def test_write_error_invalid_refs(self):
document = data_model.SedDocument(tasks=[
data_model.Task(id='task',
simulation=data_model.UniformTimeCourseSimulation(
id='sim'))
])
utils.append_all_nested_children_to_doc(document)
with self.assertRaisesRegex(ValueError, 'must have a model'):
io.SedmlSimulationWriter().run(document, '')
document = data_model.SedDocument(tasks=[
data_model.Task(id='task',
model=data_model.Model(id='model',
source='model.xml'))
])
utils.append_all_nested_children_to_doc(document)
with self.assertRaisesRegex(ValueError, 'must have a simulation'):
io.SedmlSimulationWriter().run(document, '')
document = data_model.SedDocument(tasks=[
data_model.Task(
id='task',
model=data_model.Model(id='model', source='model.xml'),
simulation=data_model.UniformTimeCourseSimulation(id='sim'),
),
], )
with self.assertRaisesRegex(ValueError, 'must be direct children'):
io.SedmlSimulationWriter().run(document, '')
def test_write_error_invalid_ids(self):
document = data_model.SedDocument(models=[
mock.Mock(id=None, source=None, language=None, changes=[]),
])
with self.assertRaisesRegex(ValueError, 'missing ids'):
io.SedmlSimulationWriter().run(document, '')
document = data_model.SedDocument(models=[
mock.Mock(id='model', source=None, language=None, changes=[]),
mock.Mock(id='model', source=None, language=None, changes=[]),
])
with self.assertRaisesRegex(ValueError, 'ids are repeated'):
io.SedmlSimulationWriter().run(document, '')
def test_write_read_without_semantic_validation(self):
document = data_model.SedDocument(
level=1,
version=3,
models=[
data_model.Model(id='model',
source='model.xml',
language='urn:sedml:language:sbml')
],
tasks=[
data_model.RepeatedTask(
id='task',
changes=[
data_model.SetValueComputeModelChange(
model=None,
symbol='x',
target_namespaces={
None:
'http://sed-ml.org/sed-ml/level1/version3'
},
math='x')
],
)
],
)
document.tasks[0].changes[0].model = document.models[0]
filename = os.path.join(self.tmp_dir, 'sim.sedml')
io.SedmlSimulationWriter().run(document,
filename,
validate_semantics=False)
document2 = io.SedmlSimulationReader().run(filename,
validate_semantics=False)
self.assertTrue(document2.is_equal(document))
def test_write_error_libsedmls(self):
document = data_model.SedDocument()
with self.assertRaisesRegex(ValueError, r'libSED-ML error:'):
writer = io.SedmlSimulationWriter()
writer._obj_to_sed_obj_map = {}
writer._create_doc(document)
doc_sed = writer._obj_to_sed_obj_map[document]
writer._call_libsedml_method(doc_sed, 'setAnnotation', '<rdf')
def test_read_unsupported_sedml_version(self):
filename = os.path.join(self.tmp_dir, 'sim.sedml')
document = data_model.SedDocument(level=1, version=4)
io.SedmlSimulationWriter().run(document, filename)
with self.assertWarnsRegex(
SedmlFeatureNotSupportedWarning,
'Only features available in L1V3 are supported'):
io.SedmlSimulationReader().run(filename)
def test_SedmlSimulationWriter__add_namespaces_to_obj(self):
obj = libsedml.SedModel()
self.assertEqual(obj.getNamespaces().getLength(), 1)
io.SedmlSimulationWriter()._add_namespaces_to_obj(
obj, {
'sbml': 'x',
'fbc': 'y'
})
self.assertEqual(
obj.getNamespaces().getURI(
obj.getNamespaces().getIndexByPrefix('sbml')), 'x')
self.assertEqual(obj.getNamespaces().getLength(), 3)
io.SedmlSimulationWriter()._add_namespaces_to_obj(
obj, {
'sbml': 'x2',
'qual': 'z'
})
self.assertEqual(
obj.getNamespaces().getURI(
