diff options
Diffstat (limited to 'astro')
| -rwxr-xr-x | astro/oskar/montage_skypatch.py | 251 |
1 files changed, 251 insertions, 0 deletions
diff --git a/astro/oskar/montage_skypatch.py b/astro/oskar/montage_skypatch.py new file mode 100755 index 0000000..5da855b --- /dev/null +++ b/astro/oskar/montage_skypatch.py @@ -0,0 +1,251 @@ +#!/usr/bin/env python3 +# +# Copyright (c) 2018 Aaron LI <aly@aaronly.me> +# MIT License +# + +""" +Montage a list of sky patches (e.g., simulated sky maps of radio halos +of 10x10 deg^2) to create a large map (e.g., hemisphere) for OSKAR +simulation to help investigate the far side confusion noise (FSCN). + +Configuration file (YAML format) +-------------------------------- +nside: 8 # npix=768, pixsize~7.33[deg] + +region: + center: [0.0, -27.0] # [deg] + rmin: 10.0 # [deg] + rmax: 80.0 # [deg] + +threshold: + min: 0.0001 # [K] + max: null + +frequency: + type: calc + start: 154.0 # [MHz] + stop: 162.0 + step: 0.16 + +input: + filename: '{dir}/cluster_{freq:06.2f}.fits' + dirlist: 'dir.list' # filename of the directory list file + pixelsize: 20 # [arcsec] + +output: + filename: 'skymodel/cluster_{freq:06.2f}.osm' + clobber: true +""" + +import os +import argparse +import logging +from functools import lru_cache + +import yaml +import numpy as np +import healpy as hp +import astropy.units as au +from astropy.io import fits +from astropy.wcs import WCS + + +logging.basicConfig(level=logging.INFO, + format='[%(levelname)s:%(lineno)d] %(message)s') +logger = logging.getLogger() + + +def get_frequencies(config): + config_freq = config['frequency'] + if config_freq['type'] == 'custom': + return np.array(config_freq['frequencies']) + else: + start = config_freq['start'] + stop = config_freq['stop'] + step = config_freq['step'] + return np.arange(start, stop+step/2, step) + + +def central_angle(points, p0): + """ + Calculate the central angles between the points with respect to the + reference point (p0) on the sphere. + + Input parameters: + points: (longitude, latitude) [deg] + point coordinates, two columns + p0: (longitude, latitude) [deg] + coordinate of reference point + + Algorithm: + (radial, azimuthal, polar): (r, theta, phi) + central_angle: alpha + longitude: lambda = theta + latitude: delta = 90 - phi + colatitude: phi + + Unit vector: + \hat{r}_1 = (cos(theta1) sin(phi1), sin(theta1) sin(phi1), cos(phi1)) + = (cos(lambda1) cos(delta1), sin(lambda1) cos(delta1), sin(delta1)) + \hat{r}_2 = (cos(theta2) sin(phi2), sin(theta2) sin(phi2), cos(phi2)) + = (cos(lambda2) cos(delta2), sin(lambda2) cos(delta2), sin(delta2)) + + Therefore the angle (alpha) between \hat{r}_1 and \hat{r}_2: + cos(alpha) = \hat{r}_1 \cdot \hat{r}_2 + = cos(delta1) cos(delta2) cos(lambda1-lambda2) + + sin(delta1) sin(delta2) + + References: + [1] Spherical Coordinates - Wolfram MathWorld + http://mathworld.wolfram.com/SphericalCoordinates.html + Equation (19) + [2] Great Circle - Wolfram MathWorld + http://mathworld.wolfram.com/GreatCircle.html + Equation (1), (2), (4) + """ + points = np.deg2rad(points) + if points.ndim == 1: + lbd1, delta1 = points[0], points[1] + elif points.ndim == 2: + lbd1, delta1 = points[:, 0], points[:, 1] + else: + raise ValueError('invalid input points') + lbd0, delta0 = np.deg2rad(p0) + dotvalue = (np.cos(delta1) * np.cos(delta0) * np.cos(lbd1-lbd0) + + np.sin(delta1) * np.sin(delta0)) + alpha = np.arccos(dotvalue) + return np.rad2deg(alpha) # [deg] + + +def get_healpix_coords(nside): + npix = hp.nside2npix(nside) + lon, lat = hp.pix2ang(nside, np.arange(npix), lonlat=True) + return (lon, lat) # [deg] + + +class Patches: + def __init__(self, config): + config_input = config['input'] + self._filename = config_input['filename'] + self._dirlist = [d.strip() + for d in open(config_input['dirlist']).readlines()] + + def get_image(self, freq, i): + i = i % len(self._dirlist) + fn = self._filename.format(freq=freq, dir=self._dirlist[i]) + logger.info('Load image: %s' % fn) + with fits.open(fn) as f: + return (f[0].data, f[0].header) + + +class SkyModel: + def __init__(self, image, freq, pixelsize, p0, min_=1e-4, max_=None): + self._image = image + self._freq = freq # [MHz] + self._pixelsize = pixelsize # [arcsec] + self._p0 = p0 # (lon, lat) [deg] + self._min = min_ # [K] + self._max = max_ # [K] + + @property + def K2JyPixel(self): + pixarea = (self._pixelsize * au.arcsec) ** 2 + equiv = au.brightness_temperature(pixarea, self._freq*au.MHz) + return au.K.to(au.Jy, equivalencies=equiv) + + @property + def mask(self): + _max = self._max or np.inf + return ((np.abs(self._image) >= self._min) & + (np.abs(self._image) <= _max)) + + @property + def wcs(self): + shape = self._image.shape + delta = self._pixelsize / 3600.0 # [deg] + wcs = WCS(naxis=2) + projection = 'SIN' + wcs.wcs.ctype = ['RA---'+projection, 'DEC--'+projection] + wcs.wcs.crval = np.array(self._p0) + wcs.wcs.crpix = np.array([shape[1], shape[0]]) / 2.0 + 1 + wcs.wcs.cdelt = np.array([-delta, delta]) + return wcs + + @property + def sky(self): + shape = self._image.shape + idx = self.mask.flatten() + wcs = self.wcs + x, y = np.meshgrid(np.arange(shape[1]), np.arange(shape[0])) + pix = np.column_stack([x.flatten()[idx], y.flatten()[idx]]) + world = wcs.wcs_pix2world(pix, 0) + ra, dec = world[:, 0], world[:, 1] + flux = self._image.flatten()[idx] * self.K2JyPixel + return np.column_stack([ra, dec, flux]) + + +if __name__ == '__main__': + parser = argparse.ArgumentParser( + description='Montage sky patches to make a large OSKAR sky model') + parser.add_argument('config', help='configuration file in YAML format') + args = parser.parse_args() + + config = yaml.load(open(args.config)) + patches = Patches(config) + frequencies = get_frequencies(config) # [MHz] + nfreq = len(frequencies) + pcenter = config['region']['center'] # [deg] + rmin = config['region']['rmin'] # [deg] + rmax = config['region']['rmax'] # [deg] + min_ = config['threshold']['min'] # [K] + max_ = config['threshold']['max'] # [K] + pixelsize = config['input']['pixelsize'] # [arcsec] + clobber = config['output']['clobber'] + + nside = config['nside'] + logger.info('Nside: %d' % nside) + resol = hp.nside2resol(nside, arcmin=True) # [arcmin] + logger.info('HEALPix resolution: %.2f [arcmin]' % resol) + imgsize = int(round(resol * 60 / pixelsize)) + logger.info('Image patch size: %d' % imgsize) + plon, plat = get_healpix_coords(nside) # [deg] + npatch = len(plon) + + for i, freq in enumerate(frequencies): + logger.info('[%d/%d] %.2f[MHz] ...' % (i+1, nfreq, freq)) + outfile = config['output']['filename'].format(freq=freq) + os.makedirs(os.path.dirname(outfile), exist_ok=True) + if os.path.exists(outfile) and (not clobber): + raise FileExistsError(outfile) + + results = [] + jj = 0 + for j, p0 in enumerate(zip(plon, plat)): + logger.info('[%d/%d|%d] patch @ (%.2f, %.2f)' % + (j+1, jj+1, npatch, p0[0], p0[1])) + if central_angle(p0, pcenter) > rmax: + logger.info('skip') + continue + + image, header = patches.get_image(freq, jj) + skymodel = SkyModel(image[:imgsize, :imgsize], + freq, pixelsize=pixelsize, + p0=p0, min_=min_, max_=max_) + sky = skymodel.sky + points = sky[:, 0:2] # (lon, lat) + angles = central_angle(points, pcenter) # [deg] + idx = ((angles >= rmin) & (angles <= rmax)) + sky = sky[idx, :] + logger.info('Source counts: %d' % len(sky)) + results.append(sky) + jj += 1 + + sky = np.row_stack(results) + logger.info('Total source counts: %d' % len(sky)) + header = ('Frequency = %.2f [MHz]\n' % freq + + 'Source counts = %d\n\n' % len(sky) + + 'R.A.[deg] Dec.[deg] flux[Jy]') + logger.info('Writing sky model to file: %s ...' % outfile) + np.savetxt(outfile, sky, fmt='%.10e, %.10e, %.10e', header=header) + logger.info("Wrote OSKAR sky model to file: %s" % outfile) |