Skip to main content

Gradient waveform design tool for arbitrary k-space trajectories.

Project description

Magnetic Resonance Arbitrary Gradient Toolbox (MRArbGrad, MAG)

Introduction

This toolbox is a pip package with C++ backend. The pip package can be called via Python interface to generate non-Cartesian gradient waveforms for built-in and external trajectories. The C++ source code (in mrarbgrad_src/ext/) can be ported to other pulse sequence project like UIH's Adept project for gradient waveform calculation.

Install

Optionally, to create a new conda environment (in case the dependencies in this package break your current environment), please run:

$ conda create -n magtest -y
$ conda activate magtest
$ conda install python==3.12 -y

This package is NOT restricted to use Python 3.12. Feel free to adjust at your convenience, just if the package works.

To install this package from PyPI:

$ pip install mrarbgrad

To install this package from a local repository:

$ bash install.bash

You can also install via pip install . but remember to delete *.egg-info or pip will run into bug when uninstalling this package in current folder (see comments in install.bash).

Examples & Usages

Examples for generating gradient waveforms for either built-in trajectory (trajectory library) or external trajectory (expressed by trajectory function or trajectory samples) can be found in the example folder.

Reference

If this project helps you, please cite our paper:

[1] Luo R, Huang H, Miao Q, Xu J, Hu P, Qi H. Real-Time Gradient Waveform Design for Arbitrary k-Space Trajectories. IEEE Transactions on Biomedical Engineering. 2026;1–12.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mrarbgrad-4.2.0.tar.gz (31.2 kB view details)

Uploaded Source

File details

Details for the file mrarbgrad-4.2.0.tar.gz.

File metadata

  • Download URL: mrarbgrad-4.2.0.tar.gz
  • Upload date:
  • Size: 31.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.8

File hashes

Hashes for mrarbgrad-4.2.0.tar.gz
Algorithm Hash digest
SHA256 818486f2c0e81649a8caddced0705a2d4d3658521859ca0fc2404960b908fd84
MD5 220f74b334038fa3f1663de658e4d79d
BLAKE2b-256 d30c923b4382f0572a24584f73510dd697feae35fd4f5fe046ee154f17d75e8f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page