Esempio n. 1
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 def testEqualGeom(self):
     """
     Test the algorithm to verify if two geometries are identical
     considering a bond-length cutoff of 10%
     """
     bond = [[0, 1, 1, 1],
             [1, 0, 1, 0],
             [1, 1, 0, 0],
             [1, 0, 0, 0]]
     geom1 = np.array([[0., 0., 0.],
                       [1., 0., 0.],
                       [-1., 0., 0.],
                       [0., 2., 0.]])
     geom2 = np.array([[0., 0., 0.],
                       [1.09, 0., 0.],
                       [-1., 0., 0.],
                       [0., 2., 0.]])
     geom3 = np.array([[0., 0., 0.],
                       [1.11, 0., 0.],
                       [-1., 0., 0.],
                       [0., 2., 0.]])
     warn = 'Verifying if two geometries are equal failed'
     equal = geometry.equal_geom(bond, geom1, geom2, 0.1)
     self.assertTrue(equal, warn)
     equal = geometry.equal_geom(bond, geom1, geom3, 0.1)
     self.assertFalse(equal, warn)
Esempio n. 2
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 def test_hir(self):
     for rotor in range(len(self.species.dihed)):
         for ai in range(self.nrotation):
             if self.hir_status[rotor][ai] == -1:
                 if self.species.wellorts:
                     job = 'hir/' + self.species.name + '_hir_' + str(rotor) + '_' + str(ai).zfill(2)
                 else:
                     job = 'hir/' + str(self.species.chemid) + '_hir_' + str(rotor) + '_' + str(ai).zfill(2)
                 err, geom = self.qc.get_qc_geom(job, self.species.natom)
                 if err == 1:  # still running
                     continue
                 elif err == -1:  # failed
                     self.hir_status[rotor][ai] = 1
                     self.hir_energies[rotor][ai] = -1
                     self.hir_geoms[rotor][ai] = geom
                 else:
                     # check if all the bond lenghts are within
                     # 15% or the original bond lengths
                     if geometry.equal_geom(self.species.bond,
                                            self.species.geom,
                                            geom,
                                            0.15):
                         err, energy = self.qc.get_qc_energy(job)
                         self.hir_status[rotor][ai] = 0
                         self.hir_energies[rotor][ai] = energy
                         self.hir_geoms[rotor][ai] = geom
                     else:
                         logging.warning("GEOMETRY OPTIMIZATION FAILED - STRUCTURES DIFFER FOR  " + job)
                         self.hir_status[rotor][ai] = 1
                         self.hir_energies[rotor][ai] = -1
                         self.hir_geoms[rotor][ai] = geom
     return 0
Esempio n. 3
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 def test_hir(self):
     for rotor in range(len(self.species.dihed)):
         for ai in range(self.nrotation):
             if self.hir_status[rotor][ai] == -1:
                 if self.species.wellorts:
                     job = 'hir/' + self.species.name + '_hir_' + str(rotor) + '_' + str(ai).zfill(2)
                 else:
                     job = 'hir/' + str(self.species.chemid) + '_hir_' + str(rotor) + '_' + str(ai).zfill(2)
                 err, geom = self.qc.get_qc_geom(job, self.species.natom)
                 if err == 1:  # still running
                     continue
                 elif err == -1:  # failed
                     self.hir_status[rotor][ai] = 1
                     self.hir_energies[rotor][ai] = -1
                     self.hir_geoms[rotor][ai] = geom
                 else:
                     # check if all the bond lenghts are within
                     # 15% or the original bond lengths
                     if geometry.equal_geom(self.species.bond,
                                            self.species.geom,
                                            geom,
                                            0.15):
                         err, energy = self.qc.get_qc_energy(job)
                         self.hir_status[rotor][ai] = 0
                         self.hir_energies[rotor][ai] = energy
                         self.hir_geoms[rotor][ai] = geom
                     else:
                         self.hir_status[rotor][ai] = 1
                         self.hir_energies[rotor][ai] = -1
                         self.hir_geoms[rotor][ai] = geom
     return 0
Esempio n. 4
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    def test_conformer(self, conf):
        """
        Test whether a conformer has the same bond matrix as the original structure.
        Returns the conformer object and -1 if not yet finished, 0 if same, and 1 if not.
        """
        add = ''
        if self.semi_emp:
            add = 'semi_emp_'
        job = self.get_job_name(conf, add=add)

        status, geom = self.qc.get_qc_geom(job, self.species.natom)
        if status == 1:  # still running
            return np.zeros((self.species.natom, 3)), -1
        elif status == -1:  # conformer search failed
            return np.zeros((self.species.natom, 3)), 1
        else:
            # check if all the bond lenghts are withing 10% of the original bond lengths
            temp = StationaryPoint('temp',
                                   self.species.charge,
                                   self.species.mult,
                                   atom=self.species.atom,
                                   geom=geom)
            temp.bond_mx()
            if geometry.equal_geom(self.species, temp, 0.10):
                return geom, 0
            else:
                return np.zeros((self.species.natom, 3)), 1
Esempio n. 5
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    def test_ring_conformer(self, index):
        """
        Test whether a conformer has the same bond matrix as the original structure.
        Returns the conformer object and -1 if not yet finished, 0 if same, and 1 if not.
        """
        if self.species.wellorts:
            job = 'conf/' + self.species.name + '_r' + str(index).zfill(self.zf) + '_' + str(self.cyc_conf_index[index]).zfill(self.zf)
        else:
            job = 'conf/' + str(self.species.chemid) + '_r' + str(index).zfill(self.zf) + '_' + str(self.cyc_conf_index[index]).zfill(self.zf)

