Tutorial for using the effective mass calculator utility

[josue-clavijo]

Hi everyone. First, thanks to Stepan and to Badal for all your kind answers.

I'd like to ask for assistance to get working the effective mass calculator utility. The issue is that when I use the code

### For the dispersion type choice
Parabolic=True
UpwardHyp=False
DownwardHyp=False

m_star, optimized_parameters, convergence_measure = \
    unfolded_band_properties.calculate_effecfive_mass(kpath, band_energy,
                                                      initial_guess_params=None,
                                                      params_bounds = (-np.inf, np.inf),
                                                      fit_weights=None, absolute_weights=False,
                                                      parabolic_dispersion=True,
                                                      hyperbolic_dispersion_positive=False,
                                                      hyperbolic_dispersion_negative=False,
                                                      params_name = ['alpha', 'kshift', 'cbm', 'gamma'])
    #===================================
    band_energy_fit = unfolded_band_properties.fit_functions(kpath, optimized_parameters,
                                                            parabolic_dispersion=True,
                                                            hyperbolic_dispersion_positive=False,
                                                            hyperbolic_dispersion_negative=False)

Where kpath and band_energy arrays (see below) were constructed from both kpoints_unfolded.dat and bandstructure_unfolded.dat files, for the top valence band containing the valence band maximum eigenvalue. In the kpath array, 1.47478091 corresponds to gamma point on BZ (k in A^-1 units), and the 0.09504498 energy It's the valence maxima eigenvalue at this gamma point:

kpath=np.array([1.26888509, 1.30982946, 1.35077383, 1.39171820, 1.43383115, 1.47478091, 1.50244259, 1.53127822, 1.56011386, 1.58894949, 1.61778513])
band_energy=np.array([-0.20705563, -0.20705563, -0.07194677, 0.04673017, 0.13000076, 0.09504498, 0.14570526, 0.10571172, 0.04919766, -0.01404133, -0.07638066])

But when i run the code, i consistently get the following error:

---

ValueError Traceback (most recent call last)
Cell In[36], line 31
28 UpwardHyp=False
29 DownwardHyp=False
---> 31 m_star, optimized_parameters, convergence_measure =
32 unfolded_band_properties.calculate_effecfive_mass(kpath, band_energy,
33 initial_guess_params=None,
34 params_bounds = (-np.inf, np.inf),
35 fit_weights=None, absolute_weights=False,
36 parabolic_dispersion=True,
37 hyperbolic_dispersion_positive=False,
38 hyperbolic_dispersion_negative=False,
39 params_name = ['alpha', 'kshift', 'cbm', 'gamma'])
41 band_energy_fit = unfolded_band_properties.fit_functions(kpath, optimized_parameters,
42 parabolic_dispersion=Parabolic,
43 hyperbolic_dispersion_positive=UpwardHyp,
44 hyperbolic_dispersion_negative=DownwardHyp)

ValueError: too many values to unpack (expected 3)

I don't know what am I missing or what am I doing wrong. Thanks in advance for all your corrections ands suggestions, since I'm not a hard coder, I'm a experimentalist exploring with the Banduppy code.

Best regards,

Josue

[bmondal94]

Hi @josue-clavijo ,
Apologies for the delayed response - I missed your message earlier.

Regarding your question, I realized I forgot to update the README documentation. Thanks for pointing that out. The effective mass calculator is part of an active, ongoing project and is still under continuous development. Recently, I made some updates to this module, which included changes to the calculate_effective_mass() function. Instead of returning 3 values, the latest version now returns 4 values.

Could you please try the following?

# Get effective mass for parabolic dispersion
m_star, popt, pcov, params_error = unfolded_band_properties.calculate_effecfive_mass(kpath_, band_energy_,
                                                                             initial_guess_params=...,
                                                                             ignore_kshift_cbm_fit=False, #
                                                                             fit_weights=inv_bws_, absolute_weights=False,
                                                                             parabolic_dispersion=True)
band_energy_fit = unfolded_band_properties.fit_functions(kpath_, popt, parabolic_dispersion=1)

ignore_kshift_cbm_fit : bool, optional
            Ignore fitting kshift and cbm parameters during fitting. The default is True.

  Returns
        -------
        m_star : (float,float) => (m* +- m*_error)
            Calculated effective mass and error in m_0 unit. 
        popt : array <== optimized_parameters
            Optimal values for the parameters so that the sum of the squared
            residuals of ``f(xdata, *popt) - ydata`` is minimized.
        pcov : 2-D array
            The estimated approximate covariance of popt. 
        params_errors : 1-D array
            One standard deviation error in parameters.
            perr = np.sqrt(np.diag(pcov))

Also, for complete documentation, you can use Python's helper function instead: help(unfolded_band_properties.calculate_effecfive_mass) .
Since the module is constantly evolving, I update the function docstrings, but I sometimes forget to update the README USAGE documentation.

Thanks for your understanding, and feel free to reach out if you have further questions!

Best regards,
Badal

[josue-clavijo]

Badal, thank you for all of your kind assistance. The updated code now works like a charm. I'll test it against some reports on effective masses for hybrid perovskites. Again, thank you very much.