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started working on converter
This commit is contained in:
Kevin Gasperich
parent
df2295206f
commit
f9ec0e9cff
63
src/utils_periodic/Gen_Ezfio_from_integral_complex_3idx.sh
Executable file
63
src/utils_periodic/Gen_Ezfio_from_integral_complex_3idx.sh
Executable file
@ -0,0 +1,63 @@
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#!/bin/bash
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ezfio=$1
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# Create the integral
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echo 'Create Integral'
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echo 'Create EZFIO'
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read nel nmo natom <<< $(cat param)
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read e_nucl <<< $(cat e_nuc)
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read nao <<< $(cat num_ao)
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read nkpts <<< $(cat num_kpts)
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read ndf <<< $(cat num_df)
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#./create_ezfio_complex_4idx.py $ezfio $nel $natom $nmo $e_nucl $nao $nkpts
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./create_ezfio_complex_3idx.py $ezfio $nel $natom $nmo $e_nucl $nao $nkpts $ndf
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#Handle the orbital consitensy check
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qp_edit -c $ezfio &> /dev/null
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cp $ezfio/{ao,mo}_basis/ao_md5
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#Read the integral
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echo 'Read Integral'
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################################################
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## using AO mono, 4-idx from pyscf ##
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################################################
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qp_run import_integrals_ao_periodic $ezfio
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################################################
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## using AO mono, 3-idx, mo coef from pyscf ##
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################################################
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#qp_run read_ao_mono_complex $ezfio
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#qp_run read_kconserv $ezfio
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#qp_run read_ao_df_complex $ezfio
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#qp_run read_mo_coef_complex $ezfio #start from converged pyscf MOs
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#
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#qp_run save_mo_df_to_disk $ezfio
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#qp_run save_mo_bielec_to_disk $ezfio
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#qp_run mo_from_ao_orth $ezfio #use canonical orthonormalized AOs as initial MO guess
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#qp_run print_H_matrix_restart $ezfio > hmat.out
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###############################################################
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## using AO mono, full 4-idx AO bielec, mo coef from pyscf ##
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###############################################################
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#qp_run read_ao_mono_complex $ezfio
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#qp_run read_kconserv $ezfio
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#qp_run read_ao_eri_chunk_complex $ezfio
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#qp_run read_mo_coef_complex $ezfio #start from converged pyscf MOs
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##qp_run mo_from_ao_orth $ezfio #use canonical orthonormalized AOs as initial MO guess
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######################################################
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## using MO mono, full 4-idx MO bielec from pyscf ##
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######################################################
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#qp_run read_mo_mono_complex $ezfio
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#qp_run read_kconserv $ezfio
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#qp_run read_mo_eri_chunk_complex $ezfio
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881
src/utils_periodic/MolPyscfToQPkpts.py
Normal file
881
src/utils_periodic/MolPyscfToQPkpts.py
Normal file
@ -0,0 +1,881 @@
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import numpy as np
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from functools import reduce
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def memoize(f):
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memo = {}
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def helper(x):
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if x not in memo:
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memo[x] = f(x)
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return memo[x]
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return helper
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@memoize
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def idx2_tri(iijj):
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'''
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iijj should be a 2-tuple
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return triangular compound index for (0-indexed counting)
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'''
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ij1=min(iijj)
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ij2=max(iijj)
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return ij1+(ij2*(ij2+1))//2
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# return ij1+(ij2*(ij2-1))//2
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def pad(arr_in,outshape):
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arr_out = np.zeros(outshape,dtype=np.complex128)
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dataslice = tuple(slice(0,arr_in.shape[dim]) for dim in range(len(outshape)))
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arr_out[dataslice] = arr_in
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return arr_out
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def makesq(vlist,n1,n2):
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'''
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make hermitian matrices of size (n2 x n2) from from lower triangles
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vlist is n1 lower triangles in flattened form
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given: ([a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t],2,4)
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output a 2x4x4 array, where each 4x4 is the square constructed from the lower triangle
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[
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[
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[a b* d* g*]
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[b c e* h*]
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[d e f i*]
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[g h i j ]
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],
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[
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[k l* n* q*]
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[l m o* r*]
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[n o p s*]
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[q r s t ]
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]
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]
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'''
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out=np.zeros([n1,n2,n2],dtype=np.complex128)
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n0 = vlist.shape[0]
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lmask=np.tri(n2,dtype=bool)
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for i in range(n0):
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out[i][lmask] = vlist[i].conj()
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out2=out.transpose([0,2,1])
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for i in range(n0):
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out2[i][lmask] = vlist[i]
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return out2
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def makesq3(vlist,n2):
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'''
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make hermitian matrices of size (n2 x n2) from from lower triangles
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vlist is n1 lower triangles in flattened form
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given: ([a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t],2,4)
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output a 2x4x4 array, where each 4x4 is the square constructed from the lower triangle
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[
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[
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[a b* d* g*]
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[b c e* h*]
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[d e f i*]
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[g h i j ]
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],
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[
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[k l* n* q*]
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[l m o* r*]
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[n o p s*]
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[q r s t ]
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]
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]
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'''
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n0 = vlist.shape[0]
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out=np.zeros([n0,n2,n2],dtype=np.complex128)
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lmask=np.tri(n2,dtype=bool)
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for i in range(n0):
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out[i][lmask] = vlist[i].conj()
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out2=out.transpose([0,2,1])
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for i in range(n0):
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out2[i][lmask] = vlist[i]
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return out2
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def makesq2(vlist,n1,n2):
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out=np.zeros([n1,n2,n2],dtype=np.complex128)
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lmask=np.tri(n2,dtype=bool)
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tmp=np.zeros([n2,n2],dtype=np.complex128)
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tmp2=np.zeros([n2,n2],dtype=np.complex128)
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for i in range(n1):
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tmp[lmask] = vlist[i].conj()
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tmp2=tmp.T
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tmp2[lmask] = vlist[i]
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out[i] = tmp2.copy()
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return out
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def get_phase(cell, kpts, kmesh=None):
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'''
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The unitary transformation that transforms the supercell basis k-mesh
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adapted basis.
