CombineArchiveContent('bounce1.txt',
CombineArchiveContentFormat.Smoldyn.value),
CombineArchiveContent('sim_1.sedml',
CombineArchiveContentFormat.SED_ML.value),
], )
archive_filename = os.path.join(self.dirname, 'archive.omex')
CombineArchiveWriter().run(archive, archive_dirname, archive_filename)
return doc, archive_filename
def test_get_parameters_variables_for_simulation(self):
params, sims, vars, plots = get_parameters_variables_outputs_for_simulation(self.FIXTURE_FILENAME, None, OneStepSimulation, None)
params, sims, vars, plots = get_parameters_variables_outputs_for_simulation(
self.FIXTURE_FILENAME, None, UniformTimeCourseSimulation, None)
self.assertTrue(params[0].is_equal(ModelAttributeChange(
id='value_parameter_k_1',
name='Value of parameter "k_1"',
target='parameters.k_1.value',
new_value='0.0',
)))
self.assertTrue(params[7].is_equal(ModelAttributeChange(
id='value_parameter_fa',
name='Value of parameter "fa"',
target='parameters.fa.value',
new_value='1E-5',
)))
self.assertTrue(params[9].is_equal(ModelAttributeChange(
id='initial_amount_species_GeneA_00__',
name='Initial amount of species "GeneA_00()"',
target='species.GeneA_00().initialCount',
new_value='1',
)))
self.assertTrue(params[17].is_equal(ModelAttributeChange(
id='expression_function_gfunc',
name='Expression of function "gfunc()"',
target='functions.gfunc.expression',
new_value='(0.5*(Atot^2))/(10+(Atot^2))',
)))
self.assertEqual(len(sims), 5)
self.assertIsInstance(sims[0], UniformTimeCourseSimulation)
expected_sim = UniformTimeCourseSimulation(
id='simulation_0',
initial_time=0.,
output_start_time=0.,
output_end_time=1000000.,
number_of_steps=1000,
algorithm=Algorithm(
kisao_id='KISAO_0000029',
changes=[
AlgorithmParameterChange(
kisao_id='KISAO_0000488',
new_value='2',
)
]
)
)
self.assertTrue(sims[0].is_equal(expected_sim))
self.assertTrue(vars[0].is_equal(Variable(
id='time',
name='Time',
symbol=Symbol.time.value,
)))
self.assertTrue(vars[1].is_equal(Variable(
id='amount_molecule_A__',
name='Dynamics of molecule "A()"',
target='molecules.A().count',
)))
self.assertTrue(vars[9].is_equal(Variable(
id='amount_species_GeneA_00__',
name='Dynamics of species "GeneA_00()"',
target='species.GeneA_00().count',
)))
self.assertEqual(len(vars), 17)
def test_get_parameters_variables_for_simulation_native_data_types(self):
params, sims, vars, plots = get_parameters_variables_outputs_for_simulation(
self.FIXTURE_FILENAME, None, UniformTimeCourseSimulation, None,
native_ids=True, native_data_types=True)
self.assertTrue(params[0].is_equal(ModelAttributeChange(
id='k_1',
name=None,
target='parameters.k_1.value',
new_value=0.0,
)))
self.assertTrue(params[7].is_equal(ModelAttributeChange(
id='fa',
name=None,
target='parameters.fa.value',
new_value=1E-5,
)))
self.assertTrue(params[9].is_equal(ModelAttributeChange(
id='GeneA_00()',
name=None,
target='species.GeneA_00().initialCount',
new_value=1,
)))
self.assertTrue(params[17].is_equal(ModelAttributeChange(
id='gfunc',
name=None,
target='functions.gfunc.expression',
new_value='(0.5*(Atot^2))/(10+(Atot^2))',
)))
self.assertEqual(len(sims), 5)
self.assertIsInstance(sims[0], UniformTimeCourseSimulation)
expected_sim = UniformTimeCourseSimulation(
id='simulation_0',
initial_time=0.,
output_start_time=0.,
output_end_time=1000000.,
number_of_steps=1000,
algorithm=Algorithm(
kisao_id='KISAO_0000029',
changes=[
AlgorithmParameterChange(
kisao_id='KISAO_0000488',
new_value=2,
)
]
)
)
self.assertTrue(sims[0].is_equal(expected_sim))
self.assertTrue(vars[0].is_equal(Variable(
id=None,
name=None,
symbol=Symbol.time.value,
)))
self.assertTrue(vars[1].is_equal(Variable(
id='A()',
name=None,
target='molecules.A().count',
)))
self.assertTrue(vars[9].is_equal(Variable(
id='GeneA_00()',
name=None,
target='species.GeneA_00().count',
)))
self.assertEqual(len(vars), 17)
def export_sed_doc(sed_doc_specs):
""" Export the specifications of SED-ML document to SED-ML
Args:
