Postprocessing Utilities ligo.skymap.postprocess.util
¶
Postprocessing utilities for HEALPix sky maps.
- ligo.skymap.postprocess.util.find_greedy_credible_levels(p, ranking=None)[source]¶
Find the greedy credible levels of a (possibly multi-dimensional) array.
- Parameters:
- pnp.ndarray
The input array, typically a HEALPix image.
- rankingnp.ndarray, optional
The array to rank in order to determine the greedy order. The default is
p
itself.
- Returns:
- clsnp.ndarray
An array with the same shape as
p
, with values ranging from0
top.sum()
, representing the greedy credible level to which each entry in the array belongs.
- ligo.skymap.postprocess.util.interp_greedy_credible_levels(x, xp, fp, right=None)[source]¶
Perform linear interpolation suitable for finding credible levels.
The linear interpolation is performed with the boundary condition that \(f(x) = 0\).
Examples
>>> xp = [1, 2, 3, 4, 5] >>> fp = [0.2, 0.4, 0.6, 0.8, 1.0] >>> interp_greedy_credible_levels([0, 0.5, 1.0, 1.5, 2.0], xp, fp) array([0. , 0.1, 0.2, 0.3, 0.4])
- ligo.skymap.postprocess.util.smooth_ud_grade(m, nside, nest=False)[source]¶
Resample a sky map to a new resolution using bilinear interpolation.
- Parameters:
- mnp.ndarray
The input HEALPix array.
- nestbool, default=False
Indicates whether the input sky map is in nested rather than ring-indexed HEALPix coordinates (default: ring).
- Returns:
- new_mnp.ndarray
The resampled HEALPix array. The sum of
m
is approximately preserved.