Compound spectral model

This model is formed by the arithmetic combination of any two other spectral models.

Example plot

Here is an example plot of the model:

import operator
from astropy import units as u
import matplotlib.pyplot as plt
from gammapy.modeling.models import (
    CompoundSpectralModel,
    LogParabolaSpectralModel,
    Models,
    PowerLawSpectralModel,
    SkyModel,
)

energy_bounds = [0.1, 100] * u.TeV
pwl = PowerLawSpectralModel(
    index=2.0, amplitude="1e-12 cm-2 s-1 TeV-1", reference="1 TeV"
)
lp = LogParabolaSpectralModel(
    amplitude="1e-12 cm-2 s-1 TeV-1", reference="10 TeV", alpha=2.0, beta=1.0
)

# freeze the amplitude to avoid degeneracy when fitting
lp.amplitude.frozen = True
model = CompoundSpectralModel(pwl, lp, operator.add)
model.plot(energy_bounds)
plt.grid(which="both")

YAML representation

Here is an example YAML file using the model:

model = SkyModel(spectral_model=model, name="compound-model")
models = Models([model])

print(models.to_yaml())

Out:

components:
-   name: compound-model
    type: SkyModel
    spectral:
        type: CompoundSpectralModel
        model1:
            type: PowerLawSpectralModel
            parameters:
            -   name: index
                value: 2.0
                is_norm: false
            -   name: amplitude
                value: 1.0e-12
                unit: cm-2 s-1 TeV-1
                is_norm: true
            -   name: reference
                value: 1.0
                unit: TeV
                frozen: true
                is_norm: false
        model2:
            type: LogParabolaSpectralModel
            parameters:
            -   name: amplitude
                value: 1.0e-12
                unit: cm-2 s-1 TeV-1
                frozen: true
                is_norm: true
            -   name: reference
                value: 10.0
                unit: TeV
                frozen: true
                is_norm: false
            -   name: alpha
                value: 2.0
                is_norm: false
            -   name: beta
                value: 1.0
                is_norm: false
        operator: add