def comp_apair_pp_libint(self, a1,a2):
""" Get's the vertex coefficient and conversion coefficients for a pair of atoms given by their atom indices """
from operator import mul
from pyscf.nao.m_prod_biloc import prod_biloc_c
if not hasattr(self, 'sv_pbloc_data') : raise RuntimeError('.sv_pbloc_data is absent')
assert a1>=0
assert a2>=0
t1 = timer()
sv = self.sv
aos = self.sv.ao_log
sp12 = np.require( np.array([sv.atom2sp[a] for a in (a1,a2)], dtype=c_int64), requirements='C')
rc12 = np.require( np.array([sv.atom2coord[a,:] for a in (a1,a2)]), requirements='C')
icc2a = np.require( np.array(self.ls_contributing(a1,a2), dtype=c_int64), requirements='C')
npmx = aos.sp2norbs[sv.atom2sp[a1]]*aos.sp2norbs[sv.atom2sp[a2]]
npac = sum([self.prod_log.sp2norbs[sv.atom2sp[ia]] for ia in icc2a ])
nout = c_int64(npmx**2+npmx*npac+10)
dout = np.require( zeros(nout.value), requirements='CW')
libnao.vrtx_cc_apair( sp12.ctypes.data_as(POINTER(c_int64)), rc12.ctypes.data_as(POINTER(c_double)), icc2a.ctypes.data_as(POINTER(c_int64)), c_int64(len(icc2a)), dout.ctypes.data_as(POINTER(c_double)), nout )
if dout[0]<1: return None
nnn = np.array(dout[0:3], dtype=int)
nnc = np.array([dout[8],dout[7]], dtype=int)
ncc = int(dout[9])
if ncc!=len(icc2a): raise RuntimeError('ncc!=len(icc2a)')
s = 10; f=s+np.prod(nnn); vrtx = dout[s:f].reshape(nnn)
s = f; f=s+np.prod(nnc); ccoe = dout[s:f].reshape(nnc)
icc2s = np.zeros(len(icc2a)+1, dtype=np.int64)
for icc,a in enumerate(icc2a): icc2s[icc+1] = icc2s[icc] + self.prod_log.sp2norbs[sv.atom2sp[a]]
pbiloc = prod_biloc_c(atoms=array([a2,a1]),vrtx=vrtx,cc2a=icc2a,cc2s=icc2s,cc=ccoe)
return pbiloc
def comp_apair_pp_libint(self, a1,a2):
""" Get's the vertex coefficient and conversion coefficients for a pair of atoms given by their atom indices """
from operator import mul
from pyscf.nao.m_prod_biloc import prod_biloc_c
if not hasattr(self, 'sv_pbloc_data') : raise RuntimeError('.sv_pbloc_data is absent')
assert a1>=0
assert a2>=0
t1 = timer()
sv = self.sv
aos = self.sv.ao_log
sp12 = np.require( np.array([sv.atom2sp[a] for a in (a1,a2)], dtype=c_int64), requirements='C')
rc12 = np.require( np.array([sv.atom2coord[a,:] for a in (a1,a2)]), requirements='C')
icc2a = np.require( np.array(self.ls_contributing(a1,a2), dtype=c_int64), requirements='C')
npmx = aos.sp2norbs[sv.atom2sp[a1]]*aos.sp2norbs[sv.atom2sp[a2]]
npac = sum([self.prod_log.sp2norbs[sv.atom2sp[ia]] for ia in icc2a ])
nout = c_int64(npmx**2+npmx*npac+10)
dout = np.require( zeros(nout.value), requirements='CW')
libnao.vrtx_cc_apair( sp12.ctypes.data_as(POINTER(c_int64)), rc12.ctypes.data_as(POINTER(c_double)), icc2a.ctypes.data_as(POINTER(c_int64)), c_int64(len(icc2a)), dout.ctypes.data_as(POINTER(c_double)), nout )
if dout[0]<1: return None
nnn = np.array(dout[0:3], dtype=int)
nnc = np.array([dout[8],dout[7]], dtype=int)
ncc = int(dout[9])
if ncc!=len(icc2a): raise RuntimeError('ncc!=len(icc2a)')
s = 10; f=s+np.prod(nnn); vrtx = dout[s:f].reshape(nnn)
s = f; f=s+np.prod(nnc); ccoe = dout[s:f].reshape(nnc)
icc2s = np.zeros(len(icc2a)+1, dtype=np.int64)
for icc,a in enumerate(icc2a): icc2s[icc+1] = icc2s[icc] + self.prod_log.sp2norbs[sv.atom2sp[a]]
pbiloc = prod_biloc_c(atoms=array([a2,a1]),vrtx=vrtx,cc2a=icc2a,cc2s=icc2s,cc=ccoe)
return pbiloc
def init_prod_basis_pp_batch(self, nao, **kw):
""" Talman's procedure should be working well with Pseudo-Potential starting point."""
