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Run pytest on MacOs as github action

After installing liblsl and trying to run liesl I get the following error. I suspect that the LabRecorder contained here somehow depends on a specific lsl version?

ConnectionError: b'/home/moanos/software/record-neon/venv/lib/python3.11/site-packages/liesl/files/labrecorder/lib/LabRecorderCLI: error while loading shared libraries: liblsl64.so.1.13.0: cannot open shared object file: No such file or directory\n'

A very dirty workaround is to do

sudo cp /usr/lib/liblsl.so /usr/lib/liblsl64.so.1.13.0

This can mess up your system, do not try unless you exacly know what you are doing

I tested on Ubuntu via provided deb file and arch via the AUR package.

For any stream with only one channel, liesl fails loading this stream.
Calling streams = XDFFile(xdffile) with a file that has such a stream in it fails at the function

def channel_labels(self) -> Union[List[str], None]:
        "get the channel labels as a list of strings"
        if self.desc is not None:
            return [i["label"] for i in self.desc["channels"]["channel"]]
        else:
            return None

when e.g.
self.desc["channels"]["channel"] = {'label': 'Force', 'unit': 'N', 'type': 'vernier'}
A working stream has the format
[{'label': 'Fp1', 'type': 'EEG', 'unit': 'microvolts'}, {'label': 'Fp2', 'type': 'EEG', 'unit': 'microvolts'}]

Solution could be

def channel_labels(self) -> Union[List[str], None]:
        "get the channel labels as a list of strings"
        if self.desc is not None:
            try:
                return [i["label"] for i in self.desc["channels"]["channel"]]
            except TypeError:
                return [self.desc["channels"]["channel"]['label']]
        else:
            return None

Wir nutzen den cli_wrapper schon seit einiger Zeit sehr erfolgreich in diversen Studien. Dabei nutzen wir einen raspberry pi zum aufzeichnen unterschiedlicher LSL-Streams (meist ein Marker, ein Audio und ein EEG stream parallel) unter Linux. [...] Heute wollte ich einen Marker-, und zwei EEG-LSL-Streams gleichzeitig aufzeichnen um einen Verstärkervergleich durchzuführen. Obwohl die EEG-Streams unterschiedliche Namen besitzen erhalte ich folgende Fehlermeldung: "Some streams were selected multible times". Ist dies ein Bug? Wenn ich die Streams manuell initialisiere und dabei den Typ der Streams in EEG1 und EEG2 ändere erscheint dieser Fehler nicht. Wir würden dennoch gern die Möglichkeit besitzen, mit unserer Aufnahme-Box auch auch EEG-LSL-Streams aufnehme zu können, die mit der Smarting-Streemer-Software erstellt wurden. Diese ermöglicht es leider nur die Namen der Streams zu definieren. Der Typ ist dann immer "EEG".

I tried to install liesl on my Ubuntu 19.10 With Intel Intel® Core™ i7-3610QM CPU (64 bit)

$ pip install liesl
Collecting liesl
  Using cached https://files.pythonhosted.org/packages/16/a9/57ad1dc14b75caccffdf0cae77f9780c961a05f9c3f5e71a1548e81670f5/liesl-0.3.4.3.tar.gz
    Complete output from command python setup.py egg_info:
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "/tmp/pip-install-OwKjpQ/liesl/setup.py", line 4, in <module>
        with (Path(__file__).parent / "readme.md").open() as f:
      File "/home/juli/.local/lib/python2.7/site-packages/pathlib.py", line 1077, in open
        return io.open(str(self), mode, buffering, encoding, errors, newline)
    IOError: [Errno 2] No such file or directory: '/tmp/pip-install-OwKjpQ/liesl/readme.md'
    
    ----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-install-OwKjpQ/liesl/

I installed the labrecorder on MacOS and did the following:

import liesl

recorder = liesl.Recorder(
    path_to_cmd='/usr/local/opt/labrecorder/LabRecorder/LabRecorder.app/Contents/MacOS/LabRecorder')

but I get the following:

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
~/Documents/github_repos/neurobooth-os/examples/record_using_lisel.py in <module>
     41 subject = "demo_subject"
     42 
---> 43 recorder = liesl.Recorder(
     44     '/usr/local/opt/labrecorder/LabRecorder/LabRecorder.app/Contents/MacOS/LabRecorder')
     45 session = liesl.Session(prefix=subject,

