Source code for vasppy.optics

"""
functions for working with optical properties from vasprun.xml
"""

from math import pi
import numpy as np
from scipy.constants import physical_constants, speed_of_light  # type: ignore
import matplotlib.pyplot as plt  # type: ignore

eV_to_recip_cm = 1.0 / (
    physical_constants["Planck constant in eV s"][0] * speed_of_light * 1e2
)


[docs]def matrix_eigvals(matrix): """Calculate the eigenvalues of a matrix. Args: matrix (np.array): The matrix to diagonalise. Returns: (np.array): Array of the matrix eigenvalues. """ eigvals, eigvecs = np.linalg.eig(matrix) return eigvals
[docs]def to_matrix(xx, yy, zz, xy, yz, xz): """Convert a list of matrix components to a symmetric 3x3 matrix. Inputs should be in the order xx, yy, zz, xy, yz, xz. Args: xx (float): xx component of the matrix. yy (float): yy component of the matrix. zz (float): zz component of the matrix. xy (float): xy component of the matrix. yz (float): yz component of the matrix. xz (float): xz component of the matrix. Returns: (np.array): The matrix, as a 3x3 numpy array. """ matrix = np.array([[xx, xy, xz], [xy, yy, yz], [xz, yz, zz]]) return matrix
[docs]def plot_dielectric_functions(dielectric, ax=None): real_dielectric = parse_dielectric_data(dielectric[1]) imag_dielectric = parse_dielectric_data(dielectric[2]) if ax is None: fig, ax = plt.subplots(1, 1, figsize=(6.0, 3.0)) else: fig = None ax.plot( dielectric[0], np.mean(real_dielectric, axis=1), "-", zorder=2 ) # better to pass in v.dielectric ax.plot(dielectric[0], np.mean(imag_dielectric, axis=1), "-", zorder=2) ax.set_xlim([0, 8]) ax.set_ylim([0, 5]) return fig
[docs]def parse_dielectric_data(data): """Convert a set of 2D vasprun formatted dielectric data to the eigenvalues of each corresponding 3x3 symmetric numpy matrices. Args: data (list): length N list of dielectric data. Each entry should be a list of ``[xx, yy, zz, xy, xz, yz ]`` dielectric tensor elements. Returns: (np.array): a Nx3 numpy array. Each row contains the eigenvalues for the corresponding row in `data`. """ return np.array([matrix_eigvals(to_matrix(*e)) for e in data])
[docs]def absorption_coefficient(dielectric): """Calculate the optical absorption coefficient from an input set of pymatgen vasprun dielectric constant data. Args: dielectric (list): A list containing the dielectric response function in the pymatgen vasprun format. | element 0: list of energies | element 1: real dielectric tensors, in ``[xx, yy, zz, xy, xz, yz]`` format. | element 2: imaginary dielectric tensors, in ``[xx, yy, zz, xy, xz, yz]`` format. Returns: (np.array): absorption coefficient using eV as frequency units (cm^-1). Notes: The absorption coefficient is calculated as .. math:: \\alpha = \\frac{2\\sqrt{2} \\pi}{\\lambda} \\sqrt{-\\epsilon_1+\\sqrt{\\epsilon_1^2+\\epsilon_2^2}} """ energies_in_eV = np.array(dielectric[0]) real_dielectric = parse_dielectric_data(dielectric[1]) imag_dielectric = parse_dielectric_data(dielectric[2]) epsilon_1 = np.mean(real_dielectric, axis=1) epsilon_2 = np.mean(imag_dielectric, axis=1) return ( 2.0 * np.sqrt(2.0) * pi * eV_to_recip_cm * energies_in_eV * np.sqrt(-epsilon_1 + np.sqrt(epsilon_1**2 + epsilon_2**2)) )