WIP: getting suggested_init without user config overrides
Description
Just a quick idea. Normally, the suggested_init will often provide information about the default parameter settings, however this doesn't necessarily work when a user overrides these inits. This provides a way to get an init that does not necessarily depend on the user configs. Just an idea.
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perhaps allowing suggested_init() to have a keyword argument to handle flipping would work:
ignore_configignore_user_configfor_asimov
Codecov Report
Merging #1470 (87fa099) into master (70f100c) will decrease coverage by
0.06%. The diff coverage is66.66%.
@@ Coverage Diff @@
## master #1470 +/- ##
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- Coverage 97.65% 97.58% -0.07%
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Files 63 63
Lines 4006 4015 +9
Branches 565 565
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+ Hits 3912 3918 +6
- Misses 55 58 +3
Partials 39 39
| Flag | Coverage Δ | |
|---|---|---|
| contrib | 25.60% <66.66%> (+0.09%) |
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| unittests | 97.35% <66.66%> (-0.07%) |
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| Impacted Files | Coverage Δ | |
|---|---|---|
| src/pyhf/parameters/paramsets.py | 94.73% <66.66%> (-5.27%) |
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Why this is interesting: it could be used to build (pre-fit) Asimov datasets even if users provide non-default initial values for constrained parameters. It may be interesting to (optionally?) pick up non-default inits for unconstrained parameters anyway.
if with maximal_pars you mean the par value that maximizes the cconstraint pdf, i'd rather call this mode_values() perhaps