Source code for pyscf.ao2mo.outcore

#!/usr/bin/env python
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# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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import numpy
import h5py
from pyscf import gto
from pyscf import lib
from pyscf.lib import logger
from pyscf.ao2mo import _ao2mo
from pyscf.ao2mo import incore
from pyscf import __config__

IOBLK_SIZE = getattr(__config__, 'ao2mo_outcore_ioblk_size', 256)  # 256 MB
IOBUF_WORDS = getattr(__config__, 'ao2mo_outcore_iobuf_words', 1e8)  # 800 MB
IOBUF_ROW_MIN = getattr(__config__, 'ao2mo_outcore_row_min', 160)
MAX_MEMORY = getattr(__config__, 'ao2mo_outcore_max_memory', 2000)  # 2GB


[docs] def full(mol, mo_coeff, erifile, dataname='eri_mo', intor='int2e', aosym='s4', comp=None, max_memory=MAX_MEMORY, ioblk_size=IOBLK_SIZE, verbose=logger.WARN, compact=True): r'''Transfer arbitrary spherical AO integrals to MO integrals for given orbitals Args: mol : :class:`Mole` object AO integrals will be generated in terms of mol._atm, mol._bas, mol._env mo_coeff : ndarray Transform (ij|kl) with the same set of orbitals. erifile : str or h5py File or h5py Group object To store the transformed integrals, in HDF5 format. Kwargs: dataname : str The dataset name in the erifile (ref the hierarchy of HDF5 format http://www.hdfgroup.org/HDF5/doc1.6/UG/09_Groups.html). By assigning different dataname, the existed integral file can be reused. If the erifile contains the dataname, the new integrals data will overwrite the old one. intor : str Name of the 2-electron integral. Ref to :func:`getints_by_shell` for the complete list of available 2-electron integral names aosym : int or str Permutation symmetry for the AO integrals | 4 or '4' or 's4': 4-fold symmetry (default) | '2ij' or 's2ij' : symmetry between i, j in (ij|kl) | '2kl' or 's2kl' : symmetry between k, l in (ij|kl) | 1 or '1' or 's1': no symmetry | 'a4ij' : 4-fold symmetry with anti-symmetry between i, j in (ij|kl) (TODO) | 'a4kl' : 4-fold symmetry with anti-symmetry between k, l in (ij|kl) (TODO) | 'a2ij' : anti-symmetry between i, j in (ij|kl) (TODO) | 'a2kl' : anti-symmetry between k, l in (ij|kl) (TODO) comp : int Components of the integrals, e.g. int2e_ip_sph has 3 components. max_memory : float or int The maximum size of cache to use (in MB), large cache may **not** improve performance. ioblk_size : float or int The block size for IO, large block size may **not** improve performance verbose : int Print level compact : bool When compact is True, depending on the four orbital sets, the returned MO integrals has (up to 4-fold) permutation symmetry. If it's False, the function will abandon any permutation symmetry, and return the "plain" MO integrals Returns: None Examples: >>> from pyscf import gto >>> from pyscf import ao2mo >>> import h5py >>> def view(h5file, dataname='eri_mo'): ... f5 = h5py.File(h5file, 'r') ... print('dataset %s, shape %s' % (str(f5.keys()), str(f5[dataname].shape))) ... f5.close() >>> mol = gto.M(atom='O 0 0 0; H 0 1 0; H 0 0 1', basis='sto3g') >>> mo1 = numpy.random.random((mol.nao_nr(), 10)) >>> ao2mo.outcore.full(mol, mo1, 'full.h5') >>> view('full.h5') dataset ['eri_mo'], shape (55, 55) >>> ao2mo.outcore.full(mol, mo1, 'full.h5', dataname='new', compact=False) >>> view('full.h5', 'new') dataset ['eri_mo', 'new'], shape (100, 100) >>> ao2mo.outcore.full(mol, mo1, 'full.h5', intor='int2e_ip1_sph', aosym='s1', comp=3) >>> view('full.h5') dataset ['eri_mo', 'new'], shape (3, 100, 100) >>> ao2mo.outcore.full(mol, mo1, 'full.h5', intor='int2e_ip1_sph', aosym='s2kl', comp=3) >>> view('full.h5') dataset ['eri_mo', 'new'], shape (3, 100, 55) ''' general(mol, (mo_coeff,)*4, erifile, dataname, intor, aosym, comp, max_memory, ioblk_size, verbose, compact) return erifile
