mirror of
https://github.com/QuantumPackage/qp2.git
synced 2024-07-08 20:33:56 +02:00
02c6539daa
should loop over union of two sets of integrals: set 1: i<=k j<=l ik<=jl set 2: i>k j<l ik<=jl looping over kpts in same way is incorrect here I've relaxed the constraints over kpt indices, while keeping those over orbital indices There is probably a more efficient way to do this where we have more kpt constraints and additional logic in orbital loops
1137 lines
44 KiB
Python
1137 lines
44 KiB
Python
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('kpt_num','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')
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j3c = intfile.get('j3c')
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naosq = nao*nao
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naotri = (nao*(nao+1))//2
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j3ckeys = list(j3c.keys())
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j3ckeys.sort(key=lambda strkey:int(strkey))
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# in new(?) version of PySCF, there is an extra layer of groups before the datasets
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# datasets used to be [/j3c/0, /j3c/1, /j3c/2, ...]
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# datasets now are [/j3c/0/0, /j3c/1/0, /j3c/2/0, ...]
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j3clist = [j3c.get(i+'/0') for i in j3ckeys]
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if j3clist==[None]*len(j3clist):
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# if using older version, stop before last level
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j3clist = [j3c.get(i) for i in j3ckeys]
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nkinvsq = 1./np.sqrt(Nk)
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# dimensions are (kikj,iaux,jao,kao), where kikj is compound index of kpts i and j
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# output dimensions should be reversed (nao, nao, naux, nkptpairs)
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j3arr=np.array([(i.value.reshape([-1,nao,nao]) if (i.shape[1] == naosq) else makesq3(i.value,nao)) * nkinvsq for i in j3clist])
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nkpt_pairs = j3arr.shape[0]
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if print_ao_ints_df:
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with open('df_ao_integral_array','w') as outfile:
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pass
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with open('df_ao_integral_array','a') as outfile:
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for k,kpt_pair in enumerate(j3arr):
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for iaux,dfbasfunc in enumerate(kpt_pair):
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for i,i0 in enumerate(dfbasfunc):
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for j,v in enumerate(i0):
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if (abs(v) > bielec_int_threshold):
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outfile.write('%s %s %s %s %s %s\n' % (i+1,j+1,iaux+1,k+1,v.real,v.imag))
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if print_mo_ints_df:
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kpair_list=[]
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for i in range(Nk):
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for j in range(Nk):
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if(i>=j):
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kpair_list.append((i,j,idx2_tri((i,j))))
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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])
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with open('df_mo_integral_array','w') as outfile:
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pass
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with open('df_mo_integral_array','a') as outfile:
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for k,kpt_pair in enumerate(j3mo):
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for iaux,dfbasfunc in enumerate(kpt_pair):
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for i,i0 in enumerate(dfbasfunc):
