def multivariate_norm_log_pdf(self,x,mu,cov):
# -0.5 * (dot(x-mu,dot(inv(cov),x-mu)) + len(x)*log(2*pi) + log(det(cov)))
self.vec_d_y[:] = x
self.vec_d_y[:] -= mu
solve(cov,reshape(self.vec_d_y,(-1,1)),reshape(self.vec_d_y2,(-1,1)),
self.covf,self.colvecf,self.pivotscov)
ret = dot(self.vec_d_y,self.vec_d_y2)
ret += len(x)*log(2*pi)
lu(cov,self.pcov,self.Lcov,self.Ucov,self.covf,self.pivotscov)
getdiag(self.Ucov,self.vec_d_y)
absolute(self.vec_d_y,self.vec_d_y2)
log(self.vec_d_y2,self.vec_d_y)
ret += sum(self.vec_d_y)
ret *= -0.5
return ret
def multivariate_norm_log_pdf(self, x, mu, cov):
# -0.5 * (dot(x-mu,dot(inv(cov),x-mu)) + len(x)*log(2*pi) + log(det(cov)))
self.vec_d_y[:] = x
self.vec_d_y[:] -= mu
solve(cov, reshape(self.vec_d_y, (-1, 1)),
reshape(self.vec_d_y2, (-1, 1)), self.covf, self.colvecf,
self.pivotscov)
ret = dot(self.vec_d_y, self.vec_d_y2)
ret += len(x) * log(2 * pi)
lu(cov, self.pcov, self.Lcov, self.Ucov, self.covf, self.pivotscov)
getdiag(self.Ucov, self.vec_d_y)
absolute(self.vec_d_y, self.vec_d_y2)
log(self.vec_d_y2, self.vec_d_y)
ret += sum(self.vec_d_y)
ret *= -0.5
return ret
def multivariate_norm_log_pdf(self,x,mu,cov):
#return -0.5 * (dot(x-mu,dot(inv(cov),x-mu)) + len(x)*log(2*pi) + sum(log(eigvals(cov))))
#return_old = -0.5 * (dot(x-mu,solve(cov,x-mu)) + len(x)*log(2*pi) + sum(log(abs(diag(scipy.linalg.lu(cov)[2])))))
self.vec_d_y[:] = x
self.vec_d_y[:] -= mu
solve(cov,reshape(self.vec_d_y,(-1,1)),reshape(self.vec_d_y2,(-1,1)),
self.covf,self.colvecf,self.pivotscov)
ret = dot(self.vec_d_y,self.vec_d_y2)
ret += len(x)*log(2*pi)
lu(cov,self.pcov,self.Lcov,self.Ucov,self.covf,self.pivotscov)
getdiag(self.Ucov,self.vec_d_y)
absolute(self.vec_d_y,self.vec_d_y2)
log(self.vec_d_y2,self.vec_d_y)
ret += sum(self.vec_d_y)
ret *= -0.5
return ret
def multivariate_norm_log_pdf(self, x, mu, cov):
#return -0.5 * (dot(x-mu,dot(inv(cov),x-mu)) + len(x)*log(2*pi) + sum(log(eigvals(cov))))
#return_old = -0.5 * (dot(x-mu,solve(cov,x-mu)) + len(x)*log(2*pi) + sum(log(abs(diag(scipy.linalg.lu(cov)[2])))))
self.vec_d_y[:] = x
self.vec_d_y[:] -= mu
solve(cov, reshape(self.vec_d_y, (-1, 1)),
reshape(self.vec_d_y2, (-1, 1)), self.covf, self.colvecf,
self.pivotscov)
ret = dot(self.vec_d_y, self.vec_d_y2)
ret += len(x) * log(2 * pi)
lu(cov, self.pcov, self.Lcov, self.Ucov, self.covf, self.pivotscov)
getdiag(self.Ucov, self.vec_d_y)
absolute(self.vec_d_y, self.vec_d_y2)
log(self.vec_d_y2, self.vec_d_y)
ret += sum(self.vec_d_y)
ret *= -0.5
return ret