        status, geom = self.qc.get_qc_geom(job, self.species.natom)
        if status == 1:  # still running
            return np.zeros((self.species.natom, 3)), -1
        elif status == -1:  # conformer search failed
            logging.debug('Conformer search failed for scan point {}'.format(job))
            return np.zeros((self.species.natom, 3)), 1
        else:
            if self.start_ring_conformer_search(index, geom):
                logging.debug('Running the next dihedral for conformer {}'.format(job))
                return geom, -1
            else:
                # check if all the bond lenghts are withing 10% or the original bond lengths
                if geometry.equal_geom(self.species.bond, self.species.geom, geom, 0.10):
                    logging.debug('Successfullly finished conformer {}'.format(job))
                    return geom, 0
                else:
                    logging.debug('Conformer too far from original structure {}'.format(job))
                    return np.zeros((self.species.natom, 3)), 1
Esempio n. 6
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    def test_hir(self):
        for rotor in range(len(self.species.dihed)):
            for ai in range(self.nrotation):
                success = None
                if self.hir_status[rotor][ai] == -1:
                    if self.species.wellorts:
                        job = 'hir/' + self.species.name + '_hir_' + str(
                            rotor) + '_' + str(ai).zfill(2)
                    else:
                        job = 'hir/' + str(
                            self.species.chemid) + '_hir_' + str(
                                rotor) + '_' + str(ai).zfill(2)
                    err, geom = self.qc.get_qc_geom(job, self.species.natom)
                    if err == 1:  # still running
                        continue
                    elif err == -1:  # failed
                        success = -1
                    else:
                        # check if all the bond lenghts are within
                        # 15% or the original bond lengths
                        temp = StationaryPoint('temp',
                                               self.species.charge,
                                               self.species.mult,
                                               atom=self.species.atom,
                                               geom=geom)
                        temp.bond_mx()
                        if geometry.equal_geom(self.species, temp, 0.15):
                            err, energy = self.qc.get_qc_energy(job)
                            if ai == 0:
                                success = 1
                            # cut off barriers above 20 kcal/mol to prevent the Fourier fit to oscillate
                            elif (energy - self.hir_energies[rotor][0]
                                  ) < 20. / constants.AUtoKCAL:
                                success = 1
                            else:
                                success = -1
                        else:
                            success = -1
                if success == 1:
                    err, energy = self.qc.get_qc_energy(job)
                    self.hir_status[rotor][ai] = 0
                    self.hir_energies[rotor][ai] = energy
                    self.hir_geoms[rotor][ai] = geom
                elif success == -1:
                    logging.warning(
                        "Hindered rotor optimization not successful for {}".
                        format(job))
                    self.hir_status[rotor][ai] = 1
                    self.hir_energies[rotor][ai] = -1
                    self.hir_geoms[rotor][ai] = geom

        return 0
Esempio n. 7
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    def test_conformer(self, conf):
        """
        Test whether a conformer has the same bond matrix as the original structure.
        Returns the conformer object and -1 if not yet finished, 0 if same, and 1 if not.
        """
        if self.species.wellorts:
            job = 'conf/' + self.species.name + '_' + str(conf).zfill(self.zf)
        else:
            job = 'conf/' + str(self.species.chemid) + '_' + str(conf).zfill(self.zf)

        status, geom = self.qc.get_qc_geom(job, self.species.natom)
        if status == 1:  # still running
            return np.zeros((self.species.natom, 3)), -1
        elif status == -1:  # conformer search failed
            return np.zeros((self.species.natom, 3)), 1
        else:
            # check if all the bond lenghts are withing 10% or the original bond lengths
            if geometry.equal_geom(self.species.bond, self.species.geom, geom, 0.10):
                return geom, 0
            else:
                return np.zeros((self.species.natom, 3)), 1
Esempio n. 8
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    def test_conformer(self, conf):
        """
        Test whether a conformer has the same bond matrix as the original structure.
        Returns the conformer object and -1 if not yet finished, 0 if same, and 1 if not.
        """
        if self.species.wellorts:
            job = 'conf/' + self.species.name + '_' + str(conf).zfill(self.zf)
        else:
            job = 'conf/' + str(self.species.chemid) + '_' + str(conf).zfill(
                self.zf)

        status, geom = self.qc.get_qc_geom(job, self.species.natom)
        if status == 1:  # still running
            return np.zeros((self.species.natom, 3)), -1
        elif status == -1:  # conformer search failed
            return np.zeros((self.species.natom, 3)), 1
        else:
            # check if all the bond lenghts are withing 10% or the original bond lengths
            if geometry.equal_geom(self.species.bond, self.species.geom, geom,
                                   0.10):
                return geom, 0
            else:
                return np.zeros((self.species.natom, 3)), 1
Esempio n. 9
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    def test_ring_conformer(self, index):
        """
        Test whether a conformer has the same bond matrix as the original structure.
        Returns the conformer object and -1 if not yet finished, 0 if same, and 1 if not.
        """
        job = self.get_job_name(index, cyc=1)

