def test_constructor():
# RA, Dec and L,B of the same point in the sky
ra, dec = (125.6, -75.3)
l, b = (288.44190139183564, -20.717313145391525)
# This should throw an error as we are using Powerlaw instead of Powerlaw()
with pytest.raises(RuntimeError):
_ = ExtendedSource("my_source", Gaussian_on_sphere, Powerlaw)
# This should throw an error because we should use a 2D function for the spatial shape
with pytest.raises(RuntimeError):
_ = ExtendedSource("my_source", Powerlaw(), Powerlaw())
# Init with RA, Dec
shape = Gaussian_on_sphere()
source1 = ExtendedSource('my_source', shape, Powerlaw())
shape.lon0 = ra * u.degree
shape.lat0 = dec * u.degree
assert source1.spatial_shape.lon0.value == ra
assert source1.spatial_shape.lat0.value == dec
# Verify that the position is free by default
assert source1.spatial_shape.lon0.free
assert source1.spatial_shape.lon0.free
def _get_point_source_composite(name):
spectral_shape = Powerlaw() + Powerlaw()
pts = PointSource(name, l=0, b=0, spectral_shape=spectral_shape)
return pts
def test_input_output_with_complex_functions():
my_particle_distribution = Powerlaw()
my_particle_distribution.index = -1.52
electrons = ParticleSource('electrons',
distribution_shape=my_particle_distribution)
# Now set up the synch. spectrum for our source and the source itself
synch_spectrum = _ComplexTestFunction()
# Use the particle distribution we created as source for the electrons
# producing synch. emission
synch_spectrum.particle_distribution = my_particle_distribution
synch_source = PointSource('synch_source',
ra=12.6,
dec=-13.5,
spectral_shape=synch_spectrum)
my_model = Model(electrons, synch_source)
my_model.display()
my_model.save("__test.yml")
new_model = load_model("__test.yml")
assert len(new_model.sources) == len(my_model.sources)
assert my_particle_distribution.index.value == new_model.electrons.spectrum.main.shape.index.value
def test_call_with_composite_function_with_units():
def one_test(spectrum):
print("Testing %s" % spectrum.expression)
pts = PointSource("test", ra=0, dec=0, spectral_shape=spectrum)
res = pts([100, 200] * u.keV)
# This will fail if the units are wrong
res.to(1 / (u.keV * u.cm**2 * u.s))
# Test a simple composition
spectrum = Powerlaw() * Exponential_cutoff()
one_test(spectrum)
spectrum = Band() + Blackbody()
one_test(spectrum)
# Test a more complicate composition
spectrum = Powerlaw() * Exponential_cutoff() + Blackbody()
one_test(spectrum)
spectrum = Powerlaw() * Exponential_cutoff() * Exponential_cutoff(
) + Blackbody()
one_test(spectrum)
if has_xspec:
spectrum = XS_phabs() * Powerlaw()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw() * XS_phabs()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw() * XS_phabs() + Blackbody()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw() * XS_phabs() + XS_powerlaw()
one_test(spectrum)
def test_memoizer():
po = Powerlaw()
a = np.random.uniform(-3, -1, 2000)
b = np.random.uniform(0.1, 10, 2000)
for aa, bb in zip(a, b):
po.index = aa
po.K = bb
po(1.0)
def test_one(class_type):
instance = class_type()
if not instance.is_prior:
# if we have fixed x_units then we will use those
# in the test
if instance.has_fixed_units():
x_unit_to_use = instance.fixed_units[0]
else:
x_unit_to_use = u.keV
# Use the function as a spectrum
ps = PointSource("test", 0, 0, instance)
if instance.name in ["Synchrotron", "_ComplexTestFunction"]:
particleSource = ParticleSource("particles", Powerlaw())
instance.set_particle_distribution(
particleSource.spectrum.main.shape)
result = ps(1.0)
assert isinstance(result, float)
result = ps(1.0 * x_unit_to_use)
assert isinstance(result, u.Quantity)
result = ps(np.array([1, 2, 3]) * x_unit_to_use)
assert isinstance(result, u.Quantity)
