Ejemplo n.º 1
0
def scf_set_reference_local(name):
    """
    Figures out the correct SCF reference to set locally
    """

    optstash = p4util.OptionsState(
        ['SCF', 'DFT_FUNCTIONAL'],
        ['SCF', 'SCF_TYPE'],
        ['SCF', 'REFERENCE'])

    # Alter default algorithm
    if not core.has_option_changed('SCF', 'SCF_TYPE'):
        core.set_local_option('SCF', 'SCF_TYPE', 'DF')

    if name == 'hf':
        if core.get_option('SCF','REFERENCE') == 'RKS':
            core.set_local_option('SCF','REFERENCE','RHF')
        elif core.get_option('SCF','REFERENCE') == 'UKS':
            core.set_local_option('SCF','REFERENCE','UHF')
    elif name == 'scf':
        if core.get_option('SCF','REFERENCE') == 'RKS':
            if (len(core.get_option('SCF', 'DFT_FUNCTIONAL')) > 0) or core.get_option('SCF', 'DFT_CUSTOM_FUNCTIONAL') is not None:
                pass
            else:
                core.set_local_option('SCF','REFERENCE','RHF')
        elif core.get_option('SCF','REFERENCE') == 'UKS':
            if (len(core.get_option('SCF', 'DFT_FUNCTIONAL')) > 0) or core.get_option('SCF', 'DFT_CUSTOM_FUNCTIONAL') is not None:
                pass
            else:
                core.set_local_option('SCF','REFERENCE','UHF')
    return optstash
Ejemplo n.º 2
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def scf_set_reference_local(name, is_dft=False):
    """
    Figures out the correct SCF reference to set locally
    """

    optstash = p4util.OptionsState(
        ['SCF_TYPE'],
        ['SCF', 'REFERENCE'])

    # Alter default algorithm
    if not core.has_global_option_changed('SCF_TYPE'):
        core.set_global_option('SCF_TYPE', 'DF')

    # Alter reference name if needed
    user_ref = core.get_option('SCF', 'REFERENCE')

    sup = build_superfunctional_from_dictionary(functionals[name], 1, 1, True)[0]
    if sup.needs_xc() or is_dft:
        if (user_ref == 'RHF'):
            core.set_local_option('SCF', 'REFERENCE', 'RKS')
        elif (user_ref == 'UHF'):
            core.set_local_option('SCF', 'REFERENCE', 'UKS')
        elif (user_ref == 'ROHF'):
            raise ValidationError('ROHF reference for DFT is not available.')
        elif (user_ref == 'CUHF'):
            raise ValidationError('CUHF reference for DFT is not available.')
    # else we are doing HF and nothing needs to be overloaded

    return optstash
Ejemplo n.º 3
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def set_module_options(module, options_dict):
    """
    Sets Psi4 module options from a module specification and input dictionary.
    """

    for k, v, in options_dict.items():
        core.set_local_option(module.upper(), k.upper(), v)
Ejemplo n.º 4
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 def restore(self):
     core.set_global_option(self.option, self.value_global)
     if not self.haschanged_global:
         core.revoke_global_option_changed(self.option)
     if self.module:
         core.set_local_option(self.module, self.option, self.value_local)
         if not self.haschanged_local:
             core.revoke_local_option_changed(self.module, self.option)
Ejemplo n.º 5
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def df_mp2_sapt_dispersion(dimer_wfn, wfn_A, wfn_B, primary_basis, aux_basis, cache, do_print=True):

    if do_print:
        core.print_out("\n  ==> E20 Dispersion (MP2) <== \n\n")

    optstash = p4util.OptionsState(['SAPT', 'SAPT0_E10'], ['SAPT', 'SAPT0_E20IND'], ['SAPT', 'SAPT0_E20DISP'],
                                   ['SAPT', 'SAPT_QUIET'])

    core.set_local_option("SAPT", "SAPT0_E10", False)
    core.set_local_option("SAPT", "SAPT0_E20IND", False)
    core.set_local_option("SAPT", "SAPT0_E20DISP", True)
    core.set_local_option("SAPT", "SAPT_QUIET", True)

    if core.get_option('SCF', 'REFERENCE') == 'RHF':
        core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERA, 'monomerA', 'dimer')
        core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERB, 'monomerB', 'dimer')

    core.IO.set_default_namespace('dimer')

    dimer_wfn.set_basisset("DF_BASIS_SAPT", aux_basis)
    dimer_wfn.set_basisset("DF_BASIS_ELST", aux_basis)
    e_sapt = core.sapt(dimer_wfn, wfn_A, wfn_B)

    optstash.restore()

    svars = dimer_wfn.variables()

    core.print_out("\n")
    core.print_out(print_sapt_var("Disp20 (MP2)", svars["E DISP20"], short=True) + "\n")
    core.print_out(print_sapt_var("Exch-Disp20,u", svars["E EXCH-DISP20"], short=True) + "\n")

    ret = {}
    ret["Exch-Disp20,u"] = svars["E EXCH-DISP20"]
    ret["Disp20,u"] = svars["E DISP20"]
    return ret
Ejemplo n.º 6
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def dft_set_reference_local(name):
    """
    Figures out the correct DFT reference to set locally
    """

    optstash = p4util.OptionsState(
        ['SCF', 'DFT_FUNCTIONAL'],
        ['SCF', 'REFERENCE'],
        ['SCF', 'SCF_TYPE'],
        ['DF_BASIS_MP2'],
        ['DFMP2', 'MP2_OS_SCALE'],
        ['DFMP2', 'MP2_SS_SCALE'])

    # Alter default algorithm
    if not core.has_option_changed('SCF', 'SCF_TYPE'):
        core.set_local_option('SCF', 'SCF_TYPE', 'DF')

    core.set_local_option('SCF', 'DFT_FUNCTIONAL', name)

    user_ref = core.get_option('SCF', 'REFERENCE')
    if (user_ref == 'RHF'):
        core.set_local_option('SCF', 'REFERENCE', 'RKS')
    elif (user_ref == 'UHF'):
        core.set_local_option('SCF', 'REFERENCE', 'UKS')
    elif (user_ref == 'ROHF'):
        raise ValidationError('ROHF reference for DFT is not available.')
    elif (user_ref == 'CUHF'):
        raise ValidationError('CUHF reference for DFT is not available.')

    return optstash
Ejemplo n.º 7
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    def set_cholesky_from(mtd_type):
        type_val = core.get_global_option(mtd_type)
        if type_val == 'CD':
            core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', 'CHOLESKY')
            # Alter default algorithm
            if not core.has_global_option_changed('SCF_TYPE'):
                optstash.add_option(['SCF_TYPE'])
                core.set_global_option('SCF_TYPE', 'CD')
                core.print_out("""    SCF Algorithm Type (re)set to CD.\n""")

        elif type_val in ['DF', 'DISK_DF']:
            if core.get_option('GPU_DFCC', 'DF_BASIS_CC') == 'CHOLESKY':
                core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', '')

            proc_util.check_disk_df(name.upper(), optstash)
        else:
            raise ValidationError("""Invalid type '%s' for DFCC""" % type_val)
Ejemplo n.º 8
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def set_options(options_dict, verbose=1):
    """Sets Psi4 options from an input dictionary.

    Parameters
    ----------
    options_dict : dict
        Dictionary where keys are "option_name" for global options or
        "module_name__option_name" (double underscore separation) for
        option local to "module_name". Values are the option value. All
        are case insensitive.
    verbose : int, optional
        Control print volume.

    Returns
    -------
    None

    """
    optionre = re.compile(r'\A(?P<module>\w+__)?(?P<option>\w+)\Z', re.IGNORECASE)
    rejected = {}

    for k, v, in options_dict.items():
        mobj = optionre.match(k)
        module = mobj.group('module').upper()[:-2] if mobj.group('module') else None
        option = mobj.group('option').upper()

        if module:
            if (module, option, v) not in [('SCF', 'GUESS', 'READ')]:
                # TODO guess/read exception is for distributed driver. should be handled differently.
                try:
                    core.set_local_option(module, option, v)
                except RuntimeError as err:
                    rejected[k] = (v, err)
                if verbose > 1:
                    print('Setting: core.set_local_option', module, option, v)
        else:
            try:
                core.set_global_option(option, v)
            except RuntimeError as err:
                rejected[k] = (v, err)
            if verbose > 1:
                print('Setting: core.set_global_option', option, v)

    if rejected:
        raise ValidationError(f'Error setting options: {rejected}')
Ejemplo n.º 9
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def pcm_helper(block):
    """
    Passes multiline string *block* to PCMSolver parser.

    Parameters
    ----------
    block: multiline string with PCM input in PCMSolver syntax.
    """

    suffix = str(os.getpid()) + '.' + str(uuid.uuid4())[:8]
    pcmsolver_fname = 'pcmsolver.' + suffix + '.inp'
    with open(pcmsolver_fname, 'w') as handle:
        handle.write(block)
    import pcmsolver
    parsed_pcm = pcmsolver.parse_pcm_input(pcmsolver_fname)
    os.remove(pcmsolver_fname)
    pcmsolver_parsed_fname = '@pcmsolver.' + suffix
    with open(pcmsolver_parsed_fname, 'w') as tmp:
        tmp.write(parsed_pcm)
    core.set_local_option('PCM', 'PCMSOLVER_PARSED_FNAME', '{}'.format(pcmsolver_parsed_fname))
Ejemplo n.º 10
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def process_option(spaces, module, key, value, line):
    """Function to process a line with set or in a set block
    into global/local domain and keyword/value.

    """
    module = module.upper()
    key = key.upper()
    isbasis = True if 'BASIS' in key else False
    value = quotify(value.strip(), isbasis=isbasis)

    if module == "GLOBALS" or module == "GLOBAL" or module == "" or module.isspace():
        # If it's really a global, we need slightly different syntax
        if runalso:
            core.set_global_option(key, dequotify(value))
        return "%score.set_global_option(\"%s\", %s)\n" % (spaces, key, value)
    else:
        # It's a local option, so we need the module name in there too
        if runalso:
            core.set_local_option(module, key, dequotify(value))
        return "%score.set_local_option(\"%s\", \"%s\", %s)\n" % (spaces, module, key, value)
Ejemplo n.º 11
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def pcm_helper(block):
    """
    Passes multiline string *block* to PCMSolver parser.

    Parameters
    ----------
    block: multiline string with PCM input in PCMSolver syntax.
    """

    suffix = str(os.getpid()) + '.' + str(uuid.uuid4())[:8]
    pcmsolver_fname = 'pcmsolver.' + suffix + '.inp'
    with open(pcmsolver_fname, 'w') as handle:
        handle.write(block)
    import pcmsolver
    parsed_pcm = pcmsolver.parse_pcm_input(pcmsolver_fname)
    os.remove(pcmsolver_fname)
    pcmsolver_parsed_fname = '@pcmsolver.' + suffix
    with open(pcmsolver_parsed_fname, 'w') as tmp:
        tmp.write(parsed_pcm)
    core.set_local_option('PCM', 'PCMSOLVER_PARSED_FNAME',
                          '{}'.format(pcmsolver_parsed_fname))
Ejemplo n.º 12
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def scf_set_reference_local(name, is_dft=False):
    """
    Figures out the correct SCF reference to set locally
    """

    optstash = p4util.OptionsState(
        ['SCF', 'SCF_TYPE'],
        ['SCF', 'REFERENCE'])

    # Alter default algorithm
    if not core.has_option_changed('SCF', 'SCF_TYPE'):
        core.set_local_option('SCF', 'SCF_TYPE', 'DF')

    # Alter reference name if needed
    user_ref = core.get_option('SCF', 'REFERENCE')
    if (name not in dft_funcs.superfunctional_noxc_names) or (is_dft):
        if (user_ref == 'RHF'):
            core.set_local_option('SCF', 'REFERENCE', 'RKS')
        elif (user_ref == 'UHF'):
            core.set_local_option('SCF', 'REFERENCE', 'UKS')
        elif (user_ref == 'ROHF'):
            raise ValidationError('ROHF reference for DFT is not available.')
        elif (user_ref == 'CUHF'):
            raise ValidationError('CUHF reference for DFT is not available.')
    # else we are doing HF and nothing needs to be overloaded

    return optstash
Ejemplo n.º 13
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def scf_set_reference_local(name, is_dft=False):
    """
    Figures out the correct SCF reference to set locally
    """

    optstash = p4util.OptionsState(['SCF', 'SCF_TYPE'], ['SCF', 'REFERENCE'])

    # Alter default algorithm
    if not core.has_option_changed('SCF', 'SCF_TYPE'):
        core.set_local_option('SCF', 'SCF_TYPE', 'DF')

    # Alter reference name if needed
    user_ref = core.get_option('SCF', 'REFERENCE')

    sup = build_superfunctional_from_dictionary(functionals[name], 1, 1,
                                                True)[0]
    if sup.needs_xc() or is_dft:
        if (user_ref == 'RHF'):
            core.set_local_option('SCF', 'REFERENCE', 'RKS')
        elif (user_ref == 'UHF'):
            core.set_local_option('SCF', 'REFERENCE', 'UKS')
        elif (user_ref == 'ROHF'):
            raise ValidationError('ROHF reference for DFT is not available.')
        elif (user_ref == 'CUHF'):
            raise ValidationError('CUHF reference for DFT is not available.')
    # else we are doing HF and nothing needs to be overloaded

    return optstash
Ejemplo n.º 14
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    def _init_addghost_C(self, oldcalc, calc):
        # print('Adding ghost %s->%s' % (oldcalc, calc))

        old_filename = self._fmt_mo_fn(oldcalc)
        data = np.load(old_filename)
        Ca_occ = core.Matrix.np_read(data, "Ca_occ")
        Cb_occ = core.Matrix.np_read(data, "Cb_occ")

        m1_nso = self.wfn_cache[('m1', 'm', oldcalc.Z)].nso()
        m2_nso = self.wfn_cache[('m2', 'm', oldcalc.Z)].nso()
        m1_nalpha = self.wfn_cache[('m1', 'm', oldcalc.Z)].nalpha()
        m2_nalpha = self.wfn_cache[('m2', 'm', oldcalc.Z)].nalpha()
        m1_nbeta = self.wfn_cache[('m1', 'm', oldcalc.Z)].nbeta()
        m2_nbeta = self.wfn_cache[('m2', 'm', oldcalc.Z)].nbeta()

        if calc.V == 'm1':
            Ca_occ_d = core.Matrix('Ca_occ', (m1_nso + m2_nso), m1_nalpha)
            Ca_occ_d.np[:m1_nso, :] = Ca_occ.np[:, :]
            Cb_occ_d = core.Matrix('Cb_occ', (m1_nso + m2_nso), m1_nbeta)
            Cb_occ_d.np[:m1_nso, :] = Cb_occ.np[:, :]
        elif calc.V == 'm2':
            Ca_occ_d = core.Matrix('Ca_occ', (m1_nso + m2_nso), m2_nalpha)
            Ca_occ_d.np[-m2_nso:, :] = Ca_occ.np[:, :]

            Cb_occ_d = core.Matrix('Cb_occ', (m1_nso + m2_nso), m2_nbeta)
            Cb_occ_d.np[-m2_nso:, :] = Cb_occ.np[:, :]

        data_dict = dict(data)
        data_dict.update(Ca_occ_d.np_write(prefix='Ca_occ'))
        data_dict.update(Cb_occ_d.np_write(prefix='Cb_occ'))

        psi_scratch = core.IOManager.shared_object().get_default_path()
        write_filename = os.path.join(
            psi_scratch,
            os.path.split(
                os.path.abspath(core.get_writer_file_prefix(
                    self.fmt_ns(calc))))[1] + ".180.npz")
        np.savez(write_filename, **data_dict)
        extras.register_numpy_file(write_filename)
        core.set_local_option('SCF', 'GUESS', 'READ')
Ejemplo n.º 15
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def process_option(spaces, module, key, value, line):
    """Function to process a line with set or in a set block
    into global/local domain and keyword/value.

