Note
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Log parabola spectral norm model#
This model parametrises a log parabola spectral correction with a norm parameter.
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 (
LogParabolaNormSpectralModel,
Models,
SkyModel,
TemplateSpectralModel,
)
energy_bounds = [0.1, 100] * u.TeV
energy = [0.3, 1, 3, 10, 30] * u.TeV
values = [40, 30, 20, 10, 1] * u.Unit("TeV-1 s-1 cm-2")
template = TemplateSpectralModel(energy, values)
norm = LogParabolaNormSpectralModel(
norm=1.5,
reference=1 * u.TeV,
)
template.plot(energy_bounds=energy_bounds, label="Template model")
lp_norm = template * norm
lp_norm.plot(energy_bounds, label="Template model with LogParabola norm correction")
plt.legend(loc="best")
plt.grid(which="both")
YAML representation#
Here is an example YAML file using the model:
components:
- name: log-parabola-norm-model
type: SkyModel
spectral:
type: CompoundSpectralModel
model1:
type: TemplateSpectralModel
parameters: []
energy:
data:
- 0.3
- 1.0
- 3.0
- 10.0
- 30.0
unit: TeV
values:
data:
- 40.0
- 30.0
- 20.0
- 10.0
- 1.0
unit: 1 / (cm2 s TeV)
model2:
type: LogParabolaNormSpectralModel
parameters:
- name: norm
value: 1.5
- name: reference
value: 1.0
unit: TeV
- name: alpha
value: 0.0
- name: beta
value: 0.0
operator: mul
metadata:
creator: Gammapy 2.0.dev40+g95c0a5676
date: '2024-11-22T14:02:34.871611'
origin: null