if instance.name in ["Synchrotron", "_ComplexTestFunction"]:
model = Model(particleSource, ps)
else:
model = Model(ps)
new_model = clone_model(model)
new_result = new_model["test"](np.array([1, 2, 3]) * x_unit_to_use)
assert np.all(new_result == result)
model.save("__test.yml", overwrite=True)
new_model = load_model("__test.yml")
new_result = new_model["test"](np.array([1, 2, 3]) * x_unit_to_use)
assert np.all(new_result == result)
else:
print('Skipping prior function')
def test_input_output():
tm = TemplateModel('__test')
tm.alpha = -0.95
tm.beta = -2.23
fake_source = PointSource("test", ra=0.0, dec=0.0, spectral_shape=tm)
fake_model = Model(fake_source)
clone = clone_model(fake_model)
assert clone.get_number_of_point_sources() == 1
assert tm.data_file == clone.test.spectrum.main.shape.data_file
assert clone.test.spectrum.main.shape.alpha.value == tm.alpha.value
assert clone.test.spectrum.main.shape.beta.value == tm.beta.value
xx = np.linspace(1, 10, 100)
assert np.allclose(clone.test.spectrum.main.shape(xx), fake_model.test.spectrum.main.shape(xx))
# Test pickling
dump = pickle.dumps(clone)
clone2 = pickle.loads(dump)
assert clone2.get_number_of_point_sources() == 1
assert tm.data_file == clone2.test.spectrum.main.shape.data_file
assert np.allclose(clone2.test.spectrum.main.shape(xx), fake_model.test.spectrum.main.shape(xx))
# Test pickling with other functions
new_shape = tm * Powerlaw()
new_shape.index_2 = -2.256
dump2 = pickle.dumps(new_shape)
clone3 = pickle.loads(dump2)
assert clone3.index_2.value == new_shape.index_2.value
# Now save to disk and reload
fake_source2 = PointSource("test", ra=0.0, dec=0.0, spectral_shape=new_shape)
fake_model2 = Model(fake_source2)
fake_model2.save("__test.yml", overwrite=True)
# Now try to reload
reloaded_model = load_model("__test.yml")
assert reloaded_model.get_number_of_point_sources() == 1
assert np.allclose(fake_model2.test.spectrum.main.shape(xx), reloaded_model.test.spectrum.main.shape(xx))
os.remove("__test.yml")
def test_call():
# Multi-component
po1 = Powerlaw()
po2 = Powerlaw()
c1 = SpectralComponent("component1", po1)
c2 = SpectralComponent("component2", po2)
point_source = PointSource("test_source", 125.4, -22.3, components=[c1, c2])
assert np.all(point_source.spectrum.component1([1, 2, 3]) == po1([1, 2, 3]))
assert np.all(point_source.spectrum.component2([1, 2, 3]) == po2([1, 2, 3]))
one = point_source.spectrum.component1([1, 2, 3])
two = point_source.spectrum.component2([1, 2, 3])
assert np.all( np.abs(one + two - point_source([1,2,3])) == 0 )
def test_constructor_1source():
# Test with one point source
pts = _get_point_source()
m = Model(pts)
# Test with a point source with an invalid name
with pytest.raises(AssertionError):
_ = PointSource("name", 0, 0, Powerlaw())
assert len(m.sources) == 1
def test_pickling_unpickling():
# 1d function
po = Powerlaw()
po.K = 5.35
new_po = pickle.loads(pickle.dumps(po))
assert new_po.K.value == po.K.value
# 2d function
gs = Gaussian_on_sphere()
_ = pickle.loads(pickle.dumps(gs))
# 3d function
c = Continuous_injection_diffusion()
_ = pickle.loads(pickle.dumps(c))
# composite function
po2 = Powerlaw()
li = Line()
composite = po2 * li + po2 - li + 2 * po2 / li # type: Function1D
# Change some parameter
composite.K_1 = 3.2
composite.a_2 = 1.56
dump = pickle.dumps(composite)
new_composite = pickle.loads(dump)
assert new_composite.K_1.value == composite.K_1.value
assert new_composite.a_2.value == composite.a_2.value
def test_add_and_remove_independent_variable():
mg = ModelGetter()
m = mg.model
# Create an independent variable
independent_variable = IndependentVariable("time", 1.0, u.s)
# Try to add it
m.add_independent_variable(independent_variable)
# Try to remove it
m.remove_independent_variable("time")
