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dft_tools/python/vasp/plotools.py

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import itertools as it
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import numpy as np
# 'simplejson' is supposed to be faster than 'json' in stdlib.
try:
import simplejson as json
except ImportError:
import json
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class Projector:
"""
Class describing a local-orbital projector.
"""
def __init__(self, matrix, ib1=1, ib2=None, nion=1):
self.p_matrix = matrix.astype(np.complex128)
self.norb, self.nb = matrix.shape
self.nion = nion
self.ib1 = ib1 - 1
if not ib2 is None:
self.ib2 = ib2 - 1
else:
self.ib2 = self.nb - 1
def project_up(self, mat):
return np.dot(self.p_matrix.conj().T, np.dot(mat, self.p_matrix))
def project_down(self, mat):
assert mat.shape == (self.nb, self.nb), " Matrix must match projector in size"
return np.dot(self.p_matrix, np.dot(mat, self.p_matrix.conj().T))
def orthogonalize(self):
"""
Orthogonalizes a projector.
Returns an overlap matrix and its eigenvalues for initial projectors.
"""
self.p_matrix, overlap, over_eig = orthogonalize_projector(self.p_matrix)
return (overlap, over_eig)
################################################################################
#
# orthogonalize_projector_matrix()
#
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################################################################################
def orthogonalize_projector_matrix(p_matrix):
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"""
Orthogonalizes a projector defined by a rectangular matrix `p_matrix`.
Parameters
----------
p_matrix (numpy.array[complex]) : matrix `Nm x Nb`, where `Nm` is
the number of orbitals, `Nb` number of bands
Returns
-------
Orthogonalized projector matrix, initial overlap matrix and its eigenvalues.
"""
# Overlap matrix O_{m m'} = \sum_{v} P_{m v} P^{*}_{v m'}
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overlap = np.dot(p_matrix, p_matrix.conj().T)
# Calculate [O^{-1/2}]_{m m'}
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eig, eigv = np.linalg.eigh(overlap)
assert np.all(eig > 0.0), ("Negative eigenvalues of the overlap matrix:"
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"projectors are ill-defined")
sqrt_eig = np.diag(1.0 / np.sqrt(eig))
shalf = np.dot(eigv, np.dot(sqrt_eig, eigv.conj().T))
# Apply \tilde{P}_{m v} = \sum_{m'} [O^{-1/2}]_{m m'} P_{m' v}
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p_ortho = np.dot(shalf, p_matrix)
return (p_ortho, overlap, eig)
################################################################################
# check_data_consistency()
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################################################################################
def check_data_consistency(pars, el_struct):
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"""
Check the consistency of the VASP data.
"""
# Check that ions inside each shell are of the same sort
for sh in pars.shells:
assert max(sh['ion_list']) <= el_struct.natom, "Site index in the projected shell exceeds the number of ions in the structure"
sorts = set([el_struct.type_of_ion[io] for io in sh['ion_list']])
assert len(sorts) == 1, "Each projected shell must contain only ions of the same sort"
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# Check that ion and orbital lists in shells match those of projectors
ion_list = sh['ion_list']
lshell = sh['lshell']
for ion in ion_list:
for par in el_struct.proj_params:
if par['isite'] - 1 == ion and par['l'] == lshell:
break
else:
errmsg = "Projector for isite = %s, l = %s does not match PROJCAR"%(ion + 1, lshell)
raise Exception(errmsg)
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################################################################################
# select_bands()
################################################################################
def select_bands(eigvals, emin, emax):
"""
Select a subset of bands lying within a given energy window.
The band energies are assumed to be sorted in an ascending order.
