Expand pm.Data capacities

[AlexAndorra]

This PR expands on @hottwaj's work in #3816. Now, pm.Data can:

• Be used with integers as well as floats, which allows using it for index variables:

with pm.Model() as model:
    index = pm.Data('index', np.array([2, 0, 1, 0, 2]))
    alpha = pm.Normal('alpha', 0, 1.5, shape=3)
    pm.Normal('obs', alpha[index], 1., observed=y)

• Be fed as input to other RVs, as asked in Error using pm.Data to supply mu parameter to Normal #3842:

with pm.Model():
    x = pm.Data("x", [1.0, 2.0, 3.0])
    y = pm.Normal("y", mu=x, shape=3)

This is ready for review -- thanks a lot in advance for the reviews 🖖

• No breaking changes (that I know of)
• Changes are covered by tests and docstrings
• Mentioned in the RELEASE-NOTES.md

[lucianopaz]

Great work @AlexAndorra! I left some comments throughout the changed you made. What I think is the most important point that should be addressed is the default dtype. I think that it should be theano.config.floatXfor floats and the corresponding intX dtype for ints. You can take a look at our intX function to find the mapping that we use to set the integer dtype based on theano's floatX.

[michaelosthege]

I have nothing to add - Lucianos point on intX/float is important and the rest looks good 👍

[AlexAndorra]

Thanks for the reviews @lucianopaz and @michaelosthege !
Actually, while trying to implement Luciano's suggestions, I realized, quite surprisingly, that no type setting was needed to implement the "pm.Data as index variables" feature. Even more, explicitly setting the type with floatX and intX was failing everything 😮
You can see that in the updated code and tests -- please tell me if I'm mistaken because I'm really surprised by that result. Otherwise, I think this is ready to merge 😊

[michaelosthege]

Thanks for the reviews @lucianopaz and @michaelosthege !
Actually, while trying to implement Luciano's suggestions, I realized, quite surprisingly, that no type setting was needed to implement the "pm.Data as index variables" feature. Even more, explicitly setting the type with floatX and intX was failing everything 😮
You can see that in the updated code and tests -- please tell me if I'm mistaken because I'm really surprised by that result. Otherwise, I think this is ready to merge 😊

You mean the pipeline for commit 0d07347 ?

It fails on a test that doesn't sound related:
FAILED pymc3/tests/test_model_helpers.py::TestHelperFunc::test_pandas_to_array

[AlexAndorra]

Ok, this was more complicated than I expected, but I think I understood the problem and figured out a more parcimonious implementation in the process. Tests pass locally -- if they pass on Travis too, this means it's ready for review 🍾

[lucianopaz]

Great catch @AlexAndorra!