with pytest.raises(AssertionError):
m.add_independent_variable(Parameter("time", 1.0))
# Try to add it twice, which shouldn't fail
m.add_independent_variable(independent_variable)
m.add_independent_variable(independent_variable)
# Try to display it just to make sure it works
m.display()
# Now try to use it
link_law = Powerlaw()
link_law.K.value = 1.0
link_law.index.value = -1.0
n_free_before_link = len(m.free_parameters)
m.link(m.one.spectrum.main.Powerlaw.K, independent_variable, link_law)
# The power law adds two parameters, but the link removes one, so
assert len(m.free_parameters) - 1 == n_free_before_link
# Now see if it works
for t in np.linspace(0, 10, 100):
independent_variable.value = t
assert m.one.spectrum.main.Powerlaw.K.value == link_law(t)
def test_constructor_1source():
# Test with one point source
pts = _get_point_source()
m = Model(pts)
# Test with a point source with an invalid name
pts = PointSource("name", 0, 0, Powerlaw())
with pytest.raises(InvalidInput):
_ = Model(pts)
# Test with two identical point sources, which should raise, as sources must have unique names
many_sources = [pts] * 2
with pytest.raises(InvalidInput):
_ = Model(*many_sources)
def test_display():
mg = ModelGetter()
m = mg.model
m.display()
m.display(complete=True)
# Now display a model without free parameters
m = Model(PointSource("test", 0.0, 0.0, Powerlaw()))
for parameter in m.parameters.values():
parameter.fix = True
m.display()
# Now display a model without fixed parameters (very unlikely)
for parameter in m.parameters.values():
parameter.free = True
m.display()
def test_duplicate():
instance = Powerlaw()
instance.index = -2.25
instance.K = 0.5
# Duplicate it
duplicate = instance.duplicate()
# Check that we have the same results
assert duplicate(2.25) == instance(2.25)
# Check that the parameters are not linked anymore
instance.index = -1.12
assert instance.index.value != duplicate.index.value
print(instance)
print(duplicate)
def _get_point_source(name="test"):
pts = PointSource(name, ra=0, dec=0, spectral_shape=Powerlaw())
return pts
def _get_particle_source(name="test_part"):
part = ParticleSource(name, Powerlaw())
return part
def _get_extended_source(name="test_ext"):
ext = ExtendedSource(name, Gaussian_on_sphere(), Powerlaw())
return ext
def test_call():
# Multi-component
po1 = Powerlaw()
po2 = Powerlaw()
c1 = SpectralComponent("component1", po1)
c2 = SpectralComponent("component2", po2)
ra, dec = (125.6, -75.3)
def test_one(class_type, name):
print("testing %s ..." % name)
shape = class_type()
source = ExtendedSource('test_source_%s' % name,
shape,
components=[c1, c2])
if name != "SpatialTemplate_2D":
shape.lon0 = ra * u.degree
shape.lat0 = dec * u.degree
else:
make_test_template(ra, dec, "__test.fits")
shape.load_file("__test.fits")
shape.K = 1.0
assert np.all(source.spectrum.component1([1, 2, 3]) == po1([1, 2, 3]))
assert np.all(source.spectrum.component2([1, 2, 3]) == po2([1, 2, 3]))
one = source.spectrum.component1([1, 2, 3])
two = source.spectrum.component2([1, 2, 3])
#check spectral components
assert np.all(
np.abs(one + two -
source.get_spatially_integrated_flux([1, 2, 3])) == 0)
#check spectral and spatial components
total = source([ra, ra, ra], [dec, dec, dec], [1, 2, 3])
spectrum = one + two
spatial = source.spatial_shape([ra, ra, ra], [dec, dec, dec])
assert np.all(np.abs(total - spectrum * spatial) == 0)
total = source([ra * 1.01] * 3, [dec * 1.01] * 3, [1, 2, 3])
spectrum = one + two
spatial = source.spatial_shape([ra * 1.01] * 3, [dec * 1.01] * 3)
assert np.all(np.abs(total - spectrum * spatial) == 0)
for key in _known_functions:
if key in ["Latitude_galactic_diffuse"]:
#not testing latitude galactic diffuse for now.
