def test_annulus(answer_store, answer_dir):
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
r_in = 10.0
r_out = 30.0
ann_pos = AnnulusModel(ra0, dec0, r_in, r_out)
ann_src = SimputPhotonList.from_models("ann", spec, ann_pos,
exp_time, area, prng=prng)
sim_cat = SimputCatalog.from_source("ann_simput.fits", ann_src,
overwrite=True)
instrument_simulator("ann_simput.fits", "ann_evt.fits", exp_time,
"lynx_hdxi", [ra0, dec0], ptsrc_bkgnd=False,
instr_bkgnd=False, foreground=False, prng=prng)
write_radial_profile("ann_evt.fits", "ann_evt_profile.fits", [ra0, dec0],
1.1*r_in, 0.9*r_out, 100, ctr_type="celestial",
emin=0.5, emax=7.0, overwrite=True)
file_answer_testing("EVENTS", "ann_evt.fits", answer_store, answer_dir)
file_answer_testing("PROFILE", "ann_evt_profile.fits", answer_store,
answer_dir)
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_beta_model(answer_store, answer_dir):
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
prng = 32
r_c = 20.0
beta = 1.0
exp_time = Quantity(500.0, "ks")
beta_src_pos = BetaModel(ra0, dec0, r_c, beta)
beta_src = SimputPhotonList.from_models("beta", spec, beta_src_pos,
exp_time, area, prng=prng)
sim_cat = SimputCatalog.from_source("beta_simput.fits", beta_src,
overwrite=True)
instrument_simulator("beta_simput.fits", "beta_evt.fits", exp_time,
"chandra_acisi_cy0", [ra0, dec0], ptsrc_bkgnd=False,
instr_bkgnd=False, foreground=False, prng=prng)
write_radial_profile("beta_evt.fits", "beta_evt_profile.fits", [ra0, dec0],
0.0, 100.0, 200, ctr_type="celestial", emin=0.5,
emax=7.0, overwrite=True)
file_answer_testing("EVENTS", "beta_evt.fits", answer_store,
answer_dir)
file_answer_testing("PROFILE", "beta_evt_profile.fits", answer_store,
answer_dir)
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_point_source():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
pt_src = SimputSpectrum.from_spectrum("pt_src", spec, ra0, dec0)
cat = SimputCatalog.from_source("pt_src_simput.fits", pt_src,
overwrite=True)
inst = get_instrument_from_registry("lynx_hdxi")
inst["name"] = "hdxi_big_psf"
inst["psf"] = ["gaussian", 5.0]
add_instrument_to_registry(inst)
instrument_simulator("pt_src_simput.fits", "pt_src_evt.fits", exp_time,
"hdxi_big_psf", [ra0, dec0], ptsrc_bkgnd=False,
instr_bkgnd=False, foreground=False, prng=prng)
psf_scale = inst["psf"][1]
dtheta = inst["fov"]*60.0/inst["num_pixels"]
f = pyfits.open("pt_src_evt.fits")
x = f["EVENTS"].data["X"]
y = f["EVENTS"].data["Y"]
f.close()
scalex = np.std(x)*sigma_to_fwhm*dtheta
scaley = np.std(y)*sigma_to_fwhm*dtheta
assert (scalex - psf_scale)/psf_scale < 0.03
assert (scaley - psf_scale)/psf_scale < 0.03
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_annulus(answer_store, answer_dir):
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
r_in = 10.0
r_out = 30.0
ann_pos = AnnulusModel(ra0, dec0, r_in, r_out)
sim_cat = SimputCatalog.from_models("ann", "ann", spec, ann_pos,
exp_time, area, prng=prng)
sim_cat.write_catalog(overwrite=True)
instrument_simulator("ann_simput.fits", "ann_evt.fits", exp_time,
"hdxi", [ra0, dec0], ptsrc_bkgnd=False,
instr_bkgnd=False, foreground=False, prng=prng)
write_radial_profile("ann_evt.fits", "ann_evt_profile.fits", [ra0, dec0],
1.1*r_in, 0.9*r_out, 100, ctr_type="celestial",
emin=0.5, emax=7.0, overwrite=True)
file_answer_testing("EVENTS", "ann_evt.fits", answer_store, answer_dir)
file_answer_testing("PROFILE", "ann_evt_profile.fits", answer_store, answer_dir)
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_beta_model_flux(answer_store, answer_dir):
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
r_c = 20.0
beta = 1.0
prng = 34
beta_src_pos = BetaModel(ra0, dec0, r_c, beta)
sim_cat = SimputCatalog.from_models("beta", "beta", spec, beta_src_pos,
exp_time, area, prng=prng)
sim_cat.write_catalog(overwrite=True)
instrument_simulator("beta_simput.fits", "beta_flux_evt.fits", exp_time,
"acisi_cy0", [ra0, dec0], ptsrc_bkgnd=False,
instr_bkgnd=False, foreground=False,
roll_angle=37.0, prng=prng)
wspec = spec.new_spec_from_band(0.5, 7.0)
make_exposure_map("beta_flux_evt.fits", "beta_expmap.fits", wspec.emid.value,
weights=wspec.flux.value, overwrite=True)
write_radial_profile("beta_flux_evt.fits", "beta_flux_evt_profile.fits",
[ra0, dec0], 0.0, 100.0, 200, ctr_type="celestial",
emin=0.5, emax=7.0, expmap_file="beta_expmap.fits",
overwrite=True)
file_answer_testing("EVENTS", "beta_flux_evt.fits", answer_store, answer_dir)
