Python numpy.complex方法代碼示例

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def cc_Wvvvv(t1,t2,eris):
    tau = make_tau(t2,t1,t1)
    #eris_vovv = np.array(eris.ovvv).transpose(1,0,3,2)
    #tmp = einsum('mb,amef->abef',t1,eris_vovv)
    #Wabef = eris.vvvv - tmp + tmp.transpose(1,0,2,3)
    #Wabef += 0.25*einsum('mnab,mnef->abef',tau,eris.oovv)
    if t1.dtype == np.complex: ds_type = 'c16'
    else: ds_type = 'f8'
    _tmpfile1 = tempfile.NamedTemporaryFile(dir=lib.param.TMPDIR)
    fimd = h5py.File(_tmpfile1.name)
    nocc, nvir = t1.shape
    Wabef = fimd.create_dataset('vvvv', (nvir,nvir,nvir,nvir), ds_type)
    for a in range(nvir):
        Wabef[a] = eris.vvvv[a] 
        Wabef[a] -= einsum('mb,mfe->bef',t1,eris.ovvv[:,a,:,:]) 
        Wabef[a] += einsum('m,mbfe->bef',t1[:,a],eris.ovvv) 
        Wabef[a] += 0.25*einsum('mnb,mnef->bef',tau[:,:,a,:],eris.oovv)
    return Wabef 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def angle_to_cortex(self, theta, rho):
        'See help(neuropythy.registration.RetinotopyModel.angle_to_cortex).'
        #TODO: This should be made to work correctly with visual area boundaries: this could be done
        # by, for each area (e.g., V2) looking at its boundaries (with V1 and V3) and flipping the
        # adjacent triangles so that there is complete coverage of each hemifield, guaranteed.
        if not pimms.is_vector(theta): return self.angle_to_cortex([theta], [rho])[0]
        theta = np.asarray(theta)
        rho = np.asarray(rho)
        zs = np.asarray(
            rho * np.exp([np.complex(z) for z in 1j * ((90.0 - theta)/180.0*np.pi)]),
            dtype=np.complex)
        coords = np.asarray([zs.real, zs.imag]).T
        if coords.shape[0] == 0: return np.zeros((0, len(self.visual_meshes), 2))
        # we step through each area in the forward model and return the appropriate values
        tx = self.transform
        res = np.transpose(
            [self.visual_meshes[area].interpolate(coords, 'cortical_coordinates', method='linear')
             for area in sorted(self.visual_meshes.keys())],
            (1,0,2))
        if tx is not None:
            res = np.asarray(
                [np.dot(tx, np.vstack((area_xy.T, np.ones(len(area_xy)))))[0:2].T
                 for area_xy in res])
        return res 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def get_init_guess(self, kshift, nroots=1, koopmans=False, diag=None):
        size = self.vector_size()
        dtype = getattr(diag, 'dtype', np.complex)
        nroots = min(nroots, size)
        guess = []
        if koopmans:
            for n in self.nonzero_opadding[kshift][::-1][:nroots]:
                g = np.zeros(int(size), dtype=dtype)
                g[n] = 1.0
                g = self.mask_frozen(g, kshift, const=0.0)
                guess.append(g)
        else:
            idx = diag.argsort()[:nroots]
            for i in idx:
                g = np.zeros(int(size), dtype=dtype)
                g[i] = 1.0
                g = self.mask_frozen(g, kshift, const=0.0)
                guess.append(g)
        return guess 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def diagonalize_asymm(H):
    """
    Diagonalize a real, *asymmetric* matrix and return sorted results.