[docs] def general(mol, mo_coeffs, erifile, dataname='eri_mo', intor='int2e', aosym='s4', comp=None, max_memory=MAX_MEMORY, ioblk_size=IOBLK_SIZE, verbose=logger.WARN, compact=True): r'''For the given four sets of orbitals, transfer arbitrary spherical AO integrals to MO integrals on the fly. Args: mol : :class:`Mole` object AO integrals will be generated in terms of mol._atm, mol._bas, mol._env mo_coeffs : 4-item list of ndarray Four sets of orbital coefficients, corresponding to the four indices of (ij|kl) erifile : str or h5py File or h5py Group object To store the transformed integrals, in HDF5 format. Kwargs dataname : str The dataset name in the erifile (ref the hierarchy of HDF5 format http://www.hdfgroup.org/HDF5/doc1.6/UG/09_Groups.html). By assigning different dataname, the existed integral file can be reused. If the erifile contains the dataname, the new integrals data will overwrite the old one. intor : str Name of the 2-electron integral. Ref to :func:`getints_by_shell` for the complete list of available 2-electron integral names aosym : int or str Permutation symmetry for the AO integrals | 4 or '4' or 's4': 4-fold symmetry (default) | '2ij' or 's2ij' : symmetry between i, j in (ij|kl) | '2kl' or 's2kl' : symmetry between k, l in (ij|kl) | 1 or '1' or 's1': no symmetry | 'a4ij' : 4-fold symmetry with anti-symmetry between i, j in (ij|kl) (TODO) | 'a4kl' : 4-fold symmetry with anti-symmetry between k, l in (ij|kl) (TODO) | 'a2ij' : anti-symmetry between i, j in (ij|kl) (TODO) | 'a2kl' : anti-symmetry between k, l in (ij|kl) (TODO) comp : int Components of the integrals, e.g. int2e_ip_sph has 3 components. max_memory : float or int The maximum size of cache to use (in MB), large cache may **not** improve performance. ioblk_size : float or int The block size for IO, large block size may **not** improve performance verbose : int Print level compact : bool When compact is True, depending on the four orbital sets, the returned MO integrals has (up to 4-fold) permutation symmetry. If it's False, the function will abandon any permutation symmetry, and return the "plain" MO integrals Returns: None Examples: >>> from pyscf import gto >>> from pyscf import ao2mo >>> import h5py >>> def view(h5file, dataname='eri_mo'): ... f5 = h5py.File(h5file, 'r') ... print('dataset %s, shape %s' % (str(f5.keys()), str(f5[dataname].shape))) ... f5.close() >>> mol = gto.M(atom='O 0 0 0; H 0 1 0; H 0 0 1', basis='sto3g') >>> mo1 = numpy.random.random((mol.nao_nr(), 10)) >>> mo2 = numpy.random.random((mol.nao_nr(), 8)) >>> mo3 = numpy.random.random((mol.nao_nr(), 6)) >>> mo4 = numpy.random.random((mol.nao_nr(), 4)) >>> ao2mo.outcore.general(mol, (mo1,mo2,mo3,mo4), 'oh2.h5') >>> view('oh2.h5') dataset ['eri_mo'], shape (80, 24) >>> ao2mo.outcore.general(mol, (mo1,mo2,mo3,mo3), 'oh2.h5') >>> view('oh2.h5') dataset ['eri_mo'], shape (80, 21) >>> ao2mo.outcore.general(mol, (mo1,mo2,mo3,mo3), 'oh2.h5', compact=False) >>> view('oh2.h5') dataset ['eri_mo'], shape (80, 36) >>> ao2mo.outcore.general(mol, (mo1,mo1,mo2,mo2), 'oh2.h5') >>> view('oh2.h5') dataset ['eri_mo'], shape (55, 36) >>> ao2mo.outcore.general(mol, (mo1,mo1,mo1,mo1), 'oh2.h5', dataname='new') >>> view('oh2.h5', 'new') dataset ['eri_mo', 'new'], shape (55, 55) >>> ao2mo.outcore.general(mol, (mo1,mo1,mo1,mo1), 'oh2.h5', intor='int2e_ip1_sph', aosym='s1', comp=3) >>> view('oh2.h5') dataset ['eri_mo', 'new'], shape (3, 100, 100) >>> ao2mo.outcore.general(mol, (mo1,mo1,mo1,mo1), 'oh2.h5', intor='int2e_ip1_sph', aosym='s2kl', comp=3) >>> view('oh2.h5') dataset ['eri_mo', 'new'], shape (3, 100, 55) ''' if any(c.dtype == numpy.complex128 for c in mo_coeffs): raise NotImplementedError('Integral