def test_exports(self):
"""Test outputs post calculation"""
# Create model and calculate
model = FairModel('Test', self.N_SAMPLES)
model.bulk_import_data({
'Loss Magnitude': {
'constant': 100
},
'Loss Event Frequency': {
'low': 10,
'mode': 15,
'high': 20
}
})
model.calculate_all()
# Export results
results = model.export_results()
self.assertIsInstance(results, pd.DataFrame)
self.assertTrue(len(results) == self.N_SAMPLES)
# Export json and ensure parse-able
json_data = model.to_json()
self.assertIsInstance(json_data, str)
_ = json.loads(json_data)
# Export params
params = model.export_params()
self.assertIsInstance(params, dict)
self.assertTrue(params)
def test_inputs(self):
"""Check the input methods (leave validation to FairDataInput)"""
# Test basic input
model = FairModel('Test', self.N_SAMPLES)
model.input_data('Loss Magnitude', constant=100)
# Test duplicate inputs passed
model.input_data('Loss Magnitude', constant=10)
# Test bulk_import_data
model.bulk_import_data({
'Loss Magnitude': {
'constant': 100
},
'Loss Event Frequency': {
'low': 10,
'mode': 15,
'high': 20
}
})
# Test import_multi_data
model.input_multi_data(
'Secondary Loss', {
'Reputational': {
'Secondary Loss Event Frequency': {
'constant': 4000
},
'Secondary Loss Event Magnitude': {
'low': 10,
'mode': 20,
'high': 100
},
},
'Legal': {
'Secondary Loss Event Frequency': {
'constant': 2000
},
'Secondary Loss Event Magnitude': {
'low': 10,
'mode': 20,
'high': 100
},
}
})
# Test input_raw_data
model.input_raw_data('Vulnerability', [1] * self.N_SAMPLES)
self.assertRaises(FairException, model.input_raw_data, 'Vulnerability',
[2] * self.N_SAMPLES)
self.assertRaises(FairException, model.input_raw_data, 'Vulnerability',
'abc')
model.calculate_all()