diff --git a/atomate/common/powerups.py b/atomate/common/powerups.py index c71667075..1e103d40d 100644 --- a/atomate/common/powerups.py +++ b/atomate/common/powerups.py @@ -1,6 +1,7 @@ """ This module defines general powerups that can be used for all workflows """ +from typing import Dict, Any, Optional from importlib import import_module from typing import List @@ -8,7 +9,7 @@ from fireworks import Workflow, FileWriteTask from fireworks.utilities.fw_utilities import get_slug -__author__ = "Janine George, Guido Petretto, Ryan Kingsbury" +__author__ = "Janine George, Guido Petretto, Ryan Kingsbury, Alex Ganose" __email__ = ( "janine.george@uclouvain.be, guido.petretto@uclouvain.be, RKingsbury@lbl.gov" ) @@ -190,20 +191,55 @@ def set_execution_options( return original_wf +def update_firetask( + original_wf: Workflow, + update_params: Dict[str, Any], + task_name_constraint: str, + fw_name_constraint: Optional[str] = None, +) -> Workflow: + """ + General powerup for arbitrary updates to a Firetask. + + Args: + original_wf: The original workflow. + update_params: A dictionary of the keyword arguments to update. + task_name_constraint: Only apply changes to the Firetasks where the + Firetask class name contains this string. + fw_name_constraint: Only apply changes to Fireworks where the Firework + name contains this substring. + + Returns: + Workflow + """ + idx_list = get_fws_and_tasks( + original_wf, + fw_name_constraint=fw_name_constraint, + task_name_constraint=task_name_constraint, + ) + for idx_fw, idx_t in idx_list: + original_wf.fws[idx_fw].tasks[idx_t].update(update_params) + + return original_wf + + def set_queue_adapter( original_wf: Workflow, queueadapter: dict = None, + fw_name_constraint: str = None, task_name_constraint: str = None, ) -> Workflow: """ - set _queueadapter spec of Fireworker(s) of a Workflow. It can be used to change the overall queueadapter during the run. + set _queueadapter spec of Fireworker(s) of a Workflow. It can be used to change the + overall queueadapter during the run. Args: original_wf (Workflow): workflow that will be changed queueadapter (dict): dict to change _queueadapter - fw_name_constraint (str): name of the Fireworks to be tagged (all if None is passed) - task_name_constraint (str): name of the Firetasks to be tagged (e.g. None or 'RunVasp') + fw_name_constraint (str): name of the Fireworks to be tagged (all if None is + passed) + task_name_constraint (str): name of the Firetasks to be tagged (e.g. None or + 'RunVasp') Returns: Workflow: modified workflow with specified Fireworkers tagged diff --git a/atomate/vasp/analysis/lattice_dynamics.py b/atomate/vasp/analysis/lattice_dynamics.py new file mode 100644 index 000000000..90b673d30 --- /dev/null +++ b/atomate/vasp/analysis/lattice_dynamics.py @@ -0,0 +1,829 @@ +from itertools import product +from joblib import Parallel, delayed +from typing import Dict, List, Tuple, Optional + +import numpy as np +import scipy as sp +import os +import psutil +from copy import copy + +from atomate.utils.utils import get_logger + +from hiphive import (ForceConstants, ForceConstantPotential, + enforce_rotational_sum_rules, ClusterSpace, + StructureContainer) +from hiphive.force_constant_model import ForceConstantModel +from hiphive.cutoffs import is_cutoff_allowed, estimate_maximum_cutoff +from hiphive.fitting import Optimizer +from hiphive.renormalization import Renormalization +from hiphive.utilities import get_displacements +from hiphive.run_tools import _clean_data, free_energy_correction, construct_fit_data + +from pymatgen.core.structure import Structure +from pymatgen.io.ase import AseAtomsAdaptor +from pymatgen.io.phonopy import get_phonopy_structure + +from ase.atoms import Atoms +from ase.cell import Cell + +from phonopy import Phonopy +from phono3py.phonon3.gruneisen import Gruneisen + + +__author__ = "Alex Ganose, Rees Chang, Junsoo Park" +__email__ = "aganose@lbl.gov, rc564@cornell.edu, jsyony37@lbl.gov" + +logger = get_logger(__name__) + +# Define some shared constants +IMAGINARY_TOL = 0.025 # in THz +MESH_DENSITY = 100.0 # should always be a float + +# Temperature for straight-up phonopy calculation of thermodynamic properties (free energy etc.) +T_QHA = [i*100 for i in range(21)] +# Temperature at which renormalization is to be performed +T_RENORM = [0,50,100,200,300,500,700,1000,1500]#[i*100 for i in range(0,16)] +# Temperature at which lattice thermal conductivity is calculated +# If renormalization is performed, T_RENORM overrides T_KLAT for lattice thermal conductivity +T_KLAT = {"t_min":100,"t_max":1500,"t_step":100} #[i*100 for i in range(0,11)] + +FIT_METHOD = "rfe" +RENORM_METHOD = 'pseudoinverse' +RENORM_NCONFIG = 5 +RENORM_CONV_THRESH = 0.1 # meV/atom +RENORM_MAX_ITER = 30 + +eV2J = sp.constants.elementary_charge +hbar = sp.constants.hbar # J-s +kB = sp.constants.Boltzmann # J/K + +def get_cutoffs(supercell_structure: Structure): + """ + Get a list of trial cutoffs based on a supercell structure for grid search. + + An initial guess for the lower bound of the cutoffs is made based on the + average period (row) of the elements in the structure, according to: + + ====== === === === + . Cutoff + ------ ----------- + Period 2ND 3RD 4TH + ====== === === === + 1 5.0 3.0 2.5 + 2 6.0 3.5 3.0 + 3 7.0 4.5 3.5 + 4 8.0 5.5 4.0 + 5 9.0 6.0 4.5 + 6 10.0 6.5 5.0 + 7 11.0 7.0 5.5 + ====== === === === + + The maximum cutoff for each order is determined by the minimum cutoff and + the following table. A full grid of all possible cutoff combinations is + generated based on the step size in the table below times a row factor + + ====== ==== ===== + Cutoff Max Step + ====== ==== ===== + 2ND +2.0 1.0 + 3RD +1.5 0.75 + 4TH +0.6 0.6 + ====== ==== ===== + + Finally, the max cutoff size is determined by the supercell lattice dimensions. + Cutoffs which result in multiple of the same orbits being populated will be + discounted. + + Args: + supercell_structure: A structure. + + Returns: + A list of trial cutoffs. + """ + # indexed as min_cutoffs[order][period] + # DO NOT CHANGE unless you know what you are doing + min_cutoffs = { + 2: {1: 5.0, 2: 6.0, 3: 7.0, 4: 8.0, 5: 9.0, 6: 10.0, 7: 11.0}, + 3: {1: 3.0, 2: 3.5, 3: 4.5, 4: 5.5, 5: 6.0, 6: 6.5, 7: 7.0}, + 4: {1: 2.5, 2: 3.0, 3: 3.5, 4: 4.0, 5: 4.5, 6: 5.0, 7: 5.5}, + } + inc = {2: 2, 3: 1.5, 4: 0.6} + steps = {2: 1, 3: 0.75, 4: 0.6} + + row = int(np.around(np.array([s.row for s in supercell_structure.species]).mean(),0)) + factor = row/4 + mins = { + 2: min_cutoffs[2][row], 3: min_cutoffs[3][row], 4: min_cutoffs[4][row] + } + + range_two = np.arange(mins[2], mins[2] + factor*(inc[2]+steps[2]), factor*steps[2]) + range_three = np.arange(mins[3], mins[3] + factor*(inc[3]+steps[3]), factor*steps[3]) + range_four = np.arange(mins[4], mins[4] + factor*(inc[4]+steps[4]), factor*steps[4]) + + cutoffs = np.array(list(map(list, product(range_two, range_three, range_four)))) + max_cutoff = estimate_maximum_cutoff(AseAtomsAdaptor.get_atoms(supercell_structure)) + cutoffs[cutoffs>max_cutoff] = max_cutoff-0.2 + logger.info('CUTOFFS \n {}'.format(cutoffs)) + logger.info('MAX_CUTOFF \n {}'.format(max_cutoff)) + good_cutoffs = np.all(cutoffs < max_cutoff-0.1, axis=1) + logger.info('GOOD CUTOFFS \n{}'.format(good_cutoffs)) + return cutoffs[good_cutoffs].tolist() + + +def fit_force_constants( + parent_structure: Structure, + supercell_matrix: np.ndarray, + structures: List["Atoms"], + all_cutoffs: List[List[float]], + disp_cut: float = 0.055, + imaginary_tol: float = IMAGINARY_TOL, + fit_method: str = FIT_METHOD, + n_jobs: int = -1, + fit_kwargs: Optional[Dict] = None +) -> Tuple["SortedForceConstants", np.ndarray, ClusterSpace, Dict]: + """ + Fit force constants using hiphive and select the optimum cutoff values. + + The optimum cutoffs will be determined according to: + 1. Number imaginary modes < ``max_n_imaginary``. + 2. Most negative imaginary frequency < ``max_imaginary_freq``. + 3. Least number of imaginary modes. + 4. Lowest free energy at 300 K. + + If criteria 1 and 2 are not satisfied, None will be returned as the + force constants. + + Args: + parent_structure: Initial input structure. + supercell_matrix: Supercell transformation matrix. + structures: A list of ase atoms objects with "forces" and + "displacements" arrays added, as required by hiPhive. + all_cutoffs: A nested list of cutoff values to trial. Each set of + cutoffs contains the radii for different orders starting with second + order. + disp_cut: determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + imaginary_tol: Tolerance used to decide if a phonon mode is imaginary, + in THz. + max_n_imaginary: Maximum number of imaginary modes allowed in the + the final fitted force constant solution. If this criteria is not + reached by any cutoff combination this FireTask will fizzle. + max_imaginary_freq: Maximum allowed imaginary frequency in the + final fitted force constant solution. If this criteria is not + reached by any cutoff combination this FireTask will fizzle. + fit_method: Method used for fitting force constants. This can be + any of the values allowed by the hiphive ``Optimizer`` class. + n_jobs: Number of processors to use for fitting coefficients. -1 means use all + processors. + fit_kwargs: Additional arguements passed to the hiphive force constant + optimizer. + + Returns: + A tuple of the best fitted force constants as a hiphive + ``SortedForceConstants`` object, array of parameters, cluster space, + and a dictionary of information on the fitting results. + """ + logger.info("Starting force constant fitting.") + + fitting_data = { + "cutoffs": [], + "rmse_test": [], + "fit_method": fit_method, + "disp_cut": disp_cut, + "imaginary_tol": imaginary_tol, +# "max_n_imaginary": max_n_imaginary, + } + + best_fit = { + "n_imaginary": np.inf, + "rmse_test": np.inf, + "cluster_space": None, + "force_constants": None, + "parameters":None, + "cutoffs": None, + } + n_cutoffs = len(all_cutoffs) + + fit_kwargs = fit_kwargs if fit_kwargs else {} + if fit_method == "rfe" and n_jobs == -1: + fit_kwargs["n_jobs"] = 1 + + cutoff_results = Parallel(n_jobs=min(os.cpu_count(),len(all_cutoffs)), backend="multiprocessing")(delayed(_run_cutoffs)( + i, cutoffs, n_cutoffs, parent_structure, structures, supercell_matrix, fit_method, + disp_cut, imaginary_tol, fit_kwargs) for i, cutoffs in enumerate(all_cutoffs)) + + logger.info('CUTOFF RESULTS \n {}'.format(cutoff_results)) + + for result in cutoff_results: + if result is None: + continue + + fitting_data["cutoffs"].append(result["cutoffs"]) + fitting_data["rmse_test"].append(result["rmse_test"]) +# fitting_data["n_imaginary"].append(result["n_imaginary"]) +# fitting_data["min_frequency"].append(result["min_frequency"]) + + if ( + result["rmse_test"] < best_fit["rmse_test"] +# and result["min_frequency"] > -np.abs(max_imaginary_freq) +# and result["n_imaginary"] <= max_n_imaginary +# and result["n_imaginary"] < best_fit["n_imaginary"] + ): + best_fit.update(result) + fitting_data["best"] = result["cutoffs"] + + logger.info("Finished fitting force constants.") + + return best_fit["force_constants"], best_fit["parameters"], best_fit["cluster_space"], fitting_data + + +def get_fit_data( + cs: ClusterSpace, + supercell: Atoms, + structures: List["Atoms"], + separate_fit: bool, + disp_cut: float, + ncut: int, + param2: np.ndarray = None +) -> "List": + """ Constructs structure container of atom-displaced supercells + Args: + cs: ClusterSpace + supercell: Atoms + Original undisplaced supercell + structures: A list of ase atoms objects with the "forces" and + "displacements" arrays included. + separate_fit: Boolean to determine whether harmonic and anharmonic fitting + are to be done separately (True) or in one shot (False) + disp_cut: if separate_fit true, determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + ncut: the parameter index where fitting separation occurs + param2: previously fit parameter array (harmonic only for now, hence 2) + + Returns: + fit_data: List[A_mat,f_vec] + """ + + saved_structures = [] + fcm = ForceConstantModel(supercell,cs) + natom = supercell.get_global_number_of_atoms() + ndim = natom*3 + nrow_all = ndim*len(saved_structures) + A_mat = np.zeros((nrow_all,cs.n_dofs)) + f_vec = np.zeros(nrow_all) + + for i, structure in enumerate(structures): + displacements = structure.get_array('displacements') + mean_displacements = np.linalg.norm(displacements,axis=1).mean() + logger.info('Mean displacements: {}'.format(mean_displacements)) + if not separate_fit: # fit all + saved_structures.append(structure) + else: # fit separately + if param2 is None: # for harmonic fitting + if mean_displacements <= disp_cut: + saved_structures.append(structure) + else: # for anharmonic fitting + if mean_displacements > disp_cut: + saved_structures.append(structure) + + fit_data_tmp = Parallel(n_jobs=min(os.cpu_count(),max(1,len(saved_structures))))(#,prefer="threads")( + delayed(construct_fit_data)(fcm,structure,s) + for s,structure in enumerate(saved_structures) + ) + for s,data in enumerate(fit_data_tmp): + logger.info('DEBUG: {}, {}'.format(s,data[0])) + A_mat[s*ndim:(s+1)*ndim] = data[0] + f_vec[s*ndim:(s+1)*ndim] = data[1] + + if param2 is not None: + f_vec -= np.dot(A_mat[:,:ncut],param2) # subtract harmonic force from total + logger.info('Fit_data dimensions: {}'.format(A_mat.shape)) + fit_data = _clean_data(A_mat,f_vec,ndim) + return fit_data + + +def _run_cutoffs( + i, + cutoffs, + n_cutoffs, + parent_structure, + structures, + supercell_matrix, + fit_method, + disp_cut, + imaginary_tol, + fit_kwargs +) -> Dict: + + logger.info( + "Testing cutoffs {} out of {}: {}".format(i+1, n_cutoffs, cutoffs) + ) + supercell_atoms = structures[0] + + if not is_cutoff_allowed(supercell_atoms, max(cutoffs)): + logger.info( + "Skipping cutoff due as it is not commensurate with supercell size" + ) + return None + + cs = ClusterSpace(supercell_atoms, cutoffs, symprec=1e-3, acoustic_sum_rules=True) + logger.debug(cs.__repr__()) + n2nd = cs.get_n_dofs_by_order(2) + nall = cs.n_dofs + + logger.info('Fitting harmonic force constants separately') + separate_fit = True +# fit_data = get_fit_data(cs, supercell_atoms, structures, separate_fit, +# disp_cut, ncut=n2nd, param2=None) + sc = get_structure_container(cs, structures, separate_fit, disp_cut, + ncut=n2nd, param2=None) + opt = Optimizer(sc.get_fit_data(), + fit_method, + [0,n2nd], + **fit_kwargs) + opt.train() + param_harmonic = opt.parameters # harmonic force constant parameters + param_tmp = np.concatenate((param_harmonic,np.zeros(cs.n_dofs-len(param_harmonic)))) + fcp = ForceConstantPotential(cs, param_tmp) + fcs = fcp.get_force_constants(supercell_atoms) + + parent_phonopy = get_phonopy_structure(parent_structure) + phonopy = Phonopy(parent_phonopy, supercell_matrix=supercell_matrix) + natom = phonopy.primitive.get_number_of_atoms() + mesh = supercell_matrix.diagonal()*2 + phonopy.set_force_constants(fcs.get_fc_array(2)) + phonopy.set_mesh(mesh,is_eigenvectors=False,is_mesh_symmetry=False) #run_mesh(is_gamma_center=True) + phonopy.run_mesh(mesh, with_eigenvectors=False, is_mesh_symmetry=False) + omega = phonopy.mesh.frequencies # THz + omega = np.sort(omega.flatten()) + imaginary = np.any(omega<-1e-3) + + if imaginary: + logger.info('Imaginary modes found! Fitting anharmonic force constants separately') +# fit_data = get_fit_data(cs, supercell_atoms, structures, separate_fit, +# disp_cut, ncut=n2nd, param2=param_harmonic) + sc = get_structure_container(cs, structures, separate_fit, disp_cut, + ncut=n2nd, param2=param_harmonic) + opt = Optimizer(sc.get_fit_data(), + fit_method, + [n2nd,nall], + **fit_kwargs) + opt.train() + param_anharmonic = opt.parameters # anharmonic force constant parameters + + parameters = np.concatenate((param_harmonic,param_anharmonic)) # combine + assert(nall==len(parameters)) + logger.info('Training complete for cutoff: {}, {}'.format(i,cutoffs)) + + else: + logger.info('No imaginary modes! Fitting all force constants in one shot') + separate_fit = False +# fit_data = get_fit_data(cs, supercell_atoms, structures, separate_fit, +# disp_cut=None, ncut=None, param2=None) + sc = get_structure_container(cs, structures, separate_fit, disp_cut=None, + ncut=None, param2=None) + opt = Optimizer(sc.get_fit_data(), + fit_method, + [0,nall], + **fit_kwargs) + opt.train() + parameters = opt.parameters + logger.info('Training complete for cutoff: {}, {}'.format(i,cutoffs)) + + logger.info('Memory use: {} %'.format(psutil.virtual_memory().percent)) + parameters = enforce_rotational_sum_rules( + cs, parameters, ["Huang", "Born-Huang"] + ) + fcp = ForceConstantPotential(cs, parameters) + fcs = fcp.get_force_constants(supercell_atoms) + logger.info('FCS generated for cutoff {}, {}'.format(i,cutoffs)) + + try: + return { + "cutoffs": cutoffs, + "rmse_test": opt.rmse_test, + "cluster_space": sc.cluster_space, + "parameters": parameters, + "force_constants": fcs + } + except Exception: + return None + + +def get_structure_container( + cs: ClusterSpace, + structures: List["Atoms"], + separate_fit: bool, + disp_cut: float, + ncut: int, + param2: np.ndarray +) -> "StructureContainer": + """ + Get a hiPhive StructureContainer from cutoffs and a list of atoms objects. + + Args: + cs: ClusterSpace + structures: A list of ase atoms objects with the "forces" and + "displacements" arrays included. + separate_fit: Boolean to determine whether harmonic and anharmonic fitting + are to be done separately (True) or in one shot (False) + disp_cut: if separate_fit true, determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + ncut: the parameter index where fitting separation occurs + param2: previously fit parameter array (harmonic only for now, hence 2) + + Returns: + A hiPhive StructureContainer. + """ + + sc = StructureContainer(cs) + saved_structures = [] + for i, structure in enumerate(structures): + displacements = structure.get_array('displacements') + mean_displacements = np.linalg.norm(displacements,axis=1).mean() + logger.info('Mean displacements: {}'.format(mean_displacements)) + if not separate_fit: # fit all + sc.add_structure(structure) + else: # fit separately + if param2 is None: # for harmonic fitting + if mean_displacements < disp_cut: + sc.add_structure(structure) + else: # for anharmonic fitting + if mean_displacements >= disp_cut: + sc.add_structure(structure) + saved_structures.append(structure) + if separate_fit and param2 is not None: # do after anharmonic fitting + A_mat = sc.get_fit_data()[0] # displacement matrix + f_vec = sc.get_fit_data()[1] # force vector + f_vec -= np.dot(A_mat[:,:ncut],param2) # subtract harmonic forces + sc.delete_all_structures() + for i, structure in enumerate(saved_structures): + natoms = structure.get_global_number_of_atoms() + ndisp = natoms*3 + structure.set_array('forces',f_vec[i*ndisp:(i+1)*ndisp].reshape(natoms,3)) + sc.add_structure(structure) + + logger.debug(sc.__repr__()) + + return sc + + +def harmonic_properties( + structure: Structure, + supercell_matrix: np.ndarray, + fcs: ForceConstants, + temperature: List, + imaginary_tol: float = IMAGINARY_TOL +) -> Tuple[Dict,Phonopy]: + """ + Uses the force constants to extract phonon properties. Used for comparing + the accuracy of force constant fits. + + Args: + structure: The parent structure. + supercell_matrix: The supercell transformation matrix. + force_constants: The force constants in numpy format. + imaginary_tol: Tolerance used to decide if a phonon mode is imaginary, + in THz. + + Returns: + A tuple of the number of imaginary modes at Gamma, the minimum phonon + frequency at Gamma, and the free energy, entropy, and heat capacity + """ + + logger.info('Evaluating harmonic properties...') + fcs2 = fcs.get_fc_array(2) + fcs3 = fcs.get_fc_array(3) + parent_phonopy = get_phonopy_structure(structure) + phonopy = Phonopy(parent_phonopy, supercell_matrix=supercell_matrix) + natom = phonopy.primitive.get_number_of_atoms() + mesh = supercell_matrix.diagonal()*2 + + phonopy.set_force_constants(fcs2) + phonopy.set_mesh(mesh,is_eigenvectors=True,is_mesh_symmetry=False) #run_mesh(is_gamma_center=True) + phonopy.run_thermal_properties(temperatures=temperature) + logger.info('Thermal properties successfully run!') + + _, free_energy, entropy, heat_capacity = phonopy.get_thermal_properties() + free_energy *= 1000/sp.constants.Avogadro/eV2J/natom # kJ/mol to eV/atom + entropy *= 1/sp.constants.Avogadro/eV2J/natom # J/K/mol to eV/K/atom + heat_capacity *= 1/sp.constants.Avogadro/eV2J/natom # J/K/mol to eV/K/atom + + freq = phonopy.mesh.frequencies # in THz + # find imaginary modes at gamma +# phonopy.run_qpoints([0, 0, 0]) +# gamma_eigs = phonopy.get_qpoints_dict()["frequencies"] + n_imaginary = int(np.sum(freq < -np.abs(imaginary_tol))) + min_freq = np.min(freq) + + if n_imaginary == 0: + logger.info('No imaginary modes!') + else: # do not calculate these if imaginary modes exist + logger.warning('Imaginary modes found!') + + if len(temperature)==1: + temperature = temperature[0] + free_energy = free_energy[0] + entropy = entropy[0] + heat_capacity = heat_capacity[0] + + return { + "temperature": temperature, + "free_energy": free_energy, + "entropy": entropy, + "heat_capacity": heat_capacity, + "n_imaginary": n_imaginary + }, phonopy + + +def anharmonic_properties( + phonopy: Phonopy, + fcs: ForceConstants, + temperature: List, + heat_capacity: np.ndarray, + n_imaginary: float, + bulk_modulus: float = None +) -> Dict: + + if n_imaginary == 0: + logger.info('Evaluating anharmonic properties...') + fcs2 = fcs.get_fc_array(2) + fcs3 = fcs.get_fc_array(3) + grun, cte, dLfrac = gruneisen(phonopy,fcs2,fcs3,temperature,heat_capacity,bulk_modulus=bulk_modulus) + else: # do not calculate these if imaginary modes exist + logger.warning('Gruneisen and thermal expansion cannot be calculated with imaginary modes. All set to 0.') + grun = np.zeros((len(temperature),3)) + cte = np.zeros((len(temperature),3)) + dLfrac = np.zeros((len(temperature),3)) + + return { + "gruneisen": grun, + "thermal_expansion": cte, + "expansion_fraction": dLfrac, + } + + +def get_total_grun( + omega: np.ndarray, + grun: np.ndarray, + kweight: np.ndarray, + T: float +) -> np.ndarray: + total = 0 + weight = 0 + nptk = omega.shape[0] + nbands = omega.shape[1] + omega = abs(omega)*1e12*2*np.pi + if T==0: + total = np.zeros((3,3)) + grun_total_diag = np.zeros(3) + else: + for i in range(nptk): + for j in range(nbands): + x = hbar*omega[i,j]/(2.0*kB*T) + dBE = (x/np.sinh(x))**2 + weight += dBE*kweight[i] + total += dBE*kweight[i]*grun[i,j] + total = total/weight + grun_total_diag = np.array([total[0,2],total[1,1],total[2,0]]) + + def percent_diff(a,b): + return abs((a-b)/b) + # This process preserves cell symmetry upon thermal expansion, i.e., it prevents + # symmetry-identical directions from inadvertently expanding by different ratios + # when/if the Gruneisen routine returns slightly different ratios for those directions + avg012 = np.mean((grun_total_diag[0],grun_total_diag[1],grun_total_diag[2])) + avg01 = np.mean((grun_total_diag[0],grun_total_diag[1])) + avg02 = np.mean((grun_total_diag[0],grun_total_diag[2])) + avg12 = np.mean((grun_total_diag[1],grun_total_diag[2])) + if percent_diff(grun_total_diag[0],avg012) < 0.1: + if percent_diff(grun_total_diag[1],avg012) < 0.1: + if percent_diff(grun_total_diag[2],avg012) < 0.1: # all siilar + grun_total_diag[0] = avg012 + grun_total_diag[1] = avg012 + grun_total_diag[2] = avg012 + elif percent_diff(grun_total_diag[2],avg02) < 0.1: # 0 and 2 similar + grun_total_diag[0] = avg02 + grun_total_diag[2] = avg02 + elif percent_diff(grun_total_diag[2],avg12) < 0.1: # 1 and 2 similar + grun_total_diag[1] = avg12 + grun_total_diag[2] = avg12 + else: + pass + elif percent_diff(grun_total_diag[1],avg01) < 0.1: # 0 and 1 similar + grun_total_diag[0] = avg01 + grun_total_diag[1] = avg01 + elif percent_diff(grun_total_diag[1],avg12) < 0.1: # 1 and 2 similar + grun_total_diag[1] = avg12 + grun_total_diag[2] = avg12 + else: + pass + elif percent_diff(grun_total_diag[0],avg01) < 0.1: # 0 and 1 similar + grun_total_diag[0] = avg01 + grun_total_diag[1] = avg01 + elif percent_diff(grun_total_diag[0],avg02) < 0.1: # 0 and 2 similar + grun_total_diag[0] = avg02 + grun_total_diag[2] = avg02 + else: # nothing similar + pass + + return grun_total_diag + + +def gruneisen( + phonopy: Phonopy, + fcs2: np.ndarray, + fcs3: np.ndarray, + temperature: List, + heat_capacity: np.ndarray, # in eV/K/atom + bulk_modulus: float = None # in GPa +) -> Tuple[List,List]: + + gruneisen = Gruneisen(fcs2,fcs3,phonopy.supercell,phonopy.primitive) + gruneisen.set_sampling_mesh(phonopy.mesh_numbers,is_gamma_center=True) + gruneisen.run() + grun = gruneisen.get_gruneisen_parameters() # (nptk,nmode,3,3) + omega = gruneisen._frequencies + qp = gruneisen._qpoints + kweight = gruneisen._weights + grun_tot = list() + for temp in temperature: + grun_tot.append(get_total_grun(omega,grun,kweight,temp)) + grun_tot = np.nan_to_num(np.array(grun_tot)) + + # linear thermal expansion coefficeint and fraction + if bulk_modulus is None: + cte = None + dLfrac = None + else: + heat_capacity *= eV2J*phonopy.primitive.get_number_of_atoms() # eV/K/atom to J/K + vol = phonopy.primitive.get_volume() +# cte = grun_tot*heat_capacity.repeat(3)/(vol/10**30)/(bulk_modulus*10**9)/3 + cte = grun_tot*heat_capacity.repeat(3).reshape(len(heat_capacity),3)/(vol/10**30)/(bulk_modulus*10**9)/3 + cte = np.nan_to_num(cte) + if len(temperature)==1: + dLfrac = cte*temperature + else: + dLfrac = thermal_expansion(temperature, cte) + logger.info('Gruneisen: \n {}'.format(grun_tot)) + logger.info('Coefficient of Thermal Expansion: \n {}'.format(cte)) + logger.info('Linear Expansion Fraction: \n {}'.format(dLfrac)) + + return grun_tot, cte, dLfrac + + +def thermal_expansion( + temperature: List, + cte: np.array, +) -> np.ndarray: + assert len(temperature)==len(cte) + if 0 not in temperature: + temperature = [0] + temperature + cte = np.array([np.array([0,0,0])] + list(cte)) + temperature = np.array(temperature) + ind = np.argsort(temperature) + temperature = temperature[ind] + cte = np.array(cte)[ind] + # linear expansion fraction + dLfrac = copy(cte) + for t in range(len(temperature)): + dLfrac[t,:] = np.trapz(cte[:t+1,:],temperature[:t+1],axis=0) + dLfrac = np.nan_to_num(dLfrac) + return dLfrac + + +def run_renormalization( + structure: Structure, + supercell_structure: Structure, + supercell_matrix: np.ndarray, + cs: ClusterSpace, + fcs: ForceConstants, + param: np.ndarray, + T: float, + nconfig: int, + renorm_method: str, + fit_method: str, + bulk_modulus: float = None, + phonopy_orig: Phonopy = None, + param_TD: np.ndarray = None, + fcs_TD: ForceConstants = None, + imaginary_tol: float = IMAGINARY_TOL, +) -> Dict: + """ + Uses the force constants to extract phonon properties. Used for comparing + the accuracy of force constant fits. + + Args: + structure: pymatgen Structure + The parent structure. + supercell : ase Atoms + Original supercell object + supercell_matrix: The supercell transformation matrix. + fcs: ForceConstants from previous fitting or renormalization + imaginary_tol: Tolerance used to decide if a phonon mode is imaginary, + in THz. + + Returns: + A tuple of the number of imaginary modes at Gamma, the minimum phonon + frequency at Gamma, and the free energy, entropy, and heat capacity + """ + + nconfig = int(nconfig) + supercell_atoms = AseAtomsAdaptor.get_atoms(supercell_structure) + renorm = Renormalization(cs,supercell_atoms,param,fcs,T,renorm_method,fit_method,param_TD=param_TD,fcs_TD=fcs_TD) + fcp_TD, fcs_TD, param_TD = renorm.renormalize(nconfig)#,conv_tresh) + + TD_data, phonopy_TD = harmonic_properties( + structure, supercell_matrix, fcs_TD, [T], imaginary_tol + ) + + if TD_data["n_imaginary"] == 0: + logger.info('Renormalized phonon is completely real at T = {} K!'.format(T)) + anharmonic_data = anharmonic_properties( + phonopy_TD, fcs_TD, [T], TD_data["heat_capacity"], TD_data["n_imaginary"], bulk_modulus=bulk_modulus + ) + TD_data.update(anharmonic_data) +# else: +# anharmonic_data = dict() +# anharmonic_data["temperature"] = T +# anharmonic_data["gruneisen"] = np.array([0,0,0]) +# anharmonic_data["thermal_expansion"] = np.array([0,0,0]) +# anharmonic_data["expansion_fraction"] = np.array([0,0,0]) + + phonopy_orig.run_mesh() + phonopy.run_mesh() + omega_h = phonopy_orig.mesh.frequencies # THz + evec_h = phonopy_orig.mesh.eigenvectors + omega_TD = phonopy.mesh.frequencies # THz + evec_TD = phonopy.mesh.eigenvectors + correction_S, correction_SC = free_energy_correction(omega_h,omega_TD,evec_h,evec_TD,[T]) # eV/atom + + TD_data["free_energy_correction_S"] = correction_S # S = -(dF/dT)_V quasiparticle correction + TD_data["free_energy_correction_SC"] = correction_SC # SCPH 4th-order correction (perturbation theory) + TD_data["fcp"] = fcp_TD + TD_data["fcs"] = fcs_TD + TD_data["param"] = param_TD + TD_data['cs'] = cs + + return TD_data + + +def thermodynamic_integration_ifc( + TD_data: Dict, + fcs: ForceConstants, + param: np.ndarray, + lambda_array: np.ndarray = np.array([0, 0.1, 0.3, 0.5, 0.7, 0.9, 1]), + TI_nconfig=3, +) -> Dict: + + supercell_structure = TD_data["supercell_structure"] + cs = TD_data['cs'] + fcs_TD = TD_data["fcs"] + param_TD = TD_data["param"] + T = TD_data['temperature'] + supercell_atoms = AseAtomsAdaptor.get_atoms(supercell_structure) + renorm = Renormalization(cs, supercell_atoms, param, fcs, T, 'least_squares', 'rfe', param_TD, fcs_TD) + matcov_TD, matcov_BO, matcov_TDBO = renorm.born_oppenheimer_qcv(TI_nconfig) + correction_TI = renorm.thermodynamic_integration(lambda_array, matcov_TD, matcov_BO, matcov_TDBO, TI_nconfig) + TD_data["free_energy_correction_TI"] = correction_TI + return TD_data + + +def setup_TE_renorm(cs,cutoffs,parent_atoms,supercell_atoms,param,dLfrac): + parent_atoms_TE = copy(parent_atoms) + new_cell = Cell(np.transpose([parent_atoms_TE.get_cell()[:,i]*(1+dLfrac[0,i]) for i in range(3)])) + parent_atoms_TE.set_cell(new_cell,scale_atoms=True) + parent_structure_TE = AseAtomsAdaptor.get_structure(parent_atoms_TE) + supercell_atoms_TE = copy(supercell_atoms) + new_supercell = Cell(np.transpose([supercell_atoms_TE.get_cell()[:,i]*(1+dLfrac[0,i]) for i in range(3)])) + supercell_atoms_TE.set_cell(new_supercell,scale_atoms=True) + supercell_structure_TE = AseAtomsAdaptor.get_structure(supercell_atoms_TE) + count = 0 + failed = False + cs_TE = ClusterSpace(parent_atoms_TE,cutoffs,symprec=1e-2,acoustic_sum_rules=True) + while True: + count += 1 + if cs_TE.n_dofs == cs.n_dofs: + break + elif count>10: + logger.warning("Could not find ClusterSpace for expanded cell identical to the original cluster space!") + failed = True + break + elif count==1: + cutoffs_TE = [i*(1+np.linalg.norm(dLfrac)) for i in cutoffs] + elif cs_TE.n_dofs > cs.n_dofs: + cutoffs_TE = [i*0.999 for i in cutoffs_TE] + elif cs_TE.n_dofs < cs.n_dofs: + cutoffs_TE = [i*1.001 for i in cutoffs_TE] + cs_TE = ClusterSpace(parent_atoms_TE,cutoffs_TE,symprec=1e-2,acoustic_sum_rules=True) + if failed: + return None, None, None, None, None, failed + else: + fcp_TE = ForceConstantPotential(cs_TE, param) + fcs_TE = fcp_TE.get_force_constants(supercell_atoms_TE) + prim_TE_phonopy = PhonopyAtoms(symbols=parent_atoms_TE.get_chemical_symbols(), + scaled_positions=parent_atoms_TE.get_scaled_positions(), + cell=parent_atoms_TE.cell) + phonopy_TE = Phonopy(prim_TE_phonopy, supercell_matrix=scmat, primitive_matrix=None) + return parent_structure_TE, supercell_structure_TE, cs_TE, phonopy_TE, fcs_TE, failed diff --git a/atomate/vasp/analysis/phonopy.py b/atomate/vasp/analysis/phonopy.py index 03c107559..ed0a0c288 100644 --- a/atomate/vasp/analysis/phonopy.py +++ b/atomate/vasp/analysis/phonopy.py @@ -1,4 +1,12 @@ import numpy as np +from monty.dev import requires + +from pymatgen.core.structure import Structure + +try: + import phonopy +except ImportError: + phonopy = False __author__ = "Kiran Mathew" __email__ = "kmathew@lbl.gov" @@ -30,8 +38,9 @@ def get_phonopy_gibbs( t_step (float): temperature step t_max (float): max temperature mesh (list/tuple): reciprocal space density - eos (str): equation of state used for fitting the energies and the volumes. - options supported by phonopy: vinet, murnaghan, birch_murnaghan + eos (str): equation of state used for fitting the energies and the + volumes. options supported by phonopy: vinet, murnaghan, + birch_murnaghan pressure (float): in GPa, optional. Returns: @@ -59,6 +68,7 @@ def get_phonopy_gibbs( return G, T +@requires(phonopy, "phonopy is required to calculate the QHA") def get_phonopy_qha( energies, volumes, @@ -83,8 +93,9 @@ def get_phonopy_qha( t_step (float): temperature step t_max (float): max temperature mesh (list/tuple): reciprocal space density - eos (str): equation of state used for fitting the energies and the volumes. - options supported by phonopy: vinet, murnaghan, birch_murnaghan + eos (str): equation of state used for fitting the energies and the + volumes. options supported by phonopy: vinet, murnaghan, + birch_murnaghan pressure (float): in GPa, optional. Returns: @@ -156,12 +167,14 @@ def get_phonopy_thermal_expansion( t_step (float): temperature step t_max (float): max temperature mesh (list/tuple): reciprocal space density - eos (str): equation of state used for fitting the energies and the volumes. - options supported by phonopy: vinet, murnaghan, birch_murnaghan + eos (str): equation of state used for fitting the energies and the + volumes. options supported by phonopy: vinet, murnaghan, + birch_murnaghan pressure (float): in GPa, optional. Returns: - (numpy.ndarray, numpy.ndarray): thermal expansion coefficient, Temperature + (numpy.ndarray, numpy.ndarray): thermal expansion coefficient, + Temperature """ # quasi-harmonic approx diff --git a/atomate/vasp/config.py b/atomate/vasp/config.py index 1c18cfc9a..68038a155 100644 --- a/atomate/vasp/config.py +++ b/atomate/vasp/config.py @@ -11,6 +11,7 @@ VASP_CMD = ">>vasp_cmd<<" VDW_KERNEL_DIR = ">>vdw_kernel_dir<<" DB_FILE = ">>db_file<<" +SHENGBTE_CMD = ">>shengbte_cmd<<" ADD_WF_METADATA = True LOBSTER_CMD = ">>lobster_cmd<<" diff --git a/atomate/vasp/drones.py b/atomate/vasp/drones.py index c7cb95835..4d1002c12 100644 --- a/atomate/vasp/drones.py +++ b/atomate/vasp/drones.py @@ -574,6 +574,7 @@ def process_vasprun(self, dir_name, taskname, filename): # perform Bader analysis using Henkelman bader if self.parse_bader and "chgcar" in d["output_file_paths"]: + print(self.parse_bader) suffix = "" if taskname == "standard" else f".