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'''
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from pyscf.pbc import tools
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from pyscf import lib
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latt_vec = cell.lattice_vectors()
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if kmesh is None:
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# Guess kmesh
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scaled_k = cell.get_scaled_kpts(kpts).round(8)
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kmesh = (len(np.unique(scaled_k[:,0])),
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len(np.unique(scaled_k[:,1])),
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len(np.unique(scaled_k[:,2])))
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R_rel_a = np.arange(kmesh[0])
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R_rel_b = np.arange(kmesh[1])
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R_rel_c = np.arange(kmesh[2])
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R_vec_rel = lib.cartesian_prod((R_rel_a, R_rel_b, R_rel_c))
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R_vec_abs = np.einsum('nu, uv -> nv', R_vec_rel, latt_vec)
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NR = len(R_vec_abs)
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phase = np.exp(1j*np.einsum('Ru, ku -> Rk', R_vec_abs, kpts))
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phase /= np.sqrt(NR) # normalization in supercell
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# R_rel_mesh has to be construct exactly same to the Ts in super_cell function
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scell = tools.super_cell(cell, kmesh)
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return scell, phase
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def mo_k2gamma(cell, mo_energy, mo_coeff, kpts, kmesh=None):
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'''
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Transform MOs in Kpoints to the equivalents supercell
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'''
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from pyscf import lib
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import scipy.linalg as la
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scell, phase = get_phase(cell, kpts, kmesh)
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E_g = np.hstack(mo_energy)
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C_k = np.asarray(mo_coeff)
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Nk, Nao, Nmo = C_k.shape
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NR = phase.shape[0]
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# Transform AO indices
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C_gamma = np.einsum('Rk, kum -> Rukm', phase, C_k)
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C_gamma = C_gamma.reshape(Nao*NR, Nk*Nmo)
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E_sort_idx = np.argsort(E_g)
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E_g = E_g[E_sort_idx]
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C_gamma = C_gamma[:,E_sort_idx]
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s = scell.pbc_intor('int1e_ovlp')
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assert(abs(reduce(np.dot, (C_gamma.conj().T, s, C_gamma))
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- np.eye(Nmo*Nk)).max() < 1e-7)
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# Transform MO indices
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E_k_degen = abs(E_g[1:] - E_g[:-1]).max() < 1e-5
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if np.any(E_k_degen):
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degen_mask = np.append(False, E_k_degen) | np.append(E_k_degen, False)
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shift = min(E_g[degen_mask]) - .1
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f = np.dot(C_gamma[:,degen_mask] * (E_g[degen_mask] - shift),
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C_gamma[:,degen_mask].conj().T)
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assert(abs(f.imag).max() < 1e-5)
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e, na_orb = la.eigh(f.real, s, type=2)
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C_gamma[:,degen_mask] = na_orb[:, e>0]
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if abs(C_gamma.imag).max() < 1e-7:
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print('!Warning Some complexe pollutions in MOs are present')
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C_gamma = C_gamma.real
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if abs(reduce(np.dot, (C_gamma.conj().T, s, C_gamma)) - np.eye(Nmo*Nk)).max() < 1e-7:
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print('!Warning Some complexe pollutions in MOs are present')
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s_k = cell.pbc_intor('int1e_ovlp', kpts=kpts)
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# overlap between k-point unitcell and gamma-point supercell
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s_k_g = np.einsum('kuv,Rk->kuRv', s_k, phase.conj()).reshape(Nk,Nao,NR*Nao)
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# The unitary transformation from k-adapted orbitals to gamma-point orbitals
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mo_phase = lib.einsum('kum,kuv,vi->kmi', C_k.conj(), s_k_g, C_gamma)
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return mo_phase
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def qp2rename():
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import shutil
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qp2names={}
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qp2names['mo_coef_complex'] = 'C.qp'
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qp2names['bielec_ao_complex'] = 'W.qp'
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qp2names['kinetic_ao_complex'] = 'T.qp'
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qp2names['ne_ao_complex'] = 'V.qp'
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qp2names['overlap_ao_complex'] = 'S.qp'
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for old,new in qp2names.items():
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shutil.move(old,new)
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shutil.copy('e_nuc','E.qp')
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def pyscf2QP(cell,mf, kpts, kmesh=None, cas_idx=None, int_threshold = 1E-8,
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print_ao_ints_bi=False,
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print_mo_ints_bi=False,
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print_ao_ints_df=True,
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print_mo_ints_df=False,
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print_ao_ints_mono=True,
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print_mo_ints_mono=False):
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'''
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kpts = List of kpoints coordinates. Cannot be null, for gamma is other script
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kmesh = Mesh of kpoints (optional)
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cas_idx = List of active MOs. If not specified all MOs are actives
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int_threshold = The integral will be not printed in they are bellow that
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'''
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from pyscf.pbc import ao2mo
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from pyscf.pbc import tools
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from pyscf.pbc.gto import ecp
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import h5py
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mo_coef_threshold = int_threshold
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ovlp_threshold = int_threshold
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kin_threshold = int_threshold
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ne_threshold = int_threshold
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bielec_int_threshold = int_threshold
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natom = len(cell.atom_coords())
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print('n_atom per kpt', natom)
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print('num_elec per kpt', cell.nelectron)
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mo_coeff = mf.mo_coeff
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# Mo_coeff actif
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mo_k = np.array([c[:,cas_idx] for c in mo_coeff] if cas_idx is not None else mo_coeff)
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e_k = np.array([e[cas_idx] for e in mf.mo_energy] if cas_idx is not None else mf.mo_energy)
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Nk, nao, nmo = mo_k.shape
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print("n Kpts", Nk)
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print("n active Mos per kpt", nmo)
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print("n AOs per kpt", nao)
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naux = mf.with_df.auxcell.nao
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print("n df fitting functions", naux)
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with open('num_df','w') as f:
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f.write(str(naux))
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# Write all the parameter need to creat a dummy EZFIO folder who will containt the integral after.