        status, geom = self.qc.get_qc_geom(job, self.species.natom)
        if status == 1:  # still running
            return np.zeros((self.species.natom, 3)), -1
        elif status == -1:  # conformer search failed
            logging.debug(
                'Conformer search failed for scan point {}'.format(job))
            return np.zeros((self.species.natom, 3)), 1
        else:
            if self.start_ring_conformer_search(index, geom):
                logging.debug(
                    'Running the next dihedral for conformer {}'.format(job))
                return geom, -1
            else:
                # check if all the bond lenghts are withing 10% or the original bond lengths
                temp = StationaryPoint('temp',
                                       self.species.charge,
                                       self.species.mult,
                                       atom=self.species.atom,
                                       geom=geom)
                temp.bond_mx()
                if geometry.equal_geom(self.species, temp, 0.10):
                    logging.debug(
                        'Successfullly finished conformer {}'.format(job))
                    return geom, 0
                else:
                    logging.debug(
                        'Conformer too far from original structure {}'.format(
                            job))
                    return np.zeros((self.species.natom, 3)), 1
Esempio n. 10
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    def test_ring_conformer(self, index):
        """
        Test whether a conformer has the same bond matrix as the original structure.
        Returns the conformer object and -1 if not yet finished, 0 if same, and 1 if not.
        """
        if self.species.wellorts:
            job = 'conf/' + self.species.name + '_r' + str(index).zfill(
                self.zf) + '_' + str(self.cyc_conf_index[index]).zfill(self.zf)
        else:
            job = 'conf/' + str(self.species.chemid) + '_r' + str(index).zfill(
                self.zf) + '_' + str(self.cyc_conf_index[index]).zfill(self.zf)

        status, geom = self.qc.get_qc_geom(job, self.species.natom)
        if status == 1:  # still running
            return np.zeros((self.species.natom, 3)), -1
        elif status == -1:  # conformer search failed
            logging.debug(
                'Conformer search failed for scan point {}'.format(job))
            return np.zeros((self.species.natom, 3)), 1
        else:
            if self.start_ring_conformer_search(index, geom):
                logging.debug(
                    'Running the next dihedral for conformer {}'.format(job))
                return geom, -1
            else:
                # check if all the bond lenghts are withing 10% or the original bond lengths
                if geometry.equal_geom(self.species.bond, self.species.geom,
                                       geom, 0.10):
                    logging.debug(
                        'Successfullly finished conformer {}'.format(job))
                    return geom, 0
                else:
                    logging.debug(
                        'Conformer too far from original structure {}'.format(
                            job))
                    return np.zeros((self.species.natom, 3)), 1
Esempio n. 11
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    def do_optimization(self):
        while 1:
            # do the conformational search
            if self.par.par['conformer_search'] == 1:
                if self.scycconf == -1 and self.sconf == -1:
                    # conformational analysis has to be started
                    logging.info(
                        '\tStarting conformational search of {}'.format(
                            self.species.name))
                    self.species.confs = Conformers(self.species, self.par,
                                                    self.qc)

                # first do the cyclic part of the molecule
                if self.scycconf == -1:
                    # start the ring conf search
                    if len(self.species.cycle_chain) > 0:
                        # there are rings in the molecule, do a search
                        self.species.confs.generate_ring_conformers(
                            copy.deepcopy(self.species.geom))
                        # set the cyclic conf status to running
                        self.scycconf = 0
                    else:
                        # there are no rings in the molecule, continue from the current geometry
                        self.species.confs.cyc_conf_geoms = [
                            copy.deepcopy(self.species.geom)
                        ]
                        # no ring conf search has to be done, set status to finished
                        self.scycconf = 1
                if self.scycconf == 0:
                    # ring conf search is running, check if finished
                    status, self.species.confs.cyc_conf_geoms = self.species.confs.check_ring_conformers(
                    )
                    if status:
                        # ring conf search is finished
                        self.scycconf = 1
                # do the open chain par of the molecule
                if self.scycconf == 1:
                    # do open chain part if cyclic part is done
                    if self.sconf == -1:
                        # open chain part has not started yet
                        for geom in self.species.confs.cyc_conf_geoms:
                            # take all the geometries from the cyclic part
                            # generate the conformers for the current geometry
                            self.species.confs.generate_conformers(0, geom)
                        # set conf status to running
                        self.sconf = 0
                    if self.sconf == 0:
                        # conformational search is running
                        # check if the conformational search is done
                        status, geom, low_energy = self.species.confs.check_conformers(
                            wait=self.wait)

                        #print('{0} {1}'.format(status, low_energy))
                        if status == 1:
                            #    cfi=open("conf_energies.txt", 'a')
                            #    cfi.write(self.species.name)
                            #    cfi.write(": Initial E: {0}".format(self.species.energy))
                            # conf search is done
                            # save lowest energy conformer as species geometry
                            self.species.geom = geom
                            # save lowest energy conformer energy
                            self.species.energy = low_energy
                            #    cfi.write(", Final E: {0}\n".format(self.species.energy))
                            #    cfi.close()

