name="ecpl_2",
model=ExpCutoffPowerLawSpectralModel(
index=2.0 * u.Unit(""),
amplitude=4 / u.cm**2 / u.s / u.TeV,
reference=1 * u.TeV,
lambda_=0.1 / u.TeV,
),
val_at_2TeV=u.Quantity(0.81873075, "cm-2 s-1 TeV-1"),
integral_1_10TeV=u.Quantity(2.83075297, "cm-2 s-1"),
eflux_1_10TeV=u.Quantity(6.41406327, "TeV cm-2 s-1"),
e_peak=np.nan * u.TeV,
),
dict(
name="GaussianSpectralModel",
model=GaussianSpectralModel(amplitude=4 / u.cm**2 / u.s,
mean=2 * u.TeV,
sigma=0.2 * u.TeV),
val_at_2TeV=u.Quantity(7.978845608028654, "cm-2 s-1 TeV-1"),
val_at_3TeV=u.Quantity(2.973439029468601e-05, "cm-2 s-1 TeV-1"),
integral_1_10TeV=u.Quantity(3.9999988533937123, "cm-2 s-1"),
integral_infinity=u.Quantity(4, "cm-2 s-1"),
eflux_1_10TeV=u.Quantity(7.999998896163037, "TeV cm-2 s-1"),
),
dict(
name="ecpl",
model=ExpCutoffPowerLawSpectralModel(
index=1.8 * u.Unit(""),
amplitude=4 / u.cm**2 / u.s / u.TeV,
reference=1 * u.TeV,
lambda_=0.1 / u.TeV,
alpha=0.8,
name="ecpl_2",
model=ExpCutoffPowerLawSpectralModel(
index=2.0 * u.Unit(""),
amplitude=4 / u.cm ** 2 / u.s / u.TeV,
reference=1 * u.TeV,
lambda_=0.1 / u.TeV,
),
val_at_2TeV=u.Quantity(0.81873075, "cm-2 s-1 TeV-1"),
integral_1_10TeV=u.Quantity(2.83075297, "cm-2 s-1"),
eflux_1_10TeV=u.Quantity(6.41406327, "TeV cm-2 s-1"),
e_peak=np.nan * u.TeV,
),
dict(
name="GaussianSpectralModel",
model=GaussianSpectralModel(
norm=4 / u.cm ** 2 / u.s, mean=2 * u.TeV, sigma=0.2 * u.TeV
),
val_at_2TeV=u.Quantity(7.978845608028654, "cm-2 s-1 TeV-1"),
val_at_3TeV=u.Quantity(2.973439029468601e-05, "cm-2 s-1 TeV-1"),
integral_1_10TeV=u.Quantity(3.9999988533937123, "cm-2 s-1"),
integral_infinity=u.Quantity(4, "cm-2 s-1"),
eflux_1_10TeV=u.Quantity(7.999998896163037, "TeV cm-2 s-1"),
),
dict(
name="ecpl",
model=ExpCutoffPowerLawSpectralModel(
index=1.8 * u.Unit(""),
amplitude=4 / u.cm ** 2 / u.s / u.TeV,
reference=1 * u.TeV,
lambda_=0.1 / u.TeV,
alpha=0.8,
\phi(E) = \frac{N_0}{\sigma \sqrt{2\pi}} \exp{ \frac{- \left( E-\bar{E} \right)^2 }{2 \sigma^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 GaussianSpectralModel, Models, SkyModel
energy_range = [0.1, 100] * u.TeV
model = GaussianSpectralModel(norm="1e-2 cm-2 s-1",
mean=2 * u.TeV,
sigma=0.2 * u.TeV)
model.plot(energy_range)
plt.grid(which="both")
plt.ylim(1e-24, 1e-1)
# %%
# YAML representation
# -------------------
# Here is an example YAML file using the model:
model = SkyModel(spectral_model=model, name="gaussian-model")
models = Models([model])
print(models.to_yaml())