    Return the eigenvalues and eigenvectors (column matrix)
    sorted from lowest to highest eigenvalue.
    """
    E,C = np.linalg.eig(H)
    #if np.allclose(E.imag, 0*E.imag):
    #    E = np.real(E)
    #else:
    #    print "WARNING: Eigenvalues are complex, will be returned as such."

    idx = E.real.argsort()
    E = E[idx]
    C = C[:,idx]

    return E,C 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def allocateVecs(self):
        self.subH = np.zeros( shape=(self.maxM,self.maxM), dtype=complex )
        self.sol = np.zeros( shape=(self.maxM), dtype=complex )
        self.dgks = np.zeros( shape=(self.maxM), dtype=complex )
        self.nConv = np.zeros( shape=(self.maxM), dtype=int )
        self.eigs = np.zeros( shape=(self.maxM), dtype=complex )
        self.evecs = np.zeros( shape=(self.maxM,self.maxM), dtype=complex )
        self.oldeigs = np.zeros( shape=(self.maxM), dtype=complex )
        self.deigs = np.zeros( shape=(self.maxM), dtype=complex )
        self.outeigs = np.zeros( shape=(self.nEigen), dtype=complex )
        self.outevecs = np.zeros( shape=(self.size,self.nEigen), dtype=complex)
        self.currentSize = 0

        self.Ax = np.zeros( shape=(self.size), dtype=complex )
        self.res = np.zeros( shape=(self.size), dtype=complex )
        self.vlist = np.zeros( shape=(self.maxM,self.size), dtype=complex )
        self.cv = np.zeros( shape = (self.size), dtype = complex )
        self.cAv = np.zeros( shape = (self.size), dtype = complex )
        self.Avlist = np.zeros( shape=(self.maxM,self.size), dtype=complex )
        self.dres = 999.9
        self.resnorm = 999.9
        self.cvEig = 0.1
        self.ciEig = 0
        self.deflated = 0 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def Wvvvv(t1,t2,eris):
    tau = make_tau(t2,t1,t1)
    #Wabef = cc_Wvvvv(t1,t2,eris) + 0.25*einsum('mnab,mnef->abef',tau,eris.oovv)
    if t1.dtype == np.complex: ds_type = 'c16'
    else: ds_type = 'f8'
    _tmpfile1 = tempfile.NamedTemporaryFile(dir=lib.param.TMPDIR)
    fimd = h5py.File(_tmpfile1.name)
    nocc, nvir = t1.shape
    Wabef = fimd.create_dataset('vvvv', (nvir,nvir,nvir,nvir), ds_type)
    #_cc_Wvvvv = cc_Wvvvv(t1,t2,eris)
    for a in range(nvir):
        #Wabef[a] = _cc_Wvvvv[a]
        Wabef[a] = eris.vvvv[a] 
        Wabef[a] -= einsum('mb,mfe->bef',t1,eris.ovvv[:,a,:,:]) 
        Wabef[a] += einsum('m,mbfe->bef',t1[:,a],eris.ovvv) 
        #Wabef[a] += 0.25*einsum('mnb,mnef->bef',tau[:,:,a,:],eris.oovv)

        #Wabef[a] += 0.25*einsum('mnb,mnef->bef',tau[:,:,a,:],eris.oovv) 
        Wabef[a] += 0.5*einsum('mnb,mnef->bef',tau[:,:,a,:],eris.oovv) 
    return Wabef 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def test_intor_r2e(self):
        mol1 = gto.M(atom=[[1   , (0. , -0.7 , 0.)],
                           [1   , (0. ,  0.7 , 0.)]],
                     basis = '631g')
        nao = mol1.nao_2c()
        eri0 = numpy.empty((3,nao,nao,nao,nao), dtype=numpy.complex)
        ip = 0
        for i in range(mol1.nbas):
            jp = 0
            for j in range(mol1.nbas):
                kp = 0
                for k in range(mol1.nbas):
                    lp = 0
                    for l in range(mol1.nbas):
                        buf = mol1.intor_by_shell('int2e_ip1_spinor', (i,j,k,l), comp=3)
                        di,dj,dk,dl = buf.shape[1:]
                        eri0[:,ip:ip+di,jp:jp+dj,kp:kp+dk,lp:lp+dl] = buf
                        lp += dl
                    kp += dk
                jp += dj
            ip += di 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def hcore_generator(self, mol):
        aoslices = mol.aoslice_2c_by_atom()
        h1 = self.get_hcore(mol)
        n2c = mol.nao_2c()
        n4c = n2c * 2
        c = lib.param.LIGHT_SPEED
        def hcore_deriv(atm_id):
            shl0, shl1, p0, p1 = aoslices[atm_id]
            with mol.with_rinv_at_nucleus(atm_id):
                z = -mol.atom_charge(atm_id)
                vn = z * mol.intor('int1e_iprinv_spinor', comp=3)
                wn = z * mol.intor('int1e_ipsprinvsp_spinor', comp=3)

