def test_model_returns_complex(self):
# This tests model failure with scalar complex.
# Quantity class has other more thorough tests.
A = Symbol('a', ['A'], ['A'], units='dimensionless', shape=1)
B = Symbol('b', ['B'], ['B'], units='dimensionless', shape=1)
for sym in (B, A):
Registry("symbols")[sym] = sym
Registry("units")[sym] = sym.units
get_config = {
'name': 'add_complex_value',
# 'connections': [{'inputs': ['b'], 'outputs': ['a']}],
'equations': ['a = b + 1j'],
# 'unit_map': {'a': "dimensionless", 'a': "dimensionless"}
'variable_symbol_map': {
"a": A,
"b": B
}
}
model = EquationModel(**get_config)
out = model.evaluate({'b': QuantityFactory.create_quantity(B, 5)},
allow_failure=True)
self.assertFalse(out['successful'])
self.assertEqual(out['message'],
'Evaluation returned invalid values (complex)')
out = model.evaluate({'b': QuantityFactory.create_quantity(B, 5j)},
allow_failure=True)
self.assertTrue(out['successful'])
self.assertTrue(np.isclose(out['a'].magnitude, 6j))
def test_unit_handling(self):
"""
Tests unit handling with a simple model that calculates the area of a rectangle as the
product of two lengths.
In this case the input lengths are provided in centimeters and meters.
Tests whether the input units are properly coerced into canonical types.
Tests whether the output units are properly set.
Tests whether the model returns as predicted.
Returns:
None
"""
L = Symbol('l', ['L'], ['L'], units=[1.0, [['centimeter', 1.0]]], shape=[1])
A = Symbol('a', ['A'], ['A'], units=[1.0, [['centimeter', 2.0]]], shape=[1])
get_area_config = {
'name': 'area',
# 'connections': [{'inputs': ['l1', 'l2'], 'outputs': ['a']}],
'equations': ['a = l1 * l2'],
# 'unit_map': {'l1': "cm", "l2": "cm", 'a': "cm^2"}
'symbol_property_map': {"a": A, "l1": L, "l2": L}
}
model = EquationModel(**get_area_config)
out = model.evaluate({'l1': QuantityFactory.create_quantity(L, 1, 'meter'),
'l2': QuantityFactory.create_quantity(L, 2)}, allow_failure=False)
self.assertTrue(math.isclose(out['a'].magnitude, 200.0))
self.assertTrue(out['a'].units == A.units)
def test_model_returns_nan(self):
# This tests model failure with scalar nan.
# Quantity class has other more thorough tests.
A = Symbol('a', ['A'], ['A'], units='dimensionless', shape=1)
B = Symbol('b', ['B'], ['B'], units='dimensionless', shape=1)
get_config = {
'name': 'equality',
# 'connections': [{'inputs': ['b'], 'outputs': ['a']}],
'equations': ['a = b'],
# 'unit_map': {'a': "dimensionless", 'a': "dimensionless"}
'symbol_property_map': {"a": A, "b": B}
}
model = EquationModel(**get_config)
out = model.evaluate({'b': QuantityFactory.create_quantity(B, float('nan'))},
allow_failure=True)
self.assertFalse(out['successful'])
self.assertEqual(out['message'], 'Evaluation returned invalid values (NaN)')
