def test_thermal(answer_store, answer_dir): prng = RandomState(71) tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) spectrum_answer_testing(spec, "thermal_spec.h5", answer_store, answer_dir) pt_src_pos = PointSourceModel(30.0, 45.0) sim_cat = SimputCatalog.from_models("thermal_model", "thermal_model", spec, pt_src_pos, exp_time, area, prng=prng) sim_cat.write_catalog(overwrite=True) instrument_simulator("thermal_model_simput.fits", "thermal_model_evt.fits", exp_time, inst_name, [30.0, 45.0], ptsrc_bkgnd=False, foreground=False, instr_bkgnd=False, prng=prng) write_spectrum("thermal_model_evt.fits", "thermal_model_evt.pha", overwrite=True) file_answer_testing("EVENTS", "thermal_model_evt.fits", answer_store, answer_dir) file_answer_testing("SPECTRUM", "thermal_model_evt.pha", answer_store, answer_dir) os.chdir(curdir) shutil.rmtree(tmpdir)
def test_background(): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) kT_sim = 1.0 Z_sim = 0.0 norm_sim = 4.0e-2 nH_sim = 0.04 redshift = 0.01 exp_time = (200., "ks") area = (1000., "cm**2") fov = (10.0, "arcmin") prng = 24 agen = ApecGenerator(0.05, 12.0, 5000, broadening=False) spec = agen.get_spectrum(kT_sim, Z_sim, redshift, norm_sim) spec.apply_foreground_absorption(norm_sim) events = make_background(area, exp_time, fov, (30.0, 45.0), spec, prng=prng) events.write_simput_file("bkgnd", overwrite=True) instrument_simulator("bkgnd_simput.fits", "bkgnd_evt.fits", exp_time, "sq_acisi_cy19", [30.0, 45.0], overwrite=True, foreground=False, ptsrc_bkgnd=False, instr_bkgnd=False, prng=prng) write_spectrum("bkgnd_evt.fits", "background_evt.pi", overwrite=True) os.system("cp %s %s ." % (arf.filename, rmf.filename)) load_user_model(mymodel, "wapec") add_user_pars("wapec", ["nH", "kT", "metallicity", "redshift", "norm"], [0.01, 4.0, 0.2, redshift, norm_sim*0.8], parmins=[0.0, 0.1, 0.0, -20.0, 0.0], parmaxs=[10.0, 20.0, 10.0, 20.0, 1.0e9], parfrozen=[False, False, False, True, False]) load_pha("background_evt.pi") set_stat("cstat") set_method("simplex") ignore(":0.5, 8.0:") set_model("wapec") fit() res = get_fit_results() assert np.abs(res.parvals[0]-nH_sim)/nH_sim < 0.1 assert np.abs(res.parvals[1]-kT_sim)/kT_sim < 0.05 assert np.abs(res.parvals[2]-Z_sim) < 0.05 assert np.abs(res.parvals[3]-norm_sim)/norm_sim < 0.05 os.chdir(curdir) shutil.rmtree(tmpdir)
def test_point_source(): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) nH_sim = 0.02 norm_sim = 1.0e-4 alpha_sim = 0.95 redshift = 0.02 exp_time = (100., "ks") area = (3000., "cm**2") spec = Spectrum.from_powerlaw(alpha_sim, redshift, norm_sim, emin=0.1, emax=11.5, nbins=2000) spec.apply_foreground_absorption(nH_sim, model="tbabs") positions = [(30.01, 45.0)] events = make_point_sources(area, exp_time, positions, (30.0, 45.0), spec, prng=prng) events.write_simput_file("ptsrc", overwrite=True) instrument_simulator("ptsrc_simput.fits", "ptsrc_evt.fits", exp_time, "sq_aciss_cy19", [30.0, 45.0], overwrite=True, foreground=False, ptsrc_bkgnd=False, instr_bkgnd=False, prng=prng) write_spectrum("ptsrc_evt.fits", "point_source_evt.pi", overwrite=True) os.system("cp %s %s ." % (arf.filename, rmf.filename)) load_user_model(mymodel, "tplaw") add_user_pars("tplaw", ["nH", "norm", "redshift", "alpha"], [0.02, norm_sim*0.8, redshift, 0.9], parmins=[0.0, 0.0, 0.0, 0.1], parmaxs=[10.0, 1.0e9, 10.0, 10.0], parfrozen=[True, False, True, False]) load_pha("point_source_evt.pi") set_stat("cstat") set_method("simplex") ignore(":0.4, 9.0:") set_model("tplaw") fit() res = get_fit_results() assert np.abs(res.parvals[0]-norm_sim)/norm_sim < 0.05 assert np.abs(res.parvals[1]-alpha_sim)/alpha_sim < 0.05 os.chdir(curdir) shutil.rmtree(tmpdir)
def test_point_source(): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) nH_sim = 0.02 norm_sim = 1.0e-4 alpha_sim = 0.95 redshift = 0.02 exp_time = (100., "ks") area = (3000., "cm**2") spec = Spectrum.from_powerlaw(alpha_sim, redshift, norm_sim, emin=0.1, emax=11.5, nbins=2000) spec.apply_foreground_absorption(nH_sim, model="tbabs") positions = [(30.01, 45.0)] events = make_point_sources(area, exp_time, positions, (30.0, 45.0), spec, prng=prng) events.write_simput_file("ptsrc", overwrite=True) instrument_simulator("ptsrc_simput.fits", "ptsrc_evt.fits", exp_time, "sq_aciss_cy20", [30.0, 45.0], overwrite=True, foreground=False, ptsrc_bkgnd=False, instr_bkgnd=False, prng=prng) write_spectrum("ptsrc_evt.fits", "point_source_evt.pi", overwrite=True) os.system("cp %s %s ." % (arf.filename, rmf.filename)) load_user_model(mymodel, "tplaw") add_user_pars("tplaw", ["nH", "norm", "redshift", "alpha"], [0.02, norm_sim*0.8, redshift, 0.9], parmins=[0.0, 0.0, 0.0, 0.1], parmaxs=[10.0, 1.0e9, 10.0, 10.0], parfrozen=[True, False, True, False]) load_pha("point_source_evt.pi") set_stat("cstat") set_method("simplex") ignore(":0.4, 9.0:") set_model("tplaw") fit() res = get_fit_results() assert np.abs(res.parvals[0]-norm_sim)/norm_sim < 0.05 assert np.abs(res.parvals[1]-alpha_sim)/alpha_sim < 0.05 os.chdir(curdir) shutil.rmtree(tmpdir)
def plaw_fit(alpha_sim, answer_store, answer_dir): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) nH_sim = 0.02 norm_sim = 1.0e-4 redshift = 0.01 exp_time = (50.0, "ks") area = 40000.0 inst_name = "new_hdxi" spec = Spectrum.from_powerlaw(alpha_sim, redshift, norm_sim, 0.1, 10.0, 20000) spec.apply_foreground_absorption(nH_sim, model="tbabs") spectrum_answer_testing(spec, f"power_law_{alpha_sim}.h5", answer_store, answer_dir) pt_src_pos = PointSourceModel(30.0, 45.0) pt_src = SimputPhotonList.from_models("plaw_model", spec, pt_src_pos, exp_time, area, prng=prng) cat = SimputCatalog.from_source("plaw_model_simput.fits", pt_src, overwrite=True) instrument_simulator("plaw_model_simput.fits", f"plaw_model_{alpha_sim}_evt.fits", exp_time, inst_name, [30.0, 45.0], instr_bkgnd=False, ptsrc_bkgnd=False, foreground=False, prng=prng) write_spectrum(f"plaw_model_{alpha_sim}_evt.fits", f"plaw_model_{alpha_sim}_evt.pha", overwrite=True) file_answer_testing("EVENTS", f"plaw_model_{alpha_sim}_evt.fits", answer_store, answer_dir) file_answer_testing("SPECTRUM", f"plaw_model_{alpha_sim}_evt.pha", answer_store, answer_dir) os.chdir(curdir) shutil.rmtree(tmpdir)
