class TestLowRank(unittest.TestCase):
"""test class for CLowRankCF"""
def setUp(self):
sp.random.seed(1)
self.n = 4
self.rank = 2
self.C = LowRankCov(self.n,self.rank)
self.name = 'lowrank'
self.C.setRandomParams()
def test_grad(self):
def func(x, i):
self.C.setParams(x)
return self.C.K()
def grad(x, i):
self.C.setParams(x)
return self.C.K_grad_i(i)
x0 = self.C.getParams()
err = mcheck_grad(func, grad, x0)
np.testing.assert_almost_equal(err, 0., decimal = 6)
def test_param_activation(self):
self.assertEqual(len(self.C.getParams()), 8)
self.C.act_X = False
self.assertEqual(len(self.C.getParams()), 0)
self.C.setParams(np.array([]))
with self.assertRaises(ValueError):
self.C.setParams(np.array([0]))
with self.assertRaises(ValueError):
self.C.K_grad_i(0)
class TestLowRank(unittest.TestCase):
"""test class for CLowRankCF"""
def setUp(self):
sp.random.seed(1)
self.n = 4
self.rank = 2
self.C = LowRankCov(self.n, self.rank)
self.name = 'lowrank'
self.C.setRandomParams()
def test_grad(self):
def func(x, i):
self.C.setParams(x)
return self.C.K()
def grad(x, i):
self.C.setParams(x)
return self.C.K_grad_i(i)
x0 = self.C.getParams()
err = mcheck_grad(func, grad, x0)
np.testing.assert_almost_equal(err, 0., decimal=6)
def test_param_activation(self):
self.assertEqual(len(self.C.getParams()), 8)
self.C.act_X = False
self.assertEqual(len(self.C.getParams()), 0)
self.C.setParams(np.array([]))
with self.assertRaises(ValueError):
self.C.setParams(np.array([0]))
with self.assertRaises(ValueError):
self.C.K_grad_i(0)
def setColCovars(self, Cg=None, Cn=None, rank=1, Cr=None):
assert Cg is not None, 'Cov2KronSum: Specify Cg!'
assert Cn is not None, 'Cov2KronSum: Specify Cn!'
assert Cg.dim==Cn.dim, 'Cov2KronSum: Cg and Cn must have same dimensions!'
if Cr is None:
Cr = LowRankCov(Cg.dim, rank)
Cr.setRandomParams()
self._rank_c = rank
else:
self._rank_c = Cr.X.shape[1]
self._dim_c = Cg.dim
self._Cr = Cr
self._Cg = Cg
self._Cn = Cn
self._Cg.register(self.col_covs_have_changed)
self._Cn.register(self.col_covs_have_changed)
self.col_covs_have_changed()
def setColCovars(self, Cg=None, Cn=None, rank=1, Cr=None):
assert Cg is not None, 'Cov2KronSum: Specify Cg!'
assert Cn is not None, 'Cov2KronSum: Specify Cn!'
assert Cg.dim == Cn.dim, 'Cov2KronSum: Cg and Cn must have same dimensions!'
if Cr is None:
Cr = LowRankCov(Cg.dim, rank)
Cr.setRandomParams()
self._rank_c = rank
else:
self._rank_c = Cr.X.shape[1]
self._dim_c = Cg.dim
self._Cr = Cr
self._Cg = Cg
self._Cn = Cn
self._Cg.register(self.col_covs_have_changed)
self._Cn.register(self.col_covs_have_changed)
self.col_covs_have_changed()
def setColCovars(self, Cg=None, Cn=None, rank=1, Cr=None):
assert Cg is not None, 'Cov2KronSum: Specify Cg!'
assert Cn is not None, 'Cov2KronSum: Specify Cn!'
assert Cg.dim==Cn.dim, 'Cov2KronSum: Cg and Cn must have same dimensions!'
assert Cr is None, '%s: more general covariance matrices are not supported at the moment' % self.__class__.__name__
if Cr is None:
Cr = LowRankCov(Cg.dim, rank)
Cr.setRandomParams()
self._rank_c = rank
else:
self._rank_c = self.Cr.dim()
self._dim_c = Cg.dim
self._Cr = Cr
self._Cg = Cg
self._Cn = Cn
self._Cg.register(self.col_covs_have_changed)
self._Cn.register(self.col_covs_have_changed)
self.col_covs_have_changed()
