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Basic Gaia data simulation, manipulation, and analysis toolkit

Project description

Python toolkit for basic Gaia data simulation, manipulation, and analysis

PyGaia provides python modules for the simulation of Gaia data and their errors, as well modules for the manipulation and analysis of the Gaia catalogue data. In particular transformations between astrometric observables and phase space variables are provided as well as transformations between sky coordinate systems. Only (very) basic functionality is provided. Full blown simulations of Gaia data in all their gory detail requires the Java tools developed by the Gaia Data Processing and Analysis Consortium (DPAC) in particular its Coordination Unit 2 (CU2).

This toolkit is basically an implementation of the performance models for Gaia which are publicly available at: http://www.rssd.esa.int/index.php?project=GAIA&page=Science_Performance. In addition much of the material in chapter 4 of the book Astrometry for Astrophysics: Methods, Models, and Applications (2012, van Altena et al.) is implemented.

Note that the code in this package is not intended for accurate astrometry applications, such as predicting in detail astrometric paths of stars on the sky, or transforming between observation epochs.

THE CURRENT VERSION OF THE CODE (0.6) CALCULATES THE PRE-LAUNCH PERFORMANCE PREDICTIONS FOR GAIA. AS OF 2014-07-18 THE PERFORMANCE NUMBERS ARE UNDER REVISION FOLLOWING THE GAIA COMMISSIONING PERIOD. THE PYGAIA CODE WILL BE UPDATED ACCORDINGLY TOWARD THE END OF AUGUST 2014.

Documentation

All classes and methods/functions are documented so use the python help() function to find out more. More extensive documentation will follow.

Installation notes

This package was developed in a python 2.7 environment and you may experience problems if you have an older version installed. In particular the scripts in the examples folder will not run because they expect the argparse module to be present.

The following python packages are required:

For the plotting tools:

Attribution

Please acknowledge the Gaia Project Scientist Support Team and the Gaia Data Processing and Analysis Consortium (DPAC) if you used this code in your research.

License

Copyright (c) 2012-2013 Anthony Brown, Gaia Data Processing and Analysis Consortium

PyGaia is open source and free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Changelog

0.6 (July 2014)

  • Warning on upcoming changes in performance predictions, following the Gaia commissioning period
  • radial velocity horizons plot in examples folder

0.5 (August 2013)

  • Utilities for obtaining absolute magnitudes of stars in V and G.
  • Functions to obtain the upper and lower bounds on the astrometric parameter errors (corresponding to the sky regions with best/worst astrometric errors).
  • Proper motion error plot.
  • Parallax horizon plot.

0.4 (April 2013)

  • Added transformation of proper motions and of position and proper motion errors.

0.31 (February 2013)

  • Updated README. TODO added.

0.3 (February 2013)

  • Added documentation on installation requirements. Added the handling of an ImportError for the argparse module to the example scripts.

0.2 (February 2013)

  • Problems in setup.py fixed as well is bugs in the error simulation code.

0.1 (February 2013)

  • First release

0.0 (October 2012)

  • Creation from bits and pieces of python code that AB had lying around.

Project details


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1.21

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1.2

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1.1

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1.0

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0.83

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0.81

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0.31

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0.9

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0.8

This version
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0.6

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0.5

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0.4

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0.3

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PyGaia-0.6.zip (56.3 kB) Copy SHA256 hash SHA256 Source None Jul 22, 2014

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