Ce métapaquet installe les paquets Python 3 pour l'astronomie. Les paquets
peuvent être utilisés pour l'analyse interactive ou pour créer des
programmes spécifiques.
Official Debian packages with high relevance
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ipython3
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7.20.0-1+deb11u1
↺
New upstream version
8.31.0
available
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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.
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- Versions
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- Popularity
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- 1638 regular users
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879 recent
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7379 total installations
(of 245023 submissions)
- Enhancements
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python3
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3.11.2-1
↺
New upstream version
3.13.1
available
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langage orienté objet interactif de haut niveau – version par défaut de Python 3
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python3:
langage orienté objet interactif de haut niveau – version par défaut de Python 3
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✏
Python, le langage de haut niveau, orienté objet, interactif, comprend une
bibliothèque de classes étendue et pleine de bonnes choses pour la
programmation réseau, l'administration système, le son et le graphisme.
Ce paquet est un paquet de dépendances, tributaire de la version par
défaut de Python 3 dans Debian (actuellement 3.12).
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- Versions
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- Tags
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✏
- devel
- interpreter, lang:python, library
- role
- devel-lib, program, shared-lib
- Popularity
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- 170735 regular users
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22774 recent
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235446 total installations
(of 245023 submissions)
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python3-aplpy
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2.2.0-1
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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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- Versions
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- Popularity
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- 12 regular users
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1 recent
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159 total installations
(of 245023 submissions)
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python3-asdf
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4.0.0-1
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bibliothèque Python 3 pour le format de données scientifiques évolué
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python3-asdf:
bibliothèque Python 3 pour le format de données scientifiques évolué
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✏
ASDF (« Advanced Scientific Data Format » – format de données scientifiques
évolué) est une proposition de format d'échange de nouvelle génération pour
les données scientifiques. ASDF vise à exister dans le même milieu que
celui qui a rendu FITS si prospère, en étant un format hybride texte et
binaire : des métadonnées modifiables par un humain pour l'échange et des
données binaires brutes rapides à charger et utiliser. Contrairement à
FITS, les métadonnées sont hautement structurées et conçues dès le départ
pour être extensibles.
Il s'agit du paquet Python 3.
- Reference
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- Versions
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- Popularity
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- 21 regular users
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13 recent
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205 total installations
(of 245023 submissions)
- Debian
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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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- 57 regular users
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140 total installations
(of 245023 submissions)
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python3-astroalign
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2.4.1-3
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enregistrement astronomique d’images quand aucune information WCS n’est disponible
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python3-astroalign:
enregistrement astronomique d’images quand aucune information WCS n’est disponible
- Description
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✏
Astroalign est un module de Python qui essaie d’aligner deux images
astronomiques d’étoiles, particulièrement quand aucune information WCS
n’est disponible.
Cela est fait en trouvant des astérismes « trois points » (triangles) dans
les deux images et en déduisant une transformation affine entre eux.
Les routines génériques d’enregistrement essaient de faire correspondre
des points caractéristiques, en utilisant des routines de détection
d’angles pour déterminer des correspondances de points. Elles échouent
généralement pour des images astronomiques stellaires puisque les étoiles
ont des structures très peu stables et sont donc, en général,
indistinguables les unes des autres. La correspondance d’astérismes est
plus robuste et plus proche de la façon humaine de faire correspondre des
images stellaires.
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- Versions
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- Popularity
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- 4 regular users
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61 total installations
(of 245023 submissions)
- Debian
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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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- 11 regular users
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142 total installations
(of 245023 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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- 20 regular users
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156 total installations
(of 245023 submissions)
- Debian
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python3-astroplan
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0.2-5
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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.