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# More an implentation detail than a real thing
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with open('param','w') as f:
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# Note the use of nmo_tot
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f.write(' '.join(map(str,(cell.nelectron*Nk, Nk*nmo, natom*Nk))))
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with open('num_ao','w') as f:
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f.write(str(nao*Nk))
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with open('num_kpts','w') as f:
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f.write(str(Nk))
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# _
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# |\ | _ | _ _. ._ |_) _ ._ | _ o _ ._
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# | \| |_| (_ | (/_ (_| | | \ (/_ |_) |_| | _> | (_) | |
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# |
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#Total energy shift due to Ewald probe charge = -1/2 * Nelec*madelung/cell.vol =
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shift = tools.pbc.madelung(cell, kpts)*cell.nelectron * -.5
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e_nuc = (cell.energy_nuc() + shift)*Nk
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print('nucl_repul', e_nuc)
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with open('e_nuc','w') as f:
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f.write(str(e_nuc))
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# __ __ _
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# |\/| | | | _ _ |_ _
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# | | |__| |__ (_) (/_ | _>
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#
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with open('mo_coef_complex','w') as outfile:
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c_kpts = np.reshape(mo_k,(Nk,nao,nmo))
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for ik in range(Nk):
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shift1=ik*nao+1
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shift2=ik*nmo+1
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for i in range(nao):
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for j in range(nmo):
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cij = c_kpts[ik,i,j]
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if abs(cij) > mo_coef_threshold:
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outfile.write('%s %s %s %s\n' % (i+shift1, j+shift2, cij.real, cij.imag))
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# ___
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# | ._ _|_ _ _ ._ _. | _ |\/| _ ._ _
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# _|_ | | |_ (/_ (_| | (_| | _> | | (_) | | (_)
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# _|
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if mf.cell.pseudo:
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v_kpts_ao = np.reshape(mf.with_df.get_pp(kpts=kpts),(Nk,nao,nao))
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else:
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v_kpts_ao = np.reshape(mf.with_df.get_nuc(kpts=kpts),(Nk,nao,nao))
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if len(cell._ecpbas) > 0:
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v_kpts_ao += np.reshape(ecp.ecp_int(cell, kpts),(Nk,nao,nao))
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ne_ao = ('ne',v_kpts_ao,ne_threshold)
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ovlp_ao = ('overlap',np.reshape(mf.get_ovlp(cell=cell,kpts=kpts),(Nk,nao,nao)),ovlp_threshold)
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kin_ao = ('kinetic',np.reshape(cell.pbc_intor('int1e_kin',1,1,kpts=kpts),(Nk,nao,nao)),kin_threshold)
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for name, intval_kpts_ao, thresh in (ne_ao, ovlp_ao, kin_ao):
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if print_ao_ints_mono:
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with open('%s_ao_complex' % name,'w') as outfile:
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for ik in range(Nk):
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shift=ik*nao+1
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for i in range(nao):
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for j in range(i,nao):
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int_ij = intval_kpts_ao[ik,i,j]
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if abs(int_ij) > thresh:
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outfile.write('%s %s %s %s\n' % (i+shift, j+shift, int_ij.real, int_ij.imag))
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if print_mo_ints_mono:
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intval_kpts_mo = np.einsum('kim,kij,kjn->kmn',mo_k.conj(),intval_kpts_ao,mo_k)
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with open('%s_mo_complex' % name,'w') as outfile:
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for ik in range(Nk):
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shift=ik*nmo+1
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for i in range(nmo):
|
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for j in range(i,nmo):
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int_ij = intval_kpts_mo[ik,i,j]
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if abs(int_ij) > thresh:
