This metapackage will install Python 3 packages for astronomy. The packages
can be used for interactive analysis, or to create specific programs.
Official Debian packages with high relevance
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ipython3
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7.20.0-1+deb11u1
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Enhanced interactive Python 3 shell
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ipython3:
Enhanced interactive Python 3 shell
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IPython can be used as a replacement for the standard Python shell,
or it can be used as a complete working environment for scientific
computing (like Matlab or Mathematica) when paired with the standard
Python scientific and numerical tools. It supports dynamic object
introspections, numbered input/output prompts, a macro system,
session logging, session restoring, complete system shell access,
verbose and colored traceback reports, auto-parentheses, auto-quoting,
and is embeddable in other Python programs.
This package contains the actual terminal shell for Python 3.
- Maintainer
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- 1786 regular users
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874 recent
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7450 total installations
(of 247490 submissions)
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python3
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3.5.3-1
↺
New upstream version
3.13.1
available
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interactive high-level object-oriented language (default python3 version)
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python3:
interactive high-level object-oriented language (default python3 version)
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Python, the high-level, interactive object oriented language,
includes an extensive class library with lots of goodies for
network programming, system administration, sounds and graphics.
This package is a dependency package, which depends on Debian's default
Python 3 version (currently v3.12).
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- Tags
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✏
- devel
- interpreter, lang:python, library
- role
- devel-lib, program, shared-lib
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- 170623 regular users
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25262 recent
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237644 total installations
(of 247490 submissions)
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python3-aplpy
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2.0.3-1
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Astronomical Plotting Library in Python
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python3-aplpy:
Astronomical Plotting Library in Python
- Description
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APLpy is a Python module aimed at producing publication-quality plots
of astronomical imaging data in FITS format. The module uses
Matplotlib, a powerful and interactive plotting package. It is capable
of creating output files in several graphical formats, including EPS,
PDF, PS, PNG, and SVG.
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- 14 regular users
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11 recent
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163 total installations
(of 247490 submissions)
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python3-asdf
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4.0.0-1
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Python 3 library for the Advanced Scientific Data Format
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python3-asdf:
Python 3 library for the Advanced Scientific Data Format
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ASDF (Advanced Scientific Data Format) is a proposed
next generation interchange format for scientific data. ASDF aims to
exist in the same middle ground that made FITS so successful, by
being a hybrid text and binary format: containing human editable
metadata for interchange, and raw binary data that is fast to load
and use. Unlike FITS, the metadata is highly structured and is
designed up-front for extensibility.
This is the Python 3 package.
- Reference
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- Maintainer
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- Versions
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- Popularity
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- 22 regular users
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26 recent
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207 total installations
(of 247490 submissions)
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python3-astlib
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0.12.0-1
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General Python3 tools for astronomy
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python3-astlib:
General Python3 tools for astronomy
- Description
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astLib is a set of Python3 modules that provides some tools for research
astronomers. It can be used for astronomical plots, some statistics, common
calculations, coordinate conversions, and manipulating FITS images with World
Coordinate System (WCS) information through PyWCSTools - a simple wrapping of
WCSTools by Jessica Mink. PyWCSTools is distributed (and developed) as part
of astLib.
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- Versions
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- Popularity
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- 91 regular users
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11 recent
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145 total installations
(of 247490 submissions)
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python3-astroalign
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2.6.1-1
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Astrometric registration of images when no WCS info is available
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python3-astroalign:
Astrometric registration of images when no WCS info is available
- Description
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Astroalign is a Python module that will try to align two stellar
astronomical images, especially when there is no WCS information
available.
It does so by finding similar 3-point asterisms (triangles) in both
images and deducing the affine transformation between them.
Generic registration routines try to match feature points, using
corner detection routines to make the point correspondence. These
generally fail for stellar astronomical images, since stars have very
little stable structure and so, in general, indistinguishable from
each other. Asterism matching is more robust, and closer to the human
way of matching stellar images.
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- Versions
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- Popularity
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- 4 regular users
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11 recent
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65 total installations
(of 247490 submissions)
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python3-astrodendro
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0.2.0+dfsg1-4
↺
New upstream version
0.3.1
available
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Astronomical Dendrograms in Python 3
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python3-astrodendro:
Astronomical Dendrograms in Python 3
- Description
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Python 3 module is to provide an easy way to compute dendrograms of observed or
simulated Astronomical data in Python 3.
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- Versions
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- Popularity
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- 12 regular users
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7 recent
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147 total installations
(of 247490 submissions)
- Debian
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python3-astroml
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1.0.2-5
↺
New upstream version
1.0.2.post1
available
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Python 3 Machine Learning library for astronomy
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python3-astroml:
Python 3 Machine Learning library for astronomy
- Description
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AstroML is a Python 3 module for machine learning and data mining built on
numpy, scipy, scikit-learn, and matplotlib. It contains a growing library of
statistical and machine learning routines for analyzing astronomical data in
Python, loaders for several open astronomical datasets, and a large suite of
examples of analyzing and visualizing astronomical datasets.
- Reference
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- Maintainer
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- Versions
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- Popularity
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- 27 regular users
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8 recent
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161 total installations
(of 247490 submissions)
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python3-astroplan
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0.10-1
↺
New upstream version
0.10.1
available
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Observation planning package for astronomers (Python 3)
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python3-astroplan:
Observation planning package for astronomers (Python 3)
- Description
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Astroplan is an observation planning package for astronomers that can help
you plan for everything but the clouds.
It is an Astropy affiliated package that seeks to make your life as an
observational astronomer a little less infuriating.
This is the Python 3 version of the package.
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- Versions
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- Popularity
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- 15 regular users
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9 recent
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169 total installations
(of 247490 submissions)
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python3-astropy
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7.0.0-1
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Core functionality for performing astrophysics with Python
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python3-astropy:
Core functionality for performing astrophysics with Python
- Description
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The astropy package contains core functionality and some common tools
needed for performing astronomy and astrophysics research with Python.
It can be extended by a number of "affiliated packages" that are
intended to work with the core package.
- Reference
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The Astropy Collaboration, A. M. Price-Whelan, B. M. Sipőcz, H. M. Günther, P. L. Lim, S. M. Crawford, S. Conseil, D. L. Shupe, M. W. Craig, N. Dencheva, A. Ginsburg, J. T. VanderPlas, L. D. Bradley, D. Pérez-Suárez, M. de Val-Borro, T. L. Aldcroft, K. L. Cruz, T. P. Robitaille, E. J. Tollerud, C. Ardelean, T. Babej, Y. P. Bach, M. Bachetti, A. V. Bakanov, S. P. Bamford, G. Barentsen, P. Barmby, A. Baumbach, K. L. Berry, F. Biscani, M. Boquien, K. A. Bostroem, L. G. Bouma, G. B. Brammer, E. M. Bray, H. Breytenbach, H. Buddelmeijer, D. J. Burke, G. Calderone, J. L. Cano Rodríguez, M. Cara, J. V. M. Cardoso, S. Cheedella, Y. Copin, L. Corrales, D. Crichton, D. D’Avella, C. Deil, É. Depagne, J. P. Dietrich, A. Donath, M. Droettboom, N. Earl, T. Erben, S. Fabbro, L. A. Ferreira, T. Finethy, R. T. Fox, L. H. Garrison, S. L. J. Gibbons, D. A. Goldstein, R. Gommers, J. P. Greco, P. Greenfield, A. M. Groener, F. Grollier, A. Hagen, P. Hirst, D. Homeier, A. J. Horton, G. Hosseinzadeh, L. Hu, J. S. Hunkeler, Ž. Ivezić, A. Jain, T. Jenness, G. Kanarek, S. Kendrew, N. S. Kern, W. E. Kerzendorf, A. Khvalko, J. King, D. Kirkby, A. M. Kulkarni, A. Kumar, A. Lee, D. Lenz, S. P. Littlefair, Z. Ma, D. M. Macleod, M. Mastropietro, C. McCully, S. Montagnac, B. M. Morris, M. Mueller, S. J. Mumford, D. Muna, N. A. Murphy, S. Nelson, G. H. Nguyen, J. P. Ninan, M. Nöthe, S. Ogaz, S. Oh, J. K. Parejko, N. Parley, S. Pascual, R. Patil, A. A. Patil, A. L. Plunkett, J. X. Prochaska, T. Rastogi, V. Reddy Janga, J. Sabater, P. Sakurikar, M. Seifert, L. E. Sherbert, H. Sherwood-Taylor, A. Y. Shih, J. Sick, M. T. Silbiger, S. Singanamalla, L. P. Singer, P. H. Sladen, K. A. Sooley, S. Sornarajah, O. Streicher, P. Teuben, S. W. Thomas, G. R. Tremblay, J. E. H. Turner, V. Terrón, M. H. van Kerkwijk, A. de la Vega, L. L. Watkins, B. A. Weaver, J. B. Whitmore, J. Woillez and V. Zabalza:
The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package.