Parameters
----------
eigvals (numpy.array) : all eigenvalues
emin, emax (float) : energy window
Returns
-------
ib_win, nb_min, nb_max :
"""
# Sanity check
if emin > eigvals.max() or emax < eigvals.min():
raise Exception("Energy window does not overlap with the band structure")
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nk, nband, ns_band = eigvals.shape
ib_win = np.zeros((nk, ns_band, 2), dtype=np.int32)
nb_min = 10000000
nb_max = 0
for isp in xrange(ns_band):
for ik in xrange(nk):
for ib in xrange(nband):
en = eigvals[ik, ib, isp]
if en >= emin:
break
ib1 = ib
for ib in xrange(ib1, nband):
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en = eigvals[ik, ib, isp]
if en > emax:
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break
else:
# If we reached the last band add 1 to get the correct bound
ib += 1
ib2 = ib - 1
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ib_win[ik, isp, 0] = ib1
ib_win[ik, isp, 1] = ib2
nb_min = min(nb_min, ib1)
nb_max = max(nb_max, ib2)
return ib_win, nb_min, nb_max
################################################################################
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################################################################################
#
# class ProjectorGroup
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#
################################################################################
################################################################################
class ProjectorGroup:
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"""
Container of projectors defined within a certain energy window.
The constructor selects a subset of projectors according to
the parameters from the config-file (passed in `pars`).
Parameters:
- gr_pars (dict) : group parameters from the config-file
- shells ([ProjectorShell]) : array of ProjectorShell objects
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- eigvals (numpy.array) : array of KS eigenvalues
"""
def __init__(self, gr_pars, shells, eigvals, ferw):
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"""
Constructor
"""
self.emin = gr_pars['emin']
self.emax = gr_pars['emax']
self.ishells = gr_pars['shells']
self.ortho = gr_pars['normalize']
self.normion = gr_pars['normion']
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self.shells = shells
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# Determine the minimum and maximum band numbers
ib_win, nb_min, nb_max = select_bands(eigvals, self.emin, self.emax)
self.ib_win = ib_win
self.nb_min = nb_min
self.nb_max = nb_max
# Select projectors within the energy window
for ish in self.ishells:
shell = self.shells[ish]
shell.select_projectors(ib_win, nb_min, nb_max)
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################################################################################
#
# nelect_window
#
################################################################################
def nelect_window(self, el_struct):
"""
Determines the total number of electrons within the window.
"""
self.nelect = 0
nk, ns_band, _ = self.ib_win.shape
rspin = 2.0 if ns_band == 1 else 1.0
for isp in xrange(ns_band):
for ik in xrange(nk):
ib1 = self.ib_win[ik, isp, 0]
ib2 = self.ib_win[ik, isp, 1]
occ = el_struct.ferw[isp, ik, ib1:ib2]
kwght = el_struct.kmesh['kweights'][ik]
self.nelect += occ.sum() * kwght * rspin
return self.nelect
################################################################################
#
# orthogonalize
#
################################################################################
def orthogonalize(self):
"""
Orthogonalize a group of projectors.
"""
# Quick exit if no normalization is requested
if not self.ortho:
return
# TODO: add the case of 'normion = True'
assert not self.normion, "'NORMION = True' is not yet implemented"
# Determine the dimension of the projector matrix
# and map the blocks to the big matrix
i1_bl = 0
bl_map = [{} for ish in self.ishells]
for ish in self.ishells:
_shell = self.shells[ish]
nion, ns, nk, nlm, nb_max = _shell.proj_win.shape
bmat_bl = [] # indices corresponding to a big block matrix
for ion in xrange(nion):
i2_bl = i1_bl + nlm
bmat_bl.append((i1_bl, i2_bl))
i1_bl = i2_bl
bl_map[ish]['bmat_blocks'] = bmat_bl
ndim = i2_bl
p_mat = np.zeros((ndim, nb_max), dtype=np.complex128)
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for isp in xrange(ns):
for ik in xrange(nk):
nb = self.ib_win[ik, isp, 1] - self.ib_win[ik, isp, 0] + 1
# Combine all projectors of the group to one block projector
for ish in self.ishells:
shell = self.shells[ish]
blocks = bl_map[ish]['bmat_blocks']
for ion in xrange(nion):
i1, i2 = blocks[ion]
p_mat[i1:i2, :nb] = shell.proj_win[ion, isp, ik, :nlm, :nb]
# Now orthogonalize the obtained block projector
p_orth, overl, eig = orthogonalize_projector_matrix(p_mat)
# Distribute back projectors in the same order
for ish in self.ishells:
shell = self.shells[ish]
blocks = bl_map[ish]['bmat_blocks']
for ion in xrange(nion):
i1, i2 = blocks[ion]
shell.proj_win[ion, isp, ik, :nlm, :nb] = p_mat[i1:i2, :nb]
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################################################################################
################################################################################
#
# class ProjectorShell
#
################################################################################
################################################################################
class ProjectorShell:
"""
Container of projectors related to a specific shell.
