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# Copyright (c) 2016 Weitian LI <liweitianux@live.com>
# MIT license
"""
FITS WCS (world coordinate system) reprojection utilities.
"""
import logging
import numpy as np
from scipy.ndimage import map_coordinates
import astropy.units as au
from astropy.coordinates import Galactic, UnitSphericalRepresentation
from astropy.wcs import WCS
from astropy.wcs.utils import wcs_to_celestial_frame
from astropy.io import fits
import healpy as hp
from .healpix import _make_healpix_header
logger = logging.getLogger(__name__)
def _convert_wcs(lon_in, lat_in, frame_in, frame_out):
"""Convert (longitude, latitude) coordinates from the input frame to
the specified output frame.
Parameters
----------
lon_in : 1D `~numpy.ndarray`
The longitude to convert, unit degree, [0, 360)
lat_in : 1D `~numpy.ndarray`
The latitude to convert, unit degree, [-90, 90]
frame_in, frame_out : tuple or `~astropy.wcs.WCS`
The input and output frames, which can be passed either as a tuple of
``(frame, lon_unit, lat_unit)`` or as a `~astropy.wcs.WCS` instance.
Returns
-------
lon_out, lat_out : 1D `~numpy.ndarray`
Output longitude and latitude in the output frame
References
----------
[1] reproject - wcs_utils.convert_world_coordinates()
https://github.com/astrofrog/reproject
"""
if isinstance(frame_in, WCS):
coordframe_in = wcs_to_celestial_frame(frame_in)
lon_in_unit = au.Unit(frame_in.wcs.cunit[0])
lat_in_unit = au.Unit(frame_in.wcs.cunit[1])
else:
coordframe_in, lon_in_unit, lat_in_unit = frame_in
#
if isinstance(frame_out, WCS):
coordframe_out = wcs_to_celestial_frame(frame_out)
lon_out_unit = au.Unit(frame_out.wcs.cunit[0])
lat_out_unit = au.Unit(frame_out.wcs.cunit[1])
else:
coordframe_out, lon_out_unit, lat_out_unit = frame_out
#
data = UnitSphericalRepresentation(lon_in*lon_in_unit, lat_in*lat_in_unit)
coords_in = coordframe_in.realize_frame(data)
coords_out = coords_in.transform_to(coordframe_out)
data_out = coords_out.represent_as("unitspherical")
lon_out = data_out.lon.to(lon_out_unit).value
lat_out = data_out.lat.to(lon_out_unit).value
return lon_out, lat_out
def _image_to_healpix(image, wcs, nside, order=1, hemisphere=None):
"""Convert image in a normal WCS projection to HEALPix data of *RING*
ordering and *Galactic* coordinate system.
Parameters
----------
image : 2D `~numpy.ndarray`
Input image array to be reprojected into HEALPix format.
wcs : `~astropy.wcs.WCS`
The WCS of the input image.
order : int, optional
The order of the spline interpolation, valid range: 0-5
hemisphere : str, optional
Specify the hemisphere on which the pixels to be reprojected.
Valid values: `"N"/"NORTH"/"NORTHERN"` (northern),
`"S"/"SOUTH"/"SOUTHERN"` (southern), or `None`.
If None, then no pixel filtering applied.
Note: northern hemisphere includes the equator, while southern not.
Returns
-------
hpdata : 1D `~numpy.ndarray`
Projected HEALPix data array (1D) of length 12*nside*nside.
The invalid pixels are filled with value NaN (`np.nan`).
NOTE
----
Since the HEALPix map is full-sky, however, the input image may contains
only part of the full sky (e.g., one of the ZEA-projected image contains
only either northern or southern Galactic hemisphere), so the argument
`hemisphere` should be specified if applicable.
Otherwise, the WCS (of input image) can NOT correctly convert the
requested sky coordinates to the pixels in the input image.
If the requested coordinates beyond the available scope of the input
image, then the converted pixel positions may be negative or even WRONG.
References
----------
[1] reproject - healpix.core.image_to_healpix()
https://github.com/astrofrog/reproject
"""
if (hemisphere is not None) and (
hemisphere.upper() not in ["N", "NORTH", "NORTHERN",
"S", "SOUTH", "SOUTHERN"]):
raise ValueError("invalid hemisphere: {0}".format(hemisphere))
#
npix = hp.nside2npix(nside)
hpidx = np.arange(npix).astype(np.int)
# Calculate the longitude and latitude in frame of output HEALPix
theta, phi = hp.pix2ang(nside, hpidx, nest=False)
lon_hp = np.degrees(phi)
lat_hp = 90.0 - np.degrees(theta)
# Convert between the celestial coordinate systems
coordsys_hp = Galactic()
frame_hp = (coordsys_hp, au.deg, au.deg)
lon_in, lat_in = _convert_wcs(lon_hp, lat_hp, frame_hp, wcs)
# Filter the pixels on the specified hemisphere
if hemisphere is None:
mask = np.ones(lat_in.shape).astype(np.bool)
elif hemisphere.upper() in ["N", "NORTH", "NORTHERN"]:
# northern hemisphere (include the equator)
mask = lat_in >= 0.0
else:
# southern hemisphere
mask = lat_in < 0.0
lon_in = lon_in[mask]
lat_in = lat_in[mask]
# Look up pixels in the input coordinate system
# NOTE: note the order of returns: (Y, X)
yi, xi = wcs.wcs_world2pix(lon_in, lat_in, 0)
# Interpolate to obtain the HEALPix data from the input image
data = map_coordinates(image, [xi, yi], order=order,
mode="constant", cval=np.nan)
# Make the HEALPix array with above hemisphere mask considered
hpdata = np.zeros(shape=npix, dtype=data.dtype)
hpdata[mask] = data
hpdata[~mask] = np.nan
return hpdata
def zea2healpix(img1, img2, nside, order=1, inpaint=False,
append_history=None, append_comment=None):
"""Reproject the maps in ZEA (zenithal/azimuthal equal area) projection
to Galactic frame and organize in HEALPix format.
