This package provides functionality to make it easy to make scatter density maps, both for interactive and non-interactive use.

Marsilea is a Python library for creating composable visualizations in a declarative way. It is built on top of Matplotlib and provides a high-level API for you to puzzle different visualizations together like logo.

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.

Uproot is a Python library for reading and writing ROOT files. It uses NumPy and does not depend on C++ ROOT.

This is a Python implementation of the APTED algorithm,which supersedes the RTED algorithm for computing the tree edit distance.

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

This package provides a Python package for calculating tissue-specificity metrics for gene expression.

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.

Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts.

geosketch is a Python package that implements the geometric sketching algorithm described by Brian Hie, Hyunghoon Cho, Benjamin DeMeo, Bryan Bryson, and Bonnie Berger in "Geometric sketching compactly summarizes the single-cell transcriptomic landscape", Cell Systems (2019). This package provides an example implementation of the algorithm as well as scripts necessary for reproducing the experiments in the paper.

paramz is a lightweight parameterization framework for parameterized model creation and handling. Its features include:

• Easy model creation with parameters.

• Fast optimized access of parameters for optimization routines.

• Memory efficient storage of parameters (only one copy in memory).

• Renaming of parameters.

• Intuitive printing of models and parameters.

• Gradient saving directly inside parameters.

• Gradient checking of parameters.

• Optimization of parameters.

• Jupyter notebook integration.

• Efficient storage of models, for reloading.

• Efficient caching.

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.

Dask is a flexible parallel computing library for analytics. It consists of two components: dynamic task scheduling optimized for computation, and large data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers.

Particle provides a pythonic interface to the Particle Data Group (PDG) particle data tables and particle identification codes, with extended particle information and extra goodies.

pyvistaqt is a helper module for pyvista to enable you to plot using Qt by placing a vtk-widget into a background renderer. This can be quite useful when you desire to update your plot in real-time.

spin is a simple interface for common development tasks. It comes with a few common build commands out the box, but can easily be customized per project.

The impetus behind developing the tool was the mass migration of scientific Python libraries (SciPy, scikit-image, and NumPy, etc.) to Meson, after distutils was deprecated. When many of the build and installation commands changed, it made sense to abstract away the nuisance of having to re-learn them.

This package is an implementation of the Promises/A+ specification and test suite in Python.

Datatree is a prototype implementation of a tree-like hierarchical data structure for xarray. Datatree is in the process of being merged upstream into xarray.

This package provides utilities and tools for open data science including tools for accessing data sets in Python.

This package provides fast computations for principal component analysis (PCA), SVD, and eigendecompositions via randomized methods

Often when we want to label multiple points on a graph the text will start heavily overlapping with both other labels and data points. This can be a major problem requiring manual solution. However this can be largely automated by smart placing of the labels (difficult) or iterative adjustment of their positions to minimize overlaps (relatively easy). This library implements the latter option to help with matplotlib graphs.

PyVista is...

• Pythonic VTK: a high-level API to the Visualization Toolkit (VTK);

• mesh data structures and filtering methods for spatial datasets;

• 3D plotting made simple and built for large/complex data geometries.

This package provides a Pythonic, well-documented interface exposing VTK's powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets.

PyMCubes is an implementation of the marching cubes algorithm to extract iso-surfaces from volumetric data. The volumetric data can be given as a three-dimensional NumPy array or as a Python function f(x, y, z).