Giordon Stark

The solution is probably to have type-checking to only specify the bounds as tuples I think (from the python code) but then also convert the bounds loaded from the JSON...

One could consider [`marshmallow`](https://marshmallow.readthedocs.io/en/stable/) as well. ``` SR1 = pyhf.orm.Channel('signal_region') ttbar = pyhf.orm.Sample('ttbar') wjets = pyhf.orm.Sample('wjets') SR1.add_sample(ttbar) SR1.add_sample(wjets) # SR1.add_samples([ttbar, wjets]) ``` the tricky part of the API is that...

> APIs is (known to be) not consistent across the asymptotic and toy based as asymptotic is returning p-values well, it's consistent here, it's that the `calc.teststatistic(test_poi)` has a different...

> My main complaint at the moment is that while we make it clear that the asymptotic test stats are in `-^mu/sigma` space this part I think is what confuses...

> Hi @mdhank - the prior behavoir is correct and we know where the bug is, just requires implementing a fix. I'll update here once we have one The issue...

The measurement definition is what uniquely identifies that model fyi -- a workspace is unique (and has a hash) via `pyhf digest` and the combination of the channel specification +...

> two models are "equal" if they provide the same `expected_data` for the same input parameters. this isn't true because a measurement can contain overrides, different values for lumi, different...

@alexander-held i'm trying to figure out what you actually expect to come out of that function. ```python >>> model.config.param_set(parameter).suggested_fixed [True, False] ``` is giving you what I would expect. `suggested_fixed_as_bool()->bool`...

Closing this as "won't fix".

`gsed` on my mac is POSIX `sed` (should be identical behavior). That is actually already split up. Can't really go with shorter bits. The first one is a single regex...