See mne-tools/mne-python#6262 (comment) :

seeing this in a example I would suggest to add a method Covariance.plot_topomap(info) to display the topomap of diagonal. this would simplify this example a lot

This will hopefully just require some short function in mne/viz/topomap.py. Even using the EvokedArray approach seems okay since it's pretty straigh

In augmentation, elastic_transform, it only applies a random transform on one input image array. I would think to be used for training, the image and mask pair should be transform in the same way. However, this single-input-image, single-output-image method makes it very inconvenient. Could we deform a list of images (np.arrays) using the same transformation in this method ? Thanks!

In the documentation built from master branch, there are two examples with missing thumbnails. These were imported from Nistats, and they are missing there as well.

We need to fix this before rolling out the next Nilearn stable.

The two examples are:

9.5.2. Example of a events.tsv file generation: the neurospin/localizer events
04_glm/first-level-models-write-events-file.py

9.8.9. D

I have disabled the PDF builds after merging #3124. It is probably something easy to fix, but is there a strong reason to keep building the PDF output?

Reported by @britta-wstnr by e-mail:

Documenting and taking it from here

1. we just came across some unexpected behavior (helping a student today) with ft_prepare_sourcemodel(). If we warp an MNI template, inwardshift has no effect - is that because that would shift grid points to the wrong positions after warping?

2. We often see problems with not inwardshifted sources when using the ope

Anatomical data can be viewed using the built-in identity transform in pycortex:

import cortex
nifti = cortex.db.get_anat('S1')
arr = nifti.get_data().T
vol = cortex.Volume(arr, 'S1', 'identity')
cortex.webgl.show(vol)

Description

As suggested on this comment, it would be good to have a function for generating random affine matrix.
This is just a reminder.

Right now the top-level ToC is:

• Installation
• Usage Notes
• Running fMRIPrep via Docker containers
• Running fMRIPrep via Singularity containers
• Processing pipeline details
• Susceptibility Distortion Correction (SDC)
• Outputs of fMRIPrep
• Defining standard and nonstandard spaces where data will be resampled
• FAQ, Tips, and Tricks
• Contributing to

Some is already in .gitignore, but some is not. We should check all examples.

It would be great to have a 3D diagram of the Freesurfer coordinate system in the documentation https://surfer.nmr.mgh.harvard.edu/fswiki/CoordinateSystems?action=AttachFile&do=get&target=fscoordinates.pdf, like this example http://www.fieldtriptoolbox.org/faq/how_are_the_different_head_and_mri_coordinate_systems_defined/ especially to clarify fsaverage vs single subject space.

cc @robertoosten

Refer to https://mriqc.readthedocs.io/en/stable/install.html#bare-metal-installation-only-python-3,

requirements.txt file does not exist. Maybe we need to update the documentation.

In the meantime, did you used to have the packages mentioned in dockerfile in requirements.txt ?

ATM "Scans file" can contain prescribed acq_time column (which could be anonymized or not) and an arbitrary number of additional columns: "Additional fields can include external behavioral measures relevant to the scan.". I think the situation is similar to _events.tsv file which now is SHOULD ha

Slicer API documentation has not been updated since January.

See footer of any documentation page, for example this: Generated on Thu Jan 30 2020 21:22:17 for Slicer by doxygen 1.8.14

an improvement suggested in closed PR thread #6267

I would prefer to indicate when it is required. Other options might be invalidated in the future.
Similar change should also be applied to the MRI section below.

This step is optional and is required only if instruments are used: \

Originally posted by @PapillonMcGill in aces/Loris#6267

not just compare different feature sets with a fixed builtin model, but users can also input a model of their own choice. it does not limit exploration of new models or pipelines - they can use implementation of best practices while evaluating the such new models on features of their choice

Most software packages of similar size and purpose as bids-validator have a comprehensive documentation. Meanwhile, we have a long README and a CONTRIBUTING file (which is not very visible).

What do you think about having dedicated docs build by some CI and then hosted on the gh-pages branch of this repo?

We could split the README into logical parts, improve the visibility of the CONTRIBUT

Has anyone managed to get the tutorial to run under singularity? I just did a pull and conversion with

singularity pull docker://miykael/nipype_tutorial:latest

There seems to be something funny about the path inside the image - jupyter isn't on it.

singularity exec -C nipype_tutorial-latest.simg jupyter notebook
/.singularity.d/actions/exec: 9: exec: jupyter: not found
singul

It's possible to be more flexible with "searchMethod": "re"

Put example in the documentation to do thing like :

• "EchoTime": > 0.1
• "SeriesDescription": "MPRAGE" or "IR-FSPGR"

Adding here other lists that either were used to create the list of this repository, or for ideas for this project.

• Martina's list
• Hitchhacker's brain to the universe
• Rémi's list
• [neurolinks](https://brainhack101.github.io/neu

Ideally I want to use this wonderful toolbox to generate the overview plots given in the interactive window but do the actual marking of these images externally.

Is there an option to generate individual plots without the interactive window (and preferably without the need for tkmedit) as I would like to run this as a batch job on our cluster and that wouldn't allow any graphical windows.

I wonder whether you could add singularity commands for quick demonstration in the Usage section. Currently it only has information for docker and command line.