Build synthetic concentration profiles

This example shows two convenient ways to build simple synthetic profiles directly with the SpectroChemPy API:

• explicit analytical expressions with top-level math aliases such as scp.exp(...);

• direct line-shape helpers such as scp.gaussian(...) when a built-in model already matches the target profile.

import spectrochempy as scp

Build profiles with analytical expressions

time = scp.linspace(0.0, 1.0, 200)

c1 = scp.exp(-0.5 * ((time - 0.25) / 0.10) ** 2)
c2 = 0.8 * scp.exp(-0.5 * ((time - 0.55) / 0.12) ** 2)
c3 = 0.6 * scp.exp(-0.5 * ((time - 0.82) / 0.08) ** 2)

Assemble as columns of a concentration matrix:

profiles = scp.stack([c1, c2, c3], axis=1)
profiles.x.title = "time"
profiles.y = scp.Coord(labels=["c1", "c2", "c3"], title="species")
profiles.name = "concentrations"
profiles.title = "relative concentration"

ax = profiles.T.plot()
ax.legend()

<matplotlib.legend.Legend object at 0x7fac70321090>

Use built-in Gaussian line-shape helper

profiles_gaussian = scp.stack(
    [
        scp.gaussian(time, ampl=1.0, pos=0.25, width=0.235, normalized=False),
        scp.gaussian(time, ampl=0.8, pos=0.55, width=0.282, normalized=False),
        scp.gaussian(time, ampl=0.6, pos=0.82, width=0.188, normalized=False),
    ],
    axis=1,
)
profiles_gaussian.x.title = "time"
profiles_gaussian.y = scp.Coord(labels=["A", "B", "C"], title="species")
profiles_gaussian.name = "concentrations_gaussian"
profiles_gaussian.title = "relative concentration"

ax = profiles_gaussian.T.plot()
ax.legend()

<matplotlib.legend.Legend object at 0x7fac703d1f90>