mne-python: EDF read in not working in certain files, read in slow

edf_test_edited.zip edf_test.zip

The attached EDF file “edf_test.edf” can be opened via pyedflib:

Python 3.6.6 |Anaconda custom (64-bit)| (default, Jun 28 2018, 11:07:29) 
Type 'copyright', 'credits' or 'license' for more information
IPython 6.4.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import pyedflib

In [2]: f = pyedflib.EdfReader("edf_test.edf")

In [3]: f.readSignal(chn=0)
Out[3]: 
array([-18000.        , -18000.        , -18000.        , ...,
         4210.98649577,   4210.98649577,   4210.98649577])

File cannot be opened with mne:

In [1]: import mne

In [2]: mne.io.read_raw_edf("edf_test.edf", preload = True)
Extracting EDF parameters from edf_test.edf...
EDF file detected
Setting channel info structure...
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-2-8bfb048068a5> in <module>()
----> 1 mne.io.read_raw_edf("edf_test.edf", preload = True)

~/anaconda3/lib/python3.6/site-packages/mne/io/edf/edf.py in read_raw_edf(input_fname, montage, eog, misc, stim_channel, annot, annotmap, exclude, preload, verbose)
   1237     return RawEDF(input_fname=input_fname, montage=montage, eog=eog, misc=misc,
   1238                   stim_channel=stim_channel, annot=annot, annotmap=annotmap,
-> 1239                   exclude=exclude, preload=preload, verbose=verbose)

~/anaconda3/lib/python3.6/site-packages/mne/io/edf/edf.py in __init__(self, input_fname, montage, eog, misc, stim_channel, annot, annotmap, exclude, preload, verbose)

~/anaconda3/lib/python3.6/site-packages/mne/utils.py in verbose(function, *args, **kwargs)
    727         with use_log_level(verbose_level):
    728             return function(*args, **kwargs)
--> 729     return function(*args, **kwargs)
    730 
    731 

~/anaconda3/lib/python3.6/site-packages/mne/io/edf/edf.py in __init__(self, input_fname, montage, eog, misc, stim_channel, annot, annotmap, exclude, preload, verbose)
    156         input_fname = os.path.abspath(input_fname)
    157         info, edf_info = _get_info(input_fname, stim_channel, annot,
--> 158                                    annotmap, eog, misc, exclude, preload)
    159         logger.info('Creating raw.info structure...')
    160         _check_update_montage(info, montage)

~/anaconda3/lib/python3.6/site-packages/mne/io/edf/edf.py in _get_info(fname, stim_channel, annot, annotmap, eog, misc, exclude, preload)
    509         data_samps = np.delete(n_samps, slice(stim_channel, stim_channel + 1))
    510     sfreq = data_samps.max() * \
--> 511         edf_info['record_length'][1] / edf_info['record_length'][0]
    512 
    513     info = _empty_info(sfreq)

~/anaconda3/lib/python3.6/site-packages/numpy/core/_methods.py in _amax(a, axis, out, keepdims)
     24 # small reductions
     25 def _amax(a, axis=None, out=None, keepdims=False):
---> 26     return umr_maximum(a, axis, None, out, keepdims)
     27 
     28 def _amin(a, axis=None, out=None, keepdims=False):

ValueError: zero-size array to reduction operation maximum which has no identity

With nme, adding stim_chan = None solves the problem:

In [3]: mne.io.read_raw_edf("edf_test.edf", preload = True, stim_channel=None)
Extracting EDF parameters from edf_test.edf...
EDF file detected
Setting channel info structure...
Creating raw.info structure...In [1]: import mne

In [2]: mne.io.read_raw_edf("edf_test_edited.edf", preload=True)
Extracting EDF parameters from edf_test_edited.edf...
EDF file detected
EDF annotations detected (consider using raw.find_edf_events() to extract them)
Setting channel info structure...
Creating raw.info structure...
Reading 0 ... 1843199  =      0.000 ...  3599.998 secs...
Out[2]: <RawEDF  |  edf_test_edited.edf, n_channels x n_times : 2 x 1843200 (3600.0 sec), ~28.1 MB, data loaded>

Reading 0 ... 1843199  =      0.000 ...  3599.998 secs...
Out[3]: <RawEDF  |  edf_test.edf, n_channels x n_times : 1 x 1843200 (3600.0 sec), ~14.1 MB, data loaded>

The same EDF file with annotations (edf_test_edited.edf):

In [3]: mne.io.read_raw_edf("edf_test_edited.edf", preload = True)
Extracting EDF parameters from edf_test_edited.edf...
EDF file detected
EDF annotations detected (consider using raw.find_edf_events() to extract them)
Setting channel info structure...
Creating raw.info structure...
Reading 0 ... 1843199  =      0.000 ...  3599.998 secs...
Out[3]: <RawEDF  |  edf_test_edited.edf, n_channels x n_times : 2 x 1843200 (3600.0 sec), ~28.1 MB, data loaded>

Note that the EDF files only contain 1 channel, but <RawEDF | edf_test_edited.edf, n_channels x n_times : 2 x 1843200 (3600.0 sec), ~28.1 MB, data loaded> states n_channels = 2.

Additionaly, EDF readin is really slow with stim_chan = None:

Timing for read in of annotated file without stim_channel=None is really slow:

%timeit mne.io.read_raw_edf("edf_test_edited.edf", preload=True)
Extracting EDF parameters from edf_test_edited.edf...
EDF file detected
EDF annotations detected (consider using raw.find_edf_events() to extract them)
Setting channel info structure...
Creating raw.info structure...
Reading 0 ... 1843199  =      0.000 ...  3599.998 secs..
4.59 s ± 12.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

compared to read in with stim_chan=None:

%timeit mne.io.read_raw_edf("edf_test_edited.edf", preload=True, stim_channel=None)
Extracting EDF parameters from edf_test_edited.edf...
EDF file detected
EDF annotations detected (consider using raw.find_edf_events() to extract them)
Setting channel info structure...
Creating raw.info structure...
<magic-timeit>:1: RuntimeWarning: 1 channel names are too long, have been truncated to 15 characters:
['EDF Annotations-1']
1 channel names are too long, have been truncated to 15 characters:
['EDF Annotations-1']
Reading 0 ... 1843199  =      0.000 ...  3599.998 secs...
59.2 ms ± 962 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

Can these issues be solved?