def test_emission_line(answer_store, answer_dir): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) const_flux = 1.0e-4 line_pos = 5.0 line_width = 0.02 line_amp = 1.0e-5 exp_time = (100.0, "ks") area = 30000.0 inst_name = "lynx_lxm" spec = Spectrum.from_constant(const_flux, 1.0, 10.0, 20000) spec.add_emission_line(line_pos, line_width, line_amp) spectrum_answer_testing(spec, "emission_line_test.h5", answer_store, answer_dir) pt_src_pos = PointSourceModel(30.0, 45.0) sim_cat = SimputCatalog.from_models("emission_line", "emission_line", spec, pt_src_pos, exp_time, area, prng=prng) sim_cat.write_catalog(overwrite=True) instrument_simulator("emission_line_simput.fits", "emission_line_evt.fits", exp_time, inst_name, [30.0, 45.0], instr_bkgnd=False, ptsrc_bkgnd=False, foreground=False, prng=prng) write_spectrum("emission_line_evt.fits", "emission_line_evt.pha", overwrite=True) file_answer_testing("EVENTS", "emission_line_evt.fits", answer_store, answer_dir) file_answer_testing("SPECTRUM", "emission_line_evt.pha", answer_store, answer_dir) os.chdir(curdir) shutil.rmtree(tmpdir)
def test_thermal_nei(answer_store, answer_dir): prng = RandomState(71) tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) spectrum_answer_testing(spec_nei, "thermal_spec_nei.h5", answer_store, answer_dir) pt_src_pos = PointSourceModel(30.0, 45.0) pt_src = SimputPhotonList.from_models("thermal_model_nei", spec_nei, pt_src_pos, exp_time, area, prng=prng) sim_cat = SimputCatalog.from_source("thermal_model_nei_simput.fits", pt_src, overwrite=True) instrument_simulator("thermal_model_nei_simput.fits", "thermal_model_nei_evt.fits", exp_time, inst_name, [30.0, 45.0], ptsrc_bkgnd=False, foreground=False, instr_bkgnd=False, prng=prng) write_spectrum("thermal_model_nei_evt.fits", "thermal_model_nei_evt.pha", overwrite=True) file_answer_testing("EVENTS", "thermal_model_nei_evt.fits", answer_store, answer_dir) file_answer_testing("SPECTRUM", "thermal_model_nei_evt.pha", answer_store, answer_dir) os.chdir(curdir) shutil.rmtree(tmpdir)
def plaw_fit(alpha_sim, answer_store, answer_dir): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) nH_sim = 0.02 norm_sim = 1.0e-4 redshift = 0.01 exp_time = (50.0, "ks") area = 40000.0 inst_name = "new_hdxi" spec = Spectrum.from_powerlaw(alpha_sim, redshift, norm_sim, 0.1, 10.0, 20000) spec.apply_foreground_absorption(nH_sim, model="tbabs") spectrum_answer_testing(spec, "power_law_%s.h5" % alpha_sim, answer_store, answer_dir) pt_src_pos = PointSourceModel(30.0, 45.0) sim_cat = SimputCatalog.from_models("plaw_model", "plaw_model", spec, pt_src_pos, exp_time, area, prng=prng) sim_cat.write_catalog(overwrite=True) instrument_simulator("plaw_model_simput.fits", "plaw_model_%s_evt.fits" % alpha_sim, exp_time, inst_name, [30.0, 45.0], instr_bkgnd=False, ptsrc_bkgnd=False, foreground=False, prng=prng) write_spectrum("plaw_model_%s_evt.fits" % alpha_sim, "plaw_model_%s_evt.pha" % alpha_sim, overwrite=True) file_answer_testing("EVENTS", "plaw_model_%s_evt.fits" % alpha_sim, answer_store, answer_dir) file_answer_testing("SPECTRUM", "plaw_model_%s_evt.pha" % alpha_sim, answer_store, answer_dir) os.chdir(curdir) shutil.rmtree(tmpdir)
