diff options
Diffstat (limited to 'fg21sim/utils')
| -rw-r--r-- | fg21sim/utils/grid.py | 30 |
1 files changed, 19 insertions, 11 deletions
diff --git a/fg21sim/utils/grid.py b/fg21sim/utils/grid.py index 8831000..a3030ac 100644 --- a/fg21sim/utils/grid.py +++ b/fg21sim/utils/grid.py @@ -7,11 +7,11 @@ Grid utilities. import numpy as np -from scipy import ndimage -import healpy as hp import numba as nb +from scipy import ndimage from .draw import ellipse +from .healpix import ang2pix_ring @nb.jit(nopython=True) @@ -180,6 +180,9 @@ def make_grid_ellipse(center, size, resolution, rotation=None): return (lon, lat, gridmap) +@nb.jit(nb.types.Tuple((nb.int64[:], nb.float64[:]))( + nb.types.UniTuple(nb.float64[:, :], 3), nb.int64), + nopython=True) def map_grid_to_healpix(grid, nside): """Map the filled coordinate grid to the HEALPix map (RING ordering). @@ -213,17 +216,22 @@ def map_grid_to_healpix(grid, nside): XXX/TODO: - Implement the flux-preserving algorithm (reference ???) """ - lon, lat, gridmap = grid + # XXX: ``numba`` does not support using 2D array as indexes + lon = grid[0].flatten() + lat = grid[1].flatten() + gridmap = grid[2].flatten() phi = np.radians(lon) theta = np.radians(90.0 - lat) - ipix = hp.ang2pix(nside, theta, phi, nest=False) + ipix = ang2pix_ring(nside, theta, phi) # Get the corresponding input grid pixels for each HEALPix pixel - indexes, counts = np.unique(ipix, return_counts=True) - shape = (len(indexes), max(counts)) - datamap = np.zeros(shape) * np.nan - # TODO: how to avoid this explicit loop ?? + # XXX: ``numba`` currently does not support ``numpy.unique()`` + ipix_perm = ipix.argsort() + ipix_sorted = ipix[ipix_perm] + idx_uniq = np.concatenate((np.array([True]), + ipix_sorted[1:] != ipix_sorted[:-1])) + indexes = ipix_sorted[idx_uniq] + values = np.zeros(indexes.shape) for i, idx in enumerate(indexes): - pixels = gridmap[ipix == idx] - datamap[i, :len(pixels)] = pixels - values = np.nanmean(datamap, axis=1) + # XXX: ``numba`` does not support using 2D array as indexes + values[i] = np.mean(gridmap[ipix == idx]) return (indexes, values) |