[Mne_analysis] question about epochs.next()

[Dan McCloy]

I see. Sounds like that would work, I'll give it a try. thanks.

FWIW, from the POV of a new mne-python user, the examples quite prominently
use "evoked" to mean "average of epochs" (e.g.,
http://martinos.org/mne/dev/auto_tutorials/plot_introduction.html?highlight=evoked).
I probably missed the Epochs.iter_evoked method() on the basis of its name
(because I didn't want averages, and it wasn't immediately obvious that
"nave=1" meant "n_epochs_to_average=1", i.e., no averaging).

So now I'm doubly-puzzled: why does Epochs.next() not return a single
epoch, and why does Epochs.iter_evoked() not return an average of epochs?
I understand the need to preserve some backwards-compatibility, but the
naming conventions here seem very ad-hoc to me and worth changing prior to
a 1.0 release.  Until then, I guess I'll just change the docstrings to
match what these methods actually do.
On Apr 5, 2016 5:11 PM, "Mainak Jas" <mainakjas at gmail.com> wrote:

> Sorry if I wasn't clear but iter_evoked() gives you a single epoch -- not
> an average. It has nave=1.
>
> Mainak
>
> On Wed, Apr 6, 2016 at 1:45 AM, Dan McCloy <drmccloy at uw.edu> wrote:
>
>> thanks Mainak, but my use case is a little strange, and I don't think
>> iter_evoked will help.  I need potentially different crop windows for each
>> event type (same length, but different start/end points), but I need to
>> keep the individual epochs (not averages) because they're getting fed into
>> a classifier.  I'm happy to do a PR to change the docs if the consensus is
>> that it is indeed the docs that should change, not the implementation of
>> next().
>>
>> On Tue, Apr 5, 2016 at 4:27 PM, Mainak Jas <mainakjas at gmail.com> wrote:
>>
>>> Hi Dan,
>>>
>>> Since you are iterating over single epochs, it might make more sense to
>>> use the iterator which returns an evoked object. You can do something like:
>>>
>>> for ev in epochs.iter_evoked()
>>>     ev.crop(tmin, tmax)
>>>
>>> Does this help? Fix to the docs is more than welcome.
>>>
>>> Best regards,
>>> Mainak
>>>
>>>
>>> On Tue, Apr 5, 2016 at 10:05 PM, Dan McCloy <drmccloy at uw.edu> wrote:
>>>
>>>> On Tue, Apr 5, 2016 at 12:19 PM, Chris Holdgraf <choldgraf at berkeley.edu
>>>> > wrote:
>>>>
>>>>> sometimes it's more useful to return arrays.
>>>>>
>>>>
>>>> Sure, but that's why there is a get_data method, right?  IMO the
>>>> docstring reflects how I expected it to work before even reading the
>>>> docstring, so my vote would be to make .next() actually do that, rather
>>>> than changing the docstring to reflect what it does currently.  Issue
>>>> created: https://github.com/mne-tools/mne-python/issues/3099
>>>>
>>>>
>>>>> On Tue, Apr 5, 2016 at 12:03 PM, Dan McCloy <drmccloy at uw.edu> wrote:
>>>>>
>>>>>> I was puzzled today why this works...
>>>>>>
>>>>>> for ix, _ in enumerate(epochs):
>>>>>>     new_epoch = epochs[ix].crop(tmin, tmax, copy=True)
>>>>>>
>>>>>> ... but this does not:
>>>>>>
>>>>>> for epoch in epochs:
>>>>>>     new_epoch = epoch.crop(..., copy=True)
>>>>>>
>>>>>> AttributeError: 'numpy.ndarray' object has no attribute 'crop'
>>>>>>
>>>>>> According to the docs, Epochs.next() is supposed to return an
>>>>>> instance of the epochs object, but it doesn't: looking at the code, it
>>>>>> actually returns something like self._data[self._current].  I would have
>>>>>> expected it to return something like self.__get_item__(self._current).  So
>>>>>> are the docs wrong, or is the definition of Epochs.next() implemented wrong?
>>>>>>
>>>>>> Daniel McCloy
>>>>>> http://dan.mccloy.info/
>>>>>> Postdoctoral Research Associate
>>>>>> Institute for Learning and Brain Sciences
>>>>>> University of Washington
>>>>>>
>>>>>>
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>>>>>
>>>>>
>>>>> --
>>>>> _____________________________________
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>>>>> PhD Candidate in Neuroscience | UC Berkeley <http://hwni.org/>
>>>>> Editor and Web Director | Berkeley Science Review
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