    """
    module = module.upper()
    key = key.upper()
    isbasis = True if 'BASIS' in key else False
    value = quotify(value.strip(), isbasis=isbasis)

    if module == "GLOBALS" or module == "GLOBAL" or module == "" or module.isspace(
    ):
        # If it's really a global, we need slightly different syntax
        if runalso:
            core.set_global_option(key, dequotify(value))
        return "%score.set_global_option(\"%s\", %s)\n" % (spaces, key, value)
    else:
        # It's a local option, so we need the module name in there too
        if runalso:
            core.set_local_option(module, key, dequotify(value))
        return "%score.set_local_option(\"%s\", \"%s\", %s)\n" % (
            spaces, module, key, value)
Ejemplo n.º 16
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def df_mp2_sapt_dispersion(dimer_wfn,
                           wfn_A,
                           wfn_B,
                           primary_basis,
                           aux_basis,
                           cache,
                           do_print=True):

    if do_print:
        core.print_out("\n  ==> E20 Dispersion (MP2) <== \n\n")

    optstash = p4util.OptionsState(['SAPT', 'SAPT0_E10'],
                                   ['SAPT', 'SAPT0_E20IND'],
                                   ['SAPT', 'SAPT0_E20DISP'],
                                   ['SAPT', 'SAPT_QUIET'])

    core.set_local_option("SAPT", "SAPT0_E10", False)
    core.set_local_option("SAPT", "SAPT0_E20IND", False)
    core.set_local_option("SAPT", "SAPT0_E20DISP", True)
    core.set_local_option("SAPT", "SAPT_QUIET", True)

    if core.get_option('SCF', 'REFERENCE') == 'RHF':
        core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERA, 'monomerA',
                                      'dimer')
        core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERB, 'monomerB',
                                      'dimer')

    core.IO.set_default_namespace('dimer')

    dimer_wfn.set_basisset("DF_BASIS_SAPT", aux_basis)
    dimer_wfn.set_basisset("DF_BASIS_ELST", aux_basis)
    e_sapt = core.sapt(dimer_wfn, wfn_A, wfn_B)

    optstash.restore()

    svars = dimer_wfn.variables()

    core.print_out("\n")
    core.print_out(
        print_sapt_var("Disp20 (MP2)", svars["E DISP20"], short=True) + "\n")
    core.print_out(
        print_sapt_var("Exch-Disp20,u", svars["E EXCH-DISP20"], short=True) +
        "\n")

    ret = {}
    ret["Exch-Disp20,u"] = svars["E EXCH-DISP20"]
    ret["Disp20,u"] = svars["E DISP20"]
    return ret
Ejemplo n.º 17
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def _reset_pe_options(pofm: Dict):
    """Acts on ``Process::environment.options`` to clear it, then set it to state encoded in **pofm**.

    Parameters
    ----------
    pofm
        Result of :py:func:`psi4.driver.p4util.prepare_options_for_modules(changedOnly=True, commandsInsteadDict=False, stateInsteadMediated=True)`

    Returns
    -------
    None

    """
    core.clean_options()

    for go, dgo in pofm['GLOBALS'].items():
        if dgo['has_changed']:
            core.set_global_option(go, dgo['value'])

    for module in _modules:
        for lo, dlo in pofm[module].items():
            if dlo['has_changed']:
                core.set_local_option(module, lo, dlo['value'])
Ejemplo n.º 18
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def reset_pe_options(pofm):
    """Acts on Process::environment.options to clear it, the set it to state encoded in `pofm`.

    Parameters
    ----------
    pofm : dict
        Result of psi4.driver.p4util.prepare_options_for_modules(changedOnly=True, commandsInsteadDict=False)

    Returns
    -------
    None

    """
    core.clean_options()

    for go, dgo in pofm['GLOBALS'].items():
        if dgo['has_changed']:
            core.set_global_option(go, dgo['value'])

    for module in _modules:
        for lo, dlo in pofm[module].items():
            if dlo['has_changed']:
                core.set_local_option(module, lo, dlo['value'])
Ejemplo n.º 19
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def reset_pe_options(pofm):
    """Acts on Process::environment.options to clear it, the set it to state encoded in `pofm`.

    Parameters
    ----------
    pofm : dict
        Result of psi4.driver.p4util.prepare_options_for_modules(changedOnly=True, commandsInsteadDict=False)

    Returns
    -------
    None

    """
    core.clean_options()

    for go, dgo in pofm['GLOBALS'].items():
        if dgo['has_changed']:
            core.set_global_option(go, dgo['value'])

    for module in _modules:
        for lo, dlo in pofm[module].items():
            if dlo['has_changed']:
                core.set_local_option(module, lo, dlo['value'])
Ejemplo n.º 20
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def run_sapt_dft(name, **kwargs):
    optstash = p4util.OptionsState(['SCF_TYPE'], ['SCF', 'REFERENCE'],
                                   ['SCF', 'DFT_GRAC_SHIFT'],
                                   ['SCF', 'SAVE_JK'])

    core.tstart()
    # Alter default algorithm
    if not core.has_global_option_changed('SCF_TYPE'):
        core.set_global_option('SCF_TYPE', 'DF')

    core.prepare_options_for_module("SAPT")

    # Get the molecule of interest
    ref_wfn = kwargs.get('ref_wfn', None)
    if ref_wfn is None:
        sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
    else:
        core.print_out(
            'Warning! SAPT argument "ref_wfn" is only able to use molecule information.'
        )
        sapt_dimer = ref_wfn.molecule()

    sapt_dimer, monomerA, monomerB = proc_util.prepare_sapt_molecule(
        sapt_dimer, "dimer")

    # Grab overall settings
    mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
    mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
    do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
    sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")

    # Print out the title and some information
    core.print_out("\n")
    core.print_out(
        "         ---------------------------------------------------------\n")
    core.print_out("         " + "SAPT(DFT) Procedure".center(58) + "\n")
    core.print_out("\n")
    core.print_out("         " + "by Daniel G. A. Smith".center(58) + "\n")
    core.print_out(
        "         ---------------------------------------------------------\n")
    core.print_out("\n")

    core.print_out(
        "  !!!  WARNING:  SAPT(DFT) capability is in beta. Please use with caution. !!!\n\n"
    )

    core.print_out("  ==> Algorithm <==\n\n")
    core.print_out("   SAPT DFT Functional     %12s\n" %
                   str(sapt_dft_functional))
    core.print_out("   Monomer A GRAC Shift    %12.6f\n" % mon_a_shift)
    core.print_out("   Monomer B GRAC Shift    %12.6f\n" % mon_b_shift)
    core.print_out("   Delta HF                %12s\n" %
                   ("True" if do_delta_hf else "False"))
    core.print_out("   JK Algorithm            %12s\n" %
                   core.get_global_option("SCF_TYPE"))
    core.print_out("\n")
    core.print_out("   Required computations:\n")
    if (do_delta_hf):
        core.print_out("     HF  (Dimer)\n")
        core.print_out("     HF  (Monomer A)\n")
        core.print_out("     HF  (Monomer B)\n")
    core.print_out("     DFT (Monomer A)\n")
    core.print_out("     DFT (Monomer B)\n")
    core.print_out("\n")

    if (sapt_dft_functional != "HF") and ((mon_a_shift == 0.0) or
                                          (mon_b_shift == 0.0)):
        raise ValidationError(
            'SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')

    if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
        raise ValidationError(
            'SAPT(DFT) currently only supports restricted references.')

    core.IO.set_default_namespace('dimer')
    data = {}

    if (core.get_global_option('SCF_TYPE') == 'DF'):
        # core.set_global_option('DF_INTS_IO', 'LOAD')
        core.set_global_option('DF_INTS_IO', 'SAVE')

    # # Compute dimer wavefunction
    hf_wfn_dimer = None
    if do_delta_hf:
        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.set_global_option('DF_INTS_IO', 'SAVE')

        core.timer_on("SAPT(DFT): Dimer SCF")
        hf_data = {}
        hf_wfn_dimer = scf_helper("SCF",
                                  molecule=sapt_dimer,
                                  banner="SAPT(DFT): delta HF Dimer",
                                  **kwargs)
        hf_data["HF DIMER"] = core.variable("CURRENT ENERGY")
        core.timer_off("SAPT(DFT): Dimer SCF")

        core.timer_on("SAPT(DFT): Monomer A SCF")
        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'dimer', 'monomerA')

        hf_wfn_A = scf_helper("SCF",
                              molecule=monomerA,
                              banner="SAPT(DFT): delta HF Monomer A",
                              **kwargs)
        hf_data["HF MONOMER A"] = core.variable("CURRENT ENERGY")
        core.timer_off("SAPT(DFT): Monomer A SCF")

        core.timer_on("SAPT(DFT): Monomer B SCF")
        core.set_global_option("SAVE_JK", True)
        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerA', 'monomerB')

        hf_wfn_B = scf_helper("SCF",
                              molecule=monomerB,
                              banner="SAPT(DFT): delta HF Monomer B",
                              **kwargs)
        hf_data["HF MONOMER B"] = core.variable("CURRENT ENERGY")
        core.set_global_option("SAVE_JK", False)
        core.timer_off("SAPT(DFT): Monomer B SCF")

        # Grab JK object and set to A (so we do not save many JK objects)
        sapt_jk = hf_wfn_B.jk()
        hf_wfn_A.set_jk(sapt_jk)
        core.set_global_option("SAVE_JK", False)

        # Move it back to monomer A
        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerB', 'dimer')

        core.print_out("\n")
        core.print_out(
            "         ---------------------------------------------------------\n"
        )
        core.print_out("         " + "SAPT(DFT): delta HF Segment".center(58) +
                       "\n")
        core.print_out("\n")
        core.print_out("         " +
                       "by Daniel G. A. Smith and Rob Parrish".center(58) +
                       "\n")
        core.print_out(
            "         ---------------------------------------------------------\n"
        )
        core.print_out("\n")

        # Build cache
        hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B,
                                                     sapt_jk, True)

        # Electrostatics
        core.timer_on("SAPT(DFT):SAPT:elst")
        elst = sapt_jk_terms.electrostatics(hf_cache, True)
        hf_data.update(elst)
        core.timer_off("SAPT(DFT):SAPT:elst")

        # Exchange
        core.timer_on("SAPT(DFT):SAPT:exch")
        exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
        hf_data.update(exch)
        core.timer_off("SAPT(DFT):SAPT:exch")

        # Induction
        core.timer_on("SAPT(DFT):SAPT:ind")
        ind = sapt_jk_terms.induction(
            hf_cache,
            sapt_jk,
            True,
            maxiter=core.get_option("SAPT", "MAXITER"),
            conv=core.get_option("SAPT", "D_CONVERGENCE"),
            Sinf=core.get_option("SAPT", "DO_IND_EXCH_SINF"))
        hf_data.update(ind)
        core.timer_off("SAPT(DFT):SAPT:ind")

        dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data[
            "HF MONOMER B"]

        core.print_out("\n")
        core.print_out(
            print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))

        data["Delta HF Correction"] = core.variable("SAPT(DFT) Delta HF")
        sapt_jk.finalize()

        del hf_wfn_A, hf_wfn_B, sapt_jk

    if hf_wfn_dimer is None:
        dimer_wfn = core.Wavefunction.build(sapt_dimer,
                                            core.get_global_option("BASIS"))
    else:
        dimer_wfn = hf_wfn_dimer

    # Set the primary functional
    core.set_local_option('SCF', 'REFERENCE', 'RKS')

    # Compute Monomer A wavefunction
    core.timer_on("SAPT(DFT): Monomer A DFT")
    if (core.get_global_option('SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'dimer', 'monomerA')

    if mon_a_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)

    core.IO.set_default_namespace('monomerA')
    wfn_A = scf_helper(sapt_dft_functional,
                       post_scf=False,
                       molecule=monomerA,
                       banner="SAPT(DFT): DFT Monomer A",
                       **kwargs)
    data["DFT MONOMERA"] = core.variable("CURRENT ENERGY")

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)
    core.timer_off("SAPT(DFT): Monomer A DFT")

    # Compute Monomer B wavefunction
    core.timer_on("SAPT(DFT): Monomer B DFT")
    if (core.get_global_option('SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'monomerA', 'monomerB')

    if mon_b_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)

    core.set_global_option("SAVE_JK", True)
    core.IO.set_default_namespace('monomerB')
    wfn_B = scf_helper(sapt_dft_functional,
                       post_scf=False,
                       molecule=monomerB,
                       banner="SAPT(DFT): DFT Monomer B",
                       **kwargs)
    data["DFT MONOMERB"] = core.variable("CURRENT ENERGY")

    # Save JK object
    sapt_jk = wfn_B.jk()
    wfn_A.set_jk(sapt_jk)
    core.set_global_option("SAVE_JK", False)

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)
    core.timer_off("SAPT(DFT): Monomer B DFT")

    # Write out header
    scf_alg = core.get_global_option("SCF_TYPE")
    sapt_dft_header(sapt_dft_functional, mon_a_shift, mon_b_shift,
                    bool(do_delta_hf), scf_alg)

    # Call SAPT(DFT)
    sapt_jk = wfn_B.jk()
    sapt_dft(dimer_wfn,
             wfn_A,
             wfn_B,
             sapt_jk=sapt_jk,
             data=data,
             print_header=False)

    # Copy data back into globals
    for k, v in data.items():
        core.set_variable(k, v)

    core.tstop()

    return dimer_wfn
Ejemplo n.º 21
0
def run_sapt_dft(name, **kwargs):
    optstash = p4util.OptionsState(['SCF', 'SCF_TYPE'], ['SCF', 'REFERENCE'],
                                   ['SCF', 'DFT_FUNCTIONAL'],
                                   ['SCF', 'DFT_GRAC_SHIFT'],
                                   ['SCF', 'SAVE_JK'])

    core.tstart()
    # Alter default algorithm
    if not core.has_option_changed('SCF', 'SCF_TYPE'):
        core.set_local_option('SCF', 'SCF_TYPE', 'DF')

    core.prepare_options_for_module("SAPT")

    # Get the molecule of interest
    ref_wfn = kwargs.get('ref_wfn', None)
    if ref_wfn is None:
        sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
    else:
        core.print_out(
            'Warning! SAPT argument "ref_wfn" is only able to use molecule information.'
        )
        sapt_dimer = ref_wfn.molecule()

    # Shifting to C1 so we need to copy the active molecule
    if sapt_dimer.schoenflies_symbol() != 'c1':
        core.print_out(
            '  SAPT does not make use of molecular symmetry, further calculations in C1 point group.\n'
        )

    # Make sure the geometry doesnt shift or rotate
    sapt_dimer = sapt_dimer.clone()
    sapt_dimer.reset_point_group('c1')
    sapt_dimer.fix_orientation(True)
    sapt_dimer.fix_com(True)
    sapt_dimer.update_geometry()

    # Grab overall settings
    mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
    mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
    do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
    sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")

    # Print out the title and some information
    core.print_out("\n")
    core.print_out(
        "         ---------------------------------------------------------\n")
    core.print_out("         " + "SAPT(DFT) Procedure".center(58) + "\n")
    core.print_out("\n")
    core.print_out("         " + "by Daniel G. A. Smith".center(58) + "\n")
    core.print_out(
        "         ---------------------------------------------------------\n")
    core.print_out("\n")

    core.print_out("  ==> Algorithm <==\n\n")
    core.print_out("   SAPT DFT Functional     %12s\n" %
                   str(sapt_dft_functional))
    core.print_out("   Monomer A GRAC Shift    %12.6f\n" % mon_a_shift)
    core.print_out("   Monomer B GRAC Shift    %12.6f\n" % mon_b_shift)
    core.print_out("   Delta HF                %12s\n" %
                   ("True" if do_delta_hf else "False"))
    core.print_out("   JK Algorithm            %12s\n" %
                   core.get_option("SCF", "SCF_TYPE"))
    core.print_out("\n")
    core.print_out("   Required computations:\n")
    if (do_delta_hf):
        core.print_out("     HF  (Dimer)\n")
        core.print_out("     HF  (Monomer A)\n")
        core.print_out("     HF  (Monomer B)\n")
    core.print_out("     DFT (Monomer A)\n")
    core.print_out("     DFT (Monomer B)\n")
    core.print_out("\n")

    if (mon_a_shift == 0.0) or (mon_b_shift == 0.0):
        raise ValidationError(
            'SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')

    if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
        raise ValidationError(
            'SAPT(DFT) currently only supports restricted references.')

    nfrag = sapt_dimer.nfragments()
    if nfrag != 2:
        raise ValidationError(
            'SAPT requires active molecule to have 2 fragments, not %s.' %
            (nfrag))

    monomerA = sapt_dimer.extract_subsets(1, 2)
    monomerA.set_name('monomerA')
    monomerB = sapt_dimer.extract_subsets(2, 1)
    monomerB.set_name('monomerB')

    core.IO.set_default_namespace('dimer')
    data = {}

    core.set_global_option("SAVE_JK", True)
    if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
        # core.set_global_option('DF_INTS_IO', 'LOAD')
        core.set_global_option('DF_INTS_IO', 'SAVE')

    # # Compute dimer wavefunction
    hf_cache = {}
    hf_wfn_dimer = None
    if do_delta_hf:
        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.set_global_option('DF_INTS_IO', 'SAVE')

        hf_data = {}
        hf_wfn_dimer = scf_helper("SCF",
                                  molecule=sapt_dimer,
                                  banner="SAPT(DFT): delta HF Dimer",
                                  **kwargs)
        hf_data["HF DIMER"] = core.get_variable("CURRENT ENERGY")