The Astronomical Journal
156(3):123
(2018)
(eprint)
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- 298 regular users
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178 recent
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1368 total installations
(of 247490 submissions)
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python3-astropy-affiliated
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2.1
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Collection of all astropy affiliated packages
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python3-astropy-affiliated:
Collection of all astropy affiliated packages
- Description
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A major part of the Astropy project is the concept of “Affiliated
Packages”. An affiliated package is an astronomy-related Python
package that is not part of the astropy core package, but has
requested to be included as part of the Astropy project’s
community. These packages are expressing an interest in Astropy’s
goals of improving reuse, interoperability, and interface standards
for Python astronomy and astrophysics packages.
This metapackage installs all affiliated packages.
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115 total installations
(of 247490 submissions)
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python3-astropy-coordinated
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2.1
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Collection of all astropy coordinated packages
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python3-astropy-coordinated:
Collection of all astropy coordinated packages
- Description
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Coordinated packages are Astropy enhancing packages that are
maintained by the Astropy Project as a whole. In practice this means
the Astropy coordination committee has administrative control of a
coordinated package repository (delegated to the maintainers), and
that maintainers of these packages have formal roles in the Astropy
Project. In some cases these are packages identified by the core team
as needing development separate from the core (either they are
experimental or problem space-focused), while others started as
affiliated packages but have become so important to the ecosystem
that they grew to become coordinated.
This metapackage installs all coordinated packages.
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- Popularity
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66 total installations
(of 247490 submissions)
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python3-astropy-healpix
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0.6-2
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HEALPix representation of spherical data - Python 3
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python3-astropy-healpix:
HEALPix representation of spherical data - Python 3
- Description
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HEALPix is an acronym for Hierarchical Equal Area isoLatitude Pixelization
of a sphere. As suggested in the name, this pixelization produces a
subdivision of a spherical surface in which each pixel covers the same
surface area as every other pixel. It is commonly used to store all-sky
astronomical images, most famously maps of the cosmic microwave background.
This is a BSD-licensed HEALPix package developed by the Astropy project
and based on C code written by Dustin Lang in astrometry.net.
This package provides modules for Python 3.
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- Popularity
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- 14 regular users
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16 recent
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179 total installations
(of 247490 submissions)
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python3-astroquery
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0.4.7+dfsg-2
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Python online astronomical database querying (Python 3)
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python3-astroquery:
Python online astronomical database querying (Python 3)
- Description
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Astroquery is a set of Python tools for querying astronomical web forms and
databases.
This is the Python 3 version of the package.
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- Versions
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- Popularity
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- 23 regular users
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13 recent
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175 total installations
(of 247490 submissions)
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python3-astroscrappy
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1.0.5-1
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Optimized Cosmic Ray Annihilation in Python
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python3-astroscrappy:
Optimized Cosmic Ray Annihilation in Python
- Description
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Astro-SCRAPPY is designed to detect cosmic rays in images (numpy arrays),
based on Pieter van Dokkum's L.A.Cosmic algorithm. Parallelization is
achieved using OpenMP.
- Reference
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- Maintainer
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- Versions
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- Popularity
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- 13 regular users
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13 recent
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172 total installations
(of 247490 submissions)
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python3-bdsf
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1.9.2-3
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Python Blob Detection and Source Finder
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python3-bdsf:
Python Blob Detection and Source Finder
- Description
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PyBDSF (the Python Blob Detection and Source Finder) is a tool
designed to decompose radio interferometry images into sources and
make available their properties for further use. PyBDSF can decompose
an image into a set of Gaussians, shapelets, or wavelets as well as
calculate spectral indices and polarization properties of sources and
measure the psf variation across an image. PyBDSF uses an interactive
environment based on CASA that will be familiar to most radio
astronomers. Additionally, PyBDSF may also be used in Python
scripts.
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- Popularity
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2 recent
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17 total installations
(of 247490 submissions)
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python3-casacore
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2.1.2-3
↺
New upstream version
3.6.1
available
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Python bindings to the casacore library
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python3-casacore:
Python bindings to the casacore library
- Description
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The casacore package contains the core libraries of the old AIPS++/CASA
package. This split was made to get a better separation of core
libraries and applications. CASA is now built on top of casacore.
This is the Python wrapper around the library.
- Maintainer
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- Versions
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- Popularity
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- 54 regular users
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10 recent
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227 total installations
(of 247490 submissions)
- Debian
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python3-ccdproc
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2.4.2-1
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Basic data reductions of astronomy CCD images
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python3-ccdproc:
Basic data reductions of astronomy CCD images
- Description
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The ccdproc package provides many of the necessary tools for processing
of ccd images built on a framework to provide error propagation and bad
pixel tracking throughout the reduction process.
- Maintainer
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- Versions
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- Popularity
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- 14 regular users
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7 recent
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165 total installations
(of 247490 submissions)
- Debian
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python3-cpl
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0.7.4-4
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Control pipeline recipes from the ESO (Python3)
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python3-cpl:
Control pipeline recipes from the ESO (Python3)
- Description
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This module can list, configure and execute CPL-based recipes from Python3.
The input, calibration and output data can be specified as FITS files
or as astropy fits objects in memory.
The Common Pipeline Library (CPL) comprises a set of ISO-C libraries that
provide a comprehensive, efficient and robust software toolkit. It forms a
basis for the creation of automated astronomical data-reduction tasks.
One of the features provided by the CPL is the ability to create
data-reduction algorithms that run as plugins (dynamic libraries). These are
called "recipes" and are one of the main aspects of the CPL data-reduction
development environment.
- Reference
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- Maintainer
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- Versions
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- Popularity
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- 12 regular users
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12 recent
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154 total installations
(of 247490 submissions)
- Debian
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python3-cvxopt
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1.1.9+dfsg-3
↺
New upstream version
1.3.2
available
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Python3 package for convex optimization
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python3-cvxopt:
Python3 package for convex optimization
- Description
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CVXOPT is a Python package for convex optimization. It includes
- Python classes for storing and manipulating dense and sparse matrices
- an interface to most of the double-precision real and complex BLAS
- an interface to the dense linear equation solvers and eigenvalue
routines from LAPACK
- interfaces to the sparse LU and Cholesky solvers from UMFPACK and
CHOLMOD.
- routines for solving convex optimization problems, an interface to
the linear programming solver in GLPK, and interfaces to the
linear and quadratic programming solvers in MOSEK
- a modeling tool for specifying convex piecewise-linear
optimization problems.
