Hi,
I am working with a legacy script.
The legacy script was written for
mne 0.15.2
and is running on Python 3.6.9 (default, Jan 26 2021, 15:33:00) on
Distributor ID: CentOS
Description: CentOS release 6.7 (Final)
The legacy script is running ok until
inv = mne.minimum_norm.make_inverse_operator(evokedList[0].info, fwd, cov, loose=0.2)
I see the python error:
operands could not be broadcast together with shapes (3,) (12,) (3,)
And the mne error feedback:
RuntimeWarning: Something went wrong in the data-driven estimation of the data rank as it exceeds the theoretical rank from the info (298 > 69). Consider setting rank to “auto” or setting it explicitly as an integer.
I could use some help interpreting these errors.
Thank you,
Megan
I am a bit confused, as the command as it is seems like rank is set to ‘auto’ by default.
Here is a bit more information.
This preceding command completed successfully:
fwd = mne.make_forward_solution(evokedList[0].info, newAlign, src, bem_sol, meg=True, eeg=False)
About the evokedList[0].info object:
Info | 28 non-empty fields
acq_pars : str | 21723 items
bads : list | 0 items
ch_names : list | MEG0113, MEG0112, MEG0111, MEG0122, MEG0123, MEG0121, …
chs : list | 306 items (GRAD: 204, MAG: 102)
comps : list | 0 items
custom_ref_applied : bool | False
description : str | 24 items
dev_head_t : Transform | 3 items
dig : list | 7 items
events : list | 1 items
experimenter : str | 9 items
file_id : dict | 4 items
highpass : float | 1.0 Hz
hpi_meas : list | 1 items
hpi_results : list | 1 items
hpi_subsystem : dict | 2 items
line_freq : float | 60.0
lowpass : float | 30.0 Hz
maxshield : bool | False
meas_date : ndarray | 2018-07-31 15:11:05 GMT
meas_id : dict | 4 items
nchan : int | 306
proc_history : list | 1 items
proj_id : ndarray | 1 items
proj_name : str | 15 items
projs : list | planar-998–0.500-0.500-PCA-01: on, …
sfreq : float | 1000.0 Hz
subject_info : dict | 6 items
acq_stim : NoneType
ctf_head_t : NoneType
dev_ctf_t : NoneType
kit_system_id : NoneType
xplotter_layout : NoneType
About the cov object:
Covariance | size : 306 x 306, n_samples : 134800
About the fwd object:
Forward | MEG channels: 306 | EEG channels: 0 | Source space: Surface with 8196 vertices | Source orientation: Free
Thanks again for any troubleshooting ideas.
Megan
Hello! Well, I was trying to recreate the error to get any more information, and the command completed without error. So possibly I had a mistake in my previous attempt to capture the error. I will see if I can close this topic