# Copyright 2014-2022 The PySCF Developers. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Author: Samragni Banerjee <samragnibanerjee4@gmail.com>
# Alexander Sokolov <alexander.y.sokolov@gmail.com>
#
import time
import numpy as np
import pyscf.ao2mo as ao2mo
import pyscf.adc
import pyscf.adc.radc
from pyscf.adc import radc_ao2mo
import itertools
from itertools import product
from pyscf import lib
from pyscf.pbc import scf
from pyscf.pbc import df
from pyscf.pbc import mp
from pyscf.lib import logger
from pyscf.pbc.adc import kadc_rhf_amplitudes
from pyscf.pbc.adc import kadc_ao2mo
from pyscf.pbc.adc import dfadc
from pyscf import __config__
from pyscf.pbc.mp.kmp2 import (get_nocc, get_nmo, padding_k_idx,_padding_k_idx,
padded_mo_coeff, get_frozen_mask, _add_padding)
from pyscf.pbc.cc.kccsd_rhf import _get_epq
from pyscf.pbc.cc.kccsd_t_rhf import _get_epqr
from pyscf.pbc.lib import kpts_helper
from pyscf.lib.parameters import LOOSE_ZERO_TOL, LARGE_DENOM # noqa
import h5py
import tempfile
# Note : All interals are in Chemist's notation except for vvvv
# Eg.of momentum conservation :
# Chemist's oovv(ijab) : ki - kj + ka - kb
# Amplitudes t2(ijab) : ki + kj - ka - kba
[docs]
def kernel(adc, nroots=1, guess=None, eris=None, kptlist=None, verbose=None):
adc.method = adc.method.lower()
if adc.method not in ("adc(2)", "adc(2)-x","adc(3)"):
raise NotImplementedError(adc.method)
cput0 = (logger.process_clock(), logger.perf_counter())
log = logger.Logger(adc.stdout, adc.verbose)
if adc.verbose >= logger.WARN:
adc.check_sanity()
adc.dump_flags()
if eris is None:
eris = adc.transform_integrals()
size = adc.vector_size()
nroots = min(nroots,size)
nkpts = adc.nkpts
nmo = adc.nmo
if kptlist is None:
kptlist = range(nkpts)
dtype = np.result_type(adc.t2[0])
evals = np.zeros((len(kptlist),nroots), np.float64)
evecs = np.zeros((len(kptlist),nroots,size), dtype)
conv = np.zeros((len(kptlist),nroots), np.bool_)
P = np.zeros((len(kptlist),nroots), np.float64)
X = np.zeros((len(kptlist),nmo,nroots), dtype)
imds = adc.get_imds(eris)
for k, kshift in enumerate(kptlist):
matvec, diag = adc.gen_matvec(kshift, imds, eris)
guess = adc.get_init_guess(nroots, diag, ascending=True)
conv_k,evals_k, evecs_k = lib.linalg_helper.davidson_nosym1(
lambda xs : [matvec(x) for x in xs], guess, diag,
nroots=nroots, verbose=log, tol=adc.conv_tol,
max_cycle=adc.max_cycle, max_space=adc.max_space,
tol_residual=adc.tol_residual)
evals_k = evals_k.real
evals[k] = evals_k
evecs[k] = evecs_k
conv[k] = conv_k.real
U = np.array(evecs[k]).T.copy()
if adc.compute_properties:
spec_fac,spec_amp = adc.get_properties(kshift,U,nroots)
P[k] = spec_fac
X[k] = spec_amp
nfalse = np.shape(conv)[0] - np.sum(conv)
msg = ("\n*************************************************************"
"\n ADC calculation summary"
"\n*************************************************************")
logger.info(adc, msg)
if nfalse >= 1:
logger.warn(adc, "Davidson iterations for %s root(s) not converged\n", nfalse)
for k, kshift in enumerate(kptlist):
for n in range(nroots):
print_string = ('%s k-point %d | root %d | Energy (Eh) = %14.10f | Energy (eV) = %12.8f ' %
(adc.method, kshift, n, evals[k][n], evals[k][n]*27.2114))
if adc.compute_properties:
print_string += ("| Spec factors = %10.8f " % P[k][n])
print_string += ("| conv = %s" % conv[k][n].real)
logger.info(adc, print_string)
log.timer('ADC', *cput0)
return evals, evecs, P, X
[docs]
class RADC(pyscf.adc.radc.RADC):
_keys = set((
'tol_residual','conv_tol', 'e_corr', 'method', 'mo_coeff',
'mol', 'mo_energy', 'incore_complete',
'scf_energy', 'e_tot', 't1', 'frozen', 'chkfile',
'max_space', 't2', 'mo_occ', 'max_cycle','kpts', 'khelper',
'exxdiv', 'cell', 'nkop_chk', 'kop_npick', 'chnk_size', 'keep_exxdiv',
))
def __init__(self, mf, frozen=None, mo_coeff=None, mo_occ=None):
from pyscf.pbc.cc.ccsd import _adjust_occ
assert (isinstance(mf, scf.khf.KSCF))
if mo_coeff is None:
mo_coeff = mf.mo_coeff
if mo_occ is None:
mo_occ = mf.mo_occ
self._scf = mf
self.kpts = self._scf.kpts
self.exxdiv = self._scf.exxdiv
self.verbose = mf.verbose
self.max_memory = mf.max_memory
self.method = "adc(2)"
self.method_type = "ip"
self.max_space = getattr(__config__, 'adc_kadc_RADC_max_space', 12)
self.max_cycle = getattr(__config__, 'adc_kadc_RADC_max_cycle', 50)
self.conv_tol = getattr(__config__, 'adc_kadc_RADC_conv_tol', 1e-7)
self.tol_residual = getattr(__config__, 'adc_kadc_RADC_tol_res', 1e-4)
self.scf_energy = mf.e_tot