This package contains the Python 3 module.
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- Versions
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- Popularity
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- 78 regular users
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100 recent
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802 total installations
(of 247490 submissions)
- Debian
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python3-dask
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1.0.0+dfsg-2
↺
New upstream version
2024.12.0
available
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Minimal task scheduling abstraction for Python 3
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python3-dask:
Minimal task scheduling abstraction for Python 3
- Description
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Dask is a flexible parallel computing library for analytics,
containing two components.
- Dynamic task scheduling optimized for computation. This is similar
to Airflow, Luigi, Celery, or Make, but optimized for interactive
computational workloads.
- "Big 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.
This contains the Python 3 version.
- Maintainer
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- Versions
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- Popularity
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- 182 regular users
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136 recent
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1272 total installations
(of 247490 submissions)
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python3-drizzle
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1.12-2
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Dithered image combination for Python
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python3-drizzle:
Dithered image combination for Python
- Description
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The drizzle library is a Python package for combining dithered images
into a single image. This library is derived from code used in
drizzlepac. Like drizzlepac, most of the code is implemented in the C
language. The biggest change from drizzlepac is that this code passes
an array that maps the input to output image into the C code, while
the drizzlepac code computes the mapping by using a Python
callback. Switching to using an array allowed the code to be greatly
simplified.
- Reference
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- Maintainer
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- Versions
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- Popularity
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- 11 regular users
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13 recent
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139 total installations
(of 247490 submissions)
- Debian
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python3-drms
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0.8.0-1
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Access HMI, AIA and MDI data with Python
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python3-drms:
Access HMI, AIA and MDI data with Python
- Description
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The drms module provides an easy-to-use Python interface for
accessing HMI, AIA and MDI data with Python. It uses the publicly
accessible Joint Science Operations Center (JSOC) server by default,
but can also be used with local NetDRMS sites.
The Helioseismic and Magnetic Imager (HMI) and the Atmospheric
Imaging Assembly (AIA) are instruments aboard the Solar Dynamics
Observatory (SDO) designed to study oscillations and the magnetic
field at the solar surface. The Michelson Doppler Imager (MDI) is the
predecessor to the current HMI and was launched aboard the Solar and
Heliospheric Observatory (SOHO). HMI and MDI observe the full solar
disk at 6173 Å with high resolution, while AIA is designed to study
the solar corona.
- Maintainer
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- Versions
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- Popularity
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- 16 regular users
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7 recent
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147 total installations
(of 247490 submissions)
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python3-einsteinpy
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0.4.0-3
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General Relativity in Python
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python3-einsteinpy:
General Relativity in Python
- Description
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EinsteinPy is an open source pure Python package
dedicated to problems arising in General Relativity
and relativistic physics, such as goedesics plotting
for schwarzschild space-time model, calculation of
schwarzschild radius for any mass given, symbolic
calculation of various functions related to GR such
as christoffel symbols. Features like visualization
of geodesics of curved black holes and 3D visualizations
are some of the features which are planned.
It is released under the MIT license.
- Maintainer
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- Versions
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- Popularity
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- 8 regular users
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7 recent
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101 total installations
(of 247490 submissions)
- Debian
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python3-emcee
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2.2.1-1
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Affine-invariant ensemble MCMC sampling for Python 3
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python3-emcee:
Affine-invariant ensemble MCMC sampling for Python 3
- Description
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emcee is an extensible, pure-Python implementation of Goodman &
Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble
sampler. It's designed for Bayesian parameter estimation.
- Reference
-
-
D. Foreman-Mackey, D.W. Hogg, D. Lang and J. Goodman:
emcee: The MCMC Hammer.
Publications of the Astronomical Society of the Pacific
125:306-312
(2013)
(eprint)
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- Popularity
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- 19 regular users
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8 recent
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152 total installations
(of 247490 submissions)
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python3-ephem
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3.7.6.0-6
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Compute positions of the planets and stars with Python
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python3-ephem:
Compute positions of the planets and stars with Python
- Description
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PyEphem provides an ephem Python package for performing high-precision
astronomy computations. The underlying numeric routines are coded in C and
are the same ones that drive the popular XEphem astronomy application, whose
author, Elwood Charles Downey, generously gave permission for their use in
PyEphem.
The name ephem is short for the word ephemeris, which is the
traditional term for a table giving the position of a planet, asteroid, or
comet for a series of dates.
Nothe that this package will continue to be maintained, but it no
longer stands at the cutting edge of astronomy in Python.
- Maintainer
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- Versions
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- Popularity
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- 301 regular users
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113 recent
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763 total installations
(of 247490 submissions)
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python3-extinction
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0.4.6-3
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Fast interstellar dust extinction laws (Python 3)
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python3-extinction:
Fast interstellar dust extinction laws (Python 3)
- Description
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Extinction contains Cython-optimised implementations of empirical dust
extinction laws found in the astronomical literature.
- Maintainer
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- Versions
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- Popularity
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- 4 regular users
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15 recent
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71 total installations
(of 247490 submissions)
- Debian
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python3-fast-histogram
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0.14-2
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Fast 1D and 2D histogram functions in Python
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python3-fast-histogram:
Fast 1D and 2D histogram functions in Python
- Description
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fast-histogram aims to provide simple and fast histogram functions for
regular bins that don't compromise on performance. It doesn't do
anything complicated - it just implements a simple histogram algorithm in C and
keeps it simple. The aim is to have functions that are fast but also robust and
reliable. The result is a 1D histogram function here that is 7-15x faster than
numpy.histogram, and a 2D histogram function that is 20-25x faster than
numpy.histogram2d.
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python3-fitsio
|
1.2.4+dfsg-1
|
Python 3 library to read from and write to FITS files
|
python3-fitsio:
Python 3 library to read from and write to FITS files
- Description
-
Fitsio provides an easy to use object-oriented API including
providing a Numpy interface to FITS files read from CFITSIO. It
allows direct access to the columns of a FITS binary table which can
be useful for reading large fits files. Compared to astropy.io.fits,
this package is closer to the underlying cfitsio library.
Fitsio also exposes a microlanguage (implemented in CFITSIO) for
making efficient SQL-like queries of tables (single tables only
though–no joins or anything like that).
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- 14 regular users
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14 recent
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python3-galpy
|
1.2-1
↺
New upstream version
1.10.1
available
|
Python 3 package for Galactic Dynamics
|
python3-galpy:
Python 3 package for Galactic Dynamics
- Description
-
Python 3 module that supports orbit integration in a variety of potentials,
evaluating and sampling various distribution functions, and the calculation of
action-angle coordinates for all static potentials.
- Maintainer
-
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- Popularity
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- 14 regular users
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7 recent
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154 total installations
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python3-gammapy
|
1.3-1
|
Python package for gamma-ray astronomy
|
python3-gammapy:
Python package for gamma-ray astronomy
- Description
-
Gammapy is an in-development affiliated package of Astropy
that builds on the core scientific Python stack to provide
tools to simulate and analyse the gamma-ray sky for telescopes
such as CTA, H.E.S.S., VERITAS, MAGIC, HAWC and Fermi-LAT.
- Reference
-
-
C. Deil, R. Zanin, J. Lefaucheur, C. Boisson, B. Khélifi, R. Terrier, M. Wood, L. Mohrmann, N. Chakraborty, J. Watson, R. López Coto, S. Klepser, M. Cerruti, J.-P. Lenain, F. Acero, A. Djannati-Ataï, S. Pita, Z. Bosnjak, J. E. Ruiz, C. Trichard, T. Vuillaume, A. Donath, J. King, L. Jouvin, E. Owen, M. P. Arribas, B. Sipocz, D. Lennarz, A. Voruganti and M. Spir-Jacob:
Gammapy - A prototype for the CTA science tools.
