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feat: Check for symmetry and positive-semidefiniteness of covariance matrices in the initialization of covobs

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This commit is contained in:
Simon Kuberski 2022-02-25 17:39:49 +01:00
commit 751d28711f
2 changed files with 35 additions and 3 deletions
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29
pyerrors/covobs.py
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@ -45,6 +45,16 @@ class Covobs:
return float(np.dot(np.transpose(self.grad), np.dot(self.cov, self.grad)))
def _set_cov(self, cov):
""" Set the covariance matrix of the covobs
Parameters
----------
cov : list or array
Has to be either of:
0 dimensional number: variance of a single covobs,
1 dimensional list or array of lenght N: variances of multiple covobs
2 dimensional list or array (N x N): Symmetric, positive-semidefinite covariance matrix
"""
self._cov = np.array(cov)
if self._cov.ndim == 0:
self.N = 1
@ -59,7 +69,26 @@ class Covobs:
else:
raise Exception('Covariance matrix has to be a 2 dimensional square matrix!')
for i in range(self.N):
for j in range(i):
if not self._cov[i][j] == self._cov[j][i]:
raise Exception('Covariance matrix is non-symmetric for (%d, %d' % (i, j))
evals = np.linalg.eigvalsh(self._cov)
for ev in evals:
if ev < 0:
raise Exception('Covariance matrix is not positive-semidefinite!')
def _set_grad(self, grad):
""" Set the gradient of the covobs
Parameters
----------
grad : list or array
Has to be either of:
0 dimensional number: gradient w.r.t. a single covobs,
1 dimensional list or array of lenght N: gradient w.r.t. multiple covobs
"""
self._grad = np.array(grad)
if self._grad.ndim in [0, 1]:
self._grad = np.reshape(self._grad, (self.N, 1))

9
tests/covobs_test.py
View file

@ -78,9 +78,8 @@ def test_covobs_init():
covobs = pe.cov_Obs(0.5, 0.002, 'test')
covobs = pe.cov_Obs([1, 2], [0.1, 0.2], 'test')
covobs = pe.cov_Obs([1, 2], np.array([0.1, 0.2]), 'test')
covobs = pe.cov_Obs([1, 2], [[0.1, 0.2], [0.1, 0.2]], 'test')
covobs = pe.cov_Obs([1, 2], np.array([[0.1, 0.2], [0.1, 0.2]]), 'test')
covobs = pe.cov_Obs([1, 2], [[0.21, 0.2], [0.2, 0.21]], 'test')
covobs = pe.cov_Obs([1, 2], np.array([[0.21, 0.2], [0.2, 0.21]]), 'test')
def test_covobs_exceptions():
@ -92,3 +91,7 @@ def test_covobs_exceptions():
covobs = pe.cov_Obs([0.5, 0.1], np.array([[2, 1, 3], [1, 2, 3]]), 'test')
with pytest.raises(Exception):
covobs = pe.cov_Obs([0.5, 0.1], np.random.random((2, 2, 2)), 'test')
with pytest.raises(Exception):
covobs = pe.cov_Obs([1.5, 0.1], [[1., .2,], [.3, .5]] , 'test')
with pytest.raises(Exception):
covobs = pe.cov_Obs([1.5, 0.1], [[8, 4,], [4, -2]] , 'test')