Python numpy.ix_方法代碼示例

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def padded_mo_energy(mp, mo_energy):
    """
    Pads energies of active MOs.

    Args:
        mp (:class:`MP2`): An instantiation of an SCF or post-Hartree-Fock object.
        mo_energy (ndarray): original non-padded molecular energies;

    Returns:
        Padded molecular energies.
    """
    frozen_mask = get_frozen_mask(mp)
    padding_convention = padding_k_idx(mp, kind="joint")
    nkpts = mp.nkpts

    result = np.zeros((nkpts, mp.nmo), dtype=mo_energy[0].dtype)
    for k in range(nkpts):
        result[np.ix_([k], padding_convention[k])] = mo_energy[k][frozen_mask[k]]

    return result 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def padded_mo_coeff(mp, mo_coeff):
    """
    Pads coefficients of active MOs.

    Args:
        mp (:class:`MP2`): An instantiation of an SCF or post-Hartree-Fock object.
        mo_coeff (ndarray): original non-padded molecular coefficients;

    Returns:
        Padded molecular coefficients.
    """
    frozen_mask = get_frozen_mask(mp)
    padding_convention = padding_k_idx(mp, kind="joint")
    nkpts = mp.nkpts

    result = np.zeros((nkpts, mo_coeff[0].shape[0], mp.nmo), dtype=mo_coeff[0].dtype)
    for k in range(nkpts):
        result[np.ix_([k], np.arange(result.shape[1]), padding_convention[k])] = mo_coeff[k][:, frozen_mask[k]]

    return result 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def padded_mo_energy(mp, mo_energy):
    """
    Pads energies of active MOs.

    Args:
        mp (:class:`MP2`): An instantiation of an SCF or post-Hartree-Fock object.
        mo_energy (ndarray): original non-padded molecular energies;

    Returns:
        Padded molecular energies.
    """
    frozen_mask = get_frozen_mask(mp)
    padding_convention = padding_k_idx(mp, kind="joint")
    nkpts = mp.nkpts

    result = (np.zeros((nkpts, mp.nmo), dtype=mo_energy[0][0].dtype),
              np.zeros((nkpts, mp.nmo), dtype=mo_energy[0][0].dtype))
    for spin in [0, 1]:
        for k in range(nkpts):
            result[spin][np.ix_([k], padding_convention[k])] = mo_energy[spin][k][frozen_mask[k]]

    return result 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def padded_mo_coeff(mp, mo_coeff):
    """
    Pads coefficients of active MOs.

    Args:
        mp (:class:`MP2`): An instantiation of an SCF or post-Hartree-Fock object.
        mo_coeff (ndarray): original non-padded molecular coefficients;

    Returns:
        Padded molecular coefficients.
    """
    frozen_mask = get_frozen_mask(mp)
    padding_convention = padding_k_idx(mp, kind="joint")
    nkpts = mp.nkpts

    result = (np.zeros((nkpts, mo_coeff[0][0].shape[0], mp.nmo[0]), dtype=mo_coeff[0][0].dtype),
              np.zeros((nkpts, mo_coeff[1][0].shape[0], mp.nmo[1]), dtype=mo_coeff[0][0].dtype))
    for spin in [0, 1]:
        for k in range(nkpts):
            result[spin][np.ix_([k], np.arange(result[spin].shape[1]), padding_convention[spin][k])] = \
                mo_coeff[spin][k][:, frozen_mask[spin][k]]

    return result 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def mask_frozen_ip(eom, vector, kshift, const=LARGE_DENOM):
    '''Replaces all frozen orbital indices of `vector` with the value `const`.'''
    r1, r2 = eom.vector_to_amplitudes(vector, kshift=kshift)
    nkpts = eom.nkpts
    nocc, nmo = eom.nocc, eom.nmo
    kconserv = eom.kconserv

    # Get location of padded elements in occupied and virtual space
    nonzero_opadding, nonzero_vpadding = eom.nonzero_opadding, eom.nonzero_vpadding

    new_r1 = const * np.ones_like(r1)
    new_r2 = const * np.ones_like(r2)

    new_r1[nonzero_opadding[kshift]] = r1[nonzero_opadding[kshift]]
    for ki in range(nkpts):
        for kj in range(nkpts):
            kb = kconserv[ki, kshift, kj]
            idx = np.ix_([ki], [kj], nonzero_opadding[ki], nonzero_opadding[kj], nonzero_vpadding[kb])
            new_r2[idx] = r2[idx]

    return eom.amplitudes_to_vector(new_r1, new_r2, kshift, kconserv) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def mask_frozen_ea(eom, vector, kshift, const=LARGE_DENOM):
    '''Replaces all frozen orbital indices of `vector` with the value `const`.'''
    r1, r2 = eom.vector_to_amplitudes(vector, kshift=kshift)
    kconserv = eom.kconserv
    nkpts = eom.nkpts
    nocc, nmo = eom.nocc, eom.nmo