from pyscf.nao import prod_log_c
from pyscf.nao.m_prod_biloc import prod_biloc_c
sv = nao
t1 = timer()
self.norbs = sv.norbs
self.init_inp_param_prod_log_dp(sv, **kw)
#t2 = timer(); print(' after init_inp_param_prod_log_dp ', t2-t1); t1=timer()
data = self.chain_data()
libnao.init_vrtx_cc_batch(data.ctypes.data_as(POINTER(c_double)),
c_int64(len(data)))
self.sv_pbloc_data = True
aos = sv.ao_log
p2srncc, p2npac, p2atoms = [], [], []
for a1, [sp1, ra1] in enumerate(zip(sv.atom2sp, sv.atom2coord)):
rc1 = aos.sp2rcut[sp1]
for a2, [sp2, ra2] in enumerate(
zip(sv.atom2sp[a1 + 1:], sv.atom2coord[a1 + 1:])):
a2 += a1 + 1
rc2, dist = aos.sp2rcut[sp2], sqrt(((ra1 - ra2)**2).sum())
if dist > rc1 + rc2: continue
cc2atom = self.ls_contributing(a1, a2)
p2atoms.append([a1, a2])
p2srncc.append([sp1, sp2] + list(ra1) + list(ra2) +
[len(cc2atom)] + list(cc2atom))
p2npac.append(
sum([
self.prod_log.sp2norbs[sv.atom2sp[ia]]
for ia in cc2atom
]))
#print(np.asarray(p2srncc))
p2ndp = np.require(zeros(len(p2srncc), dtype=np.int64),
requirements='CW')
p2srncc_cp = np.require(np.asarray(p2srncc), requirements='C')
npairs = p2srncc_cp.shape[0]
self.npairs = npairs
self.bp2info = [
] # going to be indices of atoms, list of contributing centres, conversion coefficients
if npairs > 0: # Conditional fill of the self.bp2info if there are bilocal pairs (natoms>1)
ld = p2srncc_cp.shape[1]
#print('npairs p2srncc_cp.shape', npairs, p2srncc_cp.shape)
if nao.verbosity > 0:
t2 = timer()
print('call vrtx_cc_batch ', t2 - t1, 'npairs ', npairs)
t1 = timer()
libnao.vrtx_cc_batch(c_int64(npairs),
p2srncc_cp.ctypes.data_as(POINTER(c_double)),
c_int64(ld),
p2ndp.ctypes.data_as(POINTER(c_int64)))
if nao.verbosity > 0:
t2 = timer()
print('after vrtx_cc_batch ', t2 - t1)
t1 = timer()
nout = 0
sp2norbs = sv.ao_log.sp2norbs
for srncc, ndp, npac in zip(p2srncc, p2ndp, p2npac):
sp1, sp2 = srncc[0], srncc[1]
nout = nout + ndp * sp2norbs[sp1] * sp2norbs[sp2] + npac * ndp
dout = np.require(zeros(nout), requirements='CW')
libnao.get_vrtx_cc_batch(c_int64(0), c_int64(npairs),
dout.ctypes.data_as(POINTER(c_double)),
c_int64(nout))
f = 0
for srncc, ndp, npac, [a1, a2] in zip(p2srncc, p2ndp, p2npac,
p2atoms):
if ndp < 1: continue
sp1, sp2, ncc = srncc[0], srncc[1], srncc[8]
icc2a = array(srncc[9:9 + ncc], dtype=int64)
nnn = np.array((ndp, sp2norbs[sp2], sp2norbs[sp1]),
dtype=int64)
nnc = np.array([ndp, npac], dtype=int64)
s = f
f = s + np.prod(nnn)
vrtx = dout[s:f].reshape(nnn)
s = f
f = s + np.prod(nnc)
ccoe = dout[s:f].reshape(nnc)
icc2s = np.zeros(len(icc2a) + 1, dtype=int64)
for icc, a in enumerate(icc2a):
icc2s[
icc +
1] = icc2s[icc] + self.prod_log.sp2norbs[sv.atom2sp[a]]
pbiloc = prod_biloc_c(atoms=array([a2, a1]),
vrtx=vrtx,
cc2a=icc2a,
cc2s=icc2s,
cc=ccoe)
self.bp2info.append(pbiloc)
#t2 = timer(); print('after loop ', t2-t1); t1=timer()
self.dpc2s, self.dpc2t, self.dpc2sp = self.init_c2s_domiprod(
) # dominant product's counting
self.npdp = self.dpc2s[-1]
#t2 = timer(); print('after init_c2s_domiprod ', t2-t1); t1=timer()
return self
def pb_ae(self, sv, tol_loc=1e-5, tol_biloc=1e-6, ac_rcut_ratio=1.0):
""" It should work with GTOs as well."""