Parameters
----------
img1, img2 : str or `~astropy.io.fits.PrimaryHDU`
Two input ZEA-projected FITS files
nside : int
Nside for the output HEALPix data
order : int, optional
Interpolation order, valid range: 0-5
inpaint : bool, optional
Whether to inpaint the missing pixels
append_history : list[str], optional
Append the provided history to the output FITS header
append_comment : list[str], optional
Append the provided comment to the output FITS header
Returns
-------
hp_data : 1D `~numpy.ndarray`
Reprojected HEALPix data
hp_header : `~astropy.io.fits.Header`
FITS header for the reprojected HEALPix data
NOTE
----
- One ZEA-projected FITS file only contains either the northern Galactic
hemisphere (LAM_NSGP=1), or southern Galactic hemisphere (LAM_NSGP=-1).
Thus two ZEA-projected FITS files should both be provided to get the
full-sky map.
- The two reprojected HEALPix data are simply added to compose the
full-sky HEALPix map. Duplicate/overlapping pixels are warned.
- The combined full-sky HEALPix map may still have some missing pixels,
which is also warned.
TODO: inpaint the missing pixels by interpolation
"""
if isinstance(img1, str):
img1 = fits.open(img1)[0]
if isinstance(img2, str):
img2 = fits.open(img2)[0]
zea_img1, zea_hdr1 = img1.data, img1.header
zea_img2, zea_hdr2 = img2.data, img2.header
ZEA_NSGP = {1: "Northern", -1: "Southern"}
zea_hemisphere1 = ZEA_NSGP.get(zea_hdr1["LAM_NSGP"])
zea_hemisphere2 = ZEA_NSGP.get(zea_hdr2["LAM_NSGP"])
logger.info("Read ZEA image1: {0}, shape {1}".format(
zea_hemisphere1, zea_img1.shape))
logger.info("Read ZEA image2: {0}, shape {1}".format(
zea_hemisphere2, zea_img2.shape))
zea_wcs1 = WCS(zea_hdr1)
zea_wcs2 = WCS(zea_hdr2)
logger.info("Reproject ZEA images to HEALPix ...")
hp_data1 = _image_to_healpix(zea_img1, zea_wcs1, nside=nside, order=order,
hemisphere=zea_hemisphere1.upper())
hp_data2 = _image_to_healpix(zea_img2, zea_wcs2, nside=nside, order=order,
hemisphere=zea_hemisphere2.upper())
# Merge the two HEALPix data
hp_footprint1 = (~np.isnan(hp_data1)).astype(np.int)
hp_footprint2 = (~np.isnan(hp_data2)).astype(np.int)
hp_data1[np.isnan(hp_data1)] = 0.0
hp_data2[np.isnan(hp_data2)] = 0.0
hp_data = hp_data1 + hp_data2
logger.info("Done reprojection and merge two hemispheres")
# Duplicated pixels and missing pixels
pix_dup = (hp_footprint1 + hp_footprint2) == 2
if pix_dup.sum() > 0:
logger.warning("Reprojected HEALPix data has %d duplicated pixel(s)" %
pix_dup.sum())
pix_missing = (hp_footprint1 + hp_footprint2) == 0
if pix_missing.sum() > 0:
logger.warning("Reprojected HEALPix data has %d missing pixel(s)" %
pix_missing.sum())
# XXX/TODO: inpaint
# HEALPix FITS header
header = zea_hdr1.copy(strip=True)
keys = ["CTYPE1", "CTYPE2", "CRPIX1", "CRPIX2", "CRVAL1", "CRVAL2",
"CD1_1", "CD1_2", "CD2_1", "CD2_2",
"LONPOLE", "LAM_NSGP", "LAM_SCAL"]
for k in keys:
if k in header:
del header[k]
hp_header = _make_healpix_header(header, nside=nside,
append_history=append_history,
append_comment=append_comment)
logger.info("Made HEALPix FITS header")
return (hp_data, hp_header)
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