The Linear Algebra PACKage (LAPACK) is a standard software library for numerical linear algebra. The objective of LAPACK++ is to provide a convenient, performance oriented API for development in the C++ language, that, for the most part, preserves established conventions, while, at the same time, takes advantages of modern C++ features, such as: namespaces, templates, exceptions, etc.

Basix is a finite element definition and tabulation runtime library.

Basix allows users to:

• evaluate finite element basis functions and their derivatives at a set of points;

• access geometric and topological information about reference cells;

• apply push forward and pull back operations to map data between a reference cell and a physical cell;

• permute and transform DOFs to allow higher-order elements to be use on arbitrary meshes;

• interpolate into and between finite element spaces.

Basix includes a range of built-in elements, and also allows the user to define their own custom elements.

This package provides the Python wrapper for Basix.

STIR is an object-oriented framework for tomographic image reconstruction, with an emphasis on iterative reconstruction in PET and SPECT. This package includes the C++ core and Python bindings.

This package provides a Python library for manipulating data saved as ISMRMRD.

The siemens_to_ismrmrd converter is used to convert data from Siemens raw data format into ISMRMRD raw data format.

This package provides a viewer for ISMRMRD data.

A prerequisite for sharing magnetic resonance (imaging) reconstruction algorithms and code is a common raw data format. The ISMRMRD project describes such a common raw data format, which attempts to capture the data fields that are required to describe the magnetic resonance experiment with enough detail to reconstruct images. This package provides a C/C++ library for working with the format.

The Gamma Mesh Format (GMF) and the associated library libMeshb provide programers of simulation and meshing software with an easy way to store their meshes and physical solutions. The GMF features more than 200 kinds of data types, like vertex, polyhedron, normal vector or vector solution field. The libMeshb provides a convenient way to move data between those files, via keyword tags, and the user's own structures.

libspatialindex provides spatial indexing utilities, with support for sophisticated spatial queries and interfaces for updating information and customizing the storage management of indices. The library is written in C++, with a C API.

libsupermesh is a Fortran 2008 library to intersect two overlapping meshes element by element. Pairs of overlapping elements are identified and a local mesh of their intersection is generated.

Umpire is a resource management library that allows the discovery, provision, and management of memory on machines with multiple memory devices like NUMA and GPUs.

MVAPICH2 (pronounced as “em-vah-pich 2”) is an open-source MPI software to exploit the novel features and mechanisms of high-performance networking technologies (InfiniBand, iWARP, RDMA over Converged Enhanced Ethernet (RoCE v1 and v2), Slingshot 10, and Rockport Networks) and deliver best performance and scalability to MPI applications.

MVAPICH (pronounced as “em-vah-pich”) is an open-source MPI software to exploit the novel features and mechanisms of high-performance networking technologies (InfiniBand, iWARP, RDMA over Converged Enhanced Ethernet (RoCE v1 and v2), Slingshot 10, and Rockport Networks) and deliver best performance and scalability to MPI applications. MVAPICH 4.1 has support for the Cray Slingshot 11, Cornelis OPX, and Intel PSM3 interconnects through the OFI libfabric library, and for the UCX communication library.

This package contains the binary resulting from the compilation of hello_c.c in the examples subdirectory of the Open MPI source code. It can be used to check MPI connectivity on a machine/cluster.

{dcmstack

CiftiLib is a C++ library for CIFTI-2 file reading/writing. It additionally supports CIFTI-1 files, and supports both on-disk and in-memory access. It also provides C++ code for reading and writing generic NIfTI-1 and NIfTI-2 files.

CIFTI (Connectivity Informatics Technology Initiative) standardizes file formats for the storage of connectivity data. These formats are developed by the Human Connectome Project and other interested parties.

See http://www.nitrc.org/projects/cifti/ for more information.

FSL is a comprehensive library of analysis tools for FMRI, MRI and diffusion brain imaging data. FSLeyes is a GUI for visualizing and editing brain images, from different sources and platforms.

A Python implementation of the moving average principal components analysis methods for functional MRI data translated from the MATLAB-based GIFT package.

It helps developers working in continuous integration (CI) environments by providing essential information about the CI server. It can determine if the code is running on a CI server,identify the specific server,and detect if a pull request is being tested.

Convert3d is a command-line tool for converting 3D images between common file formats. The tool also includes a growing list of commands for image manipulation, such as thresholding and resampling. The tool can also be used to obtain information about image files.

dcm2niix is designed to convert neuroimaging data from the DICOM format to the NIfTI format. dcm2niix is also able to generate a BIDS JSON format sidecar which includes relevant information for brain scientists in a vendor agnostic and human readable form.

This module provides simple, consistent access to package resources.

MRtrix3 provides a large suite of tools for image processing, analysis and visualisation, with a focus on the analysis of white matter using diffusion-weighted MRI.

fMRIPrep is a fMRI data preprocessing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to variations in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting. It performs basic processing steps (coregistration, normalization, unwarping, noise component extraction, segmentation, skull-stripping, etc.) providing outputs that can be easily submitted to a variety of group level analyses, including task-based or resting-state fMRI, graph theory measures, and surface or volume-based statistics.