def test_simulate_bkgnd_spectrum():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
prng = RandomState(29)
hdxi_arf = AuxiliaryResponseFile("xrs_hdxi_3x10.arf")
hdxi_rmf = RedistributionMatrixFile("xrs_hdxi.rmf")
exp_time = 50000.0
fov = 3600.0
simulate_spectrum(None, "hdxi", exp_time, "test_bkgnd.pha",
instr_bkgnd=True, foreground=True, prng=prng,
overwrite=True, bkgnd_area=(fov, "arcsec**2"))
ch_min = hdxi_rmf.e_to_ch(0.7)-hdxi_rmf.cmin
ch_max = hdxi_rmf.e_to_ch(2.0)-hdxi_rmf.cmin
f = pyfits.open("test_bkgnd.pha")
ncts = f["SPECTRUM"].data["COUNTS"][ch_min:ch_max].sum()
f.close()
S = ncts/exp_time/fov
dS = np.sqrt(ncts)/exp_time/fov
foreground = ConvolvedBackgroundSpectrum(hm_astro_bkgnd, hdxi_arf)
f_sum = foreground.get_flux_in_band(0.7, 2.0)[0]
i_sum = acisi_particle_bkgnd.get_flux_in_band(0.7, 2.0)[0]
b_sum = (f_sum+i_sum).to("ph/(arcsec**2*s)").value
assert np.abs(S-b_sum) < 1.645*dS
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_uniform_bkgnd_scale():
hdxi_arf = AuxiliaryResponseFile("xrs_hdxi_3x10.arf")
events, event_params = make_background((50, "ks"), "hdxi", [30., 45.],
foreground=True, instr_bkgnd=True,
ptsrc_bkgnd=False, prng=prng)
ncts = np.logical_and(events["energy"] >= 0.7, events["energy"] <= 2.0).sum()
t_exp = event_params["exposure_time"]
fov = (event_params["fov"]*60.0)**2
S = ncts/t_exp/fov
dS = np.sqrt(ncts)/t_exp/fov
foreground = ConvolvedBackgroundSpectrum(hm_astro_bkgnd, hdxi_arf)
f_sum = foreground.get_flux_in_band(0.7, 2.0)[0]
i_sum = acisi_particle_bkgnd.get_flux_in_band(0.7, 2.0)[0]
b_sum = (f_sum+i_sum).to("ph/(arcsec**2*s)").value
assert np.abs(S-b_sum) < 1.645*dS
def test_simulate_bkgnd_spectrum():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
prng = RandomState(29)
hdxi_arf = AuxiliaryResponseFile("xrs_hdxi_3x10.arf")
hdxi_rmf = RedistributionMatrixFile("xrs_hdxi.rmf")
exp_time = 50000.0
fov = 3600.0
simulate_spectrum(None, "lynx_hdxi", exp_time, "test_bkgnd.pha",
instr_bkgnd=True, foreground=True, prng=prng,
overwrite=True, bkgnd_area=(fov, "arcsec**2"))
ch_min = hdxi_rmf.eb_to_ch(0.7)-hdxi_rmf.cmin
ch_max = hdxi_rmf.eb_to_ch(2.0)-hdxi_rmf.cmin
with pyfits.open("test_bkgnd.pha") as f:
ncts = f["SPECTRUM"].data["COUNTS"][ch_min:ch_max].sum()
S = ncts/exp_time/fov
dS = np.sqrt(ncts)/exp_time/fov
foreground = ConvolvedBackgroundSpectrum.convolve(hm_astro_bkgnd, hdxi_arf)
f_sum = foreground.get_flux_in_band(0.7, 2.0)[0]
i_sum = acisi_particle_bkgnd.get_flux_in_band(0.7, 2.0)[0]*(u.cm/u.arcmin)**2
b_sum = (f_sum+i_sum).to_value("ph/(arcsec**2*s)")
assert np.abs(S-b_sum) < 1.645*dS
os.chdir(curdir)
shutil.rmtree(tmpdir)
def make_foreground(event_params, arf, rmf, prng=None):
import pyregion._region_filter as rfilter
prng = parse_prng(prng)
conv_frgnd_spec = ConvolvedBackgroundSpectrum(hm_astro_bkgnd, arf)
energy = conv_frgnd_spec.generate_energies(event_params["exposure_time"],
event_params["fov"], prng=prng,
quiet=True).value
prng = parse_prng(prng)
bkg_events = {}
n_events = energy.size
nx = event_params["num_pixels"]
bkg_events["detx"] = prng.uniform(low=-0.5*nx, high=0.5*nx, size=n_events)
bkg_events["dety"] = prng.uniform(low=-0.5*nx, high=0.5*nx, size=n_events)
bkg_events["energy"] = energy
if event_params["chips"] is None:
bkg_events["chip_id"] = np.zeros(n_events, dtype='int')
else:
bkg_events["chip_id"] = -np.ones(n_events, dtype='int')
for i, chip in enumerate(event_params["chips"]):
thisc = np.ones(n_events, dtype='bool')
rtype = chip[0]
args = chip[1:]
r = getattr(rfilter, rtype)(*args)
inside = r.inside(bkg_events["detx"], bkg_events["dety"])
thisc = np.logical_and(thisc, inside)
bkg_events["chip_id"][thisc] = i
keep = bkg_events["chip_id"] > -1
if keep.sum() == 0:
raise RuntimeError("No astrophysical foreground events were detected!!!")