transformation for complex orbitals') time_0pass = (logger.process_clock(), logger.perf_counter()) log = logger.new_logger(mol, verbose) nmoi = mo_coeffs[0].shape[1] nmoj = mo_coeffs[1].shape[1] nmol = mo_coeffs[3].shape[1] nao = mo_coeffs[0].shape[0] intor, comp = gto.moleintor._get_intor_and_comp(mol._add_suffix(intor), comp) assert (nao == mol.nao_nr('_cart' in intor)) aosym = _stand_sym_code(aosym) if aosym in ('s4', 's2kl'): nao_pair = nao * (nao+1) // 2 else: nao_pair = nao * nao if (compact and iden_coeffs(mo_coeffs[0], mo_coeffs[1]) and aosym in ('s4', 's2ij')): nij_pair = nmoi*(nmoi+1) // 2 else: nij_pair = nmoi*nmoj klmosym, nkl_pair, mokl, klshape = \ incore._conc_mos(mo_coeffs[2], mo_coeffs[3], compact and aosym in ('s4', 's2kl')) # if nij_pair > nkl_pair: # log.warn('low efficiency for AO to MO trans!') if isinstance(erifile, str): if h5py.is_hdf5(erifile): feri = h5py.File(erifile, 'a') if dataname in feri: del (feri[dataname]) else: feri = h5py.File(erifile, 'w') else: assert (isinstance(erifile, h5py.Group)) feri = erifile if comp == 1: chunks = (nmoj, nmol) shape = (nij_pair, nkl_pair) else: chunks = (1, nmoj, nmol) shape = (comp, nij_pair, nkl_pair) if nij_pair == 0 or nkl_pair == 0: feri.create_dataset(dataname, shape, 'f8') if isinstance(erifile, str): feri.close() return erifile else: h5d_eri = feri.create_dataset(dataname, shape, 'f8', chunks=chunks) log.debug('MO integrals %s are saved in %s/%s', intor, erifile, dataname) log.debug('num. MO ints = %.8g, required disk %.8g MB', float(nij_pair)*nkl_pair*comp, nij_pair*nkl_pair*comp*8/1e6) # transform e1 fswap = lib.H5TmpFile() half_e1(mol, mo_coeffs, fswap, intor, aosym, comp, max_memory, ioblk_size, log, compact) time_1pass = log.timer('AO->MO transformation for %s 1 pass'%intor, *time_0pass) def load(icomp, row0, row1, buf): if icomp+1 < comp: icomp += 1 else: # move to next row-block row0, row1 = row1, min(nij_pair, row1+iobuflen) icomp = 0 if row0 < row1: _load_from_h5g(fswap['%d'%icomp], row0, row1, buf) def save(icomp, row0, row1, buf): if comp == 1: h5d_eri[row0:row1] = buf[:row1-row0] else: h5d_eri[icomp,row0:row1] = buf[:row1-row0] ioblk_size = max(max_memory*.1, ioblk_size) iobuflen = guess_e2bufsize(ioblk_size, nij_pair, max(nao_pair,nkl_pair))[0] buf = numpy.empty((iobuflen,nao_pair)) buf_prefetch = numpy.empty_like(buf) outbuf = numpy.empty((iobuflen,nkl_pair)) buf_write = numpy.empty_like(outbuf) log.debug('step2: kl-pair (ao %d, mo %d), mem %.8g MB, ioblock %.8g MB', nao_pair, nkl_pair, iobuflen*nao_pair*8/1e6, iobuflen*nkl_pair*8/1e6) #klaoblks = len(fswap['0']) ijmoblks = int(numpy.ceil(float(nij_pair)/iobuflen)) * comp ao_loc = mol.ao_loc_nr('_cart' in intor) ti0 = time_1pass istep = 0 with lib.call_in_background(load) as prefetch: with lib.call_in_background(save) as async_write: _load_from_h5g(fswap['0'], 0, min(nij_pair, iobuflen), buf_prefetch) for row0, row1 in prange(0, nij_pair, iobuflen): nrow = row1 - row0 for icomp in range(comp): istep += 1 log.debug1('step 2 [%d/%d], [%d,%d:%d], row = %d', istep, ijmoblks, icomp, row0, row1, nrow) buf, buf_prefetch = buf_prefetch, buf prefetch(icomp, row0, row1, buf_prefetch) _ao2mo.nr_e2(buf[:nrow], mokl, klshape, aosym, klmosym, ao_loc=ao_loc, out=outbuf) async_write(icomp, row0, row1, outbuf) outbuf, buf_write = buf_write, outbuf # avoid flushing writing buffer ti1 = (logger.process_clock(), logger.perf_counter()) log.debug1('step 2 [%d/%d] CPU time: %9.2f, Wall time: %9.2f', istep, ijmoblks, ti1[0]-ti0[0], ti1[1]-ti0[1]) ti0 = ti1 fswap = None if isinstance(erifile, str): feri.close() log.timer('AO->MO transformation for %s 2 pass'%intor, *time_1pass) log.timer('AO->MO transformation for %s '%intor, *time_0pass) return erifile