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outfile.write('%s %s %s %s\n' % (i+shift, j+shift, int_ij.real, int_ij.imag))
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# ___ _
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# | ._ _|_ _ _ ._ _. | _ |_) o
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# _|_ | | |_ (/_ (_| | (_| | _> |_) |
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# _|
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#
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kconserv = tools.get_kconserv(cell, kpts)
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with open('kconserv_complex','w') as outfile:
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for a in range(Nk):
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for b in range(Nk):
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for c in range(Nk):
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d = kconserv[a,b,c]
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outfile.write('%s %s %s %s\n' % (a+1,c+1,b+1,d+1))
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|
||||
intfile=h5py.File(mf.with_df._cderi,'r')
|
||||
|
||||
j3c = intfile.get('j3c')
|
||||
naosq = nao*nao
|
||||
naotri = (nao*(nao+1))//2
|
||||
j3ckeys = list(j3c.keys())
|
||||
j3ckeys.sort(key=lambda strkey:int(strkey))
|
||||
|
||||
# in new(?) version of PySCF, there is an extra layer of groups before the datasets
|
||||
# datasets used to be [/j3c/0, /j3c/1, /j3c/2, ...]
|
||||
# datasets now are [/j3c/0/0, /j3c/1/0, /j3c/2/0, ...]
|
||||
j3clist = [j3c.get(i+'/0') for i in j3ckeys]
|
||||
if j3clist==[None]*len(j3clist):
|
||||
# if using older version, stop before last level
|
||||
j3clist = [j3c.get(i) for i in j3ckeys]
|
||||
|
||||
nkinvsq = 1./np.sqrt(Nk)
|
||||
|
||||
# dimensions are (kikj,iaux,jao,kao), where kikj is compound index of kpts i and j
|
||||
# output dimensions should be reversed (nao, nao, naux, nkptpairs)
|
||||
j3arr=np.array([(i.value.reshape([-1,nao,nao]) if (i.shape[1] == naosq) else makesq3(i.value,nao)) * nkinvsq for i in j3clist])
|
||||
|
||||
nkpt_pairs = j3arr.shape[0]
|
||||
|
||||
if print_ao_ints_df:
|
||||
with open('df_ao_integral_array','w') as outfile:
|
||||
pass
|
||||
with open('df_ao_integral_array','a') as outfile:
|
||||
for k,kpt_pair in enumerate(j3arr):
|
||||
for iaux,dfbasfunc in enumerate(kpt_pair):
|
||||
for i,i0 in enumerate(dfbasfunc):
|
||||
for j,v in enumerate(i0):
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (i+1,j+1,iaux+1,k+1,v.real,v.imag))
|
||||
|
||||
if print_mo_ints_df:
|
||||
kpair_list=[]
|
||||
for i in range(Nk):
|
||||
for j in range(Nk):
|
||||
if(i>=j):
|
||||
kpair_list.append((i,j,idx2_tri((i,j))))
|
||||
j3mo = np.array([np.einsum('mij,ik,jl->mkl',j3arr[kij],mo_k[ki].conj(),mo_k[kj]) for ki,kj,kij in kpair_list])
|
||||
with open('df_mo_integral_array','w') as outfile:
|
||||
pass
|
||||
with open('df_mo_integral_array','a') as outfile:
|
||||
for k,kpt_pair in enumerate(j3mo):
|
||||
for iaux,dfbasfunc in enumerate(kpt_pair):
|
||||
for i,i0 in enumerate(dfbasfunc):
|
||||
for j,v in enumerate(i0):
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (i+1,j+1,iaux+1,k+1,v.real,v.imag))
|
||||
|
||||
|
||||
|
||||
|
||||
# eri_4d_ao = np.zeros((Nk,nao,Nk,nao,Nk,nao,Nk,nao), dtype=np.complex)
|
||||
# for d, kd in enumerate(kpts):
|
||||
# for c, kc in enumerate(kpts):
|
||||
# if c > d: break
|
||||
# idx2_cd = idx2_tri(c,d)
|
||||
# for b, kb in enumerate(kpts):
|
||||
# if b > d: break
|
||||
# a = kconserv[b,c,d]
|
||||
# if idx2_tri(a,b) > idx2_cd: continue
|
||||
# if ((c==d) and (a>b)): continue
|
||||
# ka = kpts[a]
|
||||
# v = mf.with_df.get_ao_eri(kpts=[ka,kb,kc,kd],compact=False).reshape((nao,)*4)
|
||||
# v *= 1./Nk
|
||||
# eri_4d_ao[a,:,b,:,c,:,d] = v
|
||||
#
|
||||
# eri_4d_ao = eri_4d_ao.reshape([Nk*nao]*4)
|
||||
|
||||
|
||||
if (print_ao_ints_bi or print_mo_ints_bi):
|
||||
if print_ao_ints_bi:
|
||||
with open('bielec_ao_complex','w') as outfile:
|
||||
pass
|
||||
if print_mo_ints_bi:
|
||||
with open('bielec_mo_complex','w') as outfile:
|
||||
pass
|
||||
for d, kd in enumerate(kpts):
|
||||
for c, kc in enumerate(kpts):
|
||||
if c > d: break
|
||||
idx2_cd = idx2_tri((c,d))
|
||||
for b, kb in enumerate(kpts):
|
||||
if b > d: break
|
||||
a = kconserv[b,c,d]
|
||||
if idx2_tri((a,b)) > idx2_cd: continue
|
||||
if ((c==d) and (a>b)): continue
|
||||
ka = kpts[a]
|
||||
|
||||
if print_ao_ints_bi:
|
||||
with open('bielec_ao_complex','a') as outfile:
|
||||
eri_4d_ao_kpt = mf.with_df.get_ao_eri(kpts=[ka,kb,kc,kd],compact=False).reshape((nao,)*4)
|
||||
eri_4d_ao_kpt *= 1./Nk
|
||||
for l in range(nao):
|
||||
ll=l+d*nao
|
||||
for j in range(nao):
|
||||
jj=j+c*nao
|
||||
if jj>ll: break
|
||||
idx2_jjll = idx2_tri((jj,ll))
|
||||
for k in range(nao):
|
||||
kk=k+b*nao
|
||||
if kk>ll: break
|
||||
for i in range(nao):
|
||||
ii=i+a*nao
|
||||
if idx2_tri((ii,kk)) > idx2_jjll: break
|
||||
if ((jj==ll) and (ii>kk)): break
|
||||
v=eri_4d_ao_kpt[i,k,j,l]
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (ii+1,jj+1,kk+1,ll+1,v.real,v.imag))
|
||||
|
||||
if print_mo_ints_bi:
|
||||
with open('bielec_mo_complex','a') as outfile:
|
||||
eri_4d_mo_kpt = mf.with_df.ao2mo([mo_k[a], mo_k[b], mo_k[c], mo_k[d]],
|
||||
[ka,kb,kc,kd],compact=False).reshape((nmo,)*4)
|
||||
eri_4d_mo_kpt *= 1./Nk
|
||||
for l in range(nmo):
|
||||
ll=l+d*nmo
|
||||
for j in range(nmo):
|
||||
jj=j+c*nmo
|
||||
if jj>ll: break
|
||||
idx2_jjll = idx2_tri((jj,ll))
|
||||
