Static frequency mask estimation from visibility data

[ljgray]

The overall goal of this PR is to implement a task to come up with a static RFI mask from visibility data directly, without having to rely on a hard-coded set of bad channels.

This produces a flagging metric by reducing over baselines using the existing ReduceChisq code as follows:

• The chi2 is computed over cross-pol baselines only, and excludes baselines < 5 meters.
• Weighting is done by dividing by baseline redundancy (effectively up-weighting baselines with lower redundancy), which highlights faint frequency bands which are only otherwise visible in the high-delay chisq metric.

Flagging is then done using a simple 1D MAD metric over the 1D median in time of the chisq metric. Only nighttime data is included in the median (the hook is implemented in a ch_pipeline PR). It uses an updated version of the arPLS baseline-fitting code, which is better able to handle the lack of hard-coded static mask.

This PR does the following:

• Updated the scale_invariant_rank operation to be a bit faster
• Adds options to the MaskBaselines task to mask polarisation and to optionally combine the mask using an and operation
• Extends the ReduceBase task with a hook for custom weights
• Updates the penalized_least_squares implementation to support different weighting schemes
• Replaces the old narrowband vis flagging task with this new static RFI mask task

This code all works and is tested. This method does not appear to overflag, although there is absolutely room for improvement.

[ljgray]

@sjforeman

[tristpinsm]

sorry, was hoping to take a look this pm

[ljgray]

sorry, was hoping to take a look this pm

No worries. It won't break anything, so it's really just a review of what's being implemented in this task, which I'd ideally like to improve on in the future anyway.