A LEMS simulator written in Python which can be used to run NeuroML2 models.

Quantities is designed to handle arithmetic and conversions of physical quantities, which have a magnitude, dimensionality specified by various units, and possibly an uncertainty. It builds on the NumPy library and is designed to work with numpy.ufuncs, many of which are already supported.

Optimized einsum can significantly reduce the overall execution time of einsum-like expressions by optimizing the expression's contraction order and dispatching many operations to canonical BLAS, cuBLAS, or other specialized routines. Optimized einsum is agnostic to the backend and can handle NumPy, Dask, PyTorch, Tensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially any library which conforms to a standard API. See the documentation for more information.

The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.

The goal of this package is to provide a reference implementation of trait types for common data structures used in the scipy stack such as numpy arrays or pandas and xarray data structures. These are out of the scope of the main traitlets project but are a common requirement to build applications with traitlets in combination with the scipy stack.

The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.

This package provides encoding and decoding routines that enable the serialization and deserialization of numerical and array data types provided by numpy using the highly efficient msgpack format. Serialization of Python's native complex data types is also supported.

This package provides Python tools for the Open Reflectometry Standards Organization (ORSO). It includes utilities for working with reflectometry data files and the ORSO file format.

This Python module uses matplotlib to visualize multidimensional samples using a scatterplot matrix. In these visualizations, each one- and two-dimensional projection of the sample is plotted to reveal covariances. corner was originally conceived to display the results of Markov Chain Monte Carlo simulations and the defaults are chosen with this application in mind but it can be used for displaying many qualitatively different samples.

This is a package for image processing with Dask arrays. Features:

• Provides support for loading image files.

• Implements commonly used N-D filters.

• Includes a few N-D Fourier filters.

• Provides some functions for working with N-D label images.

• Supports a few N-D morphological operators.

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python.

This package provides a generic container plugin implementing snakemake's software-deployment interface.

Trimesh is a pure Python library for loading and using triangular meshes with an emphasis on watertight surfaces. The goal of the library is to provide a full featured and well tested Trimesh object which allows for easy manipulation and analysis, in the style of the Polygon object in the Shapely library.

This package provides fast array utilities with minimal dependencies.

scikit-fem is a library for performing finite element assembly. Its main purpose is the transformation of bilinear forms into sparse matrices and linear forms into vectors.

This package provides an extremely lightweight compatibility layer between dataframe libraries.

• full API support: cuDF, Modin, pandas, Polars, PyArrow

• lazy-only support: Dask, DuckDB, Ibis, PySpark, SQLFrame

Pint is a Python package to define, operate and manipulate physical quantities: the product of a numerical value and a unit of measurement. It allows arithmetic operations between them and conversions from and to different units.

This package provides Numba-accelerated implementations of common SciPy probability distributions and others used in particle physics.

The supported distributions are:

• Uniform

• (Truncated) Normal

• Log-normal

• Poisson

• Binomial

• (Truncated) Exponential

• Student's t

• Voigtian

• Crystal Ball

• Generalised double-sided Crystal Ball

• Tsallis-Hagedorn, a model for the minimum bias pT distribution

• Q-Gaussian

• Bernstein density (not normalized to unity)

• Cruijff density (not normalized to unity)

• CMS-Shape

• Generalized Argus

A Snakemake executor plugin for running srun jobs inside of SLURM jobs (meant for internal use by python-snakemake-executor-plugin-slurm).

PyTensor is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is a fork of the Aesara library.

This is a Python implementation of UpSet plots by Lex et al. UpSet plots are used to visualize set overlaps; like Venn diagrams but more readable.

Numpoly is a generic library for creating, manipulating and evaluating arrays of polynomials based on numpy.ndarray objects.

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python.

Scikit-opt (or sko) is a Python module implementing swarm intelligence algorithms: genetic algorithm, particle swarm optimization, simulated annealing, ant colony algorithm, immune algorithm, artificial fish swarm algorithm.