        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'dimer', 'monomerA')
        hf_wfn_A = scf_helper("SCF",
                              molecule=monomerA,
                              banner="SAPT(DFT): delta HF Monomer A",
                              **kwargs)
        hf_data["HF MONOMER A"] = core.get_variable("CURRENT ENERGY")

        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
        hf_wfn_B = scf_helper("SCF",
                              molecule=monomerB,
                              banner="SAPT(DFT): delta HF Monomer B",
                              **kwargs)
        hf_data["HF MONOMER B"] = core.get_variable("CURRENT ENERGY")

        # Move it back to monomer A
        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerB', 'dimer')

        core.print_out("\n")
        core.print_out(
            "         ---------------------------------------------------------\n"
        )
        core.print_out("         " +
                       "SAPT(DFT): delta HF Segement".center(58) + "\n")
        core.print_out("\n")
        core.print_out("         " +
                       "by Daniel G. A. Smith and Rob Parrish".center(58) +
                       "\n")
        core.print_out(
            "         ---------------------------------------------------------\n"
        )
        core.print_out("\n")

        # Build cache and JK
        sapt_jk = hf_wfn_B.jk()

        hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B,
                                                     sapt_jk, True)

        # Electostatics
        elst = sapt_jk_terms.electrostatics(hf_cache, True)
        hf_data.update(elst)

        # Exchange
        exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
        hf_data.update(exch)

        # Induction
        ind = sapt_jk_terms.induction(
            hf_cache,
            sapt_jk,
            True,
            maxiter=core.get_option("SAPT", "MAXITER"),
            conv=core.get_option("SAPT", "D_CONVERGENCE"))
        hf_data.update(ind)

        dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data[
            "HF MONOMER B"]

        core.print_out("\n")
        core.print_out(
            print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))

        data["Delta HF Correction"] = core.get_variable("SAPT(DFT) Delta HF")

    if hf_wfn_dimer is None:
        dimer_wfn = core.Wavefunction.build(sapt_dimer,
                                            core.get_global_option("BASIS"))
    else:
        dimer_wfn = hf_wfn_dimer

    # Set the primary functional
    core.set_global_option("DFT_FUNCTIONAL",
                           core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL"))
    core.set_local_option('SCF', 'REFERENCE', 'RKS')

    # Compute Monomer A wavefunction
    if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'dimer', 'monomerA')

    if mon_a_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)

    # Save the JK object
    core.IO.set_default_namespace('monomerA')
    wfn_A = scf_helper("SCF",
                       molecule=monomerA,
                       banner="SAPT(DFT): DFT Monomer A",
                       **kwargs)
    data["DFT MONOMERA"] = core.get_variable("CURRENT ENERGY")

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)

    # Compute Monomer B wavefunction
    if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'monomerA', 'monomerB')

    if mon_b_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)

    core.IO.set_default_namespace('monomerB')
    wfn_B = scf_helper("SCF",
                       molecule=monomerB,
                       banner="SAPT(DFT): DFT Monomer B",
                       **kwargs)
    data["DFT MONOMERB"] = core.get_variable("CURRENT ENERGY")

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)

    # Print out the title and some information
    core.print_out("\n")
    core.print_out(
        "         ---------------------------------------------------------\n")
    core.print_out("         " +
                   "SAPT(DFT): Intermolecular Interaction Segment".center(58) +
                   "\n")
    core.print_out("\n")
    core.print_out("         " +
                   "by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
    core.print_out(
        "         ---------------------------------------------------------\n")
    core.print_out("\n")

    core.print_out("  ==> Algorithm <==\n\n")
    core.print_out("   SAPT DFT Functional     %12s\n" %
                   str(sapt_dft_functional))
    core.print_out("   Monomer A GRAC Shift    %12.6f\n" % mon_a_shift)
    core.print_out("   Monomer B GRAC Shift    %12.6f\n" % mon_b_shift)
    core.print_out("   Delta HF                %12s\n" %
                   ("True" if do_delta_hf else "False"))
    core.print_out("   JK Algorithm            %12s\n" %
                   core.get_option("SCF", "SCF_TYPE"))

    # Build cache and JK
    sapt_jk = wfn_B.jk()

    cache = sapt_jk_terms.build_sapt_jk_cache(wfn_A, wfn_B, sapt_jk, True)

    # Electostatics
    elst = sapt_jk_terms.electrostatics(cache, True)
    data.update(elst)

    # Exchange
    exch = sapt_jk_terms.exchange(cache, sapt_jk, True)
    data.update(exch)

    # Induction
    ind = sapt_jk_terms.induction(cache,
                                  sapt_jk,
                                  True,
                                  maxiter=core.get_option("SAPT", "MAXITER"),
                                  conv=core.get_option("SAPT",
                                                       "D_CONVERGENCE"))
    data.update(ind)

    # Dispersion
    primary_basis = wfn_A.basisset()
    core.print_out("\n")
    aux_basis = core.BasisSet.build(sapt_dimer, "DF_BASIS_MP2",
                                    core.get_option("DFMP2", "DF_BASIS_MP2"),
                                    "RIFIT", core.get_global_option('BASIS'))
    fdds_disp = sapt_mp2_terms.df_fdds_dispersion(primary_basis, aux_basis,
                                                  cache)
    data.update(fdds_disp)

    if core.get_option("SAPT", "SAPT_DFT_MP2_DISP_ALG") == "FISAPT":
        mp2_disp = sapt_mp2_terms.df_mp2_fisapt_dispersion(wfn_A,
                                                           primary_basis,
                                                           aux_basis,
                                                           cache,
                                                           do_print=True)
    else:
        mp2_disp = sapt_mp2_terms.df_mp2_sapt_dispersion(dimer_wfn,
                                                         wfn_A,
                                                         wfn_B,
                                                         primary_basis,
                                                         aux_basis,
                                                         cache,
                                                         do_print=True)
    data.update(mp2_disp)

    # Print out final data
    core.print_out("\n")
    core.print_out(print_sapt_dft_summary(data, "SAPT(DFT)"))

    core.tstop()

    return dimer_wfn
Ejemplo n.º 22
0
def run_sapt_dft(name, **kwargs):
    optstash = p4util.OptionsState(['SCF_TYPE'], ['SCF', 'REFERENCE'], ['SCF', 'DFT_GRAC_SHIFT'],
                                   ['SCF', 'SAVE_JK'])

    core.tstart()
    # Alter default algorithm
    if not core.has_global_option_changed('SCF_TYPE'):
        core.set_global_option('SCF_TYPE', 'DF')

    core.prepare_options_for_module("SAPT")

    # Get the molecule of interest
    ref_wfn = kwargs.get('ref_wfn', None)
    if ref_wfn is None:
        sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
    else:
        core.print_out('Warning! SAPT argument "ref_wfn" is only able to use molecule information.')
        sapt_dimer = ref_wfn.molecule()

    sapt_dimer, monomerA, monomerB = proc_util.prepare_sapt_molecule(sapt_dimer, "dimer")

    # Grab overall settings
    mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
    mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
    do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
    sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")

    # Print out the title and some information
    core.print_out("\n")
    core.print_out("         ---------------------------------------------------------\n")
    core.print_out("         " + "SAPT(DFT) Procedure".center(58) + "\n")
    core.print_out("\n")
    core.print_out("         " + "by Daniel G. A. Smith".center(58) + "\n")
    core.print_out("         ---------------------------------------------------------\n")
    core.print_out("\n")

    core.print_out("  !!!  WARNING:  SAPT(DFT) capability is in beta. Please use with caution. !!!\n\n")

    core.print_out("  ==> Algorithm <==\n\n")
    core.print_out("   SAPT DFT Functional     %12s\n" % str(sapt_dft_functional))
    core.print_out("   Monomer A GRAC Shift    %12.6f\n" % mon_a_shift)
    core.print_out("   Monomer B GRAC Shift    %12.6f\n" % mon_b_shift)
    core.print_out("   Delta HF                %12s\n" % ("True" if do_delta_hf else "False"))
    core.print_out("   JK Algorithm            %12s\n" % core.get_global_option("SCF_TYPE"))
    core.print_out("\n")
    core.print_out("   Required computations:\n")
    if (do_delta_hf):
        core.print_out("     HF  (Dimer)\n")
        core.print_out("     HF  (Monomer A)\n")
        core.print_out("     HF  (Monomer B)\n")
    core.print_out("     DFT (Monomer A)\n")
    core.print_out("     DFT (Monomer B)\n")
    core.print_out("\n")

    if (sapt_dft_functional != "HF") and ((mon_a_shift == 0.0) or (mon_b_shift == 0.0)):
        raise ValidationError('SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')

    if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
        raise ValidationError('SAPT(DFT) currently only supports restricted references.')

    core.IO.set_default_namespace('dimer')
    data = {}

    if (core.get_global_option('SCF_TYPE') == 'DF'):
        # core.set_global_option('DF_INTS_IO', 'LOAD')
        core.set_global_option('DF_INTS_IO', 'SAVE')

    # # Compute dimer wavefunction
    hf_wfn_dimer = None
    if do_delta_hf:
        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.set_global_option('DF_INTS_IO', 'SAVE')

        hf_data = {}
        hf_wfn_dimer = scf_helper("SCF", molecule=sapt_dimer, banner="SAPT(DFT): delta HF Dimer", **kwargs)
        hf_data["HF DIMER"] = core.get_variable("CURRENT ENERGY")

        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'dimer', 'monomerA')

        hf_wfn_A = scf_helper("SCF", molecule=monomerA, banner="SAPT(DFT): delta HF Monomer A", **kwargs)
        hf_data["HF MONOMER A"] = core.get_variable("CURRENT ENERGY")

        core.set_global_option("SAVE_JK", True)
        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerA', 'monomerB')

        hf_wfn_B = scf_helper("SCF", molecule=monomerB, banner="SAPT(DFT): delta HF Monomer B", **kwargs)
        hf_data["HF MONOMER B"] = core.get_variable("CURRENT ENERGY")
        core.set_global_option("SAVE_JK", False)

        # Grab JK object and set to A (so we do not save many JK objects)
        sapt_jk = hf_wfn_B.jk()
        hf_wfn_A.set_jk(sapt_jk)
        core.set_global_option("SAVE_JK", False)

        # Move it back to monomer A
        if (core.get_global_option('SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerB', 'dimer')

        core.print_out("\n")
        core.print_out("         ---------------------------------------------------------\n")
        core.print_out("         " + "SAPT(DFT): delta HF Segement".center(58) + "\n")
        core.print_out("\n")
        core.print_out("         " + "by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
        core.print_out("         ---------------------------------------------------------\n")
        core.print_out("\n")

        # Build cache
        hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B, sapt_jk, True)

        # Electostatics
        elst = sapt_jk_terms.electrostatics(hf_cache, True)
        hf_data.update(elst)

        # Exchange
        exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
        hf_data.update(exch)

        # Induction
        ind = sapt_jk_terms.induction(
            hf_cache,
            sapt_jk,
            True,
            maxiter=core.get_option("SAPT", "MAXITER"),
            conv=core.get_option("SAPT", "D_CONVERGENCE"),
            Sinf=core.get_option("SAPT", "DO_IND_EXCH_SINF"))
        hf_data.update(ind)

        dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data["HF MONOMER B"]

        core.print_out("\n")
        core.print_out(print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))

        data["Delta HF Correction"] = core.get_variable("SAPT(DFT) Delta HF")
        sapt_jk.finalize()

        del hf_wfn_A, hf_wfn_B, sapt_jk

    if hf_wfn_dimer is None:
        dimer_wfn = core.Wavefunction.build(sapt_dimer, core.get_global_option("BASIS"))
    else:
        dimer_wfn = hf_wfn_dimer

    # Set the primary functional
    core.set_local_option('SCF', 'REFERENCE', 'RKS')

    # Compute Monomer A wavefunction
    if (core.get_global_option('SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'dimer', 'monomerA')

    if mon_a_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)

    # Save the JK object
    core.IO.set_default_namespace('monomerA')
    wfn_A = scf_helper(
        sapt_dft_functional, post_scf=False, molecule=monomerA, banner="SAPT(DFT): DFT Monomer A", **kwargs)
    data["DFT MONOMERA"] = core.get_variable("CURRENT ENERGY")

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)

    # Compute Monomer B wavefunction
    if (core.get_global_option('SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'monomerA', 'monomerB')

    if mon_b_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)

    core.set_global_option("SAVE_JK", True)
    core.IO.set_default_namespace('monomerB')
    wfn_B = scf_helper(
        sapt_dft_functional, post_scf=False, molecule=monomerB, banner="SAPT(DFT): DFT Monomer B", **kwargs)
    data["DFT MONOMERB"] = core.get_variable("CURRENT ENERGY")

    # Save JK object
    sapt_jk = wfn_B.jk()
    wfn_A.set_jk(sapt_jk)
    core.set_global_option("SAVE_JK", False)

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)

    # Write out header
    scf_alg = core.get_global_option("SCF_TYPE")
    sapt_dft_header(sapt_dft_functional, mon_a_shift, mon_b_shift, bool(do_delta_hf), scf_alg)

    # Call SAPT(DFT)
    sapt_jk = wfn_B.jk()
    sapt_dft(dimer_wfn, wfn_A, wfn_B, sapt_jk=sapt_jk, data=data, print_header=False)

    # Copy data back into globals
    for k, v in data.items():
        core.set_variable(k, v)

    core.tstop()

    return dimer_wfn
Ejemplo n.º 23
0
Archivo: frac.py Proyecto: yxie326/psi4
def ip_fitting(name,
               omega_l=0.05,
               omega_r=2.5,
               omega_convergence=1.0e-3,
               maxiter=20,
               **kwargs):
    """Optimize DFT omega parameter for molecular system.

    Parameters
    ----------
    name : string or function
        DFT functional string name or function defining functional
        whose omega is to be optimized.
    omega_l : float, optional
        Minimum omega to be considered during fitting.
    omega_r : float, optional
        Maximum omega to be considered during fitting.
    molecule : :ref:`molecule <op_py_molecule>`, optional
        Target molecule (neutral) for which omega is to be tuned, if not last defined.
    omega_convergence : float, optional
        Threshold below which to consider omega converged. (formerly omega_tolerance)
    maxiter : int, optional
        Maximum number of iterations towards omega convergence.

    Returns
    -------
    float
        Optimal omega parameter.

