Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized.

PyThresh is a comprehensive and scalable Python toolkit for thresholding outlier detection likelihood scores in univariate/multivariate data. It has been written to work in tandem with PyOD and has similar syntax and data structures. However, it is not limited to this single library.

PyThresh is meant to threshold likelihood scores generated by an outlier detector. It thresholds these likelihood scores and replaces the need to set a contamination level or have the user guess the amount of outliers that may exist in the dataset beforehand. These non-parametric methods were written to reduce the user's input/guess work and rather rely on statistics instead to threshold outlier likelihood scores. For thresholding to be applied correctly, the outlier detection likelihood scores must follow this rule: the higher the score, the higher the probability that it is an outlier in the dataset. All threshold functions return a binary array where inliers and outliers are represented by a 0 and 1 respectively.

PyThresh includes more than 30 thresholding algorithms. These algorithms range from using simple statistical analysis like the Z-score to more complex mathematical methods that involve graph theory and topology.

sklearn-compat is a small Python package that help developer writing scikit-learn compatible estimators to support multiple scikit-learn versions.

This package is an integration module of Optuna, an automatic Hyperparameter optimization software framework. The modules in this package provide users with extended functionalities for Optuna in combination with third-party libraries such as PyTorch, sklearn, and TensorFlow.

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API. Thanks to our define-by-run API, the code written with Optuna enjoys high modularity, and the user of Optuna can dynamically construct the search spaces for the hyperparameters.

This package provides a neural network library for PyTorch compatible with the scikit-learn API.

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation and providing a delightful developer experience.

DOLFINx is the computational environment of FEniCSx and implements the FEniCS Problem Solving Environment in C++ and Python.

This package provides the Python interface.

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.

FFCx is a compiler for finite element variational forms.

From a high-level description of the form in the UFL, it generates efficient low-level C code that can be used to assemble the corresponding discrete operator (tensor). In particular, a bilinear form may be assembled into a matrix and a linear form may be assembled into a vector.

This package provides the UFCx interface header.

Library implementing Block-GMres with Inexact Breakdown and Deflated Restarting, Breakdown Free Block Conjudate Gradiant, Block General Conjugate Residual and Block General Conjugate Residual with Inner Orthogonalization and with inexact breakdown and deflated restarting.

DBCSR is a library designed to efficiently perform sparse matrix-matrix multiplication, among other operations. It is MPI and OpenMP parallel and can exploit Nvidia and AMD GPUs via CUDA and HIP.

The Basic Linear Algebra Subprograms (BLAS) have been around for many decades and serve as the de facto standard for performance-portable and numerically robust implementation of essential linear algebra functionality. The objective of BLAS++ 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.

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.

The Unified Form Language (UFL) is a domain specific language for declaration of finite element discretizations of variational forms. More precisely, it defines a flexible interface for choosing finite element spaces and defining expressions for weak forms in a notation close to mathematical notation.

Grace is a 2D plotting tool for the X Window System. It has a Motif-based GUI and a scripting language that includes curve fitting, analysis, and export capabilities.

DOLFINx is the computational environment of FEniCSx and implements the FEniCS Problem Solving Environment in C++ and Python.

This package provides the C++ interface.

FFCx is a compiler for finite element variational forms.

From a high-level description of the form in the UFL, it generates efficient low-level C code that can be used to assemble the corresponding discrete operator (tensor). In particular, a bilinear form may be assembled into a matrix and a linear form may be assembled into a vector.

This package provides the CLI and Python library.

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.

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.

Plastimatch is a computer software application which has been designed for volumetric (usually medical) image processing and radiation therapy applications. It can be used for the following purposes:

• Deformable registration

• Atlas-based segmentation

• Image conversion and manipulation

• Vector field conversion and manipulation

• Gamma analysis

• Dose calculation

• Registration analysis (Jacobian)

• Segmentation analysis (Dice, Hausdorff)

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.