Custom Query (241 matches)

ASAP> s=scantable("../Data_MPCOR/2006-05-03_2100-M136.rpf","../Data_MPCOR/2006-05-03_2348-M136.rpf","../Data_MPCOR/2006-05-04_0524-M136.rpf") Auto averaging integrations Importing ../Data_MPCOR/2006-05-03_2100-M136.rpf...

Traceback (most recent call last):

File "<console>", line 1, in ? File "/usr/local/lib/python2.3/site-packages/asap/scantable.py", line 66, in init

self._fill([filename],unit, average)

File "/usr/local/lib/python2.3/site-packages/asap/scantable.py", line 1510, in _fill

self.set_fluxunit(unit)

RuntimeError?: Unit::check Illegal unit string '../Data_MPCOR/2006-05-04_0524-M136.rpf'

The file "../Data_MPCOR/2006-05-04_0524-M136.rpf" contains ok data, I can run scantable on it separately, with success.

I'm not sure of the best way to load in multiple files. At the moment, there is a problem with averaging multiple scans together so I'm using scantable. depending on the limitations, I'd suggest that having a limit of only 4 files is not very useful for those needing to average many files together. I have >10 files that I need to avaerage together, for example.

I downloaded

​ftp://ftp.atnf.csiro.au/pub/software/asap/asap_linux.tar.bz2

on 2006-05-25

I was installing asap on Debian etch (testing) and received the following error message:

Loading ASAP...
------------------------------------------------------------
Traceback (most recent call last):
  File "<string>", line 1, in ?
  File "/usr/local/lib/python2.3/site-packages/asap/__init__.py", line
276, in ?
    from asap._asap import Log as _asaplog
ImportError: libboost_python-gcc-mt-1_32.so.1.32.0: cannot open shared
object file: No such file or directory

WARNING: Loading of asap failed.

------------------------------------------------------------
Traceback (most recent call last):
  File "<string>", line 1, in ?
NameError: name 'welcome' is not defined

WARNING: Failure executing code: 'print welcome()'

ASAP>

I do have /usr/lib/libboost_python-gcc-mt-1_33_1.so.1.33.1

I also have the unversioned symlink /usr/lib/libboost_python.so - see here

  ls -l /usr/lib/libboost*
  lrwxrwxrwx 1 root root     36 2006-05-25 20:54 /usr/lib/libboost_python-gcc-1_33_1.so ->
      libboost_python-gcc-1_33_1.so.1.33.1
  -rw-r--r-- 1 root root 268716 2006-03-23 04:09 /usr/lib/libboost_python-gcc-1_33_1.so.1.33.1
  lrwxrwxrwx 1 root root     39 2006-05-25 20:54 /usr/lib/libboost_python-gcc-mt-1_33_1.so ->
      libboost_python-gcc-mt-1_33_1.so.1.33.1
  -rw-r--r-- 1 root root 268716 2006-03-23 04:09 /usr/lib/libboost_python-gcc-mt-1_33_1.so.1.33.1
  lrwxrwxrwx 1 root root     32 2006-05-25 20:54 /usr/lib/libboost_python.so ->
      libboost_python-gcc-mt-1_33_1.so

Is it not possible to have the code use different versions of this library?

Support for MX observing with multibeam is needed. MX mode is observing a point source, cycling through each beam. There are a numbr of ways this could be implemented, consult with Jim Caswell on possible solutions. One possible solution is a multistep process which should work for general MX observations:

• Form a reference spectra by averaging the data. This could either be done as a meadian average for each beam for all data OR making a mean average of each beam for each making sure to not include spectra including the source (see below for discussion on reference beam).

• Use this average spectra as a reference in a quotient spectra with original data

• Optionally data the quotient data and discard beams that were not on source

• Optionally average the onsource beam data together (ie average data from each beam together)

For this to work the onsource beam need top be known. This is called (in TCS or livedata) the reference beam. Apparently livedata knows which beam this is. Consultation with Mark C. is probably needed to find out how to know this