def reproject_car_to_hpx(input_data,
coord_system_out,
nside,
order=1,
nested=False):
import healpy as hp
from reproject.wcs_utils import convert_world_coordinates
from reproject.healpix.utils import parse_coord_system
data, wcs_in = input_data
npix = hp.nside2npix(nside)
theta, phi = hp.pix2ang(nside, np.arange(npix), nested)
lon_out = np.degrees(phi)
lat_out = 90.0 - np.degrees(theta)
# Convert between celestial coordinates
coord_system_out = parse_coord_system(coord_system_out)
with np.errstate(invalid="ignore"):
lon_in, lat_in = convert_world_coordinates(
lon_out, lat_out, (coord_system_out, u.deg, u.deg), wcs_in)
# Look up pixels in input system
yinds, xinds = wcs_in.wcs_world2pix(lon_in, lat_in, 0)
# Interpolate
data = np.pad(data, 3, mode="wrap")
healpix_data = map_coordinates(data, [xinds + 3, yinds + 3],
order=order,
mode="wrap",
cval=np.nan)
return healpix_data, (~np.isnan(healpix_data)).astype(float)
def reproject_car_to_hpx(input_data, coord_system_out, nside, order=1, nested=False):
import healpy as hp
from reproject.wcs_utils import convert_world_coordinates
from reproject.healpix.utils import parse_coord_system
data, wcs_in = input_data
npix = hp.nside2npix(nside)
theta, phi = hp.pix2ang(nside, np.arange(npix), nested)
lon_out = np.degrees(phi)
lat_out = 90.0 - np.degrees(theta)
# Convert between celestial coordinates
coord_system_out = parse_coord_system(coord_system_out)
with np.errstate(invalid="ignore"):
lon_in, lat_in = convert_world_coordinates(
lon_out, lat_out, (coord_system_out, u.deg, u.deg), wcs_in
)
# Look up pixels in input system
yinds, xinds = wcs_in.wcs_world2pix(lon_in, lat_in, 0)
# Interpolate
data = np.pad(data, 3, mode="wrap")
healpix_data = map_coordinates(
data, [xinds + 3, yinds + 3], order=order, mode="wrap", cval=np.nan
)
return healpix_data, (~np.isnan(healpix_data)).astype(float)
def _get_input_pix_celestial(wcs_in, wcs_out, shape_out):
"""Get the pixel coordinates of the pixels in an array of shape ``shape_out`` in the input WCS."""
from reproject.wcs_utils import convert_world_coordinates
# TODO: for now assuming that coordinates are spherical, not
# necessarily the case. Also assuming something about the order of the
# arguments.
# Generate pixel coordinates of output image
xp_out, yp_out = np.indices(shape_out, dtype=float)[::-1]
# Convert output pixel coordinates to pixel coordinates in original image
# (using pixel centers).
xw_out, yw_out = wcs_out.wcs_pix2world(xp_out, yp_out, 0)
xw_in, yw_in = convert_world_coordinates(xw_out, yw_out, wcs_out, wcs_in)
xp_in, yp_in = wcs_in.wcs_world2pix(xw_in, yw_in, 0)
return xp_in, yp_in
def _get_input_pix_celestial(wcs_in, wcs_out, shape_out):
"""
Get the pixel coordinates of the pixels in an array of shape ``shape_out``
in the input WCS.
"""
from reproject.wcs_utils import convert_world_coordinates
# TODO: for now assuming that coordinates are spherical, not
# necessarily the case. Also assuming something about the order of the
# arguments.
# Generate pixel coordinates of output image
xp_out, yp_out = np.indices(shape_out, dtype=float)[::-1]
# Convert output pixel coordinates to pixel coordinates in original image
# (using pixel centers).
xw_out, yw_out = wcs_out.wcs_pix2world(xp_out, yp_out, 0)
xw_in, yw_in = convert_world_coordinates(xw_out, yw_out, wcs_out, wcs_in)
xp_in, yp_in = wcs_in.wcs_world2pix(xw_in, yw_in, 0)
return xp_in, yp_in
