def __init__(self, settings_obj,):
self.settings_obj = settings_obj
try:
if self.settings_obj.poscar_path:
self.structure = Structure.from_file(self.settings_obj.poscar_path)
else:
self.structure = Structure.from_file('POSCAR')
except FileNotFoundError as e:
print(e)
print('The given filepath for the poscar did not find a poscar file, ensure POSCAR is at the end '
'e.g. /POSCAR. if no filepath was given then no poscar was found in the current directory.')
# currently only works for orthogonal structures
if not self.check_orthog_lat():
print('exiting prog')
sys.exit()
#raplce any vacuums with the default small value so that we can do voronoi analysis - it crashes for structures with large vacuum spaces
# note the size of the vacuum size swapped isn't important, will find voronoi vertices there but they'll be removed as they'll be outside of the unshifted structure or inside layers!
# only issue may be sites near the edges -> these will be ranked low due to potential sum
self.orig_struct, self.downwards_shifts, self.lowest_atoms, self.highest_atoms, self.structure = self.find_vacuums() #this changes structure to one without vacuum. copies the old structure as self.orig_struct
# find the number of ions we are intercalating
self.no_ions = int(self.settings_obj.int_dens * self.structure.num_sites) # density*no of sites = # to intercalate
#use md package to get the points of high potential
try:
if self.settings_obj.locpot_path:
self.vasp_pot, self.NGX, self.NGY, self.NGZ, self.lattice = md.read_vasp_density(self.settings_obj.locpot_path)
else:
self.vasp_pot, self.NGX, self.NGY, self.NGZ, self.lattice = md.read_vasp_density('LOCPOT')
self.grid_pot, self.electrons = md.density_2_grid(self.vasp_pot, self.NGX, self.NGY, self.NGZ) # generate the grid of potentials
self.settings_obj.locpot = True
except FileNotFoundError as e:
print(e)
print('The given filepath for the locpot did not find a locpot file, ensure LOCPOT is at the end '
'e.g. /LOCPOT. if no filepath was given then no locpot was found in the current directory.')
self.settings_obj.locpot = False
# get the intersitials using voronoi decomposition
self.interstitial_sites = self.get_interstitials() #### SLOW! very very slow!!
# go back to the original, unshifted structure
#self.shifted_structure = self.structure.copy()
self.structure = self.orig_struct.copy()
# convert interstitial sites back to fractional coords (previously were in cartesian due to the shifts!
self.interstitial_sites = [([i[0][0] / self.structure.lattice.a, i[0][1] / self.structure.lattice.b,
i[0][2] / self.structure.lattice.c], i[1]) for i in
self.interstitial_sites]
def test_density_2_grid(self):
'''Test the function for projecting the potential onto a grid'''
charge, ngx, ngy, ngz, lattice = md.read_vasp_density('CHGCAR.test')
grid_pot, electrons = md.density_2_grid(charge, ngx, ngy, ngz)
self.assertAlmostEqual(grid_pot[0, 0, 0], -.76010173913E+01)
self.assertAlmostEqual(grid_pot[55, 55, 55], -4.4496715627)
self.assertAlmostEqual(electrons, 8.00000, places=4)
def test_read_vasp(self):
'''Test the function for reading CHGCAR/LOCPOT'''
charge, ngx, ngy, ngz, lattice = md.read_vasp_density('CHGCAR.test')
self.assertEqual(charge[0], -.76010173913E+01)
self.assertEqual(charge[56 * 56 * 56 - 1], -4.4496715627)
self.assertEqual(lattice[0, 0], 2.7150000)
self.assertEqual(ngx, 56)
def test_ipr(self):
'''Test the ipr function'''
parchg = pkg_resources.resource_filename(
__name__, path_join('..', 'CHGCAR.test'))
dens, ngx, ngy, ngz, lattice = md.read_vasp_density(parchg, quiet=True)
self.assertAlmostEqual(md.inverse_participation_ratio(dens), 1.407e-5)
def test_density_2_grid(self):
'''Test the function for projecting the potential onto a grid'''
chgcar = pkg_resources.resource_filename(
__name__, path_join('..', 'CHGCAR.test'))
charge, ngx, ngy, ngz, lattice = md.read_vasp_density(chgcar,
quiet=True)
grid_pot, electrons = md.density_2_grid(charge, ngx, ngy, ngz)
self.assertAlmostEqual(grid_pot[0, 0, 0], - .76010173913E+01)
self.assertAlmostEqual(grid_pot[55, 55, 55], -4.4496715627)
self.assertAlmostEqual(electrons, 8.00000, places=4)
def test_read_vasp(self):
'''Test the function for reading CHGCAR/LOCPOT'''
chgcar = pkg_resources.resource_filename(
__name__, path_join('..', 'CHGCAR.test'))
charge, ngx, ngy, ngz, lattice = md.read_vasp_density(chgcar,