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for j,v in enumerate(i0):
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if (abs(v) > bielec_int_threshold):
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outfile.write('%s %s %s %s %s %s\n' % (i+1,j+1,iaux+1,k+1,v.real,v.imag))
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# eri_4d_ao = np.zeros((Nk,nao,Nk,nao,Nk,nao,Nk,nao), dtype=np.complex)
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# for d, kd in enumerate(kpts):
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# for c, kc in enumerate(kpts):
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# if c > d: break
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# idx2_cd = idx2_tri(c,d)
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# for b, kb in enumerate(kpts):
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# if b > d: break
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# a = kconserv[b,c,d]
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# if idx2_tri(a,b) > idx2_cd: continue
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# if ((c==d) and (a>b)): continue
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# ka = kpts[a]
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# v = mf.with_df.get_ao_eri(kpts=[ka,kb,kc,kd],compact=False).reshape((nao,)*4)
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# v *= 1./Nk
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# eri_4d_ao[a,:,b,:,c,:,d] = v
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#
|
|
# 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 testprintbi(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
|
|
from pyscf.data import nist
|
|
import h5py
|
|
import scipy
|
|
|
|
|
|
bielec_int_threshold = int_threshold
|
|
|
|
natom = cell.natm
|
|
nelec = cell.nelectron
|
|
neleca,nelecb = cell.nelec
|
|
atom_xyz = mf.cell.atom_coords()
|
|
if not(mf.cell.unit.startswith(('B','b','au','AU'))):
|
|
atom_xyz /= nist.BOHR # always convert to au
|
|
|
|
strtype=h5py.special_dtype(vlen=str)
|
|
atom_dset=qph5.create_dataset('nuclei/nucl_label',(natom,),dtype=strtype)
|
|
for i in range(natom):
|
|
atom_dset[i] = mf.cell.atom_pure_symbol(i)
|
|
qph5.create_dataset('nuclei/nucl_coord',data=atom_xyz)
|
|
qph5.create_dataset('nuclei/nucl_charge',data=mf.cell.atom_charges())
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
# ___ _
|
|
# | ._ _|_ _ _ ._ _. | _ |_) o
|
|
# _|_ | | |_ (/_ (_| | (_| | _> |_) |
|
|
# _|
|
|
#
|
|
kconserv = tools.get_kconserv(cell, kpts)
|
|
qph5.create_dataset('nuclei/kconserv',data=np.transpose(kconserv+1,(0,2,1)))
|
|
kcon_test = np.zeros((Nk,Nk,Nk),dtype=int)
|
|
for a in range(Nk):
|
|
for b in range(Nk):
|
|
for c in range(Nk):
|
|
kcon_test[a,c,b] = kconserv[a,b,c]+1
|
|
qph5.create_dataset('nuclei/kconserv_test',data=kcon_test)
|
|
|
|
|
|
with open('K.qp','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]
|
|
df_ao_tmp = np.zeros((nao,nao,naux,nkpt_pairs),dtype=np.complex128)
|
|
|
|
if print_ao_ints_df:
|
|
with open('D.qp','w') as outfile:
|
|
pass
|
|
with open('D.qp','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))
|
|
df_ao_tmp[i,j,iaux,k]=v
|
|
|
|
qph5.create_dataset('ao_two_e_ints/df_ao_integrals_real',data=df_ao_tmp.real)
|
|
qph5.create_dataset('ao_two_e_ints/df_ao_integrals_imag',data=df_ao_tmp.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])
|
|
df_mo_tmp = np.zeros((nmo,nmo,naux,nkpt_pairs),dtype=np.complex128)
|
|
with open('D_mo.qp','w') as outfile:
|
|
pass
|
|
with open('D_mo.qp','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))
|
|
df_mo_tmp[i,j,iaux,k]=v
|
|
qph5.create_dataset('mo_two_e_ints/df_mo_integrals_real',data=df_mo_tmp.real)
|
|
qph5.create_dataset('mo_two_e_ints/df_mo_integrals_imag',data=df_mo_tmp.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)
|
|
|
|
|
|
with open('W.qp','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 a>d: continue
|
|
#if ((c==d) and (a>b)): continue
|
|
ka = kpts[a]
|
|
|
|
with open('W.qp','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))
|
|
|
|
|
|
|
|
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
|
|
from pyscf.data import nist
|
|
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
|
|
neleca,nelecb = cell.nelec
|
|
atom_xyz = mf.cell.atom_coords()
|
|
