feat: rounding errors in inversion of cholesky decomposed correlation

matrix reduced.
This commit is contained in:
Fabian Joswig 2022-05-27 13:50:19 +01:00
parent e7f5961cd6
commit 09fd1fdf60

View file

@ -477,8 +477,7 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
if condn > 1 / np.sqrt(np.finfo(float).eps):
warnings.warn("Correlation matrix may be ill-conditioned, condition number: {%1.2e}" % (condn), RuntimeWarning)
chol = np.linalg.cholesky(corr)
chol_inv = np.linalg.inv(chol)
chol_inv = np.dot(chol_inv, covdiag)
chol_inv = scipy.linalg.solve(chol, covdiag)
def chisqfunc_corr(p):
model = func(p, x)