                            # set conf status to finished
                            self.sconf = 1

            else:
                # no conf search necessary, set status to finished
                self.sconf = 1
            if self.sconf == 1:  # conf search is finished
                while self.restart < self.max_restart:
                    # do the high level calculations
                    if self.par.par['high_level'] == 1:
                        if self.shigh == -1:
                            # high level calculation did not start yet
                            logging.info(
                                '\tStarting high level optimization of {}'.
                                format(self.species.name))
                            if self.species.wellorts:
                                # do the high level optimization of a ts
                                self.qc.qc_opt_ts(self.species,
                                                  self.species.geom,
                                                  high_level=1)
                            else:
                                # do the high level optimization of a well
                                self.qc.qc_opt(self.species,
                                               self.species.geom,
                                               high_level=1)
                            self.shigh = 0  # set the high status to running
                        if self.shigh == 0:
                            # high level calculation is running
                            # check if it is finished
                            status = self.qc.check_qc(self.job_high)
                            if status == 'error':
                                # found an error
                                logging.info(
                                    '\tHigh level optimization failed for {}'.
                                    format(self.species.name))
                                self.shigh = -999
                            if status == 'normal':
                                # finished successfully
                                err, new_geom = self.qc.get_qc_geom(
                                    self.job_high,
                                    self.species.natom,
                                    wait=self.wait)
                                if geometry.equal_geom(self.species.bond,
                                                       self.species.geom,
                                                       new_geom, 0.1):
                                    # geometry is as expected
                                    err, self.species.geom = self.qc.get_qc_geom(
                                        self.job_high, self.species.natom)
                                    err, self.species.energy = self.qc.get_qc_energy(
                                        self.job_high)
                                    err, self.species.freq = self.qc.get_qc_freq(
                                        self.job_high, self.species.natom)
                                    err, self.species.zpe = self.qc.get_qc_zpe(
                                        self.job_high)
                                    self.shigh = 1
                                else:
                                    # geometry diverged to other structure
                                    logging.info(
                                        '\tHigh level ts optimization converged to different structure for {}'
                                        .format(self.species.name))
                                    self.shigh = -999
                    else:
                        # no high-level calculations necessary, set status to finished
                        self.shigh = 1
                    if self.shigh == 1:
                        # do the HIR calculation
                        if self.par.par['rotor_scan'] == 1:
                            if self.shir == -1:
                                # hir not stated yet
                                logging.info(
                                    '\tStarting hindered rotor calculations of {}'
                                    .format(self.species.name))
                                self.species.hir = HIR(self.species, self.qc,
                                                       self.par)
                                self.species.hir.generate_hir_geoms(
                                    copy.deepcopy(self.species.geom))
                                self.shir = 0
                            if self.shir == 0:
                                # hir is running
                                # check if it is done:
                                status = self.species.hir.check_hir(
                                    wait=self.wait)
                                if status:
                                    if len(self.species.hir.hir_energies) > 0:
                                        # check if along the hir potential a structure was found with a lower energy
                                        min = self.species.hir.hir_energies[0][
                                            0]
                                        min_rotor = -1
                                        min_ai = -1
                                        for rotor in range(
                                                len(self.species.dihed)):
                                            for ai in range(self.species.hir.
                                                            nrotation):
                                                # use a 0.1kcal/mol cutoff for numerical noise
                                                if self.species.hir.hir_energies[
                                                        rotor][
                                                            ai] < min - 1.6E-4:
                                                    min = self.species.hir.hir_energies[
                                                        rotor][ai]
                                                    min_rotor = rotor
                                                    min_ai = ai
                                        if min_rotor > -1:
                                            self.restart += 1
                                            if self.restart < self.max_restart:
                                                # lower energy structure found
                                                logging.info(
                                                    '\t\tLower energy found during hindered rotor scan for {}'
                                                    .format(self.species.name))
                                                logging.info(
                                                    '\t\tRestart number: ' +
                                                    str(self.restart))
                                                logging.info('\t\tRotor: ' +
                                                             str(min_rotor))
                                                logging.info(
                                                    '\t\tScan point: ' +
                                                    str(min_ai))
                                                job = self.job_hir + str(
                                                    min_rotor) + '_' + str(
                                                        min_ai).zfill(2)

                                                err, self.species.geom = self.qc.get_qc_geom(
                                                    job, self.species.natom)
                                                # delete the high_level log file and the hir log files
                                                if os.path.exists(
                                                        self.job_high +
                                                        '.log'):
                                                    # logging.info("\t\t\tRemoving file " + self.job_high + '.log')
                                                    os.remove(self.job_high +
                                                              '.log')
                                                for rotor in range(
                                                        len(self.species.dihed)
                                                ):
                                                    for ai in range(
                                                            self.species.hir.
                                                            nrotation):
                                                        if os.path.exists(
                                                                self.job_hir +
                                                                str(rotor) +
                                                                '_' +
                                                                str(ai).zfill(
                                                                    2) +
                                                                '.log'):
                                                            # logging.info("\t\t\tRemoving file " + self.job_hir + str(rotor) + '_' + str(ai).zfill(2) + '.log')
                                                            os.remove(
                                                                self.job_hir +
                                                                str(rotor) +
                                                                '_' +
                                                                str(ai).zfill(
                                                                    2) +
                                                                '.log')
                                                # set the status of high and hir back to not started
                                                self.shigh = -1
                                                self.shir = -1
                                            else:
                                                logging.info(
                                                    '\t\tLower energy found, but readched max restart for {}'
                                                    .format(self.species.name))
                                                self.shir = 1
                                        else:
                                            self.shir = 1
                                    else:
                                        self.shir = 1
                        else:
                            # no hir calculations necessary, set status to finished
                            self.shir = 1
                    if not self.wait or self.shir == 1 or self.shigh == -999:
                        # break the loop if no waiting is required or
                        # if the hir calcs are done or
                        # if the high level calc failed
                        break
                    else:
                        time.sleep(1)
            if self.shir == 1:
                # finilize if no waiting is required or if the hir calcs are done
                # calculate the symmetry numbers
                symmetry.calculate_symmetry(self.species)

                # calculate the new frequencies with the internal rotations projected out
                fr_file = self.species.name
                if not self.species.wellorts:
                    fr_file += '_well'
                if self.par.par['high_level']:
                    fr_file += '_high'
                hess = self.qc.read_qc_hess(fr_file, self.species.natom)
                self.species.kinbot_freqs, self.species.reduced_freqs = frequencies.get_frequencies(
                    self.species, hess, self.species.geom)

                # write the molpro input and read the molpro energy, if available
                if self.par.par['single_point_qc'] == 'molpro':
                    molp = Molpro(self.species, self.par)
                    molp.create_molpro_input()
                    molp.create_molpro_submit()
                    status, molpro_energy = molp.get_molpro_energy()
                    if status:
                        self.species.energy = molpro_energy

