Source code for asr.c2db.pdos

"""Projected density of states."""
from asr.core import (
    command, option, ASRResult,
    prepare_result, ExternalFile, atomsopt, calcopt)
from import calculate as gscalculate
from import main as gsmain
from collections import defaultdict
import typing

import numpy as np
from ase import Atoms

from asr.utils import magnetic_atoms

def webpanel(result, context):
    from asr.database.browser import fig, describe_entry, WebPanel

    desc = '\n'.join([

    explanation = ('Orbital projected density of states without spin–orbit '
                   'coupling\n\n' + desc)

    # Projected band structure and DOS panel
    panel = WebPanel(
        title=f'Projected band structure and DOS ({context.xcname})',
                 [describe_entry(fig(pdos_figfile, link='empty'),
        plot_descriptions=[{'function': plot_pdos_nosoc,
                            'filenames': [pdos_figfile]}],

    return [panel]

pdos_figfile = 'scf-pdos_nosoc.png'

# ---------- Main functionality ---------- #

# ----- Slow steps ----- #

[docs]@command(module='asr.c2db.pdos') @atomsopt @calcopt @option('-k', '--kptdensity', type=float, help='K-point density') @option('--emptybands', type=int, help='number of empty bands to include') def calculate( atoms: Atoms, calculator: dict = gscalculate.defaults.calculator, kptdensity: float = 20.0, emptybands: int = 20, ) -> ASRResult: from asr.utils.refinegs import refinegs calc, gpw = refinegs( atoms=atoms, calculator=calculator, selfc=False, kptdensity=kptdensity, emptybands=emptybands, gpw='pdos.gpw', txt='pdos.txt', ) return ExternalFile.fromstr('pdos.gpw')
# ----- Fast steps ----- # @prepare_result class PdosResult(ASRResult): efermi: float symbols: typing.List[str] energies: typing.List[float] pdos_syl: typing.List[float] key_descriptions: typing.Dict[str, str] = dict( efermi="Fermi level [eV] of ground state with dense k-mesh.", symbols="Chemical symbols.", energies="Energy mesh of pdos results.", pdos_syl=("Projected density of states [states / eV] for every set of keys " "'s,y,l', that is spin, symbol and orbital l-quantum number.") )
[docs]@prepare_result class Result(ASRResult): dos_at_ef_nosoc: float dos_at_ef_soc: float pdos_nosoc: PdosResult pdos_soc: PdosResult key_descriptions: typing.Dict[str, str] = dict( dos_at_ef_nosoc=("Density of states at the Fermi " "level w/o soc [states / (unit cell * eV)]"), dos_at_ef_soc=("Density of states at the Fermi " "level [states / (unit cell * eV)])"), pdos_nosoc="Projected density of states w/o soc.", pdos_soc="Projected density of states" ) formats = {"webpanel2": webpanel}
[docs]@command(module='asr.c2db.pdos') @atomsopt @calcopt @option('-k', '--kptdensity', type=float, help='K-point density') @option('--emptybands', type=int, help='number of empty bands to include') def main( atoms: Atoms, calculator: dict = gscalculate.defaults.calculator, kptdensity: float = 20.0, emptybands: int = 20, ) -> Result: from gpaw import GPAW from ase.parallel import parprint from asr.c2db.magnetic_anisotropy import main as mag_ani_main # Get refined ground state with more k-points res = calculate( atoms=atoms, calculator=calculator, kptdensity=kptdensity, emptybands=emptybands, ) calc = GPAW(res) dos1 = calc.dos(shift_fermi_level=False) mag_ani = mag_ani_main(atoms=atoms, calculator=calculator) theta, phi = mag_ani.spin_angles() dos2 = calc.dos(soc=True, theta=theta, phi=phi, shift_fermi_level=False) results = {} # Calculate the dos at the Fermi energy parprint('\nComputing dos at Ef', flush=True) results['dos_at_ef_nosoc'] = dos1.raw_dos([dos1.fermi_level], width=0.0)[0] parprint('\nComputing dos at Ef with spin-orbit coupling', flush=True) results['dos_at_ef_soc'] = dos2.raw_dos([dos2.fermi_level], width=0.0)[0] # Calculate pdos parprint('\nComputing pdos', flush=True) results['pdos_nosoc'] = pdos(atoms, calculator, dos1, calc) parprint('\nComputing pdos with spin-orbit coupling', flush=True) results['pdos_soc'] = pdos(atoms, calculator, dos2, calc) return Result(results)