- Maintainer
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- Versions
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- Popularity
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- 12 regular users
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164 total installations
(of 245023 submissions)
- Debian
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python3-astropy
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3.1.2-2
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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)
- Maintainer
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- Versions
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- Popularity
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- 269 regular users
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146 recent
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1336 total installations
(of 245023 submissions)
- Debian
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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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- Versions
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- Popularity
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110 total installations
(of 245023 submissions)
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python3-astropy-coordinated
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2.1
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collection de tous les paquets « coordonnés » d’Astropy
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python3-astropy-coordinated:
collection de tous les paquets « coordonnés » d’Astropy
- Description
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✏
« Coordinated packages » sont des paquets améliorant Astropy qui sont
entretenus en tant qu’entité par le projet Astropy. En pratique, cela
signifie que le comité de coordination d’Astropy contrôle
administrativement un dépôt de paquets « coordonnés » (délégué aux
responsables de paquets), et ces responsables de paquets ont des rôles
officiels dans le projet Astropy. Dans certains cas, ce sont des paquets
identifiés par le cœur de l’équipe comme ayant besoin d’un développement
séparé du noyau central (soit parce qu’ils sont expérimentaux ou pour des
problèmes d’espace) tandis que d’autres ont commencés comme « affiliated
packages » mais sont devenus si important pour l’écosystème qu’ils ont
atteint le stade de « coordinated ».
Ce métapaquet installe tous les « coordinated packages ».
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- Versions
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- Popularity
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62 total installations
(of 245023 submissions)
- Debian
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python3-astropy-healpix
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1.0.3-1
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représentation HEALPix de données de sphère – Python 3
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python3-astropy-healpix:
représentation HEALPix de données de sphère – Python 3
- Description
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✏
HEALPix est un acronyme pour « Hierarchical Equal Area isoLatitude
Pixelization » (pixelisation hiérarchique iso-latitude d’aires égales) d’une
sphère. Comme suggéré par le nom, cette pixelisation produit une subdivision de
la surface sphérique dans laquelle chaque pixel couvre la même surface que tous
les autres. HEALPix est couramment utilisé pour stocker des images astronomiques
de tout le ciel, plus particulièrement des cartes du fond diffus cosmologique.
Ce paquet est un paquet d’HEALPix, sous licence BSD, développé par le projet
Astropy et basé sur du code C écrit par Dustin Lang pour astrometry.net.
Ce paquet fournit les modules pour Python 3.
- Maintainer
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- Versions
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- Popularity
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- 13 regular users
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2 recent
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175 total installations
(of 245023 submissions)
- Debian
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python3-astroquery
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0.4.1+dfsg-4
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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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- 22 regular users
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6 recent
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173 total installations
(of 245023 submissions)
- Debian
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python3-astroscrappy
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1.1.0-2
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annihilation optimisée de rayons cosmiques avec Python
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python3-astroscrappy:
annihilation optimisée de rayons cosmiques avec Python
- Description
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✏
Astro-SCRAPPY est conçu pour la détection des rayons cosmiques dans des
images (tableaux numpy), basée sur l’algorithme L.A.Cosmic de Pieter van
Dokkum. La parallélisation est réalisée en utilisant OpenMP.
- 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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1 recent
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168 total installations
(of 245023 submissions)
- Debian
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python3-bdsf
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1.12.0-1
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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.
- Maintainer
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- Versions
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- Popularity
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2 recent
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15 total installations
(of 245023 submissions)
- Debian
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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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liaisons de Python pour la bibliothèque casacore
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python3-casacore:
liaisons de Python pour la bibliothèque casacore
- Description
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✏
Le paquet casacore fournit les bibliothèques principales de l'ancien paquet
AIPS++/CASA («⋅Common Astronomy Software Applications⋅»). Cette séparation
permet de mieux isoler les bibliothèques principales des applications. CASA
est maintenant construit sur casacore.
Ce paquet fournit une enveloppe de Python autour de la bibliothèque.
- Maintainer
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- Versions
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- Popularity
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- 60 regular users
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9 recent
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219 total installations
(of 245023 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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- 11 regular users
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161 total installations
(of 245023 submissions)
- Debian
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python3-cpl
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0.7.4-2
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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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- 10 regular users
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1 recent
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152 total installations
(of 245023 submissions)
- Debian
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python3-cvxopt
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1.3.0+dfsg-1
↺
New upstream version
1.3.2
available
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paquet de Python⋅3 pour l’optimisation convexe
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python3-cvxopt:
paquet de Python⋅3 pour l’optimisation convexe
- Description
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✏
CVXOPT est un paquet de Python pour l’optimisation convexe. Il inclut :
– des classes de Python pour stocker et manipuler des matrices denses et
creuses ;
– une interface pour la plupart des programmes BLAS réels et
complexes à double précision ;
– une interface pour les solveurs d’équations linéaires denses et les
routines de valeur propre de LAPACK ;
– des interfaces pour les solveurs LU et Cholesky de matrices creuses
d’UMFPACK et CHOLMOD ;
– des routines pour résoudre les problèmes d’optimisation convexe, une
interface de solveur pour l’optimisation linéaire de GLPK et des
interfaces pour solveurs d’optimisation linéaire et quadratique de
MOSEK ;
– un outil de modélisation pour des problèmes d’optimisation convexe
de fonction linéaire par morceaux.