    """
    optstash = p4util.OptionsState(['SCF', 'REFERENCE'], ['SCF', 'GUESS'],
                                   ['SCF', 'DF_INTS_IO'], ['SCF', 'DFT_OMEGA'],
                                   ['DOCC'], ['SOCC'])

    kwargs = p4util.kwargs_lower(kwargs)

    # By default, do not read previous 180 orbitals file
    read = False
    read180 = ''
    if 'read' in kwargs:
        read = True
        read180 = kwargs['read']

    if core.get_option('SCF', 'REFERENCE') != 'UKS':
        core.print_out(
            """  Requested procedure `ip_fitting` runs further calculations with UKS reference.\n"""
        )
        core.set_local_option('SCF', 'REFERENCE', 'UKS')

    # Make sure the molecule the user provided is the active one, and neutral
    molecule = kwargs.pop('molecule', core.get_active_molecule())
    molecule.update_geometry()

    if molecule.molecular_charge() != 0:
        raise ValidationError(
            """IP Fitting requires neutral molecule to start.""")
    if molecule.schoenflies_symbol() != 'c1':
        core.print_out(
            """  Requested procedure `ip_fitting` does not make use of molecular symmetry: """
            """further calculations in C1 point group.\n""")
    molecule = molecule.clone()
    molecule.reset_point_group('c1')
    molecule.update_geometry()

    charge0 = molecule.molecular_charge()
    mult0 = molecule.multiplicity()

    # How many electrons are there?
    N = 0
    for A in range(molecule.natom()):
        N += molecule.Z(A)
    N -= charge0
    N = int(N)
    Nb = int((N - mult0 + 1) / 2)
    Na = int(N - Nb)

    # Work in the ot namespace for this procedure
    core.IO.set_default_namespace("ot")

    # Burn in to determine orbital eigenvalues
    if read:
        core.set_local_option("SCF", "GUESS", "READ")
        copy_file_to_scratch(read180, 'psi', 'ot', 180)
    core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
    E, wfn = driver.energy('scf',
                           dft_functional=name,
                           return_wfn=True,
                           molecule=molecule,
                           banner='IP Fitting SCF: Burn-in',
                           **kwargs)
    core.set_local_option("SCF", "DF_INTS_IO", "LOAD")

    if not wfn.functional().is_x_lrc():
        raise ValidationError(
            """Not sensible to optimize omega for non-long-range-correction functional."""
        )

    # Determine H**O, to determine mult1
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    if Na == Nb:
        H**O = -Nb
    elif Nb == 0:
        H**O = Na
    else:
        E_a = eps_a.np[int(Na - 1)]
        E_b = eps_b.np[int(Nb - 1)]
        if E_a >= E_b:
            H**O = Na
        else:
            H**O = -Nb

    Na1 = Na
    Nb1 = Nb
    if H**O > 0:
        Na1 -= 1
    else:
        Nb1 -= 1

    charge1 = charge0 + 1
    mult1 = Na1 - Nb1 + 1

    omegas = []
    E0s = []
    E1s = []
    kIPs = []
    IPs = []
    types = []

    # Right endpoint
    core.set_local_option('SCF', 'DFT_OMEGA', omega_r)

    # Neutral
    if read:
        core.set_local_option("SCF", "GUESS", "READ")
        p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)

    molecule.set_molecular_charge(charge0)
    molecule.set_multiplicity(mult0)
    E0r, wfn = driver.energy('scf',
                             dft_functional=name,
                             return_wfn=True,
                             molecule=molecule,
                             banner='IP Fitting SCF: Neutral, Right Endpoint',
                             **kwargs)
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    if Nb == 0:
        E_HOMO = eps_a.np[int(Na - 1)]
    else:
        E_a = eps_a.np[int(Na - 1)]
        E_b = eps_b.np[int(Nb - 1)]
        E_HOMO = max(E_a, E_b)
    E_HOMOr = E_HOMO
    core.IO.change_file_namespace(180, "ot", "neutral")

    # Cation
    if read:
        core.set_local_option("SCF", "GUESS", "READ")
        p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)

    molecule.set_molecular_charge(charge1)
    molecule.set_multiplicity(mult1)
    E1r = driver.energy('scf',
                        dft_functional=name,
                        molecule=molecule,
                        banner='IP Fitting SCF: Cation, Right Endpoint',
                        **kwargs)
    core.IO.change_file_namespace(180, "ot", "cation")

    IPr = E1r - E0r
    kIPr = -E_HOMOr
    delta_r = IPr - kIPr

    if IPr > kIPr:
        raise ValidationError(
            """\n***IP Fitting Error: Right Omega limit should have kIP > IP: {} !> {}"""
            .format(kIPr, IPr))

    omegas.append(omega_r)
    types.append('Right Limit')
    E0s.append(E0r)
    E1s.append(E1r)
    IPs.append(IPr)
    kIPs.append(kIPr)

    # Use previous orbitals from here out
    core.set_local_option("SCF", "GUESS", "READ")

    # Left endpoint
    core.set_local_option('SCF', 'DFT_OMEGA', omega_l)

    # Neutral
    core.IO.change_file_namespace(180, "neutral", "ot")
    molecule.set_molecular_charge(charge0)
    molecule.set_multiplicity(mult0)
    core.set_global_option("DOCC", [Nb])
    core.set_global_option("SOCC", [Na - Nb])
    E0l, wfn = driver.energy('scf',
                             dft_functional=name,
                             return_wfn=True,
                             molecule=molecule,
                             banner='IP Fitting SCF: Neutral, Left Endpoint',
                             **kwargs)
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    if Nb == 0:
        E_HOMO = eps_a.np[int(Na - 1)]
    else:
        E_a = eps_a.np[int(Na - 1)]
        E_b = eps_b.np[int(Nb - 1)]
        E_HOMO = max(E_a, E_b)
    E_HOMOl = E_HOMO
    core.IO.change_file_namespace(180, "ot", "neutral")

    # Cation
    core.IO.change_file_namespace(180, "cation", "ot")
    molecule.set_molecular_charge(charge1)
    molecule.set_multiplicity(mult1)
    core.set_global_option("DOCC", [Nb1])
    core.set_global_option("SOCC", [Na1 - Nb1])
    E1l = driver.energy('scf',
                        dft_functional=name,
                        molecule=molecule,
                        banner='IP Fitting SCF: Cation, Left Endpoint',
                        **kwargs)
    core.IO.change_file_namespace(180, "ot", "cation")

    IPl = E1l - E0l
    kIPl = -E_HOMOl
    delta_l = IPl - kIPl

    if IPl < kIPl:
        raise ValidationError(
            """\n***IP Fitting Error: Left Omega limit should have kIP < IP: {} !< {}"""
            .format(kIPl, IPl))

    omegas.append(omega_l)
    types.append('Left Limit')
    E0s.append(E0l)
    E1s.append(E1l)
    IPs.append(IPl)
    kIPs.append(kIPl)

    converged = False
    repeat_l = 0
    repeat_r = 0
    for step in range(maxiter):

        # Regula Falsi (modified)
        if repeat_l > 1:
            delta_l /= 2.0
        if repeat_r > 1:
            delta_r /= 2.0
        omega = -(omega_r - omega_l) / (delta_r - delta_l) * delta_l + omega_l
        core.set_local_option('SCF', 'DFT_OMEGA', omega)

        # Neutral
        core.IO.change_file_namespace(180, "neutral", "ot")
        molecule.set_molecular_charge(charge0)
        molecule.set_multiplicity(mult0)
        core.set_global_option("DOCC", [Nb])
        core.set_global_option("SOCC", [Na - Nb])
        E0, wfn = driver.energy(
            'scf',
            dft_functional=name,
            return_wfn=True,
            molecule=molecule,
            banner='IP Fitting SCF: Neutral, Omega = {:11.3E}'.format(omega),
            **kwargs)
        eps_a = wfn.epsilon_a()
        eps_b = wfn.epsilon_b()
        if Nb == 0:
            E_HOMO = eps_a.np[int(Na - 1)]
        else:
            E_a = eps_a.np[int(Na - 1)]
            E_b = eps_b.np[int(Nb - 1)]
            E_HOMO = max(E_a, E_b)
        core.IO.change_file_namespace(180, "ot", "neutral")

        # Cation
        core.IO.change_file_namespace(180, "cation", "ot")
        molecule.set_molecular_charge(charge1)
        molecule.set_multiplicity(mult1)
        core.set_global_option("DOCC", [Nb1])
        core.set_global_option("SOCC", [Na1 - Nb1])
        E1 = driver.energy(
            'scf',
            dft_functional=name,
            molecule=molecule,
            banner='IP Fitting SCF: Cation, Omega = {:11.3E}'.format(omega),
            **kwargs)
        core.IO.change_file_namespace(180, "ot", "cation")

        IP = E1 - E0
        kIP = -E_HOMO
        delta = IP - kIP

        if kIP > IP:
            omega_r = omega
            E0r = E0
            E1r = E1
            IPr = IP
            kIPr = kIP
            delta_r = delta
            repeat_r = 0
            repeat_l += 1
        else:
            omega_l = omega
            E0l = E0
            E1l = E1
            IPl = IP
            kIPl = kIP
            delta_l = delta
            repeat_l = 0
            repeat_r += 1

        omegas.append(omega)
        types.append('Regula-Falsi')
        E0s.append(E0)
        E1s.append(E1)
        IPs.append(IP)
        kIPs.append(kIP)

        # Termination
        if abs(omega_l - omega_r) < omega_convergence:
            converged = True
            break

    core.IO.set_default_namespace("")
    core.print_out("""\n    ==> IP Fitting Results <==\n\n""")

    core.print_out("""     => Occupation Determination <= \n\n""")
    core.print_out("""              %6s %6s %6s %6s %6s %6s\n""" %
                   ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
    core.print_out("""     Neutral: %6d %6d %6d %6d %6d %6d\n""" %
                   (N, Na, Nb, charge0, mult0, H**O))
    core.print_out("""     Cation:  %6d %6d %6d %6d %6d\n\n""" %
                   (N - 1, Na1, Nb1, charge1, mult1))

    core.print_out("""     => Regula Falsi Iterations <=\n\n""")
    core.print_out("""    %3s %11s %14s %14s %14s %s\n""" %
                   ('N', 'Omega', 'IP', 'kIP', 'Delta', 'Type'))
    for k in range(len(omegas)):
        core.print_out(
            """    %3d %11.3E %14.6E %14.6E %14.6E %s\n""" %
            (k + 1, omegas[k], IPs[k], kIPs[k], IPs[k] - kIPs[k], types[k]))

    optstash.restore()
    if converged:
        core.print_out("""\n    IP Fitting Converged\n""")
        core.print_out("""    Final omega = %14.6E\n""" %
                       ((omega_l + omega_r) / 2))
        core.print_out(
            """\n    "M,I. does the dying. Fleet just does the flying."\n""")
        core.print_out("""            -Starship Troopers\n""")

    else:
        raise ConvergenceError("""IP Fitting """, step + 1)

    return ((omega_l + omega_r) / 2)
Ejemplo n.º 24
0
Archivo: frac.py Proyecto: yxie326/psi4
def frac_traverse(name, **kwargs):
    """Scan electron occupancy from +1 electron to -1.

    Parameters
    ----------
    name : string or function
        DFT functional string name or function defining functional
        whose omega is to be optimized.
    molecule : :ref:`molecule <op_py_molecule>`, optional
        Target molecule (neutral) for which omega is to be tuned, if not last defined.
    cation_mult : int, optional
        Multiplicity of cation, if not neutral multiplicity + 1.
    anion_mult : int, optional
        Multiplicity of anion, if not neutral multiplicity + 1.
    frac_start : int, optional
        Iteration at which to start frac procedure when not reading previous
        guess. Defaults to 25.
    HOMO_occs : list, optional
        Occupations to step through for cation, by default `[1 - 0.1 * x for x in range(11)]`.
    LUMO_occs : list, optional
        Occupations to step through for anion, by default `[1 - 0.1 * x for x in range(11)]`.
    H**O : int, optional
        Index of H**O.
    LUMO : int, optional
        Index of LUMO.
    frac_diis : bool, optional
        Do use DIIS for non-1.0-occupied points?
    neutral_guess : bool, optional
        Do use neutral orbitals as guess for the anion?
    hf_guess: bool, optional
        Do use UHF guess before UKS?
    continuous_guess : bool, optional
        Do carry along guess rather than reguessing at each occupation?
    filename : str, optional
        Result filename, if not name of molecule.

    Returns
    -------
    dict
        Dictionary associating SCF energies with occupations.

    """
    optstash = p4util.OptionsState(
        ['SCF', 'GUESS'],
        ['SCF', 'DF_INTS_IO'],
        ['SCF', 'REFERENCE'],
        ["SCF", "FRAC_START"],
        ["SCF", "FRAC_RENORMALIZE"],
        #["SCF", "FRAC_LOAD"],
        ["SCF", "FRAC_OCC"],
        ["SCF", "FRAC_VAL"],
        ["SCF", "FRAC_DIIS"])
    kwargs = p4util.kwargs_lower(kwargs)

    # Make sure the molecule the user provided is the active one, and neutral
    molecule = kwargs.pop('molecule', core.get_active_molecule())
    molecule.update_geometry()

    if molecule.molecular_charge() != 0:
        raise ValidationError(
            """frac_traverse requires neutral molecule to start.""")
    if molecule.schoenflies_symbol() != 'c1':
        core.print_out(
            """  Requested procedure `frac_traverse` does not make use of molecular symmetry: """
            """further calculations in C1 point group.\n""")
    molecule = molecule.clone()
    molecule.reset_point_group('c1')
    molecule.update_geometry()

    charge0 = molecule.molecular_charge()
    mult0 = molecule.multiplicity()

    chargep = charge0 + 1
    chargem = charge0 - 1

    multp = kwargs.get('cation_mult', mult0 + 1)
    multm = kwargs.get('anion_mult', mult0 + 1)

    # By default, we start the frac procedure on the 25th iteration
    # when not reading a previous guess
    frac_start = kwargs.get('frac_start', 25)

    # By default, we occupy by tenths of electrons
    HOMO_occs = kwargs.get(
        'HOMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
    LUMO_occs = kwargs.get(
        'LUMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])

    # By default, H**O and LUMO are both in alpha
    Z = 0
    for A in range(molecule.natom()):
        Z += molecule.Z(A)
    Z -= charge0
    H**O = kwargs.get('H**O', (Z / 2 + 1 if (Z % 2) else Z / 2))
    LUMO = kwargs.get('LUMO', H**O + 1)

    # By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
    frac_diis = kwargs.get('frac_diis', True)

    # By default, use the neutral orbitals as a guess for the anion
    neutral_guess = kwargs.get('neutral_guess', True)

    # By default, burn-in with UHF first, if UKS
    hf_guess = False
    if core.get_local_option('SCF', 'REFERENCE') == 'UKS':
        hf_guess = kwargs.get('hf_guess', True)

    # By default, re-guess at each N
    continuous_guess = kwargs.get('continuous_guess', False)

    # By default, drop the files to the molecule's name
    root = kwargs.get('filename', molecule.name())
    traverse_filename = root + '.traverse.dat'
    # => Traverse <= #
    occs = []
    energies = []
    potentials = []
    convs = []

    # => Run the neutral for its orbitals, if requested <= #

    core.set_local_option("SCF", "DF_INTS_IO", "SAVE")

    old_guess = core.get_local_option("SCF", "GUESS")
    if (neutral_guess):
        if (hf_guess):
            core.set_local_option("SCF", "REFERENCE", "UHF")
        driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "DF_INTS_IO", "LOAD")

    # => Run the anion first <= #

    molecule.set_molecular_charge(chargem)
    molecule.set_multiplicity(multm)

    # => Burn the anion in with hf, if requested <= #
    if hf_guess:
        core.set_local_option("SCF", "REFERENCE", "UHF")
        driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
        core.set_local_option("SCF", "REFERENCE", "UKS")
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "DF_INTS_IO", "SAVE")

    core.set_local_option("SCF", "FRAC_START", frac_start)
    core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
    # NYI core.set_local_option("SCF", "FRAC_LOAD", False)

    for occ in LUMO_occs:

        core.set_local_option("SCF", "FRAC_OCC", [LUMO])
        core.set_local_option("SCF", "FRAC_VAL", [occ])

        E, wfn = driver.energy('scf',
                               dft_functional=name,
                               return_wfn=True,
                               molecule=molecule,
                               **kwargs)
        C = 1
        if E == 0.0:
            E = core.variable('SCF ITERATION ENERGY')
            C = 0

        if LUMO > 0:
            eps = wfn.epsilon_a()
            potentials.append(eps.get(int(LUMO) - 1))
        else:
            eps = wfn.epsilon_b()
            potentials.append(eps.get(-int(LUMO) - 1))

        occs.append(occ)
        energies.append(E)
        convs.append(C)

        core.set_local_option("SCF", "FRAC_START", 2)
        #core.set_local_option("SCF", "FRAC_LOAD", True)
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
        core.set_local_option("SCF", "DF_INTS_IO", "LOAD")

    # => Run the neutral next <= #

    molecule.set_molecular_charge(charge0)
    molecule.set_multiplicity(mult0)

    # Burn the neutral in with hf, if requested <= #

    if not continuous_guess:
        core.set_local_option("SCF", "GUESS", old_guess)
        if hf_guess:
            core.set_local_option("SCF", "FRAC_START", 0)
            core.set_local_option("SCF", "REFERENCE", "UHF")
            driver.energy('scf',
                          dft_functional=name,
                          molecule=molecule,
                          **kwargs)
            core.set_local_option("SCF", "REFERENCE", "UKS")
            core.set_local_option("SCF", "GUESS", "READ")
        # NYI core.set_local_option("SCF", "FRAC_LOAD", False)

    core.set_local_option("SCF", "FRAC_START", frac_start)
    core.set_local_option("SCF", "FRAC_RENORMALIZE", True)

    for occ in HOMO_occs:

        core.set_local_option("SCF", "FRAC_OCC", [H**O])
        core.set_local_option("SCF", "FRAC_VAL", [occ])

        E, wfn = driver.energy('scf',
                               dft_functional=name,
                               return_wfn=True,
                               molecule=molecule,
                               **kwargs)
        C = 1
        if E == 0.0:
            E = core.variable('SCF ITERATION ENERGY')
            C = 0

        if LUMO > 0:
            eps = wfn.epsilon_a()
            potentials.append(eps.get(int(H**O) - 1))
        else:
            eps = wfn.epsilon_b()
            potentials.append(eps.get(-int(H**O) - 1))

        occs.append(occ - 1.0)
        energies.append(E)
        convs.append(C)

        core.set_local_option("SCF", "FRAC_START", 2)
        # NYI core.set_local_option("SCF", "FRAC_LOAD", True)
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
        core.set_local_option("SCF", "DF_INTS_IO", "LOAD")

    # => Print the results out <= #
    E = {}
    core.print_out(
        """\n    ==> Fractional Occupation Traverse Results <==\n\n""")
    core.print_out("""    %-11s %-24s %-24s %11s\n""" %
                   ('N', 'Energy', 'H**O Energy', 'Converged'))
    for k in range(len(occs)):
        core.print_out("""    %11.3E %24.16E %24.16E %11d\n""" %
                       (occs[k], energies[k], potentials[k], convs[k]))
        E[occs[k]] = energies[k]

    core.print_out("""
    You trying to be a hero Watkins?
    Just trying to kill some bugs sir!
            -Starship Troopers""")

