Smoothbandpass: Difference between revisions

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'''Return to [[Analysis Utilities]]'''


Until casa is able to smooth the uv data prior to solving for bandpass, it may be useful to smooth the solution instead, although this is not as good as the former method. After doing this, you can use plotbandpass to overlay the smoothed solution over the original solution. *Note that if the signal to noise of your original solution is too low, this method will introduce unphysical spikes in the output solution!*
Until casa is able to smooth the uv data prior to solving for bandpass, it may be useful to smooth the solution instead, although this is not as good as the former method. After doing this, you can use plotbandpass to overlay the smoothed solution over the original solution. ''Note that if the signal to noise of your original solution is too low, this method will introduce unphysical spikes in the output solution!''


<source lang="python">
<source lang="python">

Revision as of 15:16, 3 January 2012

Return to Analysis Utilities

Until casa is able to smooth the uv data prior to solving for bandpass, it may be useful to smooth the solution instead, although this is not as good as the former method. After doing this, you can use plotbandpass to overlay the smoothed solution over the original solution. Note that if the signal to noise of your original solution is too low, this method will introduce unphysical spikes in the output solution!

au.smoothbandpass(help=True)
Usage: smoothbandpass(caltable, window_len=20, window='flat', method='ri')
The output table will have '_smoothXXwindow_method' appended to the name,
where 'XX'=window_len and 'window' is the window type.  The window 
type options are: 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'.
Method types are 'ri' = real & imaginary or 'ap' = amp & phase

For more info, see the Wikipedia page on window functions.