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 testPredictionNotChangeModel(self):
timeSeries = [1, 2, 1, 5, 3, 5, 4, 8, 1, 2]
dlm1 = dlm(timeSeries) + trend(degree=2, discount=0.95)
dlm1.fitForwardFilter()
(obs1, var1) = dlm1.predictN(N=1, date=dlm1.n - 1)
dlm2 = dlm([]) + trend(degree=2, discount=0.95)
for d in timeSeries:
dlm2.append([d], component='main')
dlm2.fitForwardFilter()
(obs2, var2) = dlm2.predictN(N=1, date=dlm2.n - 1)
self.assertAlmostEqual(obs1, obs2)
self.assertAlmostEqual(var1, var2)
def setUp(self):
self.data = np.random.rand(10).tolist()
self.features = np.random.rand(10, 2).tolist()
self.trend = trend(degree=2, w=1.0)
self.seasonality = seasonality(period=7, w=1.0)
self.dynamic = dynamic(self.features, w=1.0)
self.autoReg = autoReg(degree=3, w=1.0)
self.builder1 = builder()
def testAdd(self):
trend2 = trend(2, name='trend2')
self.dlm1 = self.dlm1 + trend2
self.assertEqual(self.dlm1.builder.staticComponents['trend2'], trend2)
dynamic2 = dynamic(features=self.features, name='d2')
self.dlm1 = self.dlm1 + dynamic2
self.assertEqual(self.dlm1.builder.dynamicComponents['d2'], dynamic2)
ar3 = autoReg(degree=3, name='ar3')
self.dlm1 = self.dlm1 + ar3
self.assertEqual(self.dlm1.builder.automaticComponents['ar3'], ar3)
def setUp(self):
self.data = [0] * 9 + [1] + [0] * 10
self.data5 = range(100)
self.features = np.random.random((20, 2)).tolist()
self.trend0 = trend(degree=0, discount=1.0, w=1.0)
self.trend1 = trend(degree=0, discount=1.0)
self.dlm1 = dlm(self.data)
self.dlm2 = dlm(self.data)
self.dlm3 = dlm([-1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1])
self.dlm4 = dlm([0, 0, 0, 0, 0, 1, 1, 1, 1, 1])
self.dlm5 = dlm(self.data5)
self.dlm6 = dlm(self.data5)
self.dlm1 + trend(degree=0, discount=1, w=1.0)
self.dlm2 + trend(degree=0, discount=1e-12, w=1.0)
self.dlm3 + seasonality(period=2, discount=1, w=1.0)
self.dlm4 + dynamic(features=[[0]
for i in range(5)] + [[1]
for i in range(5)],
discount=1,
w=1.0)
self.dlm5 + trend(degree=0, discount=1, w=1.0) + \
autoReg(degree=1, discount=1, w=1.0)
self.dlm6 + trend(degree=0, discount=1, w=1.0) + \
autoReg(degree=2, discount=1, w=1.0)
self.dlm1.evolveMode('dependent')
self.dlm2.evolveMode('dependent')
self.dlm3.evolveMode('dependent')
self.dlm4.evolveMode('dependent')
self.dlm5.evolveMode('dependent')
self.dlm6.evolveMode('dependent')
def setUp(self):
self.data = [0] * 9 + [1] + [0] * 10
self.data5 = range(100)
self.dlm1 = _dlm(self.data)
self.dlm2 = _dlm(self.data)
self.dlm3 = _dlm([-1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1])
self.dlm4 = _dlm([0, 0, 0, 0, 0, 1, 1, 1, 1, 1])
self.dlm5 = _dlm(self.data5)
self.dlm6 = _dlm(self.data5)
self.dlm7 = _dlm([0, 1, None, 1, 0, 1, -1])
self.dlm1.builder + trend(degree=0, discount=1, w=1.0)
self.dlm2.builder + trend(degree=0, discount=1e-12, w=1.0)
self.dlm3.builder + seasonality(period=2, discount=1, w=1.0)
self.dlm4.builder + dynamic(
features=[[0] for i in range(5)] + [[1] for i in range(5)],
discount=1,
w=1.0)
self.dlm5.builder + trend(degree=0, discount=1, w=1.0) + \
autoReg(degree=1, discount=1, w=1.0)
self.dlm6.builder + trend(degree=0, discount=0.9, w=1.0) + \
seasonality(period=2, discount=0.8, w=1.0) + \
autoReg(degree=3, discount=1.0)
self.dlm7.builder + trend(degree=0, discount=1, w=1.0)
self.dlm1._initialize()
self.dlm2._initialize()
self.dlm3._initialize()
self.dlm4._initialize()
self.dlm5._initialize()
self.dlm6._initialize()
self.dlm7._initialize()
self.dlm1.options.innovationType = 'whole'
self.dlm2.options.innovationType = 'whole'
self.dlm3.options.innovationType = 'whole'
self.dlm4.options.innovationType = 'whole'
self.dlm5.options.innovationType = 'whole'
self.dlm6.options.innovationType = 'whole'
self.dlm7.options.innovationType = 'whole'
def testDelete(self):
trend2 = trend(2, name='trend2')
self.dlm1 = self.dlm1 + trend2
self.dlm1.delete('trend2')
self.assertEqual(len(self.dlm1.builder.staticComponents), 1)