~/anaconda3/envs/neurobooth/lib/python3.8/site-packages/liesl/files/labrecorder/cli_wrapper.py in __init__(self, path_to_cmd)
     77     def __init__(self, path_to_cmd: str = None) -> None:
     78         self.streamargs = None
---> 79         self.cmd = find_lrcmd(path_to_cmd)
     80 
     81     def bind(self, streamargs: List[dict,] = [None]) -> None:

~/anaconda3/envs/neurobooth/lib/python3.8/site-packages/liesl/files/labrecorder/cli_wrapper.py in find_lrcmd(path_to_cmd)
     48 
     49     # if nothing worked, we end here
---> 50     raise FileNotFoundError("No valid path to LabRecorder")
     51 
     52 

FileNotFoundError: No valid path to LabRecorder

It looks like the path_to_cmd is ignored for MacOS. Is there a possibility to support this option? Thank you!

The gaze type of stream is defined in the spec and used e.g. by pupil labs.

When only a single stream is recorded, everything works fine. When two streams are selected for recording, they are recorded into the xdf twice.

Induce

Prepare two mock streams with

liesl mock

liesl mock --type Marker

start a python session and run

from liesl.api import Recorder
import time
r = Recorder
r.bind([{"type":"EEG"},{"type":"Marker"}])
r.start_recording()
time.sleep(3)
r.stop_recording()

inspect the file from the terminal with

liesl xdf recording_R001.xdf

returns on Win10 with Python 3,.9.1:

Loading recording_R001.xdf concisely

Name                             Type        Ch   Fs                      Source
--------------------------------------------------------------------------------
Liesl-Mock-EEG                   EEG         8   1000.0               84932102909
Liesl-Mock-Marker               Marker       1    0.0               118257554116

but on Linux Mint with Python 3.7.6

Loading recording_R001.xdf concisely

Name                             Type        Ch   Fs                      Source
--------------------------------------------------------------------------------
Liesl-Mock-Marker               Marker       1   0.000000000000000             8744283295937
Liesl-Mock-Marker               Marker       1   0.000000000000000             8744283295937
Liesl-Mock-EEG                   EEG         8   1000.000000000000             8729561856449
Liesl-Mock-EEG                   EEG         8   1000.000000000000             8729561856449

During loading, pyxdf.load_xdf automatically tries to dejitter the timestamps. This requires a linear regression on the measured timestamps. This step apparently failed.
Error message:
Error reading chunk length
Traceback (most recent call last):
File "/home/tianlu/anaconda3/lib/python3.8/site-packages/pyxdf/pyxdf.py", line 237, in load_xdf
chunklen = _read_varlen_int(f)
File "/home/tianlu/anaconda3/lib/python3.8/site-packages/pyxdf/pyxdf.py", line 487, in _read_varlen_int
raise RuntimeError("invalid variable-length integer encountered.")
RuntimeError: invalid variable-length integer encountered.
got zero-length chunk, scanning forward to next boundary chunk.

Intel MKL ERROR: Parameter 6 was incorrect on entry to DGELSD.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/tianlu/anaconda3/lib/python3.8/site-packages/liesl/files/xdf/load.py", line 147, in XDFFile
streams, _ = pyxdf.load_xdf(filename=str(filename))
File "/home/tianlu/anaconda3/lib/python3.8/site-packages/pyxdf/pyxdf.py", line 377, in load_xdf
temp = _jitter_removal(
File "/home/tianlu/anaconda3/lib/python3.8/site-packages/pyxdf/pyxdf.py", line 661, in _jitter_removal
mapping = np.linalg.lstsq(X, y, rcond=-1)[0]
File "<**array_function** internals>", line 5, in lstsq
File "/home/tianlu/anaconda3/lib/python3.8/site-packages/numpy/linalg/linalg.py", line 2306, in lstsq
x, resids, rank, s = gufunc(a, b, rcond, signature=signature, extobj=extobj)
File "/home/tianlu/anaconda3/lib/python3.8/site-packages/numpy/linalg/linalg.py", line 100, in _raise_linalgerror_lstsq
raise LinAlgError("SVD did not converge in Linear Least Squares")
numpy.linalg.LinAlgError: SVD did not converge in Linear Least Squares

Loading the file with pyxdf.load_xdf(filename=str(filename), dejitter_timestamps=False) works.

Thanks Robert! 😄