Ce paquet fournit le module Python 3.
- Maintainer
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- Versions
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- Popularity
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- 76 regular users
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33 recent
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802 total installations
(of 245023 submissions)
- Debian
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python3-dask
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1.0.0+dfsg-2
↺
New upstream version
2024.12.1
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
-
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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- 177 regular users
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57 recent
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1237 total installations
(of 245023 submissions)
- Debian
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python3-drizzle
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2.0.0-1
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combinaison d’image « dither » avec Python
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python3-drizzle:
combinaison d’image « dither » avec Python
- Description
-
✏
La bibliothèque drizzle est un paquet de Python pour combiner des images
« dithered » (diffusion d’erreur) en une seule image. Cette bibliothèque est
dérivée du code utilisé dans drizzlepac. Comme pour celui-ci, la majeure partie
du code est implémentée dans le langage C. La modification la plus importante
est que le code accepte un tableau qui mappe l’entrée pour une sortie d’image en
code C tandis que le code de drizzlepac calcule le mappage en utilisant une
fonction de rappel en Python. Utiliser un tableau permet de simplifier
grandement le code.
- Reference
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- Maintainer
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- Versions
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- Popularity
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- 9 regular users
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136 total installations
(of 245023 submissions)
- Debian
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python3-drms
|
0.8.0-1
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accès aux données d’HMI, AIA et MDI à l’aide de Python
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python3-drms:
accès aux données d’HMI, AIA et MDI à l’aide de Python
- Description
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✏
Le module drms fournit une interface conviviale de Python pour accéder aux
données HMI, AIA et MDI à l’aide de Python. Il utilise par défaut le serveur
JSOC (Joint Science Operations Center) d’accès public, mais peut aussi utiliser
des sites NetDRMS locaux.
HMI (Helioseismic and Magnetic Imager) et AIA (Atmospheric Imaging Assembly)
sont des instruments à bord de l’Observatoire de la dynamique solaire (SDO)
conçus pour étudier le champ magnétique et les variations et la surface solaire.
Le MDI (Michelson Doppler Imager) est le prédécesseur du HMI actuel et a été
lancé à bord de l’Observatoire solaire et héliosphérique (SoHO). HMI et MDI
étudient le disque solaire en entier à 6173 ångström avec une haute résolution,
tandis que AIA est conçu pour étudier la couronne solaire.
- Maintainer
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- Versions
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- Popularity
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- 11 regular users
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144 total installations
(of 245023 submissions)
- Debian
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python3-einsteinpy
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0.4.0-2
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General Relativity in Python
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python3-einsteinpy:
General Relativity in Python
- Description
-
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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- 6 regular users
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1 recent
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97 total installations
(of 245023 submissions)
- Debian
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python3-emcee
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3.0.2-2
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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
-
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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- 16 regular users
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python3-ephem
|
4.1.6-1
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Compute positions of the planets and stars with Python
|
python3-ephem:
Compute positions of the planets and stars with Python
- Description
-
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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- 306 regular users
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87 recent
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777 total installations
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python3-extinction
|
0.4.7-1
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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
-
Extinction contains Cython-optimised implementations of empirical dust
extinction laws found in the astronomical literature.
- Maintainer
-
- Versions
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- 4 regular users
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5 recent
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67 total installations
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python3-fast-histogram
|
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
-
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.
- Maintainer
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- 15 regular users
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11 recent
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195 total installations
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python3-fitsio
|
1.1.4+dfsg-1
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bibliothèque de Python 3 pour lire et éditer des fichiers FITS
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python3-fitsio:
bibliothèque de Python 3 pour lire et éditer des fichiers FITS
- Description
-
✏
Fitsio fournit une API conviviale orientée objet incluant une interface
Numpy pour la lecture de fichiers FITS de CFITSIO. Elle permet un accès
direct aux colonnes de la table binaire FITS qui peut être utile lors de
la lecture de très gros fichiers fits. Comparé à astropy.io.fits, ce
paquet est plus proche de la bibliothèque cfitsio sous-jacente.