file_answer_testing("PROFILE", "beta_flux_evt_profile.fits", answer_store, answer_dir)
os.chdir(curdir)
shutil.rmtree(tmpdir)
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_beta_model(answer_store, answer_dir):
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
prng = 32
r_c = 20.0
beta = 1.0
exp_time = Quantity(500.0, "ks")
beta_src_pos = BetaModel(ra0, dec0, r_c, beta)
sim_cat = SimputCatalog.from_models("beta", "beta", spec, beta_src_pos,
exp_time, area, prng=prng)
sim_cat.write_catalog(overwrite=True)
instrument_simulator("beta_simput.fits", "beta_evt.fits", exp_time,
"acisi_cy0", [ra0, dec0], ptsrc_bkgnd=False,
instr_bkgnd=False, foreground=False, prng=prng)
write_radial_profile("beta_evt.fits", "beta_evt_profile.fits", [ra0, dec0],
0.0, 100.0, 200, ctr_type="celestial", emin=0.5,
emax=7.0, overwrite=True)
file_answer_testing("EVENTS", "beta_evt.fits", answer_store, answer_dir)
file_answer_testing("PROFILE", "beta_evt_profile.fits", answer_store, answer_dir)
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_beta_model_flux(answer_store, answer_dir):
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
r_c = 20.0
beta = 1.0
prng = 34
beta_src_pos = BetaModel(ra0, dec0, r_c, beta)
sim_cat = SimputCatalog.from_models("beta",
"beta",
spec,
beta_src_pos,
exp_time,
area,
prng=prng)
sim_cat.write_catalog(overwrite=True)
instrument_simulator("beta_simput.fits",
"beta_flux_evt.fits",
exp_time,
"acisi_cy0", [ra0, dec0],
ptsrc_bkgnd=False,
instr_bkgnd=False,
foreground=False,
roll_angle=37.0,
prng=prng)
wspec = spec.new_spec_from_band(0.5, 7.0)
make_exposure_map("beta_flux_evt.fits",
"beta_expmap.fits",
wspec.emid.value,
weights=wspec.flux.value,
overwrite=True)
write_radial_profile("beta_flux_evt.fits",
"beta_flux_evt_profile.fits", [ra0, dec0],
0.0,
100.0,
200,
ctr_type="celestial",
emin=0.5,
emax=7.0,
expmap_file="beta_expmap.fits",
overwrite=True)
file_answer_testing("EVENTS", "beta_flux_evt.fits", answer_store,
answer_dir)
file_answer_testing("PROFILE", "beta_flux_evt_profile.fits", 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, 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 test_append():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
exp_time = (50.0, "ks")
area = (4.0, "m**2")
ra0 = 30.0
dec0 = 45.0
spec = Spectrum.from_powerlaw(1.1, 0.05, 1.0e-4, 0.1, 10.0, 10000)
pos1 = PointSourceModel(ra0+0.05, dec0+0.05)
pos2 = PointSourceModel(ra0-0.05, dec0-0.05)
pl1 = SimputPhotonList.from_models("pt_src1", spec, pos1, exp_time, area)
pl2 = SimputPhotonList.from_models("pt_src2", spec, pos2, exp_time, area)
sc = SimputCatalog.from_source("pt_src_simput.fits", pl1,
src_filename="pt_src1_phlist.fits",
overwrite=True)
sc.append(pl2, src_filename="pt_src2_phlist.fits",
overwrite=True)
assert os.path.exists("pt_src1_phlist.fits")
assert os.path.exists("pt_src2_phlist.fits")
assert os.path.exists("pt_src_simput.fits")
f = pyfits.open("pt_src_simput.fits")
cat = f["SRC_CAT"].data["SPECTRUM"]
assert cat[0] == "pt_src1_phlist.fits[PHLIST,1]"
assert cat[1] == "pt_src2_phlist.fits[PHLIST,1]"
f.close()
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_point_source():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
pt_src_pos = PointSourceModel(ra0, dec0)
sim_cat = SimputCatalog.from_models("pt_src", "pt_src", spec, pt_src_pos,
exp_time, area, prng=prng)
sim_cat.write_catalog(overwrite=True)
inst = get_instrument_from_registry("hdxi")
inst["name"] = "hdxi_big_psf"
inst["psf"] = ["gaussian", 5.0]
add_instrument_to_registry(inst)
instrument_simulator("pt_src_simput.fits", "pt_src_evt.fits", exp_time,
"hdxi_big_psf", [ra0, dec0], ptsrc_bkgnd=False,
instr_bkgnd=False, foreground=False, prng=prng)
psf_scale = inst["psf"][1]
dtheta = inst["fov"]*60.0/inst["num_pixels"]
f = pyfits.open("pt_src_evt.fits")
x = f["EVENTS"].data["X"]
y = f["EVENTS"].data["Y"]
f.close()
scalex = np.std(x)*sigma_to_fwhm*dtheta
scaley = np.std(y)*sigma_to_fwhm*dtheta
assert (scalex - psf_scale)/psf_scale < 0.03
assert (scaley - psf_scale)/psf_scale < 0.03
os.chdir(curdir)
shutil.rmtree(tmpdir)
def make_point_sources_file(filename,
name,
exp_time,
fov,
sky_center,
absorb_model="wabs",
nH=0.05,
area=40000.0,
prng=None,
append=False,
overwrite=False,
src_filename=None,
input_sources=None,
output_sources=None):
"""
Make a SIMPUT catalog made up of contributions from
point sources.