quiet=True)
for v, t in ((charge, np.ndarray), (ngx, int), (ngy, int), (ngz, int),
(lattice, np.ndarray)):
self.assertIsInstance(v, t)
self.assertEqual(charge[0], -.76010173913E+01)
self.assertEqual(charge[56 * 56 * 56 - 1], -4.4496715627)
self.assertEqual(lattice[0, 0], 2.7150000)
self.assertEqual(ngx, 56)
log.write("--------------------\n")
log.write(
"[WARNING] Fermi energy is not extracted. Shifting is not done\n"
)
print(
"[WARNING] fermi energy is not extracted. Shifting is not done"
)
else:
log.write("--------------------\n")
log.write("(Manually set) Fermi energy= [" + str(fermi_e) + " ] eV.\n")
log.write("--------------------\n")
#------------------------------------------------------------------
# Get the potential
#------------------------------------------------------------------
vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density(input_file,
quiet=True)
vector_a, vector_b, vector_c, av, bv, cv = md.matrix_2_abc(Lattice)
resolution_x = vector_a / NGX
resolution_y = vector_b / NGY
resolution_z = vector_c / NGZ
grid_pot, electrons = md.density_2_grid(vasp_pot, NGX, NGY, NGZ)
#------------------------------------------------------------------
# POTENTIAL
#------------------------------------------------------------------
planar = md.planar_average(grid_pot, NGX, NGY, NGZ)
shifted_planar = planar - fermi_e
plt.plot(shifted_planar)
#------------start: MACROSCOPIC AVERAGE
if Macro_average:
import macrodensity as md import matplotlib.pyplot as plt import matplotlib as mpl import numpy as np import os input_file = '' lattice_vector = 3.90821 vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density(input_file + 'LOCPOT') vector_a, vector_b, vector_c, av, bv, cv = md.matrix_2_abc(Lattice) resolution_x = vector_a / NGX resolution_y = vector_b / NGY resolution_z = vector_c / NGZ grid_pot, electrons = md.density_2_grid(vasp_pot, NGX, NGY, NGZ) # POTENTIAL planar = md.planar_average(grid_pot, NGX, NGY, NGZ) # MACROSCOPIC AVERAGE macro = md.macroscopic_average(planar, lattice_vector, resolution_z) x = np.linspace(0, 1, len(planar)) fig, ax1 = plt.subplots(1, 1, sharex=True) textsize = 22 mpl.rcParams['xtick.labelsize'] = textsize mpl.rcParams['ytick.labelsize'] = textsize mpl.rcParams['figure.figsize'] = (10, 6) ax1.plot(x, planar, label="Planar", lw=3) ax1.plot(x, macro, label="Macroscopic", lw=3) ax1.set_xlim(0, 1)
#! /usr/bin/env python
import macrodensity as md
import math
import numpy as np
import matplotlib.pyplot as plt
import csv
from itertools import izip
#------------------------------------------------------------------
# Get the potential
# This section should not be altered
#------------------------------------------------------------------
vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density('LOCPOT.slab')
vector_a, vector_b, vector_c, av, bv, cv = md.matrix_2_abc(Lattice)
resolution_x = vector_a / NGX
resolution_y = vector_b / NGY
resolution_z = vector_c / NGZ
grid_pot, electrons = md.density_2_grid(vasp_pot, NGX, NGY, NGZ)
## Get the gradiens (Field), if required.
## Comment out if not required, due to compuational expense.
grad_x, grad_y, grad_z = np.gradient(grid_pot[:, :, :], resolution_x,
resolution_y, resolution_z)
#------------------------------------------------------------------
##------------------------------------------------------------------
## Get the equation for the plane
## This is the section for plotting on a user defined plane;
## uncomment commands if this is the option that you want.
##------------------------------------------------------------------
## Input section (define the plane with 3 points)
#a_point = [0, 0, 0]
#! /usr/bin/env python
import macrodensity as md
import math
import numpy as np
import matplotlib.pyplot as plt
import csv
from itertools import izip
#------------------------------------------------------------------
# Get the potential
# This section should not be altered
#------------------------------------------------------------------
vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density('LOCPOT.slab')
vector_a,vector_b,vector_c,av,bv,cv = md.matrix_2_abc(Lattice)
resolution_x = vector_a/NGX
resolution_y = vector_b/NGY
resolution_z = vector_c/NGZ
grid_pot, electrons = md.density_2_grid(vasp_pot,NGX,NGY,NGZ)