Fitsio expose aussi un microlangage (implémenté dans CFITSIO) pour des
requêtes efficaces de type SQL dans des tables (seulement une unique
table, mais pas de « join » ou de choses du même genre).
- Maintainer
-
- Versions
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- Popularity
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- 13 regular users
-
1 recent
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161 total installations
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python3-galpy
|
1.4.0-2
↺
New upstream version
1.10.1
available
|
Python 3 package for Galactic Dynamics
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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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- Versions
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- Popularity
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- 12 regular users
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150 total installations
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python3-gammapy
|
1.3-1
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Python package for gamma-ray astronomy
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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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- 7 regular users
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2 recent
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84 total installations
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python3-gdl
|
1.1-1
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interface de Python pour GDL (GNU Data Language)
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python3-gdl:
interface de Python pour GDL (GNU Data Language)
- Description
-
✏
GNU Data Language (GDL) est un compilateur incrémental libre compatible
avec IDL (Interactive Data Language). Sa syntaxe est entièrement
compatible avec IDL 7.1. IDL est une marque déposée d’ITT Visual
Information Solutions. À partir de IDL 8.0, les éléments de langage
suivants sont pris en charge :
— boucle FOREACH ;
— indices de tableau négatifs ;
— ramasse-miettes pour les pointeurs et objets ;
— méthodes d’appel sur des objets en utilisant « . » (par exemple,
`object.aMemberProcedure,arg1`).
Le système d’entrée et sortie de fichiers est complètement implémenté. La
prise en charge de l’interface graphique (composants graphiques) est
officiellement fournie, mais pas encore finie.
Ce paquet fournit la bibliothèque/interface de Python.
- 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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- 5 regular users
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2 recent
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88 total installations
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python3-ginga
|
5.2.0-1
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boite à outils pour image astronomique pour Python
|
python3-ginga:
boite à outils pour image astronomique pour Python
-
-
✏
Ginga est une boîte à outils conçue pour créer des afficheurs pour des données
d’image scientifique en Python, visualisant les données de pixels en 2D de
tableaux de numpy. Elle peut afficher des données d’astronomie telles que celles
contenues dans des fichiers basés sur le format FITS (Flexible Image Transport
System). Elle a été écrite et est entretenue par des ingénieurs en informatique
au télescope Subaru géré par l’Observatoire astronomique national du Japon.
La boîte à outils Ginga est centrée sur l’affichage d’objet d’image avec une
prise en charge du zoom et du panorama, le mappage de couleurs et d’intensités,
un choix d’algorithmes de détection automatique de niveau de coupure et de cadre
(canvas) pour le tracé de formes géométriques échelonnables. En plus de ce
composant graphique, un afficheur générique FITS de « référence » est fourni,
basé sur utilisateur cadriciel de greffons. Un ensemble presque complet de
greffons standard est fourni pour des fonctions qu’il est espéré de trouver dans
un afficheur FITS moderne : fenêtres de panoramique ou de zoom, accès à un
catalogue d’étoiles, coupures (cuts), pics d’étoile/largeur à mi-hauteur,
vignettes, etc.
- Maintainer
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- 14 regular users
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2 recent
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180 total installations
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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
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- 12 regular users
-
164 total installations
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python3-gwcs
|
0.16.1-1
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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
-
- Versions
-
- Popularity
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- 14 regular users
-
13 recent
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169 total installations
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python3-gyoto
|
1.4.4-3
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intégration de géodésiques de relativité générale pour le langage Python 3
|
python3-gyoto:
intégration de géodésiques de relativité générale pour le langage Python 3
- Description
-
✏
Gyoto a pour but la fourniture d’un cadriciel pour le traitement des
orbites et des images obtenues par lancer de rayon dans le cadre de la
relativité générale.
Ce paquet fournit aussi un greffon de Gyoto permettant d’écrire de
nouveaux objets dans le langage Python 3.
Ce paquet fournit une extension pour le langage de programmation Python 3
exposant les fonctions de Gyoto. Il permet d’utiliser Gyoto
interactivement à partir de l’invite de Python 3 ou d’exécuter des scripts
de Gyoto complexes.
La production de vidéos nécessite le paquet python3-opencv.
- Reference
-
- Maintainer
-
- Versions
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- Popularity
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- 5 regular users
-
5 recent
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112 total installations
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python3-healpy
|
1.18.0-1
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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.