ArXiv e-prints
(2017)
(eprint)
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3 recent
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python3-gdl
|
1.1-1
|
Python interface for the GNU Data Language
|
python3-gdl:
Python interface for the GNU Data Language
- Description
-
GNU Data Language (GDL) is a free IDL (Interactive Data Language)
compatible incremental compiler. It has full syntax compatibility
with IDL 7.1. IDL is a registered trademark of ITT Visual Information
Solutions. From IDL 8.0, the following language elements are
supported:
- FOREACH loop
- negative array indices
- garbage collection pointers and objects
- call methods on an object using "." (e. g.
object.aMemberProcedure,arg1 )
The file input output system is fully implemented. GUI support (widgets) is
officially provided, but it's not complete yet.
This package contains the Python library/interface.
- Reference
-
-
A. Coulais, M. Schellens, J. Gales, S. Arabas, M. Boquien, P. Chanial, P. Messmer, D. Fillmore, O. Poplawski, S. Maret, G. Marchal, N. Galmiche and T. Mermet:
Status of GDL - GNU Data Language.
Astronomical Data Analysis Software and Systems XIX
434:187
(2010)
(eprint)
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8 recent
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python3-ginga
|
4.0.1-1
|
Astronomical image toolkit for Python
|
python3-ginga:
Astronomical image toolkit for Python
-
-
Ginga is a toolkit designed for building viewers for scientific image
data in Python, visualizing 2D pixel data in numpy arrays.
It can view astronomical data such as contained in files based on the
FITS (Flexible Image Transport System) file format. It is written and
is maintained by software engineers at the Subaru Telescope, National
Astronomical Observatory of Japan.
The Ginga toolkit centers around an image display object which supports
zooming and panning, color and intensity mapping, a choice of several
automatic cut levels algorithms and canvases for plotting scalable
geometric forms. In addition to this widget, a general purpose
"reference" FITS viewer is provided, based on a plugin framework.
A fairly complete set of standard plugins are provided for features
that is expected from a modern FITS viewer: panning and zooming windows,
star catalog access, cuts, star pick/fwhm, thumbnails, etc.
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- 17 regular users
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python3-glue
|
1.0.1+dfsg-1
↺
New upstream version
1.18.0
available
|
Python 3 library for data interaction
|
python3-glue:
Python 3 library for data interaction
- Description
-
python3-glue is a Python library for data interaction, it blurs the boundary
between GUI-centric and code-centric data exploration.
There are many ways to leverage Glue from Python. Among other things, you can
write code to do the following:
- Send data in the form of NumPy arrays or Pandas DataFrames to Glue for
exploration.
- Write startup scripts that automatically load and clean data,
before starting Glue.
- Write custom functions to parse files, and plug these functions into the
Glue GUI.
- Write custom functions to link datasets, and plug these into the Glue GUI.
- Create your own visualization modules.
- Reference
-
- Maintainer
-
- Versions
-
- Popularity
-
- 13 regular users
-
7 recent
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174 total installations
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python3-gwcs
|
0.18.3-1
|
Tools for managing the WCS of astronomical data (Python 3)
|
python3-gwcs:
Tools for managing the WCS of astronomical data (Python 3)
- Description
-
GWCS takes a general approach to WCS. It supports a data model which includes
the entire transformation pipeline from input coordinates (detector by
default) to world coordinates. The goal is to provide a flexible toolkit
which is easily extendible by adding new transforms and frames.
This package contains the Python 3 version of the package.
- Maintainer
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- 13 regular users
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20 recent
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171 total installations
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python3-gyoto
|
1.4.4-3
|
General relativistic geodesic integration for the Python 3 language
|
python3-gyoto:
General relativistic geodesic integration for the Python 3 language
- Description
-
Gyoto aims at providing a framework for computing orbits and
ray-traced images in General relativity.
This package also includes a Gyoto plug-in allowing to write new
Gyoto objects in the Python 3 language.
This package provides an extension for the Python 3 programming language
exposing the Gyoto facilities. It allows using Gyoto interactively
from the Python 3 prompt or running complex Gyoto scripts.
Producing videos requires the python3-opencv package.
- Reference
-
- Maintainer
-
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-
- Popularity
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- 7 regular users
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10 recent
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126 total installations
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python3-healpy
|
1.16.6-2
↺
New upstream version
1.18.0
available
|
HEALPix representation of spherical data - Python3 interface
|
python3-healpy:
HEALPix representation of spherical data - Python3 interface
- Description
-
HEALPix is an acronym for Hierarchical Equal Area isoLatitude Pixelization
of a sphere. As suggested in the name, this pixelization produces a
subdivision of a spherical surface in which each pixel covers the same
surface area as every other pixel. It is commonly used to store all-sky
astronomical images, most famously maps of the cosmic microwave background.
This package provides a Python3 wrapper around the C++ implementation of
HEALPix.
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- 15 regular users
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177 total installations
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python3-hips
|
0.2-3
|
Python package for Hierarchical Progressive Surveys
|
python3-hips:
Python package for Hierarchical Progressive Surveys
- Description
-
HiPS (Hierarchical Progressive Surveys) is a way to store large
astronomical survey sky image and catalog datasets on servers (such
as HiPS at CDS), that allows clients to efficiently fetch only the
image tiles or catalog parts for a given region of the sky they are
interested in. Similar to Google maps, but for astronomy (see the
HiPS paper).
This is a Python package to fetch and draw HiPS images.
- Maintainer
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- 6 regular users
-
6 recent
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76 total installations
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python3-imexam
|
0.9.1-1
|
Simple interactive astronomical image examination and plotting
|
python3-imexam:
Simple interactive astronomical image examination and plotting
- Description
-
Imexam is an affiliated package of AstroPy. It was designed to be a
lightweight library which enables users to explore data using common
methods which are consistent across viewers. It can be used from a
command line interface, through a Jupyter notebook or through a
Jupyter console. It can be used with multiple viewers, such as DS9 or
Ginga, or without a viewer as a simple library to make plots and grab
quick photometry information.
- Maintainer
-
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-
- Popularity
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- 9 regular users
-
7 recent
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116 total installations
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python3-keras
|
2.2.4-1
|
deep learning framework running on Theano or TensorFlow
|
python3-keras:
deep learning framework running on Theano or TensorFlow
- Description
-
Keras is a Python library for machine learning based on deep (multi-
layered) artificial neural networks (DNN), which follows a minimalistic
and modular design with a focus on fast experimentation.
Features of DNNs like neural layers, cost functions, optimizers,
initialization schemes, activation functions and regularization schemes
are available in Keras a standalone modules which can be plugged together
as wanted to create sequence models or more complex architectures.
Keras supports convolutions neural networks (CNN, used for image
recognition resp. classification) and recurrent neural networks (RNN,
suitable for sequence analysis like in natural language processing).
It runs as an abstraction layer on the top of Theano (math expression
compiler) by default, which makes it possible to accelerate the computations
by using (GP)GPU devices. Alternatively, Keras could run on Google's
TensorFlow (not yet available in Debian).
- Maintainer
-
- Versions
-
- Popularity
-
- 8 regular users
-
2 recent
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121 total installations
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python3-lmfit
|
0.8.0+dfsg.1-1
↺
New upstream version
1.3.2
available
|
Least-Squares Minimization with Constraints (Python 3)
|
python3-lmfit:
Least-Squares Minimization with Constraints (Python 3)
- Description
-
The lmfit Python package provides a simple, flexible interface to
non-linear optimization or curve fitting problems. The package
extends the optimization capabilities of scipy.optimize by replacing
floating pointing values for the variables to be optimized with
Parameter objects. These Parameters can be fixed or varied, have
upper and/or lower bounds placed on its value, or written as an
algebraic expression of other Parameters.
