def setUp(self):
self.kf1 = kalmanFilter(discount=[1])
self.kf0 = kalmanFilter(discount=[1e-10])
self.kf11 = kalmanFilter(discount=[1, 1])
self.trend0 = trend(degree=0, discount=1, w=1.0)
self.trend0_90 = trend(degree=0, discount=0.9, w=1.0)
self.trend0_98 = trend(degree=0, discount=0.98, w=1.0, name='a')
self.trend1 = trend(degree=1, discount=1, w=1.0)
def _initializeFromBuilder(self, exported_builder):
self.builder.initializeFromBuilder(data=self.data, exported_builder=exported_builder)
self.Filter = kalmanFilter(discount=self.builder.discount,
updateInnovation=self.options.innovationType,
index=self.builder.componentIndex)
self.result = self._result(self.n)
self.initialized = True
def _initializeFromBuilder(self, exported_builder):
self.builder.initializeFromBuilder(data=self.data, exported_builder=exported_builder)
self.Filter = kalmanFilter(discount=self.builder.discount,
updateInnovation=self.options.innovationType,
index=self.builder.componentIndex)
self.result = self._result(self.n)
self.initialized = True
def _initialize(self):
""" Initialize the model: initialize builder and filter.
"""
self.builder.initialize(noise=self.options.noise)
self.Filter = kalmanFilter(discount=self.builder.discount,
updateInnovation=self.options.innovationType,
index=self.builder.componentIndex)
self.result = self._result(self.n)
self.initialized = True
def _initialize(self):
""" Initialize the model: initialize builder and filter.
"""
self._autoNoise()
self.builder.initialize(noise=self.options.noise, data=self.padded_data)
self.Filter = kalmanFilter(discount=self.builder.discount,
updateInnovation=self.options.innovationType,
index=self.builder.componentIndex)
self.result = self._result(self.n)
self.initialized = True
def testEvolveMode(self):
dlm = builder()
dlm.add(trend(degree=1, discount=0.9, w=1.0))
dlm.add(trend(degree=1, discount=0.98, name='a', w=1.0))
dlm.initialize()
kf2 = kalmanFilter(discount=[0.9, 0.98],
updateInnovation='component',
index=dlm.componentIndex)
kf2.forwardFilter(dlm.model, 1.0)
self.assertAlmostEqual(dlm.model.innovation[0, 1], 0.0)
self.assertAlmostEqual(dlm.model.innovation[1, 0], 0.0)
def _initialize(self):
""" Initialize the model: initialize builder and filter.
"""
self.builder.initialize(noise=self.options.noise)
#if self.options.shrink == 'auto':
# self.Filter = kalmanFilter(discount = self.builder.discount, \
# shrink = 1 - min(self.builder.discount), \
# shrinkageMatrix = self.builder.sysVarPrior)
#else:
self.Filter = kalmanFilter(discount=self.builder.discount)
self.result = self._result(self.n)
self.initialized = True
def _initialize(self):
""" Initialize the model: initialize builder and filter.
"""
self.builder.initialize(noise=self.options.noise)
# if self.options.shrink == 'auto':
# self.Filter = kalmanFilter(discount = self.builder.discount,
# shrink = 1 - min(self.builder.discount),
# shrinkageMatrix = self.builder.sysVarPrior)
# else:
self.Filter = kalmanFilter(discount=self.builder.discount,
updateInnovation=self.options.innovationType,
index=self.builder.componentIndex)
self.result = self._result(self.n)
self.initialized = True
def setUp(self):
self.kf1 = kalmanFilter(discount=[1])
self.kf0 = kalmanFilter(discount=[1e-10])
self.kf11 = kalmanFilter(discount=[1, 1])