Parameters
----------
filename : string
The filename for the SIMPUT catalog.
name : string
The name of the SIMPUT photon list.
exp_time : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The exposure time of the observation in seconds.
fov : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The field of view in arcminutes.
sky_center : array-like
The center RA, Dec of the field of view in degrees.
absorb_model : string, optional
The absorption model to use, "wabs" or "tbabs". Default: "wabs"
nH : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`, optional
The hydrogen column in units of 10**22 atoms/cm**2.
Default: 0.05
area : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`, optional
The effective area in cm**2. It must be large enough
so that a sufficiently large sample is drawn for the
ARF. Default: 40000.
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.
append : boolean, optional
If True, the photon list source will be appended to an existing
SIMPUT catalog. Default: False
overwrite : boolean, optional
Set to True to overwrite previous files. Default: False
src_filename : string, optional
If set, this will be the filename to write the source
to. By default, the source will be written to the same
file as the SIMPUT catalog.
input_sources : string, optional
If set to a filename, input the source positions, fluxes,
and spectral indices from an ASCII table instead of generating
them. Default: None
output_sources : string, optional
If set to a filename, output the properties of the sources
within the field of view to a file. Default: None
"""
events = make_ptsrc_background(exp_time,
fov,
sky_center,
absorb_model=absorb_model,
nH=nH,
area=area,
input_sources=input_sources,
output_sources=output_sources,
prng=prng)
phlist = SimputPhotonList(events["ra"],
events["dec"],
events["energy"],
events["flux"],
name=name)
if append:
cat = SimputCatalog.from_file(filename)
cat.append(phlist, src_filename=src_filename, overwrite=overwrite)
else:
cat = SimputCatalog.from_source(filename,
phlist,
src_filename=src_filename,
overwrite=overwrite)
return cat
def make_cosmological_sources_file(filename, name, exp_time, fov,
sky_center, cat_center=None,
absorb_model="wabs", nH=0.05, area=40000.0,
overwrite=False, output_sources=None,
write_regions=None, src_filename=None,
prng=None, append=False):
r"""
Make a SIMPUT catalog made up of contributions from
galaxy clusters, galaxy groups, and galaxies.
Parameters
----------
filename : string
The filename for the SIMPUT catalog.
name : string
The name of the SIMPUT photon list.
exp_time : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The exposure time of the observation in seconds.
fov : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The field of view in arcminutes.
sky_center : array-like
The center RA, Dec of the field of view in degrees.
cat_center : array-like
The center of the field in the coordinates of the
halo catalog, which range from -5.0 to 5.0 degrees
along both axes. If None is given, a center will be
randomly chosen.
absorb_model : string, optional
The absorption model to use, "wabs" or "tbabs". Default: "wabs"
nH : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`, optional
The hydrogen column in units of 10**22 atoms/cm**2.
Default: 0.05
area : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`, optional
The effective area in cm**2. It must be large enough
so that a sufficiently large sample is drawn for the
ARF. Default: 40000.
overwrite : boolean, optional
Set to True to overwrite previous files. Default: False
output_sources : string, optional
If set to a filename, output the properties of the sources
within the field of view to an ASCII file. Default: None
write_regions : string, optional
If set to a filename, output circle ds9 regions corresponding to the
positions of the halos with radii corresponding to their R500
projected on the sky. Default: None
src_filename : string, optional
If set, this will be the filename to write the source
to. By default, the source will be written to the same
file as the SIMPUT catalog
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.
append : boolean, optional
If True, the photon list source will be appended to an existing
SIMPUT catalog. Default: False
"""
events = make_cosmological_sources(exp_time, fov, sky_center,
cat_center=cat_center,
absorb_model=absorb_model, nH=nH,
area=area, output_sources=output_sources,
write_regions=write_regions,prng=prng)
phlist = SimputPhotonList(events["ra"], events["dec"], events["energy"],
events["flux"], name=name)
if append:
cat = SimputCatalog.from_file(filename)
cat.append(phlist, src_filename=src_filename, overwrite=overwrite)
else:
cat = SimputCatalog.from_source(filename, phlist,
src_filename=src_filename,
overwrite=overwrite)
return cat