- Maintainer
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- 13 regular users
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6 recent
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173 total installations
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python3-hips
|
0.2-3
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Python package for Hierarchical Progressive Surveys
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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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- 3 regular users
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74 total installations
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python3-imexam
|
0.8.0-3
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examen interactif d’image astronomique et tracé simples
|
python3-imexam:
examen interactif d’image astronomique et tracé simples
- Description
-
✏
Imexam est un paquet associé à AstroPy. Il a été conçu pour être une
bibliothèque légère qui permet d’explorer des données en utilisant des
méthodes courantes qui sont constantes dans tous les visualisateurs. Il
peut être utilisé à partir d’une interface en ligne de commande, à l’aide
d’un notebook Jupyter ou d’une console Jupyter. Il peut être utilisé avec
de nombreux visualisateurs tels que DS9 ou Ginga, ou sans visualisateur
sous forme d’une simple bibliothèque pour réaliser des tracés et récupérer
rapidement des informations de photométrie.
- Maintainer
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- 6 regular users
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112 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
-
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-
- Popularity
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- 11 regular users
-
1 recent
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118 total installations
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python3-lmfit
|
0.9.11+dfsg-2
↺
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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python3-matplotlib
|
3.0.2-2
↺
New upstream version
3.10.0
available
|
système de traçage basé sur Python dans un style similaire à celui Matlab
|
python3-matplotlib:
système de traçage basé sur Python dans un style similaire à celui Matlab
- Description
-
✏
Matplotlib est une bibliothèque de traçage en Python pur conçue pour
apporter à Python des capacités de traçage d'une qualité adaptée à la
publication, avec une syntaxe familière aux utilisateurs de Matlab. L'accès
à toutes les commandes de traçage, dans l'interface pylab, est possible
soit à travers une interface fonctionnelle familière aux utilisateurs de
Matlab, soit à travers une interface orientée objet familière à ceux de Python.
- Maintainer
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- 19152 regular users
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969 recent
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24702 total installations
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python3-montage-wrapper
|
0.9.9-2
|
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
-
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- 1 regular users
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59 total installations
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python3-montagepy
|
6.1+dfsg-1
|
boite à outils de Python pour l’assemblage d’images FITS en mosaïques
|
python3-montagepy:
boite à outils de Python pour l’assemblage d’images FITS en mosaïques
- Description
-
✏
MontagePy est une boîte à outils pour assembler des images astronomiques dans
des mosaïques personnalisées.
Elle utilise des algorithmes qui préservent la fidélité de calibration et de
position (astronomiques) des images d’entrées pour produire des mosaïques qui
correspondent aux paramètres de l’utilisateur pour la projection, les
coordonnées et l’échelle spatiale. Elle prend en charge tous les systèmes de
projection et de coordonnées utilisés en astronomie.
Elle contient des modules indépendants pour analyser la géométrie des images du
ciel et pour créer et générer les mosaïques. Ces modules sont des outils
puissants en tant que tels et ont une utilité en dehors de la production de
mosaïque, dans des domaines tels que la validation des données.
- Reference
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-
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python3-mpl-scatter-density
|
0.5-1
↺
New upstream version
0.8
available
|
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.
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- 13 regular users
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python3-ndcube
|
2.0.3-1
|
paquet pour des tableaux multidimensionnels relatifs aux coordonnées –Python 3
|
python3-ndcube:
paquet pour des tableaux multidimensionnels relatifs aux coordonnées –Python 3
- Description
-
✏
ndcube est un paquet associé à SunPy pour manipuler, inspecter et
visualiser des tableaux de données multidimensions contigües ou non,
relatifs aux coordonnées. Il combine des données, des incertitudes,
des unités, des métadonnées, des masquages et des transformations de
coordonnées en classes avec un découpage unifié et des transformations
génériques de coordonnées et des capacités de tracé/animation. Il est
conçu pour gérer des données de n’importe quel nombre de dimensions et de
types d’axe (par exemple, spatial, temporel, spectral, etc., dont les
relations entre les éléments du tableau et le monde réel peuvent être
décrites par des translations WCS (World Coordinate System).
Il s'agit de la version Python 3 du paquet.
