WIP: getting suggested_init without user config overrides

[kratsg]

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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[kratsg]

perhaps allowing suggested_init() to have a keyword argument to handle flipping would work:

• ignore_config
• ignore_user_config
• for_asimov

[codecov]

Codecov Report

Merging #1470 (87fa099) into master (70f100c) will decrease coverage by 0.06%.
The diff coverage is 66.66%.

@@            Coverage Diff             @@
##           master    #1470      +/-   ##
==========================================
- Coverage   97.65%   97.58%   -0.07%     
==========================================
  Files          63       63              
  Lines        4006     4015       +9     
  Branches      565      565              
==========================================
+ Hits         3912     3918       +6     
- Misses         55       58       +3     
  Partials       39       39              

Flag	Coverage Δ
contrib	25.60% <66.66%> (+0.09%)	⬆️
unittests	97.35% <66.66%> (-0.07%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
src/pyhf/parameters/paramsets.py	94.73% <66.66%> (-5.27%)	⬇️

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[alexander-held]

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.

[lukasheinrich]

if with maximal_pars you mean the par value that maximizes the cconstraint pdf, i'd rather call this mode_values() perhaps