if not(mf.cell.unit.startswith(('B','b','au','AU'))):
|
|
atom_xyz /= nist.BOHR # always convert to au
|
|
|
|
strtype=h5py.special_dtype(vlen=str)
|
|
atom_dset=qph5.create_dataset('nuclei/nucl_label',(natom,),dtype=strtype)
|
|
for i in range(natom):
|
|
atom_dset[i] = mf.cell.atom_pure_symbol(i)
|
|
qph5.create_dataset('nuclei/nucl_coord',data=atom_xyz)
|
|
qph5.create_dataset('nuclei/nucl_charge',data=mf.cell.atom_charges())
|
|
|
|
|
|
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']=neleca*Nk
|
|
qph5['electrons'].attrs['elec_beta_num']=nelecb*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.create_group('ao_two_e_ints')
|
|
qph5['ao_two_e_ints'].attrs['df_num']=naux
|
|
|
|
qph5['ao_basis'].attrs['ao_basis']=mf.cell.basis
|
|
ao_nucl=[mf.cell.bas_atom(i)+1 for i in range(nao)]
|
|
qph5.create_dataset('ao_basis/ao_nucl',data=Nk*ao_nucl)
|
|
|
|
|
|
# _
|
|
# |\ | _ | _ _. ._ |_) _ ._ | _ 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)
|
|
|
|
with open('C.qp','w') as outfile:
|
|
c_kpts = np.reshape(mo_k,(Nk,nao,nmo))
|
|
|
|
for ik in range(Nk):
|
|
shift1=ik*nao+1
|
|
shift2=ik*nmo+1
|
|
for i in range(nao):
|
|
for j in range(nmo):
|
|
cij = c_kpts[ik,i,j]
|
|
if abs(cij) > mo_coef_threshold:
|
|
outfile.write('%s %s %s %s\n' % (i+shift1, j+shift2, cij.real, cij.imag))
|
|
|
|
# ___
|
|
# | ._ _|_ _ _ ._ _. | _ |\/| _ ._ _
|
|
# _|_ | | |_ (/_ (_| | (_| | _> | | (_) | | (_)
|
|
# _|
|
|
|
|
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 = ('V',v_kpts_ao,ne_threshold)
|
|
ovlp_ao = ('S',np.reshape(mf.get_ovlp(cell=cell,kpts=kpts),(Nk,nao,nao)),ovlp_threshold)
|
|
kin_ao = ('T',np.reshape(cell.pbc_intor('int1e_kin',1,1,kpts=kpts),(Nk,nao,nao)),kin_threshold)
|
|
|
|
kin_ao_blocked=scipy.linalg.block_diag(*kin_ao[1])
|
|
ovlp_ao_blocked=scipy.linalg.block_diag(*ovlp_ao[1])
|
|
ne_ao_blocked=scipy.linalg.block_diag(*v_kpts_ao)
|
|
qph5.create_dataset('ao_one_e_ints/ao_integrals_kinetic_real',data=kin_ao_blocked.real)
|
|
qph5.create_dataset('ao_one_e_ints/ao_integrals_kinetic_imag',data=kin_ao_blocked.imag)
|
|
qph5.create_dataset('ao_one_e_ints/ao_integrals_overlap_real',data=ovlp_ao_blocked.real)
|
|
qph5.create_dataset('ao_one_e_ints/ao_integrals_overlap_imag',data=ovlp_ao_blocked.imag)
|
|
qph5.create_dataset('ao_one_e_ints/ao_integrals_n_e_real', data=ne_ao_blocked.real)
|
|
qph5.create_dataset('ao_one_e_ints/ao_integrals_n_e_imag', data=ne_ao_blocked.imag)
|
|
|
|
|
|
|
|
for name, intval_kpts_ao, thresh in (ne_ao, ovlp_ao, kin_ao):
|
|
if print_ao_ints_mono:
|
|
with open('%s.qp' % 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.qp' % 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)
|
|
qph5.create_dataset('nuclei/kconserv',data=np.transpose(kconserv+1,(0,2,1)))
|
|
kcon_test = np.zeros((Nk,Nk,Nk),dtype=int)
|
|
for a in range(Nk):
|
|
for b in range(Nk):
|
|
for c in range(Nk):
|
|
kcon_test[a,c,b] = kconserv[a,b,c]+1
|
|
qph5.create_dataset('nuclei/kconserv_test',data=kcon_test)
|
|
|
|
|
|
with open('K.qp','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]
|
|
df_ao_tmp = np.zeros((nao,nao,naux,nkpt_pairs),dtype=np.complex128)
|
|
|
|
if print_ao_ints_df:
|
|
with open('D.qp','w') as outfile:
|
|
pass
|
|
with open('D.qp','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))
|
|
df_ao_tmp[i,j,iaux,k]=v
|
|
|
|
qph5.create_dataset('ao_two_e_ints/df_ao_integrals_real',data=df_ao_tmp.real)
|
|
qph5.create_dataset('ao_two_e_ints/df_ao_integrals_imag',data=df_ao_tmp.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])
|
|
df_mo_tmp = np.zeros((nmo,nmo,naux,nkpt_pairs),dtype=np.complex128)
|
|
with open('D_mo.qp','w') as outfile:
|
|
pass
|
|
with open('D_mo.qp','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))
|
|
df_mo_tmp[i,j,iaux,k]=v
|
|
qph5.create_dataset('mo_two_e_ints/df_mo_integrals_real',data=df_mo_tmp.real)
|
|
qph5.create_dataset('mo_two_e_ints/df_mo_integrals_imag',data=df_mo_tmp.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('W.qp','w') as outfile:
|
|
pass
|
|
if print_mo_ints_bi:
|
|
with open('W_mo.qp','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 a > d: continue
|
|
#if ((c==d) and (a>b)): continue
|
|
ka = kpts[a]
|
|
|
|
if print_ao_ints_bi:
|
|
with open('W.qp','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('W_mo.qp','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)
|
|
|
|
|