Debian Astro Python packages

Python 2, il linguaggio interattivo di alto livello orientato agli oggetti, include una vasta libreria di classi ricca di chicche per la programmazione su reti, amministrazione di sistema, suoni e grafica.

Questo è un pacchetto di dipendenza che dipende dalla versione di Python 2 in Debian (attualmente la 2.7).

• Matthias Klose

• 2.7.16-1 (buster)
• 2.7.13-2 (stretch)
• 2.7.9-1 (jessie)

devel

interpreter, lang:python

interface

commandline

role

metapackage, program

scope

utility

• 1342 regular users
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• 44126 total installations (of 252457 submissions)

• idle

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• P. Greenfield, M. Droettboom and E. Bray: ASDF: A new data format for astronomy. Astronomy and Computing 12:240-251 (2015) (eprint)

• Debian Astronomy Team
• Ole Streicher

• 1.2.1-2 (stretch)

• 3 total installations (of 252457 submissions)

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• D. Lang, D. W. Hogg, K. Mierle, M. Blanton and S. Roweis: Astrometry.net: Blind Astrometric Calibration of Arbitrary Astronomical Images. aj 139:1782-1800 (2010) (eprint)

• Debian Astronomy Team
• Ole Streicher

• 0.70+dfsg-1 (stretch)

• 1 regular users
• 74 total installations (of 252457 submissions)

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• Debian Astro Team
• Vincent Prat

• 0.2-5 (stretch)

• 1 regular users
• 2 total installations (of 252457 submissions)

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• Debian Astronomy Team
• Ole Streicher

• 1.2 (stretch)

• 2 total installations (of 252457 submissions)

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• van Dokkum, P. G.: Cosmic-Ray Rejection by Laplacian Edge Detection. Publications of the Astronomical Society of the Pacific 113:1427 - 1420 (2001) (eprint)

• Debian Astronomy Team
• Ole Streicher

• 1.0.5-1 (stretch)

• 1 regular users
• 2 total installations (of 252457 submissions)

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• Debian Astronomy Team
• Ole Streicher

• 1.2.0-1 (stretch)

• 1 regular users
• 2 total installations (of 252457 submissions)

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• Gonzaga, S., Hack and W., Fruchter, A. and Mack, J.: The DrizzlePac Handbook. (2012) (eprint)

• Debian Astronomy Team
• Ole Streicher

• 1.3-2 (stretch)

• 1 total installations (of 252457 submissions)

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PyEphem fornisce un pacchetto ephem per Python per effettuare calcoli astronomici ad alta precisione. Le procedure numeriche sottostanti sono codificate in C e sono le medesime che guidano la popolare applicazione per astronomia XEphem il cui autore, Elwood Charles Downey, ha concesso generosamente il loro utilizzo in PyEphem.

Il nome ephem è abbreviazione della parola effemeridi (ephemers in inglese) che è il termine tradizionale per una tavola che fornisce la posizione di un pianeta, asteroide o cometa per una serie di date.

Questo pacchetto contiene la versione per Python 2 del pacchetto.

• Debian Astronomy Team
• Ole Streicher

• 3.7.6.0-6 (stretch)
• 3.7.6.0-7 (buster)

• 6 regular users
• 26 total installations (of 252457 submissions)

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• Debian Astronomy Maintainers
• Josue Ortega

• 1.2-1 (stretch)
• 1.10.1 (upstream)

• 1 total installations (of 252457 submissions)

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• Debian Astronomy Team
• Ole Streicher

• 2.6.1-2 (stretch)

• 1 total installations (of 252457 submissions)

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Gyoto mira a fornire un'infrastruttura per calcolare orbite e immagini tramite ray-tracing in relatività generale.

Questo pacchetto include anche un plugin di Gyoto che permette di scrivere nuovi oggetti di Gyoto nel linguaggio Python 2.

Questo pacchetto fornisce un'estensione per il linguaggio di programmazione Python 2 che espone le funzionalità di Gyoto. Consente di utilizzare Gyoto in modo interattivo dal prompt di Python o di eseguire complessi script di Gyoto.

• F. H. Vincent, T. Paumard, E. Gourgoulhon and G. Perrin: GYOTO: a new general relativistic ray-tracing code. Classical and Quantum Gravity 28:225011 (2011) (eprint)

• Debian Astronomy Maintainers
• Thibaut Paumard

• 1.3.1-1 (buster)
• 1.2.0-2 (stretch)

• 1 regular users
• 13 total installations (of 252457 submissions)

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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 2 version of the package.

• Debian Science Maintainers
• Andreas Tille

• 0.9.11+dfsg-2 (buster)
• 0.9.5+dfsg-2 (stretch)
• 0.8.0+dfsg.1-1 (jessie)

• 24 total installations (of 252457 submissions)

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• Debian Astronomy Team
• Ole Streicher

• 0.9.8-4 (stretch)

• 1 regular users
• 2 total installations (of 252457 submissions)

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Numpy (Numerical Python) contiene un potente oggetto array a N dimensioni, funzioni sofisticate (broadcasting), strumenti per l'integrazione di codice C/C++ e Fortran e utili funzionalità per algebra lineare, trasformate di Fourier e numeri casuali.

