make activation consistent

[Trybnetic]

activation was not forced to take the correct weight dimensions.

This PR fixes this and makes the dimensions of weights consistent in pyndl

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 00cba28 on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 00cba28 on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 00cba28 on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 17a2267 on activation-checks into 4f43ded on master.

[Trybnetic]

Besides randomly throwing errors, pylint always stops at some point without raising an error or something like that..

@derNarr @dekuenstle have you any idea why this happens?

[Trybnetic]

Seems like the random errors came from not giving fixed dimensions.

dim=('outcomes', 'cues') should have fixed it.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling aa613db on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling aa613db on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling aa613db on activation-checks into 4f43ded on master.

[dekuenstle]

pyndl.ndl.ndl has also order 'cues','outcomes'. We have to keep this consistent. Why did you change the order?

[Trybnetic]

pyndl.ndl.ndl returns dimensions ('outcomes', 'cues'), so now activation is consistent with this.

But the doc string in ndl.py

"""
    Returns
    -------
    weights : xarray.DataArray
        with dimensions 'cues' and 'outcomes'. You can lookup the weights
        between a cue and an outcome with ``weights.loc[{'outcomes': outcome,
        'cues': cue}]`` or ``weights.loc[outcome].loc[cue]``.
"""

should be

"""
    Returns
    -------
    weights : xarray.DataArray
        with dimensions 'outcomes' and 'cues'. You can lookup the weights
        between a cue and an outcome with ``weights.loc[{'outcomes': outcome,
        'cues': cue}]`` or ``weights.loc[outcome].loc[cue]``.
"""

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 5684428 on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 5684428 on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 46923b8 on activation-checks into 4f43ded on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 47862f5 on activation-checks into 97efb77 on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 47862f5 on activation-checks into 97efb77 on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 47862f5 on activation-checks into 97efb77 on master.

[dekuenstle]

@Trybnetic i added also some changes, so please check them before merging.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 98f0301 on activation-checks into 97efb77 on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 98f0301 on activation-checks into 97efb77 on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling 98f0301 on activation-checks into 97efb77 on master.

[Trybnetic]

@dekuenstle I have discussed it with @derNarr. He also argues to use outcomes as the first dimension of the activation matrix.

I just did two small changes in the tests so we now use directly the matrix with the right dimensions instead of transposing the old ones

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling acd6b93 on activation-checks into 97efb77 on master.

[coveralls]

Coverage increased (+0.3%) to 59.341% when pulling acd6b93 on activation-checks into 97efb77 on master.

[Trybnetic]

Before merging we should check that the examples are still working! Due to the major changes in this PR I expect that they will not work anymore

[Trybnetic]

@derNarr @dekuenstle @sumny I could not find an example of activation in the docs, is this right? As activation is a quite useful function we should consider adding an example if there isn't one yet. But I'm not sure whether we should do this in this PR or in an extra one in which we enhance the docs in general.

What do you think?

[dekuenstle]

@Trybnetic Better an extra issure + PR for extending docs with activation estimation.

[Trybnetic]

@dekuenstle I agree with you. I've made todo note in #5 as this issue is mostly about documentation and examples.