from pyscf.nao import coulomb_am, get_atom2bas_s, conv_yzx2xyz_c, prod_log_c, ls_part_centers, comp_coulomb_den
from pyscf.nao.m_overlap_coo import overlap_coo
from pyscf.nao.m_prod_biloc import prod_biloc_c
from scipy.sparse import csr_matrix
from pyscf import gto
self.sv = sv
self.tol_loc = tol_loc
self.tol_biloc = tol_biloc
self.ac_rcut_ratio = ac_rcut_ratio
self.ac_rcut = ac_rcut_ratio * max(sv.ao_log.sp2rcut)
self.prod_log = prod_log_c().init_prod_log_dp(
sv.ao_log, tol_loc) # local basis (for each specie)
self.hkernel_csr = csr_matrix(
overlap_coo(sv, self.prod_log,
coulomb_am)) # compute local part of Coulomb interaction
self.c2s = zeros(
(sv.natm + 1), dtype=int64
) # global product Center (atom) -> start in case of atom-centered basis
for gc, sp in enumerate(sv.atom2sp):
self.c2s[gc + 1] = self.c2s[gc] + self.prod_log.sp2norbs[sp] #
c2s = self.c2s # What is the meaning of this copy ?? ... This is a pointer to self.c2s
self.bp2info = [
] # going to be some information including indices of atoms, list of contributing centres, conversion coefficients
for ia1, n1 in enumerate(sv.atom2s[1:] - sv.atom2s[0:-1]):
for ia2, n2 in enumerate(sv.atom2s[ia1 + 2:] - sv.atom2s[ia1 + 1:-1]):
ia2 += ia1 + 1
mol2 = gto.Mole(atom=[sv._atom[ia1], sv._atom[ia2]],
basis=sv.basis,
unit='bohr').build()
bs = get_atom2bas_s(mol2._bas)
ss = (bs[0], bs[1], bs[1], bs[2], bs[0], bs[1], bs[1], bs[2])
eri = mol2.intor('cint2e_sph',
shls_slice=ss).reshape(n1, n2, n1, n2)
eri = conv_yzx2xyz_c(mol2).conv_yzx2xyz_4d(eri, 'pyscf2nao',
ss).reshape(
n1 * n2, n1 * n2)
ee, xx = np.linalg.eigh(
eri
) # This the simplest way. TODO: diag in each m-channel separately
mu2d = [domi for domi, eva in enumerate(ee) if eva > tol_biloc
] # The choice of important linear combinations is here
nprod = len(mu2d)
if nprod < 1:
continue # Skip the rest of operations in case there is no large linear combinations.