obj.getNamespaces().getIndexByPrefix('sbml')), 'x2')
self.assertEqual(obj.getNamespaces().getLength(), 4)
def test_unsupported_uniform_range_type(self):
document = data_model.SedDocument(
models=[
data_model.Model(id='model',
language=data_model.ModelLanguage.SBML.value,
source='model.xml')
],
simulations=[
data_model.SteadyStateSimulation(
id='sim',
algorithm=data_model.Algorithm(kisao_id='KISAO_0000019'))
],
tasks=[
data_model.RepeatedTask(
id='task',
ranges=[
data_model.UniformRange(id='range',
start=0.,
end=10.,
number_of_steps=10,
type=mock.Mock(value='sin')),
],
sub_tasks=[
data_model.SubTask(task=data_model.Task(id='task2'),
order=1),
],
),
],
)
document.tasks[0].range = document.tasks[0].ranges[0]
document.tasks[0].sub_tasks[0].task.model = document.models[0]
document.tasks[0].sub_tasks[0].task.simulation = document.simulations[
0]
document.tasks.append(document.tasks[0].sub_tasks[0].task)
filename = os.path.join(self.tmp_dir, 'test.xml')
io.SedmlSimulationWriter().run(document,
filename,
validate_models_with_languages=False)
with self.assertRaisesRegex(NotImplementedError, 'is not supported'):
io.SedmlSimulationReader().run(filename)
def test_write_read_sedml_from_biomodels(self):
filename = os.path.join(os.path.dirname(__file__), '..', 'fixtures',
'sedml', 'BIOMD0000000673_sim.sedml')
temp_filename = os.path.join(self.tmp_dir, os.path.basename(filename))
shutil.copy(filename, temp_filename)
with open(os.path.join(self.tmp_dir, 'BIOMD0000000673_url.xml'),
'w') as file:
pass
doc = io.SedmlSimulationReader().run(
temp_filename, validate_models_with_languages=False)
filename_2 = os.path.join(self.tmp_dir, 'test.sedml')
io.SedmlSimulationWriter().run(doc,
filename_2,
validate_models_with_languages=False)
doc_2 = io.SedmlSimulationReader().run(
filename_2, validate_models_with_languages=False)
self.assertTrue(doc_2.is_equal(doc))
def test_write_error_unsupported_classes(self):
document = data_model.SedDocument(tasks=[mock.Mock(id='task')])
with self.assertRaisesRegex(NotImplementedError, 'is not supported.'):
io.SedmlSimulationWriter().run(document, '')
document = data_model.SedDocument(outputs=[mock.Mock(id='output')])
with self.assertRaisesRegex(NotImplementedError, 'is not supported.'):
io.SedmlSimulationWriter().run(document, '')
document = data_model.SedDocument(outputs=[mock.Mock(id='output')])
with self.assertRaisesRegex(NotImplementedError, 'is not supported.'):
io.SedmlSimulationWriter().run(document,
'',
validate_semantics=False)
document = data_model.SedDocument(models=[
data_model.Model(
id='model',
source='model.xml',
language=data_model.ModelLanguage.SBML.value,
changes=[
mock.Mock(id=None,
target='/sbml:sbml',
target_namespaces={'sbml': 'sbml'})
],
),
], )
with self.assertRaisesRegex(NotImplementedError, 'is not supported.'):
io.SedmlSimulationWriter().run(
document, '', validate_models_with_languages=False)
document = data_model.SedDocument(outputs=[
data_model.Plot2D(
id='plot',
curves=[
data_model.Curve(
id='curve',
x_scale='sin',
y_scale=data_model.AxisScale.linear,
x_data_generator=data_model.DataGenerator(
id='x_data_gen',
parameters=[data_model.Parameter(id='x', value=1)],
math='x'),
y_data_generator=data_model.DataGenerator(
id='y_data_gen',
parameters=[data_model.Parameter(id='y', value=2)],
math='y'),
),
]),
], )
utils.append_all_nested_children_to_doc(document)
