def test_get_values():
np.random.seed(100691)
param_vects = np.random.uniform(low=0, high=1, size=(3, 2))
values_vects = np.random.uniform(low=0, high=1, size=(3, 1))
params = []
values = []
for param_vect, value_vect in zip(param_vects, values_vects):
params.append(ParameterVector().from_dict({
'p0': param_vect[0],
'p1': param_vect[1]
}))
values.append(ParameterVector().from_dict({'obj0': value_vect[0]}))
obs = Observations()
obs.add_observation(params, values)
obs_vals = obs.get_values(as_array=True, opposite=False)
assert [_.to_array() for _ in values] == list(obs_vals)
obs_vals = obs.get_values(as_array=True, opposite=True)
assert [-1 * _.to_array() for _ in values] == list(obs_vals)
obs_vals = obs.get_values(as_array=False, opposite=False)
assert [_.to_dict() for _ in values] == list(obs_vals)
obs_vals = obs.get_values(as_array=False, opposite=True)
obs_dicts = [_.to_dict() for _ in values]
for _, obs_dict in enumerate(obs_dicts):
for key, val in obs_dict.items():
assert val == -1 * obs_vals[_][key]
def test_declaration():
np.random.seed(100691)
param_vects = np.random.uniform(low=0, high=1, size=(3, 2))
values_vects = np.random.uniform(low=0, high=1, size=(3, 1))
params = []
values = []
for param_vect, value_vect in zip(param_vects, values_vects):
params.append(
ParameterVector().from_dict({"p0": param_vect[0], "p1": param_vect[1]})
)
values.append(ParameterVector().from_dict({"obj0": value_vect[0]}))
observations = Observations()
observations.add_observation(params, values)
test_params = [param.to_array() for param in params]
test_values = [value.to_array() for value in values]
assert np.linalg.norm(test_params - observations.get_params()) < 1e-7
assert np.linalg.norm(test_values - observations.get_values()) < 1e-7