# add new vertex
vrtx = zeros([nprod, n1, n2])
for p, d in enumerate(mu2d):
vrtx[p, :, :] = xx[:, d].reshape(n1, n2)
#print(ia1,ia2,nprod,abs(einsum('pab,qab->pq', lambdx, lambdx).reshape(nprod,nprod)-np.identity(nprod)).sum())
lc2c = ls_part_centers(
sv, ia1, ia2, ac_rcut_ratio) # list of participating centers
lc2s = zeros(
(len(lc2c) + 1), dtype=int64
) # local product center -> start for the current bilocal pair
for lc, c in enumerate(lc2c):
lc2s[lc + 1] = lc2s[lc] + self.prod_log.sp2norbs[sv.atom2sp[c]]
npbp = lc2s[
-1] # size of the functions which will contribute to the given pair ia1,ia2
hkernel_bp = np.zeros(
(npbp,
npbp)) # this is local kernel for the current bilocal pair
for lc1, c1 in enumerate(lc2c):
for lc2, c2 in enumerate(lc2c):
for i1 in range(lc2s[lc1 + 1] - lc2s[lc1]):
for i2 in range(lc2s[lc2 + 1] - lc2s[lc2]):
hkernel_bp[i1 + lc2s[lc1], i2 + lc2s[
lc2]] = self.hkernel_csr[i1 + c2s[c1], i2 + c2s[
c2]] # element-by-element construction here
inv_hk = np.linalg.inv(hkernel_bp)
llp = np.zeros((npbp, nprod))
for c, s, f in zip(lc2c, lc2s, lc2s[1:]):
n3 = sv.atom2s[c + 1] - sv.atom2s[c]
lcd = self.prod_log.sp2lambda[sv.atom2sp[c]]
mol3 = gto.Mole(
atom=[sv._atom[ia1], sv._atom[ia2], sv._atom[c]],
basis=sv.basis,
unit='bohr',
spin=1).build()
bs = get_atom2bas_s(mol3._bas)
ss = (bs[2], bs[3], bs[2], bs[3], bs[0], bs[1], bs[1], bs[2])
tci_ao = mol3.intor('cint2e_sph',
shls_slice=ss).reshape(n3, n3, n1, n2)
tci_ao = conv_yzx2xyz_c(mol3).conv_yzx2xyz_4d(
tci_ao, 'pyscf2nao', ss)
lp = einsum('lcd,cdp->lp', lcd,
einsum('cdab,pab->cdp', tci_ao, vrtx))
llp[s:f, :] = lp
cc = einsum('ab,bc->ac', inv_hk, llp)
pbiloc = prod_biloc_c(atoms=array([ia1, ia2]),
vrtx=vrtx,
cc2a=lc2c,
cc2s=lc2s,
cc=cc.T)
self.bp2info.append(pbiloc)
#print(ia1, ia2, len(mu2d), lc2c, hkernel_bp.sum(), inv_hk.sum())
self.dpc2s, self.dpc2t, self.dpc2sp = self.init_c2s_domiprod(
) # dominant product's counting
return self
def init_prod_basis_pp_batch(self, nao, **kw):
""" Talman's procedure should be working well with Pseudo-Potential starting point."""
from pyscf.nao import prod_log_c
from pyscf.nao.m_prod_biloc import prod_biloc_c
sv = nao
t1 = timer()
self.norbs = sv.norbs
self.init_inp_param_prod_log_dp(sv, **kw)
#t2 = timer(); print(' after init_inp_param_prod_log_dp ', t2-t1); t1=timer()
data = self.chain_data()
libnao.init_vrtx_cc_batch(data.ctypes.data_as(POINTER(c_double)), c_int64(len(data)))
self.sv_pbloc_data = True
aos = sv.ao_log
p2srncc,p2npac,p2atoms = [],[],[]
for a1,[sp1,ra1] in enumerate(zip(sv.atom2sp, sv.atom2coord)):
