Issue initializing Muse2 on MacOs
pjkohler opened this issue · 21 comments
ℹ Computer information
- Platform OS (e.g Windows, Mac, Linux etc): macOS 10.15
- Python Version: 3.7
- Brain Interface Used (e.g Muse, OpenBCI, Notion etc): Muse with BLED112 dongle
📝 Provide detailed reproduction steps (if any)
- Install eeg-notebooks following the instructions here: https://neurotechx.github.io/eeg-notebooks/getting_started/installation.html
- Attempt to open EEG stream, using this code (adapted from this):
import os
import sys
sys.path.insert(1, '/Users/kohler/code/git/eeg-notebooks')
from eegnb import generate_save_fn
from eegnb.devices.eeg import EEG
from eegnb.experiments.visual_n170 import n170
eeg_device = EEG(device=board_name)
board_name = "muse2"
experiment = "visual_n170"
subject_id = 0
session_nb = 0
record_duration = 120
eeg_device = EEG(device=board_name)
✔️ Expected result
EEG device initialization
❌ Actual result
muse_get_recent throws an error, message "Couldn't find any stream, is your device connected?"
Note, connecting directly with muselsl like this:
from muselsl import stream, view, list_muses
muses = list_muses()
stream(muses[0]['address'])
works fine.
📷 Screenshots
Okay, so I think I have to start the stream in a separate terminal window before running the notebook. When I do that, I get a different error. I get the same error whether I use "muse" or "muse2" as the device.
Hi @pjkohler - Do you mind giving this a shot again? We have made recent changes that should attempt to fix this
of course! how do I update?
thanks! here are some steps to try
- pulling the latest changes -
git pull origin master - (optional) reinstalling dependencies in your environment for the project -
pip install -e . - try running the sample here https://neurotechx.github.io/eeg-notebooks/getting_started/installation.html#installing-the-python-library
lmk if you have any questions
ignore previous comment (that I deleted), I realize now I also have to start the stream in uvicMuse, before running eeg-notebooks.
okay, now I am able to start the experiment, but then I get the following error after pressing spacebar. Note that I have connected and started streaming using uvicMuse prior to running the eeg-notebooks code.
I was able to get around that error by adding
import nest_asyncio nest_asyncio.apply()
above. Now I get this error:
The muse is connected and streaming, I can data from it using LabRecorder software.
Hi Peter.
Have you tried the brainflow option?
Device name for native Bluetooth with brainflow is 'muse2_bfn'.
Relevant info re: OS compatibility etc here
https://brainflow.readthedocs.io/en/stable/SupportedBoards.html#muse
I haven't. Brainflow would be used to initialize the stream, right?
ah, I misunderstood ... maybe I misunderstood the whole approach you take here. There is no need to initialize the stream ahead of time, is there? I can simply pass "muse2_bfn" as the device name, and then your code will take of the rest, right? It appears so. I was able to get some data, and will continue to debug.
okay, this is pretty awesome. Thanks @JohnGriffiths, @oreHGA, everyone. I will use this in my class on Tuesday, and a lot more in future courses!
Also, for some reason, not sure why, I do not have to run import nest_asyncio nest_asyncio.apply() to get this to work anymore.
Great to hear this is working well for you Peter!
You misunderstanding is very understandable: we are using brainflow differently to how muselsl and BlueMuse are have been used in eeg-notebooks previously, namely the stream is initiated within EEG device object initialization, without the need of the user to initiate any separate third-party streaming processes, through Python or otherwise.
BrainFlow is a relatively new library that does a great job of handling data streams across a wide variety of devices. They added muse support just after Xmas, and so we are gradually moving over to that ( mainly `_bfn' ) as the default / recommended streaming option, whilst continuing to keep the others available.
You should also check out the CLI if you haven't yet: type
eegnb runexp -ip
and follow the options.
Finally, since you mentioned your class, here is a minimal eeg-notebooks script we are using in a current experiment, that may be handy as a refernce
https://github.com/GriffithsLab/muse-aob-tms/blob/main/code/run_aob_task.py
If you configure the 'run with' option in windows/mac to the correct python environment binary, then this can run a complete experiment - including stream initiation and data saving - with a simple double-click of a desktop icon. In windows I found this works better if I create a separate shortcut that points to the run_aob_task.py file. Not sure whether that would be helpful on Mac.
holy smokes, John. I have the N170 experiment working, and that may just have to do for now, since we are coming down to the wire. But I plan to teach this course for many years (Neuroscience Techniques - a sampler of different neuroscience methodologies) so will explore more in the future.
Another little snippet that might be useful
This is a quick way to grab data with the device class without having to run a psychopy experiment or to save data to file
from eegnb.devices.eeg import EEG
myeeg = EEG(device='muse2_bfb') # automatically initiates a brainflow connection
dat = myeeg.get_recent() # returns a time x channel pandas dataframe
dat.plot() # pandas matplotlib methodUnfortunately we don't have a livestreaming figure like you get with muselsl view -v 2 yet, but we will add one at some point (unless the brainflow guys beat us to it)
In the mean time there is a simple signal quality check
Command lne:
eegnb checksigqual -ed muse2_bfn
Python:
from eegnb.analysis.utils import check_report
check_report(myeeg)That prints out standard deviations on the command line every 5 secs (like the numbers on the axes in the muselsl view plots ); also a bit like the actual muse app.
okay, so I have eeg-notebooks running on my primary computer, which is running Mac OSX 10.15. One thing I am still confused about is the BLED dongle - so I do not need that at all?
In parallel, I am struggling with getting eeg-notebooks to run on my secondary computer which has Mac OSX 10.13 - I can share my specific hassles, but any general tips?
okay, upgrading to Catalina did not help. This is a MacBook Pro from 2013. Fresh conda environment.
Here are the errors that I am getting, when trying to run eegnb runexp -ip:
CBManager is not powered on and libc++abi.dylib: terminating with uncaught exception of type NSException
...
okay
from eegnb.analysis.utils import check_report check_report(myeeg)
is real cool, and should just be run before each block I would think.
no, I think issue has been resolved.