    # Get location of padded elements in occupied and virtual space
    nonzero_opadding, nonzero_vpadding = eom.nonzero_opadding, eom.nonzero_vpadding

    new_r1 = const * np.ones_like(r1)
    new_r2 = const * np.ones_like(r2)

    new_r1[nonzero_vpadding[kshift]] = r1[nonzero_vpadding[kshift]]
    for kj in range(nkpts):
        for ka in range(nkpts):
            kb = kconserv[kshift, ka, kj]
            idx = np.ix_([kj], [ka], nonzero_opadding[kj], nonzero_vpadding[ka], nonzero_vpadding[kb])
            new_r2[idx] = r2[idx]

    return eom.amplitudes_to_vector(new_r1, new_r2, kshift, kconserv) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def test_eri(self):
        """Tests all ERI implementations: with and without symmetries."""
        for eri in (ktd.PhysERI, ktd.PhysERI4, ktd.PhysERI8):
            if not eri == ktd.PhysERI8 or self.test8:
                try:
                    e = eri(self.model_krhf)
                    m = e.tdhf_full_form()

                    # Test matrix vs ref
                    testing.assert_allclose(m, retrieve_m_hf(e), atol=1e-11)

                    # Test matrix vs pyscf
                    testing.assert_allclose(self.ref_m, m[numpy.ix_(self.ov_order, self.ov_order)], atol=1e-5)
                except Exception:
                    print("When testing {} the following exception occurred:".format(eri))
                    raise 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def test_eri(self):
        """Tests all ERI implementations: with and without symmetries."""
        e = PhysERI(self.model_rks, "dft")
        mk, _ = e.tdhf_mk_form()
        testing.assert_allclose(self.ref_m, mk, atol=1e-13)

        # Test frozen
        for frozen in (1, [0, -1]):
            try:
                e = PhysERI(self.model_rks, "dft", frozen=frozen)
                mk, _ = e.tdhf_mk_form()
                ov_mask = tdhf_frozen_mask(e, kind="1ov")
                ref_m = self.ref_m[numpy.ix_(ov_mask, ov_mask)]
                testing.assert_allclose(ref_m, mk, atol=1e-13)

            except Exception:
                print("When testing with frozen={} the following exception occurred:".format(repr(frozen)))
                raise 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def remove_empty_rows_columns(np_matrix):
  """Simple util to remove empty rows and columns of a matrix.

  Args:
    np_matrix: A numpy array.
  Returns:
    A tuple consisting of:
    mat: A numpy matrix obtained by removing empty rows and columns from
      np_matrix.
    nz_row_ids: A numpy array of the ids of non-empty rows, such that
      nz_row_ids[i] is the old row index corresponding to new index i.
    nz_col_ids: A numpy array of the ids of non-empty columns, such that
      nz_col_ids[j] is the old column index corresponding to new index j.
  """
  nz_row_ids = np.where(np.sum(np_matrix, axis=1) != 0)[0]
  nz_col_ids = np.where(np.sum(np_matrix, axis=0) != 0)[0]
  mat = np_matrix[np.ix_(nz_row_ids, nz_col_ids)]
  return mat, nz_row_ids, nz_col_ids 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def test_large_fancy_indexing(self, level=rlevel):
        # Large enough to fail on 64-bit.
        nbits = np.dtype(np.intp).itemsize * 8
        thesize = int((2**nbits)**(1.0/5.0)+1)

        def dp():
            n = 3
            a = np.ones((n,)*5)
            i = np.random.randint(0, n, size=thesize)
            a[np.ix_(i, i, i, i, i)] = 0

        def dp2():
            n = 3
            a = np.ones((n,)*5)
            i = np.random.randint(0, n, size=thesize)
            a[np.ix_(i, i, i, i, i)]

        self.assertRaises(ValueError, dp)
        self.assertRaises(ValueError, dp2) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def subinv(x,eps=None):
    """ Given an matrix (x), calculate all the inverses of leave-one-out sub-matrices.
    
    :param x: a square matrix for which to find the inverses of all it's leave one out sub-matrices.
    :param eps: If not None, used to assert that the each calculated
           sub-matrix-inverse is within eps of the brute force calculation.
           Testing only, this slows the process way down since the inverse of
           each sub-matrix is calculated by the brute force method. Typically
           set to a multiple of `np.finfo(float).eps`
    """
    # handy constant for indexing
    xi = x.I
    N = x.shape[0]
    rng = np.arange(N)
    out = [None,] * N
    for k in range(N):
        k_rng = rng[rng != k]
        out[k] = xi[np.ix_(k_rng,k_rng)] - xi[k_rng,k].dot(xi[k,k_rng])/xi[k,k]
        if eps is not None:
            if not (abs(out[k] - x[np.ix_(k_rng,k_rng)].I) < eps).all():
                raise RuntimeError("Fast and brute force methods were not within epsilon (%s) for sub-matrix k = %s; max difference = %s" % 
                                   (eps, k,  abs(out[k] - x[np.ix_(k_rng,k_rng)].I).max(), ) )
    return out 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def align_hessian(self, hess) -> Array:
        blocked_hess = blockwise_expand(hess, (3, 3), False)
        alhess = np.zeros_like(blocked_hess)