sed_doc_specs (``SedDocument``)
Returns:
:obj:`SedDocument`
"""
sed_doc = SedDocument(
level=sed_doc_specs['level'],
version=sed_doc_specs['version'],
)
# add styles to SED-ML document
style_id_map = {}
for style_spec in sed_doc_specs['styles']:
style = Style(
id=style_spec.get('id'),
name=style_spec.get('name', None),
)
sed_doc.styles.append(style)
style_id_map[style.id] = style
if style_spec.get('line', None) is not None:
style.line = LineStyle(
type=style_spec['line'].get('type', None),
color=style_spec['line'].get('color', None),
thickness=style_spec['line'].get('thickness', None),
)
if style_spec['line'].get('type', None) is not None:
style.line.type = LineStyleType[style_spec['line']['type']]
if style_spec['line'].get('color', None) is not None:
style.line.color = Color(style_spec['line']['color'])
if style_spec.get('marker', None) is not None:
style.marker = MarkerStyle(
type=style_spec['marker'].get('type', None),
size=style_spec['marker'].get('size', None),
line_color=style_spec['marker'].get('lineColor', None),
line_thickness=style_spec['marker'].get('lineThickness', None),
fill_color=style_spec['marker'].get('fillColor', None),
)
if style_spec['marker'].get('type', None) is not None:
style.marker.type = MarkerStyleType[style_spec['marker']
['type']]
if style_spec['marker'].get('lineColor', None) is not None:
style.marker.line_color = Color(
style_spec['marker']['lineColor'])
if style_spec['marker'].get('fillColor', None) is not None:
style.marker.fill_color = Color(
style_spec['marker']['fillColor'])
if style_spec.get('fill', None) is not None:
style.fill = FillStyle(color=style_spec['fill'].get('color',
None), )
if style_spec['fill'].get('color', None) is not None:
style.fill.color = Color(style_spec['fill']['color'])
for style_spec, style in zip(sed_doc_specs['styles'], sed_doc.styles):
if style_spec.get('base', None) is not None:
style.base = style_id_map.get(style_spec['base'], None)
if style.base is None:
raise BadRequestException(
title='Base style `{}` for style `{}` does not exist'.
format(style_spec['base'], style.id),
instance=ValueError('Style does not exist'),
)
# add models to SED-ML document
model_id_map = {}
for model_spec in sed_doc_specs['models']:
model = Model(
id=model_spec.get('id'),
name=model_spec.get('name', None),
language=model_spec.get('language'),
source=model_spec.get('source'),
)
sed_doc.models.append(model)
model_id_map[model.id] = model
for change_spec in model_spec['changes']:
if change_spec['_type'] == 'SedModelAttributeChange':
change = ModelAttributeChange(
new_value=change_spec.get('newValue'), )
elif change_spec['_type'] == 'SedAddElementModelChange':
change = AddElementModelChange(
new_elements=change_spec.get('newElements'), )
elif change_spec['_type'] == 'SedReplaceElementModelChange':
change = ReplaceElementModelChange(
new_elements=change_spec.get('newElements'), )
elif change_spec['_type'] == 'SedRemoveElementModelChange':
change = RemoveElementModelChange()
elif change_spec['_type'] == 'SedComputeModelChange':
change = ComputeModelChange(
parameters=[],
variables=[],
math=change_spec.get('math'),
)
for parameter_spec in change_spec.get('parameters', []):
change.parameters.append(
Parameter(
id=parameter_spec.get('id'),
name=parameter_spec.get('name', None),
value=parameter_spec.get('value'),
))
for variable_spec in change_spec.get('variables', []):
change.variables.append(
Variable(
id=variable_spec.get('id'),
name=variable_spec.get('name', None),
model=variable_spec.get('model', None),
target=variable_spec.get('target',
{}).get('value', None),
target_namespaces={
namespace['prefix']: namespace['uri']
for namespace in variable_spec.get(
'target', {}).get('namespaces', [])
},
symbol=variable_spec.get('symbol', None),
task=variable_spec.get('task', None),
))
else:
raise BadRequestException(
title='Changes of type `{}` are not supported'.format(
change_spec['_type']),
instance=NotImplementedError('Invalid change'))
