Quadratic
[3]:
# Parameters
func_name = "Quadratic"
wide_energy_range = True
x_scale = "linear"
y_scale = "linear"
linear_range = True
Description
[5]:
func.display()
- description: A Quadratic function
- formula: $ a + b \cdot x + c \cdot x^2 $
- parameters:
- a:
- value: 1.0
- desc: coefficient
- min_value: None
- max_value: None
- unit:
- is_normalization: False
- delta: 0.1
- free: True
- b:
- value: 1.0
- desc: coefficient
- min_value: None
- max_value: None
- unit:
- is_normalization: False
- delta: 0.1
- free: True
- c:
- value: 1.0
- desc: coefficient
- min_value: None
- max_value: None
- unit:
- is_normalization: False
- delta: 0.1
- free: True
- a:
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)
