def test_piecewise_norm_spectral_model_init():
with pytest.raises(ValueError):
PiecewiseNormSpectralModel(energy=[
1,
] * u.TeV, norms=[1, 5])
with pytest.raises(ValueError):
PiecewiseNormSpectralModel(energy=[
1,
] * u.TeV, norms=[
1,
])
def test_piecewise_norm_spectral_model_io():
energy = [1, 3, 7, 10] * u.TeV
norms = [1, 5, 3, 0.5] * u.Unit("")
model = PiecewiseNormSpectralModel(energy=energy, norms=norms)
model.parameters[0].value = 2
model_dict = model.to_dict()
parnames = [_["name"] for _ in model_dict["parameters"]]
for k, parname in enumerate(parnames):
assert parname == f"norm_{k}"
new_model = PiecewiseNormSpectralModel.from_dict(model_dict)
assert_allclose(new_model.parameters[0].value, 2)
assert_allclose(new_model.energy, energy)
assert_allclose(new_model.norms, [2, 5, 3, 0.5])
# Example plot
# ------------
# Here is an example plot of the model:
from astropy import units as u
import matplotlib.pyplot as plt
from gammapy.modeling.models import (
Models,
PiecewiseNormSpectralModel,
PowerLawSpectralModel,
SkyModel,
)
energy_range = [0.1, 100] * u.TeV
model = PiecewiseNormSpectralModel(
energy=[0.1, 1, 3, 10, 30, 100] * u.TeV,
norms=[1, 3, 8, 10, 8, 2],
)
model.plot(energy_range, flux_unit="")
plt.grid(which="both")
# %%
# YAML representation
# -------------------
# Here is an example YAML file using the model:
model = model * PowerLawSpectralModel()
model = SkyModel(spectral_model=model, name="piecewise-norm-model")
models = Models([model])
print(models.to_yaml())
model=SmoothBrokenPowerLawSpectralModel(
index1=2.5 * u.Unit(""),
index2=1.5 * u.Unit(""),
amplitude=4 / u.cm ** 2 / u.s / u.TeV,
ebreak=0.5 * u.TeV,
reference=1 * u.TeV,
beta=1,
),
val_at_2TeV=u.Quantity(3.5355339059327378, "cm-2 s-1 TeV-1"),
integral_1_10TeV=u.Quantity(13.522782989735022, "cm-2 s-1"),
eflux_1_10TeV=u.Quantity(40.06681812966845, "TeV cm-2 s-1"),
),
dict(
name="pbpl",
model=PiecewiseNormSpectralModel(
energy=[1, 3, 7, 10] * u.TeV,
norms=[1, 5, 3, 0.5] * u.Unit(""),
),
val_at_2TeV=u.Quantity(2.76058404, ""),
integral_1_10TeV=u.Quantity(24.758255, "TeV"),
eflux_1_10TeV=u.Quantity(117.745068, "TeV2"),
),
]
# Add compound models
TEST_MODELS.append(
dict(
name="compound3",
model=TEST_MODELS[0]["model"] + TEST_MODELS[0]["model"],
val_at_2TeV=TEST_MODELS[0]["val_at_2TeV"] * 2,
integral_1_10TeV=TEST_MODELS[0]["integral_1_10TeV"] * 2,
# Example plot
# ------------
# Here is an example plot of the model:
from astropy import units as u
import matplotlib.pyplot as plt
from gammapy.modeling.models import (
Models,
PiecewiseNormSpectralModel,
PowerLawSpectralModel,
SkyModel,
)
energy_bounds = [0.1, 100] * u.TeV
model = PiecewiseNormSpectralModel(
energy=[0.1, 1, 3, 10, 30, 100] * u.TeV,
norms=[1, 3, 8, 10, 8, 2],
)
model.plot(energy_bounds, yunits=u.Unit(""))
plt.grid(which="both")
# %%
# YAML representation
# -------------------
# Here is an example YAML file using the model:
model = model * PowerLawSpectralModel()
model = SkyModel(spectral_model=model, name="piecewise-norm-model")
models = Models([model])
print(models.to_yaml())