def test_sqrt_cov_update_with_nans(self):
kf.sqrt_linear_update(
self.states, self.mcovs, self.like_vec, self.y, self.c,
self.delta, self.h, self.sqrt_r, self.positions, self.weights)
cholcovs = self.mcovs[:, :, 1:, 1:]
make_unique(cholcovs.reshape(12, 3, 3))
aaae(cholcovs, self.exp_cholcovs)
def test_sqrt_cov_update_with_nans(self):
kf.sqrt_linear_update(self.states, self.mcovs, self.like_vec, self.y,
self.c, self.delta, self.h, self.sqrt_r,
self.positions, self.weights)
cholcovs = self.mcovs[:, :, 1:, 1:]
make_unique(cholcovs.reshape(12, 3, 3))
aaae(cholcovs, self.exp_cholcovs)
def update(square_root_filters, update_args):
"""Select and call the correct update function.
The actual update functions are implemented in several modules in
:ref:`fast_routines`
"""
if square_root_filters is True:
sqrt_linear_update(*update_args)
else:
normal_linear_update(*update_args)
def test_sqrt_weight_update_with_nans(setup_linear_update, expected_linear_update):
d = setup_linear_update
kf.sqrt_linear_update(
d["state"],
d["mcovs"],
d["like_vector"],
d["y"],
d["c"],
d["delta"],
d["h"],
d["sqrt_r"],
d["positions"],
d["weights"],
)
aaae(d["weights"], expected_linear_update["expected_weights"])
def update(square_root_filters, update_type, update_args):
"""Select and call the correct update function.
The actual update functions are implemented in several modules in
:ref:`fast_routines`
"""
if square_root_filters is True:
if update_type == 'linear':
sqrt_linear_update(*update_args)
else:
sqrt_probit_update(**update_args)
else:
if update_type == 'linear':
normal_linear_update(*update_args)
else:
normal_probit_update(**update_args)
def test_sqrt_cov_update_with_nans(setup_linear_update, expected_linear_update):
d = setup_linear_update
kf.sqrt_linear_update(
d["state"],
d["mcovs"],
d["like_vector"],
d["y"],
d["c"],
d["delta"],
d["h"],
d["sqrt_r"],
d["positions"],
d["weights"],
)
modified_mcovs = d["cholcovs"]
make_unique(modified_mcovs.reshape(12, 3, 3))
aaae(modified_mcovs, expected_linear_update["exp_cholcovs"])
def test_sqrt_weight_update_with_nans(self):
kf.sqrt_linear_update(
self.states, self.mcovs, self.like_vec, self.y, self.c,
self.delta, self.h, self.sqrt_r, self.positions, self.weights)
aaae(self.weights, self.exp_weights)
def test_sqrt_weight_update_with_nans(self):
kf.sqrt_linear_update(self.states, self.mcovs, self.like_vec, self.y,
self.c, self.delta, self.h, self.sqrt_r,
self.positions, self.weights)
aaae(self.weights, self.exp_weights)