continue
this_function = _known_functions[key]
if this_function._n_dim == 2 and not this_function().is_prior:
test_one(this_function, key)
with pytest.raises(AssertionError):
#this will fail because the Latitude_galactic_diffuse function isn't normalized.
test_one(_known_functions["Latitude_galactic_diffuse"],
"Latitude_galactic_diffuse")
def test_links():
mg = ModelGetter()
m = mg.model
n_free_before_link = len(m.free_parameters)
# Link as equal (default)
m.link(m.one.spectrum.main.Powerlaw.K, m.two.spectrum.main.Powerlaw.K)
assert len(m.free_parameters) == n_free_before_link - 1
# Try to display it just to make sure it works
m.display()
# Now test the link
# This should print a warning, as trying to change the value of a linked parameters does not have any effect
with pytest.warns(RuntimeWarning):
m.one.spectrum.main.Powerlaw.K = 1.23456
# This instead should work
new_value = 1.23456
m.two.spectrum.main.Powerlaw.K.value = new_value
assert m.one.spectrum.main.Powerlaw.K.value == new_value
# Now try to remove the link
# First we remove it from the wrong parameters, which should issue a warning
with pytest.warns(RuntimeWarning):
m.unlink(m.two.spectrum.main.Powerlaw.K)
# Remove it from the right parameter
m.unlink(m.one.spectrum.main.Powerlaw.K)
assert len(m.free_parameters) == n_free_before_link
# Redo the same, but with a powerlaw law
link_law = Powerlaw()
link_law.K.value = 1.0
link_law.index.value = -1.0
n_free_before_link = len(m.free_parameters)
m.link(m.one.spectrum.main.Powerlaw.K, m.two.spectrum.main.Powerlaw.K,
link_law)
# The power law adds two parameters, but the link removes one, so
assert len(m.free_parameters) - 1 == n_free_before_link
# Check that the link works
new_value = 1.23456
m.two.spectrum.main.Powerlaw.K.value = new_value
predicted_value = link_law(new_value)
assert m.one.spectrum.main.Powerlaw.K.value == predicted_value
# Remove the link
m.unlink(m.one.spectrum.main.Powerlaw.K)
def _get_point_source_gal(name):
pts = PointSource(name, l=0, b=0, spectral_shape=Powerlaw())
return pts
def test_call_with_composite_function_with_units():
def one_test(spectrum):
print(("Testing %s" % spectrum.expression))
# # if we have fixed x_units then we will use those
# # in the test
#
# if spectrum.expression.has_fixed_units():
#
# x_unit_to_use, y_unit_to_use = spectrum.expression.fixed_units[0]
#
# else:
x_unit_to_use = u.keV
pts = PointSource("test", ra=0, dec=0, spectral_shape=spectrum)
res = pts([100, 200] * x_unit_to_use)
# This will fail if the units are wrong
res.to(1 / (u.keV * u.cm**2 * u.s))
# Test a simple composition
spectrum = Powerlaw() * Exponential_cutoff()
one_test(spectrum)
spectrum = Band() + Blackbody()
one_test(spectrum)
# Test a more complicate composition
spectrum = Powerlaw() * Exponential_cutoff() + Blackbody()
one_test(spectrum)
spectrum = Powerlaw() * Exponential_cutoff() * Exponential_cutoff() + Blackbody()
one_test(spectrum)
if has_xspec:
spectrum = XS_phabs() * Powerlaw()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw() * XS_phabs()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw() * XS_phabs() + Blackbody()
one_test(spectrum)
spectrum = XS_phabs() * XS_powerlaw() * XS_phabs() + XS_powerlaw()