rc1 = aos.sp2rcut[sp1]
for a2,[sp2,ra2] in enumerate(zip(sv.atom2sp[a1+1:], sv.atom2coord[a1+1:])):
a2+=a1+1
rc2,dist = aos.sp2rcut[sp2], sqrt(((ra1-ra2)**2).sum())
if dist>rc1+rc2 : continue
cc2atom = self.ls_contributing(a1,a2)
p2atoms.append([a1,a2])
p2srncc.append([sp1,sp2]+list(ra1)+list(ra2)+[len(cc2atom)]+list(cc2atom))
p2npac.append( sum([self.prod_log.sp2norbs[sv.atom2sp[ia]] for ia in cc2atom ]))
#print(np.asarray(p2srncc))
p2ndp = np.require( zeros(len(p2srncc), dtype=np.int64), requirements='CW')
p2srncc_cp = np.require( np.asarray(p2srncc), requirements='C')
npairs = p2srncc_cp.shape[0]
self.npairs = npairs
self.bp2info = [] # going to be indices of atoms, list of contributing centres, conversion coefficients
if npairs>0 : # Conditional fill of the self.bp2info if there are bilocal pairs (natoms>1)
ld = p2srncc_cp.shape[1]
#print('npairs p2srncc_cp.shape', npairs, p2srncc_cp.shape)
#t2 = timer(); print('call vrtx_cc_batch ', t2-t1, 'npairs ', npairs); t1=timer()
libnao.vrtx_cc_batch( c_int64(npairs), p2srncc_cp.ctypes.data_as(POINTER(c_double)),
c_int64(ld), p2ndp.ctypes.data_as(POINTER(c_int64)))
#t2 = timer(); print('after vrtx_cc_batch ', t2-t1); t1=timer()
nout = 0
sp2norbs = sv.ao_log.sp2norbs
for srncc,ndp,npac in zip(p2srncc,p2ndp,p2npac):
sp1,sp2 = srncc[0],srncc[1]
nout = nout + ndp*sp2norbs[sp1]*sp2norbs[sp2]+npac*ndp
dout = np.require( zeros(nout), requirements='CW')
libnao.get_vrtx_cc_batch(c_int64(0),c_int64(npairs),dout.ctypes.data_as(POINTER(c_double)),c_int64(nout))
f = 0
for srncc,ndp,npac,[a1,a2] in zip(p2srncc,p2ndp,p2npac,p2atoms):
if ndp<1 : continue
sp1,sp2,ncc = srncc[0],srncc[1],srncc[8]
icc2a = array(srncc[9:9+ncc], dtype=int64)
nnn = np.array((ndp,sp2norbs[sp2],sp2norbs[sp1]), dtype=int64)
nnc = np.array([ndp,npac], dtype=int64)
s = f; f=s+np.prod(nnn); vrtx = dout[s:f].reshape(nnn)
s = f; f=s+np.prod(nnc); ccoe = dout[s:f].reshape(nnc)
icc2s = np.zeros(len(icc2a)+1, dtype=int64)
for icc,a in enumerate(icc2a): icc2s[icc+1] = icc2s[icc] + self.prod_log.sp2norbs[sv.atom2sp[a]]
pbiloc = prod_biloc_c(atoms=array([a2,a1]),vrtx=vrtx,cc2a=icc2a,cc2s=icc2s,cc=ccoe)
self.bp2info.append(pbiloc)
#t2 = timer(); print('after loop ', t2-t1); t1=timer()
self.dpc2s,self.dpc2t,self.dpc2sp = self.init_c2s_domiprod() # dominant product's counting
self.npdp = self.dpc2s[-1]
#t2 = timer(); print('after init_c2s_domiprod ', t2-t1); t1=timer()
return self
def pb_ae(self, sv, tol_loc=1e-5, tol_biloc=1e-6, ac_rcut_ratio=1.0):
""" It should work with GTOs as well."""
