Source code for effmass.outputs

#! /usr/bin/env python3

"""
A module for plotting and summarising segments information, 
density-of-states information and effective mass analysis.

"""
import matplotlib

import matplotlib.pyplot as plt
import numpy as np
from adjustText import adjust_text

from effmass import ev_to_hartree
from effmass.dos import _check_integrated_dos_loaded
from effmass.dos import _check_dos_loaded
from effmass.analysis import _check_poly_order


[docs]def plot_segments(Data, Settings, segments): """Plots bandstructure overlaid with the DFT-calculated points for each Segment instance. Each Segment is labelled with it's direction in reciprocal space and index number from the segments argument. Args: Data (Data): instance of the :class:`Data` class. Settings (Settings): instance of the :class:`Settings` class. segments (list(Segment)): A list of instances of the :class:`Segment` class. Returns: Figure, Axes: tuple containing instance of the `matplotlib.pyplot.figure <https://matplotlib.org/api/figure_api.html>`_ class and `matplotlib.pyplot.axes <https://matplotlib.org/api/axes_api.html>`_ class. Notes: The x-axis of the plot is not to scale. """ fig = plt.figure(figsize=(8, 8)) ax = fig.add_subplot(111) [ax.plot(range(len(Data.energies[i])), Data.energies[i] - Data.VBM) for i in range(len(Data.energies))] points = [ax.scatter(segments[i].kpoint_indices, segments[i].energies - Data.VBM) for i in range(len(segments))] texts = [ax.text(segments[i].kpoint_indices[-1], segments[i].energies[-1] - Data.VBM, str(i)+", "+str(np.round(segments[i].direction,3))) for i in range(len(segments))] adjust_text(texts, arrowprops=dict(arrowstyle='->', color='red'), autoalign='x', force_text=(0.01,0.025)) ax.set_ylim([ -(Settings.extrema_search_depth + Settings.energy_range + 1), (Data.CBM - Data.VBM) + (Settings.extrema_search_depth + Settings.energy_range + 1) ]) return fig, ax
[docs]def plot_integrated_dos(DataVasp): """Plots integrated density of states (states/unit-cell) against energy (eV). Args: DataVasp (DataVasp): instance of the :class:`DataVasp` class. Returns: Figure, Axes: tuple containing instance of the `matplotlib.pyplot.figure <https://matplotlib.org/api/figure_api.html>`_ class and `matplotlib.pyplot.axes <https://matplotlib.org/api/axes_api.html>`_ class. Notes: The valence band maximum is set to 0 eV. """ _check_integrated_dos_loaded(DataVasp) fig = plt.figure(figsize=(8, 8)) ax = fig.add_subplot(111) energy = [x[0] - DataVasp.VBM for x in DataVasp.integrated_dos] dos_data = [x[1] for x in DataVasp.integrated_dos] ax.plot(energy, dos_data) ax.set_xlabel("Energy, eV") ax.set_ylabel("Integrated DOS, states / unit cell") ax.axvline(0, linestyle="--") ax.axvline(DataVasp.CBM - DataVasp.VBM, linestyle="--") return fig, ax
[docs]def plot_dos(DataVasp): """Plots density of states (states/unit-cell) against energy (eV). Args: DataVasp (DataVasp): instance of the :class:`DataVasp` class. Returns: Figure, Axes: tuple containing instance of the `matplotlib.pyplot.figure <https://matplotlib.org/api/figure_api.html>`_ class and `matplotlib.pyplot.axes <https://matplotlib.org/api/axes_api.html>`_ class. Notes: The valence band maximum is set to 0 eV. """ _check_dos_loaded(DataVasp) fig = plt.figure(figsize=(8, 8)) ax = fig.add_subplot(111) energy = [x[0] - DataVasp.VBM for x in DataVasp.dos] dos = [x[1] for x in DataVasp.dos] ax.plot(energy, dos) ax.set_xlabel("Energy, eV") ax.set_ylabel("DOS") ax.axvline(0, linestyle="--") ax.axvline(DataVasp.CBM - DataVasp.VBM, linestyle="--") return fig, ax
