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author | Aaron LI <aaronly.me@outlook.com> | 2016-10-10 15:50:17 +0800 |
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committer | Aaron LI <aaronly.me@outlook.com> | 2016-10-10 15:50:17 +0800 |
commit | 2d1bd712c8efed8222c95371adec85bc69100439 (patch) | |
tree | 21c3ddf5354a35b4e71ff4b41c3e716bc54cbe64 /fg21sim/utils/reproject.py | |
parent | c1c5b3d5e899f8e385c90aae4ff881ecad3c7422 (diff) | |
download | fg21sim-2d1bd712c8efed8222c95371adec85bc69100439.tar.bz2 |
utils/reproject.py: Implement zea2healpix()
The "zea2healpix()" function reprojects the maps in ZEA
(zenithal/azithumal equal area) projection to HEALPix data in Galactic
frame with RING ordering.
The other two helper functions "_image_to_healpix()" and "_convert_wcs()"
are almost copied from the "reproject" project [1]. Thanks!
TODO:
* Add some more logging
* Implement the "inpaint" argument to inpaint the HEALPix map if exists
missing pixels
[1] reproject: https://github.com/astrofrog/reproject
Diffstat (limited to 'fg21sim/utils/reproject.py')
-rw-r--r-- | fg21sim/utils/reproject.py | 240 |
1 files changed, 240 insertions, 0 deletions
diff --git a/fg21sim/utils/reproject.py b/fg21sim/utils/reproject.py new file mode 100644 index 0000000..b129dc6 --- /dev/null +++ b/fg21sim/utils/reproject.py @@ -0,0 +1,240 @@ +# 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) |