PyERFA is the Python wrapper for the ERFA library (Essential Routines for Fundamental Astronomy), a C library containing key algorithms for astronomy, which is based on the SOFA library published by the International Astronomical Union (IAU). All C routines are wrapped as Numpy universal functions, so that they can be called with scalar or array inputs.
When using matplotlib and plotting more than one line, it is common to want to be able to want to be able to cycle over one or more artist styles; but the plotting logic can quickly become involved. To address this and enable easy cycling over arbitrary kwargs, the Cycler class was developed.
Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.
pyHalo renders full mass distributions for substructure lensing simulations with gravitational lensing software package lenstronomy. The main purpose of the code is to quickly render full populations of dark matter subhalos and line of sight halos for gravitational lensing simulations. It also transltes halo properties (mass, concentration, redshift, etc) into angular units for lensing computations with lenstronomy.
This package provides a Python library for communicating with AMQP peers and brokers using the asynchronous networking framework Twisted. It contains all the necessary code to connect, send and receive messages to/from an AMQP-compliant peer or broker (Qpid, OpenAMQ, RabbitMQ) using Twisted. It also includes support for using Thrift RPC over AMQP in Twisted applications.
Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. The execution units, called tasks, are executed concurrently on a single or more worker servers using multiprocessing, Eventlet, or gevent. Tasks can execute asynchronously (in the background) or synchronously (wait until ready).
This package provides a pure Python QR Code generator module. It uses the Python Imaging Library (PIL) to allow for the generation of QR Codes.
In addition this package provides a command line tool to generate QR codes and either write these QR codes to a file or do the output as ascii art at the console.
Uniseg is a Python package used to determine Unicode text segmentations. Supported segmentations include:
Code point (any value in the Unicode codespace)
Grapheme cluster (user-perceived character made of a single or multiple Unicode code points, e.g. "G" + acute-accent)
Word break
Sentence break
Line break
This package provides the stestr command, a parallel Python test runner built around subunit. It is designed to execute unittest test suites using multiple processes to split up execution of a test suite. It will also store a history of all test runs to help in debugging failures and optimizing the scheduler to improve speed.
distro provides information about the OS distribution it runs on, such as a reliable machine-readable ID, or version information.
It is the recommended replacement for Python's original `platform.linux_distribution` function (which will be removed in Python 3.8). distro also provides a command-line interface to output the platform information in various formats.
ufo2ft (UFO to FontTools) is a fork of ufo2fdk intended to leverage FontTools (a Python library) rather than the Adobe Font Development Kit for OpenType (AFDKO), a set of C libraries/utilities so that it can be more easily extended. Like ufo2fdk, its primary purpose is to generate OpenType font binaries from Unified Font Objects (UFOs).
The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.
The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.
The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.
PLUMED is a library that provides a wide range of different methods, which include: enhanced-sampling algorithms, free-energy methods, tools to analyze the vast amounts of data produced by molecular dynamics (MD) simulations. These techniques can be used in combination with a large toolbox of collective variables that describe complex processes in physics, chemistry, material science, and biology.
This package provides tools to easily search and download French data from INSEE and IGN APIs. This data includes more than 150 000 macroeconomic series, a dozen datasets of local french data, numerous sources available on insee.fr, geographical limits of administrative areas taken from IGN as well as key metadata and SIRENE database containing data on all French compagnies.
Peewee is a simple and small ORM (object-relation mapping) tool. Peewee handles converting between pythonic values and those used by databases, so you can use Python types in your code without having to worry. It has built-in support for sqlite, mysql and postgresql. If you already have a database, you can autogenerate peewee models using pwiz, a model generator.
The goal of pygmsh is to combine the power of Gmsh with the versatility of Python. The package generalises many of the methods and functions that comprise the Gmsh Python API. In this way the meshing of complex geometries using high-level abstractions is made possible. The package provides a Python library together with a command-line utility for mesh optimisation.
SNData provides an access to data releases published by a variety of supernova (SN) surveys. It is designed to support the development of scalable analysis pipelines that translate with minimal effort between and across data sets. A summary of accessible data is provided below. Access to additional surveys is added upon request or as needed for individual research projects undertaken by the developers.
SPISEA is an python package that generates single-age, single-metallicity populations (i.e. star clusters). It gives the user control over many parameters:
cluster characteristics (age, metallicity, mass, distance)
total extinction, differential extinction, and extinction law
stellar evolution and atmosphere models
stellar multiplicity and Initial Mass Function
initial-Final Mass Relation
photometric filters
There are various file formats available for representing unstructured meshes and mesh data. The meshio package is able to read and write mesh files in many formats and to convert files from one format to another. Formats such as cgns, h5m, gmsh, xdmf and vtk are supported. The package provides command-line tools and a collection of Python modules for programmatic use.
OneTBB is a C++ runtime library that abstracts the low-level threading details necessary for optimal multi-core performance. It uses common C++ templates and coding style to eliminate tedious threading implementation work. It provides parallel loop constructs, asynchronous tasks, synchronization primitives, atomic operations, and more. python-onetbb enables threading composability between two or more thread-enabled Python libraries.
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.
Xarray (formerly xray) makes working with labelled multi-dimensional arrays simple, efficient, and fun!
Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.