one_test(spectrum)
def test_time_domain_integration():
po = Powerlaw()
default_powerlaw = Powerlaw()
src = PointSource("test", ra=0.0, dec=0.0, spectral_shape=po)
m = Model(src) # type: model.Model
# Add time independent variable
time = IndependentVariable("time", 0.0, u.s)
m.add_independent_variable(time)
# Now link one of the parameters with a simple line law
line = Line()
line.a = 0.0
m.link(po.index, time, line)
# Test the display just to make sure it doesn't crash
m.display()
# Now test the average with the integral
energies = np.linspace(1, 10, 10)
results = m.get_point_source_fluxes(0, energies,
tag=(time, 0, 10)) # type: np.ndarray
assert np.all(results == 1.0)
# Now test the linking of the normalization, first with a constant then with a line with a certain
# angular coefficient
m.unlink(po.index)
po.index.value = default_powerlaw.index.value
line2 = Line()
line2.a = 0.0
line2.b = 1.0
m.link(po.K, time, line2)
time.value = 1.0
results = m.get_point_source_fluxes(0, energies, tag=(time, 0, 10))
assert np.allclose(results, default_powerlaw(energies))
# Now make something actually happen
line2.a = 1.0
line2.b = 1.0
results = m.get_point_source_fluxes(0, energies,
tag=(time, 0, 10)) # type: np.ndarray
# Compare with analytical result
def F(x):
return line2.a.value / 2.0 * x**2 + line2.b.value * x
effective_norm = (F(10) - F(0)) / 10.0
expected_results = default_powerlaw(
energies) * effective_norm # type: np.ndarray
assert np.allclose(expected_results, results)
def test_constructor():
# RA, Dec and L,B of the same point in the sky
ra, dec = (125.6, -75.3)
l, b = (288.44190139183564, -20.717313145391525)
# This should throw as we are using Powerlaw instead of Powerlaw()
with pytest.raises(TypeError):
_ = PointSource("my_source", ra, dec, Powerlaw)
# Init with RA, Dec
point_source1 = PointSource('my_source', ra, dec, Powerlaw())
assert point_source1.position.get_ra() == ra
assert point_source1.position.get_dec() == dec
assert abs(point_source1.position.get_l() - l) < 1e-7
assert abs(point_source1.position.get_b() - b) < 1e-7
assert point_source1.position.ra.value == ra
assert point_source1.position.dec.value == dec
# Init with l,b
point_source2 = PointSource('my_source',
l=l,
b=b,
spectral_shape=Powerlaw())
assert point_source2.position.get_l() == l
assert point_source2.position.get_b() == b
assert abs(point_source2.position.get_ra() - ra) < 1e-7
assert abs(point_source2.position.get_dec() - dec) < 1e-7
assert point_source2.position.l.value == l
assert point_source2.position.b.value == b
# Multi-component
po1 = Powerlaw()
po2 = Powerlaw()
c1 = SpectralComponent("component1", po1)
c2 = SpectralComponent("component2", po2)
point_source3 = PointSource("test_source", ra, dec, components=[c1, c2])
assert np.all(
point_source3.spectrum.component1([1, 2, 3]) == po1([1, 2, 3]))
assert np.all(
point_source3.spectrum.component2([1, 2, 3]) == po2([1, 2, 3]))
with pytest.raises(AssertionError):
# Illegal RA
_ = PointSource("test", 720.0, -15.0, components=[c1, c2])
with pytest.raises(AssertionError):
# Illegal Dec
_ = PointSource("test", 120.0, 180.0, components=[c1, c2])
with pytest.raises(AssertionError):
# Illegal l
_ = PointSource("test", l=-195, b=-15.0, components=[c1, c2])
