lattice/pyerrors
1
0
Fork 0
mirror of https://github.com/fjosw/pyerrors.git synced 2025-03-15 06:40:24 +01:00
Code Issues Projects Releases Packages Wiki Activity

fix: no-autograd exception in fits works again.

Browse source
This commit is contained in:
Fabian Joswig 2022-05-25 14:51:46 +01:00
parent 9ad0146d96
commit 967ddb0ecd
1 changed files with 8 additions and 6 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

14
pyerrors/fits.py
View file

@ -263,14 +263,15 @@ def total_least_squares(x, y, func, silent=False, **kwargs):
output.chisquare_by_expected_chisquare)
fitp = out.beta
hess = jacobian(jacobian(odr_chisquare))(np.concatenate((fitp, out.xplus.ravel())))
try:
hess = jacobian(jacobian(odr_chisquare))(np.concatenate((fitp, out.xplus.ravel())))
except TypeError:
raise Exception("It is required to use autograd.numpy instead of numpy within fit functions, see the documentation for details.") from None
condn = np.linalg.cond(hess)
if condn > 1e8:
warnings.warn("Hessian matrix might be ill-conditioned ({0:1.2e}), error propagation might be unreliable.".format(condn), RuntimeWarning)
try:
hess_inv = np.linalg.inv(hess)
except TypeError:
raise Exception("It is required to use autograd.numpy instead of numpy within fit functions, see the documentation for details.") from None
except np.linalg.LinAlgError:
raise Exception("Cannot invert hessian matrix.")
except Exception:
@ -549,14 +550,15 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
output.chisquare_by_expected_chisquare)
fitp = fit_result.x
hess = jacobian(jacobian(chisqfunc))(fitp)
try:
hess = jacobian(jacobian(chisqfunc))(fitp)
except TypeError:
raise Exception("It is required to use autograd.numpy instead of numpy within fit functions, see the documentation for details.") from None
condn = np.linalg.cond(hess)
if condn > 1e8:
warnings.warn("Hessian matrix might be ill-conditioned ({0:1.2e}), error propagation might be unreliable.".format(condn), RuntimeWarning)
try:
hess_inv = np.linalg.inv(hess)
except TypeError:
raise Exception("It is required to use autograd.numpy instead of numpy within fit functions, see the documentation for details.") from None
except np.linalg.LinAlgError:
raise Exception("Cannot invert hessian matrix.")
except Exception: