[pymvpa] modifying time_attr and onset when running fit_event_hrf_model with a dataset truncated at the beginning

[Ben Smith]

Hi all,

I have a dataset with TR=2 where I want to delete the first 10 TRs (first
20 seconds) before running fit_event_hrf_model.

Deleting the first TRs is easy:

ds = ds[10:]

However I am unsure what to do with time coordinates. I understand that if
I adjust the onsets in the event list then I will also need to adjust the
time_attr in the dataset, like:

TR=2
for e in event_list:
    e['onset'] = e['onset']-10*TR
ds = ds.sa.time_coords - 10 * TR
result= fit_event_hrf_model(ds, event_list, time_attr='time_coords',

 condition_attr=('targets', 'chunks'))

My intuition is that it shouldn't matter whether you adjust event onset and
ds time coordinates as long as you adjust both or neither - so that they
stay correctly aligned.

But when I run this and test, then I do get slightly different estimates
depending solely on whether I adjust the both time coordinates and event
onsets, or neither (keeping constant the removal of 10 trs).

Mainly I am wanting to know whether or not I should adjust the time
coordinates, but I would be interested to hear from anyone who knows why
estimates actually differ.

Ben
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