{taskname}" bader = bader_analysis_from_path(dir_name, suffix=suffix) d["bader"] = bader diff --git a/atomate/vasp/firetasks/aimd.py b/atomate/vasp/firetasks/aimd.py new file mode 100644 index 000000000..83a2ff286 --- /dev/null +++ b/atomate/vasp/firetasks/aimd.py @@ -0,0 +1,501 @@ +import json +import os +import subprocess +import shlex +from datetime import datetime +from pathlib import Path + +import numpy as np +from copy import copy, deepcopy + +from monty.dev import requires +from monty.serialization import dumpfn, loadfn +from monty.json import jsanitize +from pymongo import ReturnDocument + +from atomate.utils.utils import env_chk, get_logger +from atomate.vasp.database import VaspCalcDb +from atomate.vasp.drones import VaspDrone + +from fireworks import FiretaskBase, FWAction, explicit_serialize + +from pymatgen.core.structure import Structure +from pymatgen.transformations.standard_transformations import ( + SupercellTransformation, +) + + +__author__ = "Junsoo Park" +__email__ = "junsoo.park@nasa.gov" + +logger = get_logger(__name__) + + +@explicit_serialize +class CollectMDSegments(FiretaskBase): + """ + Aggregate the structures and forces of perturbed supercells. + + Requires a ``perturbed_tasks`` key to be set in the fw_spec, containing a + list of dictionaries, each with the keys: + + - "parent_structure": The original structure. + - "supercell_matrix": The supercell transformation matrix. + - "structure": The perturbed supercell structure. + - "forces": The forces on each site in the supercell. + """ + + def run_task(self, fw_spec): + results = fw_spec.get("aimd", []) + logger.info("Found {} AIMD segments".format(len(results))) + + structures = [r["structure"] for r in results] + forces = [np.asarray(r["forces"][i]) for i in range(len(r)) for r in results] + stress = [np.asarray(r["stress"][i]) for i in range(len(r)) for r in results] + configs = [r["configurations"][i] for i in range(len(r)) for r in results] + + # if relaxation, get original structure from that calculation + calc_locs = fw_spec.get("calc_locs", []) + opt_calc_locs = [c for c in calc_locs if "optimiz" in c["name"]] + if opt_calc_locs: + opt_loc = opt_calc_locs[-1]["path"] + logger.info("Parsing optimization directory: {}".format(opt_loc)) + opt_doc = VaspDrone( + parse_dos=False, parse_locpot=False, + parse_bader=False, store_volumetric_data=[], + ).assimilate(opt_loc) + opt_output = opt_doc["calcs_reversed"][0]["output"] + structure = Structure.from_dict(opt_output["structure"]) + else: + structure = results[0]["parent_structure"] + supercell_matrix = results[0]["supercell_matrix"] + + # regenerate pure supercell structure + st = SupercellTransformation(supercell_matrix) + supercell_structure = st.apply_transformation(structure) + + structure_data = { + "structure": structure, + "supercell_structure": supercell_structure, + "supercell_matrix": supercell_matrix, + } + + logger.info("Writing structure and forces data.") + dumpfn(structures, "perturbed_structures.json") + dumpfn(forces, "perturbed_forces.json") + dumpfn(structure_data, "structure_data.json") + + +@explicit_serialize +class MDToDB(FiretaskBase): + required_params = ["db_file"] + optional_params = ["renormalized","renorm_temperature","mesh_density", "additional_fields"] + + def run_task(self, fw_spec): + db_file = env_chk(self.get("db_file"), fw_spec) + mmdb = VaspCalcDb.from_db_file(db_file, admin=True) + + # Get an id for the force constants + fitting_id = _get_fc_fitting_id(mmdb) + metadata = {"fc_fitting_id": fitting_id, "renormalization_dir": os.getcwd()} + data = { + "created_at": datetime.utcnow(), + "tags": fw_spec.get("tags", None), + "formula_pretty": structure.composition.reduced_formula, + "structure": structure.as_dict(), + "supercell_matrix": supercell_matrix, + "supercell_structure": supercell_structure.as_dict(), + "perturbed_structures": [s.as_dict() for s in perturbed_structures], + "perturbed_forces": [f.tolist() for f in forces], + "fitting_data": fitting_data, + "thermal_data": thermal_data, + "force_constants_fs_id": fc_fsid, + "phonon_dos_fs_id": dos_fsid, + "phonon_bandstructure_uniform_fs_id": uniform_bs_fsid, + "phonon_bandstructure_line_fs_id": lm_bs_fsid, + } + data.update(self.get("additional_fields", {})) + data.update(metadata) + data = jsanitize(data, strict=True, allow_bson=True) + mmdb.db.aimd_for_potential_fitting.insert_one(data) + + logger.info("Finished inserting renormalized force constants and phonon data at {} K".format(T)) + + return FWAction(update_spec=metadata) + + +@explicit_serialize +class RunHiPhive(FiretaskBase): + """ + Fit force constants using hiPhive. + + Requires "perturbed_structures.json", "perturbed_forces.json", and + "structure_data.json" files to be present in the current working directory. + + Optional parameters: + cutoffs (Optional[list[list]]): A list of cutoffs to trial. If None, + a set of trial cutoffs will be generated based on the structure + (default). + disp_cut: determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + imaginary_tol (float): Tolerance used to decide if a phonon mode + is imaginary, in THz. + fit_method (str): Method used for fitting force constants. This can + be any of the values allowed by the hiphive ``Optimizer`` class. + """ + + optional_params = [ + "cutoffs", + "disp_cut", + "temperature_qha", + "bulk_modulus", + "imaginary_tol", + "fit_method", + ] + + @requires(hiphive, "hiphive is required for lattice dynamics workflow") + def run_task(self, fw_spec): + + all_structures = loadfn("perturbed_structures.json") + all_forces = loadfn("perturbed_forces.json") + structure_data = loadfn("structure_data.json") + parent_structure = structure_data["structure"] + supercell_structure = structure_data["supercell_structure"] + supercell_matrix = np.array(structure_data["supercell_matrix"]) + + disp_cut = self.get('disp_cut', None) + cutoffs = self.get("cutoffs") or get_cutoffs(supercell_structure) + T_qha = self.get("temperature_qha", T_QHA) + T_qha.sort() + imaginary_tol = self.get("imaginary_tol") + bulk_modulus = self.get("bulk_modulus") + fit_method = self.get("fit_method") + + structures = [] + supercell_atoms = AseAtomsAdaptor.get_atoms(supercell_structure) + for structure, forces in zip(all_structures, all_forces): + atoms = AseAtomsAdaptor.get_atoms(structure) + displacements = get_displacements(atoms, supercell_atoms) + atoms.new_array("displacements", displacements) + atoms.new_array("forces", forces) + atoms.positions = supercell_atoms.get_positions() + structures.append(atoms) + + fcs, param, cs, fitting_data = fit_force_constants( + parent_structure, + supercell_matrix, + structures, + cutoffs, + disp_cut, + imaginary_tol, + fit_method + ) + + if fcs is None: + # fitting failed for some reason + raise RuntimeError( + "Could not find a force constant solution" + ) + + thermal_data, phonopy = harmonic_properties( + parent_structure, supercell_matrix, fcs, T_qha, imaginary_tol + ) + anharmonic_data = anharmonic_properties( + phonopy, fcs, T_qha, thermal_data["heat_capacity"], + thermal_data["n_imaginary"], bulk_modulus + ) + + phonopy.save("phonopy_orig.yaml") + fitting_data["n_imaginary"] = thermal_data.pop("n_imaginary") + thermal_data.update(anharmonic_data) + dumpfn(fitting_data, "fitting_data.json") + dumpfn(thermal_data, "thermal_data.json") + + logger.info("Writing cluster space and force_constants") + logger.info("{}".format(type(fcs))) + fcs.write("force_constants.fcs") + np.savetxt('parameters.txt',param) + cs.write('cluster_space.cs') + + if fitting_data["n_imaginary"] == 0: + logger.info("No imaginary modes! Writing ShengBTE files") + atoms = AseAtomsAdaptor.get_atoms(parent_structure) + fcs.write_to_shengBTE("FORCE_CONSTANTS_3RD", atoms, order=3) + fcs.write_to_phonopy("FORCE_CONSTANTS_2ND", format="text") + else: + logger.info("ShengBTE files not written due to imaginary modes.") + logger.info("You may want to perform phonon renormalization.") + + + +@explicit_serialize +class RunHiPhiveRenorm(FiretaskBase): + """ + Perform phonon renormalization to obtain dependent-temperature force constants + using hiPhive. Requires "structure_data.json" to be present in the current working + directory. + + Required parameters: + + Optional parameter: + temperature (float): temperature to perform renormalization + renorm_TE_iter (bool): if True, perform outer iteration over thermally expanded volumes + bulk_modulus (float): input bulk modulus - required for thermal expansion iterations + """ + + optional_params = ["renorm_method","temperature","nconfig","conv_thresh","max_iter", + "renorm_TE_iter","bulk_modulus","imaginary_tol"] + + @requires(hiphive, "hiphive is required for lattice dynamics workflow") + def run_task(self, fw_spec): + + cs = ClusterSpace.read('cluster_space.cs') + fcs = ForceConstants.read('force_constants.fcs') + param = np.loadtxt('parameters.txt') + fitting_data = loadfn("fitting_data.json") + structure_data = loadfn("structure_data.json") + phonopy_orig = phpy.load("phonopy_orig.yaml") + + cutoffs = fitting_data["cutoffs"] + fit_method = fitting_data["fit_method"] + imaginary_tol = fitting_data["imaginary_tol"] + + parent_structure = structure_data["structure"] + supercell_structure = structure_data["supercell_structure"] + supercell_atoms = AseAtomsAdaptor.get_atoms(supercell_structure) + supercell_matrix = np.array(structure_data["supercell_matrix"]) + + temperature = self.get("temperature") + renorm_method = self.get("renorm_method") + nconfig = self.get("nconfig") + conv_thresh = self.get("conv_thresh") + max_iter = self.get("max_iter") + renorm_TE_iter = self.get("renorm_TE_iter") + bulk_modulus = self.get("bulk_modulus") + + # Renormalization with DFT lattice + renorm_data = run_renormalization(parent_structure, supercell_atoms, supercell_matrix, cs, fcs, param, temperature, + nconfig, max_iter, conv_thresh, renorm_method, fit_method, bulk_modulus, phonopy_orig) + + # Additional renormalization with thermal expansion - optional - just single "iteration" for now + if renorm_TE_iter: + n_TE_iter = 1 + for i in range(n_TE_iter): + if renorm_data is None: # failed or incomplete + break + elif result["n_imaginary"] < 0: # still imaginary + break + else: + logger.info("Renormalizing with thermally expanded lattice - iteration {}".format(i)) + + dLfrac = renorm_data["expansion_fraction"] + param = renorm_data["param"] + + parent_structure_TE, supercell_atoms_TE, cs_TE, fcs_TE = setup_TE_iter(cs,cutoffs,parent_structure,param,temperature,dLfrac) + prim_TE_atoms = AseAtomsAdaptor.get_atoms(parent_structure_TE) + prim_TE_phonopy = PhonopyAtoms(symbols=prim_TE_atoms.get_chemical_symbols(), + scaled_positions=prim_TE_atoms.get_scaled_positions(), cell=prim_TE_atoms.cell) + phonopy_TE = Phonopy(prim_phonopy_TE, supercell_matrix=scmat, primitive_matrix=None) + + renorm_data = run_renormalization(parent_structure_TE, supercell_atoms_TE, supercell_matrix, + cs_TE, fcs_TE, param, temperature, nconfig, max_iter, + conv_thresh, renorm_method, fit_method, bulk_modulus, phonopy_TE) + structure_data["structure"] = parent_structure_TE + structure_data["supercell_structure"] = AseAtomsAdaptor.get_structure(supercell_atoms_TE) + + # write results + logger.info("Writing renormalized results") + renorm_thermal_data = dict() + fcs = renorm_data['fcs'] + fcs.write("force_constants.fcs") + thermal_keys = ["temperature","free_energy","entropy","heat_capacity", + "gruneisen","thermal_expansion","expansion_fraction", + "free_energy_correction_S","free_energy_correction_SC"] + renorm_thermal_data = {key: [] for key in thermal_keys} + for key in thermal_keys: + renorm_thermal_data[key].append(renorm_data[key]) + + logger.info("DEBUG: ",renorm_data) + if renorm_data["n_imaginary"] > 0: + logger.warning('Imaginary modes remain for {} K!'.format(temperature)) + logger.warning('ShengBTE files not written') + logger.warning('No renormalization with thermal expansion') + else: + logger.info("No imaginary modes! Writing ShengBTE files") + fcs.write_to_phonopy("FORCE_CONSTANTS_2ND".format(temperature), format="text") + + dumpfn(structure_data, "structure_data.json".format(temperature)) + dumpfn(renorm_thermal_data, "renorm_thermal_data.json".format(temperature)) + + +@explicit_serialize +class ForceConstantsToDb(FiretaskBase): + """ + Add force constants, phonon band structure and density of states + to the database. + + Assumes you are in a directory with the force constants, fitting + data, and structure data written to files. + + Required parameters: + db_file (str): Path to DB file for the database that contains the + perturbed structure calculations. + + Optional parameters: + renormalized (bool): Whether FC resulted from original fitting (False) + or renormalization process (True) determines how data are stored. + Default is False. + mesh_density (float): The density of the q-point mesh used to calculate + the phonon density of states. See the docstring for the ``mesh`` + argument in Phonopy.init_mesh() for more details. + additional_fields (dict): Additional fields added to the document, such + as user-defined tags, name, ids, etc. + """ + + required_params = ["db_file"] + optional_params = ["renormalized","renorm_temperature","mesh_density", "additional_fields"] + + @requires(hiphive, "hiphive is required for lattice dynamics workflow") + def run_task(self, fw_spec): + + db_file = env_chk(self.get("db_file"), fw_spec) + mmdb = VaspCalcDb.from_db_file(db_file, admin=True) + renormalized = self.get("renormalized", False) + renorm_temperature = self.get("renorm_temperature", None) + mesh_density = self.get("mesh_density", 100.0) + + structure_data = loadfn("structure_data.json") + structure = structure_data["structure"] + supercell_structure = structure_data["supercell_structure"] + supercell_matrix = structure_data["supercell_matrix"] + + if not renormalized: + perturbed_structures = loadfn("perturbed_structures.json") + forces = loadfn("perturbed_forces.json") + fitting_data = loadfn("fitting_data.json") + thermal_data = loadfn("thermal_data.json") + fcs = ForceConstants.read("force_constants.fcs") + + dos_fsid, uniform_bs_fsid, lm_bs_fsid, fc_fsid = _get_fc_fsid( + structure, supercell_matrix, fcs, mesh_density, mmdb + ) + + data = { + "created_at": datetime.utcnow(), + "tags": fw_spec.get("tags", None), + "formula_pretty": structure.composition.reduced_formula, + "structure": structure.as_dict(), + "supercell_matrix": supercell_matrix, + "supercell_structure": supercell_structure.as_dict(), + "perturbed_structures": [s.as_dict() for s in perturbed_structures], + "perturbed_forces": [f.tolist() for f in forces], + "fitting_data": fitting_data, + "thermal_data": thermal_data, + "force_constants_fs_id": fc_fsid, + "phonon_dos_fs_id": dos_fsid, + "phonon_bandstructure_uniform_fs_id": uniform_bs_fsid, + "phonon_bandstructure_line_fs_id": lm_bs_fsid, + } + data.update(self.get("additional_fields", {})) + + # Get an id for the force constants + fitting_id = _get_fc_fitting_id(mmdb) + metadata = {"fc_fitting_id": fitting_id, "fc_fitting_dir": os.getcwd()} + data.update(metadata) + data = jsanitize(data,strict=True,allow_bson=True) + + mmdb.db.lattice_dynamics.insert_one(data) + + logger.info("Finished inserting force constants and phonon data") + + else: + renorm_thermal_data = loadfn("renorm_thermal_data.json") + fcs = ForceConstants.read("force_constants.fcs") + T = renorm_thermal_data["temperature"] + + dos_fsid, uniform_bs_fsid, lm_bs_fsid, fc_fsid = _get_fc_fsid( + structure, supercell_matrix, fcs, mesh_density, mmdb + ) + + data_at_T = { + "created_at": datetime.utcnow(), + "tags": fw_spec.get("tags", None), + "formula_pretty": structure.composition.reduced_formula, + "structure": structure.as_dict(), + "supercell_matrix": supercell_matrix, + "supercell_structure": supercell_structure.as_dict(), + "thermal_data": renorm_thermal_data, + "force_constants_fs_id": fc_fsid, + "phonon_dos_fs_id": dos_fsid, + "phonon_bandstructure_uniform_fs_id": uniform_bs_fsid, + "phonon_bandstructure_line_fs_id": lm_bs_fsid, + } + data_at_T.update(self.get("additional_fields", {})) + + # Get an id for the force constants + fitting_id = _get_fc_fitting_id(mmdb) + metadata = {"fc_fitting_id": fitting_id, "renormalization_dir": os.getcwd()} + data_at_T.update(metadata) + data_at_T = jsanitize(data_at_T,strict=True,allow_bson=True) + + mmdb.db.renormalized_lattice_dynamics.insert_one(data_at_T) + + logger.info("Finished inserting renormalized force constants and phonon data at {} K".format(T)) + + return FWAction(update_spec=metadata) + + +def _get_fc_fitting_id(mmdb: VaspCalcDb) -> int: + """Helper method to get a force constant fitting id.""" + fc_id = mmdb.db.counter.find_one_and_update( + {"_id": "fc_fitting_id"}, + {"$inc": {"c": 1}}, + return_document=ReturnDocument.AFTER, + ) + if fc_id is None: + mmdb.db.counter.insert({"_id": "fc_fitting_id", "c": 1}) + fc_id = 1 + else: + fc_id = fc_id["c"] + + return fc_id + + +def _get_fc_fsid(structure, supercell_matrix, fcs, mesh_density, mmdb): + phonopy_fc = fcs.get_fc_array(order=2) + + logger.info("Getting uniform phonon band structure.") + uniform_bs = get_phonon_band_structure_from_fc( + structure, supercell_matrix, phonopy_fc + ) + + logger.info("Getting line mode phonon band structure.") + lm_bs = get_phonon_band_structure_symm_line_from_fc( + structure, supercell_matrix, phonopy_fc + ) + + logger.info("Getting phonon density of states.") + dos = get_phonon_dos_from_fc( + structure, supercell_matrix, phonopy_fc, mesh_density=mesh_density + ) + + logger.info("Inserting phonon objects into database.") + dos_fsid, _ = mmdb.insert_gridfs( + dos.to_json(), collection="phonon_dos_fs" + ) + uniform_bs_fsid, _ = mmdb.insert_gridfs( + uniform_bs.to_json(), collection="phonon_bandstructure_fs" + ) + lm_bs_fsid, _ = mmdb.insert_gridfs( + lm_bs.to_json(), collection="phonon_bandstructure_fs" + ) + + logger.info("Inserting force constants into database.") + fc_json = json.dumps( + {str(k): v.tolist() for k, v in fcs.get_fc_dict().items()} + ) + fc_fsid, _ = mmdb.insert_gridfs( + fc_json, collection="phonon_force_constants_fs" + ) + + return dos_fsid, uniform_bs_fsid, lm_bs_fsid, fc_fsid diff --git a/atomate/vasp/firetasks/lattice_dynamics.py b/atomate/vasp/firetasks/lattice_dynamics.py new file mode 100644 index 000000000..84a572a60 --- /dev/null +++ b/atomate/vasp/firetasks/lattice_dynamics.py @@ -0,0 +1,646 @@ +import json +import os +import subprocess +import shlex +from datetime import datetime +from pathlib import Path + +import numpy as np +from joblib import Parallel, delayed +from copy import copy, deepcopy + +from monty.dev import requires +from monty.serialization import dumpfn, loadfn +from monty.json import jsanitize +from pymongo import ReturnDocument + +import phonopy as phpy + +from atomate.utils.utils import env_chk, get_logger +from atomate.vasp.database import VaspCalcDb +from atomate.vasp.drones import VaspDrone +from atomate.vasp.analysis.lattice_dynamics import ( + T_QHA, + T_KLAT, + fit_force_constants, + harmonic_properties, + anharmonic_properties, + run_renormalization, + setup_TE_renorm, + get_cutoffs +) + +from fireworks import FiretaskBase, FWAction, explicit_serialize + +from pymatgen.core.structure import Structure +from pymatgen.io.ase import AseAtomsAdaptor +from pymatgen.io.phonopy import get_phonon_band_structure_from_fc, \ + get_phonon_dos_from_fc, get_phonon_band_structure_symm_line_from_fc +from pymatgen.io.shengbte import Control +from pymatgen.transformations.standard_transformations import ( + SupercellTransformation, +) + +try: + import hiphive + from hiphive import ForceConstants, ClusterSpace + from hiphive.utilities import get_displacements +except ImportError: + logger.info('Could not import hiphive!') + hiphive = False + + +__author__ = "Alex Ganose, Junsoo Park" +__email__ = "aganose@lbl.gov, jsyony37@lbl.gov" + +logger = get_logger(__name__) + + +@explicit_serialize +class CollectPerturbedStructures(FiretaskBase): + """ + Aggregate the structures and forces of perturbed supercells. + + Requires a ``perturbed_tasks`` key to be set in the fw_spec, containing a + list of dictionaries, each with the keys: + + - "parent_structure": The original structure. + - "supercell_matrix": The supercell transformation matrix. + - "structure": The perturbed supercell structure. + - "forces": The forces on each site in the supercell. + """ + + def run_task(self, fw_spec): + results = fw_spec.get("perturbed_tasks", []) + + if len(results) == 0: + # can happen if all parents fizzled + raise RuntimeError("No perturbed tasks found in firework spec") + + logger.info("Found {} perturbed structures".format(len(results))) + + structures = [r["structure"] for r in results] + forces = [np.asarray(r["forces"]) for r in results] + + # if relaxation, get original structure from that calculation + calc_locs = fw_spec.get("calc_locs", []) + opt_calc_locs = [c for c in calc_locs if "optimiz" in c["name"]] + if opt_calc_locs: + opt_loc = opt_calc_locs[-1]["path"] + logger.info("Parsing optimization directory: {}".format(opt_loc)) + opt_doc = VaspDrone( + parse_dos=False, parse_locpot=False, + parse_bader=False, store_volumetric_data=[], + ).assimilate(opt_loc) + opt_output = opt_doc["calcs_reversed"][0]["output"] + structure = Structure.from_dict(opt_output["structure"]) + else: + structure = results[0]["parent_structure"] + supercell_matrix = results[0]["supercell_matrix"] + + # regenerate pure supercell structure + st = SupercellTransformation(supercell_matrix) + supercell_structure = st.apply_transformation(structure) + + structure_data = { + "structure": structure, + "supercell_structure": supercell_structure, + "supercell_matrix": supercell_matrix, + } + + logger.info("Writing structure and forces data.") + dumpfn(structures, "perturbed_structures.json") + dumpfn(forces, "perturbed_forces.json") + dumpfn(structure_data, "structure_data.json") + + +@explicit_serialize +class RunHiPhive(FiretaskBase): + """ + Fit force constants using hiPhive. + + Requires "perturbed_structures.json", "perturbed_forces.json", and + "structure_data.json" files to be present in the current working directory. + + Optional parameters: + cutoffs (Optional[list[list]]): A list of cutoffs to trial. If None, + a set of trial cutoffs will be generated based on the structure + (default). + disp_cut: determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + imaginary_tol (float): Tolerance used to decide if a phonon mode + is imaginary, in THz. + fit_method (str): Method used for fitting force constants. This can + be any of the values allowed by the hiphive ``Optimizer`` class. + """ + + optional_params = [ + "cutoffs", + "disp_cut", + "temperature_qha", + "bulk_modulus", + "imaginary_tol", + "fit_method", + ] + + @requires(hiphive, "hiphive is required for lattice dynamics workflow") + def run_task(self, fw_spec): + + all_structures = loadfn("perturbed_structures.json") + all_forces = loadfn("perturbed_forces.json") + structure_data = loadfn("structure_data.json") + parent_structure = structure_data["structure"] + supercell_structure = structure_data["supercell_structure"] + supercell_matrix = np.array(structure_data["supercell_matrix"]) + + disp_cut = self.get('disp_cut', None) + cutoffs = self.get("cutoffs") or get_cutoffs(supercell_structure) + T_qha = self.get("temperature_qha", T_QHA) + T_qha.sort() + imaginary_tol = self.get("imaginary_tol") + bulk_modulus = self.get("bulk_modulus") + fit_method = self.get("fit_method") + + structures = [] + supercell_atoms = AseAtomsAdaptor.get_atoms(supercell_structure) + for structure, forces in zip(all_structures, all_forces): + atoms = AseAtomsAdaptor.get_atoms(structure) + displacements = get_displacements(atoms, supercell_atoms) + atoms.new_array("displacements", displacements) + atoms.new_array("forces", forces) + atoms.positions = supercell_atoms.get_positions() + structures.append(atoms) + + fcs, param, cs, fitting_data = fit_force_constants( + parent_structure, + supercell_matrix, + structures, + cutoffs, + disp_cut, + imaginary_tol, + fit_method + ) + + if fcs is None: + # fitting failed for some reason + raise RuntimeError( + "Could not find a force constant solution" + ) + + thermal_data, phonopy = harmonic_properties( + parent_structure, supercell_matrix, fcs, T_qha, imaginary_tol + ) + anharmonic_data = anharmonic_properties( + phonopy, fcs, T_qha, thermal_data["heat_capacity"], + thermal_data["n_imaginary"], bulk_modulus + ) + + phonopy.save("phonopy_orig.yaml") + fitting_data["n_imaginary"] = thermal_data.pop("n_imaginary") + thermal_data.update(anharmonic_data) + dumpfn(fitting_data, "fitting_data.json") + dumpfn(thermal_data, "thermal_data.json") + + logger.info("Writing cluster space and force_constants") + logger.info("{}".format(type(fcs))) + fcs.write("force_constants.fcs") + np.savetxt('parameters.txt',param) + cs.write('cluster_space.cs') + + if fitting_data["n_imaginary"] == 0: + logger.info("No imaginary modes! Writing ShengBTE files") + atoms = AseAtomsAdaptor.get_atoms(parent_structure) + fcs.write_to_shengBTE("FORCE_CONSTANTS_3RD", atoms, order=3) + fcs.write_to_phonopy("FORCE_CONSTANTS_2ND", format="text") + else: + logger.info("ShengBTE files not written due to imaginary modes.") + logger.info("You may want to perform phonon renormalization.") + + + +@explicit_serialize +class RunHiPhiveRenorm(FiretaskBase): + """ + Perform phonon renormalization to obtain dependent-temperature force constants + using hiPhive. Requires "structure_data.json" to be present in the current working + directory. + + Required parameters: + + Optional parameter: + temperature (float): temperature to perform renormalization + renorm_TE_iter (bool): if True, perform outer iteration over thermally expanded volumes + bulk_modulus (float): input bulk modulus - required for thermal expansion iterations + """ + + optional_params = ["renorm_method","temperature","nconfig", + "renorm_TE_iter","bulk_modulus","imaginary_tol"] + + @requires(hiphive, "hiphive is required for lattice dynamics workflow") + def run_task(self, fw_spec): + + cs = ClusterSpace.read('cluster_space.cs') + fcs = ForceConstants.read('force_constants.fcs') + param = np.loadtxt('parameters.txt') + fitting_data = loadfn("fitting_data.json") + structure_data = loadfn("structure_data.json") + phonopy_orig = phpy.load("phonopy_orig.yaml") + + cutoffs = fitting_data["cutoffs"] + fit_method = fitting_data["fit_method"] + + parent_structure = structure_data["structure"] + supercell_structure = structure_data["supercell_structure"] + supercell_matrix = np.array(structure_data["supercell_matrix"]) + + temperature = self.get("temperature") + renorm_method = self.get("renorm_method") + nconfig = self.get("nconfig") + renorm_TE_iter = self.get("renorm_TE_iter") + bulk_modulus = self.get("bulk_modulus") + + parent_atoms = AseAtomsAdaptor.get_atoms(parent_structure) + supercell_atoms = AseAtomsAdaptor.get_atoms(supercell_structure) + + # Renormalization with DFT lattice + TD_data = run_renormalization(parent_structure, supercell_structure, supercell_matrix, + cs, fcs, param, temperature, nconfig, renorm_method, + fit_method, bulk_modulus, phonopy_orig) + TD_structure_data = copy(structure_data) + TD_structure_data["structure"] = parent_structure + TD_structure_data["supercell_structure"] = supercell_structure + + # Additional renormalization with thermal expansion - optional - just single "iteration" for now + if renorm_TE_iter: + n_TE_iter = 1 + for i in range(n_TE_iter): + if TD_data is None: # failed or incomplete + break + elif result["n_imaginary"] < 0: # still imaginary + break + else: + logger.info("Renormalizing with thermally expanded lattice - iteration {}".format(i)) + dLfrac = TD_data["expansion_fraction"] + param_TD = TD_data["param"] + a, b, c, d, e, failed = setup_TE_renorm( + cs,cutoffs,parent_atoms,supercell_atoms,param_TD,temperature,dLfrac + ) + if not failed: + parent_structure_TD, supercell_structure_TD, cs_TD, phonopy_TD, fcs_TD = a, b, c, d, e + TD_data = run_renormalization(parent_structure_TD, supercell_structure_TD, supercell_matrix, + cs_TD, fcs, param, temperature, nconfig, + renorm_method, fit_method, bulk_modulus, + phonopy_TD, param_TD, fcs_TD + ) + TD_structure_data["structure"] = parent_structure_TD + TD_structure_data["supercell_structure"] = supercell_structure_TD + + # Thermodynamic integration for anharmonic free energy + TD_data = thermodynamic_integration_ifc(TD_data, # everything TD + fcs, # original + param, # original + ) + + # write results + logger.info("Writing renormalized results") + fcs_TD = TD_data['fcs'] + fcs_TD.write("force_constants.fcs") + thermal_keys = ["temperature","free_energy","entropy","heat_capacity", + "gruneisen","thermal_expansion","expansion_fraction", + "free_energy_correction_S","free_energy_correction_SC", + "free_energy_correction_TI"] + TD_thermal_data = {key: [] for key in thermal_keys} + for key in thermal_keys: + TD_thermal_data[key].append(TD_data[key]) + + logger.info("DEBUG: ",TD_data) + if TD_data["n_imaginary"] > 0: + logger.warning('Imaginary modes remain still exist') + logger.warning('ShengBTE FORCE_CONSTANTS_2ND not written') + else: + logger.info("No imaginary modes! Writing ShengBTE FORCE_CONSTANTS_2ND...") + fcs_TD.write_to_phonopy("FORCE_CONSTANTS_2ND".format(temperature), format="text") + + dumpfn(TD_structure_data, "structure_data.json") + dumpfn(TD_thermal_data, "thermal_data.json") + + +@explicit_serialize +class ForceConstantsToDb(FiretaskBase): + """ + Add force constants, phonon band structure and density of states + and thermal properties to the database. + + Assumes you are in a directory with the force constants, fitting + data, and structure data written to files. + + Required parameters: + db_file (str): Path to DB file for the database that contains the + perturbed structure calculations. + + Optional parameters: + renormalized (bool): Whether FC resulted from original fitting (False) + or renormalization process (True) determines how data are stored. + Default is False. + mesh_density (float): The density of the q-point mesh used to calculate + the phonon density of states. See the docstring for the ``mesh`` + argument in Phonopy.init_mesh() for more details. + additional_fields (dict): Additional fields added to the document, such + as user-defined tags, name, ids, etc. + """ + + required_params = ["db_file"] + optional_params = ["renormalized","renorm_temperature","mesh_density", "additional_fields"] + + @requires(hiphive, "hiphive is required for lattice dynamics workflow") + def run_task(self, fw_spec): + + db_file = env_chk(self.get("db_file"), fw_spec) + mmdb = VaspCalcDb.from_db_file(db_file, admin=True) + renormalized = self.get("renormalized", False) + mesh_density = self.get("mesh_density", 100.0) + + structure_data = loadfn("structure_data.json") + structure = structure_data["structure"] + supercell_structure = structure_data["supercell_structure"] + supercell_matrix = structure_data["supercell_matrix"] + + if not renormalized: + perturbed_structures = loadfn("perturbed_structures.json") + forces = loadfn("perturbed_forces.json") + fitting_data = loadfn("fitting_data.json") + thermal_data = loadfn("thermal_data.json") + fcs = ForceConstants.read("force_constants.fcs") + + dos_fsid, uniform_bs_fsid, lm_bs_fsid, fc_fsid = _get_fc_fsid( + structure, supercell_matrix, fcs, mesh_density, mmdb + ) + + data = { + "created_at": datetime.utcnow(), + "tags": fw_spec.get("tags", None), + "formula_pretty": structure.composition.reduced_formula, + "structure": structure.as_dict(), + "supercell_matrix": supercell_matrix, + "supercell_structure": supercell_structure.as_dict(), + "perturbed_structures": [s.as_dict() for s in perturbed_structures], + "perturbed_forces": [f.tolist() for f in forces], + "fitting_data": fitting_data, + "thermal_data": thermal_data, + "force_constants_fs_id": fc_fsid, + "phonon_dos_fs_id": dos_fsid, + "phonon_bandstructure_uniform_fs_id": uniform_bs_fsid, + "phonon_bandstructure_line_fs_id": lm_bs_fsid, + } + data.update(self.get("additional_fields", {})) + + # Get an id for the force constants + fitting_id = _get_fc_fitting_id(mmdb) + metadata = {"fc_fitting_id": fitting_id, "fc_fitting_dir": os.getcwd()} + data.update(metadata) + data = jsanitize(data,strict=True,allow_bson=True) + + mmdb.db.lattice_dynamics.insert_one(data) + + logger.info("Finished inserting force constants and phonon data") + + else: + TD_thermal_data = loadfn("thermal_data.json") + fcs = ForceConstants.read("force_constants.fcs") + T = TD_thermal_data["temperature"] + + dos_fsid, uniform_bs_fsid, lm_bs_fsid, fc_fsid = _get_fc_fsid( + structure, supercell_matrix, fcs, mesh_density, mmdb + ) + + data_at_T = { + "created_at": datetime.utcnow(), + "tags": fw_spec.get("tags", None), + "formula_pretty": structure.composition.reduced_formula, + "structure": structure.as_dict(), + "supercell_matrix": supercell_matrix, + "supercell_structure": supercell_structure.as_dict(), + "thermal_data": TD_thermal_data, + "force_constants_fs_id": fc_fsid, + "phonon_dos_fs_id": dos_fsid, + "phonon_bandstructure_uniform_fs_id": uniform_bs_fsid, + "phonon_bandstructure_line_fs_id": lm_bs_fsid, + } + data_at_T.update(self.get("additional_fields", {})) + + # Get an id for the force constants + fitting_id = _get_fc_fitting_id(mmdb) + metadata = {"fc_fitting_id": fitting_id, "renormalization_dir": os.getcwd()} + data_at_T.update(metadata) + data_at_T = jsanitize(data_at_T,strict=True,allow_bson=True) + + mmdb.db.renormalized_lattice_dynamics.insert_one(data_at_T) + + logger.info("Finished inserting renormalized force constants and phonon data at {} K".format(T)) + + return FWAction(update_spec=metadata) + + +@explicit_serialize +class RunShengBTE(FiretaskBase): + """ + Run ShengBTE to calculate lattice thermal conductivity. Presumes + the FORCE_CONSTANTS_3RD and FORCE_CONSTANTS_2ND, and a "structure_data.json" + file, with the keys "structure", " and "supercell_matrix" is in the current + directory. + + Required parameters: + shengbte_cmd (str): The name of the shengbte executable to run. Supports + env_chk. + + Optional parameters: + renormalized: boolean to denote whether force constants are from + phonon renormalization (True) or directly from fitting (False) + temperature (float or dict): The temperature to calculate the lattice + thermal conductivity for. Can be given as a single float, or a + dictionary with the keys "t_min", "t_max", "t_step". + control_kwargs (dict): Options to be included in the ShengBTE control + file. + """ + + required_params = ["shengbte_cmd"] + optional_params = ["renormalized","temperature", "control_kwargs"] + + def run_task(self, fw_spec): + structure_data = loadfn("structure_data.json") + structure = structure_data["structure"] + supercell_matrix = structure_data["supercell_matrix"] + temperature = self.get("temperature", T_KLAT) + renormalized = self.get("renormalized", False) + + if renormalized: + assert isinstance(temperature, (int, float)) + self["t"] = temperature + else: + if isinstance(temperature, (int, float)): + self["t"] = temperature + elif isinstance(temperature, dict): + self["t_min"] = temperature["t_min"] + self["t_max"] = temperature["t_max"] + self["t_step"] = temperature["t_step"] + else: + raise ValueError("Unsupported temperature type, must be float or dict") + + control_dict = { + "scalebroad": 0.5, + "nonanalytic": False, + "isotopes": False, + "temperature": temperature, + "scell": np.diag(supercell_matrix).tolist(), + } + control_kwargs = self.get("control_kwargs") or {} + control_dict.update(control_kwargs) + control = Control().from_structure(structure, **control_dict) + control.to_file() + + shengbte_cmd = env_chk(self["shengbte_cmd"], fw_spec) + + if isinstance(shengbte_cmd, str): + shengbte_cmd = os.path.expandvars(shengbte_cmd) + shengbte_cmd = shlex.split(shengbte_cmd) + + shengbte_cmd = list(shengbte_cmd) + logger.info("Running command: {}".format(shengbte_cmd)) + + with open("shengbte.out", "w") as f_std, open( + "shengbte_err.txt", "w", buffering=1 + ) as f_err: + # use line buffering for stderr + return_code = subprocess.call( + shengbte_cmd, stdout=f_std, stderr=f_err + ) + logger.info( + "Command {} finished running with returncode: {}".format( + shengbte_cmd, return_code + ) + ) + + if return_code == 1: + raise RuntimeError( + "Running ShengBTE failed. Check '{}/shengbte_err.txt' for " + "details.".format(os.getcwd()) + ) + + +@explicit_serialize +class ShengBTEToDb(FiretaskBase): + """ + Add lattice thermal conductivity results to database. + + Assumes you are in a directory with the ShengBTE results in. + + Required parameters: + db_file (str): Path to DB file for the database that contains the + perturbed structure calculations. + + Optional parameters: + additional_fields (dict): Additional fields added to the document. + """ + + required_params = ["db_file"] + optional_params = ["additional_fields"] + + def run_task(self, fw_spec): + db_file = env_chk(self.get("db_file"), fw_spec) + mmdb = VaspCalcDb.from_db_file(db_file, admin=True) + + control = Control().from_file("CONTROL") + structure = control.get_structure() + supercell_matrix = np.diag(control["scell"]) + + if Path("BTE.KappaTotalTensorVsT_CONV").exists(): + filename = "BTE.KappaTotalTensorVsT_CONV" + elif Path("BTE.KappaTensorVsT_CONV").exists(): + filename = "BTE.KappaTensorVsT_CONV" + elif Path("BTE.KappaTensorVsT_RTA").exists(): + filename = "BTE.KappaTensorVsT_RTA" + else: + raise RuntimeError("Could not find ShengBTE output files.") + + bte_data = np.loadtxt(filename) + if len(bte_data.shape) == 1: + # pad extra axis to make compatible with multiple temperatures + bte_data = bte_data[None, :] + + temperatures = bte_data[:, 0].tolist() + kappa = bte_data[:, 1:10].reshape(-1, 3, 3).tolist() + + data = { + "structure": structure.as_dict(), + "supercell_matrix": supercell_matrix.tolist(), + "temperatures": temperatures, + "lattice_thermal_conductivity": kappa, + "control": control.as_dict(), + "tags": fw_spec.get("tags", None), + "formula_pretty": structure.composition.reduced_formula, + "shengbte_dir": os.getcwd(), + "fc_fitting_id": fw_spec.get("fc_fitting_id", None), + "fc_fitting_dir": fw_spec.get("fc_fitting_dir", None), + "renormalization_dir": fw_spec.get("renormalization_dir", None), + "created_at": datetime.utcnow(), + } + data.update(self.get("additional_fields", {})) + + mmdb.collection = mmdb.db["lattice_thermal_conductivity"] + mmdb.collection.insert(data) + + +def _get_fc_fitting_id(mmdb: VaspCalcDb) -> int: + """Helper method to get a force constant fitting id.""" + fc_id = mmdb.db.counter.find_one_and_update( + {"_id": "fc_fitting_id"}, + {"$inc": {"c": 1}}, + return_document=ReturnDocument.AFTER, + ) + if fc_id is None: + mmdb.db.counter.insert({"_id": "fc_fitting_id", "c": 1}) + fc_id = 1 + else: + fc_id = fc_id["c"] + + return fc_id + + +def _get_fc_fsid(structure, supercell_matrix, fcs, mesh_density, mmdb): + phonopy_fc = fcs.get_fc_array(order=2) + + logger.info("Getting uniform phonon band structure.") + uniform_bs = get_phonon_band_structure_from_fc( + structure, supercell_matrix, phonopy_fc + ) + + logger.info("Getting line mode phonon band structure.") + lm_bs = get_phonon_band_structure_symm_line_from_fc( + structure, supercell_matrix, phonopy_fc + ) + + logger.info("Getting phonon density of states.") + dos = get_phonon_dos_from_fc( + structure, supercell_matrix, phonopy_fc, mesh_density=mesh_density + ) + + logger.info("Inserting phonon objects into database.") + dos_fsid, _ = mmdb.insert_gridfs( + dos.to_json(), collection="phonon_dos_fs" + ) + uniform_bs_fsid, _ = mmdb.insert_gridfs( + uniform_bs.to_json(), collection="phonon_bandstructure_fs" + ) + lm_bs_fsid, _ = mmdb.insert_gridfs( + lm_bs.to_json(), collection="phonon_bandstructure_fs" + ) + + logger.info("Inserting force constants into database.") + fc_json = json.dumps( + {str(k): v.tolist() for k, v in fcs.get_fc_dict().items()} + ) + fc_fsid, _ = mmdb.insert_gridfs( + fc_json, collection="phonon_force_constants_fs" + ) + + return dos_fsid, uniform_bs_fsid, lm_bs_fsid, fc_fsid diff --git a/atomate/vasp/firetasks/parse_outputs.py b/atomate/vasp/firetasks/parse_outputs.py index e7891e608..9e559dd91 100644 --- a/atomate/vasp/firetasks/parse_outputs.py +++ b/atomate/vasp/firetasks/parse_outputs.py @@ -37,13 +37,14 @@ from atomate.utils.utils import get_logger from atomate.vasp.database import VaspCalcDb from atomate.vasp.drones import VaspDrone, BADER_EXE_EXISTS -from atomate.vasp.config import STORE_VOLUMETRIC_DATA +from atomate.vasp.config import STORE_VOLUMETRIC_DATA, STORE_BADER __author__ = "Anubhav Jain, Kiran Mathew, Shyam Dwaraknath" __email__ = "ajain@lbl.gov, kmathew@lbl.gov, shyamd@lbl.gov" logger = get_logger(__name__) +STORE_BADER = STORE_BADER and BADER_EXE_EXISTS @explicit_serialize class VaspToDb(FiretaskBase): @@ -81,6 +82,8 @@ class VaspToDb(FiretaskBase): The path is a full mongo-style path so subdocuments can be referneced using dot notation and array keys can be referenced using the index. E.g "calcs_reversed.0.output.outar.run_stats" + vasp_drone_params (dict): Additional keyword arguments to pass to the + VaspDrone. """ optional_params = [ @@ -116,7 +119,7 @@ def run_task(self, fw_spec): parse_dos=self.get("parse_dos", False), parse_potcar_file=self.get("parse_potcar_file", True), bandstructure_mode=self.get("bandstructure_mode", False), - parse_bader=self.get("parse_bader", BADER_EXE_EXISTS), + parse_bader=STORE_BADER, #self.get("parse_bader", BADER_EXE_EXISTS), parse_chgcar=self.get("parse_chgcar", False), # deprecated parse_aeccar=self.get("parse_aeccar", False), # deprecated store_volumetric_data=self.get( diff --git a/atomate/vasp/firetasks/run_calc.py b/atomate/vasp/firetasks/run_calc.py index d6ce3b413..741cbf110 100644 --- a/atomate/vasp/firetasks/run_calc.py +++ b/atomate/vasp/firetasks/run_calc.py @@ -22,7 +22,7 @@ AliasingErrorHandler, MeshSymmetryErrorHandler, UnconvergedErrorHandler, - MaxForceErrorHandler, +# MaxForceErrorHandler, PotimErrorHandler, FrozenJobErrorHandler, NonConvergingErrorHandler, diff --git a/atomate/vasp/firetasks/tests/test_polarization_to_db.py b/atomate/vasp/firetasks/tests/test_polarization_to_db.py index d70def948..3dd25a6c7 100644 --- a/atomate/vasp/firetasks/tests/test_polarization_to_db.py +++ b/atomate/vasp/firetasks/tests/test_polarization_to_db.py @@ -1,36 +1,24 @@ -import os -import unittest +import bson +import gzip +from pathlib import Path from atomate.utils.testing import AtomateTest from atomate.vasp.firetasks.parse_outputs import PolarizationToDb - __author__ = "Tess Smidt" __email__ = "blondegeek@gmail.com" -module_dir = os.path.join(os.path.dirname(os.path.abspath(__file__))) -db_dir = os.path.join(module_dir, "..", "..", "..", "common", "test_files") -ref_dir = os.path.join(module_dir, "..", "..", "test_files") - +module_dir = Path(__file__).resolve().parent +db_dir = module_dir / "../../../common/test_files" +ref_dir = module_dir / "../../test_files" -DEBUG_MODE = ( - True # If true, retains the database and output dirs at the end of the test -) -VASP_CMD = ( - None # If None, runs a "fake" VASP. Otherwise, runs VASP with this command... -) - -class TestFerroelectricWorkflow(AtomateTest): +class TestPolarizationFiretasks(AtomateTest): def test_polarizationtodb(self): + wf_dir = ref_dir / "ferroelectric_wf" - import bson - import gzip - - reference_dir = os.path.abspath(os.path.join(ref_dir, "ferroelectric_wf")) - - with gzip.open(os.path.join(reference_dir, "tasks.bson.gz")) as f: + with gzip.open(wf_dir / "tasks.bson.gz") as f: coll_raw = f.read() coll = bson.decode_all(coll_raw) @@ -40,7 +28,7 @@ def test_polarizationtodb(self): db.insert(c) new_fw_spec = { - "_fw_env": {"db_file": os.path.join(db_dir, "db.json")}, + "_fw_env": {"db_file": db_dir / "db.json"}, "tags": ["wfid_1494203093.06934658"], } @@ -50,8 +38,4 @@ def test_polarizationtodb(self): # Check recovered change in polarization coll = self.get_task_collection("polarization_tasks") d = coll.find_one() - self.assertAlmostEqual(d["polarization_change_norm"], 46.288752795325244, 5) - - -if __name__ == "__main__": - unittest.main() + self.assertAlmostEqual(d["polarization_change_norm"], 46.28875279532, 5) \ No newline at end of file diff --git a/atomate/vasp/fireworks/aimd.py b/atomate/vasp/fireworks/aimd.py new file mode 100644 index 000000000..40a0251b2 --- /dev/null +++ b/atomate/vasp/fireworks/aimd.py @@ -0,0 +1,193 @@ +from typing import List, Optional, Union, Dict + +import os + +from atomate.common.firetasks.glue_tasks import ( + CopyFiles, + CopyFilesFromCalcLoc, + PassCalcLocs, +) + +from atomate.vasp.firetasks.aimd import ( + CollectMDSegments, + MDToDB + ) + +from fireworks import Firework + +__author__ = "Junsoo Park" +__email__ = "junsoo.park@nasa.gov" + + +class ARCMDFW(Firework): + def __init__( + self, + structure, + start_temp, + end_temp, + nsteps, + name="AIMD", + vasp_input_set=None, + vasp_cmd=VASP_CMD, + override_default_vasp_params=None, + wall_time=19200, + db_file=DB_FILE, + parents=None, + **kwargs, + ): + """ + Standard firework for a single MD run. + + Args: + structure (Structure): Input structure. + start_temp (float): Start temperature of MD run. + end_temp (float): End temperature of MD run. + nsteps (int): Number of MD steps + name (string): Name for the Firework. + vasp_input_set (string): string name for the VASP input set (e.g., + "MITMDVaspInputSet"). + vasp_cmd (string): Command to run vasp. + override_default_vasp_params (dict): If this is not None, + these params are passed to the default vasp_input_set, i.e., + MITMDSet. This allows one to easily override some + settings, e.g., user_incar_settings, etc. Particular to MD, + one can control time_step and all other settings of the input set. + wall_time (int): Total wall time in seconds before writing STOPCAR. + copy_vasp_outputs (bool): Whether to copy outputs from previous run. Defaults to True. + db_file (string): Path to file specifying db credentials. + parents (Firework): Parents of this particular Firework. FW or list of FWS. + **kwargs: Other kwargs that are passed to Firework.__init__. + """ + override_default_vasp_params = override_default_vasp_params or {} + vasp_input_set = vasp_input_set or ARCMDSet( + structure, + start_temp=start_temp, + end_temp=end_temp, + nsteps=nsteps, + **override_default_vasp_params, + ) + prev_runs = fw_spec.get("aimd", []) + last_run = prev_runs[-1] + last_config = last_run["final_configuration"] + t = [] + t.append(WriteVaspFromIOSet(structure=last_config, vasp_input_set=vasp_input_set)) + t.append( + RunVaspCustodian( + vasp_cmd=vasp_cmd, + gamma_vasp_cmd=">>vasp_cmd<<",#">>gamma_vasp_cmd<<", + handler_group="md", + wall_time=wall_time, + ) + ) + t.append(PassCalcLocs(name=name)) + t.append( + VaspToDb( + db_file=db_file, + additional_fields={"task_label": name}, + defuse_unsuccessful=False, + ) + ) + super().__init__( + t, + parents=parents, + name=f"{structure.composition.reduced_formula}-{name}", + **kwargs, + ) + + +class CollectMDSegmentsFW(Firework): + """ + Compile serial AIMD runs segmented into multiple Fireworks + + Args: + parents: Parent(s) of this Firework. + name: Name of this FW. + db_file: Path to a db file. + cutoffs: A list of cutoffs to trial. If None, a set of trial cutoffs + will be generated based on the structure (default). + disp_cut: determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + bulk_modulus: in GPa, necessary for thermal expansion + imaginary_tol: Tolerance used to decide if a phonon mode is + imaginary, in THz. + fit_method: Method used for fitting force constants. This can be + any of the values allowed by the hiphive ``Optimizer`` class. + mesh_density: The density of the q-point mesh used to calculate the + phonon density of states. See the docstring for the ``mesh`` + argument in Phonopy.init_mesh() for more details. + **kwargs: Other kwargs that are passed to Firework.__init__. + """ + + def __init__( + self, + name="Collect MD Runs", + parents: Optional[Union[Firework, List[Firework]]] = None, + db_file: str = None, + **kwargs + ): + collect = CollectMDSegments() + + to_db = AIMDToDB( + db_file=db_file, additional_fields={} + ) + pass_locs = PassCalcLocs(name=name) + + tasks = [collect, to_db, pass_locs] + super().__init__(tasks, parents=parents, name=name, **kwargs) + + +class FitForceConstantsFW(Firework): + """ + Compile perturbed supercell calculations and fit force constants + using hiPhive. + + Args: + parents: Parent(s) of this Firework. + name: Name of this FW. + db_file: Path to a db file. + cutoffs: A list of cutoffs to trial. If None, a set of trial cutoffs + will be generated based on the structure (default). + disp_cut: determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + bulk_modulus: in GPa, necessary for thermal expansion + imaginary_tol: Tolerance used to decide if a phonon mode is + imaginary, in THz. + fit_method: Method used for fitting force constants. This can be + any of the values allowed by the hiphive ``Optimizer`` class. + mesh_density: The density of the q-point mesh used to calculate the + phonon density of states. See the docstring for the ``mesh`` + argument in Phonopy.init_mesh() for more details. + **kwargs: Other kwargs that are passed to Firework.__init__. + """ + + def __init__( + self, + fit_method: str, + disp_cut: float, + bulk_modulus: float, + imaginary_tol: float, + mesh_density: float, + temperature_qha: float, + cutoffs: Optional[List[List[float]]] = None, + name="Fit Force Constants", + parents: Optional[Union[Firework, List[Firework]]] = None, + db_file: str = None, + **kwargs + ): + collect_structures = CollectPerturbedStructures() + + fit_force_constants = RunHiPhive( + cutoffs=cutoffs, + fit_method=fit_method, + disp_cut=disp_cut, + bulk_modulus=bulk_modulus, + temperature_qha=temperature_qha, + imaginary_tol=imaginary_tol, + ) + to_db = ForceConstantsToDb( + db_file=db_file, renormalized=False, mesh_density=mesh_density, additional_fields={} + ) + pass_locs = PassCalcLocs(name=name) + + tasks = [collect_structures, fit_force_constants, to_db, pass_locs] + super().__init__(tasks, parents=parents, name=name, **kwargs) diff --git a/atomate/vasp/fireworks/core.py b/atomate/vasp/fireworks/core.py index 96d245bd9..5a81b9dff 100644 --- a/atomate/vasp/fireworks/core.py +++ b/atomate/vasp/fireworks/core.py @@ -65,7 +65,7 @@ def __init__( db_file=DB_FILE, force_gamma=True, job_type="double_relaxation_run", - max_force_threshold=RELAX_MAX_FORCE, +# max_force_threshold=RELAX_MAX_FORCE, auto_npar=">>auto_npar<<", half_kpts_first_relax=HALF_KPOINTS_FIRST_RELAX, parents=None, @@ -113,7 +113,7 @@ def __init__( RunVaspCustodian( vasp_cmd=vasp_cmd, job_type=job_type, - max_force_threshold=max_force_threshold, +# max_force_threshold=max_force_threshold, ediffg=ediffg, auto_npar=auto_npar, half_kpts_first_relax=half_kpts_first_relax, diff --git a/atomate/vasp/fireworks/lattice_dynamics.py b/atomate/vasp/fireworks/lattice_dynamics.py new file mode 100644 index 000000000..db6aed82a --- /dev/null +++ b/atomate/vasp/fireworks/lattice_dynamics.py @@ -0,0 +1,220 @@ +from typing import List, Optional, Union, Dict + +import os + +from atomate.common.firetasks.glue_tasks import ( + CopyFiles, + CopyFilesFromCalcLoc, + PassCalcLocs, +) + +from atomate.vasp.config import SHENGBTE_CMD +from atomate.vasp.firetasks.lattice_dynamics import ( + CollectPerturbedStructures, + ForceConstantsToDb, + RunHiPhive, + RunHiPhiveRenorm, + RunShengBTE, + ShengBTEToDb + ) + +from fireworks import Firework + +from hiphive import ClusterSpace, ForceConstants + +__author__ = "Alex Ganose, Junsoo Park" +__email__ = "aganose@lbl.gov, jsyony37@lbl.gov" + + +class FitForceConstantsFW(Firework): + """ + Compile perturbed supercell calculations and fit force constants + using hiPhive. + + Args: + parents: Parent(s) of this Firework. + name: Name of this FW. + db_file: Path to a db file. + cutoffs: A list of cutoffs to trial. If None, a set of trial cutoffs + will be generated based on the structure (default). + disp_cut: determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + bulk_modulus: in GPa, necessary for thermal expansion + imaginary_tol: Tolerance used to decide if a phonon mode is + imaginary, in THz. + fit_method: Method used for fitting force constants. This can be + any of the values allowed by the hiphive ``Optimizer`` class. + mesh_density: The density of the q-point mesh used to calculate the + phonon density of states. See the docstring for the ``mesh`` + argument in Phonopy.init_mesh() for more details. + **kwargs: Other kwargs that are passed to Firework.__init__. + """ + + def __init__( + self, + fit_method: str, + disp_cut: float, + bulk_modulus: float, + imaginary_tol: float, + mesh_density: float, + temperature_qha: float, + cutoffs: Optional[List[List[float]]] = None, + name="Fit Force Constants", + parents: Optional[Union[Firework, List[Firework]]] = None, + db_file: str = None, + **kwargs + ): + collect_structures = CollectPerturbedStructures() + + fit_force_constants = RunHiPhive( + cutoffs=cutoffs, + fit_method=fit_method, + disp_cut=disp_cut, + bulk_modulus=bulk_modulus, + temperature_qha=temperature_qha, + imaginary_tol=imaginary_tol, + ) + to_db = ForceConstantsToDb( + db_file=db_file, renormalized=False, mesh_density=mesh_density, additional_fields={} + ) + pass_locs = PassCalcLocs(name=name) + + tasks = [collect_structures, fit_force_constants, to_db, pass_locs] + super().__init__(tasks, parents=parents, name=name, **kwargs) + + +class LatticeThermalConductivityFW(Firework): + """ + Calculate the lattice thermal conductivity using ShengBTE. + + Args: + name: Name of this FW. + prev_calc_dir: Path to a directory containing the force constant + information. Will override ``parents`` when collecting the force + constants to run ShengBTE. + db_file: Path to a db file. + shengbte_cmd: The name of the shengbte executable to run. Supports + env_chk. + renormalized: boolean to denote whether force constants are from + phonon renormalization (True) or directly from fitting (False) + temperature: The temperature to calculate the lattice thermal + conductivity for. Can be given as a single float, or a + dictionary with the keys "min", "max", "step". + shengbte_control_kwargs: Options to be included in the ShengBTE + control file. + **kwargs: Other kwargs that are passed to Firework.__init__. + """ + + def __init__( + self, + shengbte_cmd: str, + temperature: Union[float, int, dict], + renormalized: bool, + name="Lattice Thermal Conductivity", + prev_calc_dir: Optional[str] = None, + db_file: str = None, + shengbte_control_kwargs: Optional[dict] = None, + **kwargs + ): + + # files needed to run ShengBTE + + files = [ + "structure_data.json", + "FORCE_CONSTANTS_2ND", + "FORCE_CONSTANTS_3RD" + ] + + if renormalized: + assert type(temperature) in [float,int] + name = '{} at {}K'.format(name,temperature) + if prev_calc_dir: + copy_files = CopyFiles(from_dir=prev_calc_dir, filenames=files) + else: + copy_files = CopyFilesFromCalcLoc(calc_loc='Renormalization_{}K'.format(temperature), filenames=files) + + else: + if prev_calc_dir: + copy_files = CopyFiles(from_dir=prev_calc_dir, filenames=files) + else: + copy_files = CopyFilesFromCalcLoc(calc_loc='Fit Force Constants', filenames=files) + + run_shengbte = RunShengBTE( + shengbte_cmd=shengbte_cmd, + renormalized=renormalized, + temperature=temperature, + control_kwargs=shengbte_control_kwargs, + ) + + shengbte_to_db = ShengBTEToDb(db_file=db_file, additional_fields={}) + + tasks = [copy_files, run_shengbte, shengbte_to_db] + + super().__init__(tasks, name=name, **kwargs) + + + +class RenormalizationFW(Firework): + """ + Performs temperature-dependent phonon renormalization to obtain phonons + at finite temperatures. Can be used to stabilize dynamically unstable modes + + Args: + name: Name of this FW. + prev_calc_dir: Path to a directory containing the force constant + information. Will override ``parents`` when collecting the force + constants to run ShengBTE. + db_file: Path to a db file. + temperature: The temperature to perform phonon renormalization at + Can be given as a single float, or a dictionary with the keys + "min", "max", "step". + shengbte_control_kwargs: Options to be included in the ShengBTE + control file. + **kwargs: Other kwargs that are passed to Firework.__init__. + """ + + def __init__( + self, + temperature: Union[float, Dict], + renorm_method: str, + nconfig: int, + conv_thresh: float, + max_iter: float, + renorm_TE_iter: bool, + bulk_modulus: float, + mesh_density: float, + name="Renormalization", + prev_calc_dir: Optional[str] = None, + db_file: str = None, + **kwargs + ): + + # files needed to run renormalization + files = ["cluster_space.cs","parameters.txt","force_constants.fcs", + "structure_data.json","fitting_data.json","phonopy_orig.yaml"] + + name = name+"_{}K".format(temperature) + if prev_calc_dir: + copy_files = CopyFiles(from_dir=prev_calc_dir, filenames=files) + else: + copy_files = CopyFilesFromCalcLoc(calc_loc="Fit Force Constants", filenames=files) + + renorm_force_constants = RunHiPhiveRenorm( + temperature=temperature, + renorm_method=renorm_method, + nconfig=nconfig, + conv_thresh=conv_thresh, + max_iter=max_iter, + renorm_TE_iter=renorm_TE_iter, + bulk_modulus=bulk_modulus, + **kwargs + ) + + to_db = ForceConstantsToDb( + db_file=db_file, renormalized=True, renorm_temperature = temperature, + mesh_density=mesh_density, additional_fields={} + ) + pass_locs = PassCalcLocs(name=name) + + tasks = [copy_files, renorm_force_constants, to_db, pass_locs] + super().