                # delete unnecessary files
                if self.par.par['delete_intermediate_files'] == 1:
                    self.delete_files()
            if self.wait:
                if self.shir == 1 or self.shigh == -999:
                    return 0
                time.sleep(1)
            else:
                return 0
Esempio n. 12
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    def do_optimization(self):
        while 1:
            # do the conformational search
            if self.par.par['conformer_search'] == 1:
                if self.scycconf == -1 and self.sconf == -1:
                    # conformational analysis has to be started
                    logging.info('\tStarting conformational search of {}'.format(self.species.name))
                    self.species.confs = Conformers(self.species, self.par, self.qc)

                # first do the cyclic part of the molecule
                if self.scycconf == -1:
                    # start the ring conf search
                    if len(self.species.cycle_chain) > 0:
                        # there are rings in the molecule, do a search
                        self.species.confs.generate_ring_conformers(copy.deepcopy(self.species.geom))
                        # set the cyclic conf status to running
                        self.scycconf = 0
                    else:
                        # there are no rings in the molecule, continue from the current geometry
                        self.species.confs.cyc_conf_geoms = [copy.deepcopy(self.species.geom)]
                        # no ring conf search has to be done, set status to finished
                        self.scycconf = 1
                if self.scycconf == 0:
                    # ring conf search is running, check if finished
                    status, self.species.confs.cyc_conf_geoms = self.species.confs.check_ring_conformers()
                    if status:
                        # ring conf search is finished
                        self.scycconf = 1
                # do the open chain par of the molecule
                if self.scycconf == 1:
                    # do open chain part if cyclic part is done
                    if self.sconf == -1:
                        # open chain part has not started yet
                        for geom in self.species.confs.cyc_conf_geoms:
                            # take all the geometries from the cyclic part
                            # generate the conformers for the current geometry
                            self.species.confs.generate_conformers(0, geom)
                        # set conf status to running
                        self.sconf = 0
                    if self.sconf == 0:
                        # conformational search is running
                        # check if the conformational search is done
                        status, geom = self.species.confs.check_conformers(wait=self.wait)
                        if status == 1:
                            # conf search is done
                            # save lowest energy conformer as species geometry
                            self.species.geom = geom
                            # set conf status to finished
                            self.sconf = 1
            else:
                # no conf search necessary, set status to finished
                self.sconf = 1
            if self.sconf == 1:  # conf search is finished
                while self.restart < self.max_restart:
                    # do the high level calculations
                    if self.par.par['high_level'] == 1:
                        if self.shigh == -1:
                            # high level calculation did not start yet
                            logging.info('\tStarting high level optimization of {}'.format(self.species.name))
                            if self.species.wellorts:
                                # do the high level optimization of a ts
                                self.qc.qc_opt_ts(self.species, self.species.geom, high_level=1)
                            else:
                                # do the high level optimization of a well
                                self.qc.qc_opt(self.species, self.species.geom, high_level=1)
                            self.shigh = 0  # set the high status to running
                        if self.shigh == 0:
                            # high level calculation is running
                            # check if it is finished
                            status = self.qc.check_qc(self.job_high)
                            if status == 'error':
                                # found an error
                                logging.info('\tHigh level optimization failed for {}'.format(self.species.name))
                                self.shigh = -999
                            if status == 'normal':
                                # finished successfully
                                err, new_geom = self.qc.get_qc_geom(self.job_high, self.species.natom, wait=self.wait)
                                if geometry.equal_geom(self.species.bond, self.species.geom, new_geom, 0.1):
                                    # geometry is as expected
                                    err, self.species.geom = self.qc.get_qc_geom(self.job_high, self.species.natom)
                                    err, self.species.energy = self.qc.get_qc_energy(self.job_high)
                                    err, self.species.freq = self.qc.get_qc_freq(self.job_high, self.species.natom)
                                    err, self.species.zpe = self.qc.get_qc_zpe(self.job_high)
                                    self.shigh = 1
                                else:
                                    # geometry diverged to other structure
                                    logging.info('\tHigh level ts optimization converged to different structure for {}'.format(self.species.name))
                                    self.shigh = -999
                    else:
                        # no high-level calculations necessary, set status to finished
                        self.shigh = 1
                    if self.shigh == 1:
                        # do the HIR calculation
                        if self.par.par['rotor_scan'] == 1:
                            if self.shir == -1:
                                # hir not stated yet
                                logging.info('\tStarting hindered rotor calculations of {}'.format(self.species.name))
                                self.species.hir = HIR(self.species, self.qc, self.par)
                                self.species.hir.generate_hir_geoms(copy.deepcopy(self.species.geom))
                                self.shir = 0
                            if self.shir == 0:
                                # hir is running
                                # check if it is done:
                                status = self.species.hir.check_hir(wait=self.wait)
                                if status:
                                    if len(self.species.hir.hir_energies) > 0:
                                        # check if along the hir potential a structure was found with a lower energy
                                        min = self.species.hir.hir_energies[0][0]
                                        min_rotor = -1
                                        min_ai = -1
                                        for rotor in range(len(self.species.dihed)):
                                            for ai in range(self.species.hir.nrotation):
                                                # use a 0.1kcal/mol cutoff for numerical noise
                                                if self.species.hir.hir_energies[rotor][ai] < min - 1.6E-4:
                                                    min = self.species.hir.hir_energies[rotor][ai]
                                                    min_rotor = rotor
                                                    min_ai = ai
                                        if min_rotor > -1:
                                            self.restart += 1
                                            if self.restart < self.max_restart:
                                                # lower energy structure found
                                                logging.info('\t\tLower energy found during hindered rotor scan for {}'.format(self.species.name))
                                                logging.info('\t\tRestart number: ' + str(self.restart))
                                                logging.info('\t\tRotor: ' + str(min_rotor))
                                                logging.info('\t\tScan point: ' + str(min_ai))
                                                job = self.job_hir + str(min_rotor) + '_' + str(min_ai).zfill(2)

