Channel average

Channel averaging highlights using mstransform and split

Both mstransform & split support averaging data by frequency channel.  In split the amount of channel averaging (if any) is set by top-level parameter width.

width  = 1     # Number of channels to average to form one output channel

In mstransform this capability is accessed by specifying chanaverage=True and setting the resulting sub-parameter chanbin, as shown here:  

chanaverage = True      # Average data in channels.
chanbin     = 1         # Width (bin) of input channels to average to form an output channel.

Some new features of split / mstransform relative to the old implementation of split are as follows

    • oldsplit performs a flat average taking into account only the FLAG column, whereas mstransform / split use both FLAG and spectral weights (when present), resulting in a weighted average. To be specific WEIGHT_SPECTRUM is used when averaging CORRECTED_DATA, and SIGMA_SPECTRUM is used when averaging the DATA column.
    • Also mstransform / split are able to transform the input WEIGHT/SIGMA_SPECTRUM according to the rules of error propagation that apply to a weighted average, which result in an output weight equals to the sum of the input weights. For a detailed reference see, Data Reduction and Error Analysis [1].
    • Both mstransform / split drop the last output channel bin when there are not enough contributors to fully populate it. For instance, if the input SPW has 128 channels and chanbin is 10, the resulting averaged SPW would have 12 channels and not 13 channels.

The chanbin parameter can be either a scalar or a vector. In the former case, the same chanbin is applied to all the spectral windows. In the second case, each element of the chanbin vector will apply to the selected spectral windows. Obviously the size of the chanbin vector and the number of selected spectral windows have to match.

If spw combination and channel average are used together (combinespws=True, chanaverage = True), the chanbin parameter can only be a scalar. This is due to the fact that channel average applies to the already spw combined MS, which contains one single spw.

Citation Number 1
Citation Text Bevington & Robinson, 3rd Ed., McGraw Hill, 2003