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    Michael Shvartsman
    @mshvartsman
    (ah, and either source or conda is cool if you set up your shell correctly for conda, I was in zsh without having it set up correctly)
    Mihai Capotă
    @mihaic
    Good to hear. I have a branch that fixes the eventseg errors; waiting for an update to Jenkins to open a PR.
    SebastianSpeer
    @SebastianSpeer
    hello brainiak team
    I've been trying to install brainiak and use it in the Jupyter notebook. It seems to have installed fine via conda but when I try to import it, it can't find the module
    Do you have any suggestions as to how to fix this issue?
    I've also tried to install brainiak with pip
    but it also didnot work
    Mingbo Cai
    @lcnature
    Hi Sebastian. Can you show one example command of importing you have tried?
    Michael Shvartsman
    @mshvartsman
    Did you install brainiak in a conda environment that’s not your root env? Last time I checked, Jupyter doesn’t play nicely with conda envs by default. You need https://docs.anaconda.com/anaconda/user-guide/tasks/use-jupyter-notebook-extensions/#notebook-conda or another similar workaround.
    Shayne Lin
    @shayne_shlin_twitter
    Hi I have a question installing the Docker on my Mac. I tried to paste the token to the Jupyter notebook but it keeps saying that this is a invalid credential. Can anyone help? Thanks.
    Mihai Capotă
    @mihaic
    Hello, @shayne_shlin_twitter. Can you please share a link to the instructions you are following?
    Shayne Lin
    @shayne_shlin_twitter
    @mihaic Here's the link I followed: https://brainiak.org
    Mihai Capotă
    @mihaic
    @shayne_shlin_twitter, could you please also try accessing the URL presented on the command line after running the Docker command?
    Shayne Lin
    @shayne_shlin_twitter
    @mihaic Actually, I just installed condo and followed this link to install brainiak as well: https://brainiak.org
    And it works but when I tried the import functions, it said the command cannot be found. I saw that there are other people struggling with that too and another person has answered it by offering this website: https://docs.anaconda.com/anaconda/user-guide/tasks/use-jupyter-notebook-extensions/#notebook-conda
    I tried it but again, I couldn't use the function "jupyter"... Would you be kindly to give me some guidance on that? Thanks.
    Mihai Capotă
    @mihaic
    The Conda instructions at the main page of brainiak.org are not sufficient for running Jupyter. You need to separately install Jupyter. I think it would be best to try to get Docker running, because it has everything ready.
    Shayne Lin
    @shayne_shlin_twitter
    @mihaic Okay, so here's my progress with Docker and please bear with me because I'm relatively new to this... So I ran "docker pull brainiak/brainiak" and it went without error, but when I ran "ocker run -it -p 8899:8899 --name demo brainiak/brainiak", it showed this:
    The container name "/demo" is already in use by container "db4b66acb135f4832b75dea2fcc1d67abdca636a6cd1cb9a34801de6066aa49e". You have to remove (or rename) that container to be able to reuse that name.
    So I think that hyphenated random codes are the token so I pasted that onto the Jupiter notebook page but it did not work...
    Mihai Capotă
    @mihaic
    That's OK. If you don't need the previous container anymore, remove it using the following command:
    docker container rm demo
    Then the run command should work again and you should see a new URL.
    Shayne Lin
    @shayne_shlin_twitter
    I wasn't able to remove it. This is what it told me
    You cannot remove a running container db4b66acb135f4832b75dea2fcc1d67abdca636a6cd1cb9a34801de6066aa49e. Stop the container before attempting removal or force remove.
    Mihai Capotă
    @mihaic
    Go to the window where you started it and stop it.
    Shayne Lin
    @shayne_shlin_twitter
    I actually don't know how I might accidentally started it. Could you be more specific on how I can stop it? Thanks. > <
    Mihai Capotă
    @mihaic
    You started it using the docker run command.
    Alternatively, you can force remove the container:
    docker container rm -f demo
    Clare Grall
    @claregrall
    Hello! I know this issue has been discussed before, but I can't crack the solution for the following error when installing on a new computer... "cannot import name 'cython_blas' from 'brainiak.fcma' (/Users/cgrall/.local/lib/python3.7/site-packages/brainiak/fcma/init.py)"
    Mihai Capotă
    @mihaic
    Hello, @claregrall! You came to the right place for help. What instructions did you follow for your installation?
    Clare Grall
    @claregrall
    ... all of them? Maybe the real question I should be asking is about the "failed to build wheel" issue (which never finalizes with a Successfully Installed message).
    Clare Grall
    @claregrall
    installation guide for macos, trying to work through conda and pip, both fail
    Mihai Capotă
    @mihaic
    How about we try to debug the Conda installation? Can you please create a new environment, run the installation command and paste everything you see here?
    Clare Grall
    @claregrall
    it looks like creating a new environment was all it took for successful import, but I don't quite get why.. looking into it. Pardon the unnecessary messages
    Mihai Capotă
    @mihaic
    No worries. Glad it worked. :)
    sncraig01
    @sncraig01
    Hello! I was working on Brainiak tutorial #10 and was wondering what I could do to get the answer key? There are lot of sections left out and I would love to be able to see them!
    ruiqing
    @jane2qian
    hi, everyone! I'm now using SRM for over 40 participants'data, and the processing waits too long.. so I wonder does the brainiak supports GPU processing?
    Qihong Lu
    @qihongl
    Hi @manojneuro @CameronTEllis , @sncraig01 was asking about the answer keys. It just noticed we don't seem to have a clear instruction about how to get the sample responses on the tutorial website...
    @jane2qian I don't think SRM has GPU support. Parallelization is achieved by MPI. Other people can correct me if I'm wrong about it. Though I think we are about to have a faster version of SRM: brainiak/brainiak#416 ; btw how many voxels/TRs do you have in your data per participant?
    CameronTEllis
    @CameronTEllis
    @sncraig01 At present we have no answer key. We are making some edits that will be finalized soon. After that we will give the answer key to anyone who promises that they are not currently nor in the future will be in a for-credit course that uses these materials. In the mean time, if you would like me to share any of the answers with you then you can reach out to me directly and ask any specific questions you have
    ruiqing
    @jane2qian
    Thank you! @qihongl 166953 voxels*973 TRs per subject. Our aim is to differentiate groups using two step srm. I wanna try several parameters to get the optimized model in each step. I should just use the old srm version then until the fast version is released. Any advice on the parameters selection?
    manojneuro
    @manojneuro
    @qihongl @CameronTEllis I have been in touch with @sncraig01 and have helped them out. They are all set. (There was a parallel thread on the brainiak email list).
    Qihong Lu
    @qihongl
    Hi, @jane2qian sorry about the delayed reply... I forgot to check this thread.
    I think the number of voxels suggests you are doing some whole-brain analysis? I don't think the amount of data you have is enough for SRM to estimate Ws and S. Is it possible to constrain the analysis to certain ROIs? This is what's typically done in the literature.
    Qihong Lu
    @qihongl
    btw if you narrow down to some ROIs, typically speed shouldn't be an issue.
    zacharybretton
    @zacharybretton
    I am having an issue installing Brainiak. I am doing it on MacOS, and even tried using a new environment (as the person above who last had trouble). I keep getting to the failure to build a wheel, but it then always fails to install after: "ERROR: Failed building wheel for brainiak
    Running setup.py clean for brainiak
    Failed to build brainiak
    ERROR: Could not build wheels for brainiak which use PEP 517 and cannot be installed directly"
    when I try it via Conda "conda install -c brainiak -c defaults -c conda-forge brainiak" It keeps doing "Collecting package metadata (current_repodata.json): done
    Solving environment: failed with current_repodata.json, will retry with next repodata source.
    Initial quick solve with frozen env failed. Unfreezing env and trying again." and then doesn't seem to ever succeed
    zacharybretton
    @zacharybretton
    ^^^^ - I was able to get it to work, seems like theres an issue with the more recent version of Conda. So I had to downgrade and then I was able to get everything to install just fine
    Mihai Capotă
    @mihaic