change.target = change_spec.get('target').get('value')
for ns in change_spec.get('target').get('namespaces', []):
change.target_namespaces[ns.get('prefix', None)] = ns['uri']
model.changes.append(change)
# add simulations to SED-ML document
simulation_id_map = {}
for sim_spec in sed_doc_specs['simulations']:
if sim_spec['_type'] == 'SedOneStepSimulation':
sim = OneStepSimulation(
id=sim_spec.get('id'),
name=sim_spec.get('name', None),
step=sim_spec.get('step'),
)
elif sim_spec['_type'] == 'SedSteadyStateSimulation':
sim = SteadyStateSimulation(
id=sim_spec.get('id'),
name=sim_spec.get('name', None),
)
elif sim_spec['_type'] == 'SedUniformTimeCourseSimulation':
sim = UniformTimeCourseSimulation(
id=sim_spec.get('id'),
name=sim_spec.get('name', None),
initial_time=sim_spec.get('initialTime'),
output_start_time=sim_spec.get('outputStartTime'),
output_end_time=sim_spec.get('outputEndTime'),
number_of_steps=sim_spec.get('numberOfSteps'),
)
else:
raise BadRequestException(
title='Simulations of type `{}` are not supported'.format(
sim_spec['_type']),
instance=NotImplementedError('Invalid simulation')
) # pragma: no cover: unreachable due to schema validation
alg_spec = sim_spec.get('algorithm')
sim.algorithm = Algorithm(kisao_id=alg_spec.get('kisaoId'))
for change_spec in alg_spec.get('changes'):
sim.algorithm.changes.append(
AlgorithmParameterChange(
kisao_id=change_spec.get('kisaoId'),
new_value=change_spec.get('newValue'),
))
sed_doc.simulations.append(sim)
simulation_id_map[sim.id] = sim
# add tasks to SED-ML document
task_id_map = {}
for task_spec in sed_doc_specs['tasks']:
if task_spec['_type'] == 'SedTask':
model_id = task_spec.get('model')
sim_id = task_spec.get('simulation')
model = model_id_map.get(model_id, None)
sim = simulation_id_map.get(sim_id, None)
if not model:
raise BadRequestException(
title='Model `{}` for task `{}` does not exist'.format(
model_id, task_spec.get('id')),
instance=ValueError('Model does not exist'),
)
if not sim:
raise BadRequestException(
title='Simulation `{}` for task `{}` does not exist'.
format(sim_id, task_spec.get('id')),
instance=ValueError('Simulation does not exist'),
)
task = Task(
id=task_spec.get('id'),
name=task_spec.get('name', None),
model=model,
simulation=sim,
)
else:
# TODO: support repeated tasks
raise BadRequestException(
title='Tasks of type `{}` are not supported'.format(
task_spec['_type']),
instance=NotImplementedError('Invalid task')
) # pragma: no cover: unreachable due to schema validation
sed_doc.tasks.append(task)
task_id_map[task.id] = task
# add data generators to SED-ML document
data_gen_id_map = {}
for data_gen_spec in sed_doc_specs['dataGenerators']:
data_gen = DataGenerator(
id=data_gen_spec.get('id'),
name=data_gen_spec.get('name', None),
math=data_gen_spec.get('math'),
)
for var_spec in data_gen_spec['variables']:
task_id = var_spec.get('task')
task = task_id_map.get(task_id, None)
if not task:
raise BadRequestException(
title='Task `{}` for variable `{}` does not exist'.format(
task_id, var_spec.get('id')),
instance=ValueError('Task does not exist'),
)
var = Variable(
id=var_spec.get('id'),
name=var_spec.get('name', None),
task=task,
symbol=var_spec.get('symbol', None),
)
target_spec = var_spec.get('target', None)
if target_spec:
var.target = target_spec['value']
for ns in target_spec.get('namespaces', []):
var.target_namespaces[ns.get('prefix', None)] = ns['uri']
data_gen.variables.append(var)
sed_doc.data_generators.append(data_gen)
data_gen_id_map[data_gen.id] = data_gen
# add outputs to SED-ML document
for output_spec in sed_doc_specs['outputs']:
if output_spec['_type'] == 'SedReport':
output = Report(
id=output_spec.get('id'),
name=output_spec.get('name', None),
)
for data_set_spec in output_spec['dataSets']:
data_gen_id = data_set_spec['dataGenerator']
data_gen = data_gen_id_map.get(data_gen_id, None)
if not data_gen:
raise BadRequestException(
title=
'Data generator `{}` for output `{}` does not exist'.