# swapfile will be overwritten if exists.
[docs] def half_e1(mol, mo_coeffs, swapfile, intor='int2e', aosym='s4', comp=1, max_memory=MAX_MEMORY, ioblk_size=IOBLK_SIZE, verbose=logger.WARN, compact=True, ao2mopt=None): r'''Half transform arbitrary spherical AO integrals to MO integrals for the given two sets of orbitals Args: mol : :class:`Mole` object AO integrals will be generated in terms of mol._atm, mol._bas, mol._env mo_coeff : ndarray Transform (ij|kl) with the same set of orbitals. swapfile : str or h5py File or h5py Group object To store the transformed integrals, in HDF5 format. The transformed integrals are saved in blocks. Kwargs intor : str Name of the 2-electron integral. Ref to :func:`getints_by_shell` for the complete list of available 2-electron integral names aosym : int or str Permutation symmetry for the AO integrals | 4 or '4' or 's4': 4-fold symmetry (default) | '2ij' or 's2ij' : symmetry between i, j in (ij|kl) | '2kl' or 's2kl' : symmetry between k, l in (ij|kl) | 1 or '1' or 's1': no symmetry | 'a4ij' : 4-fold symmetry with anti-symmetry between i, j in (ij|kl) (TODO) | 'a4kl' : 4-fold symmetry with anti-symmetry between k, l in (ij|kl) (TODO) | 'a2ij' : anti-symmetry between i, j in (ij|kl) (TODO) | 'a2kl' : anti-symmetry between k, l in (ij|kl) (TODO) comp : int Components of the integrals, e.g. int2e_ip_sph has 3 components. verbose : int Print level max_memory : float or int The maximum size of cache to use (in MB), large cache may **not** improve performance. ioblk_size : float or int The block size for IO, large block size may **not** improve performance verbose : int Print level compact : bool When compact is True, depending on the four orbital sets, the returned MO integrals has (up to 4-fold) permutation symmetry. If it's False, the function will abandon any permutation symmetry, and return the "plain" MO integrals ao2mopt : :class:`AO2MOpt` object Precomputed data to improve performance Returns: None ''' if any(c.dtype == numpy.complex128 for c in mo_coeffs): raise NotImplementedError('Integral transformation for complex orbitals') intor = mol._add_suffix(intor) time0 = (logger.process_clock(), logger.perf_counter()) log = logger.new_logger(mol, verbose) nao = mo_coeffs[0].shape[0] aosym = _stand_sym_code(aosym) if aosym in ('s4', 's2ij'): nao_pair = nao * (nao+1) // 2 else: nao_pair = nao * nao ijmosym, nij_pair, moij, ijshape = \ incore._conc_mos(mo_coeffs[0], mo_coeffs[1], compact and aosym in ('s4', 's2ij')) e1buflen, mem_words, iobuf_words, ioblk_words = \ guess_e1bufsize(max_memory, ioblk_size, nij_pair, nao_pair, comp) ioblk_size = ioblk_words * 8/1e6 # The buffer to hold AO integrals in C code, see line (@) aobuflen = max(int((mem_words - 2*comp*e1buflen*nij_pair) // (nao_pair*comp)), IOBUF_ROW_MIN) ao_loc = mol.ao_loc_nr('_cart' in intor) shranges = guess_shell_ranges(mol, (aosym in ('s4', 's2kl')), e1buflen, aobuflen, ao_loc) if ao2mopt is None: if intor == 'int2e_cart' or intor == 'int2e_sph': ao2mopt = _ao2mo.AO2MOpt(mol, intor, 'CVHFnr_schwarz_cond', 'CVHFsetnr_direct_scf') else: ao2mopt = _ao2mo.AO2MOpt(mol, intor) if isinstance(swapfile, h5py.Group): fswap = swapfile else: fswap = lib.H5TmpFile(swapfile) for icomp in range(comp): fswap.create_group(str(icomp)) # for h5py old version log.debug('step1: tmpfile %s %.8g