cutoff_varience = 1E-4
hanksConstant = 4.89E-7
## Get the gradiens (Field), if required.
## Comment out if not required, due to compuational expense.
#grad_x,grad_y,grad_z = np.gradient(grid_pot[:,:,:],resolution_x,resolution_y,resolution_z)
#------------------------------------------------------------------
##------------------------------------------------------------------
## Get the equation for the plane
import matplotlib.pyplot as plt import csv from itertools import izip potential_file = 'LOCPOT' # The file with VASP output for potential coordinate_file = 'POSCAR' # The coordinates file NOTE NOTE This must be in vasp 4 format species = "O" # The species whose on-site potential you are interested in sample_cube = [5,5,5] # The size of the sampling cube in units of mesh points (NGX/Y/Z) # Nothing below here should require changing #------------------------------------------------------------------ # Get the potential # This section should not be altered #------------------------------------------------------------------ vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density(potential_file) vector_a,vector_b,vector_c,av,bv,cv = md.matrix_2_abc(Lattice) resolution_x = vector_a/NGX resolution_y = vector_b/NGY resolution_z = vector_c/NGZ grid_pot, electrons = md.density_2_grid(vasp_pot,NGX,NGY,NGZ) ## Get the gradiens (Field), if required. ## Comment out if not required, due to compuational expense. grad_x,grad_y,grad_z = np.gradient(grid_pot[:,:,:],resolution_x,resolution_y,resolution_z) #------------------------------------------------------------------ ##------------------------------------------------------------------ ## Getting the potentials for a group of atoms, in this case the Os ## NOTE THIS REQUIRES ASE to be available https://wiki.fysik.dtu.dk/ase/index.html ##------------------------------------------------------------------ ##------------------------------------------------------------------
import macrodensity as md
import math
import numpy as np
import matplotlib.pyplot as plt
#------------------------------------------------------------------
# READING
# Get the two potentials and change them to a planar average.
# This section should not be altered
#------------------------------------------------------------------
# SLAB
vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density('CHGCAR.Slab')
mag_a,mag_b,mag_c,vec_a,vec_b,vec_c = md.matrix_2_abc(Lattice)
resolution_x = mag_a/NGX
resolution_y = mag_b/NGY
resolution_z = mag_c/NGZ
Volume = md.get_volume(vec_a,vec_b,vec_c)
grid_pot_slab, electrons_slab = md.density_2_grid(vasp_pot,NGX,NGY,NGZ,True,Volume)
# Save the lattce vectors for use later
Vector_A = [vec_a,vec_b,vec_c]
#----------------------------------------------------------------------------------
# CONVERT TO PLANAR DENSITIES
#----------------------------------------------------------------------------------
planar_slab = md.planar_average(grid_pot_slab,NGX,NGY,NGZ)
# BULK
vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density('CHGCAR.Bulk')
mag_a,mag_b,mag_c,vec_a,vec_b,vec_c = md.matrix_2_abc(Lattice)
import csv
from itertools import izip
potential_file = 'LOCPOT' # The file with VASP output for potential
coordinate_file = 'POSCAR' # The coordinates file NOTE NOTE This must be in vasp 4 format
species = "O" # The species whose on-site potential you are interested in
sample_cube = [
5, 5, 5
] # The size of the sampling cube in units of mesh points (NGX/Y/Z)
# Nothing below here should require changing
#------------------------------------------------------------------
# Get the potential
# This section should not be altered
#------------------------------------------------------------------
vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density(potential_file)
vector_a, vector_b, vector_c, av, bv, cv = md.matrix_2_abc(Lattice)
resolution_x = vector_a / NGX
resolution_y = vector_b / NGY
resolution_z = vector_c / NGZ
grid_pot, electrons = md.density_2_grid(vasp_pot, NGX, NGY, NGZ)
