Skip to content

fit: Expose cores option of bootstrap_analysis #387

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
luisfabib merged 2 commits into from
Oct 25, 2022
Merged

fit: Expose cores option of bootstrap_analysis #387

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
f1c39a2
fit: expose cores option of bootstrap_analysis
Oct 24, 2022
f94cdcc
Merge branch 'main' into fix/fit_bootcores
luisfabib Oct 25, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 6 additions & 2 deletions deerlab/model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1018,7 +1018,7 @@ def decorator(func):
#==============================================================================================
@insert_snlls_optionals_docstrings()
def fit(model_, y, *constants, par0=None, penalties=None, bootstrap=0, noiselvl=None, mask=None, weights=None,
regparam='aic',reg='auto',regparamrange=None,**kwargs):
regparam='aic',reg='auto',regparamrange=None, bootcores=1,**kwargs):
r"""
Fit the model(s) to the dataset(s)

Expand Down Expand Up @@ -1051,6 +1051,10 @@ def fit(model_, y, *constants, par0=None, penalties=None, bootstrap=0, noiselvl=
bootstrap : scalar, optional,
Bootstrap samples for uncertainty quantification. If ``bootstrap>0``, the uncertainty quantification will be
performed via the boostrapping method with based on the number of samples specified as the argument.

bootcores : scalar, optional
Number of CPU cores/processes for parallelization of the bootstrap uncertainty quantification. If ``cores=1`` no parallel
computing is used. If ``cores=-1`` all available CPUs are used. The default is one core (no parallelization).

reg : boolean or string, optional
Determines the use of regularization on the solution of the linear problem.
Expand Down Expand Up @@ -1264,7 +1268,7 @@ def bootstrap_fcn(ysim):
if not isinstance(fit.model,list): fit.model = [fit.model]
return (fit.param,*fit.model)
# Bootstrapped uncertainty quantification
param_uq = bootstrap_analysis(bootstrap_fcn,ysplit,fitresults.model,samples=bootstrap,noiselvl=noiselvl)
param_uq = bootstrap_analysis(bootstrap_fcn,ysplit,fitresults.model,samples=bootstrap,noiselvl=noiselvl,cores=bootcores)
# Include information on the boundaries for better uncertainty estimates
paramlb = model._vecsort(model._getvector('lb'))[np.concatenate(param_idx)]
paramub = model._vecsort(model._getvector('ub'))[np.concatenate(param_idx)]
Expand Down