else:
mylog.info("Making %d events from the astrophysical foreground." % keep.sum())
for key in bkg_events:
bkg_events[key] = bkg_events[key][keep]
return make_diffuse_background(bkg_events, event_params, rmf, prng=prng)
def make_foreground(event_params, arf, rmf, prng=None):
import pyregion._region_filter as rfilter
prng = parse_prng(prng)
conv_frgnd_spec = ConvolvedBackgroundSpectrum(hm_astro_bkgnd, arf)
energy = conv_frgnd_spec.generate_energies(event_params["exposure_time"],
event_params["fov"], prng=prng,
quiet=True).value
prng = parse_prng(prng)
bkg_events = {}
n_events = energy.size
nx = event_params["num_pixels"]
bkg_events["detx"] = prng.uniform(low=-0.5*nx, high=0.5*nx, size=n_events)
bkg_events["dety"] = prng.uniform(low=-0.5*nx, high=0.5*nx, size=n_events)
bkg_events["energy"] = energy
if event_params["chips"] is None:
bkg_events["chip_id"] = np.zeros(n_events, dtype='int')
else:
bkg_events["chip_id"] = -np.ones(n_events, dtype='int')
for i, chip in enumerate(event_params["chips"]):
thisc = np.ones(n_events, dtype='bool')
rtype = chip[0]
args = chip[1:]
r = getattr(rfilter, rtype)(*args)
inside = r.inside(bkg_events["detx"], bkg_events["dety"])
thisc = np.logical_and(thisc, inside)
bkg_events["chip_id"][thisc] = i
keep = bkg_events["chip_id"] > -1
if keep.sum() == 0:
raise RuntimeError("No astrophysical foreground events were detected!!!")
else:
mylog.info("Making %d events from the astrophysical foreground." % keep.sum())
for key in bkg_events:
bkg_events[key] = bkg_events[key][keep]
return make_diffuse_background(bkg_events, event_params, rmf, prng=prng)
def make_foreground(event_params, arf, rmf, prng=None):
prng = parse_prng(prng)
conv_bkgnd_spec = ConvolvedBackgroundSpectrum(hm_astro_bkgnd, arf)
energy = conv_bkgnd_spec.generate_energies(event_params["exposure_time"],
event_params["fov"],
prng=prng,
quiet=True).value
if energy.size == 0:
raise RuntimeError(
"No astrophysical foreground events were detected!!!")
else:
mylog.info("Making %d events from the astrophysical foreground." %
energy.size)
return make_uniform_background(energy, event_params, rmf, prng=prng)
def test_uniform_bkgnd_scale():
hdxi_arf = AuxiliaryResponseFile("xrs_hdxi_3x10.arf")
events, event_params = make_background((50, "ks"),
"hdxi", [30., 45.],
foreground=True,
instr_bkgnd=True,
ptsrc_bkgnd=False,
prng=prng)
ncts = np.logical_and(events["energy"] >= 0.7,
events["energy"] <= 2.0).sum()
t_exp = event_params["exposure_time"]
fov = (event_params["fov"] * 60.0)**2
S = ncts / t_exp / fov
dS = np.sqrt(ncts) / t_exp / fov
foreground = ConvolvedBackgroundSpectrum(hm_astro_bkgnd, hdxi_arf)
f_sum = foreground.get_flux_in_band(0.7, 2.0)[0]
i_sum = acisi_particle_bkgnd.get_flux_in_band(0.7, 2.0)[0]
b_sum = (f_sum + i_sum).to("ph/(arcsec**2*s)").value
assert np.abs(S - b_sum) < 1.645 * dS
def make_foreground(event_params, arf, rmf, prng=None):
prng = parse_prng(prng)
conv_frgnd_spec = ConvolvedBackgroundSpectrum.convolve(hm_astro_bkgnd, arf)
bkg_events = {"energy": [], "detx": [], "dety": [], "chip_id": []}
pixel_area = (event_params["plate_scale"]*60.0)**2
for i, chip in enumerate(event_params["chips"]):
rtype = chip[0]
args = chip[1:]
r, bounds = create_region(rtype, args, 0.0, 0.0)
fov = np.sqrt((bounds[1]-bounds[0])*(bounds[3]-bounds[2])*pixel_area)
e = conv_frgnd_spec.generate_energies(event_params["exposure_time"],
fov, prng=prng, quiet=True).value
n_events = e.size
detx = prng.uniform(low=bounds[0], high=bounds[1], size=n_events)
dety = prng.uniform(low=bounds[2], high=bounds[3], size=n_events)
if rtype in ["Box", "Rectangle"]:
thisc = slice(None, None, None)
n_det = n_events
else:
thisc = r.contains(PixCoord(detx, dety))
n_det = thisc.sum()
bkg_events["energy"].append(e[thisc])
bkg_events["detx"].append(detx[thisc])
bkg_events["dety"].append(dety[thisc])
bkg_events["chip_id"].append(i*np.ones(n_det))
for key in bkg_events:
bkg_events[key] = np.concatenate(bkg_events[key])
if bkg_events["energy"].size == 0:
raise RuntimeError("No astrophysical foreground events "
"were detected!!!")
else:
mylog.info(f"Making {bkg_events['energy'].size} events from the "
f"astrophysical foreground.")
bkg_events = make_diffuse_background(bkg_events,
event_params, rmf, prng=prng)
mylog.info(f"Scattering energies with "
f"RMF {os.path.split(rmf.filename)[-1]}.")
return rmf.scatter_energies(bkg_events, prng=prng)