MB', fswap.filename, nij_pair*nao_pair*8/1e6) log.debug('step1: (ij,kl) = (%d,%d), mem cache %.8g MB, iobuf %.8g MB', nij_pair, nao_pair, mem_words*8/1e6, iobuf_words*8/1e6) nstep = len(shranges) e1buflen = max([x[2] for x in shranges]) e2buflen, chunks = guess_e2bufsize(ioblk_size, nij_pair, e1buflen) def save(istep, iobuf): for icomp in range(comp): _transpose_to_h5g(fswap, '%d/%d'%(icomp,istep), iobuf[icomp], e2buflen, None) # transform e1 ti0 = log.timer('Initializing ao2mo.outcore.half_e1', *time0) with lib.call_in_background(save) as async_write: buf1 = numpy.empty((comp*e1buflen,nao_pair)) buf2 = numpy.empty((comp*e1buflen,nij_pair)) buf_write = numpy.empty_like(buf2) fill = _ao2mo.nr_e1fill f_e1 = _ao2mo.nr_e1 for istep,sh_range in enumerate(shranges): log.debug1('step 1 [%d/%d], AO [%d:%d], len(buf) = %d', istep+1, nstep, *(sh_range[:3])) buflen = sh_range[2] iobuf = numpy.ndarray((comp,buflen,nij_pair), buffer=buf2) nmic = len(sh_range[3]) p1 = 0 for imic, aoshs in enumerate(sh_range[3]): log.debug2(' fill iobuf micro [%d/%d], AO [%d:%d], len(aobuf) = %d', imic+1, nmic, *aoshs) buf = fill(intor, aoshs, mol._atm, mol._bas, mol._env, aosym, comp, ao2mopt, out=buf1).reshape(-1,nao_pair) buf = f_e1(buf, moij, ijshape, aosym, ijmosym) p0, p1 = p1, p1 + aoshs[2] iobuf[:,p0:p1] = buf.reshape(comp,aoshs[2],nij_pair) ti0 = log.timer_debug1('gen AO/transform MO [%d/%d]'%(istep+1,nstep), *ti0) async_write(istep, iobuf) buf2, buf_write = buf_write, buf2 fswap = None return swapfile
def _load_from_h5g(h5group, row0, row1, out=None): nkeys = len(h5group) dat = h5group['0'] ncol = sum(h5group[str(key)].shape[-1] for key in range(nkeys)) if dat.ndim == 2: out = numpy.ndarray((row1-row0, ncol), dat.dtype, buffer=out) col1 = 0 for key in range(nkeys): dat = h5group[str(key)][row0:row1] col0, col1 = col1, col1 + dat.shape[1] out[:,col0:col1] = dat else: # multiple components out = numpy.ndarray((dat.shape[0], row1-row0, ncol), dat.dtype, buffer=out) col1 = 0 for key in range(nkeys): dat = h5group[str(key)][:,row0:row1] col0, col1 = col1, col1 + dat.shape[2] out[:,:,col0:col1] = dat return out def _transpose_to_h5g(h5group, key, dat, blksize, chunks=None): nrow, ncol = dat.shape dset = h5group.create_dataset(key, (ncol,nrow), 'f8', chunks=chunks) for col0, col1 in prange(0, ncol, blksize): dset[col0:col1] = lib.transpose(dat[:,col0:col1])
[docs] def full_iofree(mol, mo_coeff, intor='int2e', aosym='s4', comp=None, max_memory=MAX_MEMORY, ioblk_size=IOBLK_SIZE, verbose=logger.WARN, compact=True): r'''Transfer arbitrary spherical AO integrals to MO integrals for given orbitals This function is a wrap for :func:`ao2mo.outcore.general`. It's not really IO free. The returned MO integrals are held in memory. For backward compatibility, it is used to replace the non-existed function direct.full_iofree. Args: mol : :class:`Mole` object AO integrals will be generated in terms of mol._atm, mol._bas, mol._env mo_coeff : ndarray Transform (ij|kl) with the same set of orbitals. erifile : str To store the transformed integrals, in HDF5 format. Kwargs dataname : str The dataset name in the erifile (ref the hierarchy of HDF5 format http://www.hdfgroup.org/HDF5/doc1.6/UG/09_Groups.html). By assigning different dataname, the existed integral file can be reused. If the erifile contains the dataname, the new