def print_results(segment, data, settings, polyfit_order=None): polyfit_order = settings.degree_bandfit if polyfit_order is None else polyfit_order _check_poly_order(polyfit_order) print(segment.band_type, segment.direction) print("3-point finite difference mass is {:.2f}".format( segment.finite_difference_effmass())) print("5-point parabolic mass is {:.2f}".format( segment.five_point_leastsq_effmass())) try: print("weighted parabolic mass is {:.2f}".format( segment.weighted_leastsq_effmass())) except AssertionError as e: print ("----------\n") print (e) print ("\n-----------") try: print("alpha is {:.2f} 1/eV".format( segment.alpha(polyfit_order=polyfit_order) * ev_to_hartree)) print("kane mass at bandedge is {:.2f}".format( segment.kane_mass_band_edge(polyfit_order=polyfit_order))) if segment.explosion_index(polyfit_order=polyfit_order) == len( segment.dE_eV): print( "the Kane quasi linear approximation is valid for the whole segment" ) else: print("the Kane quasi-linear approximation is valid until {:.2f} eV". format(segment.dE_eV[segment.explosion_index( polyfit_order=polyfit_order)])) except AssertionError as e: print ("----------\n") print (e) print ("\n-----------") try: print("optical mass at band edge (assuming the Kane dispersion) is {:.2f}". format(segment.optical_effmass_kane_dispersion())) except AssertionError: pass plt.figure(figsize=(8, 8)) plt.plot( np.linspace(segment.dk_angs[0], segment.dk_angs[-1], 100), np.divide( segment.poly_fit( polyfit_order=polyfit_order, polyfit_weighting=False), ev_to_hartree), marker="x", ms=5, label="polynomial order {}".format(polyfit_order)) plt.plot( np.linspace(segment.dk_angs[0], segment.dk_angs[-1], 100), np.divide(segment.finite_difference_fit(), ev_to_hartree), marker="<", ms=5, label="finite diff parabolic") plt.plot( np.linspace(segment.dk_angs[0], segment.dk_angs[-1], 100), np.divide(segment.five_point_leastsq_fit(), ev_to_hartree), marker="p", ms=5, label="five point parabolic") try: plt.plot( np.linspace(segment.dk_angs[0], segment.dk_angs[-1], 100), np.divide(segment.weighted_leastsq_fit(), ev_to_hartree), marker=">", ms=5, label="weighted parabolic") except AssertionError: pass try: plt.plot( np.linspace(segment.dk_angs[0], segment.dk_angs[-1], 100), np.divide( segment.kane_fit(polyfit_order=polyfit_order), ev_to_hartree), marker="o", ms=5, label="Kane quasi-linear") except AssertionError as e: pass plt.xlabel(r"k ($ \AA^{-1} $)") plt.ylabel("energy (eV)") plt.scatter(segment.dk_angs, segment.dE_eV, marker="x", s=200, label="DFT") plt.legend() plt.show() fig, axes = plot_segments(data, settings, [segment]) plt.show() plt.figure(figsize=(8, 8)) idx = segment.explosion_index(polyfit_order=polyfit_order) plt.scatter( segment.dE_hartree[1:idx + 1], segment.transport_effmass( polyfit_order=polyfit_order, dk=segment.dk_bohr, polyfit_weighting=False)[1:idx + 1]) plt.plot([0, segment.dE_hartree[idx]], np.polyval( np.polyfit( segment.dE_hartree[1:idx + 1], segment.transport_effmass( polyfit_order=polyfit_order, dk=segment.dk_bohr, polyfit_weighting=False)[1:idx + 1], 1), [0, segment.dE_hartree[idx]])) plt.ylabel("transport mass") plt.xlabel("energy (hartree)") plt.xlim([0, segment.dE_hartree[idx]]) plt.show()