for k in range(nmo):
|
||||
kk=k+b*nmo
|
||||
if kk>ll: break
|
||||
for i in range(nmo):
|
||||
ii=i+a*nmo
|
||||
if idx2_tri((ii,kk)) > idx2_jjll: break
|
||||
if ((jj==ll) and (ii>kk)): break
|
||||
v=eri_4d_mo_kpt[i,k,j,l]
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (ii+1,jj+1,kk+1,ll+1,v.real,v.imag))
|
||||
|
||||
|
||||
def pyscf2QP2(cell,mf, kpts, kmesh=None, cas_idx=None, int_threshold = 1E-8,
|
||||
print_ao_ints_bi=False,
|
||||
print_mo_ints_bi=False,
|
||||
print_ao_ints_df=True,
|
||||
print_mo_ints_df=False,
|
||||
print_ao_ints_mono=True,
|
||||
print_mo_ints_mono=False):
|
||||
'''
|
||||
kpts = List of kpoints coordinates. Cannot be null, for gamma is other script
|
||||
kmesh = Mesh of kpoints (optional)
|
||||
cas_idx = List of active MOs. If not specified all MOs are actives
|
||||
int_threshold = The integral will be not printed in they are bellow that
|
||||
'''
|
||||
|
||||
from pyscf.pbc import ao2mo
|
||||
from pyscf.pbc import tools
|
||||
from pyscf.pbc.gto import ecp
|
||||
import h5py
|
||||
import scipy
|
||||
|
||||
qph5=h5py.File('qpdat.h5')
|
||||
qph5.create_group('nuclei')
|
||||
qph5.create_group('electrons')
|
||||
qph5.create_group('ao_basis')
|
||||
qph5.create_group('mo_basis')
|
||||
|
||||
|
||||
mo_coef_threshold = int_threshold
|
||||
ovlp_threshold = int_threshold
|
||||
kin_threshold = int_threshold
|
||||
ne_threshold = int_threshold
|
||||
bielec_int_threshold = int_threshold
|
||||
|
||||
natom = cell.natm
|
||||
nelec = cell.nelectron
|
||||
print('n_atom per kpt', natom)
|
||||
print('num_elec per kpt', nelec)
|
||||
|
||||
mo_coeff = mf.mo_coeff
|
||||
# Mo_coeff actif
|
||||
mo_k = np.array([c[:,cas_idx] for c in mo_coeff] if cas_idx is not None else mo_coeff)
|
||||
e_k = np.array([e[cas_idx] for e in mf.mo_energy] if cas_idx is not None else mf.mo_energy)
|
||||
|
||||
Nk, nao, nmo = mo_k.shape
|
||||
print("n Kpts", Nk)
|
||||
print("n active Mos per kpt", nmo)
|
||||
print("n AOs per kpt", nao)
|
||||
|
||||
naux = mf.with_df.auxcell.nao
|
||||
print("n df fitting functions", naux)
|
||||
|
||||
#in old version: param < nelec*Nk, nmo*Nk, natom*Nk
|
||||
qph5['electrons'].attrs['elec_alpha_num']=nelec*Nk
|
||||
qph5['electrons'].attrs['elec_beta_num']=nelec*Nk
|
||||
qph5['mo_basis'].attrs['mo_num']=Nk*nmo
|
||||
qph5['ao_basis'].attrs['ao_num']=Nk*nao
|
||||
qph5['nuclei'].attrs['nucl_num']=Nk*natom
|
||||
qph5['nuclei'].attrs['kpt_num']=Nk
|
||||
qph5['ao_basis'].attrs['df_num']=naux
|
||||
|
||||
# _
|
||||
# |\ | _ | _ _. ._ |_) _ ._ | _ o _ ._
|
||||
# | \| |_| (_ | (/_ (_| | | \ (/_ |_) |_| | _> | (_) | |
|
||||
# |
|
||||
|
||||
#Total energy shift due to Ewald probe charge = -1/2 * Nelec*madelung/cell.vol =
|
||||
shift = tools.pbc.madelung(cell, kpts)*cell.nelectron * -.5
|
||||
e_nuc = (cell.energy_nuc() + shift)*Nk
|
||||
|
||||
print('nucl_repul', e_nuc)
|
||||
qph5['nuclei'].attrs['nuclear_repulsion']=e_nuc
|
||||
|
||||
# __ __ _
|
||||
# |\/| | | | _ _ |_ _
|
||||
# | | |__| |__ (_) (/_ | _>
|
||||
#
|
||||
mo_coef_blocked=scipy.linalg.block_diag(*mo_k)
|
||||
qph5.create_dataset('mo_basis/mo_coef_real',data=mo_coef_blocked.real)
|
||||
qph5.create_dataset('mo_basis/mo_coef_imag',data=mo_coef_blocked.imag)
|
||||
qph5.create_dataset('mo_basis/mo_coef_kpts_real',data=mo_k.real)
|
||||
qph5.create_dataset('mo_basis/mo_coef_kpts_imag',data=mo_k.imag)
|
||||
|
||||
# ___
|
||||
# | ._ _|_ _ _ ._ _. | _ |\/| _ ._ _
|
||||
# _|_ | | |_ (/_ (_| | (_| | _> | | (_) | | (_)
|
||||
# _|
|
||||
|
||||
if mf.cell.pseudo:
|
||||
ao_n_e = np.reshape(mf.with_df.get_pp(kpts=kpts),(Nk,nao,nao))
|
||||
else:
|
||||
v_kpts_ao = np.reshape(mf.with_df.get_nuc(kpts=kpts),(Nk,nao,nao))
|
||||
if len(cell._ecpbas) > 0:
|
||||
v_kpts_ao += np.reshape(ecp.ecp_int(cell, kpts),(Nk,nao,nao))
|
||||
|
||||
ne_ao = ('ne',v_kpts_ao,ne_threshold)
|
||||
ovlp_ao = ('overlap',np.reshape(mf.get_ovlp(cell=cell,kpts=kpts),(Nk,nao,nao)),ovlp_threshold)
|
||||
kin_ao = ('kinetic',np.reshape(cell.pbc_intor('int1e_kin',1,1,kpts=kpts),(Nk,nao,nao)),kin_threshold)
|
||||
|
||||
for name, intval_kpts_ao, thresh in (ne_ao, ovlp_ao, kin_ao):
|
||||
if print_ao_ints_mono:
|
||||
with open('%s_ao_complex' % name,'w') as outfile:
|
||||
for ik in range(Nk):
|
||||
shift=ik*nao+1
|
||||
for i in range(nao):
|
||||
for j in range(i,nao):
|
||||
int_ij = intval_kpts_ao[ik,i,j]
|
||||
if abs(int_ij) > thresh:
|
||||
outfile.write('%s %s %s %s\n' % (i+shift, j+shift, int_ij.real, int_ij.imag))
|
||||
if print_mo_ints_mono:
|
||||
intval_kpts_mo = np.einsum('kim,kij,kjn->kmn',mo_k.conj(),intval_kpts_ao,mo_k)
|
||||
with open('%s_mo_complex' % name,'w') as outfile:
|
||||
for ik in range(Nk):
|
||||
shift=ik*nmo+1
|
||||
for i in range(nmo):
|
||||
for j in range(i,nmo):
|
||||
int_ij = intval_kpts_mo[ik,i,j]
|
||||
if abs(int_ij) > thresh:
|
||||
outfile.write('%s %s %s %s\n' % (i+shift, j+shift, int_ij.real, int_ij.imag))
|
||||
|
||||
|
||||
# ___ _
|
||||
# | ._ _|_ _ _ ._ _. | _ |_) o
|
||||
# _|_ | | |_ (/_ (_| | (_| | _> |_) |
|
||||
# _|
|
||||
#
|
||||
kconserv = tools.get_kconserv(cell, kpts)
|
||||
|
||||
with open('kconserv_complex','w') as outfile:
|
||||
for a in range(Nk):
|
||||
for b in range(Nk):
|
||||
for c in range(Nk):
|
||||
d = kconserv[a,b,c]
|
||||
outfile.write('%s %s %s %s\n' % (a+1,c+1,b+1,d+1))
|
||||
|
||||
|
||||
intfile=h5py.File(mf.with_df._cderi,'r')
|
||||
|
||||
j3c = intfile.get('j3c')
|
||||
naosq = nao*nao
|
||||
naotri = (nao*(nao+1))//2
|
||||
j3ckeys = list(j3c.keys())
|
||||
j3ckeys.sort(key=lambda strkey:int(strkey))
