mne-python

✉️ Mailing List Archive (read-only)
1

Dear MNE Experts:

In going through the tutorial for the new mne-python tools, I have a few questions I could use some help with. First of all, though, let me say that I think adding this functionality using python is very exciting! Anyway, here are my questions so far:

1) In the section entitled "Read and plot a segment of raw data", unless I'm missing something, I don't see a command for plotting the selected segment of raw data.

2) Similarly, for the time-frequency section, what are the commands for producing the graphs shown at the end of that section?

3) The MEG sample dataset I downloaded using the

data_path = sample.data_path()
command did not come with a "labels" subdirectory. So in the "Inverse modeling" section, I can't "compute dSPM on a raw file within a label".

Any help would be greatly appreciated.

Thanks,
Will

PS: The links at the very bottom of the mne-python page (the "Want to know more?" section) don't seem to work for non-Martinos/MGH people like me.

2

Hi William,

In going through the tutorial for the new mne-python tools, I have a few questions I could use some help with. First of all, though, let me say that I think adding this functionality using python is very exciting!

glad you like it !

Anyway, here are my questions so far:

1) In the section entitled "Read and plot a segment of raw data", unless I'm missing something, I don't see a command for plotting the selected segment of raw data.

correct.

see the example:

https://github.com/mne-tools/mne-python/blob/master/examples/plot_read_and_write_raw_data.py

the full gallery of examples should be public soon when we make public the new
mne website.

2) Similarly, for the time-frequency section, what are the commands for producing the graphs shown at the end of that section?

see:

https://github.com/mne-tools/mne-python/blob/master/examples/time_frequency/plot_time_frequency.py

3) The MEG sample dataset I downloaded using the

data_path = sample.data_path()
command did not come with a "labels" subdirectory. So in the "Inverse modeling" section, I can't "compute dSPM on a raw file within a label".

I am glad you've reached this point of the tutorial.
We need to update the sample data set with the labels.

put the labels folder attached in MEG/sample.

I am at a conference currently and I'll be back at work in a few days
to take care of all this.

Any help would be greatly appreciated.

hope this helps.

PS: The links at the very bottom of the mne-python page (the "Want to know more?" section) don't seem to work for non-Martinos/MGH people like me.

yes. The new mne website is not publicly available.

It should be up soon.

Alex
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3

Hi Alex,

Thanks very much for your help. I have another question that I feel is very basic, but I'm still finding my legs with python and I can't yet seem to figure this one out on my own. In the "Access raw data" section of the mne-python page, the command:

data_path = sample.data_path()

downloads the sample dataset from MGH. But my question is, if I have already downloaded it, how do I set the path to recognize where it is currently located, rather than having to download it again? It looks like this function comes from the "__init__.py" script in the "mne-python/mne/datasets/sample" directory, but in spite my trying to parse it I still can't seem to figure it out.

Thanks,
Will

4

Hi William,

downloads the sample dataset from MGH. But my question is, if I have already downloaded it, how do I set the path to recognize where it is currently located, rather than having to download it again? It looks like this function comes from the "__init__.py" script in the "mne-python/mne/datasets/sample" directory, but in spite my trying to parse it I still can't seem to figure it out.

you can simply do:

data_path = sample.data_path('/path/to/data')

or

data_path = sample.data_path('..')

like you would do with "cd" on unix.

ALex

5

Thanks Alex. Turns out the problem was that I was including my local "MNE-sample-data" directory in the path. Once I only included everything up to one level above that it worked. Of course, I couldn't isolate that until you showed me exactly what the syntax should be.

Thanks again,
Will