with pytest.raises(AssertionError):
# Illegal b
_ = PointSource("test", l=120.0, b=-180.0, components=[c1, c2])
def test_function_composition():
Test_function = get_a_function_class()
line = Test_function()
powerlaw = Powerlaw()
composite = powerlaw + line
composite.set_units(u.keV, 1.0 / (u.keV * u.cm**2 * u.s))
for x in ([1, 2, 3,
4], [1, 2, 3, 4] * u.keV, 1.0, np.array([1.0, 2.0, 3.0, 4.0])):
assert np.all(composite(x) == line(x) + powerlaw(x))
# Test -
po = Powerlaw()
li = Line()
composite = po - li
assert composite(1.0) == (po(1.0) - li(1.0))
# test *
composite = po * li
assert composite(2.25) == po(2.25) * li(2.25)
# test /
composite = po / li
assert composite(2.25) == po(2.25) / li(2.25)
# test .of
composite = po.of(li)
assert composite(2.25) == po(li(2.25))
# test power
composite = po**li
assert composite(2.25) == po(2.25)**li(2.25)
# test negation
neg_po = -po
assert neg_po(2.25) == -po(2.25)
# test abs
new_li = Line()
new_li.b = -10.0
abs_new_li = abs(new_li)
assert new_li(1.0) < 0
assert abs_new_li(1.0) == abs(new_li(1.0))
# test rpower
composite = 2.0**new_li
assert composite(2.25) == 2.0**(new_li(2.25))
# test multiplication by a number
composite = 2.0 * po
assert composite(2.25) == 2.0 * po(2.25)
# Number divided by
composite = 1.0 / li
assert composite(2.25) == 1.0 / li(2.25)
# Composite of composite
composite = po * li + po - li + 2 * po / li
assert composite(2.25) == po(2.25) * li(2.25) + po(2.25) - li(
2.25) + 2 * po(2.25) / li(2.25)
print(composite)
def test_call_with_units():
po = Powerlaw()
result = po(1.0)
assert result.ndim == 0
with pytest.raises(AssertionError):
# This raises because the units of the function have not been set up
_ = po(1.0 * u.keV)
# Use the function as a spectrum
ps = PointSource("test", 0, 0, po)
result = po(1.0 * u.keV)
assert isinstance(result, u.Quantity)
result = po(np.array([1, 2, 3]) * u.keV)
assert isinstance(result, u.Quantity)
# Now test all the functions
def test_one(class_type):
instance = class_type()
# Use the function as a spectrum
ps = PointSource("test", 0, 0, instance)
result = ps(1.0 * u.keV)
assert isinstance(result, u.Quantity)
result = ps(np.array([1, 2, 3]) * u.keV)
assert isinstance(result, u.Quantity)
result = ps(1.0)
assert isinstance(result, float)
for key in _known_functions:
this_function = _known_functions[key]
# Test only the power law of XSpec, which is the only one we know we can test at 1 keV
if key.find("XS") == 0 and key != "XS_powerlaw":
# An XSpec model. Test it only if it's a power law (the others might need other parameters during
# initialization)
continue
if key.find("TemplateModel") == 0:
# The TemplateModel function has its own test
continue
if this_function._n_dim == 1:
print("testing %s ..." % key)
test_one(_known_functions[key])
def test_auto_unlink():
mg = ModelGetter()
m = mg.model
n_free_before_link = len(m.free_parameters)
# Link as equal (default)
m.link(m.one.spectrum.main.Powerlaw.K, m.two.spectrum.main.Powerlaw.K)
m.link(m.one.spectrum.main.Powerlaw.index, m.two.spectrum.main.Powerlaw.index)
n_free_source2 = len(m.two.free_parameters)
#This should give a warning about automatically unlinking 2 parameters
with pytest.warns(RuntimeWarning):