self.khelper = kpts_helper.KptsHelper(mf.cell, mf.kpts)
self.cell = self._scf.cell
self.mo_coeff = mo_coeff
self.mo_occ = mo_occ
self.frozen = frozen
self.compute_properties = True
self.approx_trans_moments = True
self._nocc = None
self._nmo = None
self._nvir = None
self.nkop_chk = False
self.kop_npick = False
self.t1 = None
self.t2 = None
self.e_corr = None
self.chnk_size = None
self.imds = lambda:None
self.keep_exxdiv = False
self.mo_energy = mf.mo_energy
transform_integrals = kadc_ao2mo.transform_integrals_incore
compute_amplitudes = kadc_rhf_amplitudes.compute_amplitudes
compute_energy = kadc_rhf_amplitudes.compute_energy
compute_amplitudes_energy = kadc_rhf_amplitudes.compute_amplitudes_energy
get_chnk_size = kadc_ao2mo.calculate_chunk_size
@property
def nkpts(self):
return len(self.kpts)
@property
def nocc(self):
return self.get_nocc()
@property
def nmo(self):
return self.get_nmo()
get_nocc = get_nocc
get_nmo = get_nmo
[docs]
def kernel_gs(self):
assert(self.mo_coeff is not None)
assert(self.mo_occ is not None)
self.method = self.method.lower()
if self.method not in ("adc(2)", "adc(2)-x", "adc(3)"):
raise NotImplementedError(self.method)
if self.verbose >= logger.WARN:
self.check_sanity()
self.dump_flags_gs()
nmo = self.nmo
nocc = self.nocc
nvir = nmo - nocc
nkpts = self.nkpts
mem_incore = nkpts ** 3 * (nocc + nvir) ** 4
mem_incore *= 4
mem_incore *= 16 /1e6
mem_now = lib.current_memory()[0]
if isinstance(self._scf.with_df, df.GDF):
self.chnk_size = self.get_chnk_size()
self.with_df = self._scf.with_df
def df_transform():
return kadc_ao2mo.transform_integrals_df(self)
self.transform_integrals = df_transform
elif (mem_incore+mem_now >= self.max_memory and not self.incore_complete):
def outcore_transform():
return kadc_ao2mo.transform_integrals_outcore(self)
self.transform_integrals = outcore_transform
eris = self.transform_integrals()
self.e_corr,self.t1,self.t2 = kadc_rhf_amplitudes.compute_amplitudes_energy(
self, eris=eris, verbose=self.verbose)
print ("MPn:",self.e_corr)
self._finalize()
return self.e_corr, self.t1,self.t2
[docs]
def kernel(self, nroots=1, guess=None, eris=None, kptlist=None):
assert(self.mo_coeff is not None)
assert(self.mo_occ is not None)
self.method = self.method.lower()
if self.method not in ("adc(2)", "adc(2)-x", "adc(3)"):
raise NotImplementedError(self.method)
if self.verbose >= logger.WARN:
self.check_sanity()
self.dump_flags_gs()
nmo = self.nmo
nocc = self.nocc
nvir = nmo - nocc
nkpts = self.nkpts
mem_incore = nkpts ** 3 * (nocc + nvir) ** 4
mem_incore *= 4
mem_incore *= 16 /1e6
mem_now = lib.current_memory()[0]
if isinstance(self._scf.with_df, df.GDF):
self.chnk_size = self.get_chnk_size()
self.with_df = self._scf.with_df
def df_transform():
return kadc_ao2mo.transform_integrals_df(self)
self.transform_integrals = df_transform
elif (mem_incore+mem_now >= self.max_memory and not self.incore_complete):
def outcore_transform():
return kadc_ao2mo.transform_integrals_outcore(self)
self.transform_integrals = outcore_transform
eris = self.transform_integrals()
self.e_corr, self.t1, self.t2 = kadc_rhf_amplitudes.compute_amplitudes_energy(
self, eris=eris, verbose=self.verbose)
print ("MPn:",self.e_corr)
self._finalize()
self.method_type = self.method_type.lower()
if(self.method_type == "ea"):
e_exc, v_exc, spec_fac, x, adc_es = self.ea_adc(
nroots=nroots, guess=guess, eris=eris, kptlist=kptlist)
elif(self.method_type == "ip"):
e_exc, v_exc, spec_fac, x, adc_es = self.ip_adc(
nroots=nroots, guess=guess, eris=eris, kptlist=kptlist)
else:
raise NotImplementedError(self.method_type)
self._adc_es = adc_es
return e_exc, v_exc, spec_fac, x
[docs]
def ip_adc(self, nroots=1, guess=None, eris=None, kptlist=None):
from pyscf.pbc.adc import kadc_rhf_ip
adc_es = kadc_rhf_ip.RADCIP(self)
e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris, kptlist)
return e_exc, v_exc, spec_fac, x, adc_es
[docs]
def ea_adc(self, nroots=1, guess=None, eris=None, kptlist=None):
from pyscf.pbc.adc import kadc_rhf_ea
adc_es = kadc_rhf_ea.RADCEA(self)
e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris, kptlist)
return e_exc, v_exc, spec_fac, x, adc_es
[docs]
def density_fit(self, auxbasis=None, with_df=None):
if with_df is None:
self.with_df = df.DF(self._scf.mol)
self.with_df.max_memory = self.max_memory
self.with_df.stdout = self.stdout
self.with_df.verbose = self.verbose
if auxbasis is None:
self.with_df.auxbasis = self._scf.with_df.auxbasis
else:
self.with_df.auxbasis = auxbasis
else:
self.with_df = with_df
return self