Пример #1
0
def s2n(N, tmpdir='/tmp', Sg=1, Sv=1):
    """
    S[2]*N linear transformation:
    <[q,k]> = <[E(Sg)_{ij}, k_{kl}, E(Sv)_{kl}]> = 
            = k_{kl} [E_{il}d(kj) - E(kj)d(il)]
            = k(jl)E(SgSv)(il) - k(ki)E(SgSv)(kj)
            = D(SgSv)k.T(ij) - k.TD(SgSv)(ij)
            = [D(SgSv), k.T](ij)
    """


    SIRIFC = os.path.join(tmpdir, 'SIRIFC')
    AOONEINT = os.path.join(tmpdir, 'AOONEINT')
    AOTWOINT = os.path.join(tmpdir, 'AOTWOINT')
    LUINDF = os.path.join(tmpdir, 'LUINDF')

    ifc = sirifc.sirifc(SIRIFC)
    cmo = ifc.cmo.unblock()

    S = one.read('OVERLAP',  filename=AOONEINT).unblock().unpack()

    da, db = dens.Dab(SIRIFC)

    kN = rspvec.tomat(N, ifc, tmpdir=tmpdir).T
    kn = cmo*kN*cmo.T

    dak = (kn.T*S*da - da*S*kn.T)
    dbk = (kn.T*S*db - db*S*kn.T)*Sv

    gv = -rspvec.tovec(cmo.T*S*(dak+Sg*dbk)*S*cmo, ifc)

    return gv
Пример #2
0
 def test_tovec(self):
     Nx = rspvec.read("XDIPLEN", propfile=self.RSPVEC)["XDIPLEN"]
     kx = rspvec.tomat(Nx, self.ifc, tmpdir=self.tmpdir)
     Nx = rspvec.tovec(kx, self.ifc, tmpdir=self.tmpdir)
     this = Nx[44]
     ref = 0.75732690
     assert this == approx(ref)
Пример #3
0
def e2n(N, tmpdir='/tmp', hfx=1, Sg=1, Sv=1):
    """
    E[2]*N linear transformation:

     [k,F] = [k(pq)E(Sv)(pq), F(rs)E(rs)]
           = k(pq)F(rs) (E(ps)d(rq) - E(rq)d(ps))
           = k(pq)F(ps)E(ps) - k(pq)F(rp)E(rq)
           = [k,F](pq)E(pq)
           = kF
    <[q,kF]> = <[E_{pq}, kF(rs)E(rs)]>
             = kF(rs) <E(ps)d(rq) - E(rq)d(ps)>
             = kF(qs)D(ps) - kF(rp)D(rq)
             = [D, kF.T](pq)
    kD = <[k, E(pq)]>
       = <[k(rs) E(rs), E(pq)]>
       = k(rs) (E(rq)d(ps) - E(ps)d(rq))
       = k(rp)D(rq) - k(qs)D(ps)
       = [k.T, D](p,q)
    Fk = F[kD]
    """

    SIRIFC = os.path.join(tmpdir, 'SIRIFC')
    AOONEINT = os.path.join(tmpdir, 'AOONEINT')
    AOTWOINT = os.path.join(tmpdir, 'AOTWOINT')
    LUINDF = os.path.join(tmpdir, 'LUINDF')

    ifc = sirifc.sirifc(SIRIFC)
    cmo = get_cmo(AOONEINT, SIRIFC)

    h = one.read('ONEHAMIL', filename=AOONEINT).unblock().unpack()
    S = one.read('OVERLAP',  filename=AOONEINT).unblock().unpack().view(util.full.matrix)

    da, db = get_densities(SIRIFC)

    kN = rspvec.tomat(N, ifc, tmpdir=tmpdir).view(util.full.matrix).T
    kn = (cmo*kN*cmo.T).view(util.full.matrix)

    dak = (kn.T*S*da - da*S*kn.T)
    dbk = (kn.T*S*db - db*S*kn.T)*Sv


    (fa, fb), = two.fockab((da, db),  filename=AOTWOINT, hfx=hfx)
    fa += h; fb += h
    (fak, fbk), = two.fockab((dak, dbk), filename=AOTWOINT, hfx=hfx)

    kfa = (S*kn*fa - fa*kn*S)
    kfb = (S*kn*fb - fb*kn*S)*Sv

    fa = fak + kfa
    fb = fbk + kfb

    gao = S*(da*fa.T + Sg*db*fb.T) - (fa.T*da + Sg*fb.T*db)*S
    gm = cmo.T*gao*cmo

    # sign convention <[q,[k,F]]> = -E[2]*N
    gv = - rspvec.tovec(gm, ifc)

    return gv
Пример #4
0
def A2B(*args, **kwargs):
   
    pA, pB, ifc = args
    tmpdir = kwargs.get("tmpdir", ".")

    AOONEINT = os.path.join(tmpdir, "AOONEINT")
    S = one.read(label = "OVERLAP", filename = AOONEINT).unblock().unpack()

    cmo = ifc.cmo.unblock()
    mA = pA["matrix"]
    kB = cmo*pB["kappa"]*cmo.T

    BA = S*kB*mA - mA*kB*S

    da, db = dens.Dab(ifc_=ifc)
    G = cmo.T*(S*(da*BA.T + db*BA.T) - (BA.T*da + BA.T*db)*S)*cmo
    Gv = rspvec.tovec(G, ifc)
    return Gv
Пример #5
0
def B2C(*args, **kwargs):
   
    pB, pC, ifc = args
    tmpdir = kwargs.get("tmpdir", ".")