The principal advantage of using Parameters instead of simple
variables is that the objective function does not have to be
rewritten to reflect every change of what is varied in the fit, or
what relationships or constraints are placed on the Parameters. This
means a scientific programmer can write a general model that
encapsulates the phenomenon to be optimized, and then allow user of
that model to change what is varied and fixed, what range of values
is acceptable for Parameters, and what constraints are placed on the
model. The ease with which the model can be changed also allows one
to easily test the significance of certain Parameters in a fitting
model.
The lmfit package allows a choice of several optimization methods
available from scipy.optimize. The default, and by far best tested
optimization method used is the Levenberg-Marquardt algorithm from
MINPACK-1 as implemented in scipy.optimize.leastsq. This method
is by far the most tested and best support method in lmfit, and much
of this document assumes this algorithm is used unless explicitly
stated. An important point for many scientific analysis is that this
is only method that automatically estimates uncertainties and
correlations between fitted variables from the covariance matrix
calculated during the fit.
A few other optimization routines are also supported, including
Nelder-Mead simplex downhill, Powell's method, COBYLA, Sequential
Least Squares methods as implemented in scipy.optimize.fmin, and
several others from scipy.optimize. In their native form, some of
these methods setting allow upper or lower bounds on parameter
variables, or adding constraints on fitted variables. By using
Parameter objects, lmfit allows bounds and constraints for all of
these methods, and makes it easy to swap between methods without
hanging the objective function or set of Parameters.
Finally, because the approach derived from MINPACK-1 usin the
covariance matrix to determine uncertainties is sometimes questioned
(and sometimes rightly so), lmfit supports methods to do a brute
force search of the confidence intervals and correlations for sets of
parameters.
This is the Python 3 version of the package.
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- 33 regular users
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22 recent
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290 total installations
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python3-matplotlib
|
3.8.3-3
↺
New upstream version
3.10.0~rc1
available
|
Python based plotting system in a style similar to Matlab
|
python3-matplotlib:
Python based plotting system in a style similar to Matlab
- Description
-
Matplotlib is a pure Python plotting library designed to bring
publication quality plotting to Python with a syntax familiar to
Matlab users. All of the plotting commands in the pylab interface can
be accessed either via a functional interface familiar to Matlab
users or an object oriented interface familiar to Python users.
- Maintainer
-
- Versions
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- Popularity
-
- 19261 regular users
-
2320 recent
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24729 total installations
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python3-montage-wrapper
|
0.9.9-4
|
Python-3 wrapper for the Montage mosaicking toolkit
|
python3-montage-wrapper:
Python-3 wrapper for the Montage mosaicking toolkit
- Description
-
This package provides a Python-3 wrapper to the Montage Astronomical Image
Mosaic Engine, including both functions to access individual Montage
commands, and high-level functions to facilitate mosaicking and
re-projecting.
- Maintainer
-
- Versions
-
- Popularity
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- 3 regular users
-
6 recent
-
60 total installations
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python3-montagepy
|
6.0+dfsg-7
↺
New upstream version
6.1
available
|
Python toolkit for assembling FITS images into mosaics
|
python3-montagepy:
Python toolkit for assembling FITS images into mosaics
- Description
-
MontagePy is a toolkit for assembling astronomical images into custom mosaics.
It uses algorithms that preserve the calibration and positional (astrometric)
fidelity of the input images to deliver mosaics that meet user-specified
parameters of projection, coordinates, and spatial scale. It supports all
projections and coordinate systems in use in astronomy.
It contains independent modules for analyzing the geometry of images on the
sky, and for creating and managing mosaics; these modules are powerful tools
in their own right and have applicability outside mosaic production, in areas
such as data validation.
- Reference
-
- Maintainer
-
- Versions
-
- Popularity
-
- 6 regular users
-
12 recent
-
88 total installations
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python3-mpl-scatter-density
|
0.7-1
|
Fast scatter density plots for Matplotlib
|
python3-mpl-scatter-density:
Fast scatter density plots for Matplotlib
- Description
-
This package provides functionality to
make it easy to make your own scatter density maps, both for interactive
and non-interactive use. Fast.
This package installs the library for Python 3.
- Maintainer
-
- Versions
-
- Popularity
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- 15 regular users
-
7 recent
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198 total installations
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python3-ndcube
|
1.1.1-1
|
Package for multi-dimensional coordinate-aware arrays (Python 3)
|
python3-ndcube:
Package for multi-dimensional coordinate-aware arrays (Python 3)
- Description
-
ndcube is a SunPy affiliated package for manipulating, inspecting and
visualizing multi-dimensional contiguous and non-contiguous coordinate-aware
data arrays. It combines data, uncertainties, units, metadata, masking, and
coordinate transformations into classes with unified slicing and generic
coordinate transformations and plotting/animation capabilities. It is
designed to handle data of any number of dimensions and axis types (e.g.
spatial, temporal, spectral, etc.) whose relationship between the array
elements and the real world can be described by World Coordinate System (WCS)
translations.
This is the Python 3 version of the package.
- Maintainer
-
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- Popularity
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- 12 regular users
-
14 recent
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154 total installations
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python3-numpy
|
1.19.5-1
↺
New upstream version
2.1.3
available
|
Fast array facility to the Python language (Python 3)
|
python3-numpy:
Fast array facility to the Python language (Python 3)
- Description
-
NumPy contains a powerful N-dimensional array object, sophisticated
(broadcasting) functions, tools for integrating C/C++ and Fortran
code, and useful linear algebra, Fourier transform, and random number
capabilities.
This package installs NumPy for Python 3.
- Maintainer
-
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- Popularity
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- 25986 regular users
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4765 recent
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46476 total installations
(of 247490 submissions)
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python3-orbit-predictor
|
1.15.0-2
|
Python library to propagate satellite orbits
|
python3-orbit-predictor:
Python library to propagate satellite orbits
- Description
-
Orbit Predictor is a Python library to propagate orbits of
Earth-orbiting objects such as satellites or ISS working on top of SGP4
- Maintainer
-
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- 6 regular users
-
7 recent
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81 total installations
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python3-pandas
|
2.2.3+dfsg-5
|
data structures for "relational" or "labeled" data
|
python3-pandas:
data structures for "relational" or "labeled" data
- Description
-
pandas is a Python package providing fast, flexible, and expressive
data structures designed to make working with "relational" or
"labeled" data both easy and intuitive. It aims to be the fundamental
high-level building block for doing practical, real world data
analysis in Python. pandas is well suited for many different kinds of
data:
- Tabular data with heterogeneously-typed columns, as in an SQL
table or Excel spreadsheet
- Ordered and unordered (not necessarily fixed-frequency) time
series data.
- Arbitrary matrix data (homogeneously typed or heterogeneous) with
row and column labels
- Any other form of observational / statistical data sets. The data
actually need not be labeled at all to be placed into a pandas
data structure
This package contains the Python 3 version.
- Reference
-
-
McKinney, Wes:
pandas: a Foundational Python Library for Data Analysis and Statistics.
(2011)
(eprint)
- Maintainer
-
- Versions
-
- Popularity
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- 584 regular users
-
460 recent
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5479 total installations
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python3-photutils
|
1.6.0-1
|
Astropy affiliated package for image photometry (Python 3)
|
python3-photutils:
Astropy affiliated package for image photometry (Python 3)
- Description
-
Photutils contains functions for:
- estimating the background and background rms in astronomical images
- detecting sources in astronomical images
- estimating morphological parameters of those sources (e.g., centroid
and shape parameters)
- performing aperture and PSF photometry
This package contains the Python 3 version of the package.