format(data_gen_id, output_spec.get('id')),
instance=ValueError('Data generator does not exist'),
)
data_set = DataSet(
id=data_set_spec.get('id'),
name=data_set_spec.get('name', None),
label=data_set_spec.get('label', None),
data_generator=data_gen,
)
output.data_sets.append(data_set)
elif output_spec['_type'] == 'SedPlot2D':
output = Plot2D(
id=output_spec.get('id'),
name=output_spec.get('name', None),
)
for curve_spec in output_spec['curves']:
x_data_gen_id = curve_spec['xDataGenerator']
y_data_gen_id = curve_spec['yDataGenerator']
style_id = curve_spec.get('style', None)
x_data_gen = data_gen_id_map.get(x_data_gen_id, None)
y_data_gen = data_gen_id_map.get(y_data_gen_id, None)
style = style_id_map.get(style_id, None)
if not x_data_gen:
raise BadRequestException(
title=
'X data generator `{}` for curve `{}` does not exist'.
format(x_data_gen_id, output_spec.get('id')),
instance=ValueError('Data generator does not exist'),
)
if not y_data_gen:
raise BadRequestException(
title=
'Y data generator `{}` for curve `{}` does not exist'.
format(y_data_gen_id, output_spec.get('id')),
instance=ValueError('Data generator does not exist'),
)
if style_id is not None and style is None:
raise BadRequestException(
title='Style `{}` for curve `{}` does not exist'.
format(style_id, output_spec.get('id')),
instance=ValueError('Style does not exist'),
)
curve = Curve(
id=curve_spec.get('id'),
name=curve_spec.get('name', None),
x_data_generator=x_data_gen,
y_data_generator=y_data_gen,
x_scale=AxisScale[output_spec['xScale']],
y_scale=AxisScale[output_spec['yScale']],
style=style,
)
output.curves.append(curve)
elif output_spec['_type'] == 'SedPlot3D':
output = Plot3D(
id=output_spec.get('id'),
name=output_spec.get('name', None),
)
for surface_spec in output_spec['surfaces']:
x_data_gen_id = surface_spec['xDataGenerator']
y_data_gen_id = surface_spec['yDataGenerator']
z_data_gen_id = surface_spec['zDataGenerator']
style_id = surface_spec.get('style', None)
x_data_gen = data_gen_id_map.get(x_data_gen_id, None)
y_data_gen = data_gen_id_map.get(y_data_gen_id, None)
z_data_gen = data_gen_id_map.get(z_data_gen_id, None)
style = style_id_map.get(style_id, None)
if not x_data_gen:
raise BadRequestException(
title=
'X data generator `{}` for surface `{}` does not exist'
.format(x_data_gen_id, output_spec.get('id')),
instance=ValueError('Data generator does not exist'),
)
if not y_data_gen:
raise BadRequestException(
title=
'Y data generator `{}` for surface `{}` does not exist'
.format(y_data_gen_id, output_spec.get('id')),
instance=ValueError('Data generator does not exist'),
)
if not z_data_gen:
raise BadRequestException(
title=
'X data generator `{}` for surface `{}` does not exist'
.format(z_data_gen_id, output_spec.get('id')),
instance=ValueError('Data generator does not exist'),
)
if style_id is not None and style is None:
raise BadRequestException(
title='Style `{}` for surface `{}` does not exist'.
format(style_id, output_spec.get('id')),
instance=ValueError('Style does not exist'),
)
surface = Surface(
id=surface_spec.get('id'),
name=surface_spec.get('name', None),
x_data_generator=x_data_gen,
y_data_generator=y_data_gen,
z_data_generator=z_data_gen,
x_scale=AxisScale[output_spec['xScale']],
y_scale=AxisScale[output_spec['yScale']],
z_scale=AxisScale[output_spec['zScale']],
style=style,
)
output.surfaces.append(surface)
else:
raise BadRequestException(
title='Outputs of type `{}` are not supported'.format(
output_spec['_type']),
instance=NotImplementedError('Invalid output')
) # pragma: no cover: unreachable due to schema validation
sed_doc.outputs.append(output)
# deserialize references
model_map = {}
for model in sed_doc.models:
model_map[model.id] = model
task_map = {}
for task in sed_doc.tasks:
task_map[task.id] = task
for model in sed_doc.models:
for change in model.changes:
if isinstance(change, ComputeModelChange):
for variable in change.variables:
if variable.model:
variable.model = model_map[variable.model]
if variable.task:
variable.task = task_map[variable.task]
return sed_doc