def plaw_fit(alpha_sim, prng=None): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) bms = BetaModelSource() ds = bms.ds if prng is None: prng = bms.prng def _hard_emission(field, data): return YTQuantity( 1.0e-18, "s**-1*keV**-1") * data["density"] * data["cell_volume"] / mp ds.add_field(("gas", "hard_emission"), function=_hard_emission, units="keV**-1*s**-1") nH_sim = 0.02 A = YTQuantity(2000., "cm**2") exp_time = YTQuantity(2.0e5, "s") redshift = 0.01 sphere = ds.sphere("c", (100., "kpc")) plaw_model = PowerLawSourceModel(1.0, 0.01, 11.0, "hard_emission", alpha_sim, prng=prng) photons = PhotonList.from_data_source(sphere, redshift, A, exp_time, plaw_model) D_A = photons.parameters["fid_d_a"] dist_fac = 1.0 / (4. * np.pi * D_A * D_A * (1. + redshift)**3).in_cgs() norm_sim = float( (sphere["hard_emission"]).sum() * dist_fac.in_cgs()) * (1. + redshift) events = photons.project_photons("z", [30., 45.], absorb_model="wabs", nH=nH_sim, prng=bms.prng, no_shifting=True) events.write_simput_file("plaw", overwrite=True) instrument_simulator("plaw_simput.fits", "plaw_evt.fits", exp_time, "sq_acisi_cy19", [30.0, 45.0], overwrite=True, foreground=False, ptsrc_bkgnd=False, instr_bkgnd=False, prng=prng) write_spectrum("plaw_evt.fits", "plaw_model_evt.pi", overwrite=True) os.system("cp %s %s ." % (arf.filename, rmf.filename)) load_user_model(mymodel, "wplaw") add_user_pars("wplaw", ["nH", "norm", "redshift", "alpha"], [0.01, norm_sim * 1.1, redshift, 0.9], parmins=[0.0, 0.0, 0.0, 0.1], parmaxs=[10.0, 1.0e9, 10.0, 10.0], parfrozen=[False, False, True, False]) load_pha("plaw_model_evt.pi") set_stat("cstat") set_method("simplex") ignore(":0.6, 7.0:") set_model("wplaw") fit() res = get_fit_results() assert np.abs(res.parvals[0] - nH_sim) / nH_sim < 0.1 assert np.abs(res.parvals[1] - norm_sim) / norm_sim < 0.05 assert np.abs(res.parvals[2] - alpha_sim) / alpha_sim < 0.05 os.chdir(curdir) shutil.rmtree(tmpdir)
def test_background(): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) kT_sim = 1.0 Z_sim = 0.0 norm_sim = 4.0e-2 nH_sim = 0.04 redshift = 0.01 exp_time = (200., "ks") area = (1000., "cm**2") fov = (10.0, "arcmin") prng = 24 agen = ApecGenerator(0.05, 12.0, 5000, broadening=False) spec = agen.get_spectrum(kT_sim, Z_sim, redshift, norm_sim) spec.apply_foreground_absorption(norm_sim) events = make_background(area, exp_time, fov, (30.0, 45.0), spec, prng=prng) events.write_simput_file("bkgnd", overwrite=True) instrument_simulator("bkgnd_simput.fits", "bkgnd_evt.fits", exp_time, "sq_acisi_cy19", [30.0, 45.0], overwrite=True, foreground=False, ptsrc_bkgnd=False, instr_bkgnd=False, prng=prng) write_spectrum("bkgnd_evt.fits", "background_evt.pi", overwrite=True) os.system("cp %s %s ." % (arf.filename, rmf.filename)) load_user_model(mymodel, "wapec") add_user_pars("wapec", ["nH", "kT", "metallicity", "redshift", "norm"], [0.01, 4.0, 0.2, redshift, norm_sim * 0.8], parmins=[0.0, 0.1, 0.0, -20.0, 0.0], parmaxs=[10.0, 20.0, 10.0, 20.0, 1.0e9], parfrozen=[False, False, False, True, False]) load_pha("background_evt.pi") set_stat("cstat") set_method("simplex") ignore(":0.5, 8.0:") set_model("wapec") fit() res = get_fit_results() assert np.abs(res.parvals[0] - nH_sim) / nH_sim < 0.1 assert np.abs(res.parvals[1] - kT_sim) / kT_sim < 0.05 assert np.abs(res.parvals[2] - Z_sim) < 0.05 assert np.abs(res.parvals[3] - norm_sim) / norm_sim < 0.05 os.chdir(curdir) shutil.rmtree(tmpdir)
