def runStudy(model, dirStudyPath):
study = ModelStudy(model, # Antimony model to evaluate
dataSourceDct, # Data sources to use for fitting
parameterDct=parameterDct, # Parameters and their value ranges
dirStudyPath=dirStudyPath, # Where to store the results of bootstrapping
selectedColumns=["log10V"], # Output column is computed in the assignment rule
doSerialize=DO_SERIALIZE, # Save the results of bootstrapping
useSerialized=USE_SERIALIZED) # Use previously calculated bootstrap results if they are present
study.bootstrap(numIteration=NUM_BOOTSTRAP_ITERATION) # Do bootstrapping
print("\n\n")
study.plotFitAll(ylim=[0, 9]) # Plot fitted and observed values with band plots for confidence
print("\n\n")
study.plotParameterEstimates() # Plot the parameter estimates for each data source
class TestModelStudy(unittest.TestCase):
def setUp(self):
self._remove()
self.parametersToFit = list(th.PARAMETER_DCT.keys())
self.study = ModelStudy(th.ANTIMONY_MODEL, DATA_PATHS,
parametersToFit=PARAMETERS_TO_FIT,
dirStudyPath=SERIALIZE_DIR, isPlot=IS_PLOT, useSerialized=True)
def tearDown(self):
self._remove()
def _remove(self):
for ffile in FILES:
if os.path.isfile(ffile):
os.remove(ffile)
for ddir in DIRS:
if os.path.isdir(ddir):
shutil.rmtree(ddir)
def testConstructor1(self):
if IGNORE_TEST:
return
self.assertGreater(len(self.study.fitterDct.values()), 0)
# Ensure that ModelFitters are serialized correctly
study = ModelStudy(th.ANTIMONY_MODEL, DATA_PATHS,
parametersToFit=self.parametersToFit,
dirStudyPath=SERIALIZE_DIR, isPlot=IS_PLOT)
for name in self.study.instanceNames:
self.assertEqual(study.fitterDct[name].modelSpecification,
self.study.fitterDct[name].modelSpecification)
def testFitModel(self):
if IGNORE_TEST:
return
self.study.fitModel()
names = [v for v in self.study.fitterDct.keys()]
params0 = self.study.fitterDct[names[0]].params
params1 = self.study.fitterDct[names[1]].params
dct0 = params0.valuesdict()
dct1 = params1.valuesdict()
if IGNORE_ACCURACY:
return
for key, value in dct0.items():
self.assertTrue(np.isclose(value, dct1[key], rtol=0.5))
def testFitBootstrap(self):
if IGNORE_TEST:
return
study = ModelStudy(th.ANTIMONY_MODEL, DATA_PATHS,
parametersToFit=PARAMETERS_TO_FIT,
dirStudyPath=SERIALIZE_DIR, isPlot=IS_PLOT, useSerialized=False)
study.bootstrap(numIteration=10)
for fitter in study.fitterDct.values():
self.assertIsNotNone(fitter.bootstrapResult)
def testPlotFitAll(self):
if IGNORE_TEST:
return
self.study.fitModel()
self.study.plotFitAll()
#
self.study.bootstrap()
self.study.plotFitAll()
def testPlotParameterEstimates(self):
if IGNORE_TEST:
return
self.study.bootstrap(numIteration=20)
self.study.plotParameterEstimates()