# ---------- Recipe methodology ---------- # # ----- PDOS ----- # def pdos(atoms, calculator, dos, calc): """Do a single pdos calculation. Main functionality to do a single pdos calculation. """ from asr.core import singleprec_dict # Do calculation e_e, pdos_syl, symbols, ef = calculate_pdos(atoms, calculator, dos, calc) return PdosResult.fromdata( efermi=ef, symbols=symbols, energies=e_e, pdos_syl=singleprec_dict(pdos_syl)) def calculate_pdos(atoms, calculator, dos, calc): """Calculate the projected density of states. Returns ------- energies : nd.array energies 10 eV under and above Fermi energy pdos_syl : defaultdict pdos for spin, symbol and orbital angular momentum symbols : list chemical symbols in Atoms object efermi : float Fermi energy """ import gpaw.mpi as mpi from gpaw.utilities.progressbar import ProgressBar from ase.utils import DevNull zs = calc.atoms.get_atomic_numbers() atoms = calc.atoms efermi = calc.get_fermi_level() l_a = get_l_a(zs) ns = calc.get_number_of_spins() gaps = gsmain(atoms=atoms, calculator=calculator).gaps_nosoc e1 = gaps.get('vbm') or gaps.get('efermi') e2 = gaps.get('cbm') or gaps.get('efermi') e_e = np.linspace(e1 - 3, e2 + 3, 500) # We distinguish in (spin(s), chemical symbol(y), angular momentum (l)), # that is if there are multiple atoms in the unit cell of the same chemical # species, their pdos are added together. pdos_syl = defaultdict(float) s_i = [s for s in range(ns) for a in l_a for l in l_a[a]] a_i = [a for s in range(ns) for a in l_a for l in l_a[a]] l_i = [l for s in range(ns) for a in l_a for l in l_a[a]] sal_i = [(s, a, l) for (s, a, l) in zip(s_i, a_i, l_i)] # Set up progressbar if == 0: pb = ProgressBar() else: devnull = DevNull() pb = ProgressBar(devnull) for _, (spin, a, l) in pb.enumerate(sal_i): symbol = atoms.symbols[a] p = dos.raw_pdos(e_e, a, 'spdfg'.index(l), None, spin, 0.0) # Store in dictionary key = ','.join([str(spin), str(symbol), str(l)]) pdos_syl[key] += p return e_e, pdos_syl, list(atoms.symbols), efermi def get_l_a(zs): """Define which atoms and angular momentum to project onto. Parameters ---------- zs : [z1, z2, ...]-list or array list of atomic numbers (zi: int) Returns ------- l_a : {int: str, ...}-dict keys are atomic indices and values are a string such as 'spd' that determines which angular momentum to project onto or a given atom """ lantha = range(58, 72) acti = range(90, 104) zs = np.asarray(zs) l_a = {} atoms = Atoms(numbers=zs) mag_elements = magnetic_atoms(atoms) for a, (z, mag) in enumerate(zip(zs, mag_elements)): if z in lantha or z in acti: l_a[a] = 'spdf' else: l_a[a] = 'spd' if mag else 'sp' return l_a # ---------- Plotting ---------- # def get_ordered_syl_dict(dct_syl, symbols): """Order a dictionary with syl keys. Parameters ---------- dct_syl : dict Dictionary with keys f'{s},{y},{l}' (spin (s), chemical symbol (y), angular momentum (l)) symbols : list Sort symbols after index in this list Returns ------- outdct_syl : OrderedDict Sorted dct_syl """ from collections import OrderedDict # Setup ssili (spin, symbol index, angular momentum index) key def ssili(syl): s, y, L = syl.split(',') # Symbols list can have multiple entries of the same symbol # ex. ['O', 