def test_KCSD2D_cross_validation_five_electrodes(self):
lambdas = np.array([100.0 / 2**n for n in range(1, 20)])
n_elec = self.k.elec_pos.shape[0]
index_generator = LeaveOneOut(n_elec) #, indices=True)
self.k.lambd = cv.choose_lambda(lambdas, self.k.sampled_pots,
self.k.k_pot, self.k.elec_pos,
index_generator)
self.assertGreater(self.k.lambd, 25.0)
def test_KCSD2D_cross_validation_five_electrodes(self):
lambdas = np.array([100.0/2**n for n in xrange(1, 20)])
n_elec = self.k.elec_pos.shape[0]
index_generator = LeaveOneOut(n_elec, indices=True)
self.k.lambd = cv.choose_lambda(lambdas,
self.k.sampled_pots,
self.k.k_pot, self.k.elec_pos,
index_generator)
self.assertGreater(self.k.lambd, 25.0)
def test_KCSD_1D_lambda_choice(self):
"""for potentials calculated from model, lambda < 1.0"""
params = {'sigma': self.sigma, 'source_type': 'gauss_lim',
'x_min': -5.0, 'x_max': 10.0, 'h': self.h}
k = KCSD(self.elec_pos, self.meas_pot, params)
lambdas = np.array([100.0/2**n for n in xrange(1, 20)])
n_elec = k.solver.elec_pos.shape[0]
index_generator = LeaveOneOut(n_elec, indices=True)
k.solver.lambd = cv.choose_lambda(lambdas, k.solver.sampled_pots,
k.solver.k_pot, k.solver.elec_pos,
index_generator)
self.assertLess(k.solver.lambd, 1.0)
def test_KCSD_1D_cross_validation_two_electrodes(self):
"""cross validation should promote high lambdas in this case"""
params = {'x_min': 0.0, 'x_max': 1.0, 'gdX': 0.1,
'source_type': 'gauss_lim'}
k = KCSD(elec_pos=np.array([[0.2], [0.7]]),
sampled_pots=np.array([[1.0, 0.5]]).T,
params=params)
k.estimate_pots()
lambdas = np.array([0.1, 0.5, 1.0])
n_elec = k.solver.elec_pos.shape[0]
index_generator = LeaveOneOut(n_elec, indices=True)
k.solver.lambd = cv.choose_lambda(lambdas, k.solver.sampled_pots,
k.solver.k_pot, k.solver.elec_pos,
index_generator)
self.assertEquals(k.solver.lambd, 1.0)
def test_KCSD_1D_lambda_choice(self):
"""for potentials calculated from model, lambda < 1.0"""
params = {
'sigma': self.sigma,
'source_type': 'gauss_lim',
'x_min': -5.0,
'x_max': 10.0,
'h': self.h
}
k = KCSD(self.elec_pos, self.meas_pot, params)
lambdas = np.array([100.0 / 2**n for n in range(1, 20)])
n_elec = k.solver.elec_pos.shape[0]
index_generator = LeaveOneOut(n_elec) #, indices=True)
k.solver.lambd = cv.choose_lambda(lambdas, k.solver.sampled_pots,
k.solver.k_pot, k.solver.elec_pos,
index_generator)
self.assertLess(k.solver.lambd, 1.0)
def test_KCSD_1D_cross_validation_two_electrodes(self):
"""cross validation should promote high lambdas in this case"""
params = {
'x_min': 0.0,
'x_max': 1.0,
'gdX': 0.1,
'source_type': 'gauss_lim'
}
k = KCSD(elec_pos=np.array([[0.2], [0.7]]),
sampled_pots=np.array([[1.0, 0.5]]).T,
params=params)
k.estimate_pots()
lambdas = np.array([0.1, 0.5, 1.0])
n_elec = k.solver.elec_pos.shape[0]
index_generator = LeaveOneOut(n_elec) #, indices=True)
k.solver.lambd = cv.choose_lambda(lambdas, k.solver.sampled_pots,
k.solver.k_pot, k.solver.elec_pos,
index_generator)
self.assertEqual(k.solver.lambd, 1.0)