pyscf.adc package

Submodules

pyscf.adc.dfadc module

pyscf.adc.dfadc.get_ovvv_df(myadc, Lov, Lvv, p, chnk_size)[source]

Returns approximate ovvv integrals used in restricted implementation

pyscf.adc.dfadc.get_ovvv_spin_df(myadc, Lov, Lvv, p, chnk_size)[source]

Returns approximate ovvv integrals (different spin cases) used in unrestricted implementation

pyscf.adc.dfadc.get_vVvV_df(myadc, Lvv, LVV, p, chnk_size)[source]

Returns approximate vvvv integrals (mixed spin) used in unrestricted implementation

pyscf.adc.dfadc.get_vvvv_antisym_df(myadc, Lvv, p, chnk_size)[source]

Returns approximate antisymmetrized vvvv integrals (alpha/beta spin) used in unrestricted implementation

pyscf.adc.dfadc.get_vvvv_df(myadc, Lvv, p, chnk_size)[source]

Returns approximate vvvv integrals used in restricted implementation

pyscf.adc.radc module

Restricted algebraic diagrammatic construction

class pyscf.adc.radc.RADC(mf, frozen=0, mo_coeff=None, mo_occ=None)[source]

Bases: pyscf.lib.misc.StreamObject

Ground state calculations

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.RADC(mf).run()

Saved results

e_corrfloat

MPn correlation correction

e_totfloat

Total energy (HF + correlation)

t1, t2 :

T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

analyze()[source]
async_io = True
blkmin = 4
compute_amplitudes(eris)
compute_dyson_mo()[source]
compute_energy(t2, eris)
density_fit(auxbasis=None, with_df=None)[source]
dump_flags(verbose=None)[source]
dump_flags_gs(verbose=None)[source]
ea_adc(nroots=1, guess=None, eris=None)[source]
incore_complete = False
ip_adc(nroots=1, guess=None, eris=None)[source]
kernel(nroots=1, guess=None, eris=None)[source]

Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

kernel_gs()[source]
make_rdm1(T=None)
memorymin = 2000
transform_integrals()
class pyscf.adc.radc.RADCEA(adc)[source]

Bases: pyscf.adc.radc.RADC

restricted ADC for EA energies and spectroscopic amplitudes

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

conv_tolfloat

Convergence threshold for Davidson iterations. Default is 1e-12.

max_cycleint

Number of Davidson iterations. Default is 50.

max_spaceint

Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:
nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.RADC(mf).run()
>>> myadcea = adc.RADC(myadc).run()

Saved results

e_eafloat or list of floats

EA energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray

Eigenvectors for each EA transition.

p_eafloat

Spectroscopic amplitudes for each EA transition.

analyze()
analyze_eigenvector()
analyze_spec_factor()
compute_dyson_mo()
compute_trans_moments(orb)
gen_matvec(imds=None, eris=None)[source]
get_diag(M_ab=None, eris=None)
get_imds(eris=None)
get_init_guess(nroots=1, diag=None, ascending=True)[source]
get_properties(nroots=1)
get_trans_moments()
kernel(nroots=1, guess=None, eris=None, verbose=None)

Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

matvec(M_ab=None, eris=None)
renormalize_eigenvectors(nroots=1)
class pyscf.adc.radc.RADCIP(adc)[source]

Bases: pyscf.adc.radc.RADC

restricted ADC for IP energies and spectroscopic amplitudes

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

conv_tolfloat

Convergence threshold for Davidson iterations. Default is 1e-12.

max_cycleint

Number of Davidson iterations. Default is 50.

max_spaceint

Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:
nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.RADC(mf).run()
>>> myadcip = adc.RADC(myadc).run()

Saved results

e_ipfloat or list of floats

IP energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray

Eigenvectors for each IP transition.

p_ipfloat

Spectroscopic amplitudes for each IP transition.

analyze()
analyze_eigenvector()
analyze_spec_factor()
compute_dyson_mo()
compute_trans_moments(orb)
gen_matvec(imds=None, eris=None)[source]
get_diag(M_ij=None, eris=None)
get_imds(eris=None)
get_init_guess(nroots=1, diag=None, ascending=True)[source]
get_properties(nroots=1)
get_trans_moments()
kernel(nroots=1, guess=None, eris=None, verbose=None)

Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

matvec(M_ij=None, eris=None)
renormalize_eigenvectors(nroots=1)
pyscf.adc.radc.analyze(myadc)[source]
pyscf.adc.radc.analyze_eigenvector_ea(adc)[source]
pyscf.adc.radc.analyze_eigenvector_ip(adc)[source]
pyscf.adc.radc.analyze_spec_factor(adc)[source]
pyscf.adc.radc.compute_amplitudes(myadc, eris)[source]
pyscf.adc.radc.compute_amplitudes_energy(myadc, eris, verbose=None)[source]
pyscf.adc.radc.compute_dyson_mo(myadc)[source]
pyscf.adc.radc.compute_energy(myadc, t2, eris)[source]
pyscf.adc.radc.contract_ladder(myadc, t_amp, vvvv)[source]
pyscf.adc.radc.density_matrix(myadc, T=None)[source]
pyscf.adc.radc.ea_adc_diag(adc, M_ab=None, eris=None)[source]
pyscf.adc.radc.ea_adc_matvec(adc, M_ab=None, eris=None)[source]
pyscf.adc.radc.ea_compute_trans_moments(adc, orb)[source]
pyscf.adc.radc.ea_contract_r_vvvv(myadc, r2, vvvv)[source]
pyscf.adc.radc.get_imds_ea(adc, eris=None)[source]
pyscf.adc.radc.get_imds_ip(adc, eris=None)[source]
pyscf.adc.radc.get_properties(adc, nroots=1)[source]
pyscf.adc.radc.get_trans_moments(adc)[source]
pyscf.adc.radc.ip_adc_diag(adc, M_ij=None, eris=None)[source]
pyscf.adc.radc.ip_adc_matvec(adc, M_ij=None, eris=None)[source]
pyscf.adc.radc.ip_compute_trans_moments(adc, orb)[source]
pyscf.adc.radc.kernel(adc, nroots=1, guess=None, eris=None, verbose=None)[source]
pyscf.adc.radc.renormalize_eigenvectors_ea(adc, nroots=1)[source]
pyscf.adc.radc.renormalize_eigenvectors_ip(adc, nroots=1)[source]

pyscf.adc.radc_ao2mo module

pyscf.adc.radc_ao2mo.calculate_chunk_size(myadc)[source]
pyscf.adc.radc_ao2mo.read_dataset(h5file, dataname)[source]
pyscf.adc.radc_ao2mo.transform_integrals_df(myadc)[source]
pyscf.adc.radc_ao2mo.transform_integrals_incore(myadc)[source]
pyscf.adc.radc_ao2mo.transform_integrals_outcore(myadc)[source]
pyscf.adc.radc_ao2mo.unpack_eri_1(eri, norb)[source]
pyscf.adc.radc_ao2mo.unpack_eri_2(eri, norb)[source]
pyscf.adc.radc_ao2mo.write_dataset(data)[source]

pyscf.adc.uadc module

Unrestricted algebraic diagrammatic construction

class pyscf.adc.uadc.UADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]

Bases: pyscf.lib.misc.StreamObject

Ground state calculations

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.UADC(mf).run()

Saved results

e_corrfloat

MPn correlation correction

e_totfloat

Total energy (HF + correlation)

t1, t2 :

T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

analyze()[source]
compute_amplitudes(eris)
compute_dyson_mo()[source]
compute_energy(t1, t2, eris)
density_fit(auxbasis=None, with_df=None)[source]
dump_flags(verbose=None)[source]
dump_flags_gs(verbose=None)[source]
ea_adc(nroots=1, guess=None, eris=None)[source]
incore_complete = False
ip_adc(nroots=1, guess=None, eris=None)[source]
kernel(nroots=1, guess=None, eris=None)[source]

Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

kernel_gs()[source]
make_rdm1s(T=None)
transform_integrals()
class pyscf.adc.uadc.UADCEA(adc)[source]

Bases: pyscf.adc.uadc.UADC

unrestricted ADC for EA energies and spectroscopic amplitudes

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

conv_tolfloat

Convergence threshold for Davidson iterations. Default is 1e-12.

max_cycleint

Number of Davidson iterations. Default is 50.

max_spaceint

Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:
nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.UADC(mf).run()
>>> myadcea = adc.UADC(myadc).run()

Saved results

e_eafloat or list of floats

EA energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray

Eigenvectors for each EA transition.

p_eafloat

Spectroscopic amplitudes for each EA transition.

analyze()
analyze_eigenvector()
analyze_spec_factor()
compute_dyson_mo()
compute_trans_moments(orb, spin='alpha')
gen_matvec(imds=None, eris=None)[source]
get_diag(M_ab=None, eris=None)
get_imds(eris=None)
get_init_guess(nroots=1, diag=None, ascending=True)[source]
get_properties(nroots=1)
get_trans_moments()
kernel(nroots=1, guess=None, eris=None, verbose=None)

Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

matvec(M_ab=None, eris=None)
class pyscf.adc.uadc.UADCIP(adc)[source]

Bases: pyscf.adc.uadc.UADC

unrestricted ADC for IP energies and spectroscopic amplitudes

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

conv_tolfloat

Convergence threshold for Davidson iterations. Default is 1e-12.

max_cycleint

Number of Davidson iterations. Default is 50.

max_spaceint

Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:
nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.UADC(mf).run()
>>> myadcip = adc.UADC(myadc).run()

Saved results

e_ipfloat or list of floats

IP energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray

Eigenvectors for each IP transition.

p_ipfloat

Spectroscopic amplitudes for each IP transition.

analyze()
analyze_eigenvector()
analyze_spec_factor()
compute_dyson_mo()
compute_trans_moments(orb, spin='alpha')
gen_matvec(imds=None, eris=None)[source]
get_diag(M_ij=None, eris=None)
get_imds(eris=None)
get_init_guess(nroots=1, diag=None, ascending=True)[source]
get_properties(nroots=1)
get_trans_moments()
kernel(nroots=1, guess=None, eris=None, verbose=None)

Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

matvec(M_ij=None, eris=None)
pyscf.adc.uadc.analyze(myadc)[source]
pyscf.adc.uadc.analyze_eigenvector_ea(adc)[source]
pyscf.adc.uadc.analyze_eigenvector_ip(adc)[source]
pyscf.adc.uadc.analyze_spec_factor(adc)[source]
pyscf.adc.uadc.compute_amplitudes(myadc, eris)[source]
pyscf.adc.uadc.compute_amplitudes_energy(myadc, eris, verbose=None)[source]
pyscf.adc.uadc.compute_dyson_mo(myadc)[source]
pyscf.adc.uadc.compute_energy(myadc, t1, t2, eris)[source]
pyscf.adc.uadc.contract_ladder(myadc, t_amp, vvvv_p)[source]
pyscf.adc.uadc.contract_ladder_antisym(myadc, t_amp, vvvv_d)[source]
pyscf.adc.uadc.density_matrix_so(myadc, T=None)[source]
pyscf.adc.uadc.ea_adc_diag(adc, M_ab=None, eris=None)[source]
pyscf.adc.uadc.ea_adc_matvec(adc, M_ab=None, eris=None)[source]
pyscf.adc.uadc.ea_compute_trans_moments(adc, orb, spin='alpha')[source]
pyscf.adc.uadc.ea_contract_r_vvvv(myadc, r2, vvvv_d)[source]
pyscf.adc.uadc.ea_contract_r_vvvv_antisym(myadc, r2, vvvv_d)[source]
pyscf.adc.uadc.get_imds_ea(adc, eris=None)[source]
pyscf.adc.uadc.get_imds_ip(adc, eris=None)[source]
pyscf.adc.uadc.get_properties(adc, nroots=1)[source]
pyscf.adc.uadc.get_trans_moments(adc)[source]
pyscf.adc.uadc.ip_adc_diag(adc, M_ij=None, eris=None)[source]
pyscf.adc.uadc.ip_adc_matvec(adc, M_ij=None, eris=None)[source]
pyscf.adc.uadc.ip_compute_trans_moments(adc, orb, spin='alpha')[source]
pyscf.adc.uadc.kernel(adc, nroots=1, guess=None, eris=None, verbose=None)[source]

pyscf.adc.uadc_ao2mo module

pyscf.adc.uadc_ao2mo.calculate_chunk_size(myadc)[source]
pyscf.adc.uadc_ao2mo.transform_integrals_df(myadc)[source]
pyscf.adc.uadc_ao2mo.transform_integrals_incore(myadc)[source]
pyscf.adc.uadc_ao2mo.transform_integrals_outcore(myadc)[source]

Module contents

Algebraic Diagrammatic Construction

pyscf.adc.ADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]

Ground state calculations

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.UADC(mf).run()

Saved results

e_corrfloat

MPn correlation correction

e_totfloat

Total energy (HF + correlation)

t1, t2 :

T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

pyscf.adc.RADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]

Ground state calculations

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.RADC(mf).run()

Saved results

e_corrfloat

MPn correlation correction

e_totfloat

Total energy (HF + correlation)

t1, t2 :

T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

pyscf.adc.UADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]

Ground state calculations

Attributes:
verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.UADC(mf).run()

Saved results

e_corrfloat

MPn correlation correction

e_totfloat

Total energy (HF + correlation)

t1, t2 :

T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)