integrals data will overwrite the old one. intor : str Name of the 2-electron integral. Ref to :func:`getints_by_shell` for the complete list of available 2-electron integral names aosym : int or str Permutation symmetry for the AO integrals | 4 or '4' or 's4': 4-fold symmetry (default) | '2ij' or 's2ij' : symmetry between i, j in (ij|kl) | '2kl' or 's2kl' : symmetry between k, l in (ij|kl) | 1 or '1' or 's1': no symmetry | 'a4ij' : 4-fold symmetry with anti-symmetry between i, j in (ij|kl) (TODO) | 'a4kl' : 4-fold symmetry with anti-symmetry between k, l in (ij|kl) (TODO) | 'a2ij' : anti-symmetry between i, j in (ij|kl) (TODO) | 'a2kl' : anti-symmetry between k, l in (ij|kl) (TODO) comp : int Components of the integrals, e.g. int2e_ip_sph has 3 components. verbose : int Print level max_memory : float or int The maximum size of cache to use (in MB), large cache may **not** improve performance. ioblk_size : float or int The block size for IO, large block size may **not** improve performance verbose : int Print level compact : bool When compact is True, depending on the four orbital sets, the returned MO integrals has (up to 4-fold) permutation symmetry. If it's False, the function will abandon any permutation symmetry, and return the "plain" MO integrals Returns: 2D/3D MO-integral array. They may or may not have the permutation symmetry, depending on the given orbitals, and the kwargs compact. If the four sets of orbitals are identical, the MO integrals will at most have 4-fold symmetry. Examples: >>> from pyscf import gto >>> from pyscf import ao2mo >>> mol = gto.M(atom='O 0 0 0; H 0 1 0; H 0 0 1', basis='sto3g') >>> mo1 = numpy.random.random((mol.nao_nr(), 10)) >>> eri1 = ao2mo.outcore.full_iofree(mol, mo1) >>> print(eri1.shape) (55, 55) >>> eri1 = ao2mo.outcore.full_iofree(mol, mo1, compact=False) >>> print(eri1.shape) (100, 100) >>> eri1 = ao2mo.outcore.full_iofree(mol, mo1, intor='int2e_ip1_sph', aosym='s1', comp=3) >>> print(eri1.shape) (3, 100, 100) >>> eri1 = ao2mo.outcore.full_iofree(mol, mo1, intor='int2e_ip1_sph', aosym='s2kl', comp=3) >>> print(eri1.shape) (3, 100, 55) ''' with lib.H5TmpFile() as feri: general(mol, (mo_coeff,)*4, feri, dataname='eri_mo', intor=intor, aosym=aosym, comp=comp, max_memory=max_memory, ioblk_size=ioblk_size, verbose=verbose, compact=compact) return numpy.asarray(feri['eri_mo'])
[docs] def general_iofree(mol, mo_coeffs, intor='int2e', aosym='s4', comp=None, max_memory=MAX_MEMORY, ioblk_size=IOBLK_SIZE, verbose=logger.WARN, compact=True): r'''For the given four sets of orbitals, transfer arbitrary spherical AO integrals to MO integrals on the fly. This function is a wrap for :func:`ao2mo.outcore.general`. It's not really IO free. The returned MO integrals are held in memory. For backward compatibility, it is used to replace the non-existed function direct.general_iofree. Args: mol : :class:`Mole` object AO integrals will be generated in terms of mol._atm, mol._bas, mol._env mo_coeffs : 4-item list of ndarray Four sets of orbital coefficients, corresponding to the four indices of (ij|kl) Kwargs intor : str Name of the 2-electron integral. Ref to :func:`getints_by_shell` for the complete list of available 2-electron integral names aosym : int or str Permutation symmetry for the AO integrals | 4 or '4' or 's4': 4-fold symmetry (default) | '2ij' or 