Closed zonca closed 2 years ago
I'm already doing map2alm and alm2map in:
https://github.com/galsci/pysm/blob/main/pysm3/models/template.py#L99-L152
so it is as easy as providing an extra parameter target_nside
and use that for alm2map
from @seclark:
Would make sense to me to let people configure this (with guidelines) but default to running at 2048 for output maps with N_side <= 1024, and default to run at 2*N_side for output maps with 1024 <= N_side<= 4096. i.e., default to our recommended choices.
suggestion my Martin Reinecke, what if we used Gauss Legendre (GL) pixelization internally?
https://github.com/galsci/pysm/issues/92#issuecomment-948962496
So:
I anyone used GL pixelization before, please jump in. Otherwise, I'll give it a try myself using ducc
thanks to @mreineck providing an example of using ducc0
and GL pixels, I made a comparison focused on PySM, I posted the notebook here where it is a bit easier to read (click on button to get the notebook and try it yourself):
Good to see that this works well!
Just one word of caution: since the rings of a GL grid are not equidistant in theta, the GL map plots in the notebook can only be a rough approximantion to the real map; doing this accurately requires using the exact coordinates of every ring (obtainable, e.g., via ducc0.misc.GL_thetas()
) and telling them to matplotlib
.
will try with a more anisotropic map, for example the GNILC dust maps after adding small scales (#97), which is one of our use cases. We want to verify if error in HEALPix goes higher in such maps.
@seclark @brandonshensley I have added a section in the docs about dealing with Nside, see the commit reference above here.
target_nside
parameter, so people can smooth a 1024 map and get a 512 output without transforming twice.Originally posted by @zonca in https://github.com/galsci/pysm/issues/90#issuecomment-947830102