The constructor pre-selects a subset of projectors according to
the shell parameters passed from the config-file.
Parameters:
- sh_pars (dict) : shell parameters from the config-file
- proj_raw (numpy.array) : array of raw projectors
"""
def __init__(self, sh_pars, proj_raw, proj_params):
self.lorb = sh_pars['lshell']
self.ion_list = sh_pars['ion_list']
self.user_index = sh_pars['user_index']
try:
self.tmatrix = sh_pars['tmatrix']
except KeyError:
self.tmatrix = None
self.lm1 = self.lorb**2
self.lm2 = (self.lorb+1)**2
if self.tmatrix is None:
self.ndim = self.lm2 - self.lm1
else:
# TODO: generalize this to a tmatrix for every ion
self.ndim = self.tmatrix.shape[0]
# Pre-select a subset of projectors (this should be an array view => no memory is wasted)
# !!! This sucks but I have to change the order of 'ib' and 'ilm' indices here
# This should perhaps be done right after the projector array is read from PLOCAR
# self.proj_arr = proj_raw[self.ion_list, :, :, :, self.lm1:self.lm2].transpose((0, 1, 2, 4, 3))
# We want to select projectors from 'proj_raw' and form an array
# self.proj_arr[nion, ns, nk, nlm, nb]
# TODO: think of a smart way of copying the selected projectors
# perhaps, by redesigning slightly the structure of 'proj_arr' and 'proj_win'
# or by storing only a mapping between site/orbitals and indices of 'proj_raw'
# iproj_l = []
nion = len(self.ion_list)
nlm = self.lm2 - self.lm1
_, ns, nk, nb = proj_raw.shape
self.proj_arr = np.zeros((nion, ns, nk, nlm, nb), dtype=np.complex128)
for io, ion in enumerate(self.ion_list):
for m in xrange(nlm):
# Here we search for the index of the projector with the given isite/l/m indices
for ip, par in enumerate(proj_params):
if par['isite'] - 1 == ion and par['l'] == self.lorb and par['m'] == m:
# iproj_l.append(ip)
self.proj_arr[io, :, :, m, :] = proj_raw[ip, :, :, :]
break
# self.proj_arr = proj_raw[iproj_l, :, :, :].transpose((1, 2, 0, 3))
################################################################################
#
# select_projectors
#
################################################################################
def select_projectors(self, ib_win, nb_min, nb_max):
"""
Selects a subset of projectors corresponding to a given energy window.
"""
self.ib_win = ib_win
self.nb_min = nb_min
self.nb_max = nb_max
# Set the dimensions of the array
nb_win = self.nb_max - self.nb_min + 1
nion, ns, nk, nlm, nbtot = self.proj_arr.shape
# !!! Note that the order of the two last indices is different !!!
self.proj_win = np.zeros((nion, ns, nk, nlm, nb_win), dtype=np.complex128)
# Select projectors for a given energy window
ns_band = self.ib_win.shape[1]
for isp in xrange(ns):
for ik in xrange(nk):
# TODO: for non-collinear case something else should be done here
is_b = min(isp, ns_band)
ib1 = self.ib_win[ik, is_b, 0]
ib2 = self.ib_win[ik, is_b, 1] + 1
ib1_win = ib1 - self.nb_min
ib2_win = ib2 - self.nb_min
self.proj_win[:, isp, ik, :, ib1_win:ib2_win] = self.proj_arr[:, isp, ik, :, ib1:ib2]
################################################################################
#
# select_projectors
#
################################################################################
def density_matrix(self, el_struct, site_diag=True, spin_diag=True):
"""
Returns occupation matrix/matrices for the shell.