's2ij' : symmetry between i, j in (ij|kl) | '2kl' or 's2kl' : symmetry between k, l in (ij|kl) | 1 or '1' or 's1': no symmetry | 'a4ij' : 4-fold symmetry with anti-symmetry between i, j in (ij|kl) (TODO) | 'a4kl' : 4-fold symmetry with anti-symmetry between k, l in (ij|kl) (TODO) | 'a2ij' : anti-symmetry between i, j in (ij|kl) (TODO) | 'a2kl' : anti-symmetry between k, l in (ij|kl) (TODO) comp : int Components of the integrals, e.g. int2e_ip_sph has 3 components. verbose : int Print level compact : bool When compact is True, depending on the four orbital sets, the returned MO integrals has (up to 4-fold) permutation symmetry. If it's False, the function will abandon any permutation symmetry, and return the "plain" MO integrals Returns: 2D/3D MO-integral array. They may or may not have the permutation symmetry, depending on the given orbitals, and the kwargs compact. If the four sets of orbitals are identical, the MO integrals will at most have 4-fold symmetry. Examples: >>> from pyscf import gto >>> from pyscf import ao2mo >>> import h5py >>> def view(h5file, dataname='eri_mo'): ... f5 = h5py.File(h5file, 'r') ... print('dataset %s, shape %s' % (str(f5.keys()), str(f5[dataname].shape))) ... f5.close() >>> mol = gto.M(atom='O 0 0 0; H 0 1 0; H 0 0 1', basis='sto3g') >>> mo1 = numpy.random.random((mol.nao_nr(), 10)) >>> mo2 = numpy.random.random((mol.nao_nr(), 8)) >>> mo3 = numpy.random.random((mol.nao_nr(), 6)) >>> mo4 = numpy.random.random((mol.nao_nr(), 4)) >>> eri1 = ao2mo.outcore.general_iofree(mol, (mo1,mo2,mo3,mo4)) >>> print(eri1.shape) (80, 24) >>> eri1 = ao2mo.outcore.general_iofree(mol, (mo1,mo2,mo3,mo3)) >>> print(eri1.shape) (80, 21) >>> eri1 = ao2mo.outcore.general_iofree(mol, (mo1,mo2,mo3,mo3), compact=False) >>> print(eri1.shape) (80, 36) >>> eri1 = ao2mo.outcore.general_iofree(mol, (mo1,mo1,mo1,mo1), intor='int2e_ip1_sph', aosym='s1', comp=3) >>> print(eri1.shape) (3, 100, 100) >>> eri1 = ao2mo.outcore.general_iofree(mol, (mo1,mo1,mo1,mo1), intor='int2e_ip1_sph', aosym='s2kl', comp=3) >>> print(eri1.shape) (3, 100, 55) ''' with lib.H5TmpFile() as feri: general(mol, mo_coeffs, feri, dataname='eri_mo', intor=intor, aosym=aosym, comp=comp, max_memory=max_memory, ioblk_size=ioblk_size, verbose=verbose, compact=compact) return numpy.asarray(feri['eri_mo'])
[docs] def iden_coeffs(mo1, mo2): return (id(mo1) == id(mo2)) \ or (mo1.shape==mo2.shape and numpy.allclose(mo1,mo2))
[docs] def prange(start, end, step): for i in range(start, end, step): yield i, min(i+step, end)
[docs] def guess_e1bufsize(max_memory, ioblk_size, nij_pair, nao_pair, comp): mem_words = max(1, max_memory * 1e6 / 8) # part of the max_memory is used to hold the AO integrals. The iobuf is the # buffer to temporary hold the transformed integrals before streaming to disk. # iobuf is then divided to small blocks (ioblk_words) and streamed to disk. iobuf_words = max(int(mem_words//6), IOBUF_WORDS) ioblk_words = int(min(ioblk_size*1e6/8, iobuf_words)) e1buflen = int(mem_words*.66/(comp*(nij_pair*2+nao_pair))) e1buflen = max(e1buflen, IOBUF_ROW_MIN) return e1buflen, mem_words, iobuf_words, ioblk_words
[docs] def guess_e2bufsize(ioblk_size, nrows, ncols): e2buflen = int(min(ioblk_size*1e6/8/ncols, nrows)) e2buflen = max(e2buflen//IOBUF_ROW_MIN, 1) * IOBUF_ROW_MIN chunks = (IOBUF_ROW_MIN, ncols) return e2buflen, chunks