- Maintainer
-
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-
- Popularity
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- 13 regular users
-
18 recent
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182 total installations
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python3-poliastro
|
0.14.0-5
|
??? missing short description for package python3-poliastro :-(
|
python3-poliastro:
??? missing short description for package python3-poliastro :-(
- Maintainer
-
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- 18 regular users
-
7 recent
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99 total installations
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python3-pyavm
|
0.9.4-7
|
Python3 module to handle Astronomy Visualization Metadata Standard
|
python3-pyavm:
Python3 module to handle Astronomy Visualization Metadata Standard
- Description
-
PyAVM is a module to represent, read, and write metadata following the
Astronomy Visualization Metadata (AVM) standard.
With pyavm you can:
- Parse AVM meta-data from an existing image.
- Access and Set the metadata.
- Create an AVM object from scratch.
- Convert to a WCS object.
- Initialize from a FITS header.
- Initialize from a WCS object.
This is the Python 3 Version of the package.
- Maintainer
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- Popularity
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- 15 regular users
-
11 recent
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193 total installations
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python3-pydl
|
1.0.1-1
|
Library of IDL astronomy routines converted to Python 3
|
python3-pydl:
Library of IDL astronomy routines converted to Python 3
- Description
-
PyDL consists of Python replacements for functions that are part of the IDL
built-in library or part of astronomical IDL libraries.
The emphasis is on reproducing results of the astronomical library
functions.
Only the bare minimum of IDL built-in functions are implemented to support
this.
There are four astronomical libraries targeted:
- idlutils: a general suite of tools heavily used by SDSS.
-
Goddard utilities: The IDL Astronomy User's Library, maintained by
Wayne Landsman and distributed with idlutils.
-
idlspec2d: tools for working with SDSS, BOSS and eBOSS spectroscopic
data.
-
photoop: tools for working with SDSS imaging data.
This is the Python 3 version of the package.
- Maintainer
-
- Versions
-
- Popularity
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- 12 regular users
-
11 recent
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161 total installations
(of 247490 submissions)
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python3-pyds9
|
1.8.1-5
|
Communication with the ds9 image display program from Python
|
python3-pyds9:
Communication with the ds9 image display program from Python
- Description
-
The XPA messaging system provides seamless communication between many kinds
of Unix programs, including Tcl/Tk programs such as ds9. The pyds9 module
uses a Python interface to XPA to communicate with ds9. It supports
communication with all of ds9’s XPA access points.
- Maintainer
-
- Versions
-
- Popularity
-
- 94 regular users
-
6 recent
-
152 total installations
(of 247490 submissions)
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python3-pyfftw
|
0.13.1-2
↺
New upstream version
0.15.0
available
|
Pythonic wrapper around FFTW - Python 3
|
python3-pyfftw:
Pythonic wrapper around FFTW - Python 3
- Description
-
Pythonic wrapper around FFTW, the speedy FFT library. The ultimate
aim is to present a unified interface for all the possible transforms
that FFTW can perform.
Both the complex DFT and the real DFT are supported, as well as
arbitrary axes of abitrary shaped and strided arrays, which makes it
almost feature equivalent to standard and real FFT functions of
numpy.fft (indeed, it supports the clongdouble dtype which numpy.fft
does not).
pyFFTW is BSD-licensed and should not be confused with python-fftw, a
GPL-licensed python module with the same aim of providing python
bindings to FFTW3. Or python3-gpyfft, which provides bindings to the
OpenCL FFT library clFFT.
This package provides the Python 3 bindings.
- Maintainer
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- 19 regular users
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15 recent
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174 total installations
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python3-pygnuplot
|
0.11.16-4
↺
New upstream version
0.12.3
available
|
Simple Python wrapper for Gnuplot
|
python3-pygnuplot:
Simple Python wrapper for Gnuplot
- Description
-
PyGnuplot works as a Python pipe for Gnuplot allowing to pipe commands
to Gnuplot command prompt, plot, save data files, create postscript and PDF
files
This package installs the library for Python 3.
- Maintainer
-
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- Popularity
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- 5 regular users
-
9 recent
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122 total installations
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python3-pymoc
|
0.5.2-2
|
Python Multi-Order Coverage maps for Virtual Observatory
|
python3-pymoc:
Python Multi-Order Coverage maps for Virtual Observatory
- Description
-
PyMOC provides a Python compatible library for handling MOCs.
Frequently astronomical survey catalogues or images are sparse and
cover only a small part of the sky. In a Multi-Order Coverage map
the extent of data in a particular dataset is cached as a
pre-calculated mask image. The hierarchical nature enables fast
boolean operations in image space, without needing to perform complex
geometrical calculations. Services such as VizieR generally offer the
MOC masks, allowing a faster experience in graphical applications
such as Aladin, or for researchers quickly needing to locate which
datasets may contain overlapping coverage.
The MOC mask image itself is tessellated and stored in NASA HealPix
format, encoded inside a FITS image container. Using the HealPix
(Hierarchical Equal Area isoLatitude Pixelization) tessellation
method ensures that more precision (pixels) in the mask are available
when describing complex shapes such as approximating survey or
polygon edges, while only needing to store a single big cell/pixel
when an coverage is either completely inside, or outside of the mask.
Catalogues can be rendered on the mask as circles.
- Maintainer
-
- Versions
-
- Popularity
-
- 90 regular users
-
8 recent
-
148 total installations
(of 247490 submissions)
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python3-pynpoint
|
0.8.3-3
|
Pipeline for processing and analysis of high-contrast imaging data
|
python3-pynpoint:
Pipeline for processing and analysis of high-contrast imaging data
- Description
-
This is a generic, end-to-end pipeline for the data reduction and analysis of
high-contrast imaging data of planetary and substellar companions, as well as
circumstellar disks in scattered light.
The pipeline has a modular architecture with a central data storage in which
all results are stored by the processing modules. These modules have specific
tasks such as the subtraction of the thermal background emission, frame
selection, centering, PSF subtraction, and photometric and astrometric
measurements. The tags from the central data storage can be written to FITS,
HDF5, and text files with the available I/O modules.
- Maintainer
-
- Versions
-
- Popularity
-
- 5 regular users
-
7 recent
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66 total installations
(of 247490 submissions)
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python3-pyraf
|
2.2.1-1
|
Python interface for IRAF
|
python3-pyraf:
Python interface for IRAF
-
-
PyRAF is a command language for running IRAF tasks in a Python like
environment. It works very similar to IRAF CL, but has been updated
to allow such things as importing Python modules, GUI parameter
editing and help. It can be imported into Python allowing you to run
IRAF commands from within a larger script.
- Maintainer
-
- Versions
-
- Popularity
-
- 12 regular users
-
20 recent
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157 total installations
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python3-pyregion
|
2.0-11
|
Python module to parse ds9 region files (Python 3)
|
python3-pyregion:
Python module to parse ds9 region files (Python 3)
- Description
-
Pyregion is a Python module to parse ds9 region files. It also supports ciao
region files.
This is the Python 3 version of the package.
- Maintainer
-
- Versions
-
- Popularity
-
- 14 regular users
-
11 recent
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169 total installations
(of 247490 submissions)
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python3-pysynphot
|
0.9.8.5+dfsg-1
|
Python Synthetic Photometry Utilities
|
python3-pysynphot:
Python Synthetic Photometry Utilities
- Description
-
pysynphot simulates photometric data and spectra as they are observed with
the Hubble Space Telescope (HST). Passbands for standard photometric systems
are available, and users can incorporate their own filters, spectra, and
data. pysynphot user interface allows you to:
- Construct complicated composite spectra from various grids of model
atmosphere spectra, parameterized spectrum models, and atlases of stellar
spectrophotometry.