from pyscf.nao import coulomb_am, get_atom2bas_s, conv_yzx2xyz_c, prod_log_c, ls_part_centers, comp_coulomb_den
from pyscf.nao.m_overlap_coo import overlap_coo
from pyscf.nao.m_prod_biloc import prod_biloc_c
from scipy.sparse import csr_matrix
from pyscf import gto
self.sv = sv
self.tol_loc = tol_loc
self.tol_biloc = tol_biloc
self.ac_rcut_ratio = ac_rcut_ratio
self.ac_rcut = ac_rcut_ratio*max(sv.ao_log.sp2rcut)
self.prod_log = prod_log_c().init_prod_log_dp(sv.ao_log, tol_loc) # local basis (for each specie)
self.hkernel_csr = csr_matrix(overlap_coo(sv, self.prod_log, coulomb_am)) # compute local part of Coulomb interaction
self.c2s = zeros((sv.natm+1), dtype=int64) # global product Center (atom) -> start in case of atom-centered basis
for gc,sp in enumerate(sv.atom2sp): self.c2s[gc+1]=self.c2s[gc]+self.prod_log.sp2norbs[sp] #
c2s = self.c2s # What is the meaning of this copy ?? ... This is a pointer to self.c2s
self.bp2info = [] # going to be some information including indices of atoms, list of contributing centres, conversion coefficients
for ia1,n1 in enumerate(sv.atom2s[1:]-sv.atom2s[0:-1]):
for ia2,n2 in enumerate(sv.atom2s[ia1+2:]-sv.atom2s[ia1+1:-1]):
ia2 += ia1+1
mol2 = gto.Mole(atom=[sv._atom[ia1], sv._atom[ia2]], basis=sv.basis, unit='bohr').build()
bs = get_atom2bas_s(mol2._bas)
ss = (bs[0],bs[1], bs[1],bs[2], bs[0],bs[1], bs[1],bs[2])
eri = mol2.intor('cint2e_sph', shls_slice=ss).reshape(n1,n2,n1,n2)
eri = conv_yzx2xyz_c(mol2).conv_yzx2xyz_4d(eri, 'pyscf2nao', ss).reshape(n1*n2,n1*n2)
ee,xx = np.linalg.eigh(eri) # This the simplest way. TODO: diag in each m-channel separately
mu2d = [domi for domi,eva in enumerate(ee) if eva>tol_biloc] # The choice of important linear combinations is here
nprod=len(mu2d)
if nprod<1: continue # Skip the rest of operations in case there is no large linear combinations.
# add new vertex
vrtx = zeros([nprod,n1,n2])
for p,d in enumerate(mu2d): vrtx[p,:,:] = xx[:,d].reshape(n1,n2)
#print(ia1,ia2,nprod,abs(einsum('pab,qab->pq', lambdx, lambdx).reshape(nprod,nprod)-np.identity(nprod)).sum())
lc2c = ls_part_centers(sv, ia1, ia2, ac_rcut_ratio) # list of participating centers
lc2s = zeros((len(lc2c)+1), dtype=int64) # local product center -> start for the current bilocal pair
for lc,c in enumerate(lc2c): lc2s[lc+1]=lc2s[lc]+self.prod_log.sp2norbs[sv.atom2sp[c]]
npbp = lc2s[-1] # size of the functions which will contribute to the given pair ia1,ia2
hkernel_bp = np.zeros((npbp, npbp)) # this is local kernel for the current bilocal pair
for lc1,c1 in enumerate(lc2c):
for lc2,c2 in enumerate(lc2c):
for i1 in range(lc2s[lc1+1]-lc2s[lc1]):
for i2 in range(lc2s[lc2+1]-lc2s[lc2]):
hkernel_bp[i1+lc2s[lc1],i2+lc2s[lc2]] = self.hkernel_csr[i1+c2s[c1],i2+c2s[c2]] # element-by-element construction here
inv_hk = np.linalg.inv(hkernel_bp)
llp = np.zeros((npbp, nprod))
for c,s,f in zip(lc2c,lc2s,lc2s[1:]):
n3 = sv.atom2s[c+1]-sv.atom2s[c]
lcd = self.prod_log.sp2lambda[sv.atom2sp[c]]
mol3 = gto.Mole(atom=[sv._atom[ia1], sv._atom[ia2], sv._atom[c]], basis=sv.basis, unit='bohr', spin=1).build()
bs = get_atom2bas_s(mol3._bas)
ss = (bs[2],bs[3], bs[2],bs[3], bs[0],bs[1], bs[1],bs[2])
tci_ao = mol3.intor('cint2e_sph', shls_slice=ss).reshape(n3,n3,n1,n2)
tci_ao = conv_yzx2xyz_c(mol3).conv_yzx2xyz_4d(tci_ao, 'pyscf2nao', ss)
lp = einsum('lcd,cdp->lp', lcd,einsum('cdab,pab->cdp', tci_ao, vrtx))
llp[s:f,:] = lp
cc = einsum('ab,bc->ac', inv_hk, llp)
pbiloc = prod_biloc_c(atoms=array([ia1,ia2]), vrtx=vrtx, cc2a=lc2c, cc2s=lc2s, cc=cc.T)
self.bp2info.append(pbiloc)
#print(ia1, ia2, len(mu2d), lc2c, hkernel_bp.sum(), inv_hk.sum())
self.dpc2s,self.dpc2t,self.dpc2sp = self.init_c2s_domiprod() # dominant product's counting
return self