            v = numpy.zeros((3,n4c,n4c), numpy.complex)
            v[:,:n2c,:n2c] = vn
            v[:,n2c:,n2c:] = wn * (.25/c**2)
            v[:,p0:p1]         += h1[:,p0:p1]
            v[:,n2c+p0:n2c+p1] += h1[:,n2c+p0:n2c+p1]
            return v + v.conj().transpose(0,2,1)
        return hcore_deriv 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def make_s10(mol, gauge_orig=None, mb='RMB'):
    '''First order overlap matrix wrt external magnetic field.
    Note the side effects of set_common_origin.
    '''
    if gauge_orig is not None:
        mol.set_common_origin(gauge_orig)
    n2c = mol.nao_2c()
    n4c = n2c * 2
    c = lib.param.LIGHT_SPEED
    s1 = numpy.zeros((3, n4c, n4c), complex)
    if mb.upper() == 'RMB':
        if gauge_orig is None:
            t1 = mol.intor('int1e_giao_sa10sp_spinor', 3)
        else:
            t1 = mol.intor('int1e_cg_sa10sp_spinor', 3)
        for i in range(3):
            t1cc = t1[i] + t1[i].conj().T
            s1[i,n2c:,n2c:] = t1cc * (.25/c**2)

    if gauge_orig is None:
        sg = mol.intor('int1e_govlp_spinor', 3)
        tg = mol.intor('int1e_spgsp_spinor', 3)
        s1[:,:n2c,:n2c] += sg
        s1[:,n2c:,n2c:] += tg * (.25/c**2)
    return s1 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def test_better_float():
    # Better float function
    def check_against(f1, f2):
        return f1 if FLOAT_TYPES.index(f1) >= FLOAT_TYPES.index(f2) else f2
    for first in FLOAT_TYPES:
        for other in IUINT_TYPES + np.sctypes['complex']:
            assert_equal(better_float_of(first, other), first)
            assert_equal(better_float_of(other, first), first)
            for other2 in IUINT_TYPES + np.sctypes['complex']:
                assert_equal(better_float_of(other, other2), np.float32)
                assert_equal(better_float_of(other, other2, np.float64),
                             np.float64)
        for second in FLOAT_TYPES:
            assert_equal(better_float_of(first, second),
                         check_against(first, second))
    # Check codes and dtypes work
    assert_equal(better_float_of('f4', 'f8', 'f4'), np.float64)
    assert_equal(better_float_of('i4', 'i8', 'f8'), np.float64) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def _num_to_rqc_str(num):
    """Convert float to string to be included in RQC quil DEFGATE block
    (as written by _np_to_quil_def_str)."""
    num = _np.complex(_np.real_if_close(num))
    if _np.imag(num) == 0:
        output = str(_np.real(num))
        return output
    else:
        real_part = _np.real(num)
        imag_part = _np.imag(num)
        if imag_part < 0:
            sgn = '-'
            imag_part = imag_part * -1
        elif imag_part > 0:
            sgn = '+'
        else:
            assert False
        return '{}{}{}i'.format(real_part, sgn, imag_part) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def _patch_cython():
    # "monkey patch" some objects to avoid cyclic import structure
    from . import _npc_helper
    _npc_helper._charges = charges
    _npc_helper._np_conserved = np_conserved
    assert _npc_helper.QTYPE == charges.QTYPE
    # check types
    warn = False
    import numpy as np
    check_types = [
        (np.float64, np.complex128),
        (np.ones([1]).dtype, (1.j * np.ones([1])).dtype),
        (np.array(1.).dtype, np.array(1.j).dtype),
        (np.array(1., dtype=np.float).dtype, np.array(1., dtype=np.complex).dtype),
    ]
    types_ok = [
        _npc_helper._float_complex_are_64_bit(dt_float, dt_real)
        for dt_float, dt_real in check_types
    ]
    if not np.all(types_ok):
        import warnings
        warnings.warn("(Some of) the default dtypes are not 64-bit. "
                      "Using the compiled cython code (as you do) might make it slower.")
    # done 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def _griffin_lim(S):
    angles = np.exp(2j * np.pi * np.random.rand(*S.shape))
    S_complex = np.abs(S).astype(np.complex)
    for i in range(hparams.griffin_lim_iters):
        if i > 0:
            angles = np.exp(1j * np.angle(_stft(y)))
        y = _istft(S_complex * angles)
    return y 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def gen_H_tb(t,Nx,Ny,kvec):
    H = np.zeros((Nx,Ny,Nx,Ny),dtype=np.complex)
    for i in range(Nx):
        for j in range(Ny):
            if i == Nx-1:
                H[i,j,0   ,j] += np.exp(-1j*np.dot(np.array(kvec),np.array([Nx,0])))
            else:
                H[i,j,i+1 ,j] += 1

