get_trials fails when loading acute data

[theilmbh]

When building the trial dataframe from acute data, everything goes well up until line 241 where consequences get assigned. The problem stems from the fact that both 'response' and 'response_time' get filled in with nans because this is an acute trial. get_consequence tries to get the response time to build the bounds for the mask, but because the response time is nan, this results in a type conversion error in pandas.

get_consequence should check if reponse_time is nan before doing anything else.

[neuromusic]

hmm. I have no problem loading the acute block at /mnt/cube/ephys-example-data/Pen01_Lft_AP100_ML1300__Site03_Z2500__B1056_cat_P01_S03_1/

[neuromusic]

wait, hold on. that was with some older code. just a sec

[neuromusic]

yep. no problems with latest

from ephys import events
block_path = '/mnt/cube/ephys-example-data/Pen01_Lft_AP100_ML1300__Site03_Z2500__B1056_cat_P01_S03_1/'
trials = events.get_trials(block_path)
print trials.head()

Output:

   recording  time_samples         stimulus  stimulus_end  response  \
0          0        125068  D_scaled_burung        331790       NaN   
1          0        440996  D_scaled_burung        647718       NaN   
2          0        780458  D_scaled_burung        987180       NaN   
3          0       1109634  H_scaled_burung       1316357       NaN   
4          0       1399201  L_scaled_burung       1605920       NaN   

   response_time  consequence  correct  
0            NaN          NaN      NaN  
1            NaN          NaN      NaN  
2            NaN          NaN      NaN  
3            NaN          NaN      NaN  
4            NaN          NaN      NaN 

[theilmbh]

I run the exact same code and get this:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-5-7c06945441e5> in <module>()
      1 from ephys import events
      2 block_path = '/mnt/cube/ephys-example-data/Pen01_Lft_AP100_ML1300__Site03_Z2500__B1056_cat_P01_S03_1/'
----> 3 trials = events.get_trials(block_path)
      4 print trials.head()

/home/btheilma/code/ephys-analysis/ephys/events.py in get_trials(block_path)
    239     trials['response'] = trials.apply(lambda row: get_response(row,digmarks,fs)['codes'],axis=1)
    240     trials['response_time'] = trials.apply(lambda row: get_response(row,digmarks,fs)['time_samples'],axis=1)
--> 241     trials['consequence'] = trials.apply(lambda row: get_consequence(row,digmarks,fs)['codes'],axis=1)
    242     trials['correct'] = trials['consequence'].apply(is_correct)
    243     return trials

/usr/local/anaconda/lib/python2.7/site-packages/pandas/core/frame.pyc in apply(self, func, axis, broadcast, raw, reduce, args, **kwds)
   3716                     if reduce is None:
   3717                         reduce = True
-> 3718                     return self._apply_standard(f, axis, reduce=reduce)
   3719             else:
   3720                 return self._apply_broadcast(f, axis)

/usr/local/anaconda/lib/python2.7/site-packages/pandas/core/frame.pyc in _apply_standard(self, func, axis, ignore_failures, reduce)
   3806             try:
   3807                 for i, v in enumerate(series_gen):
-> 3808                     results[i] = func(v)
   3809                     keys.append(v.name)
   3810             except Exception as e:

/home/btheilma/code/ephys-analysis/ephys/events.py in <lambda>(row)
    239     trials['response'] = trials.apply(lambda row: get_response(row,digmarks,fs)['codes'],axis=1)
    240     trials['response_time'] = trials.apply(lambda row: get_response(row,digmarks,fs)['time_samples'],axis=1)
--> 241     trials['consequence'] = trials.apply(lambda row: get_consequence(row,digmarks,fs)['codes'],axis=1)
    242     trials['correct'] = trials['consequence'].apply(is_correct)
    243     return trials

/home/btheilma/code/ephys-analysis/ephys/events.py in get_consequence(trial_row, digmarks, fs, window)
    179         & (digmarks['time_samples']>bds[0])
    180         & (digmarks['time_samples']<bds[1])
--> 181         & digmarks['codes'].str.contains('[FfTt]')
    182         )
    183     if digmarks[resp_mask].shape[0]>0:

/usr/local/anaconda/lib/python2.7/site-packages/pandas/core/ops.pyc in wrapper(self, other, axis)
    606         else:
    607             values = self.get_values()
--> 608             other = _index.convert_scalar(values,_values_from_object(other))
    609 
    610             if issubclass(values.dtype.type, (np.datetime64, np.timedelta64)):

pandas/index.pyx in pandas.index.convert_scalar (pandas/index.c:12052)()

pandas/index.pyx in pandas.index.convert_scalar (pandas/index.c:11937)()

ValueError: ('Cannot assign nan to integer series', u'occurred at index 0')

[neuromusic]

Are you sure you've pulled my latest changes?

& digmarks['codes'].str.contains('[FfTt]') is currently line 179, not 180 as your error says:

https://github.com/gentnerlab/ephys-analysis/blob/justin/ephys/events.py#L179

[theilmbh]

I guess I missed them. Been waiting for all of the core functionality to make it into master

[theilmbh]

Ok, that works now

[theilmbh]

And for some reason today it doesn't work.