        nat = blocked_hess.shape[0]
        for iat in range(nat):
            for jat in range(nat):
                alhess[iat, jat] = (self.rotation.T).dot(blocked_hess[iat, jat].dot(self.rotation))

        alhess = alhess[np.ix_(self.atommap, self.atommap)]

        alhess = blockwise_contract(alhess)
        return alhess 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def test_imds(self):

        testing.assert_allclose(
            tuple(self.gw.imds.get_rhs(i) for i in self.gw.imds.entire_space[0]),
            tuple(self.kgw.imds.get_rhs(i) for i in zip(self.order_k, self.order_p)),
            atol=1e-8
        )
        testing.assert_allclose(
            self.gw.imds.tdm,
            self.kgw.imds.tdm[numpy.ix_(range(len(self.kgw.imds.td_e)), range(2), self.order, self.order)],
            atol=1e-7
        ) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def _get_epq(pindices,qindices,fac=[1.0,1.0],large_num=LARGE_DENOM):
    '''Create a denominator

        fac[0]*e[kp,p0:p1] + fac[1]*e[kq,q0:q1]

    where padded elements have been replaced by a large number.

    Args:
        pindices (5-list of object):
            A list of p0, p1, kp, orbital values, and non-zero indicess for the first
            denominator indices.
        qindices (5-list of object):
            A list of q0, q1, kq, orbital values, and non-zero indicess for the second
            denominator element.
        fac (3-list of float):
            Factors to multiply the first and second denominator elements.
        large_num (float):
            Number to replace the padded elements.
    '''
    def get_idx(x0,x1,kx,n0_p):
        return np.logical_and(n0_p[kx] >= x0, n0_p[kx] < x1)

    assert(all([len(x) == 5 for x in [pindices,qindices]]))
    p0,p1,kp,mo_e_p,nonzero_p = pindices
    q0,q1,kq,mo_e_q,nonzero_q = qindices
    fac_p, fac_q = fac

    epq = large_num * np.ones((p1-p0,q1-q0), dtype=mo_e_p[0].dtype)
    idxp = get_idx(p0,p1,kp,nonzero_p)
    idxq = get_idx(q0,q1,kq,nonzero_q)
    n0_ovp_pq = np.ix_(nonzero_p[kp][idxp], nonzero_q[kq][idxq])
    epq[n0_ovp_pq] = lib.direct_sum('p,q->pq', fac_p*mo_e_p[kp][p0:p1],
                                               fac_q*mo_e_q[kq][q0:q1])[n0_ovp_pq]
    return epq


# TODO: pull these 3 methods to pyscf.util and make tests 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import ix_ [as 別名]
def init_amps(self, eris):
        time0 = time.clock(), time.time()
        nocc = self.nocc
        nvir = self.nmo - nocc
        nkpts = self.nkpts
        mo_e_o = [eris.mo_energy[k][:nocc] for k in range(nkpts)]
        mo_e_v = [eris.mo_energy[k][nocc:] for k in range(nkpts)]
        t1 = numpy.zeros((nkpts, nocc, nvir), dtype=numpy.complex128)
        t2 = numpy.zeros((nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir), dtype=numpy.complex128)
        self.emp2 = 0
        eris_oovv = eris.oovv.copy()

        # Get location of padded elements in occupied and virtual space
        nonzero_opadding, nonzero_vpadding = padding_k_idx(self, kind="split")

        kconserv = kpts_helper.get_kconserv(self._scf.cell, self.kpts)
        for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
            kb = kconserv[ki, ka, kj]
            # For LARGE_DENOM, see t1new update above
            eia = LARGE_DENOM * numpy.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
            n0_ovp_ia = numpy.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
            eia[n0_ovp_ia] = (mo_e_o[ki][:,None] - mo_e_v[ka])[n0_ovp_ia]

            ejb = LARGE_DENOM * numpy.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
            n0_ovp_jb = numpy.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
            ejb[n0_ovp_jb] = (mo_e_o[kj][:,None] - mo_e_v[kb])[n0_ovp_jb]
            eijab = eia[:, None, :, None] + ejb[:, None, :]

            t2[ki, kj, ka] = eris_oovv[ki, kj, ka] / eijab

        t2 = numpy.conj(t2)
        self.emp2 = 0.25 * numpy.einsum('pqrijab,pqrijab', t2, eris_oovv).real
        self.emp2 /= nkpts

        logger.info(self, 'Init t2, MP2 energy = %.15g', self.emp2.real)
        logger.timer(self, 'init mp2', *time0)
        return self.emp2, t1, t2