"""
nion, ns, nk, nlm, nbtot = self.proj_win.shape
assert site_diag, "site_diag = False is not implemented"
assert spin_diag, "spin_diag = False is not implemented"
occ_mats = np.zeros((ns, nion, nlm, nlm), dtype=np.float64)
kweights = el_struct.kmesh['kweights']
occnums = el_struct.ferw
ib1 = self.nb_min
ib2 = self.nb_max + 1
for isp in xrange(ns):
for ik, weight, occ in it.izip(it.count(), kweights, occnums[isp, :, :]):
for io in xrange(nion):
proj_k = self.proj_win[isp, io, ik, ...]
occ_mats[isp, io, :, :] += np.dot(proj_k * occ[ib1:ib2],
proj_k.conj().T).real * weight
# if not symops is None:
# occ_mats = symmetrize_matrix_set(occ_mats, symops, ions, perm_map)
return occ_mats
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################################################################################
#
# generate_plo()
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#
################################################################################
def generate_plo(conf_pars, el_struct):
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"""
Parameters
----------
conf_pars (dict) : dictionary of input parameters (from conf-file)
el_struct : ElectronicStructure object
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"""
check_data_consistency(conf_pars, el_struct)
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proj_raw = el_struct.proj_raw
try:
efermi = conf_pars.general['efermi']
except (KeyError, AttributeError):
efermi = el_struct.efermi
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# eigvals(nktot, nband, ispin) are defined with respect to the Fermi level
eigvals = el_struct.eigvals - efermi
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pshells = []
for sh_par in conf_pars.shells:
pshells.append(ProjectorShell(sh_par, proj_raw, el_struct.proj_params))
pgroups = []
for gr_par in conf_pars.groups:
pgroup = ProjectorGroup(gr_par, pshells, eigvals, el_struct.ferw)
# pgroup.orthogonalize()
pgroups.append(pgroup)
return pshells, pgroups
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# TODO: k-points with weights should be stored once and for all
################################################################################
#
# kpoints_output
#
################################################################################
def kpoints_output(basename, el_struct):
"""
Outputs k-point data into a text file.
"""
kmesh = el_struct.kmesh
fname = basename + '.kpoints'
with open(fname, 'wt') as f:
f.write("# Number of k-points: nktot\n")
nktot = kmesh['nktot']
f.write("%i\n"%(nktot))
# TODO: add the output of reciprocal lattice vectors
f.write("# List of k-points with weights\n")
for ik in xrange(nktot):
kx, ky, kz = kmesh['kpoints'][ik, :]
kwght = kmesh['kweights'][ik]
f.write("%15.10f%15.10f%15.10f%20.10f\n"%(kx, ky, kz, kwght))
# Check if there are tetrahedra defined and if they are, output them
try:
ntet = kmesh['ntet']
volt = kmesh['volt']
f.write("\n# Number of tetrahedra and volume: ntet, volt\n")
f.write("%i %s\n"%(ntet, volt))
f.write("# List of tetrahedra: imult, ik1, ..., ik4\n")
for it in xrange(ntet):
f.write(' '.join(map("{0:d}".format, *kmesh['itet'][it, :])) + '\n')
except KeyError:
pass
################################################################################
#
# ctrl_output
#
################################################################################
def ctrl_output(conf_pars, el_struct, ng):
"""
Outputs a ctrl-file.
"""
ctrl_fname = conf_pars.general['basename'] + '.ctrl'
head_dict = {}
# TODO: Add output of tetrahedra
# Construct the header dictionary
head_dict['ngroups'] = ng
head_dict['nk'] = el_struct.kmesh['nktot']
head_dict['ns'] = el_struct.nspin
head_dict['nc_flag'] = 1 if el_struct.nc_flag else 0
# head_dict['efermi'] = conf_pars.general['efermi'] # We probably don't need Efermi
header = json.dumps(head_dict, indent=4, separators=(',', ': '))
print " Storing ctrl-file..."
with open(ctrl_fname, 'wt') as f:
f.write(header + "\n")
f.write("#END OF HEADER\n")
f.write("# k-points and weights\n")
labels = ['kx', 'ky', 'kz', 'kweight']
out = "".join(map(lambda s: s.center(15), labels))
f.write("#" + out + "\n")
for ik, kp in enumerate(el_struct.kmesh['kpoints']):
tmp1 = "".join(map("{0:15.10f}".format, kp))
out = tmp1 + "{0:16.10f}".format(el_struct.kmesh['kweights'][ik])
f.write(out + "\n")
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################################################################################
#
# plo_output
#
################################################################################
def plo_output(conf_pars, el_struct, pshells, pgroups):
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"""
Outputs PLO groups into text files.
