def test_good_inputs(self):
"""Test base_curve for good inputs"""
model = FairModel('model')
meta = FairMetaModel('meta', models=[model, model])
good_list = [model, meta, model]
for input_item in [model, meta, good_list]:
self._fbc._input_check(input_item)
def setUp(self):
self._fbr = FairBaseReport()
self._model_1 = FairModel('model1', n_simulations=5)
self._model_1.input_data('Risk', mean=100, stdev=5)
self._model_2 = FairModel('model2', n_simulations=5)
self._model_2.input_data('Risk', mean=1000, stdev=50)
self._metamodel = FairMetaModel(
name='meta',
models=[self._model_1, self._model_2],
)
def test_calculation(self):
"""Run a calulate all."""
# Test regular instantiation
m1 = FairModel.read_json(self._MODEL_JSON)
m2 = FairModel.read_json(self._MODEL_JSON)
self._meta = FairMetaModel('New Model', [m1, m2])
# Test before
self.assertFalse(self._meta.calculation_completed())
# Calculate
self._meta.calculate_all()
# Test after
self.assertTrue(self._meta.calculation_completed())
def test_tree_graph_creation(self):
"""Test violin plot creation"""
# There is little to test here other than simple creation
# Whether it comes out OK or not ... ¯\_(ツ)_/¯
model = FairModel(name='Test')
model.input_data('Loss Magnitude', mean=50, stdev=5)
model.input_data('Loss Event Frequency', low=10, mode=20, high=30)
metamodel = FairMetaModel(name='Test Meta', models=[model, model])
with warnings.catch_warnings(record=False):
warnings.simplefilter("ignore")
fvp = FairViolinPlot(metamodel)
_, _ = fvp.generate_image()
def test_creation(self):
"""Test basic instantiation"""
# Ensure existence of appropriate attributes
self.assertTrue(self._meta._model_uuid)
self.assertTrue(self._meta._creation_date)
# Check that the table is of proper-ish
self.assertEqual(len(self._meta._risk_table.columns),
self._RISK_TABLE_COLUMN_COUNT)
# Test regular instantiation
m1 = FairModel.read_json(self._MODEL_JSON)
m2 = FairModel.read_json(self._MODEL_JSON)
self._meta = FairMetaModel('New Model', [m1, m2])
# Throw garbage in metamodel
self.assertRaises(FairException, FairMetaModel, 'Garnage Name',
['Garbage Input'])
def test_generate_image(self):
"""Check HTML content can be generated"""
model_1 = FairModel(name='Model', n_simulations=10)
model_1.input_data('Loss Event Frequency', mean=10, stdev=1)
model_1.input_data('Loss Magnitude', low=0, mode=10, high=100)
model_1.calculate_all()
meta_model_1 = FairMetaModel(
name='Meta',
models=[model_1, model_1]
).calculate_all()
# Suppress warnings for number of figures generated
with warnings.catch_warnings(record=False):
warnings.simplefilter("ignore")
fsr = FairSimpleReport([model_1, meta_model_1])
_ = fsr._construct_output()
def test_input_check(self):
"""Test the validity of the input check"""
# Create inputs
bad_model = 'Not a model'
model = FairModel(name='model')
bad_meta = 0
meta = FairMetaModel(name='metamodel', models=[model, model])
model_list = [model, meta]
bad_model_list_1 = []
bad_model_list_2 = [model, bad_model]
# Test good items
for good_item in [model, meta, model_list]:
self._fbr._input_check(good_item)
# Test bad items
for bad_item in [bad_model, bad_meta, bad_model_list_1, bad_model_list_2]:
self.assertRaises(
FairException,
self._fbr._input_check,
bad_item
)