BUG: Reading EDF files can be very slow

I am trying to read an EDF file, but the .read_data() (edit, i mean load_data()) function fails. Same thing happens with this sample file from here

Looking a bit into the code I find that there is a call to _read_segment_file in io\base.py which raises an NotImplementedError. The Problem seems to be the call itself, it doesn’t even get to the called functions inside. If I comment the call out, it works fine.

self._read_segment_file(data[:, this_sl], idx, fi,
                                    int(start_file), int(stop_file),
                                    cals, mult)

Strangely enough running the sample file from the EDF-API works without problems

I hope I provided all the info needed. Unfortunately I’m not very experienced in debugging functions or classes. Thanks!

Platform:      Windows-10-10.0.14393-SP0
Python:        3.5.2 (same in 2.7.x) (v3.5.2:4def2a2901a5, Jun 25 2016, 22:18:55) [MSC v.1900 64 bit (AMD64)]
Executable:    C:\Program Files\WinPython-3.5\python-3.5.2.amd64\pythonw.exe

mne:           0.14.dev0
numpy:         1.11.2 {lapack=C:/Program Files (x86)/IntelSWTools/compilers_and_libraries/windows/mkl/include, blas=C:/Program Files (x86)/IntelSWTools/compilers_and_libraries/windows/mkl/include}
scipy:         0.18.1
matplotlib:    1.5.3

sklearn:       0.18
nibabel:       Not found
nitime:        Not found
mayavi:        Not found
nose:          1.3.7
pandas:        0.19.1
pycuda:        Not found
skcuda:        Not found

[larsoner]

It probably has to do with inefficiencies in how we loop. Different channel/sample configurations will expose those weaknesses differently. Or your other file could require different processing, e.g. resampling if not all channels have the same sample rate, which can be slow.

[larsoner]

I’m having SDD I/O of ~150MB/s for 15 seconds although the file is only 25MB large.

Yikes. That doesn’t seem right. Which file are you testing with?

Perhaps there is some optimization we can do. I’ll re-title the issue.