                                                err, self.species.geom = self.qc.get_qc_geom(job, self.species.natom)
                                                # delete the high_level log file and the hir log files
                                                if os.path.exists(self.job_high + '.log'):
                                                    # logging.info("\t\t\tRemoving file " + self.job_high + '.log')
                                                    os.remove(self.job_high + '.log')
                                                for rotor in range(len(self.species.dihed)):
                                                    for ai in range(self.species.hir.nrotation):
                                                        if os.path.exists(self.job_hir + str(rotor) + '_' + str(ai).zfill(2) + '.log'):
                                                            # logging.info("\t\t\tRemoving file " + self.job_hir + str(rotor) + '_' + str(ai).zfill(2) + '.log')
                                                            os.remove(self.job_hir + str(rotor) + '_' + str(ai).zfill(2) + '.log')
                                                # set the status of high and hir back to not started
                                                self.shigh = -1
                                                self.shir = -1
                                            else:
                                                logging.info('\t\tLower energy found, but readched max restart for {}'.format(self.species.name))
                                                self.shir = 1
                                        else:
                                            self.shir = 1
                                    else:
                                        self.shir = 1
                        else:
                            # no hir calculations necessary, set status to finished
                            self.shir = 1
                    if not self.wait or self.shir == 1 or self.shigh == -999:
                        # break the loop if no waiting is required or
                        # if the hir calcs are done or
                        # if the high level calc failed
                        break
                    else:
                        time.sleep(1)
            if self.shir == 1:
                # finilize if no waiting is required or if the hir calcs are done
                # calculate the symmetry numbers
                symmetry.calculate_symmetry(self.species)

                # calculate the new frequencies with the internal rotations projected out
                fr_file = self.species.name
                if not self.species.wellorts:
                    fr_file += '_well'
                if self.par.par['high_level']:
                        fr_file += '_high'
                hess = self.qc.read_qc_hess(fr_file, self.species.natom)
                self.species.kinbot_freqs, self.species.reduced_freqs = frequencies.get_frequencies(self.species, hess, self.species.geom)

                # write the molpro input and read the molpro energy, if available
                if self.par.par['single_point_qc'] == 'molpro':
                    molp = Molpro(self.species, self.par)
                    molp.create_molpro_input()
                    molp.create_molpro_submit()
                    status, molpro_energy = molp.get_molpro_energy()
                    if status:
                        self.species.energy = molpro_energy
                
                # delete unnecessary files
                delete = 1
                if delete:
                    self.delete_files()
            if self.wait:
                if self.shir == 1 or self.shigh == -999:
                    return 0
                time.sleep(1)
            else:
                return 0
Esempio n. 13
0
    def do_optimization(self):
        while 1:
            # do the conformational search
            if self.par['conformer_search'] == 1:
                if self.scycconf == -1 and self.sconf == -1:
                    logging.info('\tStarting conformational search of {}'.format(self.name))
                    self.species.confs = Conformers(self.species, self.par, self.qc)

                # first do the cyclic part of the molecule
                if self.scycconf == -1:
                    # start the ring conf search
                    if len(self.species.cycle_chain) > 0:
                        # there are rings in the molecule, do a search
                        self.species.confs.generate_ring_conformers(copy.deepcopy(self.species.geom))
                        # set the cyclic conf status to running
                        self.scycconf = 0
                    else:
                        # there are no rings in the molecule, continue from the current geometry
                        self.species.confs.cyc_conf_geoms = [copy.deepcopy(self.species.geom)]
                        # no ring conf search has to be done, set status to finished
                        self.scycconf = 1
                if self.scycconf == 0:
                    # ring conf search is running, check if finished
                    status, self.species.confs.cyc_conf_geoms = self.species.confs.check_ring_conformers()
                    if status:
                        # ring conf search is finished
                        self.scycconf = 1
                # first do an semi empirical optimization if requested by the user
                if self.par['semi_emp_conformer_search'] == 1:
                    logging.info('semi empirical conformer search is starting for {}'.format(self.name))
                    if self.ssemi_empconf == -1:
                        # semi empirical part has not started yet
                        self.species.semi_emp_confs = Conformers(self.species, self.par, self.qc, semi_emp=1)
                        for geom in self.species.confs.cyc_conf_geoms:
                            # take all the geometries from the cyclic part
                            # generate the conformers for the current geometry
                            self.species.semi_emp_confs.generate_conformers(0, geom)
                        # set conf status to running
                        self.ssemi_empconf = 0
                        if self.ssemi_empconf == 0:
                            # semi empirical conformational search is running
                            # check if the conformational search is done
                            status, lowest_conf, geom, self.semi_emp_low_energy, self.semi_emp_conformers, self.semi_emp_energies = self.species.semi_emp_confs.check_conformers(wait=self.wait)
                            if status == 1:
                                logging.info("semi empirical lowest energy conformer for species {} is number {}".format(self.name, lowest_conf))
                                # set conf status to finished
                                self.ssemi_empconf = 1
                else:
                    self.ssemi_empconf = 1
                if self.ssemi_empconf == 1 and self.scycconf == 1:
                    # do open chain part if cyclic (if there were any) and semi empirical (if requested) parts are done
                    if self.sconf == -1:
                        # open chain part has not started yet
                        # if semi empirical conformer were searched for, start from those, 
                        # else start from cyclic conformers
                        if self.par['semi_emp_conformer_search'] == 1:
                            self.species.confs.nconfs = 1
                            for i, geom in enumerate(self.semi_emp_conformers):
                                if (self.semi_emp_energies[i] - self.semi_emp_low_energy) * constants.AUtoKCAL < self.par['semi_emp_confomer_threshold']:
                                    self.species.confs.generate_conformers(-999, geom)
                            logging.info("There are {} structures below the {} kcal/mol threshold for species {} in the semiempirical search.". \
                                         format(i, self.par['semi_emp_confomer_threshold'], self.name))
                        else:
                            print_warning = True
                            for geom in self.species.confs.cyc_conf_geoms:
                                # take all the geometries from the cyclic part
                                # generate the conformers for the current geometry
                                self.skip_conf_check = self.species.confs.generate_conformers(0, geom, print_warning=print_warning)
                                print_warning = False
                        # set conf status to running
                        self.sconf = 0
                    if self.sconf == 0:
                        # conformational search is running
                        # check if the conformational search is done
                        if self.skip_conf_check == 0:
                            status, lowest_conf, geom, low_energy, conformers, energies = self.species.confs.check_conformers(wait=self.wait)
                            if status == 1:
                                logging.info("lowest energy conformer for species: {} is number {}".format(self.name, lowest_conf))
                                # save lowest energy conformer as species geometry
                                self.species.geom = geom
                                # save lowest energy conformer energy
                                self.species.energy = low_energy
                                # set conf status to finished
                                self.sconf = 1
                        elif self.skip_conf_check == 1:
                            self.species.geom, self.species.energy = self.species.confs.lowest_conf_info()
                            logging.info('Conformers are not checked for {} to speed up calculations.'.format(self.name))
                            logging.info('They seem to have been done in a previous run.')
                            logging.info('Energy and geometry updated based on conf/{}_low file.'.format(self.name))
                            self.sconf = 1

