def test_sqrt_unscented_predict_focus_on_weighting(self, mock_transform):
mock_transform.return_value = self.sps2
kf.sqrt_unscented_predict(
self.stage, self.sps2, self.flat_sps2, self.sws_m, self.sws_c,
self.Q, self.transform_sps_args, self.out_states, self.out_sqrt_covs)
aaae(self.out_states, self.expected_states2)
def test_sqrt_unscented_predict_focus_on_covs(self, mock_transform):
mock_transform.return_value = self.sps3
# self.q = np.eye(3) * 0.25 + np.ones((3, 3)) * 0.5
kf.sqrt_unscented_predict(
self.stage, self.sps3, self.flat_sps3, self.sws_m, self.sws_c,
self.Q, self.transform_sps_args, self.out_states, self.out_sqrt_covs)
make_unique(self.out_covs)
aaae(self.out_covs, self.exp_cholcovs)
def test_sqrt_unscented_predict_focus_on_weighting(self, mock_transform):
mock_transform.return_value = self.sps2
kf.sqrt_unscented_predict(self.stage, self.sps2, self.flat_sps2,
self.sws_m, self.sws_c, self.Q,
self.transform_sps_args, self.out_states,
self.out_sqrt_covs)
aaae(self.out_states, self.expected_states2)
def test_sqrt_unscented_predict_focus_on_covs(self, mock_transform):
mock_transform.return_value = self.sps3
# self.q = np.eye(3) * 0.25 + np.ones((3, 3)) * 0.5
kf.sqrt_unscented_predict(self.stage, self.sps3, self.flat_sps3,
self.sws_m, self.sws_c, self.Q,
self.transform_sps_args, self.out_states,
self.out_sqrt_covs)
make_unique(self.out_covs)
aaae(self.out_covs, self.exp_cholcovs)
def predict(stage, square_root_filters, predict_args):
"""Select and call the correct predict function.
The actual predict functions are implemented in several modules in
:ref:`fast_routines`
"""
if square_root_filters is True:
sqrt_unscented_predict(stage, **predict_args)
else:
normal_unscented_predict(stage, **predict_args)
def predict(period, square_root_filters, predict_args):
"""Select and call the correct predict function.
The actual predict functions are implemented in several modules in
:ref:`fast_routines`
"""
if square_root_filters is True:
sqrt_unscented_predict(period, **predict_args)
else:
normal_unscented_predict(period, **predict_args)
def test_sqrt_unscented_predict_focus_on_covs(setup_unscented_predict, mocker):
d = setup_unscented_predict
mock_transform = mocker.patch(
"skillmodels.fast_routines.kalman_filters.transform_sigma_points")
mock_transform.return_value = d["sps3"]
kf.sqrt_unscented_predict(
d["stage"],
d["sps3"],
d["flat_sps3"],
d["sws_m"],
d["sws_c"],
d["q"],
d["transform_sps_args"],
d["out_states"],
d["out_sqrt_covs"],
)
make_unique(d["out_covs"])
aaae(d["out_covs"], d["exp_cholcovs"])