diff --git a/python/converters/plovasp/examples/ce/.gitignore b/python/converters/plovasp/examples/ce/.gitignore new file mode 100644 index 00000000..bddea1c2 --- /dev/null +++ b/python/converters/plovasp/examples/ce/.gitignore @@ -0,0 +1,9 @@ +* +!.gitignore +!INCAR +!POSCAR +!POTCAR +!KPOINTS +!plo.cfg +!*.sh +!*.py diff --git a/python/converters/plovasp/examples/ce/INCAR b/python/converters/plovasp/examples/ce/INCAR new file mode 100644 index 00000000..5a61a0df --- /dev/null +++ b/python/converters/plovasp/examples/ce/INCAR @@ -0,0 +1,49 @@ +ADDGRID = TRUE +AMIX = 0.1 +AMIN = 0.01 +BMIX = 0.0001 +#IMIX = 1 +#MIXFIRST = True +ALGO = NORMAL +EDIFF = 0.00001 +EDIFFG = -0.002 +EMAX = 13.0 +EMIN = -2.0 +ENCUT = 600 +ENAUG = 1100 +IBRION = -1 +ICHARG = 5 +ISIF = 4 +ISMEAR = 2 +ISPIN = 2 +ISYM = -1 +LASPH = TRUE +LCHARG = TRUE +LDAU = True +LDAUJ = 0 +LDAUL = 3 +LDAUTYPE = 2 +LDAUU = 0.0 +LDAUPRINT = 2 +LMAXMIX = 6 +LORBIT = 13 +LREAL = False +ROPT = 1e-3 1e-3 1e-3 +LWAVE = TRUE +MAGMOM = 1.1 +#NBANDS = 16 +NEDOS = 501 +NELM = 100 +NELMDL = -7 +NELMIN = 1 +NPAR = 4 +NSIM = 1 +NSW = 0 +POTIM = 0.4 +PREC = Accurate +SIGMA = 0.1 +SMASS = 0.5 +SYMPREC = 1.0e-6 + +# Projectors +LOCPROJ = 1 : f : Pr 1 diff --git a/python/converters/plovasp/examples/ce/KPOINTS b/python/converters/plovasp/examples/ce/KPOINTS new file mode 100644 index 00000000..1370e3ff --- /dev/null +++ b/python/converters/plovasp/examples/ce/KPOINTS @@ -0,0 +1,4 @@ +Automatic kpoint scheme +0 +Gamma +4 4 4 diff --git a/python/converters/plovasp/examples/ce/POSCAR b/python/converters/plovasp/examples/ce/POSCAR new file mode 100644 index 00000000..31a4bac2 --- /dev/null +++ b/python/converters/plovasp/examples/ce/POSCAR @@ -0,0 +1,9 @@ +gamma-Ce + 1.0 + 2.5790000000000000 2.5790000000000000 0.0000000000000000 + 0.0000000000000000 2.5790000000000000 2.5790000000000000 + 2.5790000000000000 0.0000000000000000 2.5790000000000000 + Ce + 1 +Direct + 0.0 0.0 0.0 diff --git a/python/converters/plovasp/examples/ce/POTCAR b/python/converters/plovasp/examples/ce/POTCAR new file mode 100644 index 00000000..1c666c3f --- /dev/null +++ b/python/converters/plovasp/examples/ce/POTCAR @@ -0,0 +1,3011 @@ + PAW Ce 26Mar2009 + 12.0000000000000 + parameters from PSCTR are: + VRHFIN =Ce : [core=Kr4d] + LEXCH = CA + EATOM = 1067.1067 eV, 78.4301 Ry + + TITEL = PAW Ce 26Mar2009 + LULTRA = F use ultrasoft PP ? + IUNSCR = 1 unscreen: 0-lin 1-nonlin 2-no + RPACOR = 1.800 partial core radius + POMASS = 140.115; ZVAL = 12.000 mass and valenz + RCORE = 2.700 outmost cutoff radius + RWIGS = 2.500; RWIGS = 1.323 wigner-seitz radius (au A) + ENMAX = 273.088; ENMIN = 204.816 eV + RCLOC = 1.810 cutoff for local pot + LCOR = T correct aug charges + LPAW = T paw PP + EAUG = 580.196 + DEXC = 0.000 + RMAX = 2.749 core radius for proj-oper + RAUG = 1.300 factor for augmentation sphere + RDEP = 2.810 radius for radial grids + RDEPT = 2.162 core radius for aug-charge + + Atomic configuration + 14 entries + n l j E occ. + 1 0 0.50 -40012.5569 2.0000 + 2 0 0.50 -6414.9631 2.0000 + 2 1 1.50 -5754.1130 6.0000 + 3 0 0.50 -1381.7874 2.0000 + 3 1 1.50 -1170.8585 6.0000 + 3 2 2.50 -869.4387 10.0000 + 4 0 0.50 -279.2642 2.0000 + 4 1 1.50 -210.1917 6.0000 + 4 2 2.50 -110.4498 10.0000 + 5 0 0.50 -40.5958 2.0000 + 6 0 0.50 -3.8774 2.0000 + 5 1 1.50 -23.2715 6.0000 + 5 2 2.50 -3.2029 1.0000 + 4 3 2.50 -5.7775 1.0000 + Description + l E TYP RCUT TYP RCUT + 0 -40.5957679 23 1.500 + 0 -3.8774239 23 2.300 + 1 -23.2714697 23 2.000 + 1 40.8174780 23 2.300 + 2 -3.2029236 23 2.500 + 2 13.6058260 23 2.500 + 3 -5.7774954 23 2.700 + 3 -5.8505052 23 2.700 + Error from kinetic energy argument (eV) + NDATA = 100 + STEP = 20.000 1.050 + 225. 217. 213. 205. 201. 192. 183. 179. + 170. 162. 157. 149. 141. 132. 124. 117. + 109. 102. 95.1 85.3 79.2 73.4 65.2 60.2 + 55.5 49.0 43.1 39.5 34.6 30.2 26.3 22.8 + 19.7 17.1 14.7 12.6 10.3 8.76 7.05 5.97 + 4.76 3.76 2.95 2.29 1.77 1.35 1.02 0.703 + 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b/python/converters/plovasp/examples/ce/U_matrix.py @@ -0,0 +1,252 @@ +from math import sqrt +from scipy.misc import factorial as fact +from itertools import product +import numpy as np + +# The interaction matrix in desired basis +# U^{spherical}_{m1 m2 m3 m4} = \sum_{k=0}^{2l} F_k angular_matrix_element(l, k, m1, m2, m3, m4) +def U_matrix(l, radial_integrals=None, U_int=None, J_hund=None, basis="spherical", T=None): + """Calculate U matrix being given either radial_integrals or U_int and J_hund. + l = angular momentum of shell being treated (l=2 for d shell, l=3 for f shell) + radial_integrals = [F0,F2,F4,..] (default None) + U_int, J_hund = values to use to compute radial_integrals (default None), + basis = "spherical", "cubic", or "other", + T = transformation matrix from spherical to desired basis, if basis='other' (default None)""" + + # Check all necessary information is present and consistent + if radial_integrals is None and (U_int is None and J_hund is None): + raise ValueError("U_matrix: provide either the radial_integrals or U_int and J_hund.") + if radial_integrals is None and (U_int is not None and J_hund is not None): + radial_integrals = U_J_to_radial_integrals(l, U_int, J_hund) + if radial_integrals is not None and (U_int is not None and J_hund is not None): + if len(radial_integrals)-1 != l: + raise ValueError("U_matrix: inconsistency in l and number of radial_integrals provided.") + if (radial_integrals - U_J_to_radial_integrals(l, U_int, J_hund)).any() != 0.0: + print "Warning: U_matrix: radial_integrals provided do not match U_int and J_hund. Using radial_integrals to calculate spherical U_matrix." + + # Full interaction matrix + # Basis of spherical harmonics Y_{-2}, Y_{-1}, Y_{0}, Y_{1}, Y_{2} + # U^{spherical}_{m1 m2 m3 m4} = \sum_{k=0}^{2l} F_k angular_matrix_element(l, k, m1, m2, m3, m4) + U_matrix = np.zeros((2*l+1,2*l+1,2*l+1,2*l+1),dtype=float) + + m_range = range(-l,l+1) + for n, F in enumerate(radial_integrals): + k = 2*n + for m1, m2, m3, m4 in product(m_range,m_range,m_range,m_range): + U_matrix[m1+l,m2+l,m3+l,m4+l] += F * angular_matrix_element(l,k,m1,m2,m3,m4) + + # Transform from spherical basis if needed + if basis == "cubic": T = spherical_to_cubic(l) + if basis == "other" and T is None: + raise ValueError("U_matrix: provide T for other bases.") + if T is not None: U_matrix = transform_U_matrix(U_matrix, T) + + return U_matrix + +# Convert full 4-index U matrix to 2-index density-density form +def reduce_4index_to_2index(U_4index): + """Reduces the four-index matrix to two-index matrices.""" + + size = len(U_4index) # 2l+1 + U = np.zeros((size,size),dtype=float) # matrix for same spin + Uprime = np.zeros((size,size),dtype=float) # matrix for opposite spin + + m_range = range(size) + for m,mp in product(m_range,m_range): + U[m,mp] = U_4index[m,mp,m,mp].real - U_4index[m,mp,mp,m].real + Uprime[m,mp] = U_4index[m,mp,m,mp].real + + return U, Uprime + +# Construct the 2-index matrices for the density-density form +def U_matrix_kanamori(n_orb, U_int, J_hund): + """Calculate the Kanamori U and Uprime matrices.""" + + U = np.zeros((n_orb,n_orb),dtype=float) # matrix for same spin + Uprime = np.zeros((n_orb,n_orb),dtype=float) # matrix for opposite spin + + m_range = range(n_orb) + for m,mp in product(m_range,m_range): + if m == mp: + Uprime[m,mp] = U_int + else: + U[m,mp] = U_int - 3.0*J_hund + Uprime[m,mp] = U_int - 2.0*J_hund + + return U, Uprime + +# Get t2g or eg components +def t2g_submatrix(U, convention=''): + """Return only the t2g part of the full d-manifold two- or four-index U matrix.""" + if convention == 'wien2k': + return subarray(U, len(U.shape)*[(2,3,4)]) + else: + return subarray(U, len(U.shape)*[(0,1,3)]) + +def eg_submatrix(U, convention=''): + """Return only the eg part of the full d-manifold two- or four-index U matrix.""" + if convention == 'wien2k': + return subarray(U, len(U.shape)*[(0,1)]) + else: + return subarray(U, len(U.shape)*[(2,4)]) + +# Transform the interaction matrix into another basis +def transform_U_matrix(U_matrix, T): + """Transform the interaction matrix into another basis by applying matrix T.""" + return np.einsum("ij,kl,jlmo,mn,op",np.conj(T),np.conj(T),U_matrix,np.transpose(T),np.transpose(T)) + +# Rotation matrices: complex harmonics to cubic harmonics +# Complex harmonics basis: ..., Y_{-2}, Y_{-1}, Y_{0}, Y_{1}, Y_{2}, ... +def spherical_to_cubic(l, convention=''): + """Returns the spherical harmonics to cubic harmonics rotation matrix.""" + size = 2*l+1 + T = np.zeros((size,size),dtype=complex) + if convention != 'wien2k' and l == 2: + raise ValueError("spherical_to_cubic: standard convention not implemented for l=1") + if l == 0: + cubic_names = ("s") + elif l == 1: + cubic_names = ("x","y","z") + T[0,0] = 1.0/sqrt(2); T[0,2] = -1.0/sqrt(2) + T[1,0] = 1j/sqrt(2); T[1,2] = 1j/sqrt(2) + T[2,1] = 1.0 + elif l == 2: + if convention == 'wien2k': + cubic_names = ("z^2","x^2-y^2","xy","yz","xz") + T[0,2] = 1.0 + T[1,0] = 1.0/sqrt(2); T[1,4] = 1.0/sqrt(2) + T[2,0] = -1j/sqrt(2); T[2,4] = 1j/sqrt(2) + T[3,1] = 1j/sqrt(2); T[3,3] = -1j/sqrt(2) + T[4,1] = 1.0/sqrt(2); T[4,3] = 1.0/sqrt(2) + else: + cubic_names = ("xy","yz","z^2","xz","x^2-y^2") + T[0,0] = 1j/sqrt(2); T[0,4] = -1j/sqrt(2) + T[1,1] = 1j/sqrt(2); T[1,3] = 1j/sqrt(2) + T[2,2] = 1.0 + T[3,1] = 1.0/sqrt(2); T[3,3] = -1.0/sqrt(2) + T[4,0] = 1.0/sqrt(2); T[4,4] = 1.0/sqrt(2) + elif l == 3: + if convention == 'wien2k': + cubic_names = ("x(x^2-3y^2)","z(x^2-y^2)","xz^2","z^3","yz^2","xyz","y(3x^2-y^2)") + T[0,0] = 1.0/sqrt(2); T[0,6] = -1.0/sqrt(2) + T[1,1] = 1.0/sqrt(2); T[1,5] = 1.0/sqrt(2) + T[2,2] = 1.0/sqrt(2); T[2,4] = -1.0/sqrt(2) + T[3,5] = 1.0 + T[4,2] = 1j/sqrt(2); T[4,4] = 1j/sqrt(2) + T[5,1] = 1j/sqrt(2); T[5,5] = -1j/sqrt(2) + T[6,0] = 1j/sqrt(2); T[6,6] = 1j/sqrt(2) + else: + cubic_names = ("y(3x^2-y^2)","xyz","yz^2","z^3","xz^2","z(x^2-y^2)","x(x^2-3y^2)") +# Verified with the matrix generated in VASP + T[0,0] = 1j/sqrt(2); T[0,6] = 1j/sqrt(2) + T[1,1] = 1j/sqrt(2); T[1,5] = -1j/sqrt(2) + T[2,2] = 1j/sqrt(2); T[2,4] = 1j/sqrt(2) + T[3,3] = 1.0 + T[4,2] = 1.0/sqrt(2); T[4,4] = -1.0/sqrt(2) + T[5,1] = 1.0/sqrt(2); T[5,5] = 1.0/sqrt(2) + T[6,0] = 1.0/sqrt(2); T[6,6] = -1.0/sqrt(2) + else: raise ValueError("spherical_to_cubic: implemented only for l=0,1,2,3") + + return T + +# Names of cubic harmonics +def cubic_names(l): + if l == 0 or l == 's': + return ("s") + elif l == 1 or l == 'p': + return ("x","y","z") + elif l == 2 or l == 'd': + return ("xy","yz","z^2","xz","x^2-y^2") + elif l == 't2g': + return ("xy","yz","xz") + elif l == 'eg': + return ("z^2","x^2-y^2") + elif l == 3 or l == 'f': + return ("x(x^2-3y^2)","z(x^2-y^2)","xz^2","z^3","yz^2","xyz","y(3x^2-y^2)") + else: raise ValueError("cubic_names: implemented only for l=0,1,2,3") + +# Convert U,J -> radial integrals F_k +def U_J_to_radial_integrals(l, U_int, J_hund): + """Determines the radial integrals F_k from U_int and J_hund.""" + + F = np.zeros((l+1),dtype=float) + if l == 2: + F[0] = U_int + F[1] = J_hund * 14.0 / (1.0 + 0.63) + F[2] = 0.630 * F[1] + elif l == 3: + F[0] = U_int + F[1] = 6435.0 * J_hund / (286.0 + 195.0 * 451.0 / 675.0 + 250.0 * 1001.0 / 2025.0) + F[2] = 451.0 * F[1] / 675.0 + F[3] = 1001.0 * F[1] / 2025.0 + else: raise ValueError("U_J_to_radial_integrals: implemented only for l=2,3") + + return F + +# Convert radial integrals F_k -> U,J +def radial_integrals_to_U_J(l, F): + """Determines U_int and J_hund from the radial integrals.""" + + if l == 2: + U_int = F[0] + J_hund = F[1] * (1.0 + 0.63) / 14.0 + elif l == 3: + U_int = F[0] + J_hund = F[1] * (286.0 + 195.0 * 451.0 / 675.0 + 250.0 * 1001.0 / 2025.0) / 6435.0 + else: raise ValueError("radial_integrals_to_U_J: implemented only for l=2,3") + + return U_int,J_hund + +# Angular matrix elements of particle-particle interaction +# (2l+1)^2 ((l 0) (k 0) (l 0))^2 \sum_{q=-k}^{k} (-1)^{m1+m2+q} ((l -m1) (k q) (l m3)) ((l -m2) (k -q) (l m4)) +def angular_matrix_element(l, k, m1, m2, m3, m4): + result = 0 + for q in range(-k,k+1): + result += three_j_symbol((l,-m1),(k,q),(l,m3))*three_j_symbol((l,-m2),(k,-q),(l,m4))*(-1.0 if (m1+q+m2) % 2 else 1.0) + result *= (2*l+1)**2 * (three_j_symbol((l,0),(k,0),(l,0))**2) + return result + +# Wigner 3-j symbols +# ((j1 m1) (j2 m2) (j3 m3)) +def three_j_symbol(jm1, jm2, jm3): + j1, m1 = jm1 + j2, m2 = jm2 + j3, m3 = jm3 + + if (m1+m2+m3 != 0 or + m1 < -j1 or m1 > j1 or + m2 < -j2 or m2 > j2 or + m3 < -j3 or m3 > j3 or + j3 > j1 + j2 or + j3 < abs(j1-j2)): + return .0 + + result = -1.0 if (j1-j2-m3) % 2 else 1.0 + result *= sqrt(fact(j1+j2-j3)*fact(j1-j2+j3)*fact(-j1+j2+j3)/fact(j1+j2+j3+1)) + result *= sqrt(fact(j1-m1)*fact(j1+m1)*fact(j2-m2)*fact(j2+m2)*fact(j3-m3)*fact(j3+m3)) + + t_min = max(j2-j3-m1,j1-j3+m2,0) + t_max = min(j1-m1,j2+m2,j1+j2-j3) + + t_sum = 0 + for t in range(t_min,t_max+1): + t_sum += (-1.0 if t % 2 else 1.0)/(fact(t)*fact(j3-j2+m1+t)*fact(j3-j1-m2+t)*fact(j1+j2-j3-t)*fact(j1-m1-t)*fact(j2+m2-t)) + + result *= t_sum + return result + +# Clebsch-Gordan coefficients +# < j1 m1 j2 m2 | j3 m3 > = (-1)^{j1-j2+m3} \sqrt{2j3+1} ((j1 m1) (j2 m2) (j3 -m3)) +def clebsch_gordan(jm1, jm2, jm3): + norm = sqrt(2*jm3[0]+1)*(-1 if jm1[0]-jm2[0]+jm3[1] % 2 else 1) + return norm*three_j_symbol(jm1,jm2,(jm3[0],-jm3[1])) + +# Create subarray containing columns in idxlist +# e.g. idxlist = [(0),(2,3),(0,1,2,3)] gives +# column 0 for 1st dim, +# columns 2 and 3 for 2nd dim, +# columns 0,1,2 and 3 for 3rd dim. +def subarray(a,idxlist,n=None) : + if n is None: n = len(a.shape)-1 + sa = a[tuple(slice(x) for x in a.shape[:n]) + (idxlist[n],)] + return subarray(sa,idxlist, n-1) if n > 0 else sa diff --git a/python/converters/plovasp/examples/ce/hf_solver.py b/python/converters/plovasp/examples/ce/hf_solver.py new file mode 100644 index 00000000..41a96c02 --- /dev/null +++ b/python/converters/plovasp/examples/ce/hf_solver.py @@ -0,0 +1,335 @@ + +################################################################################ +# +# TRIQS: a Toolbox for Research in Interacting Quantum Systems +# +# Copyright (C) 2011 by M. Ferrero, O. Parcollet +# +# TRIQS is free software: you can redistribute it and/or modify it under the +# terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY +# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# TRIQS. If not, see . +# +################################################################################ + +from types import * +#from pytriqs.applications.dft.U_matrix import * +from U_matrix import * +from pytriqs.gf.local import * +#from hubbard_I import gf_hi_fullu, sigma_atomic_fullu +import pytriqs.utility.mpi as mpi +from itertools import izip +import numpy +import copy + +class Solver: + """ + Hartree-Fock Solver + """ + + # initialisation: + def __init__(self, beta, l, n_msb=1025, use_spin_orbit=False, Nmoments=5, dudarev=False): + + self.name = "Hartree-Fock" + self.beta = beta + self.l = l + self.Nmsb = n_msb + self.UseSpinOrbit = use_spin_orbit + self.Converged = False + self.Nspin = 2 + self.Nmoments=Nmoments + + self.dudarev = dudarev + + assert use_spin_orbit == False, "Spin-orbit is not implemented" + + self.Nlm = 2*l+1 + if (use_spin_orbit): + # no blocks! + self.gf_struct = [ ('ud', range(2*self.Nlm)) ] + else: + # up/down blocks: + self.gf_struct = [ ('up', range(self.Nlm)), ('down', range(self.Nlm)) ] + + # construct Greens functions: + self.a_list = [a for a,al in self.gf_struct] + glist = lambda : [ GfImFreq(indices = al, beta = self.beta, n_points = self.Nmsb) for a,al in self.gf_struct] + self.G = BlockGf(name_list = self.a_list, block_list = glist(),make_copies=False) + self.G_Old = self.G.copy() + self.G0 = self.G.copy() + self.Sigma = self.G.copy() + self.Sigma_Old = self.G.copy() + + + + def solve(self, U_int, J_hund, T=None, verbosity=0, Iteration_Number=1, Test_Convergence=0.0001): + """Calculation of the impurity Greens function using Hubbard-I""" + + if self.Converged : + mpi.report("Solver %(name)s has already converged: SKIPPING"%self.__dict__) + return + + if mpi.is_master_node(): + self.verbosity = verbosity + else: + self.verbosity = 0 + + #self.Nmoments = 5 + + ur,ujmn,umn=self.__set_umatrix(U=U_int,J=J_hund,T=T) + + + M = [x for x in self.G.mesh] + self.zmsb = numpy.array([x for x in M],numpy.complex_) + +# # for the tails: +# tailtempl={} +# for sig,g in self.G: +# tailtempl[sig] = copy.deepcopy(g.tail) +# for i in range(9): tailtempl[sig][i] *= 0.0 + +# self.__save_eal('eal.dat',Iteration_Number) + +# mpi.report( "Starting Fortran solver %(name)s"%self.__dict__) + + self.Sigma_Old <<= self.Sigma + self.G_Old <<= self.G + +# # call the fortran solver: +# temp = 1.0/self.beta +# gf,tail,self.atocc,self.atmag = gf_hi_fullu(e0f=self.ealmat, ur=ur, umn=umn, ujmn=ujmn, +# zmsb=self.zmsb, nmom=self.Nmoments, ns=self.Nspin, temp=temp, verbosity = self.verbosity) + + #self.sig = sigma_atomic_fullu(gf=self.gf,e0f=self.eal,zmsb=self.zmsb,ns=self.Nspin,nlm=self.Nlm) + def print_matrix(m): + for row in m: + print ''.join(map("{0:12.7f}".format, row)) + + +# Hartree-Fock solver + self.Sigma.zero() + dm = self.G.density() + if mpi.is_master_node(): +# print +# print " Reduced U-matrix:" +# print " U:" +# print_matrix(ujmn) +# print " Up:" +# print_matrix(umn) +# +## sig_test = {bl: numpy.zeros((self.Nlm, self.Nlm)) for bl in dm} +# sig_test = {} +# sig_test['up'] = numpy.dot(umn, dm['up'].real) + numpy.dot(ujmn, dm['down'].real) +# sig_test['down'] = numpy.dot(umn, dm['down'].real) + numpy.dot(ujmn, dm['up'].real) +# print " Sigma test:" +# print_matrix(sig_test['up']) + print + print " Density matrix (up):" + print_matrix(dm['up']) + print + print " Density matrix (down):" + print_matrix(dm['down']) + + if self.dudarev: + Ueff = U_int - J_hund + corr_energy = 0.0 + dft_dc = 0.0 + for bl1 in dm: +# (U - J) * (1/2 - n) + self.Sigma[bl1] << Ueff * (0.5 * numpy.identity(self.Nlm) - dm[bl1]) +# 1/2 (U - J) * \sum_{\sig} [\sum_{m} n_{m,m \sig} - \sum_{m1,m2} n_{m1,m2 \sig} n_{m2,m1 \sig}] + corr_energy += 0.5 * Ueff * (dm[bl1].trace() - (dm[bl1]*dm[bl1].conj()).sum()).real +# V[n] * n^{\dagger} + dft_dc += (self.Sigma[bl1](0) * dm[bl1].conj()).sum().real + + else: +# !!!!! +# !!!!! Mind the order of indices in the 4-index matrix! +# !!!!! + for il1 in xrange(self.Nlm): + for il2 in xrange(self.Nlm): + for il3 in xrange(self.Nlm): + for il4 in xrange(self.Nlm): + for bl1 in dm: + for bl2 in dm: + self.Sigma[bl1][il1, il2] += ur[il1, il3, il2, il4] * dm[bl2][il3, il4] + if bl1 == bl2: + self.Sigma[bl1][il1, il2] -= ur[il1, il3, il4, il2] * dm[bl1][il3, il4] + + if mpi.is_master_node() and self.verbosity > 0: + print + print " Sigma (up):" + print_matrix(self.Sigma['up'](0).real) + print + print " Sigma (down):" + print_matrix(self.Sigma['down'](0).real) +# if (self.verbosity==0): +# # No fortran output, so give basic results here +# mpi.report("Atomic occupancy in Hubbard I Solver : %s"%self.atocc) +# mpi.report("Atomic magn. mom. in Hubbard I Solver : %s"%self.atmag) + + # transfer the data to the GF class: + if (self.UseSpinOrbit): + nlmtot = self.Nlm*2 # only one block in this case! + else: + nlmtot = self.Nlm + +# M={} +# isp=-1 +# for a,al in self.gf_struct: +# isp+=1 +# M[a] = numpy.array(gf[isp*nlmtot:(isp+1)*nlmtot,isp*nlmtot:(isp+1)*nlmtot,:]).transpose(2,0,1).copy() +# for i in range(min(self.Nmoments,8)): +# tailtempl[a][i+1] = tail[i][isp*nlmtot:(isp+1)*nlmtot,isp*nlmtot:(isp+1)*nlmtot] +# +# #glist = lambda : [ GfImFreq(indices = al, beta = self.beta, n_points = self.Nmsb, data =M[a], tail =self.tailtempl[a]) +# # for a,al in self.gf_struct] +# glist = lambda : [ GfImFreq(indices = al, beta = self.beta, n_points = self.Nmsb) for a,al in self.gf_struct] +# self.G = BlockGf(name_list = self.a_list, block_list = glist(),make_copies=False) +# +# self.__copy_Gf(self.G,M,tailtempl) +# +# # Self energy: +# self.G0 <<= iOmega_n +# +# M = [ self.ealmat[isp*nlmtot:(isp+1)*nlmtot,isp*nlmtot:(isp+1)*nlmtot] for isp in range((2*self.Nlm)/nlmtot) ] +# self.G0 -= M +# self.Sigma <<= self.G0 - inverse(self.G) +# +# # invert G0 +# self.G0.invert() + + def test_distance(G1,G2, dist) : + def f(G1,G2) : + #print abs(G1.data - G2.data) + dS = max(abs(G1.data - G2.data).flatten()) + aS = max(abs(G1.data).flatten()) + if mpi.is_master_node(): + print " Distances:", dS, " vs ", aS * dist + return dS <= aS*dist + return reduce(lambda x,y : x and y, [f(g1,g2) for (i1,g1),(i2,g2) in izip(G1,G2)]) + + mpi.report("\nChecking Sigma for convergence...\nUsing tolerance %s"%Test_Convergence) + self.Converged = test_distance(self.Sigma,self.Sigma_Old,Test_Convergence) + + if self.Converged : + mpi.report("Solver HAS CONVERGED") + else : + mpi.report("Solver has not yet converged") + + return corr_energy, dft_dc + + + def GF_realomega(self, ommin, ommax, N_om, U_int, J_hund, T=None, verbosity=0, broadening=0.01): + """Calculates the GF and spectral function on the real axis.""" + + delta_om = (ommax-ommin)/(1.0*(N_om-1)) + + omega = numpy.zeros([N_om],numpy.complex_) + + ur,umn,ujmn=self.__set_umatrix(U=U_int,J=J_hund,T=T) + + for i in range(N_om): + omega[i] = ommin + delta_om * i + 1j * broadening + + tailtempl={} + for sig,g in self.G: + tailtempl[sig] = copy.deepcopy(g.tail) + for i in range(9): tailtempl[sig][i] *= 0.0 + + temp = 1.0/self.beta + gf,tail,self.atocc,self.atmag = gf_hi_fullu(e0f=self.ealmat, ur=ur, umn=umn, ujmn=ujmn, + zmsb=omega, nmom=self.Nmoments, ns=self.Nspin, temp=temp, verbosity = verbosity) + + # transfer the data to the GF class: + if (self.UseSpinOrbit): + nlmtot = self.Nlm*2 # only one block in this case! + else: + nlmtot = self.Nlm + + M={} + isp=-1 + for a,al in self.gf_struct: + isp+=1 + M[a] = numpy.array(gf[isp*nlmtot:(isp+1)*nlmtot,isp*nlmtot:(isp+1)*nlmtot,:]).transpose(2,0,1).copy() + for i in range(min(self.Nmoments,8)): + tailtempl[a][i+1] = tail[i][isp*nlmtot:(isp+1)*nlmtot,isp*nlmtot:(isp+1)*nlmtot] + + #glist = lambda : [ GfReFreq(indices = al, window = (ommin, ommax), n_points = N_om, data = M[a], tail = self.tailtempl[a]) + # for a,al in self.gf_struct] # Indices for the upfolded G + glist = lambda : [ GfReFreq(indices = al, window = (ommin, ommax), n_points = N_om) for a,al in self.gf_struct] + self.G = BlockGf(name_list = self.a_list, block_list = glist(),make_copies=False) + + self.__copy_Gf(self.G,M,tailtempl) + + # Self energy: + self.G0 = self.G.copy() + self.Sigma = self.G.copy() + self.G0 <<= Omega + 1j*broadening + + M = [ self.ealmat[isp*nlmtot:(isp+1)*nlmtot,isp*nlmtot:(isp+1)*nlmtot] for isp in range((2*self.Nlm)/nlmtot) ] + self.G0 -= M + self.Sigma <<= self.G0 - inverse(self.G) + self.Sigma.note='ReFreq' # This is important for the put_Sigma routine!!! + + #sigmamat = sigma_atomic_fullu(gf=gf,e0f=self.ealmat,zmsb=omega,nlm=self.Nlm,ns=self.Nspin) + + #return omega,gf,sigmamat + + + def __save_eal(self,Filename,it): + f=open(Filename,'a') + f.write('\neff. atomic levels, Iteration %s\n'%it) + for i in range(self.Nlm*self.Nspin): + for j in range(self.Nlm*self.Nspin): + f.write("%10.6f %10.6f "%(self.ealmat[i,j].real,self.ealmat[i,j].imag)) + f.write("\n") + f.close() + + def __copy_Gf(self,G,data,tail): + """ Copies data and tail to Gf object GF """ + for s,g in G: + g.data[:,:,:]=data[s][:,:,:] + for imom in range(1,min(self.Nmoments,8)): + g.tail.data[1+imom,:,:]=tail[s][imom] + + + def