__init__(tasks, name=name, **kwargs) diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/INCAR b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/INCAR new file mode 100644 index 000000000..2d049b275 --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/INCAR @@ -0,0 +1,21 @@ +ADDGRID = True +ALGO = Normal +EDIFF = 1e-08 +ENCUT = 700 +IBRION = -1 +ICHARG = 0 +ISIF = 3 +ISMEAR = -5 +ISPIN = 2 +LAECHG = False +LASPH = True +LCHARG = False +LORBIT = 11 +LREAL = False +LVHAR = True +LWAVE = False +MAGMOM = 128*0.6 +NELM = 100 +NSW = 0 +PREC = Accurate +SIGMA = 0.05 diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/KPOINTS b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/KPOINTS new file mode 100644 index 000000000..6677fab59 --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/KPOINTS @@ -0,0 +1,4 @@ +pymatgen v2020.1.28 with grid density = 1239 / atom +0 +Monkhorst +2 2 2 diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/POSCAR b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/POSCAR new file mode 100644 index 000000000..56a563b58 --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/POSCAR @@ -0,0 +1,136 @@ +Si128 +1.0 +15.360792 0.000000 0.000000 +7.680396 13.302841 0.000000 +0.000000 -8.868554 12.542036 +Si +128 +direct +0.002404 -0.002517 0.000123 Si +0.000357 -0.000777 0.252550 Si +0.004490 -0.001628 0.500263 Si +0.002106 -0.006496 0.747226 Si +0.002968 0.251340 -0.000424 Si +-0.003427 0.250985 0.250110 Si +-0.000782 0.251244 0.499624 Si +0.000512 0.249102 0.751360 Si +0.006130 0.492281 -0.004097 Si +-0.002867 0.504654 0.250646 Si +-0.002557 0.504956 0.501778 Si +-0.002017 0.505049 0.753557 Si +-0.000990 0.749992 0.002984 Si +-0.002484 0.747893 0.249024 Si +0.001491 0.747627 0.499072 Si +-0.002745 0.752763 0.751308 Si +0.250543 0.002043 0.002689 Si +0.250263 0.001233 0.251568 Si +0.249181 0.003382 0.499683 Si +0.252592 0.000338 0.750248 Si +0.248235 0.253531 0.002630 Si +0.251371 0.246532 0.246163 Si +0.247689 0.250186 0.499295 Si +0.248728 0.252353 0.751770 Si +0.247456 0.501566 0.000831 Si +0.245919 0.510981 0.258069 Si +0.250265 0.499354 0.499871 Si +0.248424 0.501149 0.748379 Si +0.247168 0.753267 -0.000149 Si +0.249007 0.747189 0.248607 Si +0.250103 0.751187 0.502381 Si +0.250548 0.753120 0.750159 Si +0.504837 -0.004255 -0.001475 Si +0.502158 0.000984 0.253542 Si +0.493063 0.004233 0.502475 Si +0.496057 0.004024 0.754290 Si +0.500139 0.251115 -0.000257 Si +0.496737 0.251876 0.254678 Si +0.496044 0.254600 0.500845 Si +0.497132 0.256958 0.752534 Si +0.496869 0.505817 0.003930 Si +0.500507 0.500335 0.248215 Si +0.497799 0.501539 0.498221 Si +0.498527 0.502456 0.752570 Si +0.499691 0.748601 -0.000097 Si +0.498840 0.750386 0.249273 Si +0.499950 0.751666 0.499152 Si +0.496771 0.749795 0.751294 Si +0.749428 0.001949 -0.000458 Si +0.751229 -0.002795 0.249361 Si +0.750397 -0.002559 0.500299 Si +0.748756 -0.000843 0.749283 Si +0.749923 0.249533 0.000966 Si +0.753039 0.243413 0.251122 Si +0.747658 0.252684 0.503283 Si +0.753566 0.247640 0.749662 Si +0.747313 0.502195 0.004115 Si +0.750050 0.499140 0.251465 Si +0.742704 0.506149 0.502660 Si +0.748272 0.506458 0.752443 Si +0.744373 0.752620 -0.001382 Si +0.749078 0.750121 0.249336 Si +0.750750 0.747982 0.499201 Si +0.747734 0.749730 0.746002 Si +0.187469 0.122464 0.189217 Si +0.184052 0.126282 0.437630 Si +0.180841 0.131891 0.692717 Si +0.187955 0.126552 0.941521 Si +0.190406 0.372753 0.187942 Si +0.185969 0.375798 0.438707 Si +0.190932 0.369119 0.683643 Si +0.184574 0.379973 0.942675 Si +0.186188 0.629074 0.191760 Si +0.186757 0.629134 0.443758 Si +0.189067 0.624236 0.687615 Si +0.185067 0.627484 0.938558 Si +0.188650 0.875055 0.188436 Si +0.189488 0.872896 0.434502 Si +0.188558 0.874926 0.687882 Si +0.189431 0.877489 0.938528 Si +0.434486 0.127784 0.186098 Si +0.437186 0.126922 0.436987 Si +0.430043 0.128728 0.693003 Si +0.435968 0.126353 0.933531 Si +0.439790 0.371458 0.184592 Si +0.435504 0.378703 0.441008 Si +0.440051 0.376642 0.688726 Si +0.438845 0.375748 0.937328 Si +0.441756 0.618757 0.184083 Si +0.440481 0.623350 0.435743 Si +0.434662 0.624163 0.686391 Si +0.438961 0.626271 0.940724 Si +0.436167 0.873872 0.183818 Si +0.442474 0.870235 0.433385 Si +0.433970 0.877630 0.687396 Si +0.437553 0.876921 0.938552 Si +0.685077 0.128538 0.190597 Si +0.688620 0.123968 0.436125 Si +0.686134 0.129310 0.685286 Si +0.686645 0.132644 0.943020 Si +0.687873 0.373540 0.186993 Si +0.689695 0.374393 0.438742 Si +0.686614 0.376172 0.689488 Si +0.687637 0.374833 0.938885 Si +0.690119 0.620944 0.187764 Si +0.685863 0.624962 0.438326 Si +0.687946 0.625392 0.686429 Si +0.688831 0.626261 0.939012 Si +0.688685 0.873769 0.186379 Si +0.690407 0.872704 0.436420 Si +0.690068 0.868895 0.681756 Si +0.689423 0.869237 0.939286 Si +0.934735 0.127559 0.186834 Si +0.939562 0.125044 0.437563 Si +0.935312 0.129003 0.689791 Si +0.940475 0.127166 0.937939 Si +0.942430 0.373299 0.186505 Si +0.937508 0.372289 0.436061 Si +0.936880 0.371913 0.686790 Si +0.935704 0.377405 0.934935 Si +0.935908 0.624800 0.189670 Si +0.940868 0.623802 0.437307 Si +0.939283 0.623943 0.684337 Si +0.936195 0.626949 0.942072 Si +0.936474 0.875867 0.187693 Si +0.939995 0.871104 0.436789 Si +0.938360 0.874652 0.687098 Si +0.938896 0.873531 0.937362 Si diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/POTCAR b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/POTCAR new file mode 100644 index 000000000..ae2291fdf --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/inputs/POTCAR @@ -0,0 +1,1768 @@ + PAW_PBE Si 05Jan2001 + 4.00000000000000000 + parameters from PSCTR are: + VRHFIN =Si: s2p2 + LEXCH = PE + EATOM = 103.0669 eV, 7.5752 Ry + + TITEL = PAW_PBE Si 05Jan2001 + LULTRA = F use ultrasoft PP ? + IUNSCR = 1 unscreen: 0-lin 1-nonlin 2-no + RPACOR = 1.500 partial core radius + POMASS = 28.085; ZVAL = 4.000 mass and valenz + RCORE = 1.900 outmost cutoff radius + RWIGS = 2.480; RWIGS = 1.312 wigner-seitz radius (au A) + ENMAX = 245.345; ENMIN = 184.009 eV + ICORE = 2 local potential + LCOR = T correct aug charges + LPAW = T paw PP + EAUG = 322.069 + DEXC = -.007 + RMAX = 2.944 core radius for proj-oper + RAUG = 1.300 factor for augmentation sphere + RDEP = 1.993 radius for radial grids + QCUT = -4.246; QGAM = 8.493 optimization parameters + + Description + l E TYP RCUT TYP RCUT + 0 .000 23 1.900 + 0 .000 23 1.900 + 1 .000 23 1.900 + 1 .000 23 1.900 + 2 .000 7 1.900 + Error from kinetic energy argument (eV) + NDATA = 100 + STEP = 20.000 1.050 + 10.1 9.04 8.56 7.65 7.23 6.44 5.73 5.40 + 4.79 4.25 4.00 3.54 3.13 2.77 2.45 2.16 + 1.91 1.69 1.50 1.24 1.10 .975 .812 .718 + .636 .529 .440 .388 .322 .266 .219 .180 + .148 .121 .986E-01 .804E-01 .614E-01 .504E-01 .392E-01 .328E-01 + .265E-01 .220E-01 .189E-01 .166E-01 .149E-01 .135E-01 .123E-01 .109E-01 + .977E-02 .840E-02 .707E-02 .605E-02 .488E-02 .387E-02 .290E-02 .229E-02 + .185E-02 .152E-02 .134E-02 .125E-02 .121E-02 .117E-02 .112E-02 .102E-02 + .915E-03 .776E-03 .640E-03 .524E-03 .425E-03 .369E-03 .331E-03 .310E-03 + .294E-03 .273E-03 .242E-03 .210E-03 .175E-03 .146E-03 .124E-03 .113E-03 + .105E-03 .973E-04 .879E-04 .755E-04 .633E-04 .539E-04 .478E-04 .438E-04 + .404E-04 .362E-04 .308E-04 .264E-04 .229E-04 .209E-04 .192E-04 .170E-04 + .145E-04 .126E-04 .112E-04 .103E-04 +END of PSCTR-controll parameters + local part + 98.2657514061040160 + .84157696E+01 .84210616E+01 .84276868E+01 .84387430E+01 .84542501E+01 + .84742336E+01 .84987229E+01 .85277486E+01 .85613410E+01 .85995276E+01 + .86423322E+01 .86897735E+01 .87418643E+01 .87986117E+01 .88600162E+01 + .89260725E+01 .89967686E+01 .90720854E+01 .91519966E+01 .92364669E+01 + .93254512E+01 .94188926E+01 .95167214E+01 .96188530E+01 .97251866E+01 + .98356042E+01 .99499691E+01 .10068126E+02 .10189900E+02 .10315095E+02 + .10443498E+02 .10574872E+02 .10708964E+02 .10845497E+02 .10984178E+02 + .11124691E+02 .11266702E+02 .11409858E+02 .11553785E+02 .11698096E+02 + .11842382E+02 .11986223E+02 .12129182E+02 .12270810E+02 .12410650E+02 + .12548232E+02 .12683081E+02 .12814718E+02 .12942658E+02 .13066416E+02 + .13185509E+02 .13299456E+02 .13407780E+02 .13510014E+02 .13605699E+02 + .13694388E+02 .13775652E+02 .13849074E+02 .13914259E+02 .13970835E+02 + .14018449E+02 .14056778E+02 .14085523E+02 .14104415E+02 .14113216E+02 + .14111719E+02 .14099752E+02 .14077176E+02 .14043889E+02 .13999825E+02 + .13944955E+02 .13879288E+02 .13802872E+02 .13715793E+02 .13618173E+02 + .13510175E+02 .13391996E+02 .13263872E+02 .13126073E+02 .12978903E+02 + .12822702E+02 .12657838E+02 .12484712E+02 .12303753E+02 .12115415E+02 + .11920177E+02 .11718543E+02 .11511033E+02 .11298186E+02 .11080557E+02 + .10858712E+02 .10633228E+02 .10404688E+02 .10173679E+02 .99407918E+01 + .97066146E+01 .94717325E+01 .92367246E+01 .90021609E+01 .87686001E+01 + .85365874E+01 .83066514E+01 .80793026E+01 .78550308E+01 .76343035E+01 + .74175636E+01 .72052280E+01 .69976861E+01 .67952984E+01 .65983952E+01 + .64072758E+01 .62222076E+01 .60434252E+01 .58711303E+01 .57054911E+01 + .55466426E+01 .53946862E+01 .52496902E+01 .51116906E+01 .49806911E+01 + .48566645E+01 .47395534E+01 .46292712E+01 .45257038E+01 .44287105E+01 + .43381258E+01 .42537607E+01 .41754049E+01 .41028282E+01 .40357822E+01 + .39740031E+01 .39172124E+01 .38651203E+01 .38174267E+01 .37738238E+01 + .37339979E+01 .36976315E+01 .36644056E+01 .36340010E+01 .36061008E+01 + .35803917E+01 .35565663E+01 .35343243E+01 .35133745E+01 .34934357E+01 + .34742388E+01 .34555274E+01 .34370596E+01 .34186083E+01 .33999627E+01 + .33809285E+01 .33613290E+01 .33410052E+01 .33198164E+01 .32976401E+01 + .32743723E+01 .32499276E+01 .32242387E+01 .31972561E+01 .31689481E+01 + .31393000E+01 .31083133E+01 .30760055E+01 .30424087E+01 .30075693E+01 + .29715463E+01 .29344112E+01 .28962459E+01 .28571426E+01 .28172018E+01 + .27765317E+01 .27352466E+01 .26934662E+01 .26513138E+01 .26089155E+01 + .25663991E+01 .25238927E+01 .24815236E+01 .24394173E+01 .23976966E+01 + .23564804E+01 .23158831E+01 .22760134E+01 .22369739E+01 .21988600E+01 + .21617599E+01 .21257533E+01 .20909116E+01 .20572974E+01 .20249638E+01 + .19939548E+01 .19643045E+01 .19360379E+01 .19091701E+01 .18837069E+01 + .18596450E+01 .18369720E+01 .18156670E+01 .17957010E+01 .17770368E+01 + .17596305E+01 .17434311E+01 .17283816E+01 .17144193E+01 .17014768E+01 + .16894823E+01 .16783607E+01 .16680338E+01 .16584212E+01 .16494415E+01 + .16410120E+01 .16330504E+01 .16254746E+01 .16182040E+01 .16111597E+01 + .16042653E+01 .15974473E+01 .15906355E+01 .15837638E+01 .15767703E+01 + .15695978E+01 .15621941E+01 .15545123E+01 .15465111E+01 .15381544E+01 + .15294125E+01 .15202610E+01 .15106817E+01 .15006619E+01 .14901947E+01 + .14792788E+01 .14679182E+01 .14561221E+01 .14439046E+01 .14312844E+01 + .14182846E+01 .14049321E+01 .13912574E+01 .13772942E+01 .13630791E+01 + .13486509E+01 .13340503E+01 .13193195E+01 .13045019E+01 .12896412E+01 + .12747815E+01 .12599666E+01 .12452397E+01 .12306428E+01 .12162167E+01 + .12020006E+01 .11880314E+01 .11743437E+01 .11609697E+01 .11479386E+01 + .11352766E+01 .11230067E+01 .11111486E+01 .10997186E+01 .10887293E+01 + .10781902E+01 .10681067E+01 .10584813E+01 .10493127E+01 .10405964E+01 + .10323246E+01 .10244865E+01 .10170685E+01 .10100542E+01 .10034245E+01 + .99715846E+00 .99123280E+00 .98562260E+00 .98030145E+00 .97524173E+00 + .97041488E+00 .96579171E+00 .96134265E+00 .95703806E+00 .95284844E+00 + .94874473E+00 .94469858E+00 .94068254E+00 .93667031E+00 .93263696E+00 + .92855909E+00 .92441506E+00 .92018509E+00 .91585142E+00 .91139842E+00 + .90681263E+00 .90208291E+00 .89720039E+00 .89215854E+00 .88695315E+00 + .88158229E+00 .87604630E+00 .87034770E+00 .86449110E+00 .85848313E+00 + .85233229E+00 .84604884E+00 .83964465E+00 .83313300E+00 .82652847E+00 + .81984671E+00 .81310428E+00 .80631845E+00 .79950703E+00 .79268813E+00 + .78588003E+00 .77910097E+00 .77236895E+00 .76570159E+00 .75911593E+00 + .75262828E+00 .74625407E+00 .74000773E+00 .73390251E+00 .72795041E+00 + .72216209E+00 .71654675E+00 .71111209E+00 .70586428E+00 .70080787E+00 + .69594584E+00 .69127954E+00 .68680877E+00 .68253173E+00 .67844513E+00 + .67454418E+00 .67082274E+00 .66727331E+00 .66388721E+00 .66065462E+00 + .65756473E+00 .65460586E+00 .65176555E+00 .64903076E+00 .64638795E+00 + .64382325E+00 .64132257E+00 .63887178E+00 .63645678E+00 .63406371E+00 + .63167900E+00 .62928956E+00 .62688288E+00 .62444710E+00 .62197118E+00 + .61944494E+00 .61685919E+00 .61420575E+00 .61147755E+00 .60866866E+00 + .60577434E+00 .60279104E+00 .59971643E+00 .59654939E+00 .59329003E+00 + .58993961E+00 .58650056E+00 .58297643E+00 .57937181E+00 .57569230E+00 + .57194440E+00 .56813547E+00 .56427363E+00 .56036764E+00 .55642683E+00 + .55246099E+00 .54848026E+00 .54449503E+00 .54051583E+00 .53655322E+00 + .53261771E+00 .52871961E+00 .52486898E+00 .52107551E+00 .51734843E+00 + .51369641E+00 .51012750E+00 .50664907E+00 .50326768E+00 .49998911E+00 + .49681824E+00 .49375908E+00 .49081468E+00 .48798715E+00 .48527763E+00 + .48268632E+00 .48021244E+00 .47785431E+00 .47560930E+00 .47347392E+00 + .47144387E+00 .46951402E+00 .46767855E+00 .46593095E+00 .46426412E+00 + .46267047E+00 .46114194E+00 .45967012E+00 .45824632E+00 .45686169E+00 + .45550723E+00 .45417395E+00 .45285292E+00 .45153535E+00 .45021267E+00 + .44887661E+00 .44751931E+00 .44613331E+00 .44471171E+00 .44324816E+00 + .44173692E+00 .44017295E+00 .43855190E+00 .43687017E+00 .43512491E+00 + .43331405E+00 .43143631E+00 .42949120E+00 .42747899E+00 .42540073E+00 + .42325823E+00 .42105400E+00 .41879126E+00 .41647384E+00 .41410622E+00 + .41169341E+00 .40924089E+00 .40675462E+00 .40424088E+00 .40170629E+00 + .39915769E+00 .39660209E+00 .39404660E+00 .39149835E+00 .38896445E+00 + .38645189E+00 .38396749E+00 .38151784E+00 .37910923E+00 .37674758E+00 + .37443844E+00 .37218685E+00 .36999739E+00 .36787409E+00 .36582039E+00 + .36383915E+00 .36193261E+00 .36010239E+00 .35834945E+00 .35667414E+00 + .35507613E+00 .35355450E+00 .35210772E+00 .35073362E+00 .34942953E+00 + .34819219E+00 .34701788E+00 .34590241E+00 .34484117E+00 .34382921E+00 + .34286125E+00 .34193178E+00 .34103506E+00 .34016522E+00 .33931629E+00 + .33848229E+00 .33765725E+00 .33683525E+00 .33601054E+00 .33517754E+00 + .33433091E+00 .33346559E+00 .33257683E+00 .33166028E+00 .33071198E+00 + .32972841E+00 .32870651E+00 .32764370E+00 .32653791E+00 .32538758E+00 + .32419168E+00 .32294968E+00 .32166161E+00 .32032797E+00 .31894980E+00 + .31752862E+00 .31606640E+00 .31456556E+00 .31302895E+00 .31145977E+00 + .30986158E+00 .30823823E+00 .30659385E+00 .30493275E+00 .30325946E+00 + .30157859E+00 .29989486E+00 .29821301E+00 .29653778E+00 .29487386E+00 + .29322581E+00 .29159807E+00 .28999490E+00 .28842031E+00 .28687807E+00 + .28537164E+00 .28390415E+00 .28247839E+00 .28109677E+00 .27976132E+00 + .27847363E+00 .27723491E+00 .27604592E+00 .27490700E+00 .27381809E+00 + .27277867E+00 .27178784E+00 .27084428E+00 .26994630E+00 .26909186E+00 + .26827855E+00 .26750369E+00 .26676430E+00 .26605715E+00 .26537882E+00 + .26472568E+00 .26409398E+00 .26347988E+00 .26287945E+00 .26228874E+00 + .26170381E+00 .26112076E+00 .26053579E+00 .25994520E+00 .25934545E+00 + .25873320E+00 .25810531E+00 .25745888E+00 .25679129E+00 .25610022E+00 + .25538363E+00 .25463983E+00 .25386744E+00 .25306545E+00 .25223318E+00 + .25137030E+00 .25047684E+00 .24955316E+00 .24859996E+00 .24761829E+00 + .24660949E+00 .24557519E+00 .24451731E+00 .24343801E+00 .24233971E+00 + .24122498E+00 .24009659E+00 .23895746E+00 .23781060E+00 .23665912E+00 + .23550617E+00 .23435492E+00 .23320855E+00 .23207016E+00 .23094281E+00 + .22982945E+00 .22873289E+00 .22765579E+00 .22660063E+00 .22556967E+00 + .22456498E+00 .22358834E+00 .22264131E+00 .22172517E+00 .22084092E+00 + .21998928E+00 .21917068E+00 .21838526E+00 .21763287E+00 .21691308E+00 + .21622517E+00 .21556818E+00 .21494086E+00 .21434175E+00 .21376913E+00 + .21322111E+00 .21269560E+00 .21219035E+00 .21170297E+00 .21123098E+00 + .21077179E+00 .21032276E+00 .20988120E+00 .20944443E+00 .20900979E+00 + .20857462E+00 .20813639E+00 .20769262E+00 .20724095E+00 .20677916E+00 + .20630522E+00 .20581722E+00 .20531350E+00 .20479256E+00 .20425315E+00 + .20369424E+00 .20311502E+00 .20251496E+00 .20189372E+00 .20125124E+00 + .20058769E+00 .19990349E+00 .19919926E+00 .19847589E+00 .19773443E+00 + .19697618E+00 .19620258E+00 .19541527E+00 .19461602E+00 .19380673E+00 + .19298941E+00 .19216618E+00 .19133918E+00 .19051063E+00 .18968276E+00 + .18885780E+00 .18803797E+00 .18722542E+00 .18642227E+00 .18563052E+00 + .18485209E+00 .18408877E+00 .18334220E+00 .18261388E+00 .18190512E+00 + .18121707E+00 .18055068E+00 .17990670E+00 .17928569E+00 .17868800E+00 + .17811376E+00 .17756291E+00 .17703518E+00 .17653009E+00 .17604697E+00 + .17558497E+00 .17514306E+00 .17472002E+00 .17431452E+00 .17392507E+00 + .17355005E+00 .17318776E+00 .17283640E+00 .17249410E+00 .17215895E+00 + .17182901E+00 .17150232E+00 .17117693E+00 .17085094E+00 .17052245E+00 + .17018966E+00 .16985084E+00 .16950435E+00 .16914867E+00 .16878242E+00 + .16840433E+00 .16801331E+00 .16760841E+00 .16718886E+00 .16675406E+00 + .16630358E+00 .16583717E+00 .16535477E+00 .16485650E+00 .16434264E+00 + .16381366E+00 .16327018E+00 .16271301E+00 .16214308E+00 .16156147E+00 + .16096939E+00 .16036817E+00 .15975923E+00 .15914407E+00 .15852427E+00 + .15790145E+00 .15727728E+00 .15665345E+00 .15603163E+00 .15541350E+00 + .15480071E+00 .15419486E+00 .15359747E+00 .15301002E+00 .15243388E+00 + .15187030E+00 .15132044E+00 .15078533E+00 .15026585E+00 .14976275E+00 + .14927662E+00 .14880791E+00 .14835691E+00 .14792374E+00 .14750838E+00 + .14711065E+00 .14673019E+00 .14636653E+00 .14601903E+00 .14568691E+00 + .14536927E+00 .14506509E+00 .14477325E+00 .14449251E+00 .14422157E+00 + .14395905E+00 .14370352E+00 .14345350E+00 .14320750E+00 .14296399E+00 + .14272149E+00 .14247848E+00 .14223350E+00 .14198515E+00 .14173206E+00 + .14147294E+00 .14120659E+00 .14093190E+00 .14064788E+00 .14035363E+00 + .14004840E+00 .13973155E+00 .13940258E+00 .13906112E+00 .13870694E+00 + .13833997E+00 .13796025E+00 .13756799E+00 .13716350E+00 .13674725E+00 + .13631982E+00 .13588193E+00 .13543440E+00 .13497814E+00 .13451417E+00 + .13404360E+00 .13356759E+00 .13308736E+00 .13260419E+00 .13211937E+00 + .13163425E+00 .13115013E+00 .13066836E+00 .13019023E+00 .12971703E+00 + .12924998E+00 .12879027E+00 .12833900E+00 .12789721E+00 .12746584E+00 + .12704575E+00 .12663767E+00 .12624224E+00 .12585999E+00 .12549130E+00 + .12513646E+00 .12479563E+00 .12446883E+00 .12415596E+00 .12385682E+00 + .12357106E+00 .12329824E+00 .12303778E+00 .12278902E+00 .12255119E+00 + .12232344E+00 .12210482E+00 .12189434E+00 .12169092E+00 .12149346E+00 + .12130080E+00 .12111176E+00 .12092515E+00 .12073978E+00 .12055446E+00 + .12036801E+00 .12017930E+00 .11998723E+00 .11979076E+00 .11958890E+00 + .11938073E+00 .11916544E+00 .11894226E+00 .11871055E+00 .11846975E+00 + .11821943E+00 .11795923E+00 .11768892E+00 .11740838E+00 .11711760E+00 + .11681667E+00 .11650581E+00 .11618532E+00 .11585561E+00 .11551720E+00 + .11517070E+00 .11481679E+00 .11445623E+00 .11408986E+00 .11371858E+00 + .11334333E+00 .11296511E+00 .11258491E+00 .11220379E+00 .11182279E+00 + .11144296E+00 .11106534E+00 .11069096E+00 .11032079E+00 .10995580E+00 + .10959689E+00 .10924491E+00 .10890064E+00 .10856478E+00 .10823798E+00 + .10792077E+00 .10761362E+00 .10731688E+00 .10703084E+00 .10675565E+00 + .10649140E+00 .10623807E+00 .10599552E+00 .10576356E+00 .10554186E+00 + .10533004E+00 .10512760E+00 .10493399E+00 .10474857E+00 .10457063E+00 + .10439942E+00 .10423412E+00 .10407387E+00 .10391779E+00 .10376497E+00 + .10361446E+00 .10346535E+00 .10331669E+00 .10316756E+00 .10301705E+00 + .10286430E+00 .10270846E+00 .10254874E+00 .10238439E+00 .10221475E+00 + .10203918E+00 .10185715E+00 .10166820E+00 .10147193E+00 .10126804E+00 + .10105631E+00 .10083661E+00 .10060889E+00 .10037320E+00 .10012965E+00 + .99878467E-01 .99619932E-01 .99354416E-01 .99082363E-01 .98804288E-01 + .98520765E-01 .98232428E-01 .97939960E-01 .97644087E-01 .97345569E-01 + .97045195E-01 .96743772E-01 .96442116E-01 .96141050E-01 .95841391E-01 + .95543942E-01 .95249488E-01 .94958785E-01 .94672554E-01 .94391474E-01 + .94116174E-01 .93847229E-01 .93585152E-01 .93330392E-01 .93083329E-01 + .92844268E-01 .92613442E-01 .92391008E-01 .92177045E-01 .91971556E-01 + .91774467E-01 .91585628E-01 .91404815E-01 .91231735E-01 .91066024E-01 + .90907255E-01 .90754941E-01 .90608543E-01 .90467470E-01 .90331093E-01 + .90198744E-01 .90069732E-01 .89943339E-01 .89818838E-01 .89695492E-01 + .89572566E-01 .89449332E-01 .89325075E-01 .89199102E-01 .89070749E-01 + .88939383E-01 .88804416E-01 .88665301E-01 .88521548E-01 .88372720E-01 + .88218440E-01 .88058396E-01 .87892342E-01 .87720097E-01 .87541550E-01 + .87356660E-01 .87165453E-01 .86968025E-01 .86764537E-01 .86555218E-01 + .86340357E-01 .86120303E-01 .85895462E-01 .85666290E-01 .85433289E-01 + .85197004E-01 .84958012E-01 .84716921E-01 .84474359E-01 .84230970E-01 + .83987410E-01 .83744335E-01 .83502399E-01 .83262247E-01 .83024506E-01 + .82789784E-01 .82558658E-01 .82331673E-01 .82109336E-01 .81892108E-01 + .81680401E-01 .81474576E-01 .81274938E-01 .81081732E-01 .80895145E-01 + .80715299E-01 .80542258E-01 .80376020E-01 .80216523E-01 .80063643E-01 + .79917196E-01 .79776941E-01 .79642582E-01 .79513768E-01 .79390103E-01 + .79271145E-01 .79156412E-01 .79045389E-01 .78937532E-01 .78832272E-01 + .78729025E-01 .78627196E-01 .78526182E-01 .78425382E-01 .78324201E-01 + .78222055E-01 .78118379E-01 .78012628E-01 .77904287E-01 .77792874E-01 + .77677943E-01 .77559095E-01 .77435971E-01 .77308267E-01 .77175728E-01 + .77038154E-01 .76895403E-01 .76747386E-01 .76594073E-01 .76435492E-01 + .76271726E-01 .76102913E-01 .75929245E-01 .75750968E-01 .75568374E-01 + gradient corrections used for XC + 5 + core charge-density (partial) + .13681950E+01 .13676960E+01 .13662001E+01 .13637105E+01 .13602325E+01 + .13557734E+01 .13503429E+01 .13439524E+01 .13366153E+01 .13283473E+01 + .13191655E+01 .13090892E+01 .12981393E+01 .12863384E+01 .12737107E+01 + .12602820E+01 .12460794E+01 .12311314E+01 .12154677E+01 .11991194E+01 + .11821181E+01 .11644970E+01 .11462895E+01 .11275301E+01 .11082538E+01 + .10884962E+01 .10682931E+01 .10476808E+01 .10266957E+01 .10053741E+01 + .98375267E+00 .96186759E+00 .93975503E+00 .91745077E+00 .89499021E+00 + .87240826E+00 .84973926E+00 .82701690E+00 .80427415E+00 .78154320E+00 + .75885536E+00 .73624104E+00 .71372967E+00 .69134969E+00 .66912843E+00 + .64709213E+00 .62526592E+00 .60367371E+00 .58233824E+00 .56128104E+00 + .54052238E+00 .52008130E+00 .49997559E+00 .48022178E+00 .46083513E+00 + .44182968E+00 .42321820E+00 .40501225E+00 .38722216E+00 .36985707E+00 + .35292495E+00 .33643262E+00 .32038578E+00 .30478902E+00 .28964588E+00 + .27495886E+00 .26072949E+00 .24695832E+00 .23364498E+00 .22078822E+00 + .20838596E+00 .19643530E+00 .18493258E+00 .17387344E+00 .16325283E+00 + .15306507E+00 .14330386E+00 .13396240E+00 .12503332E+00 .11650883E+00 + .10838067E+00 .10064023E+00 .93278522E-01 .86286250E-01 .79653846E-01 + .73371505E-01 .67429216E-01 .61816797E-01 .56523934E-01 .51540202E-01 + .46855108E-01 .42458109E-01 .38338647E-01 .34486174E-01 .30890174E-01 + .27540191E-01 .24425850E-01 .21536879E-01 .18863125E-01 .16394577E-01 + .14121382E-01 .12033860E-01 .10122516E-01 .83780589E-02 .67914092E-02 + .53537108E-02 .40563408E-02 .28909177E-02 .18493086E-02 .92363545E-03 + .10628041E-03 -.61011044E-03 -.12326237E-02 -.17680763E-02 -.22230146E-02 + -.26037134E-02 -.29161762E-02 -.31661368E-02 -.33590603E-02 -.35001462E-02 + -.35943310E-02 -.36462916E-02 -.36604501E-02 -.36409780E-02 -.35918012E-02 + -.35166058E-02 -.34188439E-02 -.33017396E-02 -.31682957E-02 -.30213004E-02 + -.28633344E-02 -.26967780E-02 -.25238182E-02 -.23464568E-02 -.21665171E-02 + -.19856525E-02 -.18053531E-02 -.16269545E-02 -.14516446E-02 -.12804716E-02 + -.11143516E-02 -.95407590E-03 -.80031868E-03 -.65364406E-03 -.51451335E-03 + -.38329201E-03 -.26025656E-03 -.14560117E-03 -.39444206E-04 .58165516E-04 + .14724263E-03 .22785937E-03 .30013989E-03 .36425487E-03 .42041630E-03 + .46887251E-03 .50990347E-03 .54381628E-03 .57094091E-03 .59162620E-03 + .60623608E-03 .61514601E-03 .61873968E-03 .61740593E-03 .61153588E-03 + .60152031E-03 .58774722E-03 .57059965E-03 .55045362E-03 .52767640E-03 + .50262485E-03 .47564400E-03 .44706580E-03 .41720805E-03 .38637350E-03 + .35484906E-03 .32290522E-03 .29079555E-03 .25875641E-03 .22700669E-03 + .19574775E-03 .16516340E-03 .13542004E-03 .10666685E-03 .79036088E-04 + .52643451E-04 .27588517E-04 .39552464E-05 -.18187465E-04 -.38785178E-04 + -.57797264E-04 -.75196221E-04 -.90966959E-04 -.10510606E-03 -.11762104E-03 + -.12852953E-03 -.13785858E-03 -.14564378E-03 -.15192858E-03 -.15676343E-03 + -.16020507E-03 -.16231575E-03 -.16316249E-03 -.16281641E-03 -.16135195E-03 + -.15884628E-03 -.15537859E-03 -.15102952E-03 -.14588056E-03 -.14001345E-03 + -.13350974E-03 -.12645021E-03 -.11891448E-03 -.11098056E-03 -.10272445E-03 + -.94219808E-04 -.85537643E-04 -.76746000E-04 -.67909727E-04 -.59090263E-04 + -.50345446E-04 -.41729367E-04 -.33292247E-04 -.25080349E-04 -.17135911E-04 + -.94971159E-05 -.21980781E-05 .47311376E-05 .11264479E-04 .17379846E-04 + .23059012E-04 .28287521E-04 .33054577E-04 .37352910E-04 .41178632E-04 + .44531079E-04 .47412645E-04 .49828605E-04 .51786930E-04 .53298094E-04 + .54374884E-04 .55032195E-04 .55286832E-04 .55157309E-04 .54663646E-04 + .53827166E-04 .52670302E-04 .51216402E-04 .49489534E-04 .47514310E-04 + .45315700E-04 .42918863E-04 .40348986E-04 .37631124E-04 .34790051E-04 + .31850126E-04 .28835162E-04 .25768303E-04 .22671916E-04 .19567494E-04 + .16475560E-04 .13415592E-04 .10405948E-04 .74638126E-05 .46051404E-05 + .18446197E-05 -.80436009E-06 -.33297302E-05 -.57207550E-05 -.79680369E-05 + -.10063512E-04 -.12000439E-04 -.13773381E-04 -.15378177E-04 -.16811912E-04 + -.18072880E-04 -.19160536E-04 -.20075451E-04 -.20819258E-04 -.21394593E-04 + -.21805038E-04 -.22055054E-04 -.22149917E-04 -.22095649E-04 -.21898951E-04 + -.21567128E-04 -.21108022E-04 -.20529940E-04 -.19841582E-04 -.19051971E-04 + -.18170387E-04 -.17206293E-04 -.16169276E-04 -.15068980E-04 -.13915042E-04 + -.12717039E-04 -.11484427E-04 -.10226489E-04 -.89522887E-05 -.76706186E-05 + -.63899617E-05 -.51184500E-05 -.38638299E-05 -.26334298E-05 -.14341327E-05 + -.27235171E-06 .84599016E-06 .19154768E-05 .29312118E-05 .38888277E-05 + .47844919E-05 .56149089E-05 .63773192E-05 .70694955E-05 .76897350E-05 + .82368500E-05 .87101545E-05 .91094496E-05 .94350052E-05 .96875413E-05 + .98682052E-05 .99785491E-05 .10020505E-04 .99963570E-05 .99087173E-05 + .97604944E-05 .95548661E-05 .92952495E-05 .89852710E-05 .86287366E-05 + .82296019E-05 .77919423E-05 .73199237E-05 .68177739E-05 .62897539E-05 + .57401315E-05 .51731543E-05 .45930247E-05 .40038758E-05 .34097487E-05 + .28145712E-05 .22221377E-05 .16360907E-05 .10599042E-05 .49686829E-06 + -.49924253E-07 -.57759018E-06 -.10834658E-05 -.15651156E-05 -.20203391E-05 + -.24471763E-05 -.28439110E-05 -.32090729E-05 -.35414382E-05 -.38400286E-05 + -.41041086E-05 -.43331819E-05 -.45269862E-05 -.46854867E-05 -.48088688E-05 + -.48975294E-05 -.49520671E-05 -.49732722E-05 -.49621152E-05 -.49197348E-05 + -.48474253E-05 -.47466238E-05 -.46188963E-05 -.44659241E-05 -.42894897E-05 + -.40914626E-05 -.38737848E-05 -.36384571E-05 -.33875243E-05 -.31230618E-05 + -.28471617E-05 -.25619196E-05 -.22694215E-05 -.19717316E-05 -.16708804E-05 + -.13688530E-05 -.10675792E-05 -.76892250E-06 -.47467171E-06 -.18653188E-06 + .93883276E-07 .36505838E-06 .62558254E-06 .87415472E-06 .11095882E-05 + .13308143E-05 .15368851E-05 .17269757E-05 .19003854E-05 .20565379E-05 + .21949813E-05 .23153868E-05 .24175471E-05 .25013741E-05 .25668952E-05 + .26142503E-05 .26436874E-05 .26555573E-05 .26503093E-05 .26284844E-05 + .25907101E-05 .25376938E-05 .24702158E-05 .23891225E-05 .22953197E-05 + .21897645E-05 .20734587E-05 .19474411E-05 .18127798E-05 .16705653E-05 + .15219029E-05 .13679056E-05 .12096872E-05 .10483551E-05 .88500422E-06 + .72071043E-06 .55652452E-06 .39346658E-06 .23252066E-06 .74629737E-07 + -.79308789E-07 -.22844732E-06 -.37199180E-06 -.50920504E-06 -.63940961E-06 + -.76199029E-06 -.87639606E-06 -.98214167E-06 -.10788088E-05 -.11660466E-05 + -.12435721E-05 -.13111700E-05 -.13686922E-05 -.14160567E-05 -.14532461E-05 + -.14803064E-05 -.14973448E-05 -.15045271E-05 -.15020754E-05 -.14902650E-05 + -.14694216E-05 -.14399174E-05 -.14021681E-05 -.13566289E-05 -.13037909E-05 + -.12441768E-05 -.11783371E-05 -.11068459E-05 -.10302970E-05 -.94929926E-06 + -.86447308E-06 -.77644588E-06 -.68584828E-06 -.59331011E-06 -.49945662E-06 + -.40490476E-06 -.31025967E-06 -.21611128E-06 -.12303110E-06 -.31569232E-07 + .57748417E-07 .14442274E-06 .22798375E-06 .30799272E-06 .38404404E-06 + .45576684E-06 .52282633E-06 .58492498E-06 .64180332E-06 .69324058E-06 + .73905504E-06 .77910418E-06 .81328449E-06 .84153118E-06 .86381756E-06 + .88015426E-06 .89058820E-06 .89520145E-06 .89410978E-06 .88746118E-06 + .87543410E-06 .85823565E-06 .83609958E-06 .80928424E-06 .77807038E-06 + .74275888E-06 .70366841E-06 .66113309E-06 .61550004E-06 .56712696E-06 + .51637968E-06 .46362976E-06 .40925205E-06 .35362235E-06 .29711509E-06 + .24010107E-06 .18294532E-06 .12600496E-06 .69627264E-07 .14147759E-07 + -.40111547E-07 -.92843792E-07 -.14375878E-06 -.19258433E-06 -.23906756E-06 + -.28297591E-06 -.32409812E-06 -.36224500E-06 -.39725006E-06 -.42897001E-06 + -.45728507E-06 -.48209916E-06 -.50333994E-06 -.52095868E-06 -.53493001E-06 + -.54525155E-06 -.55194338E-06 -.55504739E-06 -.55462656E-06 -.55076402E-06 + -.54356216E-06 -.53314150E-06 -.51963959E-06 -.50320973E-06 -.48401975E-06 + -.46225056E-06 -.43809484E-06 -.41175555E-06 -.38344448E-06 -.35338073E-06 + -.32178926E-06 -.28889934E-06 -.25494308E-06 -.22015395E-06 -.18476531E-06 + -.14900903E-06 -.11311405E-06 -.77305110E-07 -.41801433E-07 -.68155287E-08 + .27447957E-07 .60793314E-07 .93034769E-07 .12399739E-06 .15351793E-06 + .18144553E-06 .20764243E-06 .23198447E-06 .25436154E-06 .27467801E-06 + .29285294E-06 .30882027E-06 .32252892E-06 .33394275E-06 .34304049E-06 + .34981549E-06 .35427554E-06 .35644241E-06 .35635150E-06 .35405130E-06 + .34960280E-06 .34307888E-06 .33456359E-06 .32415143E-06 .31194653E-06 + .29806180E-06 .28261809E-06 .26574327E-06 .24757131E-06 .22824130E-06 + .20789655E-06 .18668360E-06 .16475125E-06 .14224962E-06 .11932921E-06 + .96139976E-07 .72830407E-07 .49546673E-07 .26431773E-07 .36247299E-08 + -.18740176E-07 -.40534125E-07 -.61634436E-07 -.81925182E-07 -.10129776E-06 + -.11965142E-06 -.13689368E-06 -.15294077E-06 -.16771791E-06 -.18115966E-06 + -.19321005E-06 -.20382276E-06 -.21296125E-06 -.22059870E-06 -.22671807E-06 + -.23131193E-06 -.23438237E-06 -.23594076E-06 -.23600750E-06 -.23461175E-06 + -.23179103E-06 -.22759086E-06 -.22206431E-06 -.21527152E-06 -.20727921E-06 + -.19816014E-06 -.18799253E-06 -.17685950E-06 -.16484845E-06 -.15205045E-06 + -.13855963E-06 -.12447250E-06 -.10988738E-06 -.94903693E-07 -.79621403E-07 + -.64140357E-07 -.48559691E-07 -.32977235E-07 -.17488949E-07 -.21883673E-08 + .12833922E-07 .27490772E-07 .41698943E-07 .55379535E-07 .68458384E-07 + .80866426E-07 .92540020E-07 .10342123E-06 .11345807E-06 .12260472E-06 + .13082167E-06 .13807584E-06 .14434069E-06 .14959622E-06 .15382900E-06 + .15703211E-06 .15920506E-06 .16035369E-06 .16048999E-06 .15963194E-06 + .15780325E-06 .15503317E-06 .15135615E-06 .14681154E-06 .14144331E-06 + .13529963E-06 .12843256E-06 .12089759E-06 .11275333E-06 .10406100E-06 + .94884087E-07 .85287862E-07 .75338981E-07 .65105041E-07 .54654154E-07 + .44054522E-07 .33374019E-07 .22679784E-07 .12037823E-07 .15126319E-08 + -.88331734E-08 -.18939204E-07 -.28747623E-07 -.38203459E-07 -.47254879E-07 + -.55853459E-07 -.63954411E-07 -.71516793E-07 -.78503690E-07 -.84882368E-07 + -.90624396E-07 -.95705746E-07 -.10010686E-06 -.10381269E-06 -.10681271E-06 + -.10910090E-06 -.11067571E-06 -.11153996E-06 -.11170080E-06 -.11116954E-06 + -.10996154E-06 -.10809603E-06 -.10559591E-06 -.10248761E-06 -.98800764E-07 + -.94568078E-07 -.89825012E-07 -.84609535E-07 -.78961853E-07 -.72924121E-07 + -.66540155E-07 -.59855131E-07 -.52915295E-07 -.45767653E-07 -.38459679E-07 + -.31039013E-07 -.23553171E-07 -.16049254E-07 -.85736709E-08 -.11718662E-08 + .61119401E-08 .13235002E-07 .20156282E-07 .26836672E-07 .33239202E-07 + .39329224E-07 .45074589E-07 .50445798E-07 .55416137E-07 .59961796E-07 + .64061959E-07 .67698890E-07 .70857979E-07 .73527788E-07 .75700062E-07 + .77369726E-07 .78534869E-07 .79196695E-07 .79359469E-07 .79030439E-07 + .78219742E-07 .76940295E-07 .75207668E-07 .73039951E-07 .70457594E-07 + .67483252E-07 .64141602E-07 .60459169E-07 .56464125E-07 .52186096E-07 + .47655955E-07 .42905616E-07 .37967819E-07 .32875920E-07 .27663675E-07 + .22365030E-07 .17013912E-07 .11644017E-07 .62886154E-08 .98035002E-09 + -.42489487E-08 -.93684454E-08 -.14348472E-07 -.19160688E-07 -.23778234E-07 + -.28175873E-07 -.32330112E-07 -.36219324E-07 -.39823850E-07 -.43126080E-07 + -.46110537E-07 -.48763931E-07 -.51075210E-07 -.53035587E-07 -.54638563E-07 + -.55879925E-07 -.56757740E-07 -.57272329E-07 -.57426230E-07 -.57224146E-07 + -.56672886E-07 -.55781287E-07 -.54560129E-07 -.53022041E-07 -.51181392E-07 + -.49054178E-07 -.46657901E-07 -.44011436E-07 -.41134893E-07 -.38049481E-07 + -.34777357E-07 -.31341477E-07 -.27765446E-07 -.24073361E-07 -.20289659E-07 + -.16438960E-07 -.12545917E-07 -.86350647E-08 -.47306693E-08 -.85658746E-09 + .29638742E-08 .67080927E-08 .10354256E-07 .13881483E-07 .17269938E-07 + .20500935E-07 .23557035E-07 .26422131E-07 .29081528E-07 .31522012E-07 + .33731907E-07 .35701122E-07 .37421190E-07 .38885296E-07 .40088291E-07 + .41026702E-07 .41698723E-07 .42104208E-07 .42244640E-07 .42123103E-07 + .41744235E-07 .41114181E-07 .40240528E-07 .39132243E-07 .37799593E-07 + .36254067E-07 .34508283E-07 .32575899E-07 .30471515E-07 .28210563E-07 + .25809209E-07 .23284239E-07 .20652949E-07 .17933030E-07 .15142458E-07 + .12299377E-07 .94219886E-08 .65284367E-08 .36367011E-08 .76448864E-09 + -.20708706E-08 -.48525235E-08 -.75641896E-08 -.10190252E-07 -.12715843E-07 + -.15126924E-07 -.17410360E-07 -.19553985E-07 -.21546662E-07 -.23378338E-07 + -.25040091E-07 -.26524161E-07 -.27823991E-07 -.28934240E-07 -.29850805E-07 + -.30570824E-07 -.31092681E-07 -.31415990E-07 -.31541587E-07 -.31471506E-07 + -.31208947E-07 -.30758242E-07 -.30124811E-07 -.29315117E-07 -.28336607E-07 + -.27197656E-07 -.25907504E-07 -.24476182E-07 -.22914446E-07 -.21233696E-07 + -.19445902E-07 -.17563519E-07 -.15599409E-07 -.13566750E-07 -.11478958E-07 + -.93495989E-08 -.71923027E-08 -.50206814E-08 -.28482455E-08 -.68832285E-09 + .14460198E-08 .35420528E-08 .55874571E-08 .75703930E-08 .94795661E-08 + .11304289E-07 .13034536E-07 .14660999E-07 .16175132E-07 .17569192E-07 + .18836275E-07 .19970351E-07 .20966282E-07 .21819848E-07 .22527755E-07 + .23087645E-07 .23498096E-07 .23758620E-07 .23869653E-07 .23832536E-07 + .23649501E-07 .23323639E-07 .22858875E-07 .22259928E-07 .21532276E-07 + .20682107E-07 .19716277E-07 .18642256E-07 .17468077E-07 .16202275E-07 + .14853832E-07 .13432115E-07 .11946814E-07 .10407878E-07 .88254519E-08 + .72098100E-08 .55712944E-08 .39202488E-08 .22669566E-08 .62157842E-09 + -.10059081E-08 -.26057666E-08 -.41685584E-08 -.56851958E-08 -.71469932E-08 + -.85457147E-08 -.98736182E-08 -.11123496E-07 -.12288713E-07 -.13363238E-07 + -.14341672E-07 -.15219277E-07 -.15991990E-07 -.16656444E-07 -.17209978E-07 + -.17650643E-07 -.17977205E-07 -.18189145E-07 -.18286649E-07 -.18270602E-07 + -.18142572E-07 -.17904790E-07 -.17560130E-07 -.17112081E-07 -.16564719E-07 + -.15922676E-07 -.15191103E-07 -.14375631E-07 -.13482331E-07 -.12517674E-07 + -.11488483E-07 -.10401887E-07 -.92652762E-08 -.80862521E-08 -.68725780E-08 + -.56321299E-08 -.43728474E-08 -.31026842E-08 -.18295592E-08 -.56130924E-09 + .69435835E-09 .19299107E-08 .31380331E-08 .43116711E-08 .54440703E-08 + .65288132E-08 .75598547E-08 .85315540E-08 .94387041E-08 .10276558E-07 + .11040851E-07 .11727823E-07 .12334232E-07 .12857371E-07 .13295074E-07 + .13645724E-07 .13908258E-07 .14082165E-07 .14167479E-07 .14164778E-07 + .14075170E-07 .13900281E-07 .13642236E-07 .13303645E-07 .12887576E-07 + .12397533E-07 .11837429E-07 .11211558E-07 .10524561E-07 .97813978E-08 + .89873084E-08 .81477813E-08 .72685147E-08 .63553801E-08 .54143841E-08 + .44516300E-08 .34732798E-08 .24855153E-08 .14945008E-08 .50634509E-09 + -.47293461E-09 -.14374486E-08 -.23814688E-08 -.32994621E-08 -.41861213E-08 + -.50363950E-08 -.58455154E-08 -.66090238E-08 -.73227938E-08 -.79830533E-08 + -.85864022E-08 -.91298293E-08 -.96107260E-08 -.10026897E-07 -.10376569E-07 + atomic pseudo charge-density + .40000000E+01 .39865777E+01 .39466377E+01 .38811433E+01 .37916420E+01 + .36801845E+01 .35492225E+01 .34014950E+01 .32399100E+01 .30674335E+01 + .28869885E+01 .27013712E+01 .25131849E+01 .23247937E+01 .21382919E+01 + .19554911E+01 .17779180E+01 .16068237E+01 .14431992E+01 .12877965E+01 + .11411517E+01 .10036103E+01 .87535141E+00 .75641220E+00 .64671001E+00 + .54606321E+00 .45420994E+00 .37082490E+00 .29553413E+00 .22792793E+00 + .16757210E+00 .11401744E+00 .66807913E-01 .25487409E-01 -.10394612E-01 + -.41278562E-01 -.67591071E-01 -.89742138E-01 -.10812299E+00 -.12310456E+00 + -.13503646E+00 -.14424640E+00 -.15104001E+00 -.15570097E+00 -.15849133E+00 + -.15965211E+00 -.15940402E+00 -.15794831E+00 -.15546772E+00 -.15212749E+00 + -.14807638E+00 -.14344771E+00 -.13836047E+00 -.13292033E+00 -.12722065E+00 + -.12134348E+00 -.11536052E+00 -.10933401E+00 -.10331756E+00 -.97357004E-01 + -.91491144E-01 -.85752437E-01 -.80167666E-01 -.74758549E-01 -.69542302E-01 + -.64532148E-01 -.59737801E-01 -.55165888E-01 -.50820352E-01 -.46702805E-01 + -.42812854E-01 -.39148390E-01 -.35705858E-01 -.32480486E-01 -.29466501E-01 + -.26657315E-01 -.24045694E-01 -.21623904E-01 -.19383841E-01 -.17317148E-01 + -.15415313E-01 -.13669756E-01 -.12071903E-01 -.10613252E-01 -.92854249E-02 + -.80802150E-02 -.69896243E-02 -.60058943E-02 -.51215314E-02 -.43293260E-02 + -.36223673E-02 -.29940535E-02 -.24380983E-02 -.19485349E-02 -.15197159E-02 + -.11463120E-02 -.82330764E-03 -.54599586E-03 -.30997081E-03 -.11111957E-03 + .54387194E-04 .19010535E-03 .29932800E-03 .38509665E-03 .45021268E-03 + .49724900E-03 .52856177E-03 .54630216E-03 .55242795E-03 .54871497E-03 + .53676839E-03 .51803365E-03 .49380712E-03 .46524642E-03 .43338037E-03 + .39911853E-03 .36326031E-03 .32650377E-03 .28945387E-03 .25263036E-03 + .21647525E-03 .18135985E-03 .14759141E-03 .11541928E-03 .85040816E-04 + .56606764E-04 .30226352E-04 .59719919E-05 -.16116354E-04 -.36027141E-04 + -.53773520E-04 -.69389928E-04 -.82928949E-04 -.94458459E-04 -.10405902E-03 + -.11182151E-03 -.11784499E-03 -.12223478E-03 -.12510073E-03 -.12655567E-03 + -.12671407E-03 -.12569076E-03 -.12359997E-03 -.12055430E-03 -.11666399E-03 + -.11203621E-03 -.10677448E-03 -.10097820E-03 -.94742231E-04 -.88156609E-04 + -.81306283E-04 -.74270942E-04 -.67124899E-04 -.59937023E-04 -.52770714E-04 + -.45683928E-04 -.38729233E-04 -.31953896E-04 -.25400000E-04 -.19104585E-04 + -.13099806E-04 -.74131135E-05 -.20674438E-05 .29185776E-05 .75304221E-05 + .11757438E-04 .15592625E-04 .19032404E-04 .22076388E-04 .24727147E-04 + .26989979E-04 .28872677E-04 .30385308E-04 .31539981E-04 .32350635E-04 + .32832821E-04 .33003493E-04 .32880805E-04 .32483918E-04 .31832808E-04 + .30948085E-04 .29850818E-04 .28562372E-04 .27104248E-04 .25497933E-04 + .23764761E-04 .21925781E-04 .20001631E-04 .18012428E-04 .15977661E-04 + .13916095E-04 .11845684E-04 .97834913E-05 .77456253E-05 .57471751E-05 + .38021614E-05 .19234941E-05 .12293798E-06 -.15889121E-05 -.32026485E-05 + -.47100596E-05 -.61041317E-05 -.73790420E-05 -.85301460E-05 -.95539569E-05 + -.10448119E-04 -.11211374E-04 -.11843524E-04 -.12345387E-04 -.12718747E-04 + -.12966301E-04 -.13091602E-04 -.13099000E-04 -.12993572E-04 -.12781064E-04 + -.12467816E-04 -.12060693E-04 -.11567014E-04 -.10994484E-04 -.10351114E-04 + -.96451558E-05 -.88850290E-05 -.80792508E-05 -.72363684E-05 -.63648931E-05 + -.54732369E-05 -.45696518E-05 -.36621723E-05 -.27585615E-05 -.18662606E-05 + -.99234299E-06 -.14347216E-06 .67413606E-06 .14547465E-05 .21931331E-05 + .28846026E-05 .35250133E-05 .41107897E-05 .46389311E-05 .51070171E-05 + .55132071E-05 .58562363E-05 .61354066E-05 .63505743E-05 .65021328E-05 + .65909923E-05 .66185560E-05 .65866927E-05 .64977074E-05 .63543081E-05 + .61595714E-05 .59169057E-05 .56300130E-05 .53028493E-05 .49395841E-05 + .45445596E-05 .41222492E-05 .36772171E-05 .32140765E-05 .27374510E-05 + .22519347E-05 .17620554E-05 .12722380E-05 .78677129E-06 .30977508E-06 + -.15482897E-06 -.60334483E-06 -.10323267E-05 -.14386008E-05 -.18192846E-05 + -.21718029E-05 -.24939006E-05 -.27836530E-05 -.30394730E-05 -.32601147E-05 + -.34446746E-05 -.35925898E-05 -.37036332E-05 -.37779061E-05 -.38158282E-05 + -.38181253E-05 -.37858143E-05 -.37201867E-05 -.36227899E-05 -.34954069E-05 + -.33400340E-05 -.31588583E-05 -.29542334E-05 -.27286543E-05 -.24847319E-05 + -.22251674E-05 -.19527264E-05 -.16702126E-05 -.13804427E-05 -.10862214E-05 + -.79031713E-06 -.49543860E-06 -.20421280E-06 .80835994E-07 .35730573E-06 + .62293455E-06 .87561703E-06 .11134188E-05 .13345890E-05 .15375714E-05 + .17210128E-05 .18837700E-05 .20249147E-05 .21437361E-05 .22397418E-05 + .23126566E-05 .23624198E-05 .23891799E-05 .23932885E-05 .23752919E-05 + .23359216E-05 .22760829E-05 .21968428E-05 .20994165E-05 .19851530E-05 + .18555195E-05 .17120855E-05 .15565066E-05 .13905072E-05 .12158635E-05 + .10343865E-05 .84790465E-06 .65824737E-06 .46722828E-06 .27662940E-06 + .88185931E-07 -.96428306E-07 -.27561447E-06 -.44786132E-06 -.61175681E-06 + -.76599844E-06 -.90940250E-06 -.10409120E-05 -.11596031E-05 -.12646906E-05 + -.13555318E-05 -.14316288E-05 -.14926300E-05 -.15383297E-05 -.15686666E-05 + -.15837213E-05 -.15837121E-05 -.15689899E-05 -.15400323E-05 -.14974360E-05 + -.14419091E-05 -.13742618E-05 -.12953968E-05 -.12062995E-05 -.11080263E-05 + -.10016944E-05 -.88846949E-06 -.76955446E-06 -.64617751E-06 -.51958041E-06 + -.39100686E-06 -.26169110E-06 -.13284687E-06 -.56567587E-08 .11873791E-06 + .23924662E-06 .35483853E-06 .46455060E-06 .56749495E-06 .66286537E-06 + .74994293E-06 .82810073E-06 .89680762E-06 .95563110E-06 .10042391E-05 + .10424010E-05 .10699876E-05 .10869699E-05 .10934176E-05 .10894963E-05 + .10754638E-05 .10516660E-05 .10185318E-05 .97656733E-06 .92634993E-06 + .86852113E-06 .80377954E-06 .73287323E-06 .65659178E-06 .57575821E-06 + .49122066E-06 .40384412E-06 .31450207E-06 .22406824E-06 .13340862E-06 + .43373545E-07 -.45209782E-07 -.13154447E-06 -.21487070E-06 -.29447198E-06 + -.36968088E-06 -.43988425E-06 -.50452780E-06 -.56312000E-06 -.61523545E-06 + -.66051743E-06 -.69867990E-06 -.72950871E-06 -.75286218E-06 -.76867098E-06 + -.77693736E-06 -.77773372E-06 -.77120057E-06 -.75754389E-06 -.73703197E-06 + -.70999169E-06 -.67680437E-06 -.63790116E-06 -.59375810E-06 -.54489085E-06 + -.49184910E-06 -.43521085E-06 -.37557652E-06 -.31356289E-06 -.24979711E-06 + -.18491069E-06 -.11953347E-06 -.54287909E-07 .10216647E-07 .73389332E-07 + .13466292E-06 .19349867E-06 .24939075E-06 .30187039E-06 .35050951E-06 + .39492395E-06 .43477623E-06 .46977785E-06 .49969099E-06 .52432989E-06 + .54356153E-06 .55730595E-06 .56553599E-06 .56827660E-06 .56560363E-06 + .55764217E-06 .54456455E-06 .52658783E-06 .50397094E-06 .47701156E-06 + .44604260E-06 .41142848E-06 .37356115E-06 .33285592E-06 .28974721E-06 + .24468411E-06 .19812594E-06 .15053779E-06 .10238605E-06 .54134036E-07 + .62377485E-08 -.40858297E-07 -.86724999E-07 -.13095241E-06 -.17315324E-06 + -.21296604E-06 -.25005819E-06 -.28412845E-06 -.31490922E-06 -.34216852E-06 + -.36571146E-06 -.38538147E-06 -.40106106E-06 -.41267227E-06 -.42017671E-06 + -.42357521E-06 -.42290716E-06 -.41824948E-06 -.40971522E-06 -.39745192E-06 + -.38163962E-06 -.36248861E-06 -.34023695E-06 -.31514777E-06 -.28750638E-06 + -.25761720E-06 -.22580063E-06 -.19238970E-06 -.15772682E-06 -.12216035E-06 + -.86041260E-07 -.49719795E-07 -.13542196E-07 .22152473E-07 .57035389E-07 + .90790880E-07 .12311917E-06 .15373892E-06 .18238958E-06 .20883345E-06 + .23285758E-06 .25427531E-06 .27292764E-06 .28868422E-06 .30144412E-06 + .31113631E-06 .31771980E-06 .32118358E-06 .32154617E-06 .31885504E-06 + .31318563E-06 .30464021E-06 .29334649E-06 .27945601E-06 .26314228E-06 + .24459889E-06 .22403726E-06 .20168446E-06 .17778076E-06 .15257718E-06 + .12633296E-06 .99313001E-07 .71785264E-07 .44018215E-07 .16278288E-07 + -.11172588E-07 -.38079379E-07 -.64196236E-07 -.89288663E-07 -.11313554E-06 + -.13553101E-06 -.15628613E-06 -.17523044E-06 -.19221325E-06 -.20710472E-06 + -.21979681E-06 -.23020392E-06 -.23826335E-06 -.24393555E-06 -.24720411E-06 + -.24807556E-06 -.24657898E-06 -.24276534E-06 -.23670668E-06 -.22849515E-06 + -.21824179E-06 -.20607522E-06 -.19214012E-06 -.17659568E-06 -.15961382E-06 + -.14137741E-06 -.12207837E-06 -.10191572E-06 -.81093609E-07 -.59819294E-07 + -.38301156E-07 -.16746712E-07 .46393247E-08 .25656936E-07 .46112607E-07 + .65821059E-07 .84606867E-07 .10230597E-06 .11876703E-06 .13385271E-06 + .14744070E-06 .15942470E-06 .16971515E-06 .17823984E-06 .18494433E-06 + .18979218E-06 .19276508E-06 .19386268E-06 .19310238E-06 .19051891E-06 + .18616370E-06 .18010418E-06 .17242290E-06 .16321656E-06 .15259483E-06 + .14067917E-06 .12760150E-06 .11350279E-06 .98531640E-07 .82842700E-07 + .66595175E-07 .49951237E-07 .33074453E-07 .16128219E-07 -.72577625E-09 + -.17329056E-07 -.33527803E-07 -.49174248E-07 -.64127974E-07 -.78257139E-07 + -.91439597E-07 -.10356391E-06 -.11453026E-06 -.12425121E-06 -.13265235E-06 + -.13967283E-06 -.14526574E-06 -.14939835E-06 -.15205219E-06 -.15322310E-06 + -.15292097E-06 -.15116952E-06 -.14800585E-06 -.14347989E-06 -.13765379E-06 + -.13060111E-06 -.12240601E-06 -.11316226E-06 -.10297228E-06 -.91945972E-07 + -.80199652E-07 -.67854818E-07 -.55036943E-07 -.41874230E-07 -.28496367E-07 + -.15033277E-07 -.16138861E-08 .11635077E-07 .24590251E-07 .37132763E-07 + .49149288E-07 .60533043E-07 .71184711E-07 .81013270E-07 .89936746E-07 + .97882862E-07 .10478959E-06 .11060558E-06 .11529055E-06 .11881544E-06 + .12116261E-06 .12232579E-06 .12231003E-06 .12113146E-06 .11881704E-06 + .11540410E-06 .11093987E-06 .10548093E-06 .99092491E-07 .91847710E-07 + .83826869E-07 .75116526E-07 .65808610E-07 .55999479E-07 .45788955E-07 + .35279324E-07 .24574344E-07 .13778238E-07 .29947066E-08 -.76740497E-08 + -.18128276E-07 -.28271574E-07 -.38011770E-07 -.47261731E-07 -.55940124E-07 + -.63972103E-07 -.71289941E-07 -.77833567E-07 -.83551041E-07 -.88398935E-07 + -.92342635E-07 -.95356547E-07 -.97424227E-07 -.98538416E-07 -.98700985E-07 + -.97922800E-07 -.96223506E-07 -.93631217E-07 -.90182152E-07 -.85920176E-07 + -.80896292E-07 -.75168063E-07 -.68798986E-07 -.61857809E-07 -.54417817E-07 + -.46556076E-07 -.38352659E-07 -.29889847E-07 -.21251322E-07 -.12521359E-07 + -.37840174E-08 .48776497E-08 .13382368E-07 .21651391E-07 .29609210E-07 + .37184230E-07 .44309397E-07 .50922773E-07 .56968061E-07 .62395062E-07 + .67160077E-07 .71226235E-07 .74563758E-07 .77150151E-07 .78970324E-07 + .80016644E-07 .80288910E-07 .79794261E-07 .78547019E-07 .76568461E-07 + .73886532E-07 .70535495E-07 .66555530E-07 .61992277E-07 .56896336E-07 + .51322727E-07 .45330316E-07 .38981204E-07 .32340106E-07 .25473698E-07 + .18449969E-07 .11337555E-07 .42050839E-08 -.28794736E-08 -.98494415E-08 + -.16640052E-07 -.23189038E-07 -.29437186E-07 -.35328866E-07 -.40812512E-07 + -.45841055E-07 -.50372323E-07 -.54369371E-07 -.57800775E-07 -.60640853E-07 + -.62869847E-07 -.64474033E-07 -.65445776E-07 -.65783533E-07 -.65491787E-07 + -.64580939E-07 -.63067132E-07 -.60972029E-07 -.58322543E-07 -.55150519E-07 + -.51492371E-07 -.47388682E-07 -.42883771E-07 -.38025227E-07 -.32863421E-07 + -.27450993E-07 -.21842328E-07 -.16093019E-07 -.10259328E-07 -.43976434E-08 + .14360549E-08 .71867203E-08 .12800750E-07 .18226475E-07 .23414627E-07 + .28318775E-07 .32895734E-07 .37105930E-07 .40913739E-07 .44287771E-07 + .47201122E-07 .49631572E-07 .51561743E-07 .52979202E-07 .53876527E-07 + .54251311E-07 .54106131E-07 .53448462E-07 .52290552E-07 .50649243E-07 + .48545767E-07 .46005485E-07 .43057604E-07 .39734853E-07 .36073132E-07 + .32111137E-07 .27889957E-07 .23452663E-07 .18843870E-07 .14109304E-07 + .92953505E-08 .44486096E-08 -.38454644E-09 -.51584109E-08 -.98283672E-08 + -.14351299E-07 -.18685979E-07 -.22793441E-07 -.26637321E-07 -.30184169E-07 + -.33403735E-07 -.36269219E-07 -.38757483E-07 -.40849228E-07 -.42529135E-07 + -.43785962E-07 -.44612604E-07 -.45006116E-07 -.44967688E-07 -.44502592E-07 + -.43620082E-07 -.42333262E-07 -.40658921E-07 -.38617326E-07 -.36231996E-07 + -.33529441E-07 -.30538878E-07 -.27291922E-07 -.23822258E-07 -.20165306E-07 + -.16357859E-07 -.12437720E-07 -.84433384E-08 -.44134316E-08 -.38662064E-09 + .35989364E-08 .75059000E-08 .11298093E-07 .14940832E-07 .18401234E-07 + .21648514E-07 .24654246E-07 .27392612E-07 .29840613E-07 .31978257E-07 + .33788713E-07 .35258437E-07 .36377263E-07 .37138462E-07 .37538764E-07 + .37578356E-07 .37260840E-07 .36593157E-07 .35585490E-07 .34251130E-07 + .32606315E-07 .30670044E-07 .28463867E-07 .26011653E-07 .23339341E-07 + .20474668E-07 .17446888E-07 .14286482E-07 .11024851E-07 .76940136E-08 + .43262926E-08 .95400876E-09 -.23908262E-08 -.56768089E-08 -.88734341E-08 + -.11951374E-07 -.14882742E-07 -.17641344E-07 -.20202900E-07 -.22545264E-07 + -.24648601E-07 -.26495553E-07 -.28071378E-07 -.29364057E-07 -.30364384E-07 + -.31066017E-07 -.31465510E-07 -.31562315E-07 -.31358754E-07 -.30859967E-07 + -.30073833E-07 -.29010868E-07 -.27684093E-07 -.26108889E-07 -.24302823E-07 + -.22285459E-07 -.20078151E-07 -.17703825E-07 -.15186743E-07 -.12552259E-07 + -.98265679E-08 -.70364516E-08 -.42090155E-08 -.13714314E-08 .14493211E-08 + .42267068E-08 .69348812E-08 .95489280E-08 .12045084E-07 .14400953E-07 + .16595700E-07 .18610236E-07 .20427375E-07 .22031979E-07 .23411080E-07 + .24553978E-07 .25452321E-07 .26100155E-07 .26493958E-07 .26632648E-07 + .26517566E-07 .26152438E-07 .25543316E-07 .24698497E-07 .23628420E-07 + .22345546E-07 .20864215E-07 .19200499E-07 .17372025E-07 .15397796E-07 + .13297997E-07 .11093789E-07 .88071036E-08 .64604261E-08 .40765756E-08 + .16784879E-08 -.71100283E-09 -.30693782E-08 -.53746454E-08 -.76055391E-08 + -.97417153E-08 -.11763934E-07 -.13654229E-07 -.15396065E-07 -.16974480E-07 + -.18376205E-07 -.19589781E-07 -.20605640E-07 -.21416183E-07 -.22015826E-07 + -.22401035E-07 -.22570340E-07 -.22524323E-07 -.22265595E-07 -.21798749E-07 + -.21130301E-07 -.20268601E-07 -.19223743E-07 -.18007448E-07 -.16632937E-07 + -.15114794E-07 -.13468809E-07 -.11711822E-07 -.98615529E-08 -.79364227E-08 + -.59553751E-08 -.39376911E-08 -.19028042E-08 .12988462E-09 .21411892E-08 + .41123172E-08 .60250428E-08 .78618736E-08 .96062079E-08 .11242483E-07 + .12756310E-07 .14134601E-07 .15365675E-07 .16439358E-07 .17347061E-07 + .18081847E-07 .18638478E-07 .19013451E-07 .19205011E-07 .19213151E-07 + .19039596E-07 .18687766E-07 .18162730E-07 .17471142E-07 .16621162E-07 + .15622363E-07 .14485631E-07 .13223043E-07 .11847748E-07 .10373827E-07 + .88161544E-08 .71902497E-08 .55121243E-08 .37981263E-08 .20647829E-08 + .32864295E-09 -.13938797E-08 -.30866595E-08 -.47340081E-08 -.63208176E-08 + -.78326971E-08 -.92561016E-08 -.10578451E-07 -.11788240E-07 -.12875136E-07 + -.13830065E-07 -.14645284E-07 -.15314441E-07 -.15832624E-07 -.16196389E-07 + -.16403779E-07 -.16454334E-07 -.16349071E-07 -.16090471E-07 -.15682433E-07 + -.15130227E-07 -.14440433E-07 -.13620859E-07 -.12680467E-07 -.11629267E-07 + 19.8421228800786942 T + Non local Part + 0 2 1.55770284366884382 + 8.48191151414740752 -0.636078516188222226E-01 -0.636078516188222226E-01 0.376965742998787998E-02 + Reciprocal Space Part + .87079657E+01 .86905268E+01 .86383852E+01 .85520639E+01 .84324261E+01 + .82806628E+01 .80982759E+01 .78870568E+01 .76490608E+01 .73865785E+01 + .71021037E+01 .67982989E+01 .64779593E+01 .61439752E+01 .57992933E+01 + .54468791E+01 .50896789E+01 .47305835E+01 .43723936E+01 .40177873E+01 + .36692907E+01 .33292513E+01 .29998152E+01 .26829081E+01 .23802200E+01 + .20931942E+01 .18230205E+01 .15706325E+01 .13367087E+01 .11216776E+01 + .92572621E+00 .74881221E+00 .59067848E+00 .45087066E+00 .32875652E+00 + .22354716E+00 .13431939E+00 .60038835E-01 -.41655140E-03 -.48233192E-01 + -.84639053E-01 -.11088174E+00 -.12820783E+00 -.13784377E+00 -.14097860E+00 + -.13874855E+00 -.13222400E+00 -.12239850E+00 -.11018019E+00 -.96385516E-01 + -.81735140E-01 -.66852083E-01 -.52261834E-01 -.38394355E-01 -.25587745E-01 + -.14093369E-01 -.40822094E-02 .43477954E-02 .11163663E-01 .16388781E-01 + .20094049E-01 .22388976E-01 .23412932E-01 .23326746E-01 .22304805E-01 + .20527794E-01 .18176188E-01 .15424571E-01 .12436845E-01 .93623490E-02 + .63329000E-02 .34607215E-02 .83723118E-03 -.14673812E-02 -.34038583E-02 + -.49429505E-02 -.60739569E-02 -.68028370E-02 -.71499932E-02 -.71478312E-02 + -.68381952E-02 -.62697733E-02 -.54955578E-02 -.45704368E-02 -.35489799E-02 + -.24834728E-02 -.14222372E-02 -.40826592E-03 .52181480E-03 .13384515E-02 + .20195476E-02 .25505425E-02 .29242131E-02 .31402290E-02 .32045017E-02 + .31283679E-02 .29276511E-02 .26216452E-02 .22320639E-02 .17819939E-02 + Real Space Part + .10679849E+02 .10674516E+02 .10658521E+02 .10631882E+02 .10594629E+02 + .10546798E+02 .10488435E+02 .10419590E+02 .10340316E+02 .10250666E+02 + .10150691E+02 .10040442E+02 .99199643E+01 .97892993E+01 .96484877E+01 + .94975699E+01 .93365905E+01 .91656025E+01 .89846735E+01 .87938923E+01 + .85933769E+01 .83832826E+01 .81638104E+01 .79352160E+01 .76978177E+01 + .74520045E+01 .71982421E+01 .69370789E+01 .66691491E+01 .63951751E+01 + .61159665E+01 .58324186E+01 .55455066E+01 .52562794E+01 .49658496E+01 + .46753825E+01 .43860825E+01 .40991787E+01 .38159080E+01 .35374987E+01 + .32651527E+01 .30000279E+01 .27432213E+01 .24957525E+01 .22585487E+01 + .20324314E+01 .18181051E+01 .16161478E+01 .14270049E+01 .12509847E+01 + .10882570E+01 .93885502E+00 .80267855E+00 .67950082E+00 .56897697E+00 + .47065459E+00 .38398603E+00 .30834185E+00 .24302540E+00 .18728774E+00 + .14034296E+00 .10138309E+00 .69592617E-01 .44162070E-01 .24300516E-01 + .92466753E-02 -.17214853E-02 -.92788061E-02 -.14046714E-01 -.16588732E-01 + -.17407693E-01 -.16944568E-01 -.15578795E-01 -.13629958E-01 -.11360623E-01 + -.89801560E-02 -.66492956E-02 -.44852808E-02 -.25673264E-02 -.94224811E-03 + .36993817E-03 .13706046E-02 .20774200E-02 .25196886E-02 .27342003E-02 + .27616467E-02 .26436316E-02 .24202815E-02 .21284366E-02 .18003892E-02 + .14631174E-02 .11379537E-02 .84061912E-03 .58155029E-03 .36644718E-03 + .19697068E-03 .71525435E-04 -.13929925E-04 -.65094077E-04 -.88595362E-04 + Reciprocal Space Part + -.33459269E+02 -.32885812E+02 -.31175324E+02 -.28357261E+02 -.24480084E+02 + -.19610327E+02 -.13831310E+02 -.72415472E+01 .47142272E-01 .79117577E+01 + .16220445E+02 .24834975E+02 .33613317E+02 .42412261E+02 .51090027E+02 + .59508819E+02 .67537255E+02 .75052646E+02 .81943063E+02 .88109160E+02 + .93465720E+02 .97942900E+02 .10148714E+03 .10406175E+03 .10564715E+03 + .10624077E+03 .10585660E+03 .10452449E+03 .10228909E+03 .99208571E+02 + .95353099E+02 .90803154E+02 .85647663E+02 .79982052E+02 .73906232E+02 + .67522572E+02 .60933898E+02 .54241560E+02 .47543611E+02 .40933123E+02 + .34496680E+02 .28313063E+02 .22452162E+02 .16974111E+02 .11928669E+02 + .73548473E+01 .32807727E+01 -.27621319E+00 -.33092347E+01 -.58213610E+01 + -.78249039E+01 -.93405595E+01 -.10396421E+02 -.11026891E+02 -.11271526E+02 + -.11173833E+02 -.10780072E+02 -.10138054E+02 -.92960043E+01 -.83014828E+01 + -.72003946E+01 -.60361114E+01 -.48487123E+01 -.36743572E+01 -.25447982E+01 + -.14870336E+01 -.52310141E+00 .32999049E+00 .10602053E+01 .16603003E+01 + .21275436E+01 .24633402E+01 .26727834E+01 .27641476E+01 .27483410E+01 + .26383351E+01 .24485880E+01 .21944773E+01 .18917574E+01 .15560536E+01 + .12024051E+01 .84486462E+00 .49616263E+00 .16743966E+00 -.13195032E+00 + -.39456569E+00 -.61493394E+00 -.78954326E+00 -.91677435E+00 -.99677914E+00 + -.10313144E+01 -.10235387E+01 -.97778206E+00 -.89929746E+00 -.79400304E+00 + -.66822444E+00 -.52844495E+00 -.38107084E+00 -.23221848E+00 -.87528095E-01 + Real Space Part + .47043595E+03 .47061811E+03 .47114518E+03 .47195957E+03 .47296738E+03 + .47404142E+03 .47502541E+03 .47573899E+03 .47598368E+03 .47554935E+03 + .47422109E+03 .47178640E+03 .46804221E+03 .46280172E+03 .45590085E+03 + .44720395E+03 .43660875E+03 .42405037E+03 .40950423E+03 .39298784E+03 + .37456135E+03 .35432699E+03 .33242725E+03 .30904200E+03 .28438464E+03 + .25869730E+03 .23224536E+03 .20531141E+03 .17818879E+03 .15117498E+03 + .12456500E+03 .98644898E+02 .73685748E+02 .49938027E+02 .27626718E+02 + .69471588E+01 -.11938243E+02 -.28902388E+02 -.43854906E+02 -.56742633E+02 + -.67549163E+02 -.76293525E+02 -.83028062E+02 -.87835614E+02 -.90826098E+02 + -.92132623E+02 -.91907271E+02 -.90316654E+02 -.87537414E+02 -.83751758E+02 + -.79143172E+02 -.73892400E+02 -.68173791E+02 -.62152082E+02 -.55979677E+02 + -.49794451E+02 -.43718116E+02 -.37855127E+02 -.32292132E+02 -.27097928E+02 + -.22323878E+02 -.18004740E+02 -.14159842E+02 -.10794541E+02 -.79018948E+01 + -.54644709E+01 -.34562340E+01 -.18444414E+01 -.59149265E+00 .34331959E+00 + .10021984E+01 .14274044E+01 .16600147E+01 .17388937E+01 .16998820E+01 + .15752010E+01 .13930648E+01 .11774834E+01 .94823819E+00 .72100557E+00 + .50760296E+00 .31633056E+00 .15238184E+00 .18296902E-01 -.85564833E-01 + -.16055420E+00 -.20928196E+00 -.23520343E+00 -.24224903E+00 -.23450846E+00 + -.21597247E+00 -.19033347E+00 -.16084311E+00 -.13022316E+00 -.10062372E+00 + -.73622006E-01 -.50254001E-01 -.31070866E-01 -.16212387E-01 -.54900275E-02 + Non local Part + 1 2 1.55770284366884382 + 2.65859659160385764 -0.504801881867953453E-01 -0.504801881867953453E-01 0.892956271679604986E-02 + Reciprocal Space Part + .00000000E+00 .55360975E+00 .11020032E+01 .16400357E+01 .21627048E+01 + .26652186E+01 .31430596E+01 .35920450E+01 .40083810E+01 .43887098E+01 + .47301505E+01 .50303314E+01 .52874138E+01 .55001078E+01 .56676786E+01 + .57899444E+01 .58672657E+01 .59005262E+01 .58911063E+01 .58408488E+01 + .57520191E+01 .56272596E+01 .54695387E+01 .52820975E+01 .50683934E+01 + .48320418E+01 .45767578E+01 .43062991E+01 .40244089E+01 .37347632E+01 + .34409202E+01 .31462743E+01 .28540152E+01 .25670915E+01 .22881811E+01 + .20196669E+01 .17636193E+01 .15217840E+01 .12955770E+01 .10860853E+01 + .89407229E+00 .71998985E+00 .56399389E+00 .42596477E+00 .30553088E+00 + .20209532E+00 .11486458E+00 .42878783E-01 -.14957234E-01 -.59842780E-01 + -.93050595E-01 -.11589722E+00 -.12971495E+00 -.13582584E+00 -.13551809E+00 + -.13002523E+00 -.12050824E+00 -.10804072E+00 -.93597327E-01 -.78045331E-01 + -.62139262E-01 -.46518532E-01 -.31707803E-01 -.18119864E-01 -.60607310E-02 + .42633380E-02 .12737265E-01 .19327344E-01 .24070560E-01 .27063374E-01 + .28450306E-01 .28412605E-01 .27157313E-01 .24906934E-01 .21889935E-01 + .18332245E-01 .14449871E-01 .10442718E-01 .64896733E-02 .27449375E-02 + -.66440255E-03 -.36396321E-02 -.61105795E-02 -.80348118E-02 -.93959825E-02 + -.10201473E-01 -.10479476E-01 -.10275671E-01 -.96496464E-02 -.86712031E-02 + -.74166865E-02 -.59654538E-02 -.43965915E-02 -.27859668E-02 -.12036827E-02 + .28801366E-03 .16363396E-02 .27990903E-02 .37452630E-02 .44552150E-02 + Real Space Part + .00000000E+00 .64359942E+00 .12860893E+01 .19263130E+01 .25630221E+01 + .31948350E+01 .38202017E+01 .44373750E+01 .50443910E+01 .56390587E+01 + .62189597E+01 .67814592E+01 .73237268E+01 .78427678E+01 .83354645E+01 + .87986250E+01 .92290406E+01 .96235469E+01 .99790905E+01 .10292796E+02 + .10562036E+02 .10784491E+02 .10958218E+02 .11081699E+02 .11153897E+02 + .11174283E+02 .11142876E+02 .11060254E+02 .10927558E+02 .10746490E+02 + .10519290E+02 .10248709E+02 .99379673E+01 .95907014E+01 .92109083E+01 + .88028781E+01 .83711229E+01 .79203026E+01 .74551481E+01 .69803858E+01 + .65006629E+01 .60204776E+01 .55441132E+01 .50755794E+01 .46185613E+01 + .41763765E+01 .37519415E+01 .33477477E+01 .29658468E+01 .26078460E+01 + .22749116E+01 .19677819E+01 .16867871E+01 .14318761E+01 .12026495E+01 + .99839626E+00 .81813432E+00 .66065330E+00 .52455802E+00 .40831211E+00 + .31028032E+00 .22876897E+00 .16206345E+00 .10846228E+00 .66307278E-01 + .34009364E-01 .10069850E-01 -.69027801E-02 -.18180606E-01 -.24908286E-01 + -.28099078E-01 -.28634490E-01 -.27267117E-01 -.24626205E-01 -.21225416E-01 + -.17472311E-01 -.13679034E-01 -.10073742E-01 -.68123372E-02 -.39901212E-02 + -.16530358E-02 .19178102E-03 .15663369E-02 .25131785E-02 .30879320E-02 + .33530317E-02 .33726336E-02 .32086679E-02 .29179506E-02 .25502513E-02 + .21471944E-02 .17418610E-02 .13589554E-02 .10154019E-02 .72124547E-03 + .48074009E-03 .29352474E-03 .15580136E-03 .61447592E-04 .30138377E-05 + Reciprocal Space Part + .00000000E+00 -.26932227E+01 -.52971472E+01 -.77244363E+01 -.98916316E+01 + -.11720983E+02 -.13142152E+02 -.14093748E+02 -.14524661E+02 -.14395175E+02 + -.13677819E+02 -.12357950E+02 -.10434056E+02 -.79177661E+01 -.48335806E+01 + -.12183197E+01 .28796906E+01 .74016747E+01 .12279682E+02 .17438045E+02 + .22794994E+02 .28264383E+02 .33757491E+02 .39184855E+02 .44458102E+02 + .49491724E+02 .54204777E+02 .58522445E+02 .62377462E+02 .65711339E+02 + .68475389E+02 .70631527E+02 .72152827E+02 .73023834E+02 .73240630E+02 + .72810652E+02 .71752282E+02 .70094218E+02 .67874635E+02 .65140188E+02 + .61944855E+02 .58348663E+02 .54416332E+02 .50215862E+02 .45817101E+02 + .41290320E+02 .36704841E+02 .32127729E+02 .27622587E+02 .23248472E+02 + .19058953E+02 .15101330E+02 .11416015E+02 .80360965E+01 .49870782E+01 + .22867940E+01 -.54504994E-01 -.20339040E+01 -.36554301E+01 -.49295269E+01 + -.58724172E+01 -.65053728E+01 -.68539157E+01 -.69469702E+01 -.68159914E+01 + -.64940905E+01 -.60151778E+01 -.54131449E+01 -.47211011E+01 -.39706812E+01 + -.31914370E+01 -.24103219E+01 -.16512754E+01 -.93491359E+00 -.27832313E+00 + .30503924E+00 .80534852E+00 .12163201E+01 .15350341E+01 .17616860E+01 + .18992752E+01 .19532440E+01 .19310803E+01 .18418981E+01 .16960073E+01 + .15044873E+01 .12787746E+01 .10302757E+01 .77001425E+00 .50831954E+00 + .25456290E+00 .16945576E-01 -.19765940E+00 -.38381089E+00 -.53754978E+00 + -.65639825E+00 -.73931205E+00 -.78659086E+00 -.79975259E+00 -.78137851E+00 + Real Space Part + .00000000E+00 .32174412E+02 .64081200E+02 .95454901E+02 .12603438E+03 + .15556504E+03 .18380101E+03 .21050740E+03 .23546257E+03 .25846040E+03 + .27931254E+03 .29785062E+03 .31392841E+03 .32742382E+03 .33824076E+03 + .34631080E+03 .35159451E+03 .35408254E+03 .35379625E+03 .35078802E+03 + .34514103E+03 .33696853E+03 .32641275E+03 .31364309E+03 .29885400E+03 + .28226227E+03 .26410388E+03 .24463049E+03 .22410561E+03 .20280043E+03 + .18098955E+03 .15894661E+03 .13693992E+03 .11522816E+03 .94056367E+02 + .73652166E+02 .54222369E+02 .35950069E+02 .18992243E+02 .34779240E+01 + -.10493014E+02 -.22850445E+02 -.33553946E+02 -.42592145E+02 -.49981475E+02 + -.55764394E+02 -.60007127E+02 -.62796996E+02 -.64239417E+02 -.64454665E+02 + -.63574472E+02 -.61738574E+02 -.59091275E+02 -.55778129E+02 -.51942809E+02 + -.47724232E+02 -.43254004E+02 -.38654223E+02 -.34035686E+02 -.29496509E+02 + -.25121167E+02 -.20979967E+02 -.17128906E+02 -.13609921E+02 -.10451462E+02 + -.76693710E+01 -.52679941E+01 -.32414933E+01 -.15752887E+01 -.24758462E+00 + .76907715E+00 .15062828E+01 .19982770E+01 .22805946E+01 .23888267E+01 + .23575419E+01 .22193827E+01 .20043426E+01 .17392288E+01 .14473034E+01 + .11480951E+01 .85736431E+00 .58720519E+00 .34626103E+00 .14003133E+00 + -.28753785E-01 -.15971487E+00 -.25438251E+00 -.31575466E+00 -.34786993E+00 + -.35541133E+00 -.34335220E+00 -.31665261E+00 -.28001124E+00 -.23767485E+00 + -.19330460E+00 -.14989599E+00 -.10974754E+00 -.74471444E-01 -.45038872E-01 + PAW radial sets + 323 0.989218471734281124 +(5E20.12) + augmentation charges (non sperical) + -.118612867153E+00 -.756362247412E-03 -.532145531503E-01 -.130926919871E-02 -.756362247412E-03 + -.210856503823E-04 -.122603249007E-03 .363423839020E-05 -.532145531503E-01 -.122603249007E-03 + -.179689875812E-01 -.555432069872E-03 -.130926919871E-02 .363423839020E-05 -.555432069872E-03 + .498671741032E-04 + uccopancies in atom + .200000000162E+01 .