uv_distribution_fill (From John Tobin)

[Bonnarel]

From John Tobin:
uv_distribution_fill - this definition seemed quite confusing to me as written it seems like you would always get an answer of 1/N_samples, I think it needs to be summation over i,j for n_cells with n_points >=1/n_cells. Maybe I am reading the definition incorrectly. The other issue with this definition is that it does not account for the fact that a dataset can have a large number of channels, where each is actually is own uv point. Each entry in a VO Table will be split into some number of channels, so this might need to be addressed and perhaps requires its own field. Finally, the uv filling factor will also be different depending on whether a user has continuum or spectral line observations in mind, continuum will have multi-frequency synthesis which implicitly increases its uv-coverage, while a spectral line applications will have worse uv-coverage implicitly.

[Bonnarel]

From John Tobin: uv_distribution_fill - this definition seemed quite confusing to me as written it seems like you would always get an answer of 1/N_samples, I think it needs to be summation over i,j for n_cells with n_points >=1/n_cells. Maybe I am reading the definition incorrectly. The other issue with this definition is that it does not account for the fact that a dataset can have a large number of channels, where each is actually is own uv point. Each entry in a VO Table will be split into some number of channels, so this might need to be addressed and perhaps requires its own field. Finally, the uv filling factor will also be different depending on whether a user has continuum or spectral line observations in mind, continuum will have multi-frequency synthesis which implicitly increases its uv-coverage, while a spectral line applications will have worse uv-coverage implicitly.

From François Bonnarel :

I see your point, and would like to have comments coming from our Astron and JIVE colleagues who originally proposed to characterize the uv coverage this way.

[matmanc]

About the first one I disagree. n_ij is exactly the number of samples that fall in that cell. So you would have 0 if there are no samples. If you want we can make it more explicit but I think it is formally correct.

Regarding the second point I agree the filling factor can change if you are only considering a band or a wider frequency range. I would also add that if you do a timeseries (so instead of using all the time samples you use a sub sample) you will have a even poorer filling factor. I honestly dont know a way out of this. The only thing that comes into my mind would be to consider a uv_distribution_fill_min/max considering the extreme cases. For uv_distribution_fill_min (one time sample one channel) or uv_distribution_fill_max ( all time samples all channels/frequencies) . And maybe add a characteristic value for which the observation configuration was requested?

What is your idea John?