set_atomic_levels(self,eal): + """ Helps to set correctly the variables for the atomic levels from a dictionary.""" + + assert (type(eal)==DictType), "Give a dictionary to set_atomic_levels!" + + cnt = 0 + self.ealmat[:,:] *= 0.0 + + for ind in eal: + self.Eff_Atomic_Levels[ind] = copy.deepcopy(eal[ind]) + + if self.UseSpinOrbit: + for ii in range(self.Nlm*2): + for jj in range(self.Nlm*2): + self.ealmat[ii,jj] = self.Eff_Atomic_Levels[ind][ii,jj] + else: + for ii in range(self.Nlm): + for jj in range(self.Nlm): + self.ealmat[cnt*self.Nlm + ii,cnt*self.Nlm + jj] = self.Eff_Atomic_Levels[ind][ii,jj] + + cnt += 1 + + + def __set_umatrix(self,U,J,T=None): + # U matrix: + # l = (Nlm-1)/2 + # If T is specified, it is used to transform the Basis set + Umat = U_matrix(l=self.l, U_int=U, J_hund=J, basis='cubic', T=T) + U, Up = reduce_4index_to_2index(Umat) + + return Umat, U, Up diff --git a/python/converters/plovasp/examples/ce/plo.cfg b/python/converters/plovasp/examples/ce/plo.cfg new file mode 100644 index 00000000..07cba87f --- /dev/null +++ b/python/converters/plovasp/examples/ce/plo.cfg @@ -0,0 +1,15 @@ +[General] +#EFERMI = +#BASENAME = plo_vasp +#DOSMESH = -5.0 10.0 4001 + +[Group 1] +SHELLS = 1 +NORMALIZE = False +EWINDOW = -41.45 41.8 + +[Shell 1] +LSHELL = 3 +IONS = 1 + + diff --git a/python/converters/plovasp/examples/ce/run_build.sh b/python/converters/plovasp/examples/ce/run_build.sh new file mode 100755 index 00000000..90449af8 --- /dev/null +++ b/python/converters/plovasp/examples/ce/run_build.sh @@ -0,0 +1,2 @@ +#!/bin/bash +PYTHONPATH=$HOME/Codes/triqs/triqs1.2/applications/dft_tools/dev_src/python:$HOME/Codes/triqs/triqs1.2/applications/dft_tools/dev_src/c:$PYTHONPATH pytriqs $@ diff --git a/python/converters/plovasp/examples/ce/run_plovasp.sh b/python/converters/plovasp/examples/ce/run_plovasp.sh new file mode 100755 index 00000000..e35a6bbb --- /dev/null +++ b/python/converters/plovasp/examples/ce/run_plovasp.sh @@ -0,0 +1,2 @@ +PLOVASP_PATH=$HOME/Codes/triqs/triqs1.2/applications/dft_tools/dev_src +PYTHONPATH=$PLOVASP_PATH/python:$PLOVASP_PATH/c:$PYTHONPATH pytriqs $PLOVASP_PATH/python/converters/plovasp/main.py $@ diff --git a/python/converters/plovasp/examples/ce/sc_dmft.py b/python/converters/plovasp/examples/ce/sc_dmft.py new file mode 100644 index 00000000..67ab5727 --- /dev/null +++ b/python/converters/plovasp/examples/ce/sc_dmft.py @@ -0,0 +1,164 @@ + +import os +import errno +import signal +import sys +import time +import pytriqs.utility.mpi as mpi +import converters.plovasp.main as plovasp +from test_ham_hf import dmft_cycle + +debug = True +# +# Helper functions +# +def sigint_handler(signal, frame): + raise SystemExit(1) + +def is_vasp_lock_present(): + return os.path.isfile('./vasp.lock') + +def is_vasp_running(vasp_pid): + """ + Tests if VASP initial process is still alive. + """ + pid_exists = False + if mpi.is_master_node(): + try: + os.kill(vasp_pid, 0) + except OSError, e: + pid_exists = e.errno == errno.EPERM + else: + pid_exists = True + + pid_exists = mpi.bcast(pid_exists) + return pid_exists + +def get_dft_energy(): + """ + Reads energy from the last line of OSZICAR. + """ + with open('OSZICAR', 'r') as f: + nextline = f.readline() + while nextline.strip(): + line = nextline + nextline = f.readline() +# print "OSZICAR: ", line[:-1] + + try: + dft_energy = float(line.split()[2]) + except ValueError: + print "Cannot read energy from OSZICAR, setting it to zero" + dft_energy = 0.0 + + return dft_energy + +class bcolors: + MAGENTA = '\033[95m' + BLUE = '\033[94m' + GREEN = '\033[92m' + YELLOW = '\033[93m' + RED = '\033[91m' + ENDC = '\033[0m' +# +# Main self-consistent cycle +# +def run_all(vasp_pid): + """ + """ + mpi.report(" Waiting for VASP lock to appear...") + while not is_vasp_lock_present(): + time.sleep(1) + + vasp_running = True + + while vasp_running: + if debug: print bcolors.RED + "rank %s"%(mpi.rank) + bcolors.ENDC + mpi.report(" Waiting for VASP lock to disappear...") + mpi.barrier() + while is_vasp_lock_present(): + time.sleep(1) +# if debug: print bcolors.YELLOW + " waiting: rank %s"%(mpi.rank) + bcolors.ENDC + if not is_vasp_running(vasp_pid): + mpi.report(" VASP stopped") + vasp_running = False + break + + if debug: print bcolors.MAGENTA + "rank %s"%(mpi.rank) + bcolors.ENDC + err = 0 + exc = None + try: + if debug: print bcolors.BLUE + "plovasp: rank %s"%(mpi.rank) + bcolors.ENDC + if mpi.is_master_node(): + plovasp.generate_and_output_as_text('plo.cfg', vasp_dir='./') +# Read energy from OSZICAR + dft_energy = get_dft_energy() + except Exception, exc: + err = 1 + + err = mpi.bcast(err) + if err: + if mpi.is_master_node(): + raise exc + else: + raise SystemExit(1) + + mpi.barrier() + + try: + if debug: print bcolors.GREEN + "rank %s"%(mpi.rank) + bcolors.ENDC + corr_energy, dft_dc = dmft_cycle() + except: + if mpi.is_master_node(): + print " master forwarding the exception..." + raise + else: + print " rank %i exiting..."%(mpi.rank) + raise SystemExit(1) + mpi.barrier() + + if mpi.is_master_node(): + total_energy = dft_energy + corr_energy - dft_dc + print + print "="*80 + print " Total energy: ", total_energy + print " DFT energy: ", dft_energy + print " Corr. energy: ", corr_energy + print " DFT DC: ", dft_dc + print "="*80 + print + + if mpi.is_master_node() and vasp_running: + open('./vasp.lock', 'a').close() + + if mpi.is_master_node(): + total_energy = dft_energy + corr_energy - dft_dc + with open('TOTENERGY', 'w') as f: + f.write(" Total energy: %s\n"%(total_energy)) + f.write(" DFT energy: %s\n"%(dft_energy)) + f.write(" Corr. energy: %s\n"%(corr_energy)) + f.write(" DFT DC: %s\n"%(dft_dc)) + f.write(" Energy correction: %s\n"%(corr_energy - dft_dc)) + + mpi.report("***Done") + + +if __name__ == '__main__': + try: + vasp_pid = int(sys.argv[1]) + except (ValueError, KeyError): + if