            if i == 0:
                H[i,j,Nx-1,j] += np.exp(-1j*np.dot(np.array(kvec),np.array([-Nx,0])))
            else:
                H[i,j,i-1 ,j] += 1

            if j == Ny-1:
                H[i,j,i,0   ] += np.exp(-1j*np.dot(np.array(kvec),np.array([0,Ny])))
            else:
                H[i,j,i,j+1] += 1

            if j == 0:
                H[i,j,i,Ny-1] += np.exp(-1j*np.dot(np.array(kvec),np.array([0,-Ny])))
            else:
                H[i,j,i,j-1] += 1
    return -t*H.reshape(Nx*Ny,Nx*Ny)

### get H_tb at a series of kpoints. 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import complex [as 別名]
def get_xmat(self, mol=None):
        if mol is None:
            xmol = self.get_xmol(mol)[0]
        else:
            xmol = mol
        c = lib.param.LIGHT_SPEED
        assert('1E' in self.approx.upper())

        if 'ATOM' in self.approx.upper():
            atom_slices = xmol.offset_2c_by_atom()
            n2c = xmol.nao_2c()
            x = numpy.zeros((n2c,n2c), dtype=numpy.complex)
            for ia in range(xmol.natm):
                ish0, ish1, p0, p1 = atom_slices[ia]
                shls_slice = (ish0, ish1, ish0, ish1)
                s1 = xmol.intor('int1e_ovlp_spinor', shls_slice=shls_slice)
                t1 = xmol.intor('int1e_spsp_spinor', shls_slice=shls_slice) * .5
                with xmol.with_rinv_at_nucleus(ia):
                    z = -xmol.atom_charge(ia)
                    v1 = z*xmol.intor('int1e_rinv_spinor', shls_slice=shls_slice)
                    w1 = z*xmol.intor('int1e_sprinvsp_spinor', shls_slice=shls_slice)
                x[p0:p1,p0:p1] = _x2c1e_xmatrix(t1, v1, w1, s1, c)
        else:
            s = xmol.intor_symmetric('int1e_ovlp_spinor')
            t = xmol.intor_symmetric('int1e_spsp_spinor') * .5
            v = xmol.intor_symmetric('int1e_nuc_spinor')
            w = xmol.intor_symmetric('int1e_spnucsp_spinor')
            x = _x2c1e_xmatrix(t, v, w, s, c)
        return x