- Simulate observations.
- Query the resulting structures for quantities of interest, such as
countrate, effective wavelength, effective stimulus, as well as the
wavelength and flux arrays.
- Plot HST sensitivity curves and calibration target spectra.
- Compute photometric calibration parameters for any HST instrument mode.
pysynphot can help HST observers to perform cross-instrument simulations, to
examine the transmission curve of the HST Optical Telescope Assembly (OTA),
and spectra of HST calibration targets. Expert users can take advantage of
the control and data structures available in Python to easily perform
repetitive operations such as simulate the observation of multiple type of
sources through multiple observing modes.
- Reference
-
-
P. L. Lim, R. I. Diaz and V. Laidler:
PySynphot User’s Guide.
(2015)
- Maintainer
-
- Versions
-
- Popularity
-
- 11 regular users
-
10 recent
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137 total installations
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python3-pyvo
|
0.9.2-2
↺
New upstream version
1.6
available
|
Python 3 library for data services of the Virtual observatory (VO)
|
python3-pyvo:
Python 3 library for data services of the Virtual observatory (VO)
- Description
-
The pyvo module currently provides these main capabilities:
Find archives that provide particular data of a particular type and/or relates
to a particular topic search an archive for datasets of a particular type.
Do simple searches on catalogs or databases get information about an object via
its name.
This is the Python 3 version of the package.
- Maintainer
-
- Versions
-
- Popularity
-
- 25 regular users
-
14 recent
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185 total installations
(of 247490 submissions)
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python3-radio-beam
|
0.3.2-1
|
Python Tools for Radio Beam IO and Manipulation
|
python3-radio-beam:
Python Tools for Radio Beam IO and Manipulation
- Description
-
Radio Beam is a simple toolkit for reading beam information from FITS
headers and manipulating beams. Some example applications include
Convolution/deconvolution and Unit conversion (Jy to/from K).
- Maintainer
-
- Versions
-
- Popularity
-
- 14 regular users
-
12 recent
-
176 total installations
(of 247490 submissions)
- Debian
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python3-regions
|
0.10-1
|
Python astronomy package for region handling
|
python3-regions:
Python astronomy package for region handling
- Description
-
The regions package provides (or plans to provide) classes to
represent regions defined using pixel or celestial coordinates or on
the celestial sphere.
- Maintainer
-
- Versions
-
- Popularity
-
- 16 regular users
-
18 recent
-
190 total installations
(of 247490 submissions)
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python3-reproject
|
0.10.0-2
|
Reproject astronomical images with Python 3
|
python3-reproject:
Reproject astronomical images with Python 3
- Description
-
This is a package to reproject astronomical images using various techniques
via a uniform interface. Reprojection means the re-gridding of images from
one world coordinate system to another (for example changing the pixel
resolution, orientation, coordinate system). Currently implemented are
reprojection of celestial images by interpolation, as well as by finding the
exact overlap between pixels on the celestial sphere. It can also reproject
to/from HEALPIX projections.
This package contains the Python 3 version of the package.
- Maintainer
-
- Versions
-
- Popularity
-
- 14 regular users
-
15 recent
-
176 total installations
(of 247490 submissions)
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python3-scipy
|
1.10.1-2
|
scientific tools for Python 3
|
python3-scipy:
scientific tools for Python 3
- Description
-
SciPy supplements the popular NumPy module (python-numpy package), gathering a
variety of high level science and engineering modules together as a single
package.
SciPy is a set of Open Source scientific and numeric tools for Python. It
currently supports special functions, integration, ordinary differential
equation (ODE) solvers, gradient optimization, genetic algorithms, parallel
programming tools, an expression-to-C++ compiler for fast execution, and
others.
- Maintainer
-
- Versions
-
- Popularity
-
- 15947 regular users
-
2769 recent
-
23861 total installations
(of 247490 submissions)
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python3-sep
|
1.2.1-7
|
Python library for source extraction and photometry
|
python3-sep:
Python library for source extraction and photometry
- Description
-
SEP makes the core algorithms of Source Extractor available as a
library of stand-alone functions and classes. These operate
directly on in-memory arrays (no FITS files or configuration files).
The code is derived from the Source Extractor code base (written in
C) and aims to produce results compatible with Source Extractor
whenever possible.
This Python module that wraps the C library in a Pythonic API. The
Python wrapper operates on NumPy arrays.
- Maintainer
-
- Versions
-
- Popularity
-
- 4 regular users
-
11 recent
-
66 total installations
(of 247490 submissions)
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python3-skimage
|
0.24.0-5
|
Python 3 modules for image processing
|
python3-skimage:
Python 3 modules for image processing
- Description
-
scikit-image is a collection of image processing algorithms for
Python. It performs tasks such as image loading, filtering,
morphology, segmentation, color conversions, and transformations.
This package provides the Python 3 module.
- Reference
-
-
Stéfan van der Walt, Johannes L. Schönberger, Juan Nunez-Iglesias, François Boulogne, Joshua D. Warner, Neil Yager, Emmanuelle Gouillart, Tony Yu and the scikit-image contributors:
scikit-image: Image processing in Python.
PeerJ
2:e453
(2014)
(eprint)
- Maintainer
-
- Versions
-
- Popularity
-
- 81 regular users
-
52 recent
-
1258 total installations
(of 247490 submissions)
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|
python3-sklearn
|
0.20.2+dfsg-6
↺
New upstream version
1.6.0
available
|
Python modules for machine learning and data mining - Python 3
|
python3-sklearn:
Python modules for machine learning and data mining - Python 3
- Description
-
scikit-learn is a collection of Python modules relevant to
machine/statistical learning and data mining. Non-exhaustive list of
included functionality:
- Gaussian Mixture Models
- Manifold learning
- kNN
- SVM (via LIBSVM)
This package contains the Python 3 version.
- Maintainer
-
- Versions
-
- Popularity
-
- 261 regular users
-
201 recent
-
1843 total installations
(of 247490 submissions)
- Enhancements
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python3-skyfield
|
1.49+ds-2
|
Elegant astronomy for Python
|
python3-skyfield:
Elegant astronomy for Python
- Description
-
Skyfield is a pure-Python astronomy package that is compatible with
both Python 3 and makes it easy to generate high precision
research-grade positions for planets and Earth satellites.
Skyfield computes positions for the stars, planets, and satellites in
orbit around the Earth. Its results should agree with the positions
generated by the United States Naval Observatory and their
Astronomical Almanac to within 0.0005 arcseconds (which equals half a
“mas” or milliarcsecond).
- Maintainer
-
- Versions
-
- Popularity
-
- 16 regular users
-
8 recent
-
100 total installations
(of 247490 submissions)
- Debian
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python3-sncosmo
|
2.11.2-1
|
Python library for high-level supervova cosmology analysis
|
python3-sncosmo:
Python library for high-level supervova cosmology analysis
- Description
-
SNCosmo synthesizes supernova spectra and photometry from SN models,
and has functions for fitting and sampling SN model parameters given
photometric light curve data. It offers fast implementations of
several commonly used extinction laws and can be used to construct SN
models that include dust. The SNCosmo library includes supernova
models such as SALT2, MLCS2k2, Hsiao, Nugent, PSNID, SNANA and Whalen
models, as well as a variety of built-in bandpasses and magnitude
systems, and provides convenience functions for reading and writing
peculiar data formats used in other packages. The library is
extensible, allowing new models, bandpasses, and magnitude systems to
be defined using an object-oriented interface.
