# Copyright (c) 2016 Weitian LI # MIT license """ Diffuse Galactic synchrotron emission (unpolarized) simulations. """ import os from datetime import datetime, timezone import numpy as np from astropy.io import fits import astropy.units as au import healpy as hp class Synchrotron: """Simulate the diffuse Galactic synchrotron emission based on an existing template. Parameters ---------- configs : ConfigManager object An `ConfigManager` object contains default and user configurations. For more details, see the example config specification. Attributes ---------- ??? References ---------- ??? """ def __init__(self, configs): self.configs = configs self._set_configs() self._load_template() self._load_indexmap() def _set_configs(self): """Load the configs and set the corresponding class attributes.""" data_dir = self.configs.getn("common/data_dir") self.template_path = os.path.join( data_dir, self.configs.getn("galactic/synchrotron/template")) self.template_freq = self.configs.getn( "galactic/synchrotron/template_freq") self.template_unit = au.Unit( self.configs.getn("galactic/synchrotron/template_unit")) self.indexmap_path = os.path.join( data_dir, self.configs.getn("galactic/synchrotron/indexmap")) self.smallscales = self.configs.getn( "galactic/synchrotron/add_smallscales") # output self.prefix = self.configs.getn("galactic/synchrotron/prefix") self.save = self.configs.getn("galactic/synchrotron/save") self.output_dir = self.configs.getn("galactic/synchrotron/output_dir") self.filename_pattern = self.configs.getn("output/filename_pattern") self.use_float = self.configs.getn("output/use_float") self.clobber = self.configs.getn("output/clobber") # common self.nside = self.configs.getn("common/nside") self.lmin = self.configs.getn("common/lmin") self.lmax = self.configs.getn("common/lmax") # unit of the frequency self.freq_unit = au.Unit(self.configs.getn("frequency/unit")) def _load_template(self): """Load the template map""" self.template, header = hp.read_map(self.template_path, nest=False, h=True, verbose=False) self.template_header = fits.header.Header(header) self.template_nside = self.template_header["NSIDE"] self.template_ordering = self.template_header["ORDERING"] def _load_indexmap(self): """Load the spectral index map""" self.indexmap, header = hp.read_map(self.indexmap_path, nest=False, h=True, verbose=False) self.indexmap_header = fits.header.Header(header) self.indexmap_nside = self.indexmap_header["NSIDE"] self.indexmap_ordering = self.indexmap_header["ORDERING"] def _process_template(self): """Upgrade/downgrade the template to have the same Nside as requested by the output.""" if self.nside == self.template_nside: self.hpmap = self.template.copy() else: # upgrade/downgrade the resolution self.hpmap = hp.ud_grade(self.template, nside_out=self.nside) def _process_indexmap(self): """Upgrade/downgrade the spectral index map to have the same Nside as requested by the output.""" if self.nside == self.indexmap_nside: self.hpmap_index = self.indexmap.copy() else: # upgrade/downgrade the resolution self.hpmap_index = hp.ud_grade(self.indexmap, nside_out=self.nside) def _add_smallscales(self): """Add fluctuations on small scales to the template map. XXX/TODO: * Support using different models. * This should be extensible/plug-able, e.g., a separate module and allow easily add new models for use. References ---------- [1] M. Remazeilles et al. 2015, MNRAS, 451, 4311-4327 "An improved source-subtracted and destriped 408-MHz all-sky map" Sec. 4.2: Small-scale fluctuations """ if not self.smallscales: return # To add small scale fluctuations # model: Remazeilles15 gamma = -2.703 # index of the power spectrum between l [30, 90] sigma_temp = 56 # original beam resolution of the template [ arcmin ] alpha = 0.0599 beta = 0.782 # angular power spectrum of the Gaussian random field ell = np.arange(self.lmax+1).astype(np.int) cl = np.zeros(ell.shape) ell_idx = ell >= self.lmin cl[ell_idx] = (ell[ell_idx] ** gamma * 1.0 - np.exp(-ell[ell_idx]**2 * sigma_temp**2)) cl[ell < self.lmin] = cl[self.lmin] # generate a realization of the Gaussian random field gss = hp.synfast(cls=cl, nside=self.nside) # whiten the Gaussian random field gss = (gss - gss.mean()) / gss.std() self.hpmap_smallscales = alpha * gss * self.hpmap**beta self.hpmap += self.hpmap_smallscales def _transform_frequency(self, frequency): """Transform the template map to the requested frequency, according to the spectral model and using an spectral index map. """ hpmap_f = (self.hpmap * (frequency / self.template_freq) ** self.hpmap_index) return hpmap_f def _make_header(self): """Make the header with detail information (e.g., parameters and history) for the simulated products. """ header = fits.Header() header["COMP"] = ("Galactic synchrotron (unpolarized)", "Emission component") # TODO: history = [] comments = [] for hist in history: header.add_history(hist) for cmt in comments: header.add_comment(cmt) self.header = header def output(self, hpmap, frequency): """Write the simulated synchrotron map to disk with proper header keywords and history. """ FITS_COLUMN_FORMATS = { np.dtype("float32"): "E", np.dtype("float64"): "D", } # filename = self.filename_pattern.format(prefix=self.prefix, frequency=frequency) filepath = os.path.join(self.output_dir, filename) if not hasattr(self, "header"): self._make_header() header = self.header.copy() header["FREQ"] = (frequency, "Frequency [ MHz ]") header["DATE"] = ( datetime.now(timezone.utc).astimezone().isoformat(), "File creation date" ) if self.use_float: hpmap = hpmap.astype(np.float32) hdu = fits.BinTableHDU.from_columns([ fits.Column(name="I", array=hpmap, format=FITS_COLUMN_FORMATS.get(hpmap.dtype)) ], header=header) hdu.writeto(filepath, clobber=self.clobber, checksum=True) def simulate(self, frequencies): """Simulate the synchrotron map at the specified frequencies.""" if not hasattr(self, "hpmap"): self._process_template() self._add_smallscales() if not hasattr(self, "hpmap_index"): self._process_indexmap() # hpmaps = [] for f in np.array(frequencies, ndmin=1): hpmap_f = self._transform_frequency(f) hpmaps.append(hpmap_f) if self.save: self.output(hpmap_f, f) return hpmaps