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!

Following #2415, two points that were not tackled inside #2476 in the interest of short cycles

• Add a section in 2.1 on how to determine chance with a Decoder API (waiting for #2147)
• Rethink 2.2 section on OVO vs OVA, not sure it is useful as Decoder doesn't provide this flexibility easily. But show how to plot a confusion matrix using Decoder on a simple example.

The date and time on the output of the running docker container isn't correct, adding a volume "-v /etc/localtime:/etc/localtime:ro" might fix this?

This would help me know how long a process

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

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Slicer4.110.0-2020-09-10 on MacOSX 10.14.16

Problem

The sample column in events.tsv encodes the following:

OPTIONAL. Onset of the event according to the sampling scheme of the recorded modality (i.e., referring to the raw data file that the events.tsv file accompanies).

As identified by @robertoostenveld, we do