    Hello, @zacharybretton. Thanks for the feedback. Regarding the PEP 517 error, try adding the --no-use-pep517 to the install command:

    python3 -m pip install --no-use-pep517 brainiak

    See for more details brainiak/brainiak#435
    We'll look into the problem with the newest Conda version.

    Mingbo Cai
    @lcnature
    Hi, does anyone know if the searchlight module allows the function to be passed to run_searchlight to return more than one value or vectors? (say, a list of np arrays of different shapes) Thanks!
    CameronTEllis
    @CameronTEllis
    HI Mingbo. The searchlight code natively deals with returning a list inside the kernel function. This means the output will be a numpy array with each voxel being a list. However because of the nature of numpy arrays this can be difficult to index. If you want some example code of how to use this output then I am happy to send it to you.
    Mingbo Cai
    @lcnature
    That will be nice! My function want to return a few np arrays.
    CameronTEllis
    @CameronTEllis
    Sorry about the delay @lcnature, I got buried at SFN. Here is a small chunk of code you can use that should help:
    masked_data = sl_result[mask == 1] # Get only the masked data
    
    number_elements = len(masked_data[0]) # Get the length of the first unmasked voxel
    
    concat_sl_result = np.zeros((sl_result.shape) + (number_elements, )) # Concatenate tuples to get a stacked volume for each of the SL kernel outputs
    
    # Cycle through the outputs of the SL kernel
    for element_counter in range(number_elements):
    
        # Get the volume for this SL kernel
        concat_sl_result[mask == 1, element_counter] = [voxel[element_counter] for voxel in masked_data]
    Mingbo Cai
    @lcnature
    Thank you very much, @CameronTEllis !