|
||||
|
||||
# in new(?) version of PySCF, there is an extra layer of groups before the datasets
|
||||
# datasets used to be [/j3c/0, /j3c/1, /j3c/2, ...]
|
||||
# datasets now are [/j3c/0/0, /j3c/1/0, /j3c/2/0, ...]
|
||||
j3clist = [j3c.get(i+'/0') for i in j3ckeys]
|
||||
if j3clist==[None]*len(j3clist):
|
||||
# if using older version, stop before last level
|
||||
j3clist = [j3c.get(i) for i in j3ckeys]
|
||||
|
||||
nkinvsq = 1./np.sqrt(Nk)
|
||||
|
||||
# dimensions are (kikj,iaux,jao,kao), where kikj is compound index of kpts i and j
|
||||
# output dimensions should be reversed (nao, nao, naux, nkptpairs)
|
||||
j3arr=np.array([(i.value.reshape([-1,nao,nao]) if (i.shape[1] == naosq) else makesq3(i.value,nao)) * nkinvsq for i in j3clist])
|
||||
|
||||
nkpt_pairs = j3arr.shape[0]
|
||||
|
||||
if print_ao_ints_df:
|
||||
with open('df_ao_integral_array','w') as outfile:
|
||||
pass
|
||||
with open('df_ao_integral_array','a') as outfile:
|
||||
for k,kpt_pair in enumerate(j3arr):
|
||||
for iaux,dfbasfunc in enumerate(kpt_pair):
|
||||
for i,i0 in enumerate(dfbasfunc):
|
||||
for j,v in enumerate(i0):
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (i+1,j+1,iaux+1,k+1,v.real,v.imag))
|
||||
|
||||
if print_mo_ints_df:
|
||||
kpair_list=[]
|
||||
for i in range(Nk):
|
||||
for j in range(Nk):
|
||||
if(i>=j):
|
||||
kpair_list.append((i,j,idx2_tri((i,j))))
|
||||
j3mo = np.array([np.einsum('mij,ik,jl->mkl',j3arr[kij],mo_k[ki].conj(),mo_k[kj]) for ki,kj,kij in kpair_list])
|
||||
with open('df_mo_integral_array','w') as outfile:
|
||||
pass
|
||||
with open('df_mo_integral_array','a') as outfile:
|
||||
for k,kpt_pair in enumerate(j3mo):
|
||||
for iaux,dfbasfunc in enumerate(kpt_pair):
|
||||
for i,i0 in enumerate(dfbasfunc):
|
||||
for j,v in enumerate(i0):
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (i+1,j+1,iaux+1,k+1,v.real,v.imag))
|
||||
|
||||
|
||||
|
||||
# eri_4d_ao = np.zeros((Nk,nao,Nk,nao,Nk,nao,Nk,nao), dtype=np.complex)
|
||||
# for d, kd in enumerate(kpts):
|
||||
# for c, kc in enumerate(kpts):
|
||||
# if c > d: break
|
||||
# idx2_cd = idx2_tri(c,d)
|
||||
# for b, kb in enumerate(kpts):
|
||||
# if b > d: break
|
||||
# a = kconserv[b,c,d]
|
||||
# if idx2_tri(a,b) > idx2_cd: continue
|
||||
# if ((c==d) and (a>b)): continue
|
||||
# ka = kpts[a]
|
||||
# v = mf.with_df.get_ao_eri(kpts=[ka,kb,kc,kd],compact=False).reshape((nao,)*4)
|
||||
# v *= 1./Nk
|
||||
# eri_4d_ao[a,:,b,:,c,:,d] = v
|
||||
#
|
||||
# eri_4d_ao = eri_4d_ao.reshape([Nk*nao]*4)
|
||||
|
||||
|
||||
if (print_ao_ints_bi or print_mo_ints_bi):
|
||||
if print_ao_ints_bi:
|
||||
with open('bielec_ao_complex','w') as outfile:
|
||||
pass
|
||||
if print_mo_ints_bi:
|
||||
with open('bielec_mo_complex','w') as outfile:
|
||||
pass
|
||||
for d, kd in enumerate(kpts):
|
||||
for c, kc in enumerate(kpts):
|
||||
if c > d: break
|
||||
idx2_cd = idx2_tri((c,d))
|
||||
for b, kb in enumerate(kpts):
|
||||
if b > d: break
|
||||
a = kconserv[b,c,d]
|
||||
if idx2_tri((a,b)) > idx2_cd: continue
|
||||
if ((c==d) and (a>b)): continue
|
||||
ka = kpts[a]
|
||||
|
||||
if print_ao_ints_bi:
|
||||
with open('bielec_ao_complex','a') as outfile:
|
||||
eri_4d_ao_kpt = mf.with_df.get_ao_eri(kpts=[ka,kb,kc,kd],compact=False).reshape((nao,)*4)
|
||||
eri_4d_ao_kpt *= 1./Nk
|
||||
for l in range(nao):
|
||||
ll=l+d*nao
|
||||
for j in range(nao):
|
||||
jj=j+c*nao
|
||||
if jj>ll: break
|
||||
idx2_jjll = idx2_tri((jj,ll))
|
||||
for k in range(nao):
|
||||
kk=k+b*nao
|
||||
if kk>ll: break
|
||||
for i in range(nao):
|
||||
ii=i+a*nao
|
||||
if idx2_tri((ii,kk)) > idx2_jjll: break
|
||||
if ((jj==ll) and (ii>kk)): break
|
||||
v=eri_4d_ao_kpt[i,k,j,l]
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (ii+1,jj+1,kk+1,ll+1,v.real,v.imag))
|
||||
|
||||
if print_mo_ints_bi:
|
||||
with open('bielec_mo_complex','a') as outfile:
|
||||
eri_4d_mo_kpt = mf.with_df.ao2mo([mo_k[a], mo_k[b], mo_k[c], mo_k[d]],
|
||||
[ka,kb,kc,kd],compact=False).reshape((nmo,)*4)
|
||||
eri_4d_mo_kpt *= 1./Nk
|
||||
for l in range(nmo):
|
||||
ll=l+d*nmo
|
||||
for j in range(nmo):
|
||||
jj=j+c*nmo
|
||||
if jj>ll: break
|
||||
idx2_jjll = idx2_tri((jj,ll))
|
||||
for k in range(nmo):
|
||||
kk=k+b*nmo
|
||||
if kk>ll: break
|
||||
for i in range(nmo):
|
||||
ii=i+a*nmo
|
||||
if idx2_tri((ii,kk)) > idx2_jjll: break
|
||||
if ((jj==ll) and (ii>kk)): break
|
||||
v=eri_4d_mo_kpt[i,k,j,l]
|
||||
if (abs(v) > bielec_int_threshold):
|
||||
outfile.write('%s %s %s %s %s %s\n' % (ii+1,jj+1,kk+1,ll+1,v.real,v.imag))
|
||||
|
||||
|
||||
|
||||
#def testpyscf2QP(cell,mf, kpts, kmesh=None, cas_idx=None, int_threshold = 1E-8):
|
||||
# '''
|
||||
# kpts = List of kpoints coordinates. Cannot be null, for gamma is other script
|
||||
# kmesh = Mesh of kpoints (optional)
|
||||
# cas_idx = List of active MOs. If not specified all MOs are actives
|
||||
# int_threshold = The integral will be not printed in they are bellow that
|
||||
# '''
|
||||
#
|
||||
# from pyscf.pbc import ao2mo
|
||||
# from pyscf.pbc import tools
|
||||
# from pyscf.pbc.gto import ecp
|
||||
#
|
||||
# mo_coef_threshold = int_threshold
|
||||
# ovlp_threshold = int_threshold
|
||||
# kin_threshold = int_threshold
|
||||
# ne_threshold = int_threshold
|
||||
# bielec_int_threshold = int_threshold
|
||||
#
|
