Pyzo is a Python IDE focused on interactivity and introspection,which makes it very suitable for scientific computing. Its practical design is aimed at simplicity and efficiency.

It consists of two main components, the editor and the shell, and uses a set of pluggable tools to help the programmer in various ways. Some example tools are source structure, project manager, interactive help, workspace...

Snakemake aims to reduce the complexity of creating workflows by providing a clean and modern domain specific specification language (DSL) in Python style, together with a fast and comfortable execution environment.

This package provides accelerated simulations and potentials of solids.

pyfma provides an implementation of fused multiply-add which computes (x*y) + z with a single rounding. This is useful for dot products, matrix multiplications, polynomial evaluations (e.g., with Horner's rule), Newton's method for evaluating functions, convolutions, artificial neural networks etc.

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

Thi package implements a functionality for mean-preserving interpolation of 1D data (for example, time series) with splines.

Histoprint uses a mix of terminal color codes and Unicode trickery (i.e. combining characters) to plot overlaying histograms.

SALib provides tools for global sensitivity analysis. It contains Sobol', Morris, FAST, DGSM, PAWN, HDMR, Moment Independent and fractional factorial methods.

This package provides fast numerical derivatives for analytic functions with arbitrary round-off error and error propagation.

This package implements schema validation for Xarray objects.

Formulaic is a high-performance implementation of Wilkinson formulas for Python.

This package provides a simplified scipy.signal.spectral module to do spectral analysis in Python.

This package provides a set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.

This package implements sparse arrays of arbitrary dimension on top of numpy and scipy.sparse. Sparse array is a matrix in which most of the elements are zero. python-sparse generalizes the scipy.sparse.coo_matrix and scipy.sparse.dok_matrix layouts, but extends beyond just rows and columns to an arbitrary number of dimensions. Additionally, this project maintains compatibility with the numpy.ndarray interface rather than the numpy.matrix interface used in scipy.sparse. These differences make this project useful in certain situations where scipy.sparse matrices are not well suited, but it should not be considered a full replacement. It lacks layouts that are not easily generalized like compressed sparse row/column(CSR/CSC) and depends on scipy.sparse for some computations.

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

This package implements a functionality to work with Nested sampling, a popular numerical method for Bayesian computation, which simultaneously generates samples from the posterior distribution and an estimate of the Bayesian evidence for a given likelihood and prior. nestcheck provides Python utilities for analysing samples produced by nested sampling, and estimating uncertainties on nested sampling calculations (which have different statistical properties to calculations using other numerical methods).

xarray-dataclass is a Python package that makes it easy to create xarray's DataArray and Dataset objects that are "typed" (i.e. fixed dimensions, data type, coordinates, attributes, and name) using the Python's dataclass. It's a successor of not maintained https://github.com/astropenguin/xarray-dataclasses.

xarray_einstats provides wrappers around some NumPy and SciPy functions and around einops with an API and features adapted to xarray.

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

This package provides a framework for building scientific applications. It aims to bring state of the art software design practices to scientific computing, with the goal of providing a strong skeleton on which to build scientific codes by steering the implementation towards usability and maintainability.

Snakemake aims to reduce the complexity of creating workflows by providing a clean and modern domain specific specification language (DSL) in Python style, together with a fast and comfortable execution environment.

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 contains colormaps for commonly-used oceanographic variables. Most of the colormaps started from matplotlib colormaps, but have now been adjusted using the viscm tool to be perceptually uniform.

This package implements a functionality to solve automatic numerical differentiation problems in one or more variables. Finite differences are used in an adaptive manner, coupled with a Richardson extrapolation methodology to provide a maximally accurate result. The user can configure many options like; changing the order of the method or the extrapolation, even allowing the user to specify whether complex-step, central, forward or backward differences are used.