Julia interface improvements

[roualdes]

Here's a list of Julia interface items I'd like to tackle one day.

• adopt more idiomatic package name spelling, BridgeStan instead of Bridgestan
• export K means nothing since K is never defined
• its common Julia practice to use f! when there's an out argument; add log_density, log_density_gradient (no exclamation points) which assign to new memory (instead of using an out argument)
• can drop the ::Vector{Float64} in most use cases of zeros(D); Float64 by default
• not all defined functions are exported
• double check tests for completeness

[WardBrian]

I definitely copied the export list without doing anything to it, my bad!

Re:out parameters, I believe the functions are currently implemented as you describe (new memory each time) so we should add the ! versions

for tests we should probably just recreate the Python tests in all 3 languages eventually, those are the most complete

[roualdes]

No blame here.

Yep, I see that now. You're right. We should the ! versions.

Agreed on the tests.

[WardBrian]

Would you like me to take a crack at some of these, or would you prefer to do it?

[roualdes]

Yes, please do. I phrased to to do list in the first person so as not to tell anybody what to do. I'd appreciate you giving it a go. Thanks.

[roualdes]

@WardBrian, what do you think about adding

export BS
const BS = BridgeStan

to the BridgeStan module and dropping all other exports? The effect would be

using BridgeStan

then enables BS.log_density() and BS.log_density_gradient(), ... .

This is what they do in AbstractDifferentiation.jl.

It's like a Julia version of Python's import bridgestan as bs.

To me the pithiness is nice, but I could see it also being not obvious.

[WardBrian]

A user could still do “const BS = BridgeStan” on their own, right?

[roualdes]

That's fair. It is probably better just to remind users that const BS = BridgeStan is possible, in say the example.jl, rather than force it on them.