zero_levels contains utilities to estimate and remove monopole and dipole zero levels in HEALPix maps, plus simple helpers to store iterative fit results. Code based on Wehus et al. 2017.
pip install -e .For test dependencies:
pip install -e .[test]import numpy as np
from zero_levels import TTplots
nside = 256
maps = np.vstack([map_1, map_2, map_3])
tt = TTplots(nside=nside, nside_cluster=16)
mono_dipole = tt.calculate_mono_dipole(maps)
corrected_maps = tt.dep_remove_mono_dipole(maps, mono_dipole)If one map has a fixed monopole or dipole, pass fixed_pars, for example fixed_pars={1: "mono"}.
This project is licensed under the GNU General Public License v3.0. See LICENSE.