mpi.is_master_node(): + print "VASP process pid must be provided as the first argument" + raise +# if len(sys.argv) > 1: +# vasp_path = sys.argv[1] +# else: +# try: +# vasp_path = os.environ['VASP_DIR'] +# except KeyError: +# if mpi.is_master_node(): +# print "Path to VASP must be specified either as an argument of in VASP_DIR" +# raise + signal.signal(signal.SIGINT, sigint_handler) + + run_all(vasp_pid) diff --git a/python/converters/plovasp/examples/ce/sc_dmft.sh b/python/converters/plovasp/examples/ce/sc_dmft.sh new file mode 100755 index 00000000..3acce031 --- /dev/null +++ b/python/converters/plovasp/examples/ce/sc_dmft.sh @@ -0,0 +1,9 @@ +#/bin/bash + +NPROC=8 + +rm -f vasp.lock +stdbuf -o 0 mpirun -np $NPROC ~/Codes/vasp/build_20151202/vasp.5.4.2/build/std/vasp & + +mpirun -np $NPROC ./run_build.sh sc_dmft.py $(jobs -p) || kill %1 + diff --git a/python/converters/plovasp/examples/ce/subm.sh b/python/converters/plovasp/examples/ce/subm.sh new file mode 100644 index 00000000..e8dec11c --- /dev/null +++ b/python/converters/plovasp/examples/ce/subm.sh @@ -0,0 +1,28 @@ +#!/bin/bash -l +# +#SBATCH --job-name="JOBNAME" +#SBATCH --time=36:00:00 +##SBATCH --nodes=8 +#SBATCH --ntasks=8 +#SBATCH --partition=qmac +##SBATCH --mem-per-cpu=1024 +#SBATCH --output=job.%j.o +#SBATCH --error=job.%j.e + +#======START===== +# source $HOME/.profile +# export KMP_AFFINITY=none + +# module load slurm +source /cm/shared/apps/intel/composer_xe/composer_xe_2015.0.090/mkl/bin/mklvars.sh intel64 +# module switch PrgEnv-gnu PrgEnv-intel +# module load intel/14.0.2.144 +#module load intel/mkl/64/11.2/2015.0.090 + +export OMP_NUM_THREADS=1 + +VASP_DIR=$HOME/Codes/vasp/build_20151202/vasp.5.4.2/build/std +#mpirun -np $SLURM_NTASKS $VASP_DIR/vasp +./sc_dmft.sh + + diff --git a/python/converters/plovasp/examples/ce/test_ham_hf.py b/python/converters/plovasp/examples/ce/test_ham_hf.py new file mode 100644 index 00000000..903b0c20 --- /dev/null +++ b/python/converters/plovasp/examples/ce/test_ham_hf.py @@ -0,0 +1,444 @@ +#from pytriqs.applications.dft.sumk_dft import * +from sumk_dft import * +#from pytriqs.applications.dft.converters.wien2k_converter import * +from converters.vasp_converter import * +#from pytriqs.applications.impurity_solvers.hubbard_I.hubbard_solver import Solver +from hf_solver import Solver +import shutil + +class TestSumkDFT(SumkDFT): +# calculate and save occupancy matrix in the Bloch basis for VASP charge denity recalculation + def calc_density_correction(self, filename='GAMMA', dm_type='wien2k'): + r""" + Calculates the charge density correction and stores it into a file. + + The charge density correction is needed for charge-self-consistent DFT+DMFT calculations. + It represents a density matrix of the interacting system defined in Bloch basis + and it is calculated from the sum over Matsubara frequecies of the full GF, + + ..math:: N_{\nu\nu'}(k) = \sum_{i\omega_{n}} G_{\nu\nu'}(k, i\omega_{n}) + + The density matrix for every `k`-point is stored into a file. + + Parameters + ---------- + filename : string + Name of the file to store the charge density correction. + + Returns + ------- + (deltaN, dens) : tuple + Returns a tuple containing the density matrix `deltaN` and + the corresponing total charge `dens`. + + """ + assert type(filename) == StringType, "calc_density_correction: filename has to be a string!" + assert dm_type in ('vasp', 'wien2k'), "'type' must be either 'vasp' or 'wienk'" + + ntoi = self.spin_names_to_ind[self.SO] + spn = self.spin_block_names[self.SO] + dens = {sp: 0.0 for sp in spn} + +# Fetch Fermi weights and energy window band indices + if dm_type == 'vasp': + fermi_weights = 0 + band_window = 0 + if mpi.is_master_node(): + ar = HDFArchive(self.hdf_file,'r') + fermi_weights = ar['dft_misc_input']['dft_fermi_weights'] + band_window = ar['dft_misc_input']['band_window'] + del ar + fermi_weights = mpi.bcast(fermi_weights) + band_window = mpi.bcast(band_window) + +# Convert Fermi weights to a density matrix + dens_mat_dft = {} + for sp in spn: + dens_mat_dft[sp] = [fermi_weights[ik, ntoi[sp], :].astype(numpy.complex_) for ik in xrange(self.n_k)] + + # Set up deltaN: + deltaN = {} + for sp in spn: + deltaN[sp] = [numpy.zeros([self.n_orbitals[ik,ntoi[sp]],self.n_orbitals[ik,ntoi[sp]]], numpy.complex_) for ik in range(self.n_k)] + + ikarray = numpy.array(range(self.n_k)) + for ik in mpi.slice_array(ikarray): + G_latt_iw = self.lattice_gf(ik = ik, mu = self.chemical_potential, iw_or_w = "iw") + for bname,gf in G_latt_iw: + deltaN[bname][ik][:, :] = G_latt_iw[bname].density() + dens[bname] += self.bz_weights[ik] * G_latt_iw[bname].total_density() + if dm_type == 'vasp': +# In 'vasp'-mode subtract the DFT density matrix + diag_inds = numpy.diag_indices(self.n_orbitals[ik, ntoi[bname]]) + deltaN[bname][ik][diag_inds] -= dens_mat_dft[bname][ik] + dens[bname] -= self.bz_weights[ik] * dens_mat_dft[bname][ik].sum().real + + # mpi reduce: + for bname in deltaN: + for ik in range(self.n_k): + deltaN[bname][ik] = mpi.all_reduce(mpi.world, deltaN[bname][ik], lambda x,y : x+y) + dens[bname] = mpi.all_reduce(mpi.world, dens[bname], lambda x,y : x+y) + mpi.barrier() + + # now save to file: + if dm_type == 'wien2k': + if mpi.is_master_node(): + if self.SP == 0: + f = open(filename,'w') + else: + f = open(filename+'up','w') + f1 = open(filename+'dn','w') + # write chemical potential (in Rydberg): + f.write("%.14f\n"%(self.chemical_potential/self.energy_unit)) + if self.SP != 0: f1.write("%.14f\n"%(self.chemical_potential/self.energy_unit)) + # write beta in rydberg-1 + f.write("%.14f\n"%(G_latt_iw.mesh.beta*self.energy_unit)) + if self.SP != 0: f1.write("%.14f\n"%(G_latt_iw.mesh.beta*self.energy_unit)) + + if self.SP == 0: # no spin-polarization + + for ik in range(self.n_k): + f.write("%s\n"%self.n_orbitals[ik,0]) + for inu in