| #!/usr/bin/env python | |
| # Copyright 2024 Board of Regents of the Universities of Wisconsin | |
| # Written by Nate Vack <[email protected]> | |
| """MRI Image Mosaic. | |
| Makes an MxN mosaic of images, intended for checking things like defacing | |
| and alignment. |
| #!/usr/bin/env python | |
| """ | |
| Simple EMA schedule generator. Outputs to stdout. | |
| Usage: | |
| ema_gen.py [options] <record_id> <sched_field> <start_time> <days> <samples_per_day> <sampling_min> <gap_min> | |
| ema_gen.py interval_test <iters> <num_samples> <sampling_minutes> <gap_minutes> | |
| Options: |
| #!/usr/bin/env python | |
| """ | |
| Takes a REDCap CSV file and splits it into: | |
| * A file for each event | |
| * A file for repeated instruments in events where they happen | |
| So, if your data has events 'scr,' 'pre,' and 'post', and 'pre' and 'post' | |
| each have a repeated instument called 'meds', you can expect |
| """ | |
| Generates an array blocks * block_len long, containing 1 and 2. | |
| It's shuffled such that there can never be more than block_len | |
| consecutive repetitions of either value. | |
| """ | |
| import numpy as np | |
| blocks = 100 | |
| block_len = 8 | |
| groupnums = (np.arange(blocks * block_len) % 2) + 1 |
This Slack group is for any and everyone involved in tech at UW-Madison. Students, staff, faculty, alumni, and emeriti are all welcome. We're here to share tips and tricks, debate policy, but more importantly: to be a community.
The current admins are:
| # Binary builds | |
| tap "homebrew/cask" | |
| # Lets me get at things like sequel-pro-nightly | |
| tap "homebrew/cask-versions" | |
| # mas -> "Mac App Store" | |
| brew "mas" | |
| mas "Xcode", id: 497799835 | |
| brew "imagemagick" |
I hereby claim:
To claim this, I am signing this object:
| # -*- coding: utf-8 -*- | |
| # Written by Nate Vack <[email protected]> at the Center for Healthy Minds | |
| # Copyright 2019 Board of Regents of the University of Wisconsin System | |
| # Permission is hereby granted, free of charge, to any person obtaining a copy | |
| # of this software and associated documentation files (the "Software"), to deal | |
| # in the Software without restriction, including without limitation the rights | |
| # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| # copies of the Software, and to permit persons to whom the Software is |
| #!/usr/bin/env python | |
| """ | |
| Compute stimulus orderings for the mnemonic similarity task, described in: | |
| Stark SM, Stevenson R, Wu C, Rutledge S, & Stark CEL (2015). Stability of | |
| age-related deficits in the mnemonic similarity task across task variations. | |
| Behavioral Neuroscience 129(3), 257-268. | |
| Written by Nate Vack <[email protected]> at the Center for Healthy Minds, | |
| University of Wisconsin-Madison, for the mp2 study conducted by Dan Grupe |
| #!/bin/bash | |
| # Written by Jonah Chaiken and Nate Vack | |
| # Support: [email protected] | |
| help=" Usage: convert_dcm2niix.sh <in_file> <out_file> | |
| This program will individually convert a dicom archive file to a NIfTI file. | |
| The input can be either a .tar file containing bzip2'd dicom slices, or a |