    # Drop the files out
    with open(traverse_filename, 'w') as fh:
        fh.write("""    %-11s %-24s %-24s %11s\n""" %
                 ('N', 'Energy', 'H**O Energy', 'Converged'))
        for k in range(len(occs)):
            fh.write("""    %11.3E %24.16E %24.16E %11d\n""" %
                     (occs[k], energies[k], potentials[k], convs[k]))

    optstash.restore()
    return E
Ejemplo n.º 25
0
Archivo: frac.py Proyecto: yxie326/psi4
def frac_nuke(name, **kwargs):
    """Pull all the electrons out, one at a time"""
    optstash = p4util.OptionsState(
        ['SCF', 'GUESS'],
        ['SCF', 'DF_INTS_IO'],
        ["SCF", "FRAC_START"],
        ["SCF", "FRAC_RENORMALIZE"],
        # NYI ["SCF", "FRAC_LOAD"],
        ["SCF", "FRAC_OCC"],
        ["SCF", "FRAC_VAL"],
        ["SCF", "FRAC_DIIS"])

    kwargs = p4util.kwargs_lower(kwargs)

    # Make sure the molecule the user provided is the active one, and neutral
    molecule = kwargs.pop('molecule', core.get_active_molecule())
    molecule.update_geometry()

    if molecule.molecular_charge() != 0:
        raise ValidationError(
            """frac_nuke requires neutral molecule to start.""")
    if molecule.schoenflies_symbol() != 'c1':
        core.print_out(
            """  Requested procedure `frac_nuke` does not make use of molecular symmetry: """
            """further calculations in C1 point group.\n""")
    molecule = molecule.clone()
    molecule.reset_point_group('c1')
    molecule.update_geometry()

    charge0 = molecule.molecular_charge()
    mult0 = molecule.multiplicity()

    # By default, we start the frac procedure on the 25th iteration
    # when not reading a previous guess
    frac_start = kwargs.get('frac_start', 25)

    # By default, we occupy by tenths of electrons
    foccs = kwargs.get('foccs',
                       [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])

    # By default, H**O and LUMO are both in alpha
    N = 0
    for A in range(molecule.natom()):
        N += molecule.Z(A)
    N -= charge0
    N = int(N)
    Nb = int((N - mult0 + 1) / 2)
    Na = int(N - Nb)

    charge = charge0
    mult = mult0

    # By default, nuke all the electrons
    Nmin = 0
    if 'nmax' in kwargs:
        Nmin = N - int(kwargs['nmax'])

    # By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
    frac_diis = kwargs.get('frac_diis', True)

    # By default, drop the files to the molecule's name
    root = kwargs.get('filename', molecule.name())
    traverse_filename = root + '.traverse.dat'
    stats_filename = root + '.stats.dat'

    # => Traverse <= #
    core.set_local_option("SCF", "DF_INTS_IO", "SAVE")

    Ns = []
    energies = []
    potentials = []
    convs = []
    stats = []

    # Run one SCF to burn things in
    E, wfn = driver.energy('scf',
                           dft_functional=name,
                           return_wfn=True,
                           molecule=molecule,
                           **kwargs)

    # Determine H**O
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    eps_a.print_out()
    if Na == Nb:
        H**O = -Nb
    elif Nb == 0:
        H**O = Na
    else:
        E_a = eps_a.get(int(Na - 1))
        E_b = eps_b.get(int(Nb - 1))
        if E_a >= E_b:
            H**O = Na
        else:
            H**O = -Nb

    stats.append("""    %6d %6d %6d %6d %6d %6d\n""" %
                 (N, Na, Nb, charge, mult, H**O))

    if H**O > 0:
        Na -= 1
    else:
        Nb -= 1
    charge += 1
    mult = Na - Nb + 1

    core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
    core.set_local_option("SCF", "FRAC_START", frac_start)
    core.set_local_option("SCF", "FRAC_RENORMALIZE", True)

    # Nuke 'em Rico!
    for Nintegral in range(N, Nmin, -1):

        # Nuke the current H**O
        for occ in foccs:

            core.set_local_option("SCF", "FRAC_OCC", [H**O])
            core.set_local_option("SCF", "FRAC_VAL", [occ])

            E, wfn = driver.energy('scf',
                                   dft_functional=name,
                                   return_wfn=True,
                                   molecule=molecule,
                                   **kwargs)
            C = 1
            if E == 0.0:
                E = core.variable('SCF ITERATION ENERGY')
                C = 0

            if H**O > 0:
                eps = wfn.epsilon_a()
                potentials.append(eps.np[H**O - 1])
            else:
                eps = wfn.epsilon_b()
                potentials.append(eps.np[-H**O - 1])

            Ns.append(Nintegral + occ - 1.0)
            energies.append(E)
            convs.append(C)

            core.set_local_option("SCF", "FRAC_START", 2)
            # NYI core.set_local_option("SCF", "FRAC_LOAD", True)
            core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
            core.set_local_option("SCF", "GUESS", "READ")

        # Set the next charge/mult
        molecule.set_molecular_charge(charge)
        molecule.set_multiplicity(mult)

        # Determine H**O
        print('DGAS: What ref should this point to?')
        #ref = core.legacy_wavefunction()
        eps_a = wfn.epsilon_a()
        eps_b = wfn.epsilon_b()
        if Na == Nb:
            H**O = -Nb
        elif Nb == 0:
            H**O = Na
        else:
            E_a = eps_a.np[int(Na - 1)]
            E_b = eps_b.np[int(Nb - 1)]
            if E_a >= E_b:
                H**O = Na
            else:
                H**O = -Nb

        stats.append("""    %6d %6d %6d %6d %6d %6d\n""" %
                     (Nintegral - 1, Na, Nb, charge, mult, H**O))

        if H**O > 0:
            Na -= 1
        else:
            Nb -= 1
        charge += 1
        mult = Na - Nb + 1

    core.set_local_option("SCF", "DF_INTS_IO", "NONE")

    # => Print the results out <= #
    E = {}
    core.print_out("""\n    ==> Fractional Occupation Nuke Results <==\n\n""")
    core.print_out("""    %-11s %-24s %-24s %11s\n""" %
                   ('N', 'Energy', 'H**O Energy', 'Converged'))
    for k in range(len(Ns)):
        core.print_out("""    %11.3E %24.16E %24.16E %11d\n""" %
                       (Ns[k], energies[k], potentials[k], convs[k]))
        E[Ns[k]] = energies[k]

    core.print_out('\n')
    core.print_out("""    %6s %6s %6s %6s %6s %6s\n""" %
                   ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
    for line in stats:
        core.print_out(line)

    core.print_out(
        '\n    "You shoot a nuke down a bug hole, you got a lot of dead bugs"\n'
    )
    core.print_out('            -Starship Troopers\n')

    # Drop the files out
    with open(traverse_filename, 'w') as fh:
        fh.write("""    %-11s %-24s %-24s %11s\n""" %
                 ('N', 'Energy', 'H**O Energy', 'Converged'))
        for k in range(len(Ns)):
            fh.write("""    %11.3E %24.16E %24.16E %11d\n""" %
                     (Ns[k], energies[k], potentials[k], convs[k]))

    with open(stats_filename, 'w') as fh:
        fh.write("""    %6s %6s %6s %6s %6s %6s\n""" %
                 ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
        for line in stats:
            fh.write(line)

    optstash.restore()
    return E
Ejemplo n.º 26
0
def write_zmat(name, dertype, molecule):
    """Returns string with contents of Cfour ZMAT file as gathered from
    active molecule, current keyword settings, and cfour {...} block.

    """
    # Handle memory
    mem = int(0.000001 * core.get_memory())
    if mem == 524:
        memcmd, memkw = '', {}
    else:
        memcmd, memkw = qcdb.cfour.muster_memory(mem)

    # Handle molecule and basis set
    if molecule.name() == 'blank_molecule_psi4_yo':
        molcmd, molkw = '', {}
        bascmd, baskw = '', {}
        core.set_local_option('CFOUR', 'TRANSLATE_PSI4', False)
    else:
        molecule.update_geometry()
        #print(molecule.create_psi4_string_from_molecule())
        qcdbmolecule = qcdb.Molecule(
            molecule.create_psi4_string_from_molecule())
        qcdbmolecule.tagline = molecule.name()
        molcmd, molkw = qcdbmolecule.format_molecule_for_cfour()

        if core.get_global_option('BASIS') in ["", "(AUTO)"]:
            bascmd, baskw = '', {}
        else:
            user_pg = molecule.schoenflies_symbol()
            molecule.reset_point_group(
                'c1')  # need basis printed for *every* atom
            qbs = core.BasisSet.build(molecule, "BASIS",
                                      core.get_global_option('BASIS'))
            if qbs.has_ECP():
                raise ValidationError("""ECPs not hooked up for Cfour""")
            with open('GENBAS', 'w') as cfour_basfile:
                cfour_basfile.write(qbs.genbas())
            core.print_out(
                '  GENBAS loaded from Psi4 LibMints for basis %s\n' %
                (core.get_global_option('BASIS')))
            molecule.reset_point_group(user_pg)
            molecule.update_geometry()
            bascmd, baskw = qcdbmolecule.format_basis_for_cfour(
                qbs.has_puream())

    # Handle psi4 keywords implying cfour keyword values
    if core.get_option('CFOUR', 'TRANSLATE_PSI4'):
        psicmd, psikw = qcdb.cfour.muster_psi4options(
            p4util.prepare_options_for_modules(changedOnly=True))
    else:
        psicmd, psikw = '', {}

    # Handle calc type and quantum chemical method
    mdccmd, mdckw = qcdb.cfour.muster_modelchem(name, dertype)

    # Handle calc type and quantum chemical method
    mdccmd, mdckw = qcdb.cfour.muster_modelchem(name, dertype)

    # Handle driver vs input/default keyword reconciliation
    userkw = p4util.prepare_options_for_modules()
    userkw = qcdb.options.reconcile_options(userkw, memkw)
    userkw = qcdb.options.reconcile_options(userkw, molkw)
    userkw = qcdb.options.reconcile_options(userkw, baskw)
    userkw = qcdb.options.reconcile_options(userkw, psikw)
    userkw = qcdb.options.reconcile_options(userkw, mdckw)

    # Handle conversion of psi4 keyword structure into cfour format
    optcmd = qcdb.options.prepare_options_for_cfour(userkw)

    # Handle text to be passed untouched to cfour
    litcmd = core.get_global_option('LITERAL_CFOUR')

    # Assemble ZMAT pieces
    zmat = memcmd + molcmd + optcmd + mdccmd + psicmd + bascmd + litcmd

    if len(re.findall(r'^\*(ACES2|CFOUR|CRAPS)\(', zmat, re.MULTILINE)) != 1:
        core.print_out('\n  Faulty ZMAT constructed:\n%s' % (zmat))
        raise ValidationError("""
Multiple *CFOUR(...) blocks in input. This usually arises
because molecule or options are specified both the psi4 way through
molecule {...} and set ... and the cfour way through cfour {...}.""")

    return zmat
Ejemplo n.º 27
0
def run_gaussian_2(name, **kwargs):

    # throw an exception for open-shells
    if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
        raise ValidationError("""g2 computations require "reference rhf".""")

    # stash user options:
    optstash = p4util.OptionsState(['FNOCC', 'COMPUTE_TRIPLES'],
                                   ['FNOCC', 'COMPUTE_MP4_TRIPLES'], ['BASIS'],
                                   ['FREEZE_CORE'], ['MP2_TYPE'], ['SCF_TYPE'])

    # override default scf_type
    core.set_global_option('SCF_TYPE', 'PK')

    # optimize geometry at scf level
    core.clean()
    core.set_global_option('BASIS', "6-31G(D)")
    driver.optimize('scf')
    core.clean()

    # scf frequencies for zpe
    # NOTE This line should not be needed, but without it there's a seg fault
    scf_e, ref = driver.frequency('scf', return_wfn=True)

    # thermodynamic properties
    du = core.variable('THERMAL ENERGY CORRECTION')
    dh = core.variable('ENTHALPY CORRECTION')
    dg = core.variable('GIBBS FREE ENERGY CORRECTION')

    freqs = ref.frequencies()
    nfreq = freqs.dim(0)
    freqsum = 0.0
    for i in range(0, nfreq):
        freqsum += freqs.get(i)
    zpe = freqsum / constants.hartree2wavenumbers * 0.8929 * 0.5
    core.clean()

    # optimize geometry at mp2 (no frozen core) level
    # note: freeze_core isn't an option in MP2
    core.set_global_option('FREEZE_CORE', "FALSE")
    core.set_global_option('MP2_TYPE', 'CONV')
    driver.optimize('mp2')
    core.clean()

    # qcisd(t)
    core.set_local_option('FNOCC', 'COMPUTE_MP4_TRIPLES', "TRUE")
    core.set_global_option('FREEZE_CORE', "TRUE")
    core.set_global_option('BASIS', "6-311G(D_P)")
    ref = driver.proc.run_fnocc('qcisd(t)', return_wfn=True, **kwargs)

    # HLC: high-level correction based on number of valence electrons
    nirrep = ref.nirrep()
    frzcpi = ref.frzcpi()
    nfzc = 0
    for i in range(0, nirrep):
        nfzc += frzcpi[i]
    nalpha = ref.nalpha() - nfzc
    nbeta = ref.nbeta() - nfzc
    # hlc of gaussian-2
    hlc = -0.00481 * nalpha - 0.00019 * nbeta
    # hlc of gaussian-1
    hlc1 = -0.00614 * nalpha

    eqci_6311gdp = core.variable("QCISD(T) TOTAL ENERGY")
    emp4_6311gd = core.variable("MP4 TOTAL ENERGY")
    emp2_6311gd = core.variable("MP2 TOTAL ENERGY")
    core.clean()

    # correction for diffuse functions
    core.set_global_option('BASIS', "6-311+G(D_P)")
    driver.energy('mp4')
    emp4_6311pg_dp = core.variable("MP4 TOTAL ENERGY")
    emp2_6311pg_dp = core.variable("MP2 TOTAL ENERGY")
    core.clean()

    # correction for polarization functions
    core.set_global_option('BASIS', "6-311G(2DF_P)")
    driver.energy('mp4')
    emp4_6311g2dfp = core.variable("MP4 TOTAL ENERGY")
    emp2_6311g2dfp = core.variable("MP2 TOTAL ENERGY")
    core.clean()

    # big basis mp2
    core.set_global_option('BASIS', "6-311+G(3DF_2P)")
    #run_fnocc('_mp2',**kwargs)
    driver.energy('mp2')
    emp2_big = core.variable("MP2 TOTAL ENERGY")
    core.clean()
    eqci = eqci_6311gdp
    e_delta_g2 = emp2_big + emp2_6311gd - emp2_6311g2dfp - emp2_6311pg_dp
    e_plus = emp4_6311pg_dp - emp4_6311gd
    e_2df = emp4_6311g2dfp - emp4_6311gd

    eg2 = eqci + e_delta_g2 + e_plus + e_2df
    eg2_mp2_0k = eqci + (emp2_big - emp2_6311gd) + hlc + zpe

    core.print_out('\n')
    core.print_out('  ==>  G1/G2 Energy Components  <==\n')
    core.print_out('\n')
    core.print_out('        QCISD(T):            %20.12lf\n' % eqci)
    core.print_out('        E(Delta):            %20.12lf\n' % e_delta_g2)
    core.print_out('        E(2DF):              %20.12lf\n' % e_2df)
    core.print_out('        E(+):                %20.12lf\n' % e_plus)
    core.print_out('        E(G1 HLC):           %20.12lf\n' % hlc1)
    core.print_out('        E(G2 HLC):           %20.12lf\n' % hlc)
    core.print_out('        E(ZPE):              %20.12lf\n' % zpe)
    core.print_out('\n')
    core.print_out('  ==>  0 Kelvin Results  <==\n')
    core.print_out('\n')
    eg2_0k = eg2 + zpe + hlc
    core.print_out('        G1:                  %20.12lf\n' %
                   (eqci + e_plus + e_2df + hlc1 + zpe))
    core.print_out('        G2(MP2):             %20.12lf\n' % eg2_mp2_0k)
    core.print_out('        G2:                  %20.12lf\n' % eg2_0k)

    core.set_variable("G1 TOTAL ENERGY", eqci + e_plus + e_2df + hlc1 + zpe)
    core.set_variable("G2 TOTAL ENERGY", eg2_0k)
    core.set_variable("G2(MP2) TOTAL ENERGY", eg2_mp2_0k)

    core.print_out('\n')
    T = core.get_global_option('T')
    core.print_out('  ==>  %3.0lf Kelvin Results  <==\n' % T)
    core.print_out('\n')

    internal_energy = eg2_mp2_0k + du - zpe / 0.8929
    enthalpy = eg2_mp2_0k + dh - zpe / 0.8929
    gibbs = eg2_mp2_0k + dg - zpe / 0.8929

    core.print_out('        G2(MP2) energy:      %20.12lf\n' % internal_energy)
    core.print_out('        G2(MP2) enthalpy:    %20.12lf\n' % enthalpy)
    core.print_out('        G2(MP2) free energy: %20.12lf\n' % gibbs)
    core.print_out('\n')

    core.set_variable("G2(MP2) INTERNAL ENERGY", internal_energy)
    core.set_variable("G2(MP2) ENTHALPY", enthalpy)
    core.set_variable("G2(MP2) FREE ENERGY", gibbs)

    internal_energy = eg2_0k + du - zpe / 0.8929
    enthalpy = eg2_0k + dh - zpe / 0.8929
    gibbs = eg2_0k + dg - zpe / 0.8929

    core.print_out('        G2 energy:           %20.12lf\n' % internal_energy)
    core.print_out('        G2 enthalpy:         %20.12lf\n' % enthalpy)
    core.print_out('        G2 free energy:      %20.12lf\n' % gibbs)

    core.set_variable("CURRENT ENERGY", eg2_0k)

    core.set_variable("G2 INTERNAL ENERGY", internal_energy)
    core.set_variable("G2 ENTHALPY", enthalpy)
    core.set_variable("G2 FREE ENERGY", gibbs)

    core.clean()

    optstash.restore()

    # return 0K g2 results
    return eg2_0k
Ejemplo n.º 28
0
def frac_traverse(name, **kwargs):
    """Scan electron occupancy from +1 electron to -1.

