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Python, IPython, matplotlib links provided on the left.
Startup
bash-2.05b$ casapy
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Available tools:
cb (calibrater) im (imager)
ms (MS) tb (table)
mp (MS plot) tp (table plot)
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Available tasks:
imager: clean, feather, invert, mosaic, (wproj)
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type 'exp tool' or 'exp tool.function' for help
CASA [1]:
Some key interface differences between casa (python) and aips++ (glish) for
those familiar with AIPS++.
- No tool constructors (more data-centric).
- No ':=' or ';' needed.
- On-line help (exp)
- CNTRL-C
- Memory usage
- casa 27M footprint (c.f. aips++ 103M starting)
- pre-loading imager, calibrater, ms, and imager tasks (adds 1M to startup)
- Startup time (casa: 1.9s (ballista), aips++: 10.1s (ballista))
- Performance (approx. 15% faster on *tested* scripts)
- Python is 0-based. Awkward but uniform. MS selection solves much of this.
- Error handling (loquacious versus laconic)
glish
: Caught an exception! Event type=run exception=RecordInterface: field
FLAG_LEVEL is unknown
File: servers.g, Line 1009
Stack: .(), ms.g line 419
.()
python
Exception Reported: RecordInterface: field FLAG_LEVEL is unknown
For glish-users
- Detailed functionality has been migrated over and is usable nearly identically as before.
Python imaging
im.open('ngc5921_src.split.ms')
im.setdata(mode='channel',nchan=[46],start=[1],step=[1],fieldid=[0])
im.setimage(nx=256,ny=256,cellx=quantity(15.,'arcsec'),celly=quantity(15.,'arcsec'),mode='channel',nchan=46,fieldid=0)
im.weight(type='briggs',rmode='norm',robust=0.5)
im.clean(algorithm='hogbom',niter=6000,gain=0.1,threshold=quantity(8.,'mJy'),model=['ngc5921_py.model'],image=['ngc5921_py.image'],residual=['ngc5921_py.residual'],mask=[''])
Glish imaging
im:=imager('ngc5921_src.split.ms')
im.setdata(mode='channel',nchan=46,start=1,step=1,fieldid=1)
im.setimage(nx=256,ny=256,cellx='15arcsec',celly='15arcsec',mode='channel',nchan=46,fieldid=1)
im.weight(type='briggs',rmode='norm',robust=0.5)
im.clean(algorithm='hogbom',niter=6000,gain=0.1,threshold='8mJy',model='gtest2.model',image='gtest2.image',residual='gtest2.residual',mask='')
- Glish records -> Python dictionaries
- dict.keys()
- dict.sort()
- dict.has_key('keyname')
- dict.values()
- dict['keyname']
- del dict['keyname']
- range specifications
CASA [11]: range(4,7)
Out[11]: [4, 5, 6]
CASA [12]: range(1,3)
Out[12]: [1, 2]
CASA [13]: range(4,7)+range(55,60)
Out[13]: [4, 5, 6, 55, 56, 57, 58, 59]
- quantities (for now)
CASA [4]: quan=quantity(5.,'km/s')
CASA [5]: quan.value
Out[5]: 5.0
CASA [6]: quan.units
Out[6]: 'km/s'
Functionality Update:
- Previously, parts of imager completed; calibrater stubbed
- Now:
imager 30 methods, 8 untested, 6 not implemented, 1 abort, 0 fail
calibrater 16 methods, 1 untested, 3 not implemented, 0 abort, 1 fail
ms 29 methods, 6 untested; 3 not implemented, 0 abort, 3 fail
tables stubbed
tableplot stubbed
msplot stubbed
---
autoflag started
measures started
- help system enabled with argument information
In [1]: exp im.setdata
Set the data parameters selection for subsequent processing :
mode = velocity
nchan = [ 1 ]
start = [ 0 ]
step = [ 1 ]
mstart = { value=0.0, units=km/s }
mstep = { value=0.0, units=km/s }
spwid = [ 0 ]
fieldid = [ 0 ]
msselect
async = false
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Example Reduction:
- NGC 5921
- All regression tests being ported
Tasks:
- Focus area for Focus Group!
Why Matplotlib?
- interface (zoom, cursor, etc)
- many point rendering
- publication quality (many formats bmp, eps, jpg, png, ps, svg)
- use TeX labelling
To Do:
- complete functionality for initial release
- improved logging
- matplotlib
- documentation
- ----
- interface working group in spring (March?)
Please send any comments or questions about CASA or AIPS++
to aips2-requests@nrao.edu
Copyright © 1995-2000,2001,2002,2003,2004 Associated Universities Inc.,
Washington, D.C.
This code is available under the terms of the GNU General Public Lincense
Modified on
Thursday, 31-Jul-2008 14:54:57 MDT
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