range(self.n_orbitals[ik,0]): + for imu in range(self.n_orbitals[ik,0]): + valre = (deltaN['up'][ik][inu,imu].real + deltaN['down'][ik][inu,imu].real) / 2.0 + valim = (deltaN['up'][ik][inu,imu].imag + deltaN['down'][ik][inu,imu].imag) / 2.0 + f.write("%.14f %.14f "%(valre,valim)) + f.write("\n") + f.write("\n") + f.close() + + elif self.SP == 1: # with spin-polarization + + # dict of filename: (spin index, block_name) + if self.SO == 0: to_write = {f: (0, 'up'), f1: (1, 'down')} + if self.SO == 1: to_write = {f: (0, 'ud'), f1: (0, 'ud')} + for fout in to_write.iterkeys(): + isp, sp = to_write[fout] + for ik in range(self.n_k): + fout.write("%s\n"%self.n_orbitals[ik,isp]) + for inu in range(self.n_orbitals[ik,isp]): + for imu in range(self.n_orbitals[ik,isp]): + fout.write("%.14f %.14f "%(deltaN[sp][ik][inu,imu].real,deltaN[sp][ik][inu,imu].imag)) + fout.write("\n") + fout.write("\n") + fout.close() + elif dm_type == 'vasp': +# assert self.SP == 0, "Spin-polarized density matrix is not implemented" + + if mpi.is_master_node(): + with open(filename, 'w') as f: + f.write(" %i -1 ! Number of k-points, default number of bands\n"%(self.n_k)) + for sp in spn: + for ik in xrange(self.n_k): + ib1 = band_window[0][ik, 0] + ib2 = band_window[0][ik, 1] + f.write(" %i %i %i\n"%(ik + 1, ib1, ib2)) + for inu in xrange(self.n_orbitals[ik, 0]): + for imu in xrange(self.n_orbitals[ik, 0]): + if self.SP == 0: + valre = (deltaN['up'][ik][inu, imu].real + deltaN['down'][ik][inu, imu].real) / 2.0 + valim = (deltaN['up'][ik][inu, imu].imag + deltaN['down'][ik][inu, imu].imag) / 2.0 + else: + valre = deltaN[sp][ik][inu, imu].real + valim = deltaN[sp][ik][inu, imu].imag + + f.write(" %.14f %.14f"%(valre, valim)) + f.write("\n") + else: + raise NotImplementedError("Unknown density matrix type: '%s'"%(dm_type)) + + return deltaN, dens + + def calc_hamiltonian_correction(self, filename='GAMMA'): + r""" + Calculates the charge density correction and stores it into a file. + + The charge density correction is needed for charge-self-consistent DFT+DMFT calculations. + It represents a density matrix of the interacting system defined in Bloch basis + and it is calculated from the sum over Matsubara frequecies of the full GF, + + ..math:: N_{\nu\nu'}(k) = \sum_{i\omega_{n}} G_{\nu\nu'}(k, i\omega_{n}) + + The density matrix for every `k`-point is stored into a file. + + Parameters + ---------- + filename : string + Name of the file to store the charge density correction. + + Returns + ------- + (deltaN, dens) : tuple + Returns a tuple containing the density matrix `deltaN` and + the corresponing total charge `dens`. + + """ + assert type(filename) == StringType, "calc_density_correction: filename has to be a string!" + + ntoi = self.spin_names_to_ind[self.SO] + spn = self.spin_block_names[self.SO] + dens = {sp: 0.0 for sp in spn} + +# Fetch Fermi weights and energy window band indices + fermi_weights = 0 + band_window = 0 + if mpi.is_master_node(): + ar = HDFArchive(self.hdf_file,'r') + fermi_weights = ar['dft_misc_input']['dft_fermi_weights'] + band_window = ar['dft_misc_input']['band_window'] + del ar + fermi_weights = mpi.bcast(fermi_weights) + band_window = mpi.bcast(band_window) + + # Set up deltaH: + deltaH = {} + for sp in spn: + deltaH[sp] = [numpy.zeros([self.n_orbitals[ik,ntoi[sp]],self.n_orbitals[ik,ntoi[sp]]], numpy.complex_) for ik in range(self.n_k)] + + ikarray = numpy.array(range(self.n_k)) + for ik in mpi.slice_array(ikarray): + sigma_minus_dc = [s.copy() for s in self.Sigma_imp_iw] + sigma_minus_dc = self.add_dc('iw') + + beta = self.Sigma_imp_iw[0].mesh.beta # override beta if Sigma_iw is present + n_iw = len(self.Sigma_imp_iw[0].mesh) + + block_structure = [ range(self.n_orbitals[ik,ntoi[sp]]) for sp in spn ] + gf_struct = [ (spn[isp], block_structure[isp]) for isp in range(self.n_spin_blocks[self.SO]) ] + block_ind_list = [block for block,inner in gf_struct] + glist = lambda : [ GfImFreq(indices=inner,beta=beta,n_points=n_iw) for block,inner in gf_struct] + G_latt = BlockGf(name_list = block_ind_list, block_list = glist(), make_copies = False) + G_latt.zero() + + for icrsh in range(self.n_corr_shells): + for bname, gf in G_latt: + gf += self.upfold(ik,icrsh,bname,sigma_minus_dc[icrsh][bname],gf) + + for sp in spn: + deltaH[sp][ik][:, :] = G_latt[sp](0) # Any Matsubara frequency will do +# G_latt_iw = self.lattice_gf(ik = ik, mu = self.chemical_potential, iw_or_w = "iw") +# for bname,gf in G_latt_iw: +# deltaN[bname][ik][:, :] = G_latt_iw[bname].density() +# dens[bname] += self.bz_weights[ik] * G_latt_iw[bname].total_density() +# if dm_type == 'vasp': +## In 'vasp'-mode subtract the DFT density matrix +# diag_inds = numpy.diag_indices(self.n_orbitals[ik, ntoi[bname]]) +# deltaN[bname][ik][diag_inds] -= dens_mat_dft[bname][ik] +# dens[bname] -= self.bz_weights[ik] * dens_mat_dft[bname][ik].sum().real + + # mpi reduce: + for bname in deltaH: + for ik in range(self.n_k): + deltaH[bname][ik] = mpi.all_reduce(mpi.world, deltaH[bname][ik], lambda x,y : x+y) + mpi.barrier() + + # now save to file: + if mpi.is_master_node(): + with open(filename, 'w') as f: + f.write("H %i -1 ! Number of k-points, default number of bands\n"%(self.n_k)) + for sp in spn: + for ik in xrange(self.n_k): + ib1 = band_window[0][ik, 0] + ib2 = band_window[0][ik, 1] + f.write(" %i %i %i\n"%(ik + 1, ib1, ib2)) + for inu in xrange(self.n_orbitals[ik, 0]): + for imu in xrange(self.n_orbitals[ik, 0]): + if self.SP == 0: + valre = (deltaH['up'][ik][inu, imu].real + deltaH['down'][ik][inu, imu].real) / 2.0 + valim = (deltaH['up'][ik][inu, imu].imag + deltaH['down'][ik][inu, imu].imag) / 2.0 + else: + valre = deltaH[sp][ik][inu, imu].real + valim = deltaH[sp][ik][inu, imu].imag + + f.write(" %.14f %.14f"%(valre, valim)) + f.write("\n") + return deltaH + +def dmft_cycle(): + lda_filename = 'vasp' + beta = 400 + U_int = 4.00 + J_hund = 0.70 + Loops = 1 # Number of DMFT sc-loops + Mix = 1.0 # Mixing factor in QMC + DC_type = 0 # 0...FLL, 1...Held, 2... AMF, 3...Lichtenstein + DC_Mix = 1.0 # 1.0 ... all from imp; 0.0 ... all from Gloc + useBlocs = False # use bloc structure from LDA input + useMatrix = True # use the U matrix calculated from Slater coefficients instead of (U+2J, U, U-J) + chemical_potential_init=-0.0 # initial chemical potential + + use_dudarev = True + + HDFfilename = lda_filename+'.h5' + +# Convert DMFT input: +# Can be commented after the first run + Converter = VaspConverter(filename=lda_filename) + Converter.convert_dft_input() + +#check if there are previous runs: + previous_runs = 0 + previous_present = False + + if mpi.is_master_node(): + ar = HDFArchive(HDFfilename,'a') + if 'iterations' in ar: + previous_present = True + previous_runs = ar['iterations'] + else: + previous_runs = 0 + previous_present = False + del ar + + mpi.barrier() + previous_runs = mpi.bcast(previous_runs) + previous_present = mpi.bcast(previous_present) + +# Init the SumK class +#SK=SumkDFT(hdf_file=lda_filename+'.h5',use_dft_blocks=False) + SK=TestSumkDFT(hdf_file=lda_filename+'.h5',use_dft_blocks=False) + + Norb = SK.corr_shells[0]['dim'] + l = SK.corr_shells[0]['l'] + +# Init the Hubbard-I solver: + S = Solver(beta = beta, l = l, dudarev=use_dudarev) + +# DEBUG +#SK.put_Sigma(Sigma_imp=[S.Sigma]) +#dH = SK.calc_hamiltonian_correction(filename='GAMMA') +# END DEBUG + + chemical_potential=chemical_potential_init +# load previous data: old self-energy, chemical potential, DC correction + if (previous_present): + mpi.report("Using stored data for initialisation") + if (mpi.is_master_node()): + ar = HDFArchive(HDFfilename,'a') + S.Sigma <<= ar['SigmaF'] + del ar + things_to_load=['chemical_potential','dc_imp'] + old_data=SK.load(things_to_load) + chemical_potential=old_data[0] + SK.dc_imp=old_data[1] + S.Sigma = mpi.bcast(S.Sigma) + chemical_potential=mpi.bcast(chemical_potential) + SK.dc_imp=mpi.bcast(SK.dc_imp) + + +# DMFT loop: + for Iteration_Number in range(1,Loops+1): + + itn = Iteration_Number + previous_runs + + # put Sigma into the SumK class: + S.Sigma.zero() # !!!! + SK.put_Sigma(Sigma_imp = [ S.Sigma ]) + + # Compute the SumK, possibly fixing mu by dichotomy + if SK.density_required and (Iteration_Number > 1): + chemical_potential = SK.calc_mu( precision = 0.001 ) + else: + mpi.report("No adjustment of chemical potential\nTotal density = %.3f"%SK.total_density(mu=chemical_potential)) + + # Density: + S.G <<= SK.extract_G_loc()[0] + mpi.report("Total charge of Gloc : %.6f"%S.G.total_density()) + + # calculated DC at the first run to have reasonable initial non-interacting atomic level positions + if ((Iteration_Number==1)and(previous_present==False)): + if use_dudarev: + dc_value_init = 0.0 + else: + dc_value_init=U_int/2.0 + dm=S.G.density() + SK.calc_dc( dm, U_interact = U_int, J_hund = J_hund, orb = 0, use_dc_formula = DC_type, use_dc_value=dc_value_init) + + # calculate non-interacting atomic level positions: +# eal = SK.eff_atomic_levels()[0] +# S.set_atomic_levels( eal = eal ) + + # solve it: + corr_energy, dft_dc = S.solve(U_int = U_int, J_hund = J_hund, verbosity = 1) + + # Now mix Sigma and G: + if ((itn>1)or(previous_present)): + if (mpi.is_master_node()and (Mix<1.0)): + ar = HDFArchive(HDFfilename,'r') + mpi.report("Mixing Sigma and G with factor %s"%Mix) + if ('SigmaF' in ar): + S.Sigma <<= Mix * S.Sigma + (1.0-Mix) * ar['SigmaF'] + if ('GF' in ar): + S.G <<= Mix * S.G + (1.0-Mix) * ar['GF'] + del ar + S.G = mpi.bcast(S.G) + S.Sigma = mpi.bcast(S.Sigma) + + # after the Solver has finished, set new double counting: +# dm = S.G.density() +# if not use_dudarev: +# SK.calc_dc( dm, U_interact = U_int, J_hund = J_hund, orb = 0, use_dc_formula = DC_type ) + + # correlation energy calculations: + correnerg = 0.5 * (S.G * S.Sigma).total_density() + mpi.report("Corr. energy = %s"%correnerg) + + # store the impurity self-energy, GF as well as correlation energy in h5 + if (mpi.is_master_node()): + ar = HDFArchive(HDFfilename,'a') + ar['iterations'] = itn + ar['chemical_cotential%s'%itn] = chemical_potential + ar['SigmaF'] = S.Sigma + ar['GF'] = S.G + ar['correnerg%s'%itn] = correnerg + ar['DCenerg%s'%itn] = SK.dc_energ + del ar + + #Save essential SumkDFT data: + things_to_save=['chemical_potential','dc_energ','dc_imp'] + SK.save(things_to_save) + + # print out occupancy matrix of Ce 4f +# mpi.report("Orbital densities of impurity Green function:") +# for s in dm: +# mpi.report("Block %s: "%s) +# for ii in range(len(dm[s])): +# str = '' +# for jj in range(len(dm[s])): +# if (dm[s][ii,jj].real>0): +# str += " %.4f"%(dm[s][ii,jj].real) +# else: +# str += " %.4f"%(dm[s][ii,jj].real) +# mpi.report(str) + mpi.report("Total charge of impurity problem : %.6f"%S.G.total_density()) + + +# find exact chemical potential +#if (SK.density_required): +# SK.chemical_potential = SK.calc_mu( precision = 0.000001 ) +# SK.chemical_potential = SK.calc_mu( precision = 0.01 ) + +#dN, d = SK.calc_density_correction(filename='GAMMA', dm_type='vasp') +#mpi.report("Trace of Density Matrix: %s"%d) + mpi.report("Storing Hamiltonian correction GAMMA...") + SK.put_Sigma(Sigma_imp=[S.Sigma]) + dH = SK.calc_hamiltonian_correction(filename='GAMMA') +# shutil.copyfile('GAMMA', 'it%i.GAMMA'%(itn)) + +# store correlation energy contribution to be read by Wien2ki and then included to DFT+DMFT total energy + if (mpi.is_master_node()): + ar = HDFArchive(HDFfilename) + itn = ar['iterations'] + correnerg = ar['correnerg%s'%itn] + DCenerg = ar['DCenerg%s'%itn] + del ar + correnerg -= DCenerg[0] + f=open(lda_filename+'.qdmft','a') + f.write("%.16f\n"%correnerg) + f.close() + + return corr_energy, dft_dc + +if __name__ == '__main__': + dmft_cycle()