with self.assertRaisesRegex(NotImplementedError, 'is not supported.'):
io.SedmlSimulationWriter().run(document, '')
document = data_model.SedDocument(tasks=[
data_model.RepeatedTask(
id='task',
ranges=[
mock.Mock(id=None),
],
sub_tasks=[
data_model.SubTask(order=1, task=data_model.Task())
],
),
], )
with self.assertRaisesRegex(ValueError, 'not an instance of'):
io.SedmlSimulationWriter().run(
document, '', validate_models_with_languages=False)
task = document.tasks[0]
writer = io.SedmlSimulationWriter()
writer._obj_to_sed_obj_map = {task: None}
with self.assertRaisesRegex(NotImplementedError, 'is not supported.'):
writer._add_range_to_repeated_task(task=task,
range_obj=task.ranges[0])
def test_write_read(self):
shutil.copy(
os.path.join(os.path.dirname(__file__), '..', 'fixtures',
'BIOMD0000000075.xml'),
os.path.join(self.tmp_dir, 'model.sbml'))
model1 = data_model.Model(
id='model1',
name='Model1',
source='model.sbml',
language='urn:sedml:language:sbml',
changes=[
data_model.ModelAttributeChange(
target='/sbml:sbml/sbml:model[id=\'a\']/@id',
new_value='234'),
data_model.ModelAttributeChange(
target='/sbml:sbml/sbml:model[id=\'b\']/@id',
new_value='432'),
data_model.AddElementModelChange(
target=
'/sbml:sbml/sbml:model[id=\'b\']/sbml:listOfParameters',
new_elements=
'<sbml:parameter xmlns:sbml="http://www.sbml.org/sbml/level2/version3" id="new_parameter" value="1.0"/>'
),
data_model.AddElementModelChange(
target=
'/sbml:sbml/sbml:model[id=\'b\']/sbml:listOfParameters',
new_elements=
'<parameter id="new_parameter_1" value="1.0"/><parameter id="new_parameter_2" value="1.0"/>'
),
data_model.ReplaceElementModelChange(
target=
'/sbml:sbml/sbml:model[id=\'b\']/sbml:listOfParameters/sbml:parameter[@id=\'p1\']',
new_elements='<parameter id="p1" value="1.0"/>'),
data_model.ReplaceElementModelChange(
target=
'/sbml:sbml/sbml:model[id=\'b\']/sbml:listOfParameters/sbml:parameter[@id=\'p1\']',
new_elements=
'<parameter id="p1" value="1.0"/><parameter id="p1" value="1.0"/>'
),
data_model.RemoveElementModelChange(
target=
'/sbml:sbml/sbml:model[id=\'b\']/sbml:listOfParameters/sbml:parameter[@id=\'p1\']',
),
data_model.ComputeModelChange(
target=
'/sbml:sbml/sbml:model[id=\'b\']/sbml:listOfParameters/sbml:parameter[@id=\'p1\']',
parameters=[
data_model.Parameter(id='a', value=1.5),
data_model.Parameter(id='b', value=2.25),
],
variables=[
data_model.Variable(
id='x',
target='variable_target_x',
),
data_model.Variable(
id='y',
target='variable_target_y',
),
],
math='a * x + b * y',
),
],
)
for var in model1.changes[-1].variables:
var.model = model1
model2 = data_model.Model(
id='model2',
name='Model2',
source='model.sbml',
language='urn:sedml:language:sbml',
changes=[
data_model.ModelAttributeChange(
target='/sbml:sbml/sbml:model[id=\'a\']/@id',
new_value='234',
),
data_model.ModelAttributeChange(
target='/sbml:sbml/sbml:model[id=\'b\']/@id',
new_value='432'),
],
)
ss_simulation = data_model.SteadyStateSimulation(
id='simulation1',
name='Simulation1',
algorithm=data_model.Algorithm(
kisao_id='KISAO_0000019',
changes=[
data_model.AlgorithmParameterChange(
kisao_id='KISAO_0000211', new_value='1.234'),
]),
)
one_step_simulation = data_model.OneStepSimulation(
id='simulation2',
name='Simulation2',
algorithm=data_model.Algorithm(
kisao_id='KISAO_0000019',
changes=[
data_model.AlgorithmParameterChange(
kisao_id='KISAO_0000211', new_value='1.234'),
]),
step=10.)
