def random(d_shape, Q_shape, sp_shape, dim, rank=None):
if rank is None:
rank = dim
ndim = len(d_shape)
temp = np.random.normal(size=Q_shape + (dim, rank))
Q, _ = array_map(np.linalg.qr, [temp], ndim)
d = np.random.gamma(1., 1., size=d_shape + (rank, ))
sp = np.random.gamma(1., 1., size=sp_shape)
return FixedEigMatrix(d, Q, sp)
def random(d_shape, Q_shape, sp_shape, dim, rank=None):
if rank is None:
rank = dim
ndim = len(d_shape)
temp = np.random.normal(size=Q_shape + (dim, rank))
Q, _ = array_map(np.linalg.qr, [temp], ndim)
d = np.random.gamma(1., 1., size=d_shape + (rank,))
sp = np.random.gamma(1., 1., size=sp_shape)
return FixedEigMatrix(d, Q, sp)
def pinv(self):
try:
return FullMatrix(array_map(my_inv, [self._S], self.ndim))
except np.linalg.LinAlgError:
return FullMatrix(array_map(np.linalg.pinv, [self._S], self.ndim))
def full(self):
S = array_map(np.diag, [self._s], self.ndim)
return FullMatrix(S)
def to_eig(self):
d, Q = array_map(np.linalg.eigh, [self._S], self.ndim)
return FixedEigMatrix(d, Q, 0)
def sqrt_dot(self, x):
L = array_map(np.linalg.cholesky, [self._S + 1e-10 * np.eye(self.dim)], self.ndim)
return dot(L, x)
def conv(self, other):
other = other.full()
P = array_map(my_inv, [self._S + other._S], self.ndim)
return FullMatrix(dot(self._S, dot(P, other._S)))
def inv(self):
return FullMatrix(array_map(np.linalg.inv, [self._S], self.ndim))
def inv(self):
return FullMatrix(array_map(my_inv, [self._S], self.ndim))
def pinv(self):
try:
return FullMatrix(array_map(my_inv, [self._S], self.ndim))
except np.linalg.LinAlgError:
return FullMatrix(array_map(np.linalg.pinv, [self._S], self.ndim))
def full(self):
S = array_map(np.diag, [self._s], self.ndim)
return FullMatrix(S)
def to_eig(self):
d, Q = array_map(np.linalg.eigh, [self._S], self.ndim)
return FixedEigMatrix(d, Q, 0)
def sqrt_dot(self, x):
L = array_map(np.linalg.cholesky, [self._S + 1e-10 * np.eye(self.dim)],
self.ndim)
return dot(L, x)
def conv(self, other):
other = other.full()
P = array_map(my_inv, [self._S + other._S], self.ndim)
return FullMatrix(dot(self._S, dot(P, other._S)))
def inv(self):
return FullMatrix(array_map(my_inv, [self._S], self.ndim))
def logdet(self):
_, ld = array_map(np.linalg.slogdet, [self._S], self.ndim)
return ld
def logdet(self):
_, ld = array_map(np.linalg.slogdet, [self._S], self.ndim)
return ld
def inv(self):
return FullMatrix(array_map(np.linalg.inv, [self._S], self.ndim))