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- 12 regular users
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python3-numpy
|
1.8.2-2
↺
New upstream version
2.2.1
available
|
gestion rapide des tableaux pour le langage Python – Python 3
|
python3-numpy:
gestion rapide des tableaux pour le langage Python – Python 3
- Description
-
✏
NumPy (Numerical Python) fournit un puissant objet de tableau à
n dimensions, des fonctions sophistiquées (dispersion), des outils pour
intégrer du code Fortran et C/C++, des outils pratiques pour l'algèbre
linéaire, la transformation de Fourier et la génération de nombres
aléatoires.
Ce paquet installe NumPy pour Python 3.
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-
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- 25858 regular users
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4174 recent
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46344 total installations
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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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- 5 regular users
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76 total installations
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python3-pandas
|
0.23.3+dfsg-3
|
structures de données pour des données « relationnelles » ou « étiquetées »
|
python3-pandas:
structures de données pour des données « relationnelles » ou « étiquetées »
- Description
-
✏
Pandas est un paquet de Python fournissant des structures de données
rapides, modulables et expressives, conçues pour travailler facilement et
intuitivement avec des données « relationnelles » ou « étiquetées ». Il
vise à être un bloc de construction fondamental et de haut niveau pour
réaliser l’analyse pratique de données du monde réel en Python. Pandas
convient bien pour différentes sortes de données :
— données de tableaux avec des colonnes de types hétérogènes, comme dans
des tables SQL ou des feuilles de calcul Excel ;
— données de séries temporelles triées ou non (pas nécessairement à
fréquence fixe) ;
— données de matrices arbitraires (de type homogène ou non) avec des
étiquettes de ligne et colonne ;
— n’importe quelle forme d’ensembles de données d’observations ou
statistiques. Les données n’ont en fait pas du tout besoin d’être
étiquetées pour être placées dans des structures de données pandas.
Ce paquet fournit la version Python⋅3.
- Reference
-
-
McKinney, Wes:
pandas: a Foundational Python Library for Data Analysis and Statistics.
(2011)
(eprint)
- Maintainer
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- 570 regular users
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338 recent
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5485 total installations
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python3-photutils
|
0.6-1
|
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
-
- Versions
-
- Popularity
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- 14 regular users
-
2 recent
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178 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
-
- Versions
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- Popularity
-
- 13 regular users
-
94 total installations
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python3-pyavm
|
0.9.4-5
|
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
-
- Versions
-
- Popularity
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- 14 regular users
-
1 recent
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185 total installations
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python3-pydl
|
0.6.0-3
|
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
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1 recent
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157 total installations
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python3-pyds9
|
1.8.1-1
|
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
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- 57 regular users
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5 recent
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149 total installations
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python3-pyfftw
|
0.11.1-2
↺
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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-
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- 17 regular users
-
8 recent
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161 total installations
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python3-pygnuplot
|
0.11.16-2
↺
New upstream version
0.12.3
available
|
enveloppe simple de Python pour Gnuplot
|
python3-pygnuplot:
enveloppe simple de Python pour Gnuplot
- Description
-
✏
PyGnuplot fonctionne comme une tuyauterie Python pour Gnuplot, permettant
d’enchainer les commandes vers l’invite de commande de Gnuplot, faire le
tracé, enregistrer les fichiers de données et créer les fichiers
PostScript et PDF.
Ce paquet installe la bibliothèque pour Python 3.
- Maintainer
-
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- 4 regular users
-
1 recent
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114 total installations
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python3-pymoc
|
0.5.0-4
|
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
-
- 56 regular users
-
3 recent
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146 total installations
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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
-
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-
- Popularity
-
- 5 regular users
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62 total installations
(of 245023 submissions)
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python3-pyraf
|
2.1.15-2
|
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
-
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-
- Popularity
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- 11 regular users
-
5 recent
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150 total installations
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python3-pyregion
|
2.3.0-2
|
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
-
- 12 regular users
-
2 recent
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165 total installations
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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
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- 10 regular users
-
134 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
-
- 24 regular users
-
8 recent
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183 total installations
(of 245023 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
-
- 15 regular users
-
6 recent
-
171 total installations
(of 245023 submissions)
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python3-regions
|
0.4-1
|
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
-
1 recent
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186 total installations
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python3-reproject
|
0.4-3
|
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
-
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-
- Popularity
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- 13 regular users
-
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171 total installations
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python3-scipy
|
1.14.1-3
↺
New upstream version
1.15.0~rc1
available
|
outils scientifiques pour Python 3
|
python3-scipy:
outils scientifiques pour Python 3
- Description
-
✏
SciPy complète le module NumPy populaire (paquet python-numpy),
rassemblant une grande variété de modules de haut niveau technique dans un
seul paquet.
