Floating Point Exception from Source Estimation (the first introduction tutorial on EEG/MEG analysis with MNE

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:question: If you have a question or issue with MNE-Python, please include the following info:

  • MNE version: e.g. 1.4.2
  • operating system: e.g. macOS Ventura 13.0

# load inverse operator

inverse_operator_file = (

sample_data_folder / "MEG" / "sample" / "sample_audvis-meg-oct-6-meg-inv.fif"

)

inv_operator = mne.minimum_norm.read_inverse_operator(inverse_operator_file)

# set signal-to-noise ratio (SNR) to compute regularization parameter (λ²)

snr = 3.0

lambda2 = 1.0 / snr**2

# generate the source time course (STC)

stc = mne.minimum_norm.apply_inverse(

vis_evoked, inv_operator, lambda2=lambda2, method="MNE"

) # or dSPM, sLORETA, eLORETA

# path to subjects' MRI files

subjects_dir = sample_data_folder / "subjects"

print(stc.data)

# plot the STC

stc.plot(

initial_time=0.1, hemi="split", views=["lat","med"], subjects_dir=subjects_dir

)

error message: zsh: floating point exception /Users/frankyang/opt/anaconda3/bin/python

I basically just copy paste the code from the MNE notebook to my own python IDE VSS. I also downloaded all the dependencies following the command in the tutorial.