'Fe', 'O']. In this case 'O' will have index 0 and # 'Fe' will have index 1. si = symbols.index(y) li = ['s', 'p', 'd', 'f'].index(L) return f'{s}{si}{li}' return OrderedDict(sorted(dct_syl.items(), key=lambda t: ssili(t[0]))) def get_yl_colors(dct_syl): """Get the color indices corresponding to each symbol and angular momentum. Parameters ---------- dct_syl : OrderedDict Ordered dictionary with keys f'{s},{y},{l}' (spin (s), chemical symbol (y), angular momentum (l)) Returns ------- color_yl : OrderedDict Color strings for each symbol and angular momentum """ from collections import OrderedDict color_yl = OrderedDict() c = 0 for key in dct_syl: # Do not differentiate spin by color if int(key[0]) == 0: # if spin is 0 color_yl[key[2:]] = 'C{}'.format(c) c += 1 c = c % 10 # only 10 colors available in cycler return color_yl def plot_pdos_nosoc(context, *args, **kwargs): return plot_pdos(context, *args, soc=False, **kwargs) def plot_pdos_soc(context, *args, **kwargs): return plot_pdos(context, *args, soc=True, **kwargs) def plot_pdos(context, filename, soc=True, figsize=(5.5, 5), lw=1): def smooth(y, npts=3): return np.convolve(y, np.ones(npts) / npts, mode='same') pdos_name = 'pdos_soc' if soc else 'pdos_nosoc' result = context.result pdos = result[pdos_name] import matplotlib.pyplot as plt from matplotlib import rcParams import matplotlib.patheffects as path_effects ref = context.energy_reference() eref = ref.value # Extract raw data pdos_syl = get_ordered_syl_dict(pdos['pdos_syl'], context.atoms.symbols) e_e = pdos['energies'] - eref ef = pdos['efermi'] gs_results = context.gs_results() # Find energy range to plot in if soc: emin = gs_results.get('vbm', ef) - 3 - eref emax = gs_results.get('cbm', ef) + 3 - eref else: nosoc_data = gs_results['gaps_nosoc'] vbmnosoc = nosoc_data.get('vbm', ef) cbmnosoc = nosoc_data.get('cbm', ef) if vbmnosoc is None: vbmnosoc = ef if cbmnosoc is None: cbmnosoc = ef emin = vbmnosoc - 3 - eref emax = cbmnosoc + 3 - eref # Set up energy range to plot in i1, i2 = abs(e_e - emin).argmin(), abs(e_e - emax).argmin() # Get color code color_yl = get_yl_colors(pdos_syl) # Figure out if pdos has been calculated for more than one spin channel spinpol = False for k in pdos_syl: if int(k[0]) == 1: spinpol = True break # Set up plot plt.figure(figsize=figsize) ax = plt.gca() # Plot pdos pdosint_s = defaultdict(float) for key in pdos_syl: pdos = pdos_syl[key] spin, symbol, lstr = key.split(',') spin = int(spin) sign = 1 if spin == 0 else -1 # Integrate pdos to find suiting pdos range pdosint_s[spin] += np.trapz(y=pdos[i1:i2], x=e_e[i1:i2]) # Label atomic symbol and angular momentum if spin == 0: label = '{} ({})'.format(symbol, lstr) else: label = None ax.plot(smooth(pdos) * sign, e_e, label=label, color=color_yl[key[2:]]) ax.axhline(ef - eref, color='k', ls=':') # Set up axis limits ax.set_ylim(emin, emax) if spinpol: # Use symmetric limits xmax = max(pdosint_s.values()) ax.set_xlim(-xmax * 0.5, xmax * 0.5) else: ax.set_xlim(0, pdosint_s[0] * 0.5) # Annotate E_F xlim = ax.get_xlim() x0 = xlim[0] + (xlim[1] - xlim[0]) * 0.99 text = plt.text(x0, ef - eref, r'$E_\mathrm{F}$', fontsize=rcParams['font.size'] * 1.25, ha='right', va='bottom') text.set_path_effects([ path_effects.Stroke(linewidth=3, foreground='white', alpha=0.5), path_effects.Normal() ]) ax.set_xlabel('Projected DOS [states / eV]') ax.set_ylabel(ref.mpl_plotlabel()) # Set up legend plt.legend(bbox_to_anchor=(0., 1.02, 1., 0.), loc='lower left', ncol=3, mode="expand", borderaxespad=0.) plt.savefig(filename, bbox_inches='tight') plt.close() if __name__ == '__main__': main.cli()