    Parameters
    ----------
    name : string or function
        DFT functional string name or function defining functional
        whose omega is to be optimized.
    molecule : :ref:`molecule <op_py_molecule>`, optional
        Target molecule (neutral) for which omega is to be tuned, if not last defined.
    cation_mult : int, optional
        Multiplicity of cation, if not neutral multiplicity + 1.
    anion_mult : int, optional
        Multiplicity of anion, if not neutral multiplicity + 1.
    frac_start : int, optional
        Iteration at which to start frac procedure when not reading previous
        guess. Defaults to 25.
    HOMO_occs : list, optional
        Occupations to step through for cation, by default `[1 - 0.1 * x for x in range(11)]`.
    LUMO_occs : list, optional
        Occupations to step through for anion, by default `[1 - 0.1 * x for x in range(11)]`.
    H**O : int, optional
        Index of H**O.
    LUMO : int, optional
        Index of LUMO.
    frac_diis : bool, optional
        Do use DIIS for non-1.0-occupied points?
    neutral_guess : bool, optional
        Do use neutral orbitals as guess for the anion?
    hf_guess: bool, optional
        Do use UHF guess before UKS?
    continuous_guess : bool, optional
        Do carry along guess rather than reguessing at each occupation?
    filename : str, optional
        Result filename, if not name of molecule.

    Returns
    -------
    dict
        Dictionary associating SCF energies with occupations.

    """
    optstash = p4util.OptionsState(
        ['SCF', 'GUESS'],
        ['SCF', 'DF_INTS_IO'],
        ['SCF', 'REFERENCE'],
        ["SCF", "FRAC_START"],
        ["SCF", "FRAC_RENORMALIZE"],
        #["SCF", "FRAC_LOAD"],
        ["SCF", "FRAC_OCC"],
        ["SCF", "FRAC_VAL"],
        ["SCF", "FRAC_DIIS"])
    kwargs = p4util.kwargs_lower(kwargs)

    # Make sure the molecule the user provided is the active one, and neutral
    molecule = kwargs.pop('molecule', core.get_active_molecule())
    molecule.update_geometry()

    if molecule.molecular_charge() != 0:
        raise ValidationError("""frac_traverse requires neutral molecule to start.""")
    if molecule.schoenflies_symbol() != 'c1':
        core.print_out("""  Requested procedure `frac_traverse` does not make use of molecular symmetry: """
                       """further calculations in C1 point group.\n""")
    molecule = molecule.clone()
    molecule.reset_point_group('c1')
    molecule.update_geometry()

    charge0 = molecule.molecular_charge()
    mult0 = molecule.multiplicity()

    chargep = charge0 + 1
    chargem = charge0 - 1

    multp = kwargs.get('cation_mult', mult0 + 1)
    multm = kwargs.get('anion_mult', mult0 + 1)

    # By default, we start the frac procedure on the 25th iteration
    # when not reading a previous guess
    frac_start = kwargs.get('frac_start', 25)

    # By default, we occupy by tenths of electrons
    HOMO_occs = kwargs.get('HOMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
    LUMO_occs = kwargs.get('LUMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])

    # By default, H**O and LUMO are both in alpha
    Z = 0
    for A in range(molecule.natom()):
        Z += molecule.Z(A)
    Z -= charge0
    H**O = kwargs.get('H**O', (Z / 2 + 1 if (Z % 2) else Z / 2))
    LUMO = kwargs.get('LUMO', H**O + 1)

    # By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
    frac_diis = kwargs.get('frac_diis', True)

    # By default, use the neutral orbitals as a guess for the anion
    neutral_guess = kwargs.get('neutral_guess', True)

    # By default, burn-in with UHF first, if UKS
    hf_guess = False
    if core.get_local_option('SCF', 'REFERENCE') == 'UKS':
        hf_guess = kwargs.get('hf_guess', True)

    # By default, re-guess at each N
    continuous_guess = kwargs.get('continuous_guess', False)

    # By default, drop the files to the molecule's name
    root = kwargs.get('filename', molecule.name())
    traverse_filename = root + '.traverse.dat'
    # => Traverse <= #
    occs = []
    energies = []
    potentials = []
    convs = []

    # => Run the neutral for its orbitals, if requested <= #

    core.set_local_option("SCF", "DF_INTS_IO", "SAVE")

    old_guess = core.get_local_option("SCF", "GUESS")
    if (neutral_guess):
        if (hf_guess):
            core.set_local_option("SCF", "REFERENCE", "UHF")
        driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "DF_INTS_IO", "LOAD")

    # => Run the anion first <= #

    molecule.set_molecular_charge(chargem)
    molecule.set_multiplicity(multm)

    # => Burn the anion in with hf, if requested <= #
    if hf_guess:
        core.set_local_option("SCF", "REFERENCE","UHF")
        driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
        core.set_local_option("SCF", "REFERENCE", "UKS")
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "DF_INTS_IO", "SAVE")

    core.set_local_option("SCF", "FRAC_START", frac_start)
    core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
    # NYI core.set_local_option("SCF", "FRAC_LOAD", False)

    for occ in LUMO_occs:

        core.set_local_option("SCF", "FRAC_OCC", [LUMO])
        core.set_local_option("SCF", "FRAC_VAL", [occ])

        E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)
        C = 1
        if E == 0.0:
            E = core.variable('SCF ITERATION ENERGY')
            C = 0

        if LUMO > 0:
            eps = wfn.epsilon_a()
            potentials.append(eps.get(int(LUMO) - 1))
        else:
            eps = wfn.epsilon_b()
            potentials.append(eps.get(-int(LUMO) - 1))

        occs.append(occ)
        energies.append(E)
        convs.append(C)

        core.set_local_option("SCF", "FRAC_START", 2)
        #core.set_local_option("SCF", "FRAC_LOAD", True)
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
        core.set_local_option("SCF", "DF_INTS_IO", "LOAD")


    # => Run the neutral next <= #

    molecule.set_molecular_charge(charge0)
    molecule.set_multiplicity(mult0)

    # Burn the neutral in with hf, if requested <= #

    if not continuous_guess:
        core.set_local_option("SCF", "GUESS", old_guess)
        if hf_guess:
            core.set_local_option("SCF", "FRAC_START", 0)
            core.set_local_option("SCF", "REFERENCE", "UHF")
            driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
            core.set_local_option("SCF", "REFERENCE", "UKS")
            core.set_local_option("SCF", "GUESS", "READ")
        # NYI core.set_local_option("SCF", "FRAC_LOAD", False)

    core.set_local_option("SCF", "FRAC_START", frac_start)
    core.set_local_option("SCF", "FRAC_RENORMALIZE", True)

    for occ in HOMO_occs:

        core.set_local_option("SCF", "FRAC_OCC", [H**O])
        core.set_local_option("SCF", "FRAC_VAL", [occ])

        E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)
        C = 1
        if E == 0.0:
            E = core.variable('SCF ITERATION ENERGY')
            C = 0

        if LUMO > 0:
            eps = wfn.epsilon_a()
            potentials.append(eps.get(int(H**O) - 1))
        else:
            eps = wfn.epsilon_b()
            potentials.append(eps.get(-int(H**O) - 1))

        occs.append(occ - 1.0)
        energies.append(E)
        convs.append(C)

        core.set_local_option("SCF", "FRAC_START", 2)
        # NYI core.set_local_option("SCF", "FRAC_LOAD", True)
        core.set_local_option("SCF", "GUESS", "READ")
        core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
        core.set_local_option("SCF", "DF_INTS_IO", "LOAD")

    # => Print the results out <= #
    E = {}
    core.print_out("""\n    ==> Fractional Occupation Traverse Results <==\n\n""")
    core.print_out("""    %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
    for k in range(len(occs)):
        core.print_out("""    %11.3E %24.16E %24.16E %11d\n""" % (occs[k], energies[k], potentials[k], convs[k]))
        E[occs[k]] = energies[k]

    core.print_out("""
    You trying to be a hero Watkins?
    Just trying to kill some bugs sir!
            -Starship Troopers""")

    # Drop the files out
    with open(traverse_filename, 'w') as fh:
        fh.write("""    %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
        for k in range(len(occs)):
            fh.write("""    %11.3E %24.16E %24.16E %11d\n""" % (occs[k], energies[k], potentials[k], convs[k]))

    optstash.restore()
    return E
Ejemplo n.º 29
0
def _set_convergence_criterion(ptype, method_name, scf_Ec, pscf_Ec, scf_Dc, pscf_Dc, gen_Ec, verbose=1):
    r"""
    This function will set local SCF and global energy convergence criterion
    to the defaults listed at:
    http://www.psicode.org/psi4manual/master/scf.html#convergence-and-
    algorithm-defaults. SCF will be converged more tightly if a post-SCF
    method is select (pscf_Ec, and pscf_Dc) else the looser (scf_Ec, and
    scf_Dc convergence criterion will be used).

    ptype -         Procedure type (energy, gradient, etc). Nearly always test on
                    procedures['energy'] since that's guaranteed to exist for a method.
    method_name -   Name of the method
    scf_Ec -        E convergence criterion for scf target method
    pscf_Ec -       E convergence criterion for scf of post-scf target method
    scf_Dc -        D convergence criterion for scf target method
    pscf_Dc -       D convergence criterion for scf of post-scf target method
    gen_Ec -        E convergence criterion for post-scf target method

    """
    optstash = p4util.OptionsState(
        ['SCF', 'E_CONVERGENCE'],
        ['SCF', 'D_CONVERGENCE'],
        ['E_CONVERGENCE'])

    # Kind of want to move this out of here
    _method_exists(ptype, method_name)

    if verbose >= 2:
        print('      Setting convergence', end=' ')
    # Set method-dependent scf convergence criteria, check against energy routines
    if not core.has_option_changed('SCF', 'E_CONVERGENCE'):
        if procedures['energy'][method_name] == proc.run_scf:
            core.set_local_option('SCF', 'E_CONVERGENCE', scf_Ec)
            if verbose >= 2:
                print(scf_Ec, end=' ')
        else:
            core.set_local_option('SCF', 'E_CONVERGENCE', pscf_Ec)
            if verbose >= 2:
                print(pscf_Ec, end=' ')
    else:
        if verbose >= 2:
            print('CUSTOM', core.get_option('SCF', 'E_CONVERGENCE'), end=' ')

    if not core.has_option_changed('SCF', 'D_CONVERGENCE'):
        if procedures['energy'][method_name] == proc.run_scf:
            core.set_local_option('SCF', 'D_CONVERGENCE', scf_Dc)
            if verbose >= 2:
                print(scf_Dc, end=' ')
        else:
            core.set_local_option('SCF', 'D_CONVERGENCE', pscf_Dc)
            if verbose >= 2:
                print(pscf_Dc, end=' ')
    else:
        if verbose >= 2:
            print('CUSTOM', core.get_option('SCF', 'D_CONVERGENCE'), end=' ')

    # Set post-scf convergence criteria (global will cover all correlated modules)
    if not core.has_global_option_changed('E_CONVERGENCE'):
        if procedures['energy'][method_name] != proc.run_scf:
            core.set_global_option('E_CONVERGENCE', gen_Ec)
            if verbose >= 2:
                print(gen_Ec, end=' ')
    else:
        if procedures['energy'][method_name] != proc.run_scf:
            if verbose >= 2:
                print('CUSTOM', core.get_global_option('E_CONVERGENCE'), end=' ')

    if verbose >= 2:
        print('')
    return optstash
Ejemplo n.º 30
0
def _set_convergence_criterion(ptype,
                               method_name,
                               scf_Ec,
                               pscf_Ec,
                               scf_Dc,
                               pscf_Dc,
                               gen_Ec,
                               verbose=1):
    r"""
    This function will set local SCF and global energy convergence criterion
    to the defaults listed at:
    http://www.psicode.org/psi4manual/master/scf.html#convergence-and-
    algorithm-defaults. SCF will be converged more tightly if a post-SCF
    method is select (pscf_Ec, and pscf_Dc) else the looser (scf_Ec, and
    scf_Dc convergence criterion will be used).

    ptype -         Procedure type (energy, gradient, etc). Nearly always test on
                    procedures['energy'] since that's guaranteed to exist for a method.
    method_name -   Name of the method
    scf_Ec -        E convergence criterion for scf target method
    pscf_Ec -       E convergence criterion for scf of post-scf target method
    scf_Dc -        D convergence criterion for scf target method
    pscf_Dc -       D convergence criterion for scf of post-scf target method
    gen_Ec -        E convergence criterion for post-scf target method

    """
    optstash = p4util.OptionsState(['SCF', 'E_CONVERGENCE'],
                                   ['SCF', 'D_CONVERGENCE'], ['E_CONVERGENCE'])

    # Kind of want to move this out of here
    _method_exists(ptype, method_name)

    if verbose >= 2:
        print('      Setting convergence', end=' ')
    # Set method-dependent scf convergence criteria, check against energy routines
    if not core.has_option_changed('SCF', 'E_CONVERGENCE'):
        if procedures['energy'][method_name] == proc.run_scf:
            core.set_local_option('SCF', 'E_CONVERGENCE', scf_Ec)
            if verbose >= 2:
                print(scf_Ec, end=' ')
        else:
            core.set_local_option('SCF', 'E_CONVERGENCE', pscf_Ec)
            if verbose >= 2:
                print(pscf_Ec, end=' ')
    else:
        if verbose >= 2:
            print('CUSTOM', core.get_option('SCF', 'E_CONVERGENCE'), end=' ')

    if not core.has_option_changed('SCF', 'D_CONVERGENCE'):
        if procedures['energy'][method_name] == proc.run_scf:
            core.set_local_option('SCF', 'D_CONVERGENCE', scf_Dc)
            if verbose >= 2:
                print(scf_Dc, end=' ')
        else:
            core.set_local_option('SCF', 'D_CONVERGENCE', pscf_Dc)
            if verbose >= 2:
                print(pscf_Dc, end=' ')
    else:
        if verbose >= 2:
            print('CUSTOM', core.get_option('SCF', 'D_CONVERGENCE'), end=' ')

    # Set post-scf convergence criteria (global will cover all correlated modules)
    if not core.has_global_option_changed('E_CONVERGENCE'):
        if procedures['energy'][method_name] != proc.run_scf:
            core.set_global_option('E_CONVERGENCE', gen_Ec)
            if verbose >= 2:
                print(gen_Ec, end=' ')
    else:
        if procedures['energy'][method_name] != proc.run_scf:
            if verbose >= 2:
                print('CUSTOM',
                      core.get_global_option('E_CONVERGENCE'),
                      end=' ')

    if verbose >= 2:
        print('')
    return optstash
Ejemplo n.º 31
0
def run_gaussian_2(name, **kwargs):

    # throw an exception for open-shells
    if (core.get_option('SCF','REFERENCE') != 'RHF' ):
        raise ValidationError("""g2 computations require "reference rhf".""")

