def test_dcost(self):
state_grid = np.arange ( 1, 365*10, 5 )
gamma = 100
lag = 1
N = len(state_grid)
state_config = OrderedDict ({'magnitude':3})
I = np.identity( N )
D = np.matrix(I - np.roll( I, lag ))
x = np.ones_like(state_grid)*3.
a = TemporalSmoother ( state_grid, gamma, lag=lag, required_params=['magnitude'] )
x_dict = OrderedDict ({'magnitude':x})
cost = gamma*(D.dot(x)).T.dot(D.dot(x))
assert_equal ( np.squeeze(a.der_cost( x_dict, state_config)[1]), np.zeros(N) )
def test_cost(self):
state_grid = np.arange ( 1, 365*10, 5 )
gamma = 100
lag = 1
N = len(state_grid)
state_config = OrderedDict ({'magnitude':3})
I = np.identity( N )
D = np.matrix(I - np.roll( I, lag ))
x = np.ones_like(state_grid)*3.
a = TemporalSmoother ( state_grid, gamma, lag=lag, required_params=['magnitude'] )
x_dict = OrderedDict ({'magnitude':x})
cost = x.dot ( D*D.T).dot(x)
cost = 0.5*gamma*cost
#import pdb; pdb.set_trace()
assert_equal ( np.squeeze(a.der_cost( x_dict, state_config)[0]), cost )
def test_dcost(self):
state_grid = np.arange(1, 365 * 10, 5)
gamma = 100
lag = 1
N = len(state_grid)
state_config = OrderedDict({'magnitude': 3})
I = np.identity(N)
D = np.matrix(I - np.roll(I, lag))
x = np.ones_like(state_grid) * 3.
a = TemporalSmoother(state_grid,
gamma,
lag=lag,
required_params=['magnitude'])
x_dict = OrderedDict({'magnitude': x})
cost = gamma * (D.dot(x)).T.dot(D.dot(x))
assert_equal(np.squeeze(a.der_cost(x_dict, state_config)[1]),
np.zeros(N))
def test_cost(self):
state_grid = np.arange(1, 365 * 10, 5)
gamma = 100
lag = 1
N = len(state_grid)
state_config = OrderedDict({'magnitude': 3})
I = np.identity(N)
D = np.matrix(I - np.roll(I, lag))
x = np.ones_like(state_grid) * 3.
a = TemporalSmoother(state_grid,
gamma,
lag=lag,
required_params=['magnitude'])
x_dict = OrderedDict({'magnitude': x})
cost = x.dot(D * D.T).dot(x)
cost = 0.5 * gamma * cost
#import pdb; pdb.set_trace()
assert_equal(np.squeeze(a.der_cost(x_dict, state_config)[0]), cost)