Lorentzian fits

import nexus as nx
import numpy as np
import matplotlib.pyplot as plt

load a reference spectrum

intensity = np.loadtxt('Fe_alpha_spectrum_wide.txt')

plt.plot(intensity)
plt.show()

Calibrate experimental data

v = 8.3
shift = 0.0

velocities, offset, scaling, vel_theo, int_theo = nx.data.CalibrateChannelsAlphaFe(
                                                    intensity = intensity,
                                                    velocity= v,
                                                    thickness = 10e3,
                                                    Bhf = 33,
                                                    B_fwhm = 0,
                                                    emission = False,
                                                    mode = "constant",
                                                    shift = shift)

print("offset: {}".format(offset))
print("scaling: {}".format(scaling))
print("max velocity in experiment: {}".format(v*scaling))

offset: 0.29844467432932387
scaling: 0.9640092539880852
max velocity in experiment: 8.001276808101109

Get all Lorentzian parameters

n_lor, indices_lor, velocity_lor, intensities_lor, widths_lor, areas_lor, baseline_lor, fit_curve = nx.data.GetLorentzian(
                                                                                                      velocities,
                                                                                                      intensity,
                                                                                                      n=6,
                                                                                                      neg=True,
                                                                                                      baseline=None
                                                                                                      )

print(n_lor)
print(indices_lor)
print(velocity_lor)
print(intensities_lor)
print(widths_lor)
print(areas_lor)
print(baseline_lor)

plt.plot(velocities, intensity)
plt.plot(velocities, fit_curve)
plt.show()

6
[ 96 166 237 292 363 433]
[-5.32343661 -3.07623348 -0.84988943  0.84587101  3.08106968  5.32568563]
[-980.29961236 -936.81445391 -742.80437577 -741.84551569 -921.26441169
 -976.35410283]
[0.70463913 0.46580674 0.271412   0.25158578 0.45156303 0.66741383]
[2170.0785944  1370.91089519  633.36398958  586.33988414 1306.93065309
 2047.16303298]
6150.561289921998

Get just the linewidth of each peak

widths = nx.data.GetLinewidths(velocities, intensity, n=6, neg=True)

print(widths)

[0.70463913 0.46580674 0.271412   0.25158578 0.45156303 0.66741383]

Get the processed areas of each peak

folded_areas, area_ratio = nx.data.GetAreas(velocities,
                                            intensity,
                                            n=6,
                                            neg=True,
                                            norm = "min")

print(folded_areas)
print(area_ratio)

[4217.24162738 2677.84154828 1219.70387372]
[3.45759468 2.19548499 1.        ]