# based on the size of buffer, dynamic range of AO-shells for each buffer
[docs] def guess_shell_ranges(mol, aosym, max_iobuf, max_aobuf=None, ao_loc=None, compress_diag=True): if ao_loc is None: ao_loc = mol.ao_loc_nr() max_iobuf = max(1, max_iobuf) dims = ao_loc[1:] - ao_loc[:-1] dijs = (dims.reshape(-1,1) * dims) nbas = dijs.shape[0] if aosym: if compress_diag: #:for i in range(mol.nbas): #: di = ao_loc[i+1] - ao_loc[i] #: for j in range(i): #: dj = ao_loc[j+1] - ao_loc[j] #: lstdij.append(di*dj) #: lstdij.append(di*(di+1)//2) idx = numpy.arange(nbas) dijs[idx,idx] = dims*(dims+1)//2 lstdij = dijs[numpy.tril_indices(nbas)] else: #:for i in range(mol.nbas): #: di = ao_loc[i+1] - ao_loc[i] #: for j in range(i+1): #: dj = ao_loc[j+1] - ao_loc[j] #: lstdij.append(di*dj) lstdij = dijs[numpy.tril_indices(nbas)] else: #:for i in range(mol.nbas): #: di = ao_loc[i+1] - ao_loc[i] #: for j in range(mol.nbas): #: dj = ao_loc[j+1] - ao_loc[j] #: lstdij.append(di*dj) lstdij = dijs.ravel() dij_loc = numpy.append(0, numpy.cumsum(lstdij)) ijsh_range = balance_partition(dij_loc, max_iobuf) if max_aobuf is not None: max_aobuf = max(1, max_aobuf) def div_each_iobuf(ijstart, ijstop, buflen): # to fill each iobuf, AO integrals may need to be fill to aobuf several times return (ijstart, ijstop, buflen, balance_partition(dij_loc, max_aobuf, ijstart, ijstop)) ijsh_range = [div_each_iobuf(*x) for x in ijsh_range] return ijsh_range
def _stand_sym_code(sym): if isinstance(sym, int): return 's%d' % sym elif 's' == sym[0] or 'a' == sym[0]: return sym else: return 's' + sym
[docs] def balance_segs(segs_lst, blksize, start_id=0, stop_id=None): loc = numpy.append(0, numpy.cumsum(segs_lst)) return balance_partition(loc, blksize, start_id, stop_id)
[docs] def balance_partition(ao_loc, blksize, start_id=0, stop_id=None): if stop_id is None: stop_id = len(ao_loc) - 1 else: stop_id = min(stop_id, start_id+len(ao_loc)-1) displs = lib.misc._blocksize_partition(ao_loc[start_id:stop_id+1], blksize) displs = [i+start_id for i in displs] tasks = [] for i0, i1 in zip(displs[:-1],displs[1:]): tasks.append((i0, i1, ao_loc[i1]-ao_loc[i0])) return tasks
del (MAX_MEMORY) if __name__ == '__main__': from pyscf import scf from pyscf.ao2mo import addons mol = gto.Mole() mol.verbose = 5 #mol.output = 'out_outcore' mol.atom = [ ["O" , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = {'H': 'cc-pvtz', 'O': 'cc-pvtz',} mol.build() nao = mol.nao_nr() npair = nao*(nao+1)//2 rhf = scf.RHF(mol) rhf.scf() print(logger.process_clock()) full(mol, rhf.mo_coeff, 'h2oeri.h5', max_memory=10, ioblk_size=5) print(logger.process_clock()) eri0 = incore.full(rhf._eri, rhf.mo_coeff) feri = h5py.File('h2oeri.h5', 'r') print('full', abs(eri0-feri['eri_mo']).sum()) feri.close() print(logger.process_clock()) c = rhf.mo_coeff general(mol, (c,c,c,c), 'h2oeri.h5', max_memory=10, ioblk_size=5) print(logger.process_clock()) feri = h5py.File('h2oeri.h5', 'r') print('general', abs(eri0-feri['eri_mo']).sum()) feri.close() # set ijsame and klsame to False, then check c = rhf.mo_coeff n = c.shape[1] general(mol, (c,c,c,c), 'h2oeri.h5', max_memory=10, ioblk_size=5, compact=False) feri = h5py.File('h2oeri.h5', 'r') eri1 = numpy.array(feri['eri_mo']).reshape(n,n,n,n) eri1 = addons.restore(4, eri1, n) print('general', abs(eri0-eri1).sum())