    AOONEINT = os.path.join(tmpdir, "AOONEINT")
    S = one.read(label = "OVERLAP", filename = AOONEINT).unblock().unpack()

    cmo = ifc.cmo.unblock()
    mB = pB["matrix"]
    mC = pC["matrix"]
    kB = cmo*pB["kappa"]*cmo.T
    kC = cmo*pC["kappa"]*cmo.T


    kBmC = S*kB*mC - mC*kB*S
    kCmB = S*kC*mB - mB*kC*S
    BC = kBmC + kCmB

    da, db = dens.Dab(ifc_=ifc)
    G = cmo.T*(S*(da*BC.T + db*BC.T) - (BC.T*da + BC.T*db)*S)*cmo
    Gv = rspvec.tovec(G, ifc)
    return Gv
Пример #6
0
def E3(pB, pC, ifc, **kwargs):
    """ Emulate the so called E3 contribution to a quadratic response function
        <<A; B, C>> = NA  E3 (NB NC +  NC NB) + A2 (NB NC + NC NB) + NA (B2 NC + C2 NB)

        Emulation of current Dalton implementation in terms of high spin fock matrices
        Closed and open shell matrices
        Dc = inactive 
        Do = -active
        Fc = Fa+Q
        Fo = ? CHECK

        Formulas
        1/2*[qa, [kb, [kc, H]]] + P(b,c)

        [kc, H] = (p~q|rs)H(Sc, 0) + (pq|r~s) H(0, Sc)
        [kb, [kc, H]] 
                = (p~~q|rs)H(SbSc, 0) + (p~q|r~s) H(Sb, Sc)
                + (p~q|r~s)H(Sc, Sb) + (pq|r~~s) H(0, SbSc)

        and for 
        H(S1, S2) generates Fock from (D(S1) g D(S2) - Da g Da - Db g Db
        F(S1, S2) = E(S1) g D(S2) - D(S1) g E(S2) - Ea g Da - Da g Ea - Eb g Db - Db g Eb
                  = Ea [ g D(S2) - D(S1) g - g Da - Da g ]
                  + Eb [ S1 g D(S2) - D(S1) g S2  - g Db - Db g ]
    """


    tmpdir = kwargs.get('tmpdir', '/tmp')
    AOONEINT = os.path.join(tmpdir, "AOONEINT")
    h = one.read(label='ONEHAMIL', filename=AOONEINT).unpack().unblock()
    S = one.read(label='OVERLAP', filename=AOONEINT).unblock().unpack()

    AOTWOINT = os.path.join(tmpdir, "AOTWOINT")
    kwargs['filename'] = AOTWOINT


    cmo = ifc.cmo.unblock()
    kB = cmo*pB["kappa"]*cmo.T
    kC = cmo*pC["kappa"]*cmo.T
    kB_ = kB*S
    _kB = S*kB
    kC_ = kC*S
    _kC = S*kC

    sB = pB.get("spin", 1)
    sC = pC.get("spin", 1)
   
    #
    # Fock matrices
    #
    da, db = dens.Dab(ifc_=ifc)
    (fa, fb), = two.fockab((da, db), **kwargs)
    fa += h
    fb += h
    Bfa, Bfb = [_kB*f - f*kB_ for f in (fa, sB*fb)]
    Cfa, Cfb = [_kC*f - f*kC_ for f in (fa, sC*fb)]
    
    BCfa, BCfb = [_kB*Cf - Cf*kB_ for Cf in (Cfa, sB*Cfb)]
    CBfa, CBfb = [_kC*Bf - Bf*kC_ for Bf in (Bfa, sC*Bfb)]

    daB, dbB = [_kB.T*d - d*kB_.T  for d in (da, sB*db)]
    (faB, fbB), = two.fockab((daB, dbB), **kwargs)
    CfaB, CfbB = [_kC*fB - fB*kC_ for fB in (faB, sC*fbB)]

    daC, dbC = [_kC.T*d - d*kC_.T  for d in (da, sC*db)]
    (faC, fbC), = two.fockab((daC, dbC), **kwargs)
    BfaC, BfbC = [_kB*fC - fC*kB_ for fC in (faC, sB*fbC)]
    
    daBC, dbBC  = (_kB.T*dC - dC*kB_.T for dC in (daC, sB*dbC))
    daCB, dbCB  = (_kC.T*dB - dB*kC_.T for dB in (daB, sC*dbB))
    daBC = 0.5*(daBC + daCB)
    dbBC = 0.5*(dbBC + dbCB)
    (faBC, fbBC), = two.fockab((daBC, dbBC), **kwargs)

 #
 # Add all focks
 #
    fa = faBC + BfaC + CfaB + .5*(BCfa + CBfa)
    fb = fbBC + BfbC + CfbB + .5*(BCfb + CBfb)

    G = cmo.T*(S*(da*fa.T + db*fb.T) - (fa.T*da + fb.T*db)*S)*cmo
    #G =  cmo.T*(S*da*fa.T - fa.T*da *S)*cmo + \
    #      cmo.T*(S*db*fb.T - fb.T*db *S)*cmo 


    Gv = rspvec.tovec(G, ifc)
    #print Gv

    return Gv
Пример #7
0
 def mat2vec(self, mat):
     ifc = self._sirifc()
     mat = rspvec.tovec(np.array(mat), ifc)
     return mat
Пример #8
0
 def test_tovec(self):
     ref = rspvec.read("XDIPLEN", propfile=self.RSPVEC)["XDIPLEN"]
     kx = rspvec.tomat(ref, self.ifc, tmpdir=self.tmpdir)
     this = rspvec.tovec(kx, self.ifc, tmpdir=self.tmpdir)
     np.testing.assert_almost_equal(this, ref)