time_course_simulation = data_model.UniformTimeCourseSimulation(
id='simulation3',
name='Simulation3',
algorithm=data_model.Algorithm(
kisao_id='KISAO_0000019',
changes=[
data_model.AlgorithmParameterChange(
kisao_id='KISAO_0000209', new_value='1.234'),
data_model.AlgorithmParameterChange(
kisao_id='KISAO_0000211', new_value='4.321'),
]),
initial_time=10.,
output_start_time=20.,
output_end_time=30,
number_of_steps=10)
task1 = data_model.Task(id='task1',
name='Task1',
model=model1,
simulation=time_course_simulation)
task2 = data_model.Task(id='task2',
name='Task2',
model=model2,
simulation=time_course_simulation)
task3 = data_model.RepeatedTask(
id='task3',
name='Task3',
reset_model_for_each_iteration=True,
changes=[],
sub_tasks=[
data_model.SubTask(task=task1, order=1),
data_model.SubTask(task=task2, order=2),
],
ranges=[
data_model.UniformRange(
id='range1',
start=10.,
end=20.,
number_of_steps=4,
type=data_model.UniformRangeType.linear),
data_model.UniformRange(id='range2',
start=10.,
end=20.,
number_of_steps=4,
type=data_model.UniformRangeType.log),
data_model.VectorRange(id='range3',
values=[3., 5., 7., 11., 13.]),
],
)
task3.ranges.append(
data_model.FunctionalRange(
id='range4',
range=task3.ranges[0],
parameters=[
data_model.Parameter(
id='x2',
value=2.0,
),
],
variables=[
data_model.Variable(
id='y2',
model=model1,
target=
"/sbml:sbml/sbml:model/sbml:listOfParameters/sbml:Parameter[@id='param_1']",
),
],
math='{} * {} + {}'.format(task3.ranges[0].id, 'x2', 'y2'),
), )
task3.range = task3.ranges[1]
task3.changes.append(
data_model.SetValueComputeModelChange(
model=model1,
target=
"/sbml:sbml/sbml:model/sbml:listOfParameters/sbml:parameter[@id='p1']",
range=task3.ranges[0],
parameters=[],
variables=[],
math='range1',
), )
task3.changes.append(
data_model.SetValueComputeModelChange(
model=model1,
target=
"/sbml:sbml/sbml:model/sbml:listOfParameters/sbml:parameter[@id='p1']",
range=task3.ranges[0],
parameters=[],
variables=[
data_model.Variable(
id='range1_var1',
model=model1,
target=
"/sbml:sbml/sbml:model/sbml:listOfParameters/sbml:parameter[@id='p1']",
)
],
math='range1 * range1_var1',
), )
task3.changes.append(
data_model.SetValueComputeModelChange(
model=model1,
target=
"/sbml:sbml/sbml:model/sbml:listOfParameters/sbml:parameter[@id='p1']",
range=task3.ranges[0],
parameters=[
data_model.Parameter(id='range1_p1', value=2.5),
],
variables=[],
math='range1 * range1_p1',
), )
report = data_model.Report(
id='report1',
name='Report1',
data_sets=[
data_model.DataSet(
id='dataset1',
name='Dataset1',
label='Dataset-1',
data_generator=data_model.DataGenerator(
id='dataGen1',
name='DataGen1',
variables=[
data_model.Variable(
id='DataGenVar1',
name='DataGenVar1',
target='/sbml:sbml/sbml:model/@id',
task=task1,
)
],
parameters=[
data_model.Parameter(id='DataGenParam1',
name='DataGenParam1',
value=2.)