- Maintainer
-
- Versions
-
- Popularity
-
- 6 regular users
-
11 recent
-
65 total installations
(of 247490 submissions)
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python3-spectral-cube
|
0.6.0-3
|
Manipulate astronomical data cubes with Python
|
python3-spectral-cube:
Manipulate astronomical data cubes with Python
- Description
-
The spectral-cube package provides an easy way to read, manipulate,
analyze, and write data cubes with two positional dimensions and one
spectral dimension, optionally with Stokes parameters. It aims to be a
versatile data container for building custom analysis routines.
- Reference
-
- Maintainer
-
- Versions
-
- Popularity
-
- 13 regular users
-
11 recent
-
174 total installations
(of 247490 submissions)
- Debian
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python3-specutils
|
0.2.2-1
|
Base classes and utilities for astronomical spectra in Python
|
python3-specutils:
Base classes and utilities for astronomical spectra in Python
- Description
-
The specutils package implements base classes and utilities for
interacting with astronomical spectra in Python and the Astropy
project. It is intended for eventual merger with the astropy package,
but for now is being developed independently.
- Maintainer
-
- Versions
-
- Popularity
-
- 13 regular users
-
13 recent
-
163 total installations
(of 247490 submissions)
- Debian
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|
python3-sunpy
|
4.1.2-1
↺
New upstream version
6.0.4
available
|
Software library for solar physics based on Python
|
python3-sunpy:
Software library for solar physics based on Python
- Description
-
SunPy is a community-developed free and open-source software package for
solar physics. SunPy is meant to be a free alternative to the SolarSoft data
analysis environment. The aim of the SunPy project is to provide the
software tools necessary so that anyone can analyze solar data.
- Reference
-
-
T. SunPy Community, S.J. Mumford, S. Christe, D. Perez-Suarez, J. Ireland, A.Y. Shih, A.R. Inglis, S. Liedtke, R.J. Hewett, F. Mayer, K. Hughitt, N. Freij, T. Meszaros, S.M. Bennett, M. Malocha, J. Evans, A. Agrawal, A.J. Leonard, T.P. Robitaille, B. Mampaey, J. Ivan Campos-Rozo and M.S. Kirk:
SunPy-Python for solar physics.
Computational Science and Discovery
8(1):014009
(2015)
(eprint)
- Maintainer
-
- Versions
-
- Popularity
-
- 10 regular users
-
9 recent
-
139 total installations
(of 247490 submissions)
- Debian
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|
python3-theano
|
1.0.3+dfsg-1
|
CPU/GPU math expression compiler for Python 3
|
python3-theano:
CPU/GPU math expression compiler for Python 3
- Description
-
Theano is a Python library that allows one to define and evaluate mathematical
expressions involving multi-dimensional arrays efficiently. It provides a
high-level Numpy like expression language for functional description of
calculation, rearranges expressions for speed and stability, and generates
native machine instructions for fast calculation. Optionally, highly
accelerated computations could be carried out on graphics cards processors.
This package contains Theano for Python 3.
- Reference
-
-
Theano Development Team:
Theano: A Python framework for fast computation of mathematical expressions.
(2016)
(eprint)
- Maintainer
-
- Versions
-
- Popularity
-
- 13 regular users
-
9 recent
-
210 total installations
(of 247490 submissions)
- Debian
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|
python3-vispy
|
0.14.1-2
↺
New upstream version
0.14.3
available
|
interactive visualization in Python 3
|
python3-vispy:
interactive visualization in Python 3
- Description
-
Vispy is a high-performance interactive 2D/3D data visualization library.
Vispy leverages the computational power of modern Graphics Processing Units
(GPUs) through the OpenGL library to display very large datasets.
This package provides VisPy for the Python 3 interpreter.
- Reference
-
- Maintainer
-
- Versions
-
- Popularity
-
- 7 regular users
-
20 recent
-
151 total installations
(of 247490 submissions)
- Debian
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|
python3-yt
|
3.6.1-1
|
Framework for analyzing and visualizing simulation data (Python 3)
|
python3-yt:
Framework for analyzing and visualizing simulation data (Python 3)
- Description
-
The yt project aims to produce an integrated science environment for
collaboratively asking and answering astrophysical questions. To do so, it will
encompass the creation of initial conditions, the execution of simulations, and
the detailed exploration and visualization of the resultant data. It will also
provide a standard framework based on physical quantities interoperability
between codes.
This package contains the Python 3 version of the package.
- Reference
-
- Maintainer
-
- Versions
-
- Popularity
-
- 16 regular users
-
11 recent
-
154 total installations
(of 247490 submissions)
- Debian
-
- Upstream
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|
Packaging has started and developers might try the packaging code in VCS
|
▾
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python3-bokeh
|
3.4.0-0
|
interactive visualization library for modern web browsers
|
python3-bokeh:
interactive visualization library for modern web browsers
- Description
-
Bokeh is an interactive visualization library for modern web browsers.
It provides elegant, concise construction of versatile graphics and
affords high-performance interactivity across large or streaming
datasets. Bokeh can help anyone who wants to create interactive plots,
dashboards, and data applications quickly and easily.
- Responsible
-
- Versions
-
- Debian
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- Upstream
-
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python3-heliopy
|
0.8.0-1
|
Python for heliospheric and planetary physics
|
python3-heliopy:
Python for heliospheric and planetary physics
- Description
-
A python library for heliospheric and planetary Physics.
The primary goal of HelioPy is to provide a set of tools
to download and read in data, and to carry out other
common data processing tasks.
- Responsible
-
- Versions
-
- Debian
-
- Upstream
-
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python3-pyspeckit
|
0.1.20-1
|
Python toolkit for fitting and manipulating spectroscopic data (Python 3)
|
python3-pyspeckit:
Python toolkit for fitting and manipulating spectroscopic data (Python 3)
- Description
-
PySpecKit is a code framework designed to allow for analysis of spectroscopic
data from a wide variety of astronomical instruments.
Initial implementation focuses on optical and radio applications, e.g.
gaussian and voigt profile fitting, baseline/continuum fitting, and
equivalent width measurements.
- Responsible
-
- Versions
-
- Debian
-
- Upstream
-
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python3-supersmoother
|
0.4-1
|
Python implementation of Friedman's Supersmoother (Python 3)
|
python3-supersmoother:
Python implementation of Friedman's Supersmoother (Python 3)
- Description
-
This is an efficient implementation of Friedman’s SuperSmoother based in
Python. It makes use of numpy for fast numerical computation
This package installs the library for Python 3.
- Responsible
-
- Versions
-
- Debian
-
- Upstream
-
|
No known packages available but some record of interest (WNPP bug)
|
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python3-gatspy
|
|
General tools for Astronomical Time Series in Python
|
python3-gatspy:
General tools for Astronomical Time Series in Python
- Description
-
- Debian
-
- Upstream
-
|
▾
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python3-pytorch
|
|
Tensors and Dynamic neural networks with GPU acceleration
|
python3-pytorch:
Tensors and Dynamic neural networks with GPU acceleration
- Description
-
- Debian
-
- Upstream
-
|
▾
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python3-sherpa
|
|
Modeling and fitting in Python 3
|
python3-sherpa:
Modeling and fitting in Python 3
- Description
-
Sherpa is a Python package for modeling and fitting. It enables the user to
construct complex models from simple definitions and fit those models to
data, using a variety of statistics and optimization methods.
It was originally developed by the Smithsonian Astrophysical Observatory /
Chandra X-Ray Center as part of the larger CIAO package for X-ray data
analysis
- Debian
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- Upstream
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