Numpy rimpiazza i moduli python-numeric e python-numarray che sono ora deprecati e non dovrebbero essere usati se non per il supporto a software datato.

• Sandro Tosi

• 1.12.1-3 (stretch)
• 1.8.2-2 (jessie)
• 1.16.2-1 (buster)

devel

lang:python, library

field

mathematics

role

devel-lib

• 432 regular users
• 241 recent
• 9128 total installations (of 252457 submissions)

• python-shapely

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• Debian Astronomy Team
• Ole Streicher

• 0.3-3 (stretch)
• 2.2.0 (upstream)

• 1 regular users
• 2 total installations (of 252457 submissions)

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• Debian Astro Team
• Vincent Prat

• 0.5.3-3 (stretch)

• 1 regular users
• 2 total installations (of 252457 submissions)

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Wrapper Python per FFTW, la veloce libreria FFT. Il fine ultimo è presentare un'interfaccia unitaria per tutte le possibili trasformazioni che FFTW può effettuare.

Sono gestite sia la DFT complessa che quella reale, così come assi arbitrari di array di forma e passo arbitrari, che la rendono quasi funzionalmente equivalente alle funzioni FFT standard e reali di numpy.fft (inoltre, gestisce il dtype clongdouble, mentre numpy.fft non lo fa).

pyFFTW ha una licenza BSD e non dovrebbe essere confuso con python-fftw, un modulo Python con licenza GPL che ha lo stesso intento di fornire collegamenti Python a FFTW3. Non deve nemmeno essere confuso con python-gpyfft che fornisce collegamenti alla libreria OpenCL FFT clFFT.

Questo pacchetto fornisce i collegamenti Python 2.

• Debian Science Maintainers
• Drew Parsons

• 0.11.1-2 (buster)
• 0.9.2+dfsg-2 (jessie)

• 4 total installations (of 252457 submissions)

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• Debian Astro Team
• Paul Sladen

• 0.4.2-1 (stretch)

• 1 total installations (of 252457 submissions)

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• P. L. Lim, R. I. Diaz and V. Laidler: PySynphot User’s Guide. (2015)

• Debian Astronomy Team
• Ole Streicher

• 0.9.8.5+dfsg-1 (stretch)

• 1 total installations (of 252457 submissions)

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• Debian Astronomy Team
• Ole Streicher

• 0.3.1-4 (stretch)

• 1 regular users
• 2 total installations (of 252457 submissions)

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scikit-image è una raccolta di algoritmi per l'elaborazione di immagini per Python. Esegue compiti come: caricamento, filtraggio, morfologia, segmentazione, conversione di colori e trasformazioni di immagini.

Questo pacchetto fornisce il modulo per Python 2.

• 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)

• Debian Science Maintainers
• Ole Streicher

• 0.12.3-8 (stretch)
• 0.14.2-2 (buster)
• 0.10.1-2 (jessie)
• 0.25.2 (upstream)

• 4 regular users
• 43 total installations (of 252457 submissions)

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• A. Ginsburg, T. Robitaille, C. Beaumont, E. Rosolowsky, A. Leroy, C. Brogan, T. Hunter, P. Teuben and D. Brisbin: Radio Astronomy Tools in Python: Spectral-cube, pvextractor, and more. Revolution in Astronomy with ALMA: The Third Year :363 (2015) (eprint)

• Debian Astronomy Team
• Ole Streicher

• 0.4.0-2 (stretch)

• 1 regular users
• 2 total installations (of 252457 submissions)

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• 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)

• Debian Astronomy Team
• Ole Streicher

• 0.7.4-2 (stretch)
• 6.1.0~rc1 (upstream)

• 1 total installations (of 252457 submissions)

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Il progetto yt ha lo scopo di produrre un ambiente scientifico integrato per porre domande di astrofisica e rispondere, in maniera collaborativa. Per fare ciò, comprende la creazione delle condizioni iniziali, l'esecuzione delle simulazioni e la dettagliata esplorazione e visualizzazione dei dati risultanti. Fornisce anche un'infrastruttura standard basata sull'interoperatività delle quantità fisiche tra i codici.

Questo pacchetto contiene la versione per Python 2 del pacchetto.

• M.J. Turk, B.D. Smith, J.S. Oishi, S. Skory, S.W. Skillman, T. Abel and M.L. Norman: yt: A Multi-code Analysis Toolkit for Astrophysical Simulation Data. ApJS 192:9 (2011) (eprint)

• Debian Astronomy Team
• BW Keller

• 3.5.0-1 (buster)
• 3.2.3-2 (stretch)

• 1 regular users
• 10 total installations (of 252457 submissions)

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The VOTable format is defined by the International Virtual Observatory Alliance to facilitate data exchange in astronomy. This library implements most of the specification and offers simple and advanced, streaming interfaces. Also included is a simple client to query TAP servers.

There are many other libraries to parse VOTables into python programs, the default probably being astropy's. This one is geared for maximal control, streaming, and the possibility to write fairly mad instance documents.

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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

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