||||
# natom = len(cell.atom_coords())
|
||||
# print('n_atom per kpt', natom)
|
||||
# print('num_elec per kpt', cell.nelectron)
|
||||
#
|
||||
# mo_coeff = mf.mo_coeff
|
||||
# # Mo_coeff actif
|
||||
# mo_k = np.array([c[:,cas_idx] for c in mo_coeff] if cas_idx is not None else mo_coeff)
|
||||
# e_k = np.array([e[cas_idx] for e in mf.mo_energy] if cas_idx is not None else mf.mo_energy)
|
||||
#
|
||||
# Nk, nao, nmo = mo_k.shape
|
||||
# print("n Kpts", Nk)
|
||||
# print("n active Mos per kpt", nmo)
|
||||
# print("n AOs per kpt", nao)
|
||||
#
|
||||
# naux = mf.with_df.get_naoaux()
|
||||
# print("n df fitting functions", naux)
|
||||
#
|
||||
# # _
|
||||
# # |\ | _ | _ _. ._ |_) _ ._ | _ o _ ._
|
||||
# # | \| |_| (_ | (/_ (_| | | \ (/_ |_) |_| | _> | (_) | |
|
||||
# # |
|
||||
#
|
||||
# #Total energy shift due to Ewald probe charge = -1/2 * Nelec*madelung/cell.vol =
|
||||
# shift = tools.pbc.madelung(cell, kpts)*cell.nelectron * -.5
|
||||
# e_nuc = (cell.energy_nuc() + shift)*Nk
|
||||
#
|
||||
# print('nucl_repul', e_nuc)
|
||||
#
|
||||
#
|
||||
# # ___
|
||||
# # | ._ _|_ _ _ ._ _. | _ |\/| _ ._ _
|
||||
# # _|_ | | |_ (/_ (_| | (_| | _> | | (_) | | (_)
|
||||
# # _|
|
||||
#
|
||||
# if mf.cell.pseudo:
|
||||
# v_kpts_ao = np.reshape(mf.with_df.get_pp(kpts=kpts),(Nk,nao,nao))
|
||||
# else:
|
||||
# v_kpts_ao = np.reshape(mf.with_df.get_nuc(kpts=kpts),(Nk,nao,nao))
|
||||
# if len(cell._ecpbas) > 0:
|
||||
# v_kpts_ao += np.reshape(ecp.ecp_int(cell, kpts),(Nk,nao,nao))
|
||||
#
|
||||
# ne_ao = ('ne',v_kpts_ao,ne_threshold)
|
||||
# ovlp_ao = ('overlap',np.reshape(mf.get_ovlp(cell=cell,kpts=kpts),(Nk,nao,nao)),ovlp_threshold)
|
||||
# kin_ao = ('kinetic',np.reshape(cell.pbc_intor('int1e_kin',1,1,kpts=kpts),(Nk,nao,nao)),kin_threshold)
|
||||
#
|
||||
#
|
||||
# # ___ _
|
||||
# # | ._ _|_ _ _ ._ _. | _ |_) o
|
||||
# # _|_ | | |_ (/_ (_| | (_| | _> |_) |
|
||||
# # _|
|
||||
# #
|
||||
# kconserv = tools.get_kconserv(cell, kpts)
|
||||
#
|
||||
#
|
||||
# import h5py
|
||||
#
|
||||
# intfile=h5py.File(mf.with_df._cderi,'r')
|
||||
#
|
||||
# j3c = intfile.get('j3c')
|
||||
# naosq = nao*nao
|
||||
# naotri = (nao*(nao+1))//2
|
||||
# j3keys = list(j3c.keys())
|
||||
# j3keys.sort(key=lambda x:int(x))
|
||||
# j3clist = [j3c.get(i) for i in j3keys]
|
||||
# nkinvsq = 1./np.sqrt(Nk)
|
||||
#
|
||||
# # dimensions are (kikj,iaux,jao,kao), where kikj is compound index of kpts i and j
|
||||
# # output dimensions should be reversed (nao, nao, naux, nkptpairs)
|
||||
# j3arr=np.array([(pad(i.value.reshape([-1,nao,nao]),[naux,nao,nao]) if (i.shape[1] == naosq) else makesq(i.value,naux,nao)) * nkinvsq for i in j3clist])
|
||||
#
|
||||
# nkpt_pairs = j3arr.shape[0]
|
||||
#
|
||||
# kpair_list=[]
|
||||
# for i in range(Nk):
|
||||
# for j in range(Nk):
|
||||
# if(i>=j):
|
||||
# kpair_list.append((i,j,idx2_tri((i,j))))
|
||||
# j3mo = np.array([np.einsum('mij,ik,jl->mkl',j3arr[kij,:,:,:],mo_k[ki,:,:].conj(),mo_k[kj,:,:]) for ki,kj,kij in kpair_list])
|
||||
#
|
||||
#
|
||||
#
|
||||
# eri_mo = np.zeros(4*[nmo*Nk],dtype=np.complex128)
|
||||
# eri_ao = np.zeros(4*[nao*Nk],dtype=np.complex128)
|
||||
#
|
||||
# for d, kd in enumerate(kpts):
|
||||
# for c, kc in enumerate(kpts):
|
||||
# for b, kb in enumerate(kpts):
|
||||
# a = kconserv[b,c,d]
|
||||
# ka = kpts[a]
|
||||
# eri_4d_ao_kpt = mf.with_df.get_ao_eri(kpts=[ka,kb,kc,kd],compact=False).reshape((nao,)*4)
|
||||
# eri_4d_ao_kpt *= 1./Nk
|
||||
# for l in range(nao):
|
||||
# ll=l+d*nao
|
||||
# for j in range(nao):
|
||||
# jj=j+c*nao
|
||||
# for k in range(nao):
|
||||
# kk=k+b*nao
|
||||
# for i in range(nao):
|
||||
# ii=i+a*nao
|
||||
# v=eri_4d_ao_kpt[i,k,j,l]
|
||||
# eri_ao[ii,kk,jj,ll]=v
|
||||
#
|
||||
# eri_4d_mo_kpt = mf.with_df.ao2mo([mo_k[a], mo_k[b], mo_k[c], mo_k[d]],
|
||||
# [ka,kb,kc,kd],compact=False).reshape((nmo,)*4)
|
||||
# eri_4d_mo_kpt *= 1./Nk
|
||||
# for l in range(nmo):
|
||||
# ll=l+d*nmo
|
||||
# for j in range(nmo):
|
||||
# jj=j+c*nmo
|
||||
# for k in range(nmo):
|
||||
# kk=k+b*nmo
|
||||
# for i in range(nmo):
|
||||
# ii=i+a*nmo
|
||||
# v=eri_4d_mo_kpt[i,k,j,l]
|
||||
# eri_mo[ii,kk,jj,ll]=v
|
||||
#
|
||||
# return (mo_k,j3arr,j3mo,eri_ao,eri_mo,kpair_list)
|
||||
|
||||
|
||||
78
src/utils_periodic/create_ezfio_complex_3idx.py
Executable file
78
src/utils_periodic/create_ezfio_complex_3idx.py
Executable file
@ -0,0 +1,78 @@
|
||||
#!/usr/bin/env python
|
||||
from ezfio import ezfio
|
||||
import h5py
|
||||
|
||||
import sys
|
||||
filename = sys.argv[1]
|
||||
h5filename = sys.argv[2]
|
||||
#num_elec, nucl_num, mo_num = map(int,sys.argv[2:5])
|
||||
|
||||
#nuclear_repulsion = float(sys.argv[5])
|
||||
#ao_num = int(sys.argv[6])
|
||||
#n_kpts = int(sys.argv[7])
|
||||
#n_aux = int(sys.argv[8])
|
||||
ezfio.set_file(filename)
|
||||
qph5=h5py.File(h5filename.'r')
|
||||
|
||||
ezfio.electrons_elec_alpha_num = qph5['electrons'].attrs['elec_alpha_num']
|
||||
ezfio.electrons_elec_beta_num = qph5['electrons'].attrs['elec_beta_num']
|
||||
|
||||
nucl_num = qph5['nuclei'].attrs['nucl_num']
|
||||
kpt_num = qph5['nuclei'].attrs['kpt_num']
|
||||
#df_num = qph5['???'].attrs['df_num']
|
||||
|
||||
mo_num = qph5['mo_basis'].attrs['mo_num']
|
||||
ezfio.set_mo_basis_mo_num(mo_num)
|
||||
|
||||
#ao_num = mo_num
|
||||
#Important !
