def test_initialization():
# Test Kalman filter initialization
mod = Representation(1, k_states=2)
# Test invalid state initialization
assert_raises(RuntimeError, lambda: mod._initialize_state())
# Test valid initialization
initial_state = np.zeros(2, ) + 1.5
initial_state_cov = np.eye(2) * 3.
mod.initialize_known(initial_state, initial_state_cov)
assert_equal(mod._initial_state.sum(), 3)
assert_equal(mod._initial_state_cov.diagonal().sum(), 6)
# Test invalid initial_state
initial_state = np.zeros(10, )
assert_raises(
ValueError,
lambda: mod.initialize_known(initial_state, initial_state_cov))
initial_state = np.zeros((10, 10))
assert_raises(
ValueError,
lambda: mod.initialize_known(initial_state, initial_state_cov))
# Test invalid initial_state_cov
initial_state = np.zeros(2, ) + 1.5
initial_state_cov = np.eye(3)
assert_raises(
ValueError,
lambda: mod.initialize_known(initial_state, initial_state_cov))
def test_initialization():
# Test Kalman filter initialization
mod = Representation(1, k_states=2)
# Test invalid state initialization
assert_raises(RuntimeError, lambda: mod._initialize_state())
# Test valid initialization
initial_state = np.zeros(2,) + 1.5
initial_state_cov = np.eye(2) * 3.
mod.initialize_known(initial_state, initial_state_cov)
assert_equal(mod._initial_state.sum(), 3)
assert_equal(mod._initial_state_cov.diagonal().sum(), 6)
# Test invalid initial_state
initial_state = np.zeros(10,)
assert_raises(ValueError, lambda: mod.initialize_known(initial_state, initial_state_cov))
initial_state = np.zeros((10,10))
assert_raises(ValueError, lambda: mod.initialize_known(initial_state, initial_state_cov))
# Test invalid initial_state_cov
initial_state = np.zeros(2,) + 1.5
initial_state_cov = np.eye(3)
assert_raises(ValueError, lambda: mod.initialize_known(initial_state, initial_state_cov))
def test_representation():
# Test Representation construction
# Test an invalid number of states
def zero_kstates():
mod = Representation(1, 0)
assert_raises(ValueError, zero_kstates)
# Test an invalid endogenous array
def empty_endog():
endog = np.zeros((0,0))
mod = Representation(endog, k_states=2)
assert_raises(ValueError, empty_endog)
# Test a Fortran-ordered endogenous array (which will be assumed to be in
# wide format: k_endog x nobs)
nobs = 10
k_endog = 2
endog = np.asfortranarray(np.arange(nobs*k_endog).reshape(k_endog,nobs)*1.)
mod = Representation(endog, k_states=2)
assert_equal(mod.nobs, nobs)
assert_equal(mod.k_endog, k_endog)
# Test a C-ordered endogenous array (which will be assumed to be in
# tall format: nobs x k_endog)
nobs = 10
k_endog = 2
endog = np.arange(nobs*k_endog).reshape(nobs,k_endog)*1.
mod = Representation(endog, k_states=2)
assert_equal(mod.nobs, nobs)
assert_equal(mod.k_endog, k_endog)
# Test getting the statespace representation
assert_equal(mod._statespace, None)
mod._initialize_representation()
assert_equal(mod._statespace is not None, True)
def test_representation():
# Test Representation construction
# Test an invalid number of states
def zero_kstates():
mod = Representation(1, 0)
assert_raises(ValueError, zero_kstates)
# Test an invalid endogenous array
def empty_endog():
endog = np.zeros((0, 0))
mod = Representation(endog, k_states=2)
assert_raises(ValueError, empty_endog)
# Test a Fortran-ordered endogenous array (which will be assumed to be in
# wide format: k_endog x nobs)
nobs = 10
k_endog = 2
endog = np.asfortranarray(
np.arange(nobs * k_endog).reshape(k_endog, nobs) * 1.)
mod = Representation(endog, k_states=2)
assert_equal(mod.nobs, nobs)
assert_equal(mod.k_endog, k_endog)
# Test a C-ordered endogenous array (which will be assumed to be in
# tall format: nobs x k_endog)
nobs = 10
k_endog = 2
endog = np.arange(nobs * k_endog).reshape(nobs, k_endog) * 1.
mod = Representation(endog, k_states=2)
assert_equal(mod.nobs, nobs)
assert_equal(mod.k_endog, k_endog)
# Test getting the statespace representation
assert_equal(mod._statespace, None)
mod._initialize_representation()
assert_equal(mod._statespace is not None, True)
def test_bind():
# Test binding endogenous data to Kalman filter
mod = Representation(1, k_states=2)
# Test invalid endogenous array (it must be ndarray)
assert_raises(ValueError, lambda: mod.bind([1, 2, 3, 4]))
# Test valid (nobs x 1) endogenous array
mod.bind(np.arange(10) * 1.)
assert_equal(mod.nobs, 10)
# Test valid (k_endog x 0) endogenous array
mod.bind(np.zeros(0, dtype=np.float64))
# Test invalid (3-dim) endogenous array
assert_raises(ValueError,
lambda: mod.bind(np.arange(12).reshape(2, 2, 3) * 1.))
# Test valid F-contiguous
mod.bind(np.asfortranarray(np.arange(10).reshape(1, 10)))
assert_equal(mod.nobs, 10)
# Test valid C-contiguous
mod.bind(np.arange(10).reshape(10, 1))
assert_equal(mod.nobs, 10)
# Test invalid F-contiguous
assert_raises(
ValueError,
lambda: mod.bind(np.asfortranarray(np.arange(10).reshape(10, 1))))
# Test invalid C-contiguous
assert_raises(ValueError, lambda: mod.bind(np.arange(10).reshape(1, 10)))
def empty_endog():
endog = np.zeros((0, 0))
mod = Representation(endog, k_states=2)
def zero_kstates():
mod = Representation(1, 0)
def test_bind():
# Test binding endogenous data to Kalman filter
mod = Representation(1, k_states=2)
# Test invalid endogenous array (it must be ndarray)
assert_raises(ValueError, lambda: mod.bind([1,2,3,4]))
# Test valid (nobs x 1) endogenous array
mod.bind(np.arange(10)*1.)
assert_equal(mod.nobs, 10)
# Test valid (k_endog x 0) endogenous array
mod.bind(np.zeros(0,dtype=np.float64))
# Test invalid (3-dim) endogenous array
assert_raises(ValueError, lambda: mod.bind(np.arange(12).reshape(2,2,3)*1.))
# Test valid F-contiguous
mod.bind(np.asfortranarray(np.arange(10).reshape(1,10)))
assert_equal(mod.nobs, 10)
# Test valid C-contiguous
mod.bind(np.arange(10).reshape(10,1))
assert_equal(mod.nobs, 10)
# Test invalid F-contiguous
assert_raises(ValueError, lambda: mod.bind(np.asfortranarray(np.arange(10).reshape(10,1))))
# Test invalid C-contiguous
assert_raises(ValueError, lambda: mod.bind(np.arange(10).reshape(1,10)))