m.remove_source(m.two.name)
assert len(m.free_parameters) == n_free_before_link - n_free_source2
# Redo the same, but with a powerlaw law
mg = ModelGetter()
m = mg.model
link_law = Powerlaw()
link_law.K.value = 1.0
link_law.index.value = -1.0
m.link(m.one.spectrum.main.Powerlaw.K, m.two.spectrum.main.Powerlaw.K, link_law)
with pytest.warns(RuntimeWarning):
m.remove_source(m.two.name)
assert len(m.free_parameters) == n_free_before_link - n_free_source2
# Redo the same, but with two linked parameters
mg = ModelGetter()
m = mg.model
m.link([m.one.spectrum.main.Powerlaw.K,m.ext_one.spectrum.main.Powerlaw.K],m.two.spectrum.main.Powerlaw.K)
with pytest.warns(RuntimeWarning):
m.remove_source(m.two.name)
assert len(m.free_parameters) == n_free_before_link - n_free_source2
m.unlink([m.one.spectrum.main.Powerlaw.K, m.ext_one.spectrum.main.Powerlaw.K])
def test_call_with_units():
po = Powerlaw()
result = po(1.0)
assert result.ndim == 0
with pytest.raises(AssertionError):
# This raises because the units of the function have not been set up
_ = po(1.0 * u.keV)
# Use the function as a spectrum
ps = PointSource("test", 0, 0, po)
result = po(1.0 * u.keV)
assert isinstance(result, u.Quantity)
result = po(np.array([1, 2, 3]) * u.keV)
assert isinstance(result, u.Quantity)
# Now test all the functions
def test_one(class_type):
instance = class_type()
if not instance.is_prior:
# if we have fixed x_units then we will use those
# in the test
if instance.has_fixed_units():
x_unit_to_use = instance.fixed_units[0]
else:
x_unit_to_use = u.keV
# Use the function as a spectrum
ps = PointSource("test", 0, 0, instance)
if instance.name in ["Synchrotron", "_ComplexTestFunction"]:
particleSource = ParticleSource("particles", Powerlaw())
instance.set_particle_distribution(
particleSource.spectrum.main.shape)
# elif instance.name in ["PhAbs", "TbAbs"]:
# instance
result = ps(1.0)
assert isinstance(result, float)
result = ps(1.0 * x_unit_to_use)
assert isinstance(result, u.Quantity)
result = ps(np.array([1, 2, 3]) * x_unit_to_use)
assert isinstance(result, u.Quantity)
if instance.name in ["Synchrotron", "_ComplexTestFunction"]:
model = Model(particleSource, ps)
else:
model = Model(ps)
new_model = clone_model(model)
new_result = new_model["test"](np.array([1, 2, 3]) * x_unit_to_use)
assert np.all(new_result == result)
model.save("__test.yml", overwrite=True)
new_model = load_model("__test.yml")
new_result = new_model["test"](np.array([1, 2, 3]) * x_unit_to_use)
assert np.all(new_result == result)
else:
print('Skipping prior function')
for key in _known_functions:
this_function = _known_functions[key]
# Test only the power law of XSpec, which is the only one we know we can test at 1 keV
if key.find("XS") == 0 and key != "XS_powerlaw" or (
key in _multiplicative_models):
# An XSpec model. Test it only if it's a power law (the others might need other parameters during
# initialization)
continue
if key.find("TemplateModel") == 0:
# The TemplateModel function has its own test
continue
# if key.find("Synchrotron")==0:
# Naima Synchtron function should have its own test
# continue
if this_function._n_dim == 1:
print("testing %s ..." % key)
test_one(_known_functions[key])