],
math='DataGenVar1 - DataGenParam1',
)),
],
)
plot2d = data_model.Plot2D(
id='plot2d',
name='Plot2D',
curves=[
data_model.Curve(
id='curve1',
name='Curve1',
x_scale=data_model.AxisScale.linear,
y_scale=data_model.AxisScale.log,
x_data_generator=data_model.DataGenerator(
id='xDataGen2',
name='XDataGen2',
variables=[
data_model.Variable(id='xDataGenVar1',
name='XDataGenVar1',
symbol='urn:sedml:symbol:time',
task=task2)
],
parameters=[
data_model.Parameter(id='xDataGenParam1',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar1 * xDataGenParam1',
),
y_data_generator=data_model.DataGenerator(
id='yDataGen3',
name='yDataGen3',
variables=[
data_model.Variable(
id='xDataGenVar2',
name='XDataGenVar1',
target='/sbml:sbml/sbml:model/@id',
task=task2,
)
],
parameters=[
data_model.Parameter(id='xDataGenParam2',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar2 * xDataGenParam2',
),
),
data_model.Curve(
id='curve2',
name='Curve2',
x_scale=data_model.AxisScale.linear,
y_scale=data_model.AxisScale.log,
x_data_generator=data_model.DataGenerator(
id='yDataGen4',
name='yDataGen4',
variables=[
data_model.Variable(
id='yDataGenVar1',
target='/sbml:sbml/sbml:model/@id',
task=task1,
)
],
parameters=[
data_model.Parameter(id='YDataGenParam1', value=2.)
],
math='yDataGenVar1 + YDataGenParam1',
),
y_data_generator=data_model.DataGenerator(
id='yDataGen5',
name='yDataGen5',
variables=[
data_model.Variable(
id='yDataGenVar2',
target='/sbml:sbml/sbml:model/@id',
task=task1,
)
],
parameters=[
data_model.Parameter(id='YDataGenParam2',
value=2.),
],
math='yDataGenVar2 + YDataGenParam2',
),
),
])
plot3d = data_model.Plot3D(
id='plot3d',
name='Plot3D',
surfaces=[
data_model.Surface(
id='surface1',
name='Surface1',
x_scale=data_model.AxisScale.linear,
y_scale=data_model.AxisScale.log,
z_scale=data_model.AxisScale.linear,
x_data_generator=data_model.DataGenerator(
id='xDataGen6',
name='XDataGen6',
variables=[
data_model.Variable(
id='xDataGenVar3',
name='XDataGenVar2',
target='/sbml:sbml/sbml:model/@id',
task=task2,
)
],
parameters=[
data_model.Parameter(id='xDataGenParam3',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar3 * xDataGenParam3',
),
y_data_generator=data_model.DataGenerator(
id='xDataGen8',
name='XDataGen8',
variables=[
data_model.Variable(
id='xDataGenVar4',
name='XDataGenVar2',
target='/sbml:sbml/sbml:model/@id',
task=task2,
)
],
parameters=[
data_model.Parameter(id='xDataGenParam4',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar4 * xDataGenParam4',
),
z_data_generator=data_model.DataGenerator(
id='xDataGen9',
name='XDataGen9',
variables=[
data_model.Variable(
id='xDataGenVar5',
name='XDataGenVar2',
target='/sbml:sbml/sbml:model/@id',
task=task2,
)
],
parameters=[
data_model.Parameter(id='xDataGenParam5',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar5 * xDataGenParam5',
),
),
data_model.Surface(
id='surface2',
name='Surface2',
x_scale=data_model.AxisScale.linear,
y_scale=data_model.AxisScale.log,
z_scale=data_model.AxisScale.log,
x_data_generator=data_model.DataGenerator(
id='xDataGen10',
name='XDataGen10',
variables=[
data_model.Variable(
id='xDataGenVar6',
name='XDataGenVar2',
target='/sbml:sbml/sbml:model/@id',
task=task2,
)
],
parameters=[
data_model.Parameter(id='xDataGenParam6',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar6 * xDataGenParam6',
),
y_data_generator=data_model.DataGenerator(
id='xDataGen11',
name='XDataGen11',
variables=[
data_model.Variable(
id='xDataGenVar7',
name='XDataGenVar2',
target='/sbml:sbml/sbml:model/@id',
task=task2,
)
],
parameters=[
data_model.Parameter(id='xDataGenParam7',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar7 * xDataGenParam7',
),
z_data_generator=data_model.DataGenerator(
id='xDataGen12',
name='XDataGen12',
variables=[
data_model.Variable(
id='xDataGenVar8',
name='XDataGenVar2',
target='/sbml:sbml/sbml:model/@id',
task=task2,
)
],
parameters=[
data_model.Parameter(id='xDataGenParam8',
name='XDataGenParam1',
value=2.)