SciPy est un ensemble d’outils scientifiques et numériques pour Python. Il
prend en charge, entre autres, les fonctions spéciales, la résolution
d’intégrales et d’équations différentielles ordinaires, l’optimisation par
gradient, des algorithmes génétiques, des outils de programmation
parallèle, un compilateur expression-vers-C++ pour une exécution rapide.
- Maintainer
-
- Versions
-
- Popularity
-
- 15949 regular users
-
2681 recent
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23876 total installations
(of 245023 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
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- 4 regular users
-
1 recent
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62 total installations
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python3-skimage
|
0.10.1-2
↺
New upstream version
0.25.0
available
|
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
-
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-
- Popularity
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- 81 regular users
-
27 recent
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1237 total installations
(of 245023 submissions)
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|
python3-sklearn
|
0.23.2-5
↺
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
-
- 250 regular users
-
264 recent
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1830 total installations
(of 245023 submissions)
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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
-
1 recent
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95 total installations
(of 245023 submissions)
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python3-sncosmo
|
2.9.0-1
|
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
-
- 5 regular users
-
61 total installations
(of 245023 submissions)
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python3-spectral-cube
|
0.4.3-2
|
manipulation de cubes de données astronomiques avec Python
|
python3-spectral-cube:
manipulation de cubes de données astronomiques avec Python
- Description
-
✏
Le paquet spectral-cube fournit un moyen simple de lire, manipuler,
analyser et écrire des cubes multidimensionnels de données avec deux
dimensions de position et une dimension spectrale, et, de manière
facultative, avec des paramètres de Stokes.
- Reference
-
- Maintainer
-
- Versions
-
- Popularity
-
- 14 regular users
-
6 recent
-
169 total installations
(of 245023 submissions)
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|
python3-specutils
|
1.9.1-1
|
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
-
5 recent
-
159 total installations
(of 245023 submissions)
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|
python3-sunpy
|
6.0.3-2
↺
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
-
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-
- Popularity
-
- 10 regular users
-
2 recent
-
136 total installations
(of 245023 submissions)
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|
python3-theano
|
0.8.2-6
|
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
-
- 14 regular users
-
2 recent
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206 total installations
(of 245023 submissions)
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|
python3-vispy
|
0.6.6-1
↺
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
-
- 8 regular users
-
1 recent
-
139 total installations
(of 245023 submissions)
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|
python3-yt
|
3.2.3-2
|
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
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- 13 regular users
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2 recent
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147 total installations
(of 245023 submissions)
- Debian
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- Improve entry
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Packaging has started and developers might try the packaging code in VCS
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python3-bokeh
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3.4.0-0
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interactive visualization library for modern web browsers
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python3-bokeh:
interactive visualization library for modern web browsers
- Description
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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.
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- Debian
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python3-heliopy
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0.8.0-1
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Python for heliospheric and planetary physics
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python3-heliopy:
Python for heliospheric and planetary physics
- Description
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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.
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- Debian
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python3-pyspeckit
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0.1.20-1
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Python toolkit for fitting and manipulating spectroscopic data (Python 3)
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python3-pyspeckit:
Python toolkit for fitting and manipulating spectroscopic data (Python 3)
- Description
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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.
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- Debian
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python3-supersmoother
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0.4-1
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Python implementation of Friedman's Supersmoother (Python 3)
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python3-supersmoother:
Python implementation of Friedman's Supersmoother (Python 3)
- Description
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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.
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- Debian
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No known packages available but some record of interest (WNPP bug)
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python3-gatspy
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General tools for Astronomical Time Series in Python
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python3-gatspy:
General tools for Astronomical Time Series in Python
- Description
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- Debian
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- Upstream
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python3-pytorch
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Tensors and Dynamic neural networks with GPU acceleration
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python3-pytorch:
Tensors and Dynamic neural networks with GPU acceleration
- Description
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- Debian
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python3-sherpa
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Modeling and fitting in Python 3
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python3-sherpa:
Modeling and fitting in Python 3
- Description
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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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