comparison larch_lcf.py @ 1:6c28339b73f7 draft

planemo upload for repository https://github.com/MaterialsGalaxy/larch-tools/tree/main/larch_lcf commit 1cf6d7160497ba58fe16a51f00d088a20934eba6

0:f59731986b61

def plot(
    group_to_fit: Group,
    fit_group: Group,
    energy_min: float,
    energy_max: float,
):
    formatted_label = ""
    for label, weight in fit_group.weights.items():
        formatted_label += f"{label}: {weight:.3%}\n"

        linewidth=2,
        color="orange",
        linestyle="--",
    )
    plt.grid(color="black", linestyle=":", linewidth=1)  # show and format grid
    plt.xlim(energy_min, energy_max)
    plt.xlabel("Energy (eV)")
    plt.ylabel("normalised x$\mu$(E)")  # noqa: W605
    plt.legend()
    plt.savefig("plot.png", format="png")
    plt.close("all")

    for component in input_values["components"]:
        component_group = read_group(component["component_file"])
        set_label(component_group, component["label"])
        component_groups.append(component_group)

    fit_group = lincombo_fit(group_to_fit, component_groups)
    print(f"Goodness of fit (rfactor): {fit_group.rfactor:.6%}")

    energy_min = input_values["energy_min"]
    energy_max = input_values["energy_max"]
    if input_values["energy_format"] == "relative":
        e0 = group_to_fit.e0
        if energy_min is not None:
            energy_min += e0
        if energy_max is not None:
            energy_max += e0

    plot(group_to_fit, fit_group, energy_min, energy_max)

1:6c28339b73f7

def plot(
    group_to_fit: Group,
    fit_group: Group,
    x_limit_min: float,
    x_limit_max: float,
):
    formatted_label = ""
    for label, weight in fit_group.weights.items():
        formatted_label += f"{label}: {weight:.3%}\n"

        linewidth=2,
        color="orange",
        linestyle="--",
    )
    plt.grid(color="black", linestyle=":", linewidth=1)  # show and format grid
    plt.xlim(x_limit_min, x_limit_max)
    plt.xlabel("Energy (eV)")
    plt.ylabel("normalised x$\mu$(E)")  # noqa: W605
    plt.legend()
    plt.savefig("plot.png", format="png")
    plt.close("all")

    for component in input_values["components"]:
        component_group = read_group(component["component_file"])
        set_label(component_group, component["label"])
        component_groups.append(component_group)

    energy_min = input_values["energy_min"]
    energy_max = input_values["energy_max"]
    fit_group = lincombo_fit(
        group=group_to_fit,
        components=component_groups,
        xmin=energy_min,
        xmax=energy_max,
    )
    print(f"Goodness of fit (rfactor): {fit_group.rfactor:.6%}")

    x_limit_min = input_values["x_limit_min"]
    x_limit_max = input_values["x_limit_max"]
    plot(group_to_fit, fit_group, x_limit_min, x_limit_max)