            else:
                # no conf search necessary, set status to finished
                self.sconf = 1
            if self.sconf == 1:  # conf search is finished
                # if the conformers were already done in a previous run
                # not clear what the purpose of these lines were
                if self.par['conformer_search'] == 1:
                    status, lowest_conf, geom, low_energy, conformers, energies = self.species.confs.check_conformers(wait=self.wait)
                        
                while self.restart <= self.max_restart:
                    # do the high level calculations
                    if self.par['high_level'] == 1:
                        if self.shigh == -1:
                            if self.species.wellorts:
                                name = self.species.name
                            else:
                                name = self.species.chemid
                            # high level calculation did not start yet
                            logging.info('\tStarting high level optimization of {}'.format(name))
                            if self.species.wellorts:
                                # do the high level optimization of a ts
                                self.qc.qc_opt_ts(self.species, self.species.geom, high_level=1)
                            else:
                                # do the high level optimization of a well
                                self.qc.qc_opt(self.species, self.species.geom, high_level=1)
                            self.shigh = 0  # set the high status to running
                        if self.shigh == 0:
                            # high level calculation is running
                            # check if it is finished
                            status = self.qc.check_qc(self.job_high)
                            if status == 'error':
                                # found an error
                                logging.info('\tHigh level optimization failed for {}'.format(self.name))
                                self.shigh = -999
                            elif status == 'normal':
                                # finished successfully
                                err, new_geom = self.qc.get_qc_geom(self.job_high, self.species.natom, wait=self.wait)
                                temp = StationaryPoint('temp',
                                                       self.species.charge,
                                                       self.species.mult,
                                                       atom=self.species.atom,
                                                       geom=new_geom)
                                temp.bond_mx()
                                if self.species.wellorts:  # for TS we need reasonable geometry agreement and normal mode correlation
                                    if self.par['conformer_search'] == 0:
                                        fr_file = self.fr_file_name(0)  # name of the original TS file
                                    else:
                                        if self.skip_conf_check == 0: 
                                            fr_file = 'conf/{}_{}'.format(self.fr_file_name(0), lowest_conf)
                                        else:
                                            fr_file = 'conf/{}_low'.format(self.fr_file_name(0))
                                    if self.qc.qc == 'gauss':
                                        imagmode = reader_gauss.read_imag_mode(fr_file, self.species.natom)
                                    fr_file = self.fr_file_name(1)
                                    if self.qc.qc == 'gauss':
                                        imagmode_high = reader_gauss.read_imag_mode(fr_file, self.species.natom)
                                    # either geom is roughly same with closely matching imaginary modes, or geometry is very close
                                    # maybe we need to do IRC at the high level as well...
                                    same_geom = ((geometry.matrix_corr(imagmode, imagmode_high) > 0.9) and \
                                            (geometry.equal_geom(self.species, temp, 0.3))) \
                                            or (geometry.equal_geom(self.species, temp, 0.15))
                                else:
                                    same_geom = geometry.equal_geom(self.species, temp, 0.1)