Filenames are defined by <basename> that is passed from config-file.
All necessary general parameters are stored in a file '<basename>.ctrl'.
Each group is stored in a '<basename>.plog<Ng>' file. The format is the
following:
# Energy window: emin, emax
ib_min, ib_max
nelect
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# Eigenvalues
isp, ik1, kx, ky, kz, kweight
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ib1, ib2
eig1
eig2
...
eigN
ik2, kx, ky, kz, kweight
...
# Projected shells
Nshells
# Shells: <shell indices>
# Shell <1>
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Shell 1
ndim
# complex arrays: plo(ns, nion, ndim, nb)
...
# Shells: <shell indices>
# Shell <2>
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Shell 2
...
"""
for ig, pgroup in enumerate(pgroups):
plo_fname = conf_pars.general['basename'] + '.pg%i'%(ig + 1)
print " Storing PLO-group file '%s'..."%(plo_fname)
head_dict = {}
head_dict['ewindow'] = (pgroup.emin, pgroup.emax)
head_dict['nb_max'] = pgroup.nb_max
# Number of electrons within the window
head_dict['nelect'] = pgroup.nelect_window(el_struct)
print " Density within window:", head_dict['nelect']
head_shells = []
for ish in pgroup.ishells:
shell = pgroup.shells[ish]
sh_dict = {}
sh_dict['shell_index'] = ish
sh_dict['lorb'] = shell.lorb
sh_dict['ndim'] = shell.ndim
# Convert ion indices from the internal representation (starting from 0)
# to conventional VASP representation (starting from 1)
ion_output = [io + 1 for io in shell.ion_list]
sh_dict['ion_list'] = ion_output
sh_dict['ion_sort'] = el_struct.type_of_ion[shell.ion_list[0]]
# TODO: add the output of transformation matrices
head_shells.append(sh_dict)
head_dict['shells'] = head_shells
header = json.dumps(head_dict, indent=4, separators=(',', ': '))
with open(plo_fname, 'wt') as f:
f.write(header + "\n")
f.write("#END OF HEADER\n")
# Eigenvalues within the window
f.write("# Eigenvalues within the energy window: %s, %s\n"%(pgroup.emin, pgroup.emax))
nk, nband, ns_band = el_struct.eigvals.shape
for isp in xrange(ns_band):
f.write("# is = %i\n"%(isp + 1))
for ik in xrange(nk):
ib1, ib2 = pgroup.ib_win[ik, isp, 0], pgroup.ib_win[ik, isp, 1]
f.write(" %i %i\n"%(ib1, ib2))
for ib in xrange(ib1, ib2 + 1):
f.write("%15.7f\n"%(el_struct.eigvals[ik, ib, isp]))
# Projected shells
f.write("# Projected shells\n")
f.write("# Shells: %s\n"%(pgroup.ishells))
for ish in pgroup.ishells:
shell = pgroup.shells[ish]
f.write("# Shell %i\n"%(ish))
nion, ns, nk, nlm, nb = shell.proj_win.shape
for isp in xrange(ns):
f.write("# is = %i\n"%(isp + 1))
for ik in xrange(nk):
f.write("# ik = %i\n"%(ik + 1))
for ion in xrange(nion):
for ilm in xrange(nlm):
ib1, ib2 = pgroup.ib_win[ik, isp, 0], pgroup.ib_win[ik, isp, 1]
ib1_win = ib1 - shell.nb_min
ib2_win = ib2 - shell.nb_min
for ib in xrange(ib1_win, ib2_win + 1):
p = shell.proj_win[ion, isp, ik, ilm, ib]
f.write("{0:16.10f}{1:16.10f}\n".format(p.real, p.imag))
f.write("\n")
################################################################################
#
# output_as_text
#
################################################################################
def output_as_text(pars, el_struct, pshells, pgroups):
"""
Output all information necessary for the converter as text files.
"""
ctrl_output(pars, el_struct, len(pgroups))
plo_output(pars, el_struct, pshells, pgroups)