This document lays out a set of Python packaging practices. I don't claim they are best practices, but they fit my needs, and might fit yours.
This document has been superseded as of January 2023.
This was written in July 2020, superseding this gist from 2019.
| import os | |
| import nibabel as nb | |
| import numpy as np | |
| # Create an image with a "plausible" range of fMRI values | |
| img = nb.Nifti1Image(np.random.uniform(500, 2000, (256,256,256,1)), np.eye(4)) | |
| # Verify numpy's giving us float64 | |
| assert img.get_data_dtype() == np.float64 | |
| # Quantize to 16 bits and reload |
| <!-- | |
| Initially provided by John Harwell on the HCP user list [0]. | |
| Modified by Chris Markiewicz based on example wb.spec files. | |
| [0] https://groups.google.com/a/humanconnectome.org/g/hcp-users/c/EGuwdaTVFuw/m/Pir-LpbHAQAJ | |
| --> | |
| <!ELEMENT CaretSpecFile (MetaData?, DataFile+)> | |
| <!ATTLIST CaretSpecFile | |
| Version ( 1.0 ) #REQUIRED |
OpenNeuro has implemented a data retention policy, stating that datasets that have been in draft state for greater than 28 days may be reverted to the latest snapshot. Unfortunately, we don't currently have an interface for viewing what changes have been made since the last snapshot, so users may not know whether they want to create a new snapshot or not.
This gist shows two ways to view the changes using the OpenNeuro CLI. We will use ds000001 as an example.
The easy but slow approach would be to use the CLI to download two copies of your dataset, the most recent tag and the draft, and run diff -r on the pair:
| /* eslint-disable */ | |
| /** | |
| * This file was automatically generated by json-schema-to-typescript. | |
| * DO NOT MODIFY IT BY HAND. Instead, modify the source JSONSchema file, | |
| * and run json-schema-to-typescript to regenerate this file. | |
| */ | |
| export interface Context { | |
| /** | |
| * The BIDS specification schema |