                                err, fr = self.qc.get_qc_freq(self.job_high, self.species.natom)
                                if self.species.natom == 1:
                                    freq_ok = 1
                                elif len(fr) == 1 and fr[0] == 0:
                                    freq_ok = 0
                                elif self.species.wellorts == 0 and fr[0] > 0.:
                                    freq_ok = 1
                                elif self.species.wellorts == 1 and fr[0] < 0. and fr[1] > 0.:
                                    freq_ok = 1
                                else:
                                    freq_ok = 0
                                if same_geom and freq_ok:
                                    # geometry is as expected and normal modes are the same for TS
                                    err, self.species.geom = self.qc.get_qc_geom(self.job_high, self.species.natom)
                                    err, self.species.energy = self.qc.get_qc_energy(self.job_high)
                                    err, self.species.freq = self.qc.get_qc_freq(self.job_high, self.species.natom)
                                    err, self.species.zpe = self.qc.get_qc_zpe(self.job_high)
                                    self.shigh = 1
                                else:
                                    # geometry diverged to other structure
                                    if not same_geom:
                                        logging.info('\tHigh level optimization converged to different structure for {}, related channels are deleted.'.format(self.name))
                                    if not freq_ok:
                                        logging.info('\tWrong number of imaginary frequencies for {}, related channels are deleted.'.format(self.name))
                                    self.shigh = -999
                              
                    else:
                        # no high-level calculations necessary, set status to finished
                        self.shigh = 1
                    if self.shigh == 1:
                        # do the HIR calculation
                        if self.par['rotor_scan'] == 1:
                            if self.shir == -1:
                                # hir not stated yet
                                logging.info('\tStarting hindered rotor calculations of {}'.format(self.name))
                                self.species.hir = HIR(self.species, self.qc, self.par)
                                self.species.hir.generate_hir_geoms(copy.deepcopy(self.species.geom), self.par['rigid_hir'])
                                self.shir = 0
                            if self.shir == 0:
                                # hir is running
                                # check if it is done:
                                status = self.species.hir.check_hir(wait=self.wait)
                                if status:
                                    if len(self.species.hir.hir_energies) > 0:
                                        # check if along the hir potential a structure was found with a lower energy
                                        min = self.species.hir.hir_energies[0][0]
                                        min_rotor = -1
                                        min_ai = -1
                                        for rotor in range(len(self.species.dihed)):
                                            for ai in range(self.species.hir.nrotation):
                                                # use a 0.1kcal/mol cutoff for numerical noise
                                                if self.species.hir.hir_energies[rotor][ai] < min - 1.6E-4:
                                                    min = self.species.hir.hir_energies[rotor][ai]
                                                    min_rotor = rotor
                                                    min_ai = ai
                                        if min_rotor > -1:
                                            self.restart += 1
                                            if self.restart < self.max_restart:
                                                # lower energy structure found
                                                logging.info('\t\tLower energy found during hindered rotor scan for {}'.format(self.name))
                                                logging.info('\t\tRestart number: ' + str(self.restart))
                                                logging.info('\t\tRotor: ' + str(min_rotor))
                                                logging.info('\t\tScan point: ' + str(min_ai))
                                                job = self.job_hir + str(min_rotor) + '_' + str(min_ai).zfill(2)

                                                err, self.species.geom = self.qc.get_qc_geom(job, self.species.natom)
                                                # delete the high_level log file and the hir log files
                                                if os.path.exists(self.job_high + '.log'):
                                                    # logging.info("\t\t\tRemoving file " + self.job_high + '.log')
                                                    os.remove(self.job_high + '.log')
                                                for rotor in range(len(self.species.dihed)):
                                                    for ai in range(self.species.hir.nrotation):
                                                        if os.path.exists(self.job_hir + str(rotor) + '_' + str(ai).zfill(2) + '.log'):
                                                            # logging.info("\t\t\tRemoving file " + self.job_hir + str(rotor) + '_' + str(ai).zfill(2) + '.log')
                                                            os.remove(self.job_hir + str(rotor) + '_' + str(ai).zfill(2) + '.log')
                                                # set the status of high and hir back to not started
                                                self.shigh = -1
                                                self.shir = -1
                                            else:
                                                logging.info('\t\tLower energy found, but readched max restart for {}'.format(self.name))
                                                self.shir = 1
                                        else:
                                            self.shir = 1
                                    else:
                                        self.shir = 1
                        else:
                            # no hir calculations necessary, set status to finished
                            self.shir = 1
                    if not self.wait or self.shir == 1 or self.shigh == -999:
                        # break the loop if no waiting is required or
                        # if the hir calcs are done or
                        # if the high level calc failed
                        break
                    else:
                        time.sleep(1)
            if self.shir == 1:
                # finalize if no waiting is required or if the hir calcs are done
                # calculate the symmetry numbers
                symmetry.calculate_symmetry(self.species)

                # calculate the new frequencies with the internal rotations projected out
                fr_file = self.name
                if not self.species.wellorts:
                    fr_file += '_well'
                if self.par['high_level']:
                    fr_file += '_high'
                fr_file = self.fr_file_name(self.par['high_level'])
                hess = self.qc.read_qc_hess(fr_file, self.species.natom)
                self.species.kinbot_freqs, self.species.reduced_freqs = frequencies.get_frequencies(self.species, hess, self.species.geom)

                # write the molpro input and read the molpro energy, if available
                if self.par['L3_calc'] == 1:
                    if self.par['single_point_qc'] == 'molpro':
                        molp = Molpro(self.species, self.par)
                        if 'barrierless_saddle' in self.name:
                            key = self.par['barrierless_saddle_single_point_key']
                            molp.create_molpro_input(bls=1)
                        else:
                            key = self.par['single_point_key']
                            molp.create_molpro_input()
                        molp.create_molpro_submit()
                        status, molpro_energy = molp.get_molpro_energy(key)

                        # FIXME this might be wrong here:
                        if status:
                            self.species.energy = molpro_energy

                    self.delete_files()

            if self.wait:
                if self.shir == 1 or self.shigh == -999:
                    return 0
                time.sleep(1)
            else:
                return 0