    # stash user options:
    optstash = p4util.OptionsState(
        ['FNOCC','COMPUTE_TRIPLES'],
        ['FNOCC','COMPUTE_MP4_TRIPLES'],
        ['FREEZE_CORE'],
        ['MP2_TYPE'],
        ['SCF','SCF_TYPE'])

    # override default scf_type
    core.set_local_option('SCF','SCF_TYPE','PK')

    # optimize geometry at scf level
    core.clean()
    core.set_global_option('BASIS',"6-31G(D)")
    driver.optimize('scf')
    core.clean()

    # scf frequencies for zpe
    # NOTE This line should not be needed, but without it there's a seg fault
    scf_e, ref = driver.frequency('scf', return_wfn=True)

    # thermodynamic properties
    du = core.get_variable('INTERNAL ENERGY CORRECTION')
    dh = core.get_variable('ENTHALPY CORRECTION')
    dg = core.get_variable('GIBBS FREE ENERGY CORRECTION')

    freqs   = ref.frequencies()
    nfreq   = freqs.dim(0)
    freqsum = 0.0
    for i in range(0, nfreq):
        freqsum += freqs.get(i)
    zpe = freqsum / p4const.psi_hartree2wavenumbers * 0.8929 * 0.5
    core.clean()

    # optimize geometry at mp2 (no frozen core) level
    # note: freeze_core isn't an option in MP2
    core.set_global_option('FREEZE_CORE',"FALSE")
    core.set_global_option('MP2_TYPE', 'CONV')
    driver.optimize('mp2')
    core.clean()

    # qcisd(t)
    core.set_local_option('FNOCC','COMPUTE_MP4_TRIPLES',"TRUE")
    core.set_global_option('FREEZE_CORE',"TRUE")
    core.set_global_option('BASIS',"6-311G(D_P)")
    ref = driver.proc.run_fnocc('qcisd(t)', return_wfn=True, **kwargs)

    # HLC: high-level correction based on number of valence electrons
    nirrep = ref.nirrep()
    frzcpi = ref.frzcpi()
    nfzc = 0
    for i in range (0,nirrep):
        nfzc += frzcpi[i]
    nalpha = ref.nalpha() - nfzc
    nbeta  = ref.nbeta() - nfzc
    # hlc of gaussian-2
    hlc = -0.00481 * nalpha -0.00019 * nbeta
    # hlc of gaussian-1
    hlc1 = -0.00614 * nalpha

    eqci_6311gdp = core.get_variable("QCISD(T) TOTAL ENERGY")
    emp4_6311gd  = core.get_variable("MP4 TOTAL ENERGY")
    emp2_6311gd  = core.get_variable("MP2 TOTAL ENERGY")
    core.clean()

    # correction for diffuse functions
    core.set_global_option('BASIS',"6-311+G(D_P)")
    driver.energy('mp4')
    emp4_6311pg_dp = core.get_variable("MP4 TOTAL ENERGY")
    emp2_6311pg_dp = core.get_variable("MP2 TOTAL ENERGY")
    core.clean()

    # correction for polarization functions
    core.set_global_option('BASIS',"6-311G(2DF_P)")
    driver.energy('mp4')
    emp4_6311g2dfp = core.get_variable("MP4 TOTAL ENERGY")
    emp2_6311g2dfp = core.get_variable("MP2 TOTAL ENERGY")
    core.clean()

    # big basis mp2
    core.set_global_option('BASIS',"6-311+G(3DF_2P)")
    #run_fnocc('_mp2',**kwargs)
    driver.energy('mp2')
    emp2_big = core.get_variable("MP2 TOTAL ENERGY")
    core.clean()
    eqci       = eqci_6311gdp
    e_delta_g2 = emp2_big + emp2_6311gd - emp2_6311g2dfp - emp2_6311pg_dp
    e_plus     = emp4_6311pg_dp - emp4_6311gd
    e_2df      = emp4_6311g2dfp - emp4_6311gd

    eg2 = eqci + e_delta_g2 + e_plus + e_2df
    eg2_mp2_0k = eqci + (emp2_big - emp2_6311gd) + hlc + zpe

    core.print_out('\n')
    core.print_out('  ==>  G1/G2 Energy Components  <==\n')
    core.print_out('\n')
    core.print_out('        QCISD(T):            %20.12lf\n' % eqci)
    core.print_out('        E(Delta):            %20.12lf\n' % e_delta_g2)
    core.print_out('        E(2DF):              %20.12lf\n' % e_2df)
    core.print_out('        E(+):                %20.12lf\n' % e_plus)
    core.print_out('        E(G1 HLC):           %20.12lf\n' % hlc1)
    core.print_out('        E(G2 HLC):           %20.12lf\n' % hlc)
    core.print_out('        E(ZPE):              %20.12lf\n' % zpe)
    core.print_out('\n')
    core.print_out('  ==>  0 Kelvin Results  <==\n')
    core.print_out('\n')
    eg2_0k = eg2 + zpe + hlc
    core.print_out('        G1:                  %20.12lf\n' % (eqci + e_plus + e_2df + hlc1 + zpe))
    core.print_out('        G2(MP2):             %20.12lf\n' % eg2_mp2_0k)
    core.print_out('        G2:                  %20.12lf\n' % eg2_0k)

    core.set_variable("G1 TOTAL ENERGY",eqci + e_plus + e_2df + hlc1 + zpe)
    core.set_variable("G2 TOTAL ENERGY",eg2_0k)
    core.set_variable("G2(MP2) TOTAL ENERGY",eg2_mp2_0k)

    core.print_out('\n')
    T = core.get_global_option('T')
    core.print_out('  ==>  %3.0lf Kelvin Results  <==\n'% T)
    core.print_out('\n')

    internal_energy = eg2_mp2_0k + du - zpe / 0.8929
    enthalpy        = eg2_mp2_0k + dh - zpe / 0.8929
    gibbs           = eg2_mp2_0k + dg - zpe / 0.8929

    core.print_out('        G2(MP2) energy:      %20.12lf\n' % internal_energy )
    core.print_out('        G2(MP2) enthalpy:    %20.12lf\n' % enthalpy)
    core.print_out('        G2(MP2) free energy: %20.12lf\n' % gibbs)
    core.print_out('\n')

    core.set_variable("G2(MP2) INTERNAL ENERGY",internal_energy)
    core.set_variable("G2(MP2) ENTHALPY",enthalpy)
    core.set_variable("G2(MP2) FREE ENERGY",gibbs)

    internal_energy = eg2_0k + du - zpe / 0.8929
    enthalpy        = eg2_0k + dh - zpe / 0.8929
    gibbs           = eg2_0k + dg - zpe / 0.8929

    core.print_out('        G2 energy:           %20.12lf\n' % internal_energy )
    core.print_out('        G2 enthalpy:         %20.12lf\n' % enthalpy)
    core.print_out('        G2 free energy:      %20.12lf\n' % gibbs)

    core.set_variable("CURRENT ENERGY",eg2_0k)

    core.set_variable("G2 INTERNAL ENERGY",internal_energy)
    core.set_variable("G2 ENTHALPY",enthalpy)
    core.set_variable("G2 FREE ENERGY",gibbs)

    core.clean()

    optstash.restore()

    # return 0K g2 results
    return eg2_0k
Ejemplo n.º 32
0
def run_sapt_dft(name, **kwargs):
    optstash = p4util.OptionsState(['SCF', 'SCF_TYPE'],
                                   ['SCF', 'REFERENCE'],
                                   ['SCF', 'DFT_FUNCTIONAL'],
                                   ['SCF', 'DFT_GRAC_SHIFT'],
                                   ['SCF', 'SAVE_JK'])

    core.tstart()
    # Alter default algorithm
    if not core.has_option_changed('SCF', 'SCF_TYPE'):
        core.set_local_option('SCF', 'SCF_TYPE', 'DF')

    core.prepare_options_for_module("SAPT")

    # Get the molecule of interest
    ref_wfn = kwargs.get('ref_wfn', None)
    if ref_wfn is None:
        sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
    else:
        core.print_out('Warning! SAPT argument "ref_wfn" is only able to use molecule information.')
        sapt_dimer = ref_wfn.molecule()

    sapt_dimer, monomerA, monomerB = proc_util.prepare_sapt_molecule(sapt_dimer, "dimer")

    # Grab overall settings
    mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
    mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
    do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
    sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")

    # Print out the title and some information
    core.print_out("\n")
    core.print_out("         ---------------------------------------------------------\n")
    core.print_out("         " + "SAPT(DFT) Procedure".center(58) + "\n")
    core.print_out("\n")
    core.print_out("         " + "by Daniel G. A. Smith".center(58) + "\n")
    core.print_out("         ---------------------------------------------------------\n")
    core.print_out("\n")

    core.print_out("  ==> Algorithm <==\n\n")
    core.print_out("   SAPT DFT Functional     %12s\n" % str(sapt_dft_functional))
    core.print_out("   Monomer A GRAC Shift    %12.6f\n" % mon_a_shift)
    core.print_out("   Monomer B GRAC Shift    %12.6f\n" % mon_b_shift)
    core.print_out("   Delta HF                %12s\n" % ("True" if do_delta_hf else "False"))
    core.print_out("   JK Algorithm            %12s\n" % core.get_option("SCF", "SCF_TYPE"))
    core.print_out("\n")
    core.print_out("   Required computations:\n")
    if (do_delta_hf):
        core.print_out("     HF  (Dimer)\n")
        core.print_out("     HF  (Monomer A)\n")
        core.print_out("     HF  (Monomer B)\n")
    core.print_out("     DFT (Monomer A)\n")
    core.print_out("     DFT (Monomer B)\n")
    core.print_out("\n")

    if (sapt_dft_functional != "HF") and ((mon_a_shift == 0.0) or (mon_b_shift == 0.0)):
        raise ValidationError('SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')

    if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
        raise ValidationError('SAPT(DFT) currently only supports restricted references.')


    core.IO.set_default_namespace('dimer')
    data = {}

    core.set_global_option("SAVE_JK", True)
    if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
        # core.set_global_option('DF_INTS_IO', 'LOAD')
        core.set_global_option('DF_INTS_IO', 'SAVE')

    # # Compute dimer wavefunction
    hf_cache = {}
    hf_wfn_dimer = None
    if do_delta_hf:
        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.set_global_option('DF_INTS_IO', 'SAVE')

        hf_data = {}
        hf_wfn_dimer = scf_helper(
            "SCF", molecule=sapt_dimer, banner="SAPT(DFT): delta HF Dimer", **kwargs)
        hf_data["HF DIMER"] = core.get_variable("CURRENT ENERGY")

        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'dimer', 'monomerA')
        hf_wfn_A = scf_helper(
            "SCF", molecule=monomerA, banner="SAPT(DFT): delta HF Monomer A", **kwargs)
        hf_data["HF MONOMER A"] = core.get_variable("CURRENT ENERGY")

        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
        hf_wfn_B = scf_helper(
            "SCF", molecule=monomerB, banner="SAPT(DFT): delta HF Monomer B", **kwargs)
        hf_data["HF MONOMER B"] = core.get_variable("CURRENT ENERGY")

        # Move it back to monomer A
        if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
            core.IO.change_file_namespace(97, 'monomerB', 'dimer')

        core.print_out("\n")
        core.print_out("         ---------------------------------------------------------\n")
        core.print_out("         " + "SAPT(DFT): delta HF Segement".center(58) + "\n")
        core.print_out("\n")
        core.print_out("         " + "by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
        core.print_out("         ---------------------------------------------------------\n")
        core.print_out("\n")

        # Build cache and JK
        sapt_jk = hf_wfn_B.jk()

        hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B, sapt_jk, True)

        # Electostatics
        elst = sapt_jk_terms.electrostatics(hf_cache, True)
        hf_data.update(elst)

        # Exchange
        exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
        hf_data.update(exch)

        # Induction
        ind = sapt_jk_terms.induction(
            hf_cache,
            sapt_jk,
            True,
            maxiter=core.get_option("SAPT", "MAXITER"),
            conv=core.get_option("SAPT", "D_CONVERGENCE"))
        hf_data.update(ind)

        dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data["HF MONOMER B"]

        core.print_out("\n")
        core.print_out(print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))

        data["Delta HF Correction"] = core.get_variable("SAPT(DFT) Delta HF")

    if hf_wfn_dimer is None:
        dimer_wfn = core.Wavefunction.build(sapt_dimer, core.get_global_option("BASIS"))
    else:
        dimer_wfn = hf_wfn_dimer

    # Set the primary functional
    core.set_global_option("DFT_FUNCTIONAL", core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL"))
    core.set_local_option('SCF', 'REFERENCE', 'RKS')

    # Compute Monomer A wavefunction
    if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'dimer', 'monomerA')

    if mon_a_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)

    # Save the JK object
    core.IO.set_default_namespace('monomerA')
    wfn_A = scf_helper("SCF", molecule=monomerA, banner="SAPT(DFT): DFT Monomer A", **kwargs)
    data["DFT MONOMERA"] = core.get_variable("CURRENT ENERGY")

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)

    # Compute Monomer B wavefunction
    if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
        core.IO.change_file_namespace(97, 'monomerA', 'monomerB')

    if mon_b_shift:
        core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)

    core.IO.set_default_namespace('monomerB')
    wfn_B = scf_helper("SCF", molecule=monomerB, banner="SAPT(DFT): DFT Monomer B", **kwargs)
    data["DFT MONOMERB"] = core.get_variable("CURRENT ENERGY")

    core.set_global_option("DFT_GRAC_SHIFT", 0.0)

    # Print out the title and some information
    core.print_out("\n")
    core.print_out("         ---------------------------------------------------------\n")
    core.print_out("         " + "SAPT(DFT): Intermolecular Interaction Segment".center(58) + "\n")
    core.print_out("\n")
    core.print_out("         " + "by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
    core.print_out("         ---------------------------------------------------------\n")
    core.print_out("\n")

    core.print_out("  ==> Algorithm <==\n\n")
    core.print_out("   SAPT DFT Functional     %12s\n" % str(sapt_dft_functional))
    core.print_out("   Monomer A GRAC Shift    %12.6f\n" % mon_a_shift)
    core.print_out("   Monomer B GRAC Shift    %12.6f\n" % mon_b_shift)
    core.print_out("   Delta HF                %12s\n" % ("True" if do_delta_hf else "False"))
    core.print_out("   JK Algorithm            %12s\n" % core.get_option("SCF", "SCF_TYPE"))

    # Build cache and JK
    sapt_jk = wfn_B.jk()

    cache = sapt_jk_terms.build_sapt_jk_cache(wfn_A, wfn_B, sapt_jk, True)

    # Electostatics
    elst = sapt_jk_terms.electrostatics(cache, True)
    data.update(elst)

    # Exchange
    exch = sapt_jk_terms.exchange(cache, sapt_jk, True)
    data.update(exch)

    # Induction
    ind = sapt_jk_terms.induction(
        cache,
        sapt_jk,
        True,
        maxiter=core.get_option("SAPT", "MAXITER"),
        conv=core.get_option("SAPT", "D_CONVERGENCE"))
    data.update(ind)

    # Dispersion
    primary_basis = wfn_A.basisset()
    core.print_out("\n")
    aux_basis = core.BasisSet.build(sapt_dimer, "DF_BASIS_MP2",
                                    core.get_option("DFMP2", "DF_BASIS_MP2"), "RIFIT",
                                    core.get_global_option('BASIS'))
    fdds_disp = sapt_mp2_terms.df_fdds_dispersion(primary_basis, aux_basis, cache)
    data.update(fdds_disp)

    if core.get_option("SAPT", "SAPT_DFT_MP2_DISP_ALG") == "FISAPT":
        mp2_disp = sapt_mp2_terms.df_mp2_fisapt_dispersion(wfn_A, primary_basis, aux_basis, cache, do_print=True)
    else:
        mp2_disp = sapt_mp2_terms.df_mp2_sapt_dispersion(
            dimer_wfn, wfn_A, wfn_B, primary_basis, aux_basis, cache, do_print=True)
    data.update(mp2_disp)

    # Print out final data
    core.print_out("\n")
    core.print_out(print_sapt_dft_summary(data, "SAPT(DFT)"))

    # Copy data back into globals
    for k, v in data.items():
        core.set_variable(k, v)

    core.tstop()

    return dimer_wfn
Ejemplo n.º 33
0
def frac_nuke(name, **kwargs):
    """Pull all the electrons out, one at a time"""
    optstash = p4util.OptionsState(
        ['SCF', 'GUESS'],
        ['SCF', 'DF_INTS_IO'],
        ["SCF", "FRAC_START"],
        ["SCF", "FRAC_RENORMALIZE"],
        # NYI ["SCF", "FRAC_LOAD"],
        ["SCF", "FRAC_OCC"],
        ["SCF", "FRAC_VAL"],
        ["SCF", "FRAC_DIIS"])

    kwargs = p4util.kwargs_lower(kwargs)