def do_beta_model(source, v_field, em_field, axis="z", prng=None): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) if prng is None: prng = source.prng ds = source.ds A = 30000. exp_time = 1.0e4 redshift = 0.05 nH_sim = 0.02 sphere = ds.sphere("c", (0.5, "Mpc")) kT_sim = source.kT Z_sim = source.Z thermal_model = ThermalSourceModel("apec", 0.1, 11.5, 20000, Zmet=Z_sim, prng=prng) photons = PhotonList.from_data_source(sphere, redshift, A, exp_time, thermal_model) D_A = photons.parameters["fid_d_a"] norm_sim = sphere.quantities.total_quantity(em_field) norm_sim *= 1.0e-14/(4*np.pi*D_A*D_A*(1.+redshift)*(1.+redshift)) norm_sim = float(norm_sim.in_cgs()) v1, v2 = sphere.quantities.weighted_variance(v_field, em_field) if isinstance(axis, string_types): if axis == "z": fac = 1.0 else: fac = 0.0 else: axis /= np.sqrt(np.dot(axis, axis)) fac = np.dot(axis, [0.0, 0.0, 1.0]) sigma_sim = fac*float(v1.in_units("km/s")) mu_sim = -fac*float(v2.in_units("km/s")) events = photons.project_photons(axis, [30.0, 45.0], absorb_model="tbabs", nH=nH_sim, prng=prng) events.write_simput_file("beta_model", overwrite=True) instrument_simulator("beta_model_simput.fits", "beta_model_evt.fits", exp_time, "mucal", [30.0, 45.0], overwrite=True, foreground=False, ptsrc_bkgnd=False, instr_bkgnd=False, prng=prng) write_spectrum("beta_model_evt.fits", "beta_model_evt.pi", overwrite=True) os.system("cp %s %s ." % (arf.filename, rmf.filename)) load_user_model(mymodel, "tbapec") add_user_pars("tbapec", ["nH", "kT", "metallicity", "redshift", "norm", "velocity"], [0.02, 4.0, 0.2, 0.04, norm_sim*0.8, 300.0], parmins=[0.0, 0.1, 0.0, -200.0, 0.0, 0.0], parmaxs=[10.0, 20.0, 10.0, 200.0, 1.0e9, 20000.0], parfrozen=[True, False, False, False, False, False]) load_pha("beta_model_evt.pi") set_stat("cstat") set_method("levmar") ignore(":0.6, 8.0:") set_model("tbapec") fit() res = get_fit_results() redshift_sim = (1.0+mu_sim/ckms)*(1.0+redshift) - 1.0 assert np.abs(res.parvals[0]-kT_sim)/kT_sim < 0.05 assert np.abs(res.parvals[1]-Z_sim)/Z_sim < 0.05 assert np.abs(res.parvals[2]-redshift_sim)/redshift_sim < 0.05 assert np.abs(res.parvals[3]-norm_sim) < 0.05 assert np.abs(res.parvals[4]-sigma_sim) < 30.0 os.chdir(curdir) shutil.rmtree(tmpdir)
def plaw_fit(alpha_sim): tmpdir = tempfile.mkdtemp() curdir = os.getcwd() os.chdir(tmpdir) nH_sim = 0.02 norm_sim = 1.0e-4 redshift = 0.01 exp_time = (50.0, "ks") area = 40000.0 inst_name = "hdxi" spec = Spectrum.from_powerlaw(alpha_sim, redshift, norm_sim) spec.apply_foreground_absorption(nH_sim, model="tbabs") e = spec.generate_energies(exp_time, area, prng=prng) pt_src = PointSourceModel(30.0, 45.0, e.size) write_photon_list("plaw_model", "plaw_model", e.flux, pt_src.ra, pt_src.dec, e, overwrite=True) instrument_simulator("plaw_model_simput.fits", "plaw_model_evt.fits", exp_time, inst_name, [30.0, 45.0], instr_bkgnd=False, ptsrc_bkgnd=False, foreground=False, prng=prng) inst = get_instrument_from_registry(inst_name) arf = AuxiliaryResponseFile(inst["arf"]) rmf = RedistributionMatrixFile(inst["rmf"]) os.system("cp %s ." % arf.filename) convert_rmf(rmf.filename) write_spectrum("plaw_model_evt.fits", "plaw_model_evt.pha", overwrite=True) load_user_model(mymodel, "tplaw") add_user_pars("tplaw", ["nH", "norm", "redshift", "alpha"], [0.01, norm_sim * 0.8, redshift, 0.9], parmins=[0.0, 0.0, 0.0, 0.1], parmaxs=[10.0, 1.0e9, 10.0, 10.0], parfrozen=[False, False, True, False]) load_pha("plaw_model_evt.pha") set_stat("cstat") set_method("simplex") ignore(":0.6, 8.0:") set_model("tplaw") fit() set_covar_opt("sigma", 1.645) covar() res = get_covar_results() assert np.abs(res.parvals[0] - nH_sim) < res.parmaxes[0] assert np.abs(res.parvals[1] - norm_sim) < res.parmaxes[1] assert np.abs(res.parvals[2] - alpha_sim) < res.parmaxes[2] os.chdir(curdir) shutil.rmtree(tmpdir)
def simulate_spectrum(spec, instrument, exp_time, out_file, overwrite=False, prng=None): """ Generate a PI or PHA spectrum from a :class:`~soxs.spectra.Spectrum` by convolving it with responses. To be used if one wants to create a spectrum without worrying about spatial response. Similar to XSPEC's "fakeit". Parameters ---------- spec : :class:`~soxs.spectra.Spectrum` The spectrum to be convolved. instrument : string The name of the instrument to use, which picks an instrument specification from the instrument registry. exp_time : float, (value, unit) tuple, or :class:`~astropy.units.Quantity` The exposure time in seconds. out_file : string The file to write the spectrum to. overwrite : boolean, optional Whether or not to overwrite an existing file. Default: False prng : :class:`~numpy.random.RandomState` object, integer, or None A pseudo-random number generator. Typically will only be specified if you have a reason to generate the same set of random numbers, such as for a test. Default is None, which sets the seed based on the system time. Examples -------- >>> spec = soxs.Spectrum.from_file("my_spectrum.txt") >>> soxs.simulate_spectrum(spec, "mucal", 100000.0, ... "my_spec.pi", overwrite=True) """ from soxs.events import write_spectrum from soxs.instrument import RedistributionMatrixFile, \ AuxiliaryResponseFile from soxs.spectra import ConvolvedSpectrum prng = parse_prng(prng) exp_time = parse_value(exp_time, "s") try: instrument_spec = instrument_registry[instrument] except KeyError: raise KeyError("Instrument %s is not in the instrument registry!" % instrument) arf_file = check_file_location(instrument_spec["arf"], "files") rmf_file = check_file_location(instrument_spec["rmf"], "files") arf = AuxiliaryResponseFile(arf_file) rmf = RedistributionMatrixFile(rmf_file) cspec = ConvolvedSpectrum(spec, arf) events = {} events["energy"] = cspec.generate_energies(exp_time, prng=prng).value events = rmf.scatter_energies(events, prng=prng) events["arf"] = arf.filename events["rmf"] = rmf.filename events["exposure_time"] = exp_time events["channel_type"] = rmf.header["CHANTYPE"] events["telescope"] = rmf.header["TELESCOP"] events["instrument"] = rmf.header["INSTRUME"] events["mission"] = rmf.header.get("MISSION", "") write_spectrum(events, out_file, overwrite=overwrite)