SmoothlyBrokenPowerLaw
[3]:
# Parameters
func_name = "SmoothlyBrokenPowerLaw"
wide_energy_range = True
x_scale = "log"
y_scale = "log"
linear_range = False
Description
[5]:
func.display()
- description: A Smoothly Broken Power Law
- formula: $n.a.$
- parameters:
- K:
- value: 1.0
- desc: normalization
- min_value: 1e-50
- max_value: None
- unit:
- is_normalization: True
- delta: 0.1
- free: True
- alpha:
- value: -1.0
- desc: power law index below the break
- min_value: -1.5
- max_value: 2.0
- unit:
- is_normalization: False
- delta: 0.1
- free: True
- break_energy:
- value: 300.0000000000001
- desc: location of the peak
- min_value: 10.0
- max_value: None
- unit:
- is_normalization: False
- delta: 30.000000000000014
- free: True
- break_scale:
- value: 0.5
- desc: smoothness of the break
- min_value: 0.0
- max_value: 10.0
- unit:
- is_normalization: False
- delta: 0.05
- free: False
- beta:
- value: -2.0
- desc: power law index above the break
- min_value: -5.0
- max_value: -1.6
- unit:
- is_normalization: False
- delta: 0.2
- free: True
- pivot:
- value: 100.0
- desc: where the spectrum is normalized
- min_value: None
- max_value: None
- unit:
- is_normalization: False
- delta: 10.0
- free: False
- K:
Shape
The shape of the function.
If this is not a photon model but a prior or linear function then ignore the units as these docs are auto-generated
[6]:
fig, ax = plt.subplots()
ax.plot(energy_grid, func(energy_grid), color=blue)
ax.set_xlabel("energy (keV)")
ax.set_ylabel("photon flux")
ax.set_xscale(x_scale)
ax.set_yscale(y_scale)
F\(_{\nu}\)
The F\(_{\nu}\) shape of the photon model if this is not a photon model, please ignore this auto-generated plot
[7]:
fig, ax = plt.subplots()
ax.plot(energy_grid, energy_grid * func(energy_grid), red)
ax.set_xlabel("energy (keV)")
ax.set_ylabel(r"energy flux (F$_{\nu}$)")
ax.set_xscale(x_scale)
ax.set_yscale(y_scale)
\(\nu\)F\(_{\nu}\)
The \(\nu\)F\(_{\nu}\) shape of the photon model if this is not a photon model, please ignore this auto-generated plot
[8]:
fig, ax = plt.subplots()
ax.plot(energy_grid, energy_grid**2 * func(energy_grid), color=green)
ax.set_xlabel("energy (keV)")
ax.set_ylabel(r"$\nu$F$_{\nu}$")
ax.set_xscale(x_scale)
ax.set_yscale(y_scale)
