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crocodile's Issues

'inv' function generality

Crocodile's 'inv' function is described as "Invert a hermitian-symetric two-dimensional grid. The hermitian symetric dimension is the second (last) index, like in numpy.fft":

"""Invert a hermitian-symetric two-dimensional grid.
.

AFAIUI, this is related to how the sample uv data are generated, see

v=numpy.hstack([v, numpy.conj(v)])
.

The question is: what if we use uv data generated by Oskar? Do they have the same structure (hermitean-symmetric)? And if they have more general structure then how should 'inv' look like in this general case?

Document gridding's data characteristics

The way gridding works, we have a few connected characteristics of the handled data:

  • In doimg, we "mirror" coordinates and conjugate visibilities. In my understanding, this is correct because it reflects "inverted" baselines.
  • This causes in turn causes the result of gridding to be hermitian
  • This property is what makes sure that the result image of the FFT is, in fact, real-valued

It would make the program easier to follow if this was spelled out explicitly.

Document results of Hogbom's CLEAN

As Anna commented in the Radio Cortex specification, Hogbom produces a clean image, a model image and residual. We believe this maps to comps+res, comps and res respectively, but this is never documented explicitly.

Hard-coded numbers in synthesis.py

Calls to wkernelaf in synthesis.py contain hard-coded numbes 257 and 15. Those would be better understood if they had text names. Also, should those be adjustable in any way?

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