],
math='xDataGenVar8 * xDataGenParam8',
),
),
])
now = datetime.datetime(2020,
1,
2,
1,
2,
3,
tzinfo=dateutil.tz.tzutc())
document = data_model.SedDocument(
level=1,
version=3,
models=[model1],
simulations=[time_course_simulation],
tasks=[task1],
data_generators=([d.data_generator for d in report.data_sets]),
outputs=[report],
metadata=Metadata(
description="description",
tags=['tag-1', 'tag-2'],
authors=[
Person(given_name='first',
other_name='middle',
family_name='last'),
],
references=ExternalReferences(
identifiers=None,
citations=[
Citation(title='creative title',
authors='Author-1 & Author-2',
journal='major journal',
volume='10',
issue='20',
pages='30-40',
year=2020,
identifiers=[
Identifier(
namespace="doi",
id='10.0/1.0',
url="https://doi.org/10.0/1.0"),
])
]),
license=OntologyTerm(
namespace='SPDX',
id='MIT',
url='https://spdx.org/licenses/MIT.html',
),
created=now,
updated=now,
),
)
self._set_target_namespaces(document)
filename = os.path.join(self.tmp_dir, 'test.xml')
io.SedmlSimulationWriter().run(document, filename)
document2 = io.SedmlSimulationReader().run(filename)
self.assertTrue(document.is_equal(document2))
document = data_model.SedDocument(
level=1,
version=3,
models=[model1, model2],
simulations=[
ss_simulation, one_step_simulation, time_course_simulation
],
tasks=[task1, task2, task3],
data_generators=([d.data_generator for d in report.data_sets] +
[c.x_data_generator for c in plot2d.curves] +
[c.y_data_generator for c in plot2d.curves] +
[s.x_data_generator for s in plot3d.surfaces] +
[s.y_data_generator for s in plot3d.surfaces] +
[s.z_data_generator for s in plot3d.surfaces]),
outputs=[report, plot2d, plot3d],
metadata=Metadata(
description="description",
license=OntologyTerm(
namespace='SPDX',
id='MIT',
url='https://spdx.org/licenses/MIT.html',
),
),
)
self._set_target_namespaces(document)
filename = os.path.join(self.tmp_dir, 'test.xml')
io.SedmlSimulationWriter().run(document, filename)
document2 = io.SedmlSimulationReader().run(filename)
self.assertTrue(document.is_equal(document2))
document2.metadata.license.namespace = None
document2.metadata.license.url = None
io.SedmlSimulationWriter().run(document2, filename)
document3 = io.SedmlSimulationReader().run(filename)
self.assertTrue(document2.is_equal(document3))
document3.metadata = None
io.SedmlSimulationWriter().run(document3, filename)
document4 = io.SedmlSimulationReader().run(filename)
self.assertTrue(document4.is_equal(document3))
document.models[0].changes[
2].new_elements = '<parameter id="new_parameter" value="1.0/>'
document.models[0].changes[
4].new_elements = '<parameter id="new_parameter" value="1.0"/>'
with self.assertRaisesRegex(ValueError, 'invalid XML'):
io.SedmlSimulationWriter().run(document, filename)
document.models[0].changes[
2].new_elements = '<parameter id="new_parameter" value="1.0"/>'
document.models[0].changes[
4].new_elements = '<parameter id="new_parameter" value="1.0/>'
with self.assertRaisesRegex(ValueError, 'invalid XML'):
io.SedmlSimulationWriter().run(document, filename)