    # Make sure the molecule the user provided is the active one, and neutral
    molecule = kwargs.pop('molecule', core.get_active_molecule())
    molecule.update_geometry()

    if molecule.molecular_charge() != 0:
        raise ValidationError("""frac_nuke requires neutral molecule to start.""")
    if molecule.schoenflies_symbol() != 'c1':
        core.print_out("""  Requested procedure `frac_nuke` does not make use of molecular symmetry: """
                       """further calculations in C1 point group.\n""")
    molecule = molecule.clone()
    molecule.reset_point_group('c1')
    molecule.update_geometry()

    charge0 = molecule.molecular_charge()
    mult0 = molecule.multiplicity()

    # By default, we start the frac procedure on the 25th iteration
    # when not reading a previous guess
    frac_start = kwargs.get('frac_start', 25)

    # By default, we occupy by tenths of electrons
    foccs = kwargs.get('foccs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])

    # By default, H**O and LUMO are both in alpha
    N = 0
    for A in range(molecule.natom()):
        N += molecule.Z(A)
    N -= charge0
    N = int(N)
    Nb = int((N - mult0 + 1) / 2)
    Na = int(N - Nb)

    charge = charge0
    mult = mult0

    # By default, nuke all the electrons
    Nmin = 0
    if 'nmax' in kwargs:
        Nmin = N - int(kwargs['nmax'])

    # By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
    frac_diis = kwargs.get('frac_diis', True)

    # By default, drop the files to the molecule's name
    root = kwargs.get('filename', molecule.name())
    traverse_filename = root + '.traverse.dat'
    stats_filename = root + '.stats.dat'

    # => Traverse <= #
    core.set_local_option("SCF", "DF_INTS_IO", "SAVE")

    Ns = []
    energies = []
    potentials = []
    convs = []
    stats = []

    # Run one SCF to burn things in
    E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)

    # Determine H**O
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    eps_a.print_out()
    if Na == Nb:
        H**O = -Nb
    elif Nb == 0:
        H**O = Na
    else:
        E_a = eps_a.get(int(Na - 1))
        E_b = eps_b.get(int(Nb - 1))
        if E_a >= E_b:
            H**O = Na
        else:
            H**O = -Nb

    stats.append("""    %6d %6d %6d %6d %6d %6d\n""" % (N, Na, Nb, charge, mult, H**O))

    if H**O > 0:
        Na -= 1
    else:
        Nb -= 1
    charge += 1
    mult = Na - Nb + 1

    core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
    core.set_local_option("SCF", "FRAC_START", frac_start)
    core.set_local_option("SCF", "FRAC_RENORMALIZE", True)

    # Nuke 'em Rico!
    for Nintegral in range(N, Nmin, -1):

        # Nuke the current H**O
        for occ in foccs:

            core.set_local_option("SCF", "FRAC_OCC", [H**O])
            core.set_local_option("SCF", "FRAC_VAL", [occ])

            E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)
            C = 1
            if E == 0.0:
                E = core.variable('SCF ITERATION ENERGY')
                C = 0

            if H**O > 0:
                eps = wfn.epsilon_a()
                potentials.append(eps.np[H**O - 1])
            else:
                eps = wfn.epsilon_b()
                potentials.append(eps.np[-H**O - 1])

            Ns.append(Nintegral + occ - 1.0)
            energies.append(E)
            convs.append(C)

            core.set_local_option("SCF", "FRAC_START", 2)
            # NYI core.set_local_option("SCF", "FRAC_LOAD", True)
            core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
            core.set_local_option("SCF", "GUESS", "READ")

        # Set the next charge/mult
        molecule.set_molecular_charge(charge)
        molecule.set_multiplicity(mult)

        # Determine H**O
        print('DGAS: What ref should this point to?')
        #ref = core.legacy_wavefunction()
        eps_a = wfn.epsilon_a()
        eps_b = wfn.epsilon_b()
        if Na == Nb:
            H**O = -Nb
        elif Nb == 0:
            H**O = Na
        else:
            E_a = eps_a.np[int(Na - 1)]
            E_b = eps_b.np[int(Nb - 1)]
            if E_a >= E_b:
                H**O = Na
            else:
                H**O = -Nb

        stats.append("""    %6d %6d %6d %6d %6d %6d\n""" % (Nintegral-1, Na, Nb, charge, mult, H**O))

        if H**O > 0:
            Na -= 1
        else:
            Nb -= 1
        charge += 1
        mult = Na - Nb + 1

    core.set_local_option("SCF", "DF_INTS_IO", "NONE")

    # => Print the results out <= #
    E = {}
    core.print_out("""\n    ==> Fractional Occupation Nuke Results <==\n\n""")
    core.print_out("""    %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
    for k in range(len(Ns)):
        core.print_out("""    %11.3E %24.16E %24.16E %11d\n""" % (Ns[k], energies[k], potentials[k], convs[k]))
        E[Ns[k]] = energies[k]

    core.print_out('\n')
    core.print_out("""    %6s %6s %6s %6s %6s %6s\n""" % ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
    for line in stats:
        core.print_out(line)

    core.print_out('\n    "You shoot a nuke down a bug hole, you got a lot of dead bugs"\n')
    core.print_out('            -Starship Troopers\n')

    # Drop the files out
    with open(traverse_filename, 'w') as fh:
        fh.write("""    %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
        for k in range(len(Ns)):
            fh.write("""    %11.3E %24.16E %24.16E %11d\n""" % (Ns[k], energies[k], potentials[k], convs[k]))

    with open(stats_filename, 'w') as fh:
        fh.write("""    %6s %6s %6s %6s %6s %6s\n""" % ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
        for line in stats:
            fh.write(line)

    optstash.restore()
    return E
Ejemplo n.º 34
0
def ip_fitting(name, omega_l=0.05, omega_r=2.5, omega_convergence=1.0e-3, maxiter=20, **kwargs):
    """Optimize DFT omega parameter for molecular system.

    Parameters
    ----------
    name : string or function
        DFT functional string name or function defining functional
        whose omega is to be optimized.
    omega_l : float, optional
        Minimum omega to be considered during fitting.
    omega_r : float, optional
        Maximum omega to be considered during fitting.
    molecule : :ref:`molecule <op_py_molecule>`, optional
        Target molecule (neutral) for which omega is to be tuned, if not last defined.
    omega_convergence : float, optional
        Threshold below which to consider omega converged. (formerly omega_tolerance)
    maxiter : int, optional
        Maximum number of iterations towards omega convergence.

    Returns
    -------
    float
        Optimal omega parameter.

    """
    optstash = p4util.OptionsState(
        ['SCF', 'REFERENCE'],
        ['SCF', 'GUESS'],
        ['SCF', 'DF_INTS_IO'],
        ['SCF', 'DFT_OMEGA'],
        ['DOCC'],
        ['SOCC'])

    kwargs = p4util.kwargs_lower(kwargs)

    # By default, do not read previous 180 orbitals file
    read = False
    read180 = ''
    if 'read' in kwargs:
        read = True
        read180 = kwargs['read']

    if core.get_option('SCF', 'REFERENCE') != 'UKS':
        core.print_out("""  Requested procedure `ip_fitting` runs further calculations with UKS reference.\n""")
        core.set_local_option('SCF', 'REFERENCE', 'UKS')

    # Make sure the molecule the user provided is the active one, and neutral
    molecule = kwargs.pop('molecule', core.get_active_molecule())
    molecule.update_geometry()

    if molecule.molecular_charge() != 0:
        raise ValidationError("""IP Fitting requires neutral molecule to start.""")
    if molecule.schoenflies_symbol() != 'c1':
        core.print_out("""  Requested procedure `ip_fitting` does not make use of molecular symmetry: """
                       """further calculations in C1 point group.\n""")
    molecule = molecule.clone()
    molecule.reset_point_group('c1')
    molecule.update_geometry()

    charge0 = molecule.molecular_charge()
    mult0 = molecule.multiplicity()

    # How many electrons are there?
    N = 0
    for A in range(molecule.natom()):
        N += molecule.Z(A)
    N -= charge0
    N = int(N)
    Nb = int((N - mult0 + 1) / 2)
    Na = int(N - Nb)

    # Work in the ot namespace for this procedure
    core.IO.set_default_namespace("ot")

    # Burn in to determine orbital eigenvalues
    if read:
        core.set_local_option("SCF", "GUESS", "READ")
        copy_file_to_scratch(read180, 'psi', 'ot', 180)
    core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
    E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
                           banner='IP Fitting SCF: Burn-in', **kwargs)
    core.set_local_option("SCF", "DF_INTS_IO", "LOAD")

    if not wfn.functional().is_x_lrc():
        raise ValidationError("""Not sensible to optimize omega for non-long-range-correction functional.""")

    # Determine H**O, to determine mult1
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    if Na == Nb:
        H**O = -Nb
    elif Nb == 0:
        H**O = Na
    else:
        E_a = eps_a.np[int(Na - 1)]
        E_b = eps_b.np[int(Nb - 1)]
        if E_a >= E_b:
            H**O = Na
        else:
            H**O = -Nb

    Na1 = Na
    Nb1 = Nb
    if H**O > 0:
        Na1 -= 1
    else:
        Nb1 -= 1

    charge1 = charge0 + 1
    mult1 = Na1 - Nb1 + 1

    omegas = []
    E0s = []
    E1s = []
    kIPs = []
    IPs = []
    types = []

    # Right endpoint
    core.set_local_option('SCF', 'DFT_OMEGA', omega_r)

    # Neutral
    if read:
        core.set_local_option("SCF", "GUESS", "READ")
        p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)

    molecule.set_molecular_charge(charge0)
    molecule.set_multiplicity(mult0)
    E0r, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
                             banner='IP Fitting SCF: Neutral, Right Endpoint', **kwargs)
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    if Nb == 0:
        E_HOMO = eps_a.np[int(Na - 1)]
    else:
        E_a = eps_a.np[int(Na - 1)]
        E_b = eps_b.np[int(Nb - 1)]
        E_HOMO = max(E_a, E_b)
    E_HOMOr = E_HOMO
    core.IO.change_file_namespace(180, "ot", "neutral")

    # Cation
    if read:
        core.set_local_option("SCF", "GUESS", "READ")
        p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)

    molecule.set_molecular_charge(charge1)
    molecule.set_multiplicity(mult1)
    E1r = driver.energy('scf', dft_functional=name, molecule=molecule,
                               banner='IP Fitting SCF: Cation, Right Endpoint', **kwargs)
    core.IO.change_file_namespace(180, "ot", "cation")

    IPr = E1r - E0r
    kIPr = -E_HOMOr
    delta_r = IPr - kIPr

    if IPr > kIPr:
        raise ValidationError("""\n***IP Fitting Error: Right Omega limit should have kIP > IP: {} !> {}""".format(kIPr, IPr))

    omegas.append(omega_r)
    types.append('Right Limit')
    E0s.append(E0r)
    E1s.append(E1r)
    IPs.append(IPr)
    kIPs.append(kIPr)

    # Use previous orbitals from here out
    core.set_local_option("SCF", "GUESS", "READ")

    # Left endpoint
    core.set_local_option('SCF', 'DFT_OMEGA', omega_l)

    # Neutral
    core.IO.change_file_namespace(180, "neutral", "ot")
    molecule.set_molecular_charge(charge0)
    molecule.set_multiplicity(mult0)
    core.set_global_option("DOCC", [Nb])
    core.set_global_option("SOCC", [Na - Nb])
    E0l, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
                             banner='IP Fitting SCF: Neutral, Left Endpoint', **kwargs)
    eps_a = wfn.epsilon_a()
    eps_b = wfn.epsilon_b()
    if Nb == 0:
        E_HOMO = eps_a.np[int(Na - 1)]
    else:
        E_a = eps_a.np[int(Na - 1)]
        E_b = eps_b.np[int(Nb - 1)]
        E_HOMO = max(E_a, E_b)
    E_HOMOl = E_HOMO
    core.IO.change_file_namespace(180, "ot", "neutral")

    # Cation
    core.IO.change_file_namespace(180, "cation", "ot")
    molecule.set_molecular_charge(charge1)
    molecule.set_multiplicity(mult1)
    core.set_global_option("DOCC", [Nb1])
    core.set_global_option("SOCC", [Na1 - Nb1])
    E1l = driver.energy('scf', dft_functional=name, molecule=molecule,
                        banner='IP Fitting SCF: Cation, Left Endpoint', **kwargs)
    core.IO.change_file_namespace(180, "ot", "cation")

    IPl = E1l - E0l
    kIPl = -E_HOMOl
    delta_l = IPl - kIPl

    if IPl < kIPl:
        raise ValidationError("""\n***IP Fitting Error: Left Omega limit should have kIP < IP: {} !< {}""".format(kIPl, IPl))

    omegas.append(omega_l)
    types.append('Left Limit')
    E0s.append(E0l)
    E1s.append(E1l)
    IPs.append(IPl)
    kIPs.append(kIPl)

    converged = False
    repeat_l = 0
    repeat_r = 0
    for step in range(maxiter):

        # Regula Falsi (modified)
        if repeat_l > 1:
            delta_l /= 2.0
        if repeat_r > 1:
            delta_r /= 2.0
        omega = - (omega_r - omega_l) / (delta_r - delta_l) * delta_l + omega_l
        core.set_local_option('SCF', 'DFT_OMEGA', omega)

        # Neutral
        core.IO.change_file_namespace(180, "neutral", "ot")
        molecule.set_molecular_charge(charge0)
        molecule.set_multiplicity(mult0)
        core.set_global_option("DOCC", [Nb])
        core.set_global_option("SOCC", [Na - Nb])
        E0, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
                                banner='IP Fitting SCF: Neutral, Omega = {:11.3E}'.format(omega), **kwargs)
        eps_a = wfn.epsilon_a()
        eps_b = wfn.epsilon_b()
        if Nb == 0:
            E_HOMO = eps_a.np[int(Na - 1)]
        else:
            E_a = eps_a.np[int(Na - 1)]
            E_b = eps_b.np[int(Nb - 1)]
            E_HOMO = max(E_a, E_b)
        core.IO.change_file_namespace(180, "ot", "neutral")

        # Cation
        core.IO.change_file_namespace(180, "cation", "ot")
        molecule.set_molecular_charge(charge1)
        molecule.set_multiplicity(mult1)
        core.set_global_option("DOCC", [Nb1])
        core.set_global_option("SOCC", [Na1 - Nb1])
        E1 = driver.energy('scf', dft_functional=name, molecule=molecule,
                           banner='IP Fitting SCF: Cation, Omega = {:11.3E}'.format(omega), **kwargs)
        core.IO.change_file_namespace(180, "ot", "cation")

        IP = E1 - E0
        kIP = -E_HOMO
        delta = IP - kIP

        if kIP > IP:
            omega_r = omega
            E0r = E0
            E1r = E1
            IPr = IP
            kIPr = kIP
            delta_r = delta
            repeat_r = 0
            repeat_l += 1
        else:
            omega_l = omega
            E0l = E0
            E1l = E1
            IPl = IP
            kIPl = kIP
            delta_l = delta
            repeat_l = 0
            repeat_r += 1

        omegas.append(omega)
        types.append('Regula-Falsi')
        E0s.append(E0)
        E1s.append(E1)
        IPs.append(IP)
        kIPs.append(kIP)

        # Termination
        if abs(omega_l - omega_r) < omega_convergence:
            converged = True
            break

    core.IO.set_default_namespace("")
    core.print_out("""\n    ==> IP Fitting Results <==\n\n""")

    core.print_out("""     => Occupation Determination <= \n\n""")
    core.print_out("""              %6s %6s %6s %6s %6s %6s\n""" % ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
    core.print_out("""     Neutral: %6d %6d %6d %6d %6d %6d\n""" % (N, Na, Nb, charge0, mult0, H**O))
    core.print_out("""     Cation:  %6d %6d %6d %6d %6d\n\n""" % (N - 1, Na1, Nb1, charge1, mult1))

    core.print_out("""     => Regula Falsi Iterations <=\n\n""")
    core.print_out("""    %3s %11s %14s %14s %14s %s\n""" % ('N','Omega','IP','kIP','Delta','Type'))
    for k in range(len(omegas)):
        core.print_out("""    %3d %11.3E %14.6E %14.6E %14.6E %s\n""" %
                       (k + 1, omegas[k], IPs[k], kIPs[k], IPs[k] - kIPs[k], types[k]))

    optstash.restore()
    if converged:
        core.print_out("""\n    IP Fitting Converged\n""")
        core.print_out("""    Final omega = %14.6E\n""" % ((omega_l + omega_r) / 2))
        core.print_out("""\n    "M,I. does the dying. Fleet just does the flying."\n""")
        core.print_out("""            -Starship Troopers\n""")

    else:
        raise ConvergenceError("""IP Fitting """, step + 1)

    return ((omega_l + omega_r) / 2)