Jupyter notebooks to demonstrate two wide field imaging algorithms: N-Faceting and the improved W-stacking
🍎 Updated on 16 January 2021: now we have decreased the number of w-planes by a factor of 2. -- Andre Offringa's suggestion
Please refer to W-stacking-improved Optimised with decreased w-planes (works for both odd and even W).ipynb
🍎 Updated on 31 December 2020: now the correcting function on z-axis can be calculated more accurately - adequate interpolation of the gridding correction function with your nominated number of orders -- Sze's input
Please refer to Sze - New Interpolation on Z - W-stacking-improved Optimised (works for both odd and even W).ipynb
🍎 Updated early December 2020: Please refer to W-stacking-improved Optimised (works for both odd and even W).ipynb
The W-stacking-improved Optimised series jupyter notebooks are ready for you to try out. You can even exchange the gridding function as you like.
📙 The default gridding function used is still our least-misfit gridding function. See paper https://doi.org/10.1093/mnras/stz2970 and Github repo https://github.com/SzeMengTan/OptimalGridding for reference.
The paper and codes are on the way.
haoyang.ye AT cantab.net
Description of the algorithms can be found in my thesis (https://doi.org/10.17863/CAM.39448). The paper is on the way.
Please consult for reference.
Ye, H. (2019). Accurate image reconstruction in radio interferometry (Doctoral thesis). https://doi.org/10.17863/CAM.39448
Haoyang Ye, Stephen F Gull, Sze M Tan, Bojan Nikolic, Optimal gridding and degridding in radio interferometry imaging, Monthly Notices of the Royal Astronomical Society, Volume 491, Issue 1, January 2020, Pages 1146–1159, https://doi.org/10.1093/mnras/stz2970