|
||||
import math
|
||||
nelec_per_kpt = num_elec // n_kpts
|
||||
nelec_alpha_per_kpt = int(math.ceil(nelec_per_kpt / 2.))
|
||||
nelec_beta_per_kpt = int(math.floor(nelec_per_kpt / 2.))
|
||||
|
||||
ezfio.electrons_elec_alpha_num = int(nelec_alpha_per_kpt * n_kpts)
|
||||
ezfio.electrons_elec_beta_num = int(nelec_beta_per_kpt * n_kpts)
|
||||
|
||||
#ezfio.electrons_elec_alpha_num = int(math.ceil(num_elec / 2.))
|
||||
#ezfio.electrons_elec_beta_num = int(math.floor(num_elec / 2.))
|
||||
|
||||
#ezfio.set_utils_num_kpts(n_kpts)
|
||||
#ezfio.set_integrals_bielec_df_num(n_aux)
|
||||
|
||||
#Important
|
||||
ezfio.set_nuclei_nucl_num(nucl_num)
|
||||
ezfio.set_nuclei_nucl_charge([0.]*nucl_num)
|
||||
ezfio.set_nuclei_nucl_coord( [ [0.], [0.], [0.] ]*nucl_num )
|
||||
ezfio.set_nuclei_nucl_label( ['He'] * nucl_num )
|
||||
|
||||
ezfio.set_nuclei_io_nuclear_repulsion('Read')
|
||||
ezfio.set_nuclei_nuclear_repulsion(nuclear_repulsion)
|
||||
|
||||
# Ao num
|
||||
#ao_num = mo_num
|
||||
ezfio.set_ao_basis_ao_basis("Dummy one. We read MO")
|
||||
ezfio.set_ao_basis_ao_num(ao_num)
|
||||
ezfio.set_ao_basis_ao_nucl([1]*ao_num) #Maybe put a realy incorrect stuff
|
||||
|
||||
#Just need one
|
||||
ao_prim_num_max = 5
|
||||
|
||||
d = [ [0] *ao_prim_num_max]*ao_num
|
||||
ezfio.set_ao_basis_ao_prim_num([ao_prim_num_max]*ao_num)
|
||||
ezfio.set_ao_basis_ao_power(d)
|
||||
ezfio.set_ao_basis_ao_coef(d)
|
||||
ezfio.set_ao_basis_ao_expo(d)
|
||||
|
||||
#Dummy one
|
||||
ao_md5 = '3b8b464dfc95f282129bde3efef3c502'
|
||||
ezfio.set_ao_basis_ao_md5(ao_md5)
|
||||
ezfio.set_mo_basis_ao_md5(ao_md5)
|
||||
|
||||
|
||||
ezfio.set_mo_basis_mo_num(mo_num)
|
||||
c_mo = [[1 if i==j else 0 for i in range(mo_num)] for j in range(ao_num)]
|
||||
ezfio.set_mo_basis_mo_coef([ [0]*mo_num] * ao_num)
|
||||
#ezfio.set_mo_basis_mo_coef_real(c_mo)
|
||||
|
||||
ezfio.set_nuclei_is_periodic(True)
|
||||
@ -73,15 +73,23 @@ later:
|
||||
|
||||
|
||||
NOTES:
|
||||
number of unique 4-tuples with 8-fold symmetry is a8(n)=n*(n+1)*(n^2+n+2)/8
|
||||
number of unique 4-tuples with 4-fold symmetry is a4(n)=n^2*(n^2+3)/4
|
||||
a8 is number of unique real 2e ints with n mos
|
||||
a4 is number of unique* complex 2e ints with n mos (where p+i*q and p-i*q are counted as one, not two)
|
||||
a4(n) = a8(n) + a8(n-1)
|
||||
3-index integrals
|
||||
<ij|kl> = \sum_\mu (ik|\mu)(jl|\mu)
|
||||
store (ik|\mu) for I<=K
|
||||
if i>k, take conjugate transpose in first two dimensions
|
||||
|
||||
we can already generate the list of <ij|kl> with unique values for the 8-fold case
|
||||
the set of these for 4-fold symmetry is the union of the 8-fold set for n and the 8-fold set for n-1 with a simple transformation
|
||||
<ij|kl>_{4,n} = <ij|kl>_{8,n} + <(k+1)j|i(l+1)>_{8,n-1}
|
||||
df_mo(:,:,mu,kjkl) = C(:,:,kj)^\dagger.df_ao(:,:,mu,kjkl).C(:,:,kl)
|
||||
|
||||
2e int compound indexing
|
||||
number of unique 4-tuples with 8-fold symmetry is a8(n)=n*(n+1)*(n^2+n+2)/8
|
||||
number of unique 4-tuples with 4-fold symmetry is a4(n)=n^2*(n^2+3)/4
|
||||
a8 is number of unique real 2e ints with n mos
|
||||
a4 is number of unique* complex 2e ints with n mos (where p+i*q and p-i*q are counted as one, not two)
|
||||
a4(n) = a8(n) + a8(n-1)
|
||||
|
||||
we can already generate the list of <ij|kl> with unique values for the 8-fold case
|
||||
the set of these for 4-fold symmetry is the union of the 8-fold set for n and the 8-fold set for n-1 with a simple transformation
|
||||
<ij|kl>_{4,n} = <ij|kl>_{8,n} + <(k+1)j|i(l+1)>_{8,n-1}
|
||||
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user