Log parabola

[3]:

# Parameters
func_name = "Log_parabola"
wide_energy_range = True
x_scale = "log"
y_scale = "log"
linear_range = False

Description

[5]:

func.display()
  • description: A log-parabolic function. NOTE that we use the high-energy convention of using the natural log in place of the base-10 logarithm. This means that beta is a factor 1 / log10(e) larger than what returned by those software using the other convention.
  • formula: $ K \left( \frac{x}{piv} \right)^{\alpha -\beta \log{\left( \frac{x}{piv} \right)}} $
  • parameters:
    • K:
      • value: 1.0
      • desc: Normalization
      • min_value: 1e-30
      • max_value: 100000.0
      • unit:
      • is_normalization: True
      • delta: 0.1
      • free: True
    • piv:
      • value: 1.0
      • desc: Pivot (keep this fixed)
      • min_value: None
      • max_value: None
      • unit:
      • is_normalization: False
      • delta: 0.1
      • free: False
    • alpha:
      • value: -2.0
      • desc: index
      • min_value: None
      • max_value: None
      • unit:
      • is_normalization: False
      • delta: 0.2
      • free: True
    • beta:
      • value: 1.0
      • desc: curvature (positive is concave, negative is convex)
      • min_value: None
      • max_value: None
      • unit:
      • is_normalization: False
      • delta: 0.1
      • free: True

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)
../_images/notebooks_Log_parabola_8_0.png

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)

../_images/notebooks_Log_parabola_10_0.png

\(\nu\)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)
../_images/notebooks_Log_parabola_12_0.png