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feat: Add Cramer-rao uncertainties + covariance using autodiff to non-minuit fits by default #2269

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feat: Add Cramer-rao uncertainties + covariance using autodiff to non-minuit fits by default #2269

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a3abc9a
add autodiff machinery to jax and pytorch backends
phinate Aug 9, 2023
eee1b3f
run linting
phinate Aug 9, 2023
123f2a0
fix torch by casting res to tensor
phinate Aug 9, 2023
d95c433
add tensorflow
phinate Aug 9, 2023
9b99a5f
stitch in fixed pars before calculating uncerts
phinate Aug 11, 2023
e6281ee
patch in fisher_cov as identity for tests
phinate Aug 11, 2023
11f0a0f
lint
phinate Aug 14, 2023
d7f3e9d
add correlation calculations, and correctly zero out covariance and c…
phinate Aug 14, 2023
474bd1a
fix docstrings
phinate Aug 14, 2023
ee56ec6
adjust to ignore zeroing out corr/cov for minuit, since it already ha…
phinate Aug 14, 2023
5537ad9
quickly patch in skipping minuit for autodiff tests (silently passing)
phinate Aug 14, 2023
b1c9b3d
ignore venv in gitignore
phinate Oct 20, 2023
3a22760
add poi_name='mu'
phinate Oct 20, 2023
8f286ba
document setting things to zero, and add pointers to the minuit issue…
phinate Oct 20, 2023
d3142fc
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Oct 20, 2023
5d3d3d6
Merge branch 'main' into autodiff-uncerts
phinate Apr 23, 2024
b24b591
Merge branch 'main' into autodiff-uncerts
phinate Sep 24, 2024
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[pre-commit.ci] auto fixes from pre-commit.com hooks 
for more information, see https://pre-commit.ci
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pre-commit-ci[bot] committed Oct 20, 2023
commit d3142fc71f3266e7a2318765ec34bd27868b2bfc
2 changes: 1 addition & 1 deletion src/pyhf/optimize/mixins.py
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Expand Up @@ -131,7 +131,7 @@ def _internal_postprocess(

# we also need to edit the covariance matrix to zero-out uncertainties!
# NOTE: minuit already does this (https://github.com/scikit-hep/iminuit/issues/762#issuecomment-1207436406)
if fixed_vals is not None and not using_minuit:
if fixed_vals is not None and not using_minuit:
fixed_bools = [False] * len(init_pars)
# Convert fixed_bools to a numpy array and reshape to make it a column vector
fixed_mask = tensorlib.reshape(
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