GILDAS-Python binding

Transcription

1 GILDAS-Python binding Using Python from GILDAS, and vice-versa Sébastien BARDEAU, IRAM Grenoble Science Software User Meeting, 08-apr-2016

2 The GILDAS software GILDAS is a collection of state-of-the-art softwares oriented toward (sub-)millimeter radioastronomical applications (either single-dish or interferometer). It is daily used to reduce all data acquired with the IRAM 30M telescope and Plateau de Bure Interferometer PDBI (except VLBI observations). GILDAS is easily extensible. GILDAS is written in Fortran-90, with a few parts in C/C++ (mainly keyboard interaction, plotting, widgets). A kernel: SIC: Sympathetic Interpreter of Commands GreG: Grenoble Graphic Dedicated programs: ASTRO: ephemeris and observation preparation CLASS: single-dish spectra CLIC: calibration of the PdBI MAPPING: aperture synthesis and deconvolution... 08/04/2016 GILDAS Python binding 2

3 Gildas-Python binding: why? Back to 2007 goals: Provide Python functionalities to GILDAS users Provide GILDAS modules to Python users Allow GILDAS to be used simultaneously/interactively with other Python-ported softwares. Prepare users to Python and CASA Prepare a bridge between GILDAS and CASA 08/04/2016 GILDAS Python binding 3

4 Python: developed since 1990 by Guido von Rossum (a Monty Python fan), written in C. current (parallel) releases are Python (05-dec-2015) and (06-dec-2015). interpreted, interactive, object-oriented, extensible programming language. Syntax: Python (like C) is case-sensitive. Python uses indentation as block delimiters (no begin/end, or {}): 1 or more spaces, and always the same number for the same block. * % or $ are forbidden in identifiers (variable names).. (dot) has a special meaning (objects attributes or methods). * (see usingpython.py) Providing new features to python: Built-in modules * (see usingpython.py) External modules: Python developers community provides a large set of packages (modules) for many purposes. Installation: retrieve the module archive, expand it anywhere, setup.py script uses distutils module * (re)define your PYTHONPATH environment variable for non-standard installation. When installed, just import the module into Python. shell> python setup.py build shell> python setup.py install 08/04/2016 GILDAS Python binding 4

5 Arrays in Arrays in Python: Numeric / Numpy / Numarray modules array handling is inefficient in Python* - elements can be any kind of Python object: memory and CPU consuming Numpy provide a better handling * only values are stored, single or double precision Multidimensional-array arrangement in memory: C (and thus Python) uses row-major order (last dimension is contiguous in memory), and indices run from 0. Fortran (and thus GILDAS) uses column-major order (first dimension is contiguous in memory), and indices run from 1. (see usingpython.py) 08/04/2016 GILDAS Python binding 5

6 Requirements Machine / OS: 32 or 64 bits Any Linux, Mac OSX. Python: Versions 2.6, 2.7, 3.* (binaries + headers) Array module: Numpy (tested up to 1.9.2, already released) 08/04/2016 GILDAS Python binding 6

7 1: Using Python from GILDAS 'SIC\PYTHON' command: First call launches Python interpreter in background No arguments jumps to Python prompt * One python file name as argument executes it * Any other string is sent to Python interpreter * Using Python functions: Search in Python main name space for unknown functions called from SIC * Can accept a variable number of arguments * (see usingpygildas.sic, bessel.greg) (see usingpygildas.sic, onefile.py) 08/04/2016 GILDAS Python binding 7

8 2: Using GILDAS from Python Python modules: pysic and other modules launch the process in background provide useful functions * import variables into the Gildas dictionary. Dynamic definition and deletion. * (see usingpygildas.py) Import naming rules: Names are lowercased, and forbidden characters are converted: SIC ABC ABC%DEF Python abc abc.def Names can not overwrite Python commands ('import', 'def', 'del',...) or built-in objects ('range', 'file', 'type',...) Sharing variables: GILDAS process owns the allocated memory area Numpy arrays point to the same memory area (read and write). 08/04/2016 GILDAS Python binding 8

9 Demos Demos Import FITS file into GILDAS A GreG procedure (from GreG) (see importfits.greg) A Python script (from python) (see importfits.py) Crossed call SIC/LineDB and CLASS/Weeds: Extensions of Sic and Class at user level (i.e. using only class procedures and python scripts). (see dedicated talks, gildas doc and sources) 08/04/2016 GILDAS Python binding 9

10 Summary Call Python from GILDAS: 'PYTHON' command SIC> PYTHON Command-line Python arithmetic functions callable from GILDAS Call GILDAS from Python: pysic and py* modules >>> pysic.comm('command line') Specific functions (.exa(),...) Special attributes (.gdict) Variable sharing mechanism Re-entering is not supported Documentation is available in GILDAS sources ( cookbooks/gildas/gildas-python.tex ) and on GILDAS web page ( > GILDAS > Doc > GILDAS-Python ) 08/04/2016 GILDAS Python binding 10