<reponame>cajfisher/vasppy
#! /usr/bin/env python3

from vasppy import procar
from vasppy.outcar import reciprocal_lattice_from_outcar
import argparse

#def x_axis( cartesian_k_points ):
#    if cartesian_k_points is not None:
#        x_axis = [ 0.0 ]
#        for i in range( 1, len(cartesian_k_points) ):
#            d = cartesian_k_points[i - 1] - cartesian_k_points[i]
#            d = np.sqrt( np.dot( d, d) )
#            x_axis.append( d + x_axis[-1] )
#        x_axis = np.array( x_axis )
#    else:
#        x_axis = np.arange( len( cartesian_k_points ) ) 
#    return x_axis

def orbitals_with_l( l ):
    to_return = { 's' : [ 0 ],
                  'p' : [ 1, 2, 3 ],
                  'd' : [ 4, 5, 6, 7, 8 ],
                  'f' : [ 9, 10, 11, 12, 13 ],
                  'all' : None }
    return to_return[ l ]
 
def main():
    parser = argparse.ArgumentParser()
    parser.add_argument( '-i', '--ions', help='ion indices for band projection (default: sum over all ions)', nargs='+', type=int )
    parser.add_argument( '-s', '--spins', help='spin indices for band projection (default [ 1 ])', nargs='+', type=int, default=[ 1 ] )
    parser.add_argument( '-o', '--orbitals', help='orbital indices for band projection (default: sum over all orbitals)', nargs='+', type=int )
    parser.add_argument( '-e', '--efermi', help='set fermi energy as reference for energy scale', type=float, default=0.0 )
    parser.add_argument( '-l', '--l-angular-momentum', help='select all orbitals with angular momentum L for band projection. This supercedes the --orbitals option', choices=[ 's', 'p', 'd', 'f', 'all' ] )
    parser.add_argument( '-f', '--procar', help='PROCAR filename (default PROCAR)', type=str, default='PROCAR' )
    parser.add_argument( '--scaling', help='Energy scaling for band widths (default 0.2 eV)', type=float, default=0.2 )
    parser.add_argument( '-x', '--xscaling', help='Automatic scaling of x-axis using reciprocal lattice vectors read from OUTCAR', action='store_true', default=False )
    args = parser.parse_args()

    if args.l_angular_momentum:
        args.orbitals = orbitals_with_l( args.l_angular_momentum )

    if args.xscaling:
        reciprocal_lattice = reciprocal_lattice_from_outcar( 'OUTCAR' ) # Move reading the reciprocal lattice to procar.py
    else:
        reciprocal_lattice = None

    pcar = procar.Procar()
    pcar.read_from_file( args.procar )
    pcar.print_weighted_band_structure( spins = args.spins, 
                                        ions = args.ions, 
                                        orbitals = args.orbitals, 
                                        scaling = args.scaling, 
                                        e_fermi = args.efermi, 
                                        reciprocal_lattice = reciprocal_lattice )

if __name__ == '__main__':
    main()

#! /usr/bin/env python3

from vasppy import procar
from vasppy.outcar import reciprocal_lattice_from_outcar
import argparse

#def x_axis( cartesian_k_points ):
#    if cartesian_k_points is not None:
#        x_axis = [ 0.0 ]
#        for i in range( 1, len(cartesian_k_points) ):
#            d = cartesian_k_points[i - 1] - cartesian_k_points[i]
#            d = np.sqrt( np.dot( d, d) )
#            x_axis.append( d + x_axis[-1] )
#        x_axis = np.array( x_axis )
#    else:
#        x_axis = np.arange( len( cartesian_k_points ) ) 
#    return x_axis

def orbitals_with_l( l ):
    to_return = { 's' : [ 0 ],
                  'p' : [ 1, 2, 3 ],
                  'd' : [ 4, 5, 6, 7, 8 ],
                  'f' : [ 9, 10, 11, 12, 13 ],
                  'all' : None }
    return to_return[ l ]
 
def main():
    parser = argparse.ArgumentParser()
    parser.add_argument( '-i', '--ions', help='ion indices for band projection (default: sum over all ions)', nargs='+', type=int )
    parser.add_argument( '-s', '--spins', help='spin indices for band projection (default [ 1 ])', nargs='+', type=int, default=[ 1 ] )
    parser.add_argument( '-o', '--orbitals', help='orbital indices for band projection (default: sum over all orbitals)', nargs='+', type=int )
    parser.add_argument( '-e', '--efermi', help='set fermi energy as reference for energy scale', type=float, default=0.0 )
    parser.add_argument( '-l', '--l-angular-momentum', help='select all orbitals with angular momentum L for band projection. This supercedes the --orbitals option', choices=[ 's', 'p', 'd', 'f', 'all' ] )
    parser.add_argument( '-f', '--procar', help='PROCAR filename (default PROCAR)', type=str, default='PROCAR' )
    parser.add_argument( '--scaling', help='Energy scaling for band widths (default 0.2 eV)', type=float, default=0.2 )
    parser.add_argument( '-x', '--xscaling', help='Automatic scaling of x-axis using reciprocal lattice vectors read from OUTCAR', action='store_true', default=False )
    args = parser.parse_args()

    if args.l_angular_momentum:
        args.orbitals = orbitals_with_l( args.l_angular_momentum )

    if args.xscaling:
        reciprocal_lattice = reciprocal_lattice_from_outcar( 'OUTCAR' ) # Move reading the reciprocal lattice to procar.py
    else:
        reciprocal_lattice = None

    pcar = procar.Procar()
    pcar.read_from_file( args.procar )
    pcar.print_weighted_band_structure( spins = args.spins, 
                                        ions = args.ions, 
                                        orbitals = args.orbitals, 
                                        scaling = args.scaling, 
                                        e_fermi = args.efermi, 
                                        reciprocal_lattice = reciprocal_lattice )

if __name__ == '__main__':
    main()
#! /usr/bin/env python3 #def x_axis( cartesian_k_points ): #    if cartesian_k_points is not None: #        x_axis = [ 0.0 ] #        for i in range( 1, len(cartesian_k_points) ): #            d = cartesian_k_points[i - 1] - cartesian_k_points[i] #            d = np.sqrt( np.dot( d, d) ) #            x_axis.append( d + x_axis[-1] ) #        x_axis = np.array( x_axis ) #    else: #        x_axis = np.arange( len( cartesian_k_points ) ) #    return x_axis # Move reading the reciprocal lattice to procar.py