def test_exception(self):
"""
Forget the trailing 'end' and ensure it produces an error
:return:
"""
exception_message = "Antimony: Error in model string, line 19: syntax error, unexpected end of file, expecting '-' or '+' or => or '<'"
try:
with model.BuildAntimony(self.copasi_file2) as loader:
self.mod2 = loader.load("""
model model2
compartment cell = 1.0
var A in cell
var B in cell
vAProd = 0.1
kADeg = 0.2
kBProd = 0.3
kBDeg = 0.4
vBasalAProd = 0.001
A = 0
B = 0
AProd: => A; cell*vAProd*B+vBasalAProd
ADeg: A =>; cell*kADeg*A
BProd: => B; cell*kBProd*A
BDeg: B => ; cell*kBDeg*B
""")
except Exception as E:
self.assertEqual(str(E), str(exception_message))
def test_build(self):
"""
Make copasi file from antimony
:return:
"""
with model.BuildAntimony(self.copasi_file1) as loader:
self.mod1 = loader.load("""
model model1
compartment cell = 1.0
var A in cell
var B in cell
vAProd = 0.1
kADeg = 0.2
kBProd = 0.3
kBDeg = 0.4
A = 0
B = 0
AProd: => A; cell*vAProd
ADeg: A =>; cell*kADeg*A*B
BProd: => B; cell*kBProd*A
BDeg: B => ; cell*kBDeg*B
end
""")
self.assertTrue(os.path.isfile(self.copasi_file1))
def setUp(self):
## create model selection directory
self.dire = os.path.join(os.path.dirname(__file__), 'AntimonyModels')
if not os.path.isdir(self.dire):
os.makedirs(self.dire)
self.copasi_file1 = os.path.join(self.dire, 'negative_feedback.cps')
with model.BuildAntimony(self.copasi_file1) as loader:
self.mod = loader.load("""
model model1
compartment cell = 1.0
var A in cell
var B in cell
vAProd = 0.1
kADeg = 0.2
kBProd = 0.3
kBDeg = 0.4
vBasalAProd = 0.001
A = 0
B = 0
AProd: => A; cell*vAProd*B+vBasalAProd
ADeg: A =>; cell*kADeg*A
BProd: => B; cell*kBProd*A
BDeg: B => ; cell*kBDeg*B
end
""")
assert os.path.isfile(self.copasi_file1)
def setUp(self):
## create model selection directory
self.dire = os.path.join(os.path.dirname(__file__), 'AntimonyModels')
if not os.path.isdir(self.dire):
os.makedirs(self.dire)
self.copasi_file1 = os.path.join(self.dire, 'negative_feedback.cps')
with model.BuildAntimony(self.copasi_file1) as loader:
self.mod = loader.load(
"""
model model1
compartment cell = 1.0
var A in cell
var B in cell
vAProd = 0.1
kADeg = 0.2
kBProd = 0.3
kBDeg = 0.4
vBasalAProd = 0.001
A = 0
B = 0
AProd: => A; cell*vAProd*B+vBasalAProd
ADeg: A =>; cell*kADeg*A
BProd: => B; cell*kBProd*A
BDeg: B => ; cell*kBDeg*B
end
"""
)
if not os.path.isfile(self.copasi_file1):
raise errors.FileDoesNotExistError('Copasi File "{}" was not created in '
'setting up the test case'.format(self.copasi_file1))
def test_build_model_to_file_path_which_already_exists(self):
with model.BuildAntimony(self.copasi_file1) as loader:
mod = loader.load(
"""
model model1
compartment cell = 1.0
var A in cell
var C in cell
vAProd = 0.1
kADeg = 0.2
kCProd = 0.3
kCDeg = 0.4
vBasalAProd = 0.001
A = 0
C = 0
AProd: => A; cell*vAProd*B+vBasalAProd
ADeg: A =>; cell*kADeg*A
CProd: => C; cell*kCProd*A
CDeg: C => ; cell*kCDeg*C
end
"""
)
self.assertNotIn('B', [i.name for i in mod.metabolites])
def setUp(self):
ant1 = """
model first()
compartment Cell = 1;
R1: A => B ; Cell * k1 * A;
R2: B => C ; Cell * k2 * B;
R3: C => A ; Cell * k3 * C;
k1 = 0.1;
k2 = 0.1;
k3 = 0.1;
A = 100;
B = 0;
C = 0;
end
"""
ant2 = """
model second()
compartment Cell = 1;
R1: A => B ; Cell * k1 * A;
R2: B => C ; Cell * k2 * B;
R3: B => A ; Cell * k3 * B;
k1 = 0.1;
k2 = 0.1;
k3 = 0.1;
A = 100;
B = 0;
C = 0;
end
"""
self.fname1 = os.path.join(os.path.dirname(__file__), 'first.cps')
self.fname2 = os.path.join(os.path.dirname(__file__), 'second.cps')
with model.BuildAntimony(self.fname1) as loader:
self.mod1 = loader.load(ant1)
with model.BuildAntimony(self.fname2) as loader:
self.mod2 = loader.load(ant2)
self.fname1 = os.path.join(os.path.dirname(__file__), 'dataset1.txt')
self.fname2 = os.path.join(os.path.dirname(__file__), 'dataset2.txt')
self.mod1.simulate(0, 9, 1, report_name=self.fname1)
self.mod2.simulate(0, 9, 1, report_name=self.fname2)
with tasks.ParameterEstimation.Context(
[self.mod1, self.mod2], [self.fname1, self.fname2],
context='s', parameters='g'
) as context:
self.config = context.get_config()
config_dct = dict(
models=dict(
first=dict(
copasi_file=self.mod1.copasi_file,
),
second=dict(
copasi_file=self.mod2.copasi_file
)
),
datasets=dict(
experiments=dict(
first_exp=dict(
filename=self.fname1
),
second_exp=dict(
filename=self.fname2
)
)
),
items=dict(
fit_items='g'
),
settings=dict(
working_directory=os.path.dirname(__file__),
run_mode=True,
method='genetic_algorithm',
population_size=5,
number_of_generations=25
)
)
self.config = tasks.ParameterEstimation.Config(**config_dct)
self.pe = tasks.ParameterEstimation(self.config)