## Get the gradiens (Field), if required.
## Comment out if not required, due to compuational expense.
grad_x, grad_y, grad_z = np.gradient(grid_pot[:, :, :], resolution_x,
resolution_y, resolution_z)
#------------------------------------------------------------------
##------------------------------------------------------------------
## Getting the potentials for a group of atoms, in this case the Os
## NOTE THIS REQUIRES ASE to be available https://wiki.fysik.dtu.dk/ase/index.html
##------------------------------------------------------------------
#! /usr/bin/env python
import macrodensity as md
import math
import numpy as np
import matplotlib.pyplot as plt
input_file = 'LOCPOT'
lattice_vector = 4.75
output_file = 'planar.dat'
# No need to alter anything after here
#------------------------------------------------------------------
# Get the potential
# This section should not be altered
#------------------------------------------------------------------
vasp_pot, NGX, NGY, NGZ, Lattice = md.read_vasp_density(input_file)
vector_a,vector_b,vector_c,av,bv,cv = md.matrix_2_abc(Lattice)
resolution_x = vector_a/NGX
resolution_y = vector_b/NGY
resolution_z = vector_c/NGZ
grid_pot, electrons = md.density_2_grid(vasp_pot,NGX,NGY,NGZ)
#------------------------------------------------------------------
## POTENTIAL
planar = md.planar_average(grid_pot,NGX,NGY,NGZ)
## MACROSCOPIC AVERAGE
macro = md.macroscopic_average(planar,lattice_vector,resolution_z)
plt.plot(planar)
plt.plot(macro)
plt.savefig('Planar.eps')
plt.show()
np.savetxt(output_file,planar)
##------------------------------------------------------------------
def __init__(
self,
settings_obj,
):
self.settings_obj = settings_obj
try:
if self.settings_obj.poscar_path:
self.structure = Structure.from_file(
self.settings_obj.poscar_path)
else:
self.structure = Structure.from_file('POSCAR')
except FileNotFoundError as e:
print(e)
print(
'The given filepath for the poscar did not find a poscar file, ensure POSCAR is at the end '
'e.g. /POSCAR. if no filepath was given then no poscar was found in the current directory.'
)
self.no_ions = int(self.settings_obj.int_dens *
self.structure.num_sites)
try:
if self.settings_obj.locpot_path:
self.vasp_pot, self.NGX, self.NGY, self.NGZ, self.lattice = md.read_vasp_density(
self.settings_obj.locpot_path)
else:
self.vasp_pot, self.NGX, self.NGY, self.NGZ, self.lattice = md.read_vasp_density(
'LOCPOT')
self.grid_pot, self.electrons = md.density_2_grid(
self.vasp_pot, self.NGX, self.NGY,
self.NGZ) # generate the grid of potentials
except FileNotFoundError as e:
print(e)
print(
'The given filepath for the locpot did not find a locpot file, ensure LOCPOT is at the end '
'e.g. /LOCPOT. if no filepath was given then no locpot was found in the current directory.'
)
# then run as normal, once voronoi done and cells found, convert back and carry on
if not self.check_orthog_lat():
print('exiting prog')
sys.exit()
self.find_vacuums(
) #this changes structure to one without vacuum. copies the old structure as self.orig_struct
self.evaluator = ValenceIonicRadiusEvaluator(
self.structure
) #computes site valence and ionic radii using bond valence analyser.
# note this uses the sites, periodic table, bond valence, composition and local env packages! (as well as structure)
self.radii = self.evaluator.radii
self.valences = self.evaluator.valences
self.interstitial = Interstitial(
self.structure,
radii=self.radii,
valences=self.valences,
symmetry_flag=self.settings_obj.sym_dist)
# this evaluates the structure and uses radii and valence to generate voronoi sites depending on whether vertex,
# facecenter or edge center is selected.
# note: not sur eif hsould set oxi_state = False. By default it is true and it then uses ionic radii in the calculation,
# shouldnt really change centres? Returns and interstitial object. ._defect_sites returns the coordinates and labels of
# all intersittial sites which were found from the voronoi nodes/edges/faces/all depending on settings.
# sym if False so we get all sites, including symmetry inequivalent sites!
print('\n')
self.interstitial_sites = [
([site._fcoords[0], site._fcoords[1],
site._fcoords[2]], site.properties.get('voronoi_radius', None))
for site in self.interstitial._defect_sites
] # this creates a list of tuples: [ (array of site location
# fractional coordinates, Voronoi radius') ]
# replaced with self.get_nearest_neighbour_dist(site)
# shift vornoi up if shifted!
self.interstitial_sites = [
([
i[0][0] * self.structure.lattice.a -
self.downwards_shifts[0][0],
i[0][1] * self.structure.lattice.b -
self.downwards_shifts[1][1],
i[0][2] * self.structure.lattice.c -
self.downwards_shifts[2][2]
], i[1]) for i in self.interstitial_sites
] #shift it and convert to cart coords at the same time
# go back to the original, unshifted structure
self.shifted_structure = self.structure.copy()
self.structure = self.orig_struct.copy()
self.interstitial_sites = [([
i[0][0] / self.structure.lattice.a,
i[0][1] / self.structure.lattice.b,
i[0][2] / self.structure.lattice.c
], i[1]) for i in self.interstitial_sites
] # convert it back to fractional coords