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 + .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 + .666666667141E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 + .000000000000E+00 + grid + .353278105438E-04 .364765828105E-04 .376627102856E-04 .388874076671E-04 .401519291522E-04 + .414575697215E-04 .428056664648E-04 .441975999512E-04 .456347956421E-04 .471187253514E-04 + .486509087530E-04 .502329149365E-04 .518663640144E-04 .535529287814E-04 .552943364272E-04 + .570923703053E-04 .589488717596E-04 .608657420098E-04 .628449440985E-04 .648885049016E-04 + .669985172040E-04 .691771418426E-04 .714266099194E-04 .737492250864E-04 .761473659044E-04 + .786234882792E-04 .811801279764E-04 .838199032186E-04 .865455173661E-04 .893597616862E-04 + .922655182109E-04 .952657626888E-04 .983635676325E-04 .101562105465E-03 .104864651768E-03 + .108274588638E-03 .111795408149E-03 .115430715926E-03 .119184234844E-03 .123059808833E-03 + .127061406819E-03 .131193126789E-03 .135459199986E-03 .139863995240E-03 .144412023447E-03 + .149107942186E-03 .153956560487E-03 .158962843759E-03 .164131918874E-03 .169469079417E-03 + .174979791106E-03 .180669697392E-03 .186544625235E-03 .192610591076E-03 .198873806993E-03 + .205340687067E-03 .212017853948E-03 .218912145639E-03 .226030622496E-03 .233380574462E-03 + .240969528530E-03 .248805256452E-03 .256895782699E-03 .265249392676E-03 .273874641209E-03 + .282780361308E-03 .291975673207E-03 .301469993709E-03 .311273045829E-03 .321394868748E-03 + .331845828098E-03 .342636626573E-03 .353778314896E-03 .365282303127E-03 .377160372357E-03 + .389424686766E-03 .402087806084E-03 .415162698451E-03 .428662753701E-03 .442601797068E-03 + .456994103352E-03 .471854411533E-03 .487197939863E-03 .503040401457E-03 .519398020380E-03 + .536287548263E-03 .553726281459E-03 .571732078754E-03 .590323379658E-03 .609519223288E-03 + .629339267864E-03 .649803810846E-03 .670933809712E-03 .692750903429E-03 .715277434606E-03 + .738536472381E-03 .762551836040E-03 .787348119413E-03 .812950716063E-03 .839385845286E-03 + .866680578963E-03 .894862869287E-03 .923961577387E-03 .954006502881E-03 .985028414399E-03 + .101705908109E-02 .105013130516E-02 .108427895544E-02 .111953700213E-02 .115594155253E-02 + .119352988810E-02 .123234050257E-02 .127241314140E-02 .131378884247E-02 .135650997813E-02 + .140062029854E-02 .144616497653E-02 .149319065382E-02 .154174548883E-02 .159187920594E-02 + .164364314647E-02 .169709032120E-02 .175227546473E-02 .180925509145E-02 .186808755348E-02 + .192883310041E-02 .199155394099E-02 .205631430683E-02 .212318051821E-02 .219222105197E-02 + .226350661166E-02 .233711019991E-02 .241310719324E-02 .249157541920E-02 .257259523611E-02 + .265624961535E-02 .274262422631E-02 .283180752413E-02 .292389084032E-02 .301896847624E-02 + .311713779968E-02 .321849934462E-02 .332315691413E-02 .343121768671E-02 .354279232604E-02 + .365799509430E-02 .377694396919E-02 .389976076474E-02 .402657125610E-02 .415750530828E-02 + .429269700920E-02 .443228480697E-02 .457641165169E-02 .472522514185E-02 .487887767547E-02 + .503752660617E-02 .520133440431E-02 .537046882339E-02 .554510307185E-02 .572541599040E-02 + .591159223525E-02 .610382246712E-02 .630230354657E-02 .650723873558E-02 .671883790569E-02 + .693731775293E-02 .716290201977E-02 .739582172419E-02 .763631539635E-02 .788462932276E-02 + .814101779859E-02 .840574338805E-02 .867907719326E-02 .896129913194E-02 .925269822400E-02 + .955357288758E-02 .986423124464E-02 .101849914365E-01 .105161819495E-01 .108581419519E-01 + .112112216404E-01 .115757825996E-01 .119521981717E-01 .123408538391E-01 .127421476193E-01 + .131564904721E-01 .135843067208E-01 .140260344867E-01 .144821261375E-01 .149530487510E-01 + .154392845931E-01 .159413316118E-01 .164597039470E-01 .169949324574E-01 .175475652638E-01 + .181181683104E-01 .187073259445E-01 .193156415151E-01 .199437379906E-01 .205922585965E-01 + .212618674747E-01 .219532503631E-01 .226671152982E-01 .234041933402E-01 .241652393213E-01 + .249510326191E-01 .257623779547E-01 .266001062165E-01 .274650753115E-01 .283581710436E-01 + .292803080210E-01 .302324305924E-01 .312155138146E-01 .322305644506E-01 .332786220011E-01 + .343607597686E-01 .354780859567E-01 .366317448050E-01 .378229177610E-01 .390528246900E-01 + .403227251240E-01 .416339195521E-01 .429877507520E-01 .443856051652E-01 .458289143166E-01 + .473191562810E-01 .488578571964E-01 .504465928270E-01 .520869901769E-01 .537807291563E-01 + .555295443019E-01 .573352265534E-01 .591996250870E-01 .611246492098E-01 .631122703148E-01 + .651645238996E-01 .672835116512E-01 .694714035982E-01 .717304403333E-01 .740629353074E-01 + .764712771991E-01 .789579323611E-01 .815254473456E-01 .841764515121E-01 .869136597208E-01 + .897398751118E-01 .926579919768E-01 .956709987225E-01 .987819809310E-01 .101994124520E+00 + .105310719005E+00 .108735160869E+00 .112270957040E+00 .115921728481E+00 .119691213902E+00 + .123583273585E+00 .127601893339E+00 .131751188583E+00 .136035408556E+00 .140458940676E+00 + .145026315024E+00 .149742208992E+00 .154611452068E+00 .159639030781E+00 .164830093811E+00 + .170189957261E+00 .175724110099E+00 .181438219781E+00 .187338138056E+00 .193429906954E+00 + .199719764979E+00 .206214153496E+00 .212919723327E+00 .219843341560E+00 .226992098585E+00 + .234373315355E+00 .241994550880E+00 .249863609972E+00 .257988551235E+00 .266377695319E+00 + .275039633439E+00 .283983236179E+00 .293217662568E+00 .302752369466E+00 .312597121246E+00 + .322761999795E+00 .333257414835E+00 .344094114590E+00 .355283196787E+00 .366836120023E+00 + .378764715502E+00 .391081199148E+00 .403798184116E+00 .416928693710E+00 .430486174720E+00 + .444484511190E+00 .458938038641E+00 .473861558747E+00 .489270354497E+00 .505180205845E+00 + .521607405869E+00 .538568777456E+00 .556081690535E+00 .574164079857E+00 .592834463369E+00 + .612111961177E+00 .632016315122E+00 .652567909002E+00 .673787789445E+00 .695697687463E+00 + .718320040705E+00 .741678016440E+00 .765795535274E+00 .790697295655E+00 .816408799161E+00 + .842956376619E+00 .870367215068E+00 .898669385601E+00 .927891872115E+00 .958064600989E+00 + .989218471734E+00 .102138538864E+01 .105459829343E+01 + aepotential + .249296618412E+05 .247076583257E+05 .244443255599E+05 .241414371172E+05 .238011681064E+05 + .234259054160E+05 .230182276498E+05 .225808680933E+05 .221166790321E+05 .216285959644E+05 + .211196020425E+05 .205926935296E+05 .200508469868E+05 .194969885786E+05 .189339660140E+05 + .183645234482E+05 .177912796436E+05 .172167095020E+05 .166431291099E+05 .160726841798E+05 + .155073419145E+05 .149488860093E+05 .143989147023E+05 .138588415092E+05 .133298984061E+05 + .128131411287E+05 .123094562646E+05 .118195698156E+05 .113440569063E+05 .108833523432E+05 + .104377617399E+05 .100074729506E+05 .959256758265E+04 .919303239296E+04 .880877039590E+04 + .843961154725E+04 .808532289425E+04 .774561810756E+04 .742016634235E+04 .710860038888E+04 + .681052409519E+04 .652551907131E+04 .625315067621E+04 .599297332353E+04 .574453513086E+04 + .550738195528E+04 .528106086162E+04 .506512306412E+04 .485912638819E+04 .466263730249E+04 + .447523256840E+04 .429650053920E+04 .412604216570E+04 .396347173509E+04 .380841738005E+04 + .366052140119E+04 .351944041296E+04 .338484535875E+04 .325642140535E+04 .313386774487E+04 + .301689731751E+04 .290523647712E+04 .279862460324E+04 .269681368551E+04 .259956787532E+04 + .250666302499E+04 .241788621528E+04 .233303528113E+04 .225191833487E+04 .217435329790E+04 + .210016743837E+04 .202919692087E+04 .196128636819E+04 .189628843674E+04 .183406340726E+04 + .177447879164E+04 .171740895648E+04 .166273476188E+04 .161034321676E+04 .156012715054E+04 + .151198490272E+04 .146582002337E+04 .142154099431E+04 .137906095998E+04 .133829747604E+04 + .129917226882E+04 .126161100972E+04 .122554310047E+04 .119090147066E+04 .115762238690E+04 + .112564527212E+04 .109491253468E+04 .106536940758E+04 .103696379654E+04 .100964613669E+04 + .983369256582E+03 .958088251357E+03 .933760361363E+03 .910344858922E+03 .887802940737E+03 + .866097626532E+03 .845193663442E+03 .825057435693E+03 .805656879371E+03 .786961401872E+03 + .768941805860E+03 .751570217559E+03 .734820018832E+03 .718665782978E+03 .703083214326E+03 + .688049090980E+03 .673541210507E+03 .659538338921E+03 .646020162215E+03 .632967240499E+03 + .620360964749E+03 .608183515718E+03 .596417825223E+03 .585047539244E+03 .574056983177E+03 + .563431128839E+03 .553155563184E+03 .543216458754E+03 .533600545498E+03 .524295084194E+03 + .515287841173E+03 .506567064354E+03 .498121460542E+03 .489940173731E+03 .482012764716E+03 + .474329191586E+03 .466879791201E+03 .459655261667E+03 .452646645612E+03 .445845314309E+03 + .439242952579E+03 .432831544450E+03 .426603359477E+03 .420550939758E+03 .414667087568E+03 + .408944853585E+03 .403377525679E+03 .397958618253E+03 .392681862072E+03 .387541194587E+03 + .382530750726E+03 .377644854114E+03 .372878008707E+03 .368224890830E+03 .363680341587E+03 + .359239359657E+03 .354897094389E+03 .350648839276E+03 .346490025719E+03 .342416217091E+03 + .338423103118E+03 .334506494502E+03 .330662317854E+03 .326886610852E+03 .323175517677E+03 + .319525284662E+03 .315932256206E+03 .312392870893E+03 .308903657842E+03 .305461233272E+03 + .302062297267E+03 .298703630762E+03 .295382092719E+03 .292094617500E+03 .288838212437E+03 + .285609955593E+03 .282406993707E+03 .279226540330E+03 .276065874141E+03 .272922337452E+03 + .269793334886E+03 .266676332242E+03 .263568855544E+03 .260468490264E+03 .257372880728E+03 + .254279729706E+03 .251186798183E+03 .248091905310E+03 .244992928548E+03 .241887803987E+03 + .238774526866E+03 .235651152274E+03 .232515796051E+03 .229366635883E+03 .226201912602E+03 + .223019931688E+03 .219819064985E+03 .216597752635E+03 .213354505238E+03 .210087906247E+03 + .206796614606E+03 .203479367655E+03 .200134984304E+03 .196762368500E+03 .193360513013E+03 + .189928503567E+03 .186465523338E+03 .182970857876E+03 .179443900479E+03 .175884158076E+03 + .172291257693E+03 .168664953559E+03 .165005134953E+03 .161311834879E+03 .157585239680E+03 + .153825699735E+03 .150033741355E+03 .146210080040E+03 .142355635261E+03 .138471546918E+03 + .134559193631E+03 .130620212984E+03 .126656523815E+03 .122670350542E+03 .118664249404E+03 + .114641136335E+03 .110604315898E+03 .106557510391E+03 .102504887754E+03 .984510863142E+02 + .944012336261E+02 .903609557846E+02 .863363724670E+02 .823340718078E+02 .783610579892E+02 + .744246633582E+02 .705324162159E+02 .666918555610E+02 .629102856287E+02 .591944669183E+02 + .555502477826E+02 .519821532120E+02 .484929672536E+02 .450833747318E+02 .417517679306E+02 + .384943726247E+02 .353058986338E+02 .321809414460E+02 .291163276325E+02 .261144334538E+02 + .231871492547E+02 .203596538297E+02 .176726025177E+02 .151810751243E+02 .129490421749E+02 + .110393419236E+02 .950085943829E+01 .835601596774E+01 .759220035195E+01 .716026979128E+01 + .698171586735E+01 .696337537316E+01 .701521042419E+01 .706481632887E+01 .706399956522E+01 + .698712622280E+01 .682461424434E+01 .657568967629E+01 .624298209986E+01 .582958804938E+01 + .533805380599E+01 .477041519949E+01 .412860165824E+01 .341481131402E+01 .263171136544E+01 + .178246368857E+01 .870634878579E+00 -.999438728779E-01 -.112531868169E+01 -.220152969452E+01 + -.332469269108E+01 -.449104609659E+01 -.569696875391E+01 -.693897492955E+01 -.821369210611E+01 + -.951782536530E+01 -.108481102767E+02 -.122012545007E+02 -.135738669876E+02 -.149623728146E+02 + -.163629115444E+02 -.177712178383E+02 -.191824854283E+02 -.205912200739E+02 -.219910944781E+02 + -.233748284178E+02 -.247341312735E+02 -.260597521130E+02 -.273417019240E+02 -.285696929862E+02 + -.297338408481E+02 -.308256300402E+02 -.318391145291E+02 -.327722934381E+02 -.336286096960E+02 + -.344184453032E+02 -.351602594335E+02 -.358801411316E+02 -.366068307978E+02 -.373574862777E+02 + -.381118849160E+02 -.387867273418E+02 -.392441857634E+02 -.393634904186E+02 -.391349287009E+02 + -.386756216504E+02 -.381417407639E+02 -.376357898778E+02 -.371876084285E+02 -.367857308718E+02 + -.364089017521E+02 -.360404072746E+02 -.356705440643E+02 -.352947736909E+02 -.349113812250E+02 + -.345198086599E+02 -.341197549222E+02 -.337108274651E+02 + core charge-density + .566100405752E-04 .603274790726E-04 .642889041986E-04 .685103164325E-04 .730087642691E-04 + .778024127357E-04 .829106163764E-04 .883539969928E-04 .941545264508E-04 .100335614880E-03 + .106922204616E-03 .113940870262E-03 .121419925256E-03 .129389535376E-03 .137881839620E-03 + .146931078955E-03 .156573733420E-03 .166848668143E-03 .177797288839E-03 .189463707397E-03 + .201894918215E-03 .215140985966E-03 .229255245539E-03 .244294514933E-03 .260319321939E-03 + .277394145493E-03 .295587672651E-03 .314973072166E-03 .335628285763E-03 .357636338214E-03 + .381085667437E-03 .406070475885E-03 .432691104597E-03 .461054431344E-03 .491274294413E-03 + .523471943665E-03 .557776520581E-03 .594325569167E-03 .633265579655E-03 .674752567074E-03 + .718952686923E-03 .766042890258E-03 .816211620710E-03 .869659556058E-03 .926600397160E-03 + .987261707239E-03 .105188580466E-02 .112073071253E-02 .119407116880E-02 .127219970037E-02 + .135542776555E-02 .144408696885E-02 .153853035261E-02 .163913377046E-02 .174629734739E-02 + .186044703187E-02 .198203624583E-02 .211154763822E-02 .224949494879E-02 .239642498860E-02 + .255291974450E-02 .271959861504E-02 .289712078585E-02 .308618775280E-02 .328754600198E-02 + .350198985578E-02 .373036449505E-02 .397356916791E-02 .423256059621E-02 .450835659128E-02 + .480203989148E-02 .511476223442E-02 .544774867755E-02 .580230218169E-02 .617980847259E-02 + .658174119662E-02 .700966738736E-02 .746525326090E-02 .795027035842E-02 .846660205552E-02 + .901625045908E-02 .960134371288E-02 .102241437348E-01 .108870544090E-01 .115926302582E-01 + .123435856218E-01 .131428043661E-01 .139933501568E-01 .148984773211E-01 .158616423311E-01 + .168865159410E-01 .179769960102E-01 .191372210475E-01 .203715845116E-01 .216847499059E-01 + .230816667048E-01 .245675871519E-01 .261480839698E-01 .278290690246E-01 .296168129868E-01 + .315179660337E-01 .335395796374E-01 .356891294839E-01 .379745395704E-01 .404042075275E-01 + .429870312127E-01 .457324366235E-01 .486504071769E-01 .517515144015E-01 .550469500898E-01 + .585485599535E-01 .622688788272E-01 .662211674610E-01 .704194509412E-01 .748785587749E-01 + .796141666712E-01 .846428400460E-01 .899820792747E-01 .956503667062E-01 .101667215451E+00 + .108053219945E+00 .114830108271E+00 .122020796239E+00 .129649443177E+00 .137741509388E+00 + .146323815234E+00 .155424601742E+00 .165073592657E+00 .175302057823E+00 .186142877738E+00 + .197630609132E+00 .209801551371E+00 .222693813452E+00 .236347381338E+00 .250804185329E+00 + .266108167138E+00 .282305346272E+00 .299443885308E+00 .317574153560E+00 .336748788604E+00 + .357022755061E+00 .378453399961E+00 .401100503966E+00 .425026327615E+00 .450295651730E+00 + .476975810973E+00 .505136719518E+00 .534850887654E+00 .566193428081E+00 .599242050517E+00 + .634077043169E+00 .670781239474E+00 .709439968420E+00 .750140986642E+00 .792974390370E+00 + .838032505174E+00 .885409751349E+00 .935202482669E+00 .987508796104E+00 .104242831002E+01 + .110006190827E+01 .116051144745E+01 .122387942461E+01 .129026860260E+01 .135978159017E+01 + .143252037390E+01 .150858579919E+01 .158807699749E+01 .167109075688E+01 .175772083353E+01 + .184805720162E+01 .194218523933E+01 .204018484914E+01 .214212951079E+01 .224808526583E+01 + .235810963304E+01 .247225045485E+01 .259054467535E+01 .271301705146E+01 .283967879975E+01 + .297052618226E+01 .310553903613E+01 .324467925296E+01 .338788921520E+01 .353509019870E+01 + .368618075190E+01 .384103506433E+01 .399950133877E+01 .416140018359E+01 .432652304404E+01 + .449463069343E+01 .466545180749E+01 .483868164752E+01 .501398088047E+01 .519097456619E+01 + .536925134438E+01 .554836285615E+01 .572782343649E+01 .590711011606E+01 .608566297177E+01 + .626288586635E+01 .643814761788E+01 .661078363938E+01 .678009808823E+01 .694536656274E+01 + .710583938103E+01 .726074547323E+01 .740929691345E+01 .755069411170E+01 .768413167876E+01 + .780880496809E+01 .792391728912E+01 .802868777438E+01 .812235987040E+01 .820421040778E+01 + .827355919064E+01 .832977902881E+01 .837230611874E+01 .840065066096E+01 .841440758325E+01 + .841326722016E+01 .839702578152E+01 .836559542526E+01 .831901373419E+01 .825745238298E+01 + .818122477058E+01 .809079238605E+01 .798676967249E+01 .786992715557E+01 .774119261011E+01 + .760165005169E+01 .745253636003E+01 .729523536819E+01 .713126928576E+01 .696228736593E+01 + .679005177517E+01 .661642067944E+01 .644332862203E+01 .627276433335E+01 .610674618159E+01 + .594729554133E+01 .579640842184E+01 .565602576681E+01 .552800287068E+01 .541407839925E+01 + .531584353892E+01 .523471177953E+01 .517188984282E+01 .512835026211E+01 .510480613184E+01 + .510168858572E+01 .511912762968E+01 .515693703459E+01 .521460405617E+01 .529128475754E+01 + .538580562001E+01 .549667189770E+01 .562208280769E+01 .575995323743E+01 .590794134470E+01 + .606348131935E+01 .622382063669E+01 .638606123530E+01 .654720408632E+01 .670419655739E+01 + .685398184633E+01 .699354961718E+01 .711998685544E+01 .723052788809E+01 .732260249172E+01 + .739388103439E+01 .744231565540E+01 .746617657427E+01 .746408272963E+01 .743502607482E+01 + .737838899666E+01 .729395447390E+01 .718190874815E+01 .704283644131E+01 .687770821462E+01 + .668786122365E+01 .647497277612E+01 .624102774402E+01 .598828041327E+01 .571921157222E+01 + .543648174187E+01 .514288153425E+01 .484128019032E+01 .453457339482E+01 .422563149315E+01 + .391724924503E+01 .361209824281E+01 .331268309860E+01 .302130245731E+01 .274001582420E+01 + .247061708263E+01 .221461541805E+01 .197322413413E+01 .174735759662E+01 .153763606876E+01 + .134439807766E+01 .116771931577E+01 .100743688382E+01 .863177180939E+00 .734385201328E+00 + .620352489207E+00 .520241312105E+00 .433105012361E+00 .357908953755E+00 .293558971531E+00 + .238939332961E+00 .192952602310E+00 .154550561105E+00 .122752025089E+00 .966509456742E-01 + .754197389551E-01 .583105713293E-01 .446553155083E-01 .338641489723E-01 .254227504169E-01 + .188882123217E-01 .138839144900E-01 .100936595806E-01 + kinetic energy-density + .667223264162E+01 .673711797765E+01 .680446051695E+01 .687434851945E+01 .694687595542E+01 + .702214224715E+01 .710025264340E+01 .718131851959E+01 .726545770326E+01 .735279480889E+01 + .744346157547E+01 .753759722098E+01 .763534880551E+01 .773687160651E+01 .784232950769E+01 + .795189540556E+01 .806575163262E+01 .818409040251E+01 .830711427710E+01 .843503666033E+01 + .856808232008E+01 .870648794174E+01 .885050271727E+01 .900038897044E+01 .915642282528E+01 + .931889491632E+01 .948811114834E+01 .966439350589E+01 .984808091773E+01 .100395301784E+02 + .102391169326E+02 .104472367229E+02 .106643061077E+02 .108907638526E+02 .111270721976E+02 + .113737182071E+02 .116312152061E+02 .119001043069E+02 .121809560330E+02 .124743720445E+02 + .127809869719E+02 .131014703626E+02 .134365287498E+02 .137869078483E+02 .141533948854E+02 + .145368210760E+02 .149380642484E+02 .153580516325E+02 .157977628176E+02 .162582328917E+02 + .167405557713E+02 .172458877376E+02 .177754511847E+02 .183305385986E+02 .189125167802E+02 + .195228313211E+02 .201630113570E+02 .208346746071E+02 .215395327218E+02 .222793969540E+02 + .230561841768E+02 .238719232645E+02 .247287618625E+02 .256289735654E+02 .265749655308E+02 + .275692865534E+02 .286146356255E+02 .297138710144E+02 .308700198863E+02 .320862885081E+02 + .333660730613E+02 .347129711045E+02 .361307937197E+02 .376235783832E+02 .391956026049E+02 + .408513983733E+02 .425957674600E+02 .444337976250E+02 .463708797814E+02 .484127261615E+02 + .505653895529E+02 .528352836548E+02 .552292046175E+02 .577543538336E+02 .604183620400E+02 + .632293148117E+02 .661957795124E+02 .693268337816E+02 .726320956402E+02 .761217552952E+02 + .798066087313E+02 .836980931813E+02 .878083245648E+02 .921501369964E+02 .967371244646E+02 + .101583684778E+03 .106705065895E+03 .112117414743E+03 .117837828637E+03 .123884409424E+03 + .130276320461E+03 .137033846552E+03 .144178456977E+03 .151732871716E+03 .159721131020E+03 + .168168668441E+03 .177102387447E+03 .186550741762E+03 .196543819548E+03 .207113431542E+03 + .218293203301E+03 .230118671632E+03 .242627385346E+03 .255859010429E+03 .269855439723E+03 + .284660907211E+03 .300322106967E+03 .316888316840E+03 .334411526903E+03 .352946572698E+03 + .372551273268E+03 .393286573957E+03 .415216693909E+03 .438409278191E+03 .462935554406E+03 + .488870493624E+03 .516292975418E+03 .545285956739E+03 .575936644299E+03 .608336670067E+03 + .642582269425E+03 .678774461430E+03 .717019230563E+03 .757427709234E+03 .800116360219E+03 + .845207158092E+03 .892827768584E+03 .943111724662E+03 .996198598018E+03 .105223416443E+04 + .111137056136E+04 .117376643592E+04 .123958708122E+04 .130900455875E+04 .138219780446E+04 + .145935271573E+04 .154066221641E+04 .162632629657E+04 .171655202365E+04 .181155352120E+04 + .191155191114E+04 .201677521519E+04 .212745821087E+04 .224384223707E+04 .236617494387E+04 + .249470998100E+04 .262970661903E+04 .277142929698E+04 .292014708990E+04 .307613308942E+04 + .323966369031E+04 .341101777559E+04 .359047579274E+04 .377831871320E+04 .397482686744E+04 + .418027864771E+04 .439494907065E+04 .461910819220E+04 .485301936717E+04 .509693734651E+04 + .535110620572E+04 .561575709823E+04 .589110582872E+04 .617735024215E+04 .647466742549E+04 + .678321072048E+04 .710310654759E+04 .743445104313E+04 .777730651347E+04 .813169771335E+04 + .849760795736E+04 .887497507731E+04 .926368724144E+04 .966357865505E+04 .100744251666E+05 + .104959398071E+05 .109277682965E+05 .113694845538E+05 .118205862555E+05 .122804904900E+05 + .127485295625E+05 .132239470112E+05 .137058938992E+05 .141934254546E+05 .146854981352E+05 + .151809671997E+05 .156785848725E+05 .161769991918E+05 .166747536369E+05 .171702876279E+05 + .176619379985E+05 .181479415367E+05 .186264386884E+05 .190954785183E+05 .195530250094E+05 + .199969647834E+05 .204251163067E+05 .208352406373E+05 .212250537526E+05 .215922404774E+05 + .219344700116E+05 .222494130342E+05 .225347603288E+05 .227882428528E+05 .230076531342E+05 + .231908678498E+05 .233358714016E+05 .234407802719E+05 .235038678982E+05 .235235897755E+05 + .234986084530E+05 .234278180618E+05 .233103679754E+05 .231456851799E+05 .229334949056E+05 + .226738390590E+05 .223670919806E+05 .220139730591E+05 .216155557379E+05 .211732724746E+05 + .206889152456E+05 .201646312393E+05 .196029134408E+05 .190065858947E+05 .183787835298E+05 + .177229265428E+05 .170426894747E+05 .163419652635E+05 .156248247191E+05 .148954720435E+05 + .141581971857E+05 .134173261542E+05 .126771693102E+05 .119419713654E+05 .112158605938E+05 + .105028007380E+05 .980654499989E+04 .913059236999E+04 .847814611827E+04 .785207438837E+04 + .725487344929E+04 .668863511301E+04 .615502069364E+04 .565524417361E+04 .519006672766E+04 + .475980357784E+04 .436434266402E+04 .400317320563E+04 .367542131406E+04 .337988973053E+04 + .311509948092E+04 .287933226802E+04 .267067318949E+04 .248705363715E+04 .232629412847E+04 + .218614659385E+04 .206433545994E+04 .195859678351E+04 .186671469198E+04 .178655445016E+04 + .171609157853E+04 .165343658116E+04 .159685499112E+04 .154478259599E+04 .149583585719E+04 + .144881767535E+04 .140271877451E+04 .135671507596E+04 .131016150708E+04 .126258274155E+04 + .121366139499E+04 .116322420862E+04 .111122674356E+04 .105773708455E+04 .100291901627E+04 + .947015091482E+03 .890329959869E+03 .833214272270E+03 .776049418457E+03 .719233299337E+03 + .663167278558E+03 .608244406410E+03 .554838966220E+03 .503297358442E+03 .453930336633E+03 + .407006601755E+03 .362747806752E+03 .321325033168E+03 .282856907413E+03 .247409252478E+03 + .214996590257E+03 .185585245619E+03 .159098177908E+03 .135421633456E+03 .114413857777E+03 + .959157099433E+02 .797613979036E+02 .657850515169E+02 .538188522131E+02 .436847873034E+02 + .351899916323E+02 .281331203679E+02 .223174729841E+02 .175614967879E+02 .137029357329E+02 + .105987319431E+02 .812353742881E+01 .616817860109E+01 .463832203023E+01 .345324816958E+01 + .254463542651E+01 .185531926861E+01 .133803588607E+01 + pspotential + -.284668580974E+02 -.284683169301E+02 -.284697298194E+02 -.284710982122E+02 -.284724235102E+02 + -.284737070698E+02 -.284749502063E+02 -.284761541924E+02 -.284773202611E+02 -.284784496066E+02 + -.284795433857E+02 -.284806027180E+02 -.284816286891E+02 -.284826223489E+02 -.284835847157E+02 + -.284845167748E+02 -.284854194805E+02 -.284862937574E+02 -.284871405012E+02 -.284879605786E+02 + -.284887548297E+02 -.284895240675E+02 -.284902690805E+02 -.284909906311E+02 -.284916894586E+02 + -.284923662782E+02 -.284930217837E+02 -.284936566461E+02 -.284942715156E+02 -.284948670220E+02 + -.284954437749E+02 -.284960023654E+02 -.284965433652E+02 -.284970673288E+02 -.284975747926E+02 + -.284980662764E+02 -.284985422834E+02 -.284990033014E+02 -.284994498023E+02 -.284998822437E+02 + -.285003010685E+02 -.285007067055E+02 -.285010995703E+02 -.285014800653E+02 -.285018485803E+02 + -.285022054928E+02 -.285025511684E+02 -.285028859612E+02 -.285032102143E+02 -.285035242597E+02 + -.285038284193E+02 -.285041230047E+02 -.285044083177E+02 -.285046846506E+02 -.285049522867E+02 + -.285052115003E+02 -.285054625570E+02 -.285057057141E+02 -.285059412208E+02 -.285061693187E+02 + -.285063902416E+02 -.285066042160E+02 -.285068114613E+02 -.285070121901E+02 -.285072066083E+02 + -.285073949154E+02 -.285075773047E+02 -.285077539632E+02 -.285079250725E+02 -.285080908082E+02 + -.285082513405E+02 -.285084068344E+02 -.285085574497E+02 -.285087033412E+02 -.285088446592E+02 + -.285089815489E+02 -.285091141512E+02 -.285092426028E+02 -.285093670362E+02 -.285094875796E+02 + -.285096043574E+02 -.285097174903E+02 -.285098270953E+02 -.285099332857E+02 -.285100361716E+02 + -.285101358596E+02 -.285102324533E+02 -.285103260530E+02 -.285104167563E+02 -.285105046579E+02 + -.285105898494E+02 -.285106724202E+02 -.285107524569E+02 -.285108300437E+02 -.285109052623E+02 + -.285109781925E+02 -.285110489115E+02 -.285111174947E+02 -.285111840153E+02 -.285112485448E+02 + -.285113111527E+02 -.285113719068E+02 -.285114308734E+02 -.285114881171E+02 -.285115437009E+02 + -.285115976866E+02 -.285116501346E+02 -.285117011040E+02 -.285117506529E+02 -.285117988383E+02 + -.285118457160E+02 -.285118913411E+02 -.285119357679E+02 -.285119790499E+02 -.285120212399E+02 + -.285120623903E+02 -.285121025528E+02 -.285121417791E+02 -.285121801201E+02 -.285122176271E+02 + -.285122543509E+02 -.285122903425E+02 -.285123256531E+02 -.285123603339E+02 -.285123944366E+02 + -.285124280136E+02 -.285124611175E+02 -.285124938019E+02 -.285125261211E+02 -.285125581306E+02 + -.285125898869E+02 -.285126214480E+02 -.285126528730E+02 -.285126842231E+02 -.285127155610E+02 + -.285127469515E+02 -.285127784618E+02 -.285128101613E+02 -.285128421220E+02 -.285128744192E+02 + -.285129071308E+02 -.285129403386E+02 -.285129741276E+02 -.285130085872E+02 -.285130438109E+02 + -.285130798969E+02 -.285131169482E+02 -.285131550734E+02 -.285131943868E+02 -.285132350088E+02 + -.285132770666E+02 -.285133206943E+02 -.285133660339E+02 -.285134132352E+02 -.285134624572E+02 + -.285135138679E+02 -.285135676456E+02 -.285136239791E+02 -.285136830688E+02 -.285137451272E+02 + -.285138103801E+02 -.285138790671E+02 -.285139514428E+02 -.285140277778E+02 -.285141083597E+02 + -.285141934943E+02 -.285142835068E+02 -.285143787430E+02 -.285144795711E+02 -.285145863826E+02 + -.285146995943E+02 -.285148196500E+02 -.285149470220E+02 -.285150822131E+02 -.285152257590E+02 + -.285153782298E+02 -.285155402330E+02 -.285157124155E+02 -.285158954666E+02 -.285160901204E+02 + -.285162971590E+02 -.285165174159E+02 -.285167517787E+02 -.285170011938E+02 -.285172666691E+02 + -.285175492789E+02 -.285178501680E+02 -.285181705563E+02 -.285185117440E+02 -.285188751165E+02 + -.285192621507E+02 -.285196744202E+02 -.285201136023E+02 -.285205814849E+02 -.285210799732E+02 + -.285216110981E+02 -.285221770239E+02 -.285227800576E+02 -.285234226581E+02 -.285241074462E+02 + -.285248372152E+02 -.285256149423E+02 -.285264438010E+02 -.285273271733E+02 -.285282686643E+02 + -.285292721163E+02 -.285303416243E+02 -.285314815531E+02 -.285326965547E+02 -.285339915870E+02 + -.285353719343E+02 -.285368432283E+02 -.285384114710E+02 -.285400830591E+02 -.285418648095E+02 + -.285437639871E+02 -.285457883340E+02 -.285479461006E+02 -.285502460786E+02 -.285526976368E+02 + -.285553107581E+02 -.285580960799E+02 -.285610649366E+02 -.285642294047E+02 -.285676023510E+02 + -.285711974839E+02 -.285750294079E+02 -.285791136815E+02 -.285834668789E+02 -.285881066552E+02 + -.285930518163E+02 -.285983223931E+02 -.286039397193E+02 -.286099265159E+02 -.286163069793E+02 + -.286231068758E+02 -.286303536416E+02 -.286380764889E+02 -.286463065191E+02 -.286550768420E+02 + -.286644227033E+02 -.286743816188E+02 -.286849935181E+02 -.286963008955E+02 -.287083489715E+02 + -.287211858626E+02 -.287348627628E+02 -.287494341353E+02 -.287649579152E+02 -.287814957256E+02 + -.287991131063E+02 -.288178797557E+02 -.288378697884E+02 -.288591620081E+02 -.288818401970E+02 + -.289059934240E+02 -.289317163713E+02 -.289591096822E+02 -.289882803316E+02 -.290193420199E+02 + -.290524155945E+02 -.290876294986E+02 -.291251202524E+02 -.291650329680E+02 -.292075219026E+02 + -.292527510523E+02 -.293008947930E+02 -.293521385709E+02 -.294066796496E+02 -.294647279184E+02 + -.295265067689E+02 -.295922540467E+02 -.296622230833E+02 -.297366838166E+02 -.298159240051E+02 + -.299002505394E+02 -.299899908538E+02 -.300854944348E+02 -.301871344177E+02 -.302953092527E+02 + -.304104444074E+02 -.305329940542E+02 -.306634426595E+02 -.308023063576E+02 -.309501339324E+02 + -.311075071620E+02 -.312750401800E+02 -.314533773784E+02 -.316431892087E+02 -.318451650241E+02 + -.320600018433E+02 -.322883876156E+02 -.325309772422E+02 -.327883593234E+02 -.330610114486E+02 + -.333492420108E+02 -.336531172581E+02 -.339723739182E+02 -.343063205135E+02 -.346537343042E+02 + -.350127645096E+02 -.353808527148E+02 -.357546711895E+02 -.361300477034E+02 -.365017781319E+02 + -.368631244736E+02 -.372047033483E+02 -.375125520335E+02 -.377657440182E+02 -.379353182676E+02 + -.379879388728E+02 -.378969924352E+02 -.376572675510E+02 -.372895576252E+02 -.368609887562E+02 + -.364580390768E+02 -.360705398248E+02 -.356893343561E+02 -.353112759338E+02 -.349371692255E+02 + -.345669009212E+02 -.341257373489E+02 -.337108274651E+02 + core charge-density (pseudized) + .158850907132E-07 .169349744559E-07 .180542475326E-07 .192474960507E-07 .205196092244E-07 + .218757994079E-07 .233216234522E-07 .248630054739E-07 .265062611287E-07 .282581234892E-07 + .301257706327E-07 .321168550529E-07 .342395350151E-07 .365025079838E-07 .389150462599E-07 + .414870349726E-07 .442290125832E-07 .471522140648E-07 .502686169368E-07 .535909903417E-07 + .571329473648E-07 .609090008129E-07 .649346226787E-07 .692263075359E-07 .738016401239E-07 + .786793673994E-07 .838794753501E-07 .894232708855E-07 .953334691390E-07 .101634286542E-06 + .108351540046E-06 .115512752907E-06 .123147267460E-06 .131286365342E-06 .139963395669E-06 + .149213911678E-06 .159075816404E-06 .169589517985E-06 .180798095227E-06 .192747474115E-06 + .205486615992E-06 .219067718171E-06 .233546427810E-06 .248982069915E-06 .265437890425E-06 + .282981315349E-06 .301684227038E-06 .321623258718E-06 .342880108482E-06 .365541874040E-06 + .389701409594E-06 .415457706293E-06 .442916297843E-06 .472189692914E-06 .503397836133E-06 + .536668599544E-06 .572138306547E-06 .609952290465E-06 .650265490033E-06 .693243084236E-06 + .739061169114E-06 .787907479286E-06 .839982157176E-06 .895498573063E-06 .954684199344E-06 + .101778154256E-05 .108504913706E-05 .115676260427E-05 .123321578204E-05 .131472192859E-05 + .140161500606E-05 .149425104883E-05 .159300962235E-05 .169829537834E-05 .181053971277E-05 + .193020253346E-05 .205777414445E-05 .219377725496E-05 .233876912105E-05 .249334382893E-05 + .265813472909E-05 .283381703132E-05 .302111057124E-05 .322078275972E-05 .343365172714E-05 + .366058967549E-05 .390252645204E-05 .416045335916E-05 .443542721593E-05 .472857468816E-05 + .504109690465E-05 .537427437842E-05 .572947225328E-05 .610814589706E-05 .651184686453E-05 + .694222925437E-05 .740105648627E-05 .789020852588E-05 .841168958728E-05 .896763634441E-05 + .956032668519E-05 .101921890442E-04 .108658123520E-04 .115839566421E-04 .123495643585E-04 + .131657724114E-04 .140359250280E-04 .149635874541E-04 .159525605604E-04 .170068964137E-04 + .181309148776E-04 .193292213099E-04 .206067254291E-04 .219686614285E-04 .234206094181E-04 + .249685182840E-04 .266187300582E-04 .283780058984E-04 .302535537841E-04 .322530580431E-04 + .343847108279E-04 .366572456728E-04 .390799732669E-04 .416628195906E-04 .444163665717E-04 + .473518954273E-04 .504814328676E-04 .538178003533E-04 .573746666051E-04 .611666035821E-04 + .652091461570E-04 .695188557326E-04 .741133880594E-04 .790115655314E-04 .842334542561E-04 + .898004462130E-04 .957353468361E-04 .102062468380E-03 .108807729446E-03 .115998761083E-03 + .123665019889E-03 .131837908571E-03 .140550904475E-03 .149839696579E-03 .159742331544E-03 + .170299369380E-03 .181554049396E-03 .193552467086E-03 .206343762684E-03 .219980322147E-03 + .234517991391E-03 .250016304646E-03 .266538727861E-03 .284152918146E-03 .302931000300E-03 + .322949861560E-03 .344291465748E-03 .367043188107E-03 .391298172159E-03 .417155710061E-03 + .444721647953E-03 .474108817981E-03 .505437498701E-03 .538835905735E-03 .574440714657E-03 + .612397618202E-03 .652861920041E-03 .695999167499E-03 .741985825749E-03 .791009996188E-03 + .843272181843E-03 .898986102869E-03 .958379565380E-03 .102169538706E-02 .108919238320E-02 + .116114641712E-02 .123785151900E-02 .131962107766E-02 .140678910979E-02 .149971161181E-02 + .159876799938E-02 .170436264031E-02 .181692648675E-02 .193691881296E-02 .206482906523E-02 + .220117883122E-02 .234652393586E-02 .250145667215E-02 .266660817484E-02 .284265094610E-02 + .303030154244E-02 .323032343282E-02 .344353003832E-02 .367078796445E-02 .391302043770E-02 + .417121095843E-02 .444640718317E-02 .473972504961E-02 .505235315859E-02 .538555742793E-02 + .574068603353E-02 .611917465425E-02 .652255203717E-02 .695244590122E-02 .741058919732E-02 + .789882674413E-02 .841912225897E-02 .897356580441E-02 .956438167099E-02 .101939367177E-01 + .108647491919E-01 .115794980501E-01 .123410328028E-01 .131523839044E-01 .140167737110E-01 + .149376280269E-01 .159185882611E-01 .169635242136E-01 .180765475092E-01 .192620256957E-01 + .205245970213E-01 .218691859007E-01 .233010190786E-01 .248256424935E-01 .264489388384E-01 + .281771458098E-01 .300168750282E-01 .319751316050E-01 .340593343169E-01 .362773363404E-01 + .386374464823E-01 .411484508237E-01 .438196346781E-01 .466608047400E-01 .496823112734E-01 + .528950701615E-01 .563105846042E-01 .599409662088E-01 .637989551781E-01 .678979392487E-01 + .722519709725E-01 .768757828747E-01 .817847999463E-01 .869951488479E-01 .925236631107E-01 + .983878835213E-01 .104606052760E+00 .111197103239E+00 .118180636950E+00 .125576895976E+00 + .133406722150E+00 .141691504177E+00 .150453110317E+00 .159713804529E+00 .169496143740E+00 + .179822853659E+00 .190716680317E+00 .202200214208E+00 .214295683694E+00 .227024713996E+00 + .240408047883E+00 .254465223863E+00 .269214207487E+00 .284670971153E+00 .300849017672E+00 + .317758842779E+00 .335407331821E+00 .353797086014E+00 .372925673998E+00 .392784804976E+00 + .413359420546E+00 .434626703479E+00 .456555003242E+00 .479102680107E+00 .502216872244E+00 + .525832193516E+00 .549869373680E+00 .574233857642E+00 .598814386387E+00 .623481589187E+00 + .648086625061E+00 .672459920978E+00 .696410065316E+00 .719722927378E+00 .742161087375E+00 + .763463676005E+00 .783346738217E+00 .801504251502E+00 .817609944243E+00 .831320073323E+00 + .842277330789E+00 .850116055018E+00 .854468920152E+00 .854975265373E+00 .851291199249E+00 + .843101569433E+00 .830133819226E+00 .812173654295E+00 .789082308931E+00 .760815025548E+00 + .727440137991E+00 .689157874534E+00 .646317668655E+00 .599432387566E+00 .549187469489E+00 + .496442519212E+00 .442222478719E+00 .387695112852E+00 .334131296257E+00 .282844548501E+00 + .235106556397E+00 .192036190812E+00 .154460937507E+00 .122751901168E+00 .966509456742E-01 + .754197389551E-01 .583105713293E-01 .446553155083E-01 .338641489723E-01 .254227504169E-01 + .188882123217E-01 .138839144900E-01 .100936595806E-01 + pseudo wavefunction + .575355356415E-04 .594064477253E-04 .613381972024E-04 .633327623533E-04 .653921857868E-04 + .675185765325E-04 .697141122004E-04 .719810412106E-04 .743216850967E-04 .767384408824E-04 + .792337835369E-04 .818102685089E-04 .844705343442E-04 .872173053874E-04 .900533945721E-04 + .929817063013E-04 .960052394220E-04 .991270902962E-04 .102350455972E-03 .105678637457E-03 + .109115043101E-03 .112663192082E-03 .116326718016E-03 .120109372672E-03 .124015029819E-03 + .128047689192E-03 .132211480586E-03 .136510668086E-03 .140949654437E-03 .145532985548E-03 + .150265355149E-03 .155151609602E-03 .160196752857E-03 .165405951581E-03 .170784540448E-03 + .176338027603E-03 .182072100302E-03 .187992630735E-03 .194105682043E-03 .200417514522E-03 + .206934592042E-03 .213663588656E-03 .220611395446E-03 .227785127571E-03 .235192131559E-03 + .242839992828E-03 .250736543454E-03 .258889870194E-03 .267308322765E-03 .276000522397E-03 + .284975370659E-03 .294242058578E-03 .303810076049E-03 .313689221556E-03 .323889612204E-03 + .334421694082E-03 .345296252956E-03 .356524425323E-03 .368117709807E-03 .380087978939E-03 + .392447491317E-03 .405208904153E-03 .418385286245E-03 .431990131351E-03 .446037372013E-03 + .460541393824E-03 .475517050162E-03 .490979677395E-03 .506945110594E-03 .523429699744E-03 + .540450326492E-03 .558024421429E-03 .576169981949E-03 .594905590672E-03 .614250434477E-03 + .634224324152E-03 .654847714681E-03 .676141726189E-03 .698128165574E-03 .720829548839E-03 + .744269124145E-03 .768470895626E-03 .793459647966E-03 .819260971781E-03 .845901289826E-03 + .873407884057E-03 .901808923562E-03 .931133493415E-03 .961411624459E-03 .992674324057E-03 + .102495360785E-02 .105828253254E-02 .109269522973E-02 .112822694092E-02 .116491405352E-02 + .120279413821E-02 .124190598731E-02 .128228965460E-02 .132398649626E-02 .136703921328E-02 + .141149189515E-02 .145739006503E-02 .150478072633E-02 .155371241090E-02 .160423522870E-02 + .165640091909E-02 .171026290385E-02 .176587634186E-02 .182329818560E-02 .188258723945E-02 + .194380421993E-02 .200701181784E-02 .207227476250E-02 .213965988796E-02 .220923620153E-02 + .228107495436E-02 .235524971443E-02 .243183644189E-02 .251091356682E-02 .259256206952E-02 + .267686556349E-02 .276391038097E-02 .285378566135E-02 .294658344250E-02 .304239875489E-02 + .314132971901E-02 .324347764574E-02 .334894714010E-02 .345784620834E-02 .357028636854E-02 + .368638276474E-02 .380625428484E-02 .393002368229E-02 .405781770175E-02 .418976720886E-02 + .432600732415E-02 .446667756139E-02 .461192197039E-02 .476188928438E-02 .491673307231E-02 + .507661189599E-02 .524168947234E-02 .541213484098E-02 .558812253715E-02 .576983277035E-02 + .595745160873E-02 .615117116944E-02 .635118981518E-02 .655771235717E-02 .677095026461E-02 + .699112188101E-02 .721845264752E-02 .745317533347E-02 .769553027439E-02 .794576561781E-02 + .820413757691E-02 .847091069247E-02 .874635810329E-02 .903076182533E-02 .932441303995E-02 + .962761239135E-02 .994067029381E-02 .102639072487E-01 .105976541719E-01 .109422527315E-01 + .112980556968E-01 .116654272983E-01 .120447435995E-01 .124363928804E-01 .128407760336E-01 + .132583069731E-01 .136894130563E-01 .141345355194E-01 .145941299272E-01 .150686666365E-01 + .155586312758E-01 .160645252384E-01 .165868661936E-01 .171261886122E-01 .176830443099E-01 + .182580030081E-01 .188516529119E-01 .194646013071E-01 .200974751761E-01 .207509218330E-01 + .214256095793E-01 .221222283799E-01 .228414905610E-01 .235841315294E-01 .243509105150E-01 + .251426113360E-01 .259600431889E-01 .268040414619E-01 .276754685752E-01 .285752148462E-01 + .295041993818E-01 .304633709985E-01 .314537091706E-01 .324762250072E-01 .335319622594E-01 + .346219983579E-01 .357474454814E-01 .369094516585E-01 .381092019006E-01 .393479193701E-01 + .406268665822E-01 .419473466418E-01 .433107045170E-01 .447183283484E-01 .461716507967E-01 + .476721504277E-01 .492213531363E-01 .508208336098E-01 .524722168313E-01 .541771796234E-01 + .559374522328E-01 .577548199563E-01 .596311248087E-01 .615682672319E-01 .635682078464E-01 + .656329692451E-01 .677646378278E-01 .699653656785E-01 .722373724825E-01 .745829474842E-01 + .770044514849E-01 .795043188773E-01 .820850597180E-01 .847492618341E-01 .874995929625E-01 + .903388029198E-01 .932697257982E-01 .962952821862E-01 .994184814074E-01 .102642423774E+00 + .105970302852E+00 .109405407722E+00 .112951125248E+00 .116610942317E+00 .120388448077E+00 + .124287336121E+00 .128311406648E+00 .132464568547E+00 .136750841429E+00 .141174357551E+00 + .145739363643E+00 .150450222608E+00 .155311415056E+00 .160327540676E+00 .165503319382E+00 + .170843592230E+00 .176353322051E+00 .182037593757E+00 .187901614291E+00 .193950712150E+00 + .200190336440E+00 .206626055381E+00 .213263554212E+00 .220108632399E+00 .227167200068E+00 + .234445273557E+00 .241948969987E+00 .249684500724E+00 .257658163593E+00 .265876333703E+00 + .274345452710E+00 .283072016330E+00 .292062559898E+00 .301323641738E+00 .310861824101E+00 + .320683651362E+00 .330795625188E+00 .341204176307E+00 .351915632491E+00 .362936182330E+00 + .374271834305E+00 .385928370642E+00 .397911295339E+00 .410225775742E+00 .422876576925E+00 + .435867988095E+00 .449203740138E+00 .462886913351E+00 .476919834292E+00 .491303960597E+00 + .506039752485E+00 .521126529587E+00 .536562311577E+00 .552343640997E+00 .568465386534E+00 + .584920524858E+00 .601699899070E+00 .618791951638E+00 .636182429658E+00 .653854060191E+00 + .671786193400E+00 .689954411226E+00 .708330099434E+00 .726879981021E+00 .745565609229E+00 + .764342818847E+00 .783161135014E+00 .801963139531E+00 .820683795679E+00 .839249733873E+00 + .857578502086E+00 .875577787069E+00 .893144614848E+00 .910164542018E+00 .926510852941E+00 + .942043782108E+00 .956609785792E+00 .970040892551E+00 .982154168203E+00 .992751337468E+00 + .100161861137E+01 .100852677652E+01 .101323160906E+01 .101547468225E+01 .101498464091E+01 + .101147901878E+01 .100466111560E+01 .994375951175E+00 + ae wavefunction + .723210491674E-03 .746578583504E-03 .770700951777E-03 .795601892046E-03 .821306479222E-03 + .847840592364E-03 .875230940233E-03 .903505087646E-03 .932691482648E-03 .962819484530E-03 + .993919392710E-03 .102602247652E-02 .105916100589E-02 .109336828301E-02 .112867867496E-02 + .116512764731E-02 .120275179882E-02 .124158889712E-02 .128167791559E-02 .132305907123E-02 + .136577386383E-02 .140986511623E-02 .145537701585E-02 .150235515746E-02 .155084658728E-02 + .160089984836E-02 .165256502735E-02 .170589380272E-02 .176093949434E-02 .181775711461E-02 + .187640342107E-02 .193693697064E-02 .199941817539E-02 .206390935997E-02 .213047482081E-02 + .219918088694E-02 .227009598271E-02 .234329069219E-02 .241883782559E-02 .249681248751E-02 + .257729214718E-02 .266035671067E-02 .274608859525E-02 .283457280576E-02 .292589701322E-02 + .302015163557E-02 .311742992074E-02 .321782803195E-02 .332144513543E-02 .342838349055E-02 + .353874854230E-02 .365264901643E-02 .377019701702E-02 .389150812670E-02 .401670150953E-02 + .414590001658E-02 .427923029422E-02 .441682289522E-02 .455881239271E-02 .470533749697E-02 + .485654117518E-02 .501257077409E-02 .517357814572E-02 .533971977604E-02 .551115691676E-02 + .568805572017E-02 .587058737709E-02 .605892825797E-02 .625326005711E-02 .645376994004E-02 + .666065069409E-02 .687410088207E-02 .709432499912E-02 .732153363272E-02 .755594362580E-02 + .779777824289E-02 .804726733939E-02 .830464753379E-02 .857016238277E-02 .884406255928E-02 + .912660603329E-02 .941805825521E-02 .971869234197E-02 .100287892654E-01 .103486380429E-01 + .106785359304E-01 .110187886169E-01 .113697104211E-01 .117316244893E-01 .121048629944E-01 + .124897673360E-01 .128866883414E-01 .132959864662E-01 .137180319953E-01 .141532052432E-01 + .146018967537E-01 .150645074973E-01 .155414490675E-01 .160331438739E-01 .165400253324E-01 + .170625380517E-01 .176011380142E-01 .181562927528E-01 .187284815203E-01 .193181954522E-01 + .199259377210E-01 .205522236809E-01 .211975810029E-01 .218625497970E-01 .225476827224E-01 + .232535450820E-01 .239807149024E-01 .247297829946E-01 .255013529962E-01 .262960413920E-01 + .271144775113E-01 .279573034995E-01 .288251742619E-01 .297187573775E-01 .306387329797E-01 + .315857936016E-01 .325606439823E-01 .335640008323E-01 .345965925527E-01 .356591589072E-01 + .367524506409E-01 .378772290432E-01 .390342654498E-01 .402243406813E-01 .414482444099E-01 + .427067744540E-01 .440007359916E-01 .453309406888E-01 .466982057375E-01 .481033527959E-01 + .495472068255E-01 .510305948176E-01 .525543444026E-01 .541192823346E-01 .557262328435E-01 + .573760158460E-01 .590694450081E-01 .608073256492E-01 .625904524789E-01 .644196071575E-01 + .662955556690E-01 .682190454976E-01 .701908025956E-01 .722115281337E-01 .742818950192E-01 + .764025441734E-01 .785740805545E-01 .807970689137E-01 .830720292724E-01 .853994321068E-01 + .877796932277E-01 .902131683422E-01 .927001472824E-01 .952408478902E-01 .978354095427E-01 + .100483886305E+00 .103186239701E+00 .105942331082E+00 .108751913586E+00 .111614623678E+00 + .114529972255E+00 .117497335304E+00 .120515944107E+00 .123584874990E+00 .126703038594E+00 + .129869168677E+00 .133081810436E+00 .136339308348E+00 .139639793532E+00 .142981170636E+00 + .146361104253E+00 .149777004875E+00 .153226014404E+00 .156704991228E+00 .160210494897E+00 + .163738770409E+00 .167285732154E+00 .170846947546E+00 .174417620387E+00 .177992574025E+00 + .181566234348E+00 .185132612703E+00 .188685288794E+00 .192217393669E+00 .195721592871E+00 + .199190069873E+00 .202614509914E+00 .205986084362E+00 .209295435754E+00 .212532663666E+00 + .215687311579E+00 .218748354949E+00 .221704190648E+00 .224542628026E+00 .227250881804E+00 + .229815567059E+00 .232222696565E+00 .234457680772E+00 .236505330719E+00 .238349864209E+00 + .239974915563E+00 .241363549317E+00 .242498278209E+00 .243361085852E+00 .243933454457E+00 + .244196398032E+00 .244130501447E+00 .243715965781E+00 .242932660377E+00 .241760182005E+00 + .240177921559E+00 .238165138679E+00 .235701044686E+00 .232764894196E+00 .229336085751E+00 + .225394271769E+00 .220919478069E+00 .215892233186E+00 .210293707615E+00 .204105863065E+00 + .197311611722E+00 .189894985412E+00 .181841314484E+00 .173137416083E+00 .163771791405E+00 + .153734831344E+00 .143019029848E+00 .131619204110E+00 .119532720583E+00 .106759725623E+00 + .933033793783E-01 .791700913290E-01 .643697556467E-01 .489159842705E-01 .328263352823E-01 + .161225338086E-01 -.116931769311E-02 -.190185432589E-01 -.373897150652E-01 -.562424965567E-01 + -.755315101746E-01 -.952062316141E-01 -.115210910670E+00 -.135484516518E+00 -.155960703517E+00 + -.176567793429E+00 -.197228772403E+00 -.217861306439E+00 -.238377786432E+00 -.258685421094E+00 + -.278686400098E+00 -.298278147634E+00 -.317353677390E+00 -.335802046575E+00 -.353508895291E+00 + -.370357053514E+00 -.386227201622E+00 -.400998577469E+00 -.414549728634E+00 -.426759310469E+00 + -.437506929404E+00 -.446674028239E+00 -.454144807390E+00 -.459807173979E+00 -.463553709570E+00 + -.465282646961E+00 -.464898846615E+00 -.462314763759E+00 -.457451397642E+00 -.450239215005E+00 + -.440619040214E+00 -.428542904958E+00 -.413974850650E+00 -.396891676910E+00 -.377283629551E+00 + -.355155021405E+00 -.330524779042E+00 -.303426907952E+00 -.273910868147E+00 -.242041851308E+00 + -.207900949827E+00 -.171585207413E+00 -.133207540559E+00 -.928965205479E-01 -.507960069887E-01 + -.706462660247E-02 .381249046254E-01 .845866118155E-01 .132122232827E+00 .180522312943E+00 + .229567399836E+00 .279029316983E+00 .328672503777E+00 .378255433412E+00 .427532158406E+00 + .476254091096E+00 .524172202057E+00 .571039898221E+00 .616616860053E+00 .660673895312E+00 + .702998092998E+00 .743396069181E+00 .781691750831E+00 .817716502043E+00 .851295258407E+00 + .882238299672E+00 .910345743397E+00 .935421491735E+00 .957287299205E+00 .975791213531E+00 + .990810701652E+00 .100225314042E+01 .101005569012E+01 .101418535258E+01 .101463927777E+01 + .101144510801E+01 .100466111560E+01 .994375951175E+00 + pseudo wavefunction + .138848147713E-05 .143363143073E-05 .148024954817E-05 .152838357046E-05 .157808279106E-05 + .162939810629E-05 .168238206754E-05 .173708893499E-05 .179357473326E-05 .185189730873E-05 + .191211638882E-05 .197429364312E-05 .203849274656E-05 .210477944463E-05 .217322162069E-05 + .224388936550E-05 .231685504901E-05 .239219339443E-05 .246998155480E-05 .255029919199E-05 + .263322855826E-05 .271885458052E-05 .280726494727E-05 .289855019843E-05 .299280381807E-05 + .309012233011E-05 .319060539717E-05 .329435592268E-05 .340148015621E-05 .351208780231E-05 + .362629213282E-05 .374421010294E-05 .386596247091E-05 .399167392177E-05 .412147319496E-05 + .425549321623E-05 .439387123372E-05 .453674895855E-05 .468427270993E-05 .483659356497E-05 + .499386751345E-05 .515625561753E-05 .532392417672E-05 .549704489814E-05 .567579507240E-05 + .586035775516E-05 .605092195456E-05 .624768282482E-05 .645084186605E-05 .666060713066E-05 + .687719343636E-05 .710082258618E-05 .733172359563E-05 .757013292719E-05 .781629473250E-05 + .807046110236E-05 .833289232491E-05 .860385715220E-05 .888363307535E-05 .917250660878E-05 + .947077358361E-05 .977873945059E-05 .100967195929E-04 .104250396492E-04 .107640358469E-04 + .111140553467E-04 .114754565982E-04 .118486097064E-04 .122338968115E-04 .126317124796E-04 + .130424641070E-04 .134665723375E-04 .139044714931E-04 .143566100184E-04 .148234509404E-04 + .153054723424E-04 .158031678534E-04 .163170471539E-04 .168476364977E-04 .173954792507E-04 + .179611364475E-04 .185451873656E-04 .191482301190E-04 .197708822706E-04 .204137814640E-04 + .210775860774E-04 .217629758970E-04 .224706528134E-04 .232013415404E-04 .239557903567E-04 + .247347718727E-04 .255390838211E-04 .263695498740E-04 .272270204861E-04 .281123737658E-04 + .290265163739E-04 .299703844525E-04 .309449445827E-04 .319511947751E-04 .329901654910E-04 + .340629206980E-04 .351705589586E-04 .363142145555E-04 .374950586529E-04 .387143004951E-04 + .399731886447E-04 .412730122609E-04 .426151024191E-04 .440008334734E-04 .454316244639E-04 + .469089405685E-04 .484342946036E-04 .500092485720E-04 .516354152616E-04 .533144598965E-04 + .550481018409E-04 .568381163590E-04 .586863364318E-04 .605946546324E-04 .625650250632E-04 + .645994653551E-04 .667000587319E-04 .688689561416E-04 .711083784571E-04 .734206187480E-04 + .758080446262E-04 .782731006675E-04 .808183109118E-04 .834462814443E-04 .861597030606E-04 + .889613540173E-04 .918541028731E-04 .948409114207E-04 .979248377142E-04 .101109039194E-03 + .104396775914E-03 .107791413872E-03 .111296428448E-03 .114915407952E-03 .118652057294E-03 + .122510201760E-03 .126493790920E-03 .130606902659E-03 .134853747338E-03 .139238672088E-03 + .143766165242E-03 .148440860915E-03 .153267543723E-03 .158251153660E-03 .163396791131E-03 + .168709722144E-03 .174195383669E-03 .179859389171E-03 .185707534319E-03 .191745802874E-03 + .197980372773E-03 .204417622402E-03 .211064137063E-03 .217926715664E-03 .225012377598E-03 + .232328369866E-03 .239882174401E-03 .247681515644E-03 .255734368344E-03 .264048965612E-03 + .272633807228E-03 .281497668203E-03 .290649607612E-03 .300098977705E-03 .309855433294E-03 + .319928941443E-03 .330329791440E-03 .341068605095E-03 .352156347338E-03 .363604337150E-03 + .375424258823E-03 .387628173562E-03 .400228531432E-03 .413238183671E-03 .426670395356E-03 + .440538858462E-03 .454857705282E-03 .469641522262E-03 .484905364210E-03 .500664768938E-03 + .516935772296E-03 .533734923645E-03 .551079301749E-03 .568986531105E-03 .587474798722E-03 + .606562871331E-03 .626270113061E-03 .646616503561E-03 .667622656585E-03 .689309839028E-03 + .711699990427E-03 .734815742920E-03 .758680441650E-03 .783318165627E-03 .808753749025E-03 + .835012802915E-03 .862121737409E-03 .890107784211E-03 .918999019551E-03 .948824387471E-03 + .979613723446E-03 .101139777830E-02 .104420824237E-02 .107807776989E-02 .111304000356E-02 + .114912959911E-02 .118638225005E-02 .122483471218E-02 .126452482815E-02 .130549155155E-02 + .134777497086E-02 .139141633267E-02 .143645806444E-02 .148294379626E-02 .153091838171E-02 + .158042791736E-02 .163151976091E-02 .168424254740E-02 .173864620342E-02 .179478195889E-02 + .185270235589E-02 .191246125433E-02 .197411383369E-02 .203771659049E-02 .210332733071E-02 + .217100515649E-02 .224081044631E-02 .231280482772E-02 .238705114166E-02 .246361339709E-02 + .254255671485E-02 .262394725904E-02 .270785215452E-02 .279433938855E-02 .288347769449E-02 + .297533641527E-02 .306998534399E-02 .316749453861E-02 .326793410732E-02 .337137396094E-02 + .347788352781E-02 .358753142647E-02 .370038509052E-02 .381651033932E-02 .393597088755E-02 + .405882778553E-02 .418513878099E-02 .431495759219E-02 .444833308019E-02 .458530830718E-02 + .472591946529E-02 .487019465868E-02 .501815251889E-02 .516980063105E-02 .532513374505E-02 + .548413174236E-02 .564675732521E-02 .581295338964E-02 .598264003926E-02 .615571118988E-02 + .633203070846E-02 .651142802188E-02 .669369312193E-02 .687857088273E-02 .706575459498E-02 + .725487860842E-02 .744550995872E-02 .763713883827E-02 .782916775105E-02 .802089917058E-02 + .821152149574E-02 .840009307223E-02 .858552401783E-02 .876655555604E-02 .894173652625E-02 + .910939669822E-02 .926761647490E-02 .941419252015E-02 .954659879722E-02 .966194244997E-02 + .975691390319E-02 .982773050077E-02 .987007294359E-02 .987901373415E-02 .984893678510E-02 + .977344730712E-02 .964527106365E-02 .945614207061E-02 .919667783672E-02 .885624129362E-02 + .842278866608E-02 .788270269565E-02 .722061087326E-02 .641918867735E-02 .545894827979E-02 + .431801379800E-02 .297188497289E-02 .139319217287E-02 -.448553094467E-03 -.258720639694E-02 + -.506022962024E-02 -.790891121518E-02 -.111785546697E-01 -.149186192039E-01 -.191827929812E-01 + -.240289749478E-01 -.295191367867E-01 -.357190314954E-01 -.426977099021E-01 -.505268012579E-01 + -.592795092078E-01 -.690292703957E-01 -.798480203107E-01 -.918040104754E-01 -.104959123678E+00 + -.119365640755E+00 -.135052537078E+00 -.152079847668E+00 + ae wavefunction + -.536934453859E-05 -.554283679026E-05 -.572192904881E-05 -.590680169358E-05 -.609764089026E-05 + -.629463877488E-05 -.649799364359E-05 -.670791014832E-05 -.692459949849E-05 -.714827966909E-05 + -.737917561507E-05 -.761751949247E-05 -.786355088640E-05 -.811751704595E-05 -.837967312645E-05 + -.865028243916E-05 -.892961670862E-05 -.921795633789E-05 -.951559068196E-05 -.982281832946E-05 + -.101399473930E-04 -.104672958085E-04 -.108051916432E-04 -.111539734135E-04 -.115139904123E-04 + -.118856030458E-04 -.122691831813E-04 -.126651145043E-04 -.130737928877E-04 -.134956267708E-04 + -.139310375502E-04 -.143804599824E-04 -.148443425977E-04 -.153231481275E-04 -.158173539430E-04 + -.163274525071E-04 -.168539518402E-04 -.173973759985E-04 -.179582655672E-04 -.185371781670E-04 + -.191346889761E-04 -.197513912662E-04 -.203878969549E-04 -.210448371726E-04 -.217228628465E-04 + -.224226453000E-04 -.231448768698E-04 -.238902715395E-04 -.246595655907E-04 -.254535182727E-04 + -.262729124892E-04 -.271185555052E-04 -.279912796712E-04 -.288919431682E-04 -.298214307715E-04 + -.307806546346E-04 -.317705550946E-04 -.327921014965E-04 -.338462930403E-04 -.349341596486E-04 + -.360567628560E-04 -.372151967208E-04 -.384105887585E-04 -.396441008986E-04 -.409169304631E-04 + -.422303111689E-04 -.435855141531E-04 -.449838490212E-04 -.464266649193E-04 -.479153516296E-04 + -.494513406894E-04 -.510361065335E-04 -.526711676611E-04 -.543580878243E-04 -.560984772421E-04 + -.578939938353E-04 -.597463444862E-04 -.616572863188E-04 -.636286280026E-04 -.656622310770E-04 + -.677600112965E-04 -.699239399964E-04 -.721560454777E-04 -.744584144105E-04 -.768331932539E-04 + -.792825896932E-04 -.818088740907E-04 -.844143809508E-04 -.871015103953E-04 -.898727296496E-04 + -.927305745357E-04 -.956776509712E-04 -.987166364702E-04 -.101850281645E-03 -.105081411705E-03 + -.108412927949E-03 -.111847809248E-03 -.115389113513E-03 -.119039979150E-03 -.122803626483E-03 + -.126683359162E-03 -.130682565527E-03 -.134804719940E-03 -.139053384073E-03 -.143432208139E-03 + -.147944932068E-03 -.152595386619E-03 -.157387494410E-03 -.162325270874E-03 -.167412825110E-03 + -.172654360643E-03 -.178054176055E-03 -.183616665503E-03 -.189346319090E-03 -.195247723081E-03 + -.201325559962E-03 -.207584608305E-03 -.214029742439E-03 -.220665931907E-03 -.227498240686E-03 + -.234531826147E-03 -.241771937751E-03 -.249223915435E-03 -.256893187684E-03 -.264785269257E-03 + -.272905758533E-03 -.281260334465E-03 -.289854753099E-03 -.298694843630E-03 -.307786503967E-03 + -.317135695765E-03 -.326748438899E-03 -.336630805319E-03 -.346788912276E-03 -.357228914847E-03 + -.367956997739E-03 -.378979366308E-03 -.390302236747E-03 -.401931825406E-03 -.413874337166E-03 + -.426135952835E-03 -.438722815493E-03 -.451641015734E-03 -.464896575730E-03 -.478495432072E-03 + -.492443417301E-03 -.506746240072E-03 -.521409463873E-03 -.536438484230E-03 -.551838504315E-03 + -.567614508895E-03 -.583771236517E-03 -.600313149877E-03 -.617244404277E-03 -.634568814079E-03 + -.652289817096E-03 -.670410436812E-03 -.688933242371E-03 -.707860306229E-03 -.727193159410E-03 + -.746932744273E-03 -.767079364717E-03 -.787632633752E-03 -.808591418363E-03 -.829953781613E-03 + -.851716921913E-03 -.873877109413E-03 -.896429619485E-03 -.919368663237E-03 -.942687315069E-03 + -.966377437233E-03 -.990429601424E-03 -.101483300741E-02 -.103957539876E-02 -.106464297566E-02 + -.109002030507E-02 -.111569022805E-02 -.114163376471E-02 -.116783001666E-02 -.119425606737E-02 + -.122088688052E-02 -.124769519669E-02 -.127465142868E-02 -.130172355576E-02 -.132887701736E-02 + -.135607460649E-02 -.138327636352E-02 -.141043947082E-02 -.143751814883E-02 -.146446355430E-02 + -.149122368142E-02 -.151774326652E-02 -.154396369741E-02 -.156982292811E-02 -.159525539999E-02 + -.162019197054E-02 -.164455985064E-02 -.166828255181E-02 -.169127984444E-02 -.171346772851E-02 + -.173475841814E-02 -.175506034127E-02 -.177427815611E-02 -.179231278583E-02 -.180906147281E-02 + -.182441785436E-02 -.183827206105E-02 -.185051083943E-02 -.186101770044E-02 -.186967309504E-02 + -.187635461816E-02 -.188093724242E-02 -.188329358242E-02 -.188329419051E-02 -.188080788474E-02 + -.187570210923E-02 -.186784332698E-02 -.185709744495E-02 -.184333027040E-02 -.182640799755E-02 + -.180619772262E-02 -.178256798498E-02 -.175538933148E-02 -.172453490022E-02 -.168988101939E-02 + -.165130781581E-02 -.160869982728E-02 -.156194661142E-02 -.151094334343E-02 -.145559139361E-02 + -.139579887503E-02 -.133148115055E-02 -.126256128768E-02 -.118897044893E-02 -.111064820449E-02 + -.102754275349E-02 -.939611039582E-03 -.846818745856E-03 -.749140153709E-03 -.646557849671E-03 + -.539062263517E-03 -.426651020394E-03 -.309328089220E-03 -.187102709897E-03 -.599880838515E-04 + .720001825600E-04 .208845882540E-03 .350534246572E-03 .497054178393E-03 .648400632914E-03 + .804577064382E-03 .965597871782E-03 .113149078626E-02 .130229918063E-02 .147808432308E-02 + .165892762793E-02 .184493295336E-02 .203622894624E-02 .223297134696E-02 .243534507736E-02 + .264356588222E-02 .285788129106E-02 .307857069465E-02 .330594435780E-02 .354034119917E-02 + .378212515797E-02 .403167994363E-02 .428940193867E-02 .455569100166E-02 .483093890027E-02 + .511551509457E-02 .540974958539E-02 .571391254373E-02 .602819044082E-02 .635265840777E-02 + .668724856637E-02 .703171409088E-02 .738558878481E-02 .774814198662E-02 .811832865644E-02 + .849473454000E-02 .887551635833E-02 .925833702998E-02 .964029599629E-02 .100178547868E-01 + .103867580288E-01 .107419501671E-01 .110774882165E-01 .113864509092E-01 .116608446298E-01 + .118915065430E-01 .120680053329E-01 .121785399967E-01 .122098372057E-01 .121470479066E-01 + .119736441032E-01 .116713171792E-01 .112198796429E-01 .105971727185E-01 .977898257453E-02 + .873896786599E-02 .744860013681E-02 .587711563848E-02 .399147119709E-02 .175628797936E-02 + -.866239019038E-03 -.391647408054E-02 -.743746940754E-02 -.114749637066E-01 -.160771276901E-01 + -.212941062664E-01 -.271776042085E-01 -.337807161610E-01 -.411579574899E-01 -.493653243621E-01 + -.584602786172E-01 -.685016626504E-01 -.795495976261E-01 -.916654172796E-01 -.104911674326E+00 + -.119352243438E+00 -.135052537078E+00 -.152079847668E+00 + pseudo wavefunction + .291401328267E-08 .310660741021E-08 .331193054558E-08 .353082397944E-08 .376418460535E-08 + .401296859474E-08 .427819531469E-08 .456095150469E-08 .486239572944E-08 .518376312600E-08 + .552637046455E-08 .589162154379E-08 .628101294285E-08 .669614015334E-08 .713870411675E-08 + .761051819386E-08 .811351559483E-08 .864975730028E-08 .922144050602E-08 .983090762574E-08 + .104806558889E-07 .111733475729E-07 .119118209112E-07 .126991017233E-07 .135384158119E-07 + .144332021812E-07 .153871271269E-07 .164040992594E-07 .174882855184E-07 .186441282465E-07 + .198763633914E-07 .211900399110E-07 .225905404609E-07 .240836034492E-07 .256753465491E-07 + .273722917656E-07 .291813921584E-07 .311100603318E-07 .331661988066E-07 .353582324001E-07 + .376951427462E-07 .401865050959E-07 .428425275519E-07 .456740928944E-07 .486928031728E-07 + .519110272435E-07 .553419514499E-07 .589996336526E-07 .628990608296E-07 .670562104837E-07 + .714881161091E-07 .762129369843E-07 .812500325772E-07 .866200418695E-07 .923449679216E-07 + .984482680290E-07 .104954949835E-06 .111891673797E-06 .119286862426E-06 .127170816744E-06 + .135575840437E-06 .144536372221E-06 .154089126946E-06 .164273246033E-06 .175130457852E-06 + .186705248698E-06 .199045045072E-06 .212200408000E-06 .226225240208E-06 .241177006976E-06 + .257116971601E-06 .274110446410E-06 .292227060376E-06 .311541044413E-06 .332131535525E-06 + .354082901063E-06 .377485084413E-06 .402433973521E-06 .429031793789E-06 .457387526929E-06 + .487617357500E-06 .519845148962E-06 .554202951188E-06 .590831541524E-06 .629881001606E-06 + .671511332296E-06 .715893109266E-06 .763208181910E-06 .813650418444E-06 .867426500254E-06 + .924756768742E-06 .985876128147E-06 .105103500802E-05 .112050038933E-05 .119455689838E-05 + .127350797300E-05 .135767710584E-05 .144740916984E-05 .154307183128E-05 .164505705620E-05 + .175378271646E-05 .186969430185E-05 .199326674539E-05 .212500636934E-05 .226545295966E-05 + .241518197771E-05 .257480691811E-05 .274498182232E-05 .292640395847E-05 .311981667823E-05 + .332601246248E-05 .354583616833E-05 .378018849066E-05 .403002965244E-05 .429638333898E-05 + .458034089216E-05 .488306578181E-05 .520579837264E-05 .554986100620E-05 .591666341865E-05 + .630770851660E-05 .672459853464E-05 .716904159982E-05 .764285872985E-05 .814799129391E-05 + .868650896637E-05 .926061820619E-05 .987267129663E-05 .105251759823E-04 .112208057432E-04 + .119624107473E-04 .127530295272E-04 .135959014285E-04 .144944798800E-04 .154524465418E-04 + .164737263873E-04 .175625037821E-04 .187232396258E-04 .199606896253E-04 .212799237765E-04 + .226863471325E-04 .241857219440E-04 .257841912628E-04 .274883041044E-04 .293050422725E-04 + .312418489565E-04 .333066592171E-04 .355079324866E-04 .378546872150E-04 .403565378054E-04 + .430237339888E-04 .458672027984E-04 .488985933180E-04 .521303243834E-04 .555756354354E-04 + .592486407301E-04 .631643871285E-04 .673389157022E-04 .717893274054E-04 .765338530833E-04 + .815919281008E-04 .869842718977E-04 .927329727939E-04 .988615783914E-04 .105395191942E-03 + .112360575071E-03 .119786257283E-03 .127702652682E-03 .136142184401E-03 .145139417227E-03 + .154731198977E-03 .164956811193E-03 .175858129767E-03 .187479796156E-03 .199869399874E-03 + .213077673012E-03 .227158697560E-03 .242170126392E-03 .258173418790E-03 .275234091470E-03 + .293421986129E-03 .312811554584E-03 .333482162664E-03 .355518414075E-03 .379010495548E-03 + .404054544654E-03 .430753041771E-03 .459215227769E-03 .489557549103E-03 .521904132075E-03 + .556387288181E-03 .593148052553E-03 .632336757633E-03 .674113644380E-03 .718649513420E-03 + .766126418722E-03 .816738406546E-03 .870692302575E-03 .928208550323E-03 .989522104105E-03 + .105488338007E-02 .112455926899E-02 .119883421475E-02 .127801136268E-02 .136241378226E-02 + .145238576868E-02 .154829422848E-02 .165053015436E-02 .175951019478E-02 .187567832433E-02 + .199950762094E-02 .213150215675E-02 .227219900947E-02 .242217040155E-02 .258202597513E-02 + .275241521072E-02 .293402999840E-02 .312760737056E-02 .333393240565E-02 .355384131315E-02 + .378822470998E-02 .403803109964E-02 .430427056539E-02 .458801868954E-02 .489042071142E-02 + .521269593699E-02 .555614241356E-02 .592214188380E-02 .631216503324E-02 .672777704632E-02 + .717064348614E-02 .764253651345E-02 .814534146086E-02 .868106377808E-02 .925183636437E-02 + .985992730423E-02 .105077480221E-01 .111978618716E-01 .119329931739E-01 .127160367202E-01 + .135500677497E-01 .144383524159E-01 .153843587512E-01 .163917681354E-01 .174644872754E-01 + .186066606954E-01 .198226837362E-01 .211172160564E-01 .224951956216E-01 .239618531636E-01 + .255227270816E-01 .271836787499E-01 .289509081858E-01 .308309700202E-01 .328307896988E-01 + .349576798280E-01 .372193565604E-01 .396239558955E-01 .421800497506E-01 .448966616271E-01 + .477832816749E-01 .508498809210E-01 .541069243959E-01 .575653828518E-01 .612367427231E-01 + .651330139336E-01 .692667351008E-01 .736509756357E-01 .782993341711E-01 .832259326911E-01 + .884454056628E-01 .939728833996E-01 .998239688107E-01 .106014706613E+00 .112561544003E+00 + .119481281715E+00 .126791014304E+00 .134508058440E+00 .142649867935E+00 .151233934173E+00 + .160277670588E+00 .169798279848E+00 .179812602404E+00 .190336945154E+00 .201386889071E+00 + .212977074828E+00 .225120965693E+00 .237830587274E+00 .251116244142E+00 .264986213837E+00 + .279446419435E+00 .294500082568E+00 .310147359718E+00 .326384965564E+00 .343205788327E+00 + .360598503251E+00 .378547191656E+00 .397030974266E+00 .416023668739E+00 .435493482341E+00 + .455402751380E+00 .475707739190E+00 .496358503829E+00 .517298844985E+00 .538466336475E+00 + .559792445834E+00 .581202735295E+00 .602617128586E+00 .623950214870E+00 .645111544538E+00 + .666005851127E+00 .686533109442E+00 .706588312368E+00 .726060818994E+00 .744833096173E+00 + .762778647533E+00 .779758902369E+00 .795618827667E+00 .810181037401E+00 .823238213856E+00 + .834543737580E+00 .843795379495E+00 .850759109048E+00 + ae wavefunction + -.227639975927E-06 -.241553083020E-06 -.256238531448E-06 -.271743785200E-06 -.288119039224E-06 + -.305417391637E-06 -.323695026587E-06 -.343011408299E-06 -.363429487022E-06 -.385015917681E-06 + -.407841292027E-06 -.431980385198E-06 -.457512417605E-06 -.484521333149E-06 -.513096094823E-06 + -.543330998835E-06 -.575326008437E-06 -.609187108752E-06 -.645026683949E-06 -.682963918224E-06 + -.723125222119E-06 -.765644685826E-06 -.810664561235E-06 -.858335774579E-06 -.908818471664E-06 + -.962282597814E-06 -.101890851477E-05 -.107888765696E-05 -.114242322970E-05 -.120973095201E-05 + -.128103984706E-05 -.135659308322E-05 -.143664886909E-05 -.152148140599E-05 -.161138190170E-05 + -.170665964933E-05 -.180764317575E-05 -.191468146391E-05 -.202814525399E-05 -.214842842850E-05 + -.227594948673E-05 -.241115311447E-05 -.255451185510E-05 -.270652788873E-05 -.286773492636E-05 + -.303870022660E-05 -.322002674287E-05 -.341235540958E-05 -.361636757635E-05 -.383278759983E-05 + -.406238560344E-05 -.430598041586E-05 -.456444269986E-05 -.483869828392E-05 -.512973170970E-05 + -.543859000934E-05 -.576638672758E-05 -.611430620447E-05 -.648360813551E-05 -.687563242730E-05 + -.729180436770E-05 -.773364013080E-05 -.820275263846E-05 -.870085780133E-05 -.922978116380E-05 + -.979146497909E-05 -.103879757420E-04 -.110215122090E-04 -.116944139365E-04 -.124091703718E-04 + -.131684305304E-04 -.139750132996E-04 -.148319184057E-04 -.157423380908E-04 -.167096695415E-04 + -.177375281191E-04 -.188297614430E-04 -.199904643804E-04 -.212239950010E-04 -.225349915590E-04 + -.239283905651E-04 -.254094460215E-04 -.269837498904E-04 -.286572538768E-04 -.304362926072E-04 + -.323276082937E-04 -.343383769763E-04 -.364762364443E-04 -.387493159417E-04 -.411662677688E-04 + -.437363009004E-04 -.464692167451E-04 -.493754471826E-04 -.524660950179E-04 -.557529770072E-04 + -.592486696121E-04 -.629665576550E-04 -.669208860529E-04 -.711268148224E-04 -.756004775571E-04 + -.803590435918E-04 -.854207840798E-04 -.908051422247E-04 -.965328079196E-04 -.102625797063E-03 + -.109107535840E-03 -.116002950260E-03 -.123338561283E-03 -.131142585864E-03 -.139445044266E-03 + -.148277874034E-03 -.157675051007E-03 -.167672717809E-03 -.178309320241E-03 -.189625752061E-03 + -.201665508629E-03 -.214474849945E-03 -.228102973627E-03 -.242602198405E-03 -.258028158739E-03 + -.274440011195E-03 -.291900653263E-03 -.310476955313E-03 -.330240006432E-03 -.351265374934E-03 + -.373633384344E-03 -.397429405728E-03 -.422744167254E-03 -.449674081948E-03 -.478321594601E-03 + -.508795548883E-03 -.541211575720E-03 -.575692504072E-03 -.612368795275E-03 -.651379002161E-03 + -.692870254233E-03 -.736998770214E-03 -.783930399325E-03 -.833841192722E-03 -.886918006549E-03 + -.943359138131E-03 -.100337499686E-02 -.106718881141E-02 -.113503737486E-02 -.120717182952E-02 + -.128385849317E-02 -.136537972838E-02 -.145203485685E-02 -.154414112049E-02 -.164203469122E-02 + -.174607173112E-02 -.185662950504E-02 -.197410754735E-02 -.209892888474E-02 -.223154131687E-02 + -.237241875665E-02 -.252206263177E-02 -.268100334926E-02 -.284980182450E-02 -.302905107608E-02 + -.321937788792E-02 -.342144453961E-02 -.363595060592E-02 -.386363482621E-02 -.410527704411E-02 + -.436170021744E-02 -.463377249841E-02 -.492240938313E-02 -.522857592952E-02 -.555328904201E-02 + -.589761982068E-02 -.626269597230E-02 -.664970427950E-02 -.705989312401E-02 -.749457505857E-02 + -.795512942174E-02 -.844300498806E-02 -.895972264571E-02 -.950687809174E-02 -.100861445343E-01 + -.106992753895E-01 -.113481069581E-01 -.120345610684E-01 -.127606476645E-01 -.135284673243E-01 + -.143402136813E-01 -.151981757303E-01 -.161047399864E-01 -.170623924716E-01 -.180737204949E-01 + -.191414141916E-01 -.202682677838E-01 -.214571805211E-01 -.227111572555E-01 -.240333086037E-01 + -.254268506438E-01 -.268951040903E-01 -.284414928881E-01 -.300695421604E-01 -.317828754443E-01 + -.335852111384E-01 -.354803580901E-01 -.374722102372E-01 -.395647402230E-01 -.417619918931E-01 + -.440680715826E-01 -.464871380971E-01 -.490233912878E-01 -.516810591191E-01 -.544643831232E-01 + -.573776021360E-01 -.604249342075E-01 -.636105565785E-01 -.669385836182E-01 -.704130426186E-01 + -.740378473440E-01 -.778167692409E-01 -.817534062181E-01 -.858511489161E-01 -.901131443956E-01 + -.945422571848E-01 -.991410276437E-01 -.103911627616E+00 -.108855813361E+00 -.113974875783E+00 + -.119269587988E+00 -.124740150247E+00 -.130386132443E+00 -.136206414151E+00 -.142199122499E+00 + -.148361568035E+00 -.154690178833E+00 -.161180433171E+00 -.167826791131E+00 -.174622625584E+00 + -.181560153093E+00 -.188630365378E+00 -.195822962130E+00 -.203126286096E+00 -.210527261502E+00 + -.218011337039E+00 -.225562434682E+00 -.233162905552E+00 -.240793493705E+00 -.248433308057E+00 + -.256059801489E+00 -.263648754700E+00 -.271174260698E+00 -.278608704786E+00 -.285922735197E+00 + -.293085222036E+00 -.300063207002E+00 -.306821852678E+00 -.313324406286E+00 -.319532196442E+00 + -.325404680492E+00 -.330899553158E+00 -.335972915728E+00 -.340579493099E+00 -.344672879444E+00 + -.348205795003E+00 -.351130344271E+00 -.353398274261E+00 -.354961236692E+00 -.355771058893E+00 + -.355780026498E+00 -.354941178483E+00 -.353208612980E+00 -.350537801067E+00 -.346885905329E+00 + -.342212100159E+00 -.336477891180E+00 -.329647431712E+00 -.321687834653E+00 -.312569478552E+00 + -.302266306889E+00 -.290756119819E+00 -.278020857663E+00 -.264046875488E+00 -.248825207961E+00 + -.232351823470E+00 -.214627866128E+00 -.195659883790E+00 -.175460039600E+00 -.154046303832E+00 + -.131442622052E+00 -.107679054871E+00 -.827918840025E-01 -.568236791368E-01 -.298233205159E-01 + -.184597323164E-02 .270469885701E-01 .567881062803E-01 .873040050703E-01 .118515596879E+00 + .150338306883E+00 .182682313261E+00 .215452796875E+00 .248550212706E+00 .281870620849E+00 + .315306154149E+00 .348745752676E+00 .382076353569E+00 .415184746117E+00 .447960165155E+00 + .480297179596E+00 .512097397715E+00 .543267510319E+00 .573711993632E+00 .603322782157E+00 + .631972546868E+00 .659516791165E+00 .685802866227E+00 .710679504466E+00 .734002703277E+00 + .755638014234E+00 .775461066058E+00 .793357766636E+00 .809224792331E+00 .822970439701E+00 + .834515700400E+00 .843795379495E+00 .850759109048E+00 + pseudo wavefunction + .188259325656E-09 .200701836025E-09 .213966701744E-09 .228108274249E-09 .243184497194E-09 + .259257143867E-09 .276392070301E-09 .294659485112E-09 .314134237172E-09 .334896122293E-09 + .357030210184E-09 .380627193015E-09 .405783757020E-09 .432602978655E-09 .461194746947E-09 + .491676213752E-09 .524172273773E-09 .558816076302E-09 .595749570786E-09 .635124088452E-09 + .677100962369E-09 .721852188493E-09 .769561130406E-09 .820423270627E-09 .874647011580E-09 + .932454529506E-09 .994082684803E-09 .105978399254E-08 .112982765710E-08 .120450067525E-08 + .128410901202E-08 .136897885444E-08 .145945794800E-08 .155591702150E-08 .165875130612E-08 + .176838215480E-08 .188525876868E-08 .200986003770E-08 .214269650275E-08 .228431244760E-08 + .243528812901E-08 .259624215430E-08 .276783401601E-08 .295076679410E-08 .314579003675E-08 + .335370283154E-08 .357535707967E-08 .381166098646E-08 .406358278269E-08 .433215469178E-08 + .461847715923E-08 .492372336155E-08 .524914401326E-08 .559607249152E-08 .596593029951E-08 + .636023289086E-08 .678059587908E-08 .722874165731E-08 .770650645568E-08 .821584786499E-08 + .875885285776E-08 .933774633931E-08 .995490026410E-08 .106128433544E-07 .113142714617E-07 + .120620586123E-07 .128592687834E-07 .137091684574E-07 .146152400060E-07 .155811959585E-07 + .166109942135E-07 .177088542561E-07 .188792744464E-07 .201270504508E-07 .214572948920E-07 + .228754582969E-07 .243873514295E-07 .259991690995E-07 .277175155448E-07 .295494314911E-07 + .315024230005E-07 .335844922259E-07 .358041701992E-07 .381705517848E-07 .406933329453E-07 + .433828504679E-07 .462501243186E-07 .493069027933E-07 .525657106550E-07 .560399004512E-07 + .597437072231E-07 .636923068306E-07 .679018781323E-07 .723896692744E-07 .771740683610E-07 + .822746787944E-07 .877123995959E-07 .935095110327E-07 .996897659063E-07 .106278486872E-06 + .113302670191E-06 .120791096338E-06 .128774447922E-06 .137285435397E-06 .146358931079E-06 + .156032112024E-06 .166344612347E-06 .177338685603E-06 .189059377909E-06 .201554712490E-06 + .214875886441E-06 .229077480474E-06 .244217682537E-06 .260358526204E-06 .277566144822E-06 + .295911042451E-06 .315468382706E-06 .336318296692E-06 .358546211276E-06 .382243199059E-06 + .407506351473E-06 .434439176528E-06 .463152022837E-06 .493762531665E-06 .526396118840E-06 + .561186488509E-06 .598276180831E-06 .637817155864E-06 .679971416021E-06 .724911669647E-06 + .772822038440E-06 .823898811601E-06 .878351249803E-06 .936402442264E-06 .998290220443E-06 + .106426813207E-05 .113460647955E-05 .120959342687E-05 .128953617969E-05 .137476224337E-05 + .146562076397E-05 .156248395791E-05 .166574863599E-05 .177583782802E-05 .189320251473E-05 + .201832347399E-05 .215171324889E-05 .229391824580E-05 .244552097081E-05 .260714241377E-05 + .277944458969E-05 .296313324782E-05 .315896075937E-05 .336772919581E-05 .359029361017E-05 + .382756553466E-05 .408051670906E-05 .435018305473E-05 .463766891071E-05 .494415154892E-05 + .527088598687E-05 .561921011746E-05 .599055017661E-05 .638642657091E-05 .680846008894E-05 + .725837852142E-05 .773802371682E-05 .824935910117E-05 .879447769232E-05 .937561064095E-05 + .999513633285E-05 .106555900890E-04 .113596745027E-04 .121102704547E-04 .129104488515E-04 + .137634831326E-04 .146728625977E-04 .156423066068E-04 .166757797093E-04 .177775077628E-04 + .189519951060E-04 .202040428520E-04 .215387683771E-04 .229616260786E-04 .244784294863E-04 + .260953748122E-04 .278190660317E-04 .296565415935E-04 .316153028623E-04 .337033444036E-04 + .359291862279E-04 .383019081186E-04 .408311861731E-04 .435273316971E-04 .464013325996E-04 + .494648974426E-04 .527305023115E-04 .562114406801E-04 .599218764523E-04 .638769003772E-04 + .680925900398E-04 .725860736440E-04 .773755978153E-04 .824805996618E-04 .879217833433E-04 + .937212014151E-04 .999023412187E-04 .106490216612E-03 .113511465340E-03 .120994452360E-03 + .128969379448E-03 .137468401441E-03 .146525749442E-03 .156177861381E-03 .166463520291E-03 + .177424000698E-03 .189103223502E-03 .201547919779E-03 .214807803882E-03 .228935756279E-03 + .243988016516E-03 .260024386720E-03 .277108446041E-03 .295307776404E-03 .314694199941E-03 + .335344028437E-03 .357338325072E-03 .380763178723E-03 .405709990999E-03 .432275776138E-03 + .460563473773E-03 .490682274495E-03 .522747957989E-03 .556883243367E-03 .593218151151E-03 + .631890376108E-03 .673045669922E-03 .716838232348E-03 .763431109165E-03 .812996594826E-03 + .865716637226E-03 .921783241464E-03 .981398868826E-03 .104477682649E-02 .111214164262E-02 + .118372942048E-02 .125978816423E-02 .134057806758E-02 .142637175521E-02 .151745446512E-02 + .161412415806E-02 .171669153832E-02 .182547996737E-02 .194082524924E-02 .206307526326E-02 + .219258941639E-02 .232973788293E-02 .247490059520E-02 .262846594337E-02 .279082913687E-02 + .296239017320E-02 .314355135267E-02 .333471426917E-02 .353627619812E-02 .374862579194E-02 + .397213798232E-02 .420716797543E-02 .445404421192E-02 .471306014793E-02 .498446469549E-02 + .526845114184E-02 .556514434534E-02 .587458598281E-02 .619671759756E-02 .653136116924E-02 + .687819689722E-02 .723673785601E-02 .760630114682E-02 .798597513191E-02 .837458229890E-02 + .877063726069E-02 .917229935323E-02 .957731924895E-02 .998297895804E-02 .103860245445E-01 + .107825908400E-01 .111681173956E-01 .115372548753E-01 .118837610617E-01 .122003856210E-01 + .124787427655E-01 .127091709518E-01 .128805787801E-01 .129802763102E-01 .129937910905E-01 + .129046683256E-01 .126942547801E-01 .123414662634E-01 .118225388591E-01 .111107644916E-01 + .101762119689E-01 .898543534943E-02 .750117238625E-02 .568203694441E-02 .348221074715E-02 + .851141640091E-03 -.226674211916E-02 -.593228912367E-02 -.102118375499E-01 -.151773626963E-01 + -.209065329490E-01 -.274826407059E-01 -.349943660481E-01 -.435353202661E-01 -.532033034353E-01 + -.640991948492E-01 -.763253771158E-01 -.899835741667E-01 -.105171960694E+00 -.121981376528E+00 + -.140490455867E+00 -.160752140242E+00 -.182838197398E+00 + ae wavefunction + .329908017899E-08 .350070879538E-08 .371353032623E-08 .393823260492E-08 .417554304096E-08 + .442623111551E-08 .469111103129E-08 .497104452448E-08 .526694384922E-08 .557977494597E-08 + .591056080576E-08 .626038504303E-08 .663039569071E-08 .702180923184E-08 .743591488320E-08 + .787407914718E-08 .833775064943E-08 .882846528060E-08 .934785166202E-08 .989763695626E-08 + .104796530450E-07 .110958430977E-07 .117482685572E-07 .124391165681E-07 .131707078780E-07 + .139455052412E-07 .147661223583E-07 .156353333861E-07 .165560830548E-07 .175314974331E-07 + .185648953814E-07 .196598007399E-07 .208199552982E-07 .220493325979E-07 .233521526224E-07 + .247328974311E-07 .261963278005E-07 .277475009372E-07 .293917893326E-07 .311349008342E-07 + .329829000119E-07 .349422309040E-07 .370197412336E-07 .392227081895E-07 .415588658745E-07 + .440364345292E-07 .466641516475E-07 .494513051048E-07 .524077684326E-07 .555440383768E-07 + .588712748880E-07 .624013437039E-07 .661468616893E-07 .701212451142E-07 .743387610605E-07 + .788145821596E-07 .835648448764E-07 .886067115712E-07 .939584365812E-07 .996394365846E-07 + .105670365522E-06 .112073194371E-06 .118871296086E-06 .126089536039E-06 .133754368318E-06 + .141893938246E-06 .150538191549E-06 .159718990577E-06 .169470238034E-06 .179828008724E-06 + .190830689788E-06 .202519130018E-06 .214936798801E-06 .228129955327E-06 .242147828705E-06 + .257042809702E-06 .272870654832E-06 .289690703594E-06 .307566109690E-06 .326564087128E-06 + .346756172139E-06 .368218501929E-06 .391032111332E-06 .415283248495E-06 .441063710808E-06 + .468471202359E-06 .497609714270E-06 .528589929370E-06 .561529652727E-06 .596554269675E-06 + .633797233063E-06 .673400581564E-06 .715515490979E-06 .760302860615E-06 .807933936922E-06 + .858590976703E-06 .912467952376E-06 .969771301889E-06 .103072072606E-05 .109555003626E-05 + .116450805559E-05 .123785957678E-05 .131588638035E-05 .139888831671E-05 .148718445608E-05 + .158111431043E-05 .168103913172E-05 .178734329115E-05 .190043574433E-05 .202075158739E-05 + .214875370975E-05 .228493454907E-05 .242981795469E-05 .258396116581E-05 .274795691142E-05 + .292243563898E-05 .310806787948E-05 .330556675685E-05 .351569065019E-05 .373924601751E-05 + .397709039049E-05 .423013554987E-05 .449935089198E-05 .478576699710E-05 .509047941113E-05 + .541465265242E-05 .575952445644E-05 .612641027142E-05 .651670801861E-05 .693190313178E-05 + .737357389105E-05 .784339706665E-05 .834315388946E-05 .887473636521E-05 .944015395058E-05 + .100415406097E-04 .106811622710E-04 .113614247036E-04 .120848818358E-04 .128542445362E-04 + .136723898809E-04 .145423709291E-04 .154674270325E-04 .164509947032E-04 .174967190638E-04 + .186084659092E-04 .197903344043E-04 .210466704466E-04 .223820807216E-04 .238014474792E-04 + .253099440608E-04 .269130512058E-04 .286165741680E-04 .304266606703E-04 .323498197291E-04 + .343929413762E-04 .365633173085E-04 .388686624936E-04 .413171377592E-04 .439173733939E-04 + .466784937828E-04 .496101431055E-04 .527225121145E-04 .560263660175E-04 .595330734786E-04 + .632546367534E-04 .672037229692E-04 .713936965562E-04 .758386528320E-04 .805534527382E-04 + .855537587174E-04 .908560717189E-04 .964777693090E-04 .102437144857E-03 .108753447759E-03 + .115446924650E-03 .122538861549E-03 .130051626865E-03 .138008715186E-03 .146434791756E-03 + .155355737528E-03 .164798694679E-03 .174792112435E-03 .185365793069E-03 .196550937879E-03 + .208380192963E-03 .220887694586E-03 .234109113894E-03 .248081700728E-03 .262844326268E-03 + .278437524200E-03 .294903530092E-03 .312286318645E-03 .330631638438E-03 .349987043795E-03 + .370401923370E-03 .391927525004E-03 .414616976437E-03 .438525301396E-03 .463709430588E-03 + .490228207127E-03 .518142385893E-03 .547514626344E-03 .578409478292E-03 .610893360173E-03 + .645034529359E-03 .680903044093E-03 .718570716657E-03 .758111057440E-03 .799599209646E-03 + .843111874437E-03 .888727226421E-03 .936524819495E-03 .986585483195E-03 .103899120984E-02 + .109382503292E-02 .115117089748E-02 .121111352320E-02 .127373826159E-02 .133913094834E-02 + .140737775294E-02 .147856502718E-02 .155277915525E-02 .163010640797E-02 .171063280434E-02 + .179444398399E-02 .188162509437E-02 .197226069717E-02 .206643469870E-02 .216423030948E-02 + .226573003870E-02 .237101572979E-02 .248016864360E-02 .259326959640E-02 .271039916068E-02 + .283163793710E-02 .295706690745E-02 .308676787920E-02 .322082403378E-02 .335932059220E-02 + .350234561239E-02 .364999093291E-02 .380235327479E-02 .395953550720E-02 .412164806889E-02 + .428881051644E-02 .446115314045E-02 .463881855679E-02 .482196315214E-02 .501075825528E-02 + .520539093344E-02 .540606438254E-02 .561299798267E-02 .582642719909E-02 .604660358714E-02 + .627379516452E-02 .650828731395E-02 .675038417942E-02 .700041028844E-02 .725871197647E-02 + .752565817955E-02 .780164027316E-02 .808707077981E-02 .838238086423E-02 .868801655628E-02 + .900443360736E-02 .933209082854E-02 .967144170169E-02 .100229240120E-01 .103869472209E-01 + .107638772809E-01 .111540185848E-01 .115575927342E-01 .119747138083E-01 .124053598104E-01 + .128493399678E-01 .133062575600E-01 .137754679559E-01 .142560315452E-01 .147466612667E-01 + .152456644480E-01 .157508787005E-01 .162596016357E-01 .167685142012E-01 .172735974648E-01 + .177700427009E-01 .182521546525E-01 .187132478523E-01 .191455358726E-01 .195400133505E-01 + .198863305955E-01 .201726605474E-01 .203855578566E-01 .205098099183E-01 .205282799298E-01 + .204217424344E-01 .201687124905E-01 .197452704861E-01 .191248856466E-01 .182782422416E-01 + .171730730409E-01 .157740040676E-01 .140424119477E-01 .119362882257E-01 .941009223694E-02 + .641455956391E-02 .289643672970E-02 -.120182972349E-02 -.594230845433E-02 -.113915061558E-01 + -.176199584845E-01 -.247017208792E-01 -.327140327375E-01 -.417371826148E-01 -.518544026197E-01 + -.631516436073E-01 -.757171941354E-01 -.896411710603E-01 -.105014918512E+00 -.121930338317E+00 + -.140479159189E+00 -.160752140242E+00 -.182838197398E+00 + End of Dataset diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/INCAR b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/INCAR new file mode 100644 index 000000000..1a9f52780 --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/INCAR @@ -0,0 +1,21 @@ +ADDGRID = True +ALGO = Normal +EDIFF = 1e-08 +ENCUT = 700 +IBRION = -1 +ICHARG = 0 +ISIF = 3 +ISMEAR = 0 +ISPIN = 2 +LAECHG = False +LASPH = True +LCHARG = False +LORBIT = 11 +LREAL = False +LVHAR = True +LWAVE = False +MAGMOM = 128*0.6 +NELM = 100 +NSW = 0 +PREC = Accurate +SIGMA = 0.05 diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/KPOINTS b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/KPOINTS new file mode 100644 index 000000000..6677fab59 --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/KPOINTS @@ -0,0 +1,4 @@ +pymatgen v2020.1.28 with grid density = 1239 / atom +0 +Monkhorst +2 2 2 diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/POSCAR b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/POSCAR new file mode 100644 index 000000000..eb785ce7e --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/POSCAR @@ -0,0 +1,136 @@ +Si128 +1.0 +15.360792 0.000000 0.000000 +7.680396 13.302841 0.000000 +0.000000 -8.868554 12.542036 +Si +128 +direct +0.004419 -0.000206 -0.000856 Si +0.001716 -0.001367 0.250994 Si +0.002871 -0.004453 0.496571 Si +0.000199 0.001004 0.750643 Si +-0.000672 0.253464 0.002350 Si +-0.003594 0.251178 0.252602 Si +0.000081 0.250947 0.503137 Si +0.000449 0.249353 0.751900 Si +0.002693 0.497479 -0.004425 Si +0.000960 0.496715 0.245595 Si +-0.000752 0.502784 0.499361 Si +-0.007283 0.500032 0.753217 Si +0.003741 0.749200 -0.000740 Si +-0.001400 0.749737 0.250047 Si +0.000132 0.751798 0.500399 Si +-0.001588 0.750422 0.746906 Si +0.252396 -0.000527 -0.001692 Si +0.247616 0.000719 0.246260 Si +0.251735 -0.000509 0.501759 Si +0.250663 -0.002549 0.746700 Si +0.243529 0.250402 -0.003080 Si +0.248591 0.253497 0.252598 Si +0.251067 0.251146 0.501087 Si +0.253028 0.248259 0.748963 Si +0.252229 0.497433 -0.005447 Si +0.255737 0.495567 0.247760 Si +0.256858 0.498454 0.497979 Si +0.250017 0.494558 0.749618 Si +0.253598 0.748814 -0.002255 Si +0.249361 0.748185 0.249731 Si +0.249074 0.745734 0.495905 Si +0.245320 0.751543 0.750463 Si +0.500627 0.004722 0.006082 Si +0.500585 0.000886 0.248733 Si +0.500080 -0.004574 0.496196 Si +0.500977 0.001687 0.752934 Si +0.500895 0.249757 -0.001718 Si +0.497767 0.250410 0.249989 Si +0.502624 0.252356 0.504582 Si +0.502054 0.251831 0.748284 Si +0.502678 0.496720 -0.003033 Si +0.502103 0.496828 0.249518 Si +0.498530 0.497817 0.499945 Si +0.501845 0.497086 0.747815 Si +0.499688 0.749119 -0.001771 Si +0.498626 0.756874 0.251304 Si +0.495511 0.752555 0.501879 Si +0.501056 0.750903 0.751113 Si +0.751824 -0.001653 0.003010 Si +0.752569 -0.006292 0.250890 Si +0.749700 0.000960 0.501732 Si +0.747081 0.001600 0.753815 Si +0.749716 0.250449 0.002061 Si +0.747165 0.254844 0.249754 Si +0.747741 0.250044 0.499631 Si +0.749158 0.252723 0.750535 Si +0.753785 0.498736 0.000233 Si +0.750250 0.507911 0.255749 Si +0.748354 0.500599 0.498820 Si +0.752714 0.493600 0.743093 Si +0.746217 0.749203 -0.002251 Si +0.755075 0.749992 0.247867 Si +0.749259 0.752119 0.502124 Si +0.747662 0.751824 0.753020 Si +0.186204 0.127200 0.188827 Si +0.188356 0.124138 0.439900 Si +0.185286 0.125426 0.687308 Si +0.189301 0.124669 0.937938 Si +0.189908 0.371564 0.189809 Si +0.186088 0.377527 0.439945 Si +0.185459 0.374256 0.687623 Si +0.187870 0.377619 0.940800 Si +0.183809 0.631022 0.188910 Si +0.189650 0.622139 0.437493 Si +0.188741 0.628350 0.687871 Si +0.186295 0.627701 0.938973 Si +0.185553 0.876714 0.187931 Si +0.188614 0.875100 0.437290 Si +0.190809 0.873341 0.688654 Si +0.187579 0.873076 0.940127 Si +0.438747 0.121582 0.186361 Si +0.435186 0.124894 0.434709 Si +0.436347 0.125254 0.684250 Si +0.440967 0.123474 0.936608 Si +0.439668 0.372737 0.189247 Si +0.430693 0.376971 0.439410 Si +0.437890 0.373999 0.686350 Si +0.436376 0.378937 0.937187 Si +0.436937 0.627062 0.189243 Si +0.437285 0.629181 0.440075 Si +0.439976 0.622246 0.687670 Si +0.431227 0.628216 0.940327 Si +0.434018 0.876606 0.185760 Si +0.438422 0.872462 0.436441 Si +0.436000 0.875639 0.686955 Si +0.434784 0.877715 0.941421 Si +0.687436 0.121554 0.185661 Si +0.685953 0.124306 0.438298 Si +0.689755 0.119176 0.687189 Si +0.686332 0.128397 0.936948 Si +0.686764 0.378560 0.190140 Si +0.689784 0.379171 0.436946 Si +0.686554 0.380682 0.688244 Si +0.686129 0.374762 0.936997 Si +0.687256 0.620816 0.184061 Si +0.686313 0.628028 0.439813 Si +0.687753 0.626497 0.688568 Si +0.685704 0.628037 0.937508 Si +0.686470 0.877937 0.186396 Si +0.686007 0.878400 0.438826 Si +0.687927 0.872425 0.690325 Si +0.685678 0.873399 0.937346 Si +0.939966 0.121715 0.184463 Si +0.938280 0.125985 0.439959 Si +0.935714 0.125861 0.688139 Si +0.941256 0.121740 0.934856 Si +0.940509 0.370740 0.184174 Si +0.934583 0.375952 0.438550 Si +0.933805 0.375006 0.691141 Si +0.939116 0.373552 0.936880 Si +0.938269 0.626982 0.190164 Si +0.944814 0.622757 0.438232 Si +0.935640 0.629382 0.687222 Si +0.933990 0.629804 0.937675 Si +0.935086 0.877005 0.189286 Si +0.938269 0.874576 0.437978 Si +0.939148 0.875524 0.684622 Si +0.935925 0.874399 0.934462 Si diff --git a/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/POTCAR b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/POTCAR new file mode 100644 index 000000000..ae2291fdf --- /dev/null +++ b/atomate/vasp/test_files/lattice_dynamics_wf/0/outputs/POTCAR @@ -0,0 +1,1768 @@ + PAW_PBE Si 05Jan2001 + 4.00000000000000000 + parameters from PSCTR are: + VRHFIN =Si: s2p2 + LEXCH = PE + EATOM = 103.0669 eV, 7.5752 Ry + + TITEL = PAW_PBE Si 05Jan2001 + LULTRA = F use ultrasoft PP ? + IUNSCR = 1 unscreen: 0-lin 1-nonlin 2-no + RPACOR = 1.500 partial core radius + POMASS = 28.085; ZVAL = 4.000 mass and valenz + RCORE = 1.900 outmost cutoff radius + RWIGS = 2.480; RWIGS = 1.312 wigner-seitz radius (au A) + ENMAX = 245.345; ENMIN = 184.009 eV + ICORE = 2 local potential + LCOR = T correct aug charges + LPAW = T paw PP + EAUG = 322.069 + DEXC = -.007 + RMAX = 2.944 core radius for proj-oper + RAUG = 1.300 factor for augmentation sphere + RDEP = 1.993 radius for radial grids + QCUT = -4.246; QGAM = 8.493 optimization parameters + + Description + l E TYP RCUT TYP RCUT + 0 .000 23 1.900 + 0 .000 23 1.900 + 1 .000 23 1.900 + 1 .000 23 1.900 + 2 .000 7 1.900 + Error from kinetic energy argument (eV) + NDATA = 100 + STEP = 20.000 1.050 + 10.1 9.04 8.56 7.65 7.23 6.44 5.73 5.40 + 4.79 4.25 4.00 3.54 3.13 2.77 2.45 2.16 + 1.91 1.69 1.50 1.24 1.10 .975 .812 .718 + .636 .529 .440 .388 .322 .266 .219 .180 + .148 .121 .986E-01 .804E-01 .614E-01 .504E-01 .392E-01 .328E-01 + .265E-01 .220E-01 .189E-01 .166E-01 .149E-01 .135E-01 .123E-01 .109E-01 + .977E-02 .840E-02 .707E-02 .605E-02 .488E-02 .387E-02 .290E-02 .229E-02 + .185E-02 .152E-02 .134E-02 .125E-02 .121E-02 .117E-02 .112E-02 .102E-02 + .915E-03 .776E-03 .640E-03 .524E-03 .425E-03 .369E-03 .331E-03 .310E-03 + .294E-03 .273E-03 .242E-03 .210E-03 .175E-03 .146E-03 .124E-03 .113E-03 + .105E-03 .973E-04 .879E-04 .755E-04 .633E-04 .539E-04 .478E-04 .438E-04 + .404E-04 .362E-04 .308E-04 .264E-04 .229E-04 .209E-04 .192E-04 .170E-04 + .145E-04 .126E-04 .112E-04 .103E-04 +END of PSCTR-controll parameters + local part + 98.2657514061040160 + .84157696E+01 .84210616E+01 .84276868E+01 .84387430E+01 .84542501E+01 + .84742336E+01 .84987229E+01 .85277486E+01 .85613410E+01 .85995276E+01 + .86423322E+01 .86897735E+01 .87418643E+01 .87986117E+01 .88600162E+01 + .89260725E+01 .89967686E+01 .90720854E+01 .91519966E+01 .92364669E+01 + .93254512E+01 .94188926E+01 .95167214E+01 .96188530E+01 .97251866E+01 + .98356042E+01 .99499691E+01 .10068126E+02 .10189900E+02 .10315095E+02 + .10443498E+02 .10574872E+02 .10708964E+02 .10845497E+02 .10984178E+02 + .11124691E+02 .11266702E+02 .11409858E+02 .11553785E+02 .11698096E+02 + .11842382E+02 .11986223E+02 .12129182E+02 .12270810E+02 .12410650E+02 + .12548232E+02 .12683081E+02 .12814718E+02 .12942658E+02 .13066416E+02 + .13185509E+02 .13299456E+02 .13407780E+02 .13510014E+02 .13605699E+02 + .13694388E+02 .13775652E+02 .13849074E+02 .13914259E+02 .13970835E+02 + .14018449E+02 .14056778E+02 .14085523E+02 .14104415E+02 .14113216E+02 + .14111719E+02 .14099752E+02 .14077176E+02 .14043889E+02 .13999825E+02 + .13944955E+02 .13879288E+02 .13802872E+02 .13715793E+02 .13618173E+02 + .13510175E+02 .13391996E+02 .13263872E+02 .13126073E+02 .12978903E+02 + .12822702E+02 .12657838E+02 .12484712E+02 .12303753E+02 .12115415E+02 + .11920177E+02 .11718543E+02 .11511033E+02 .11298186E+02 .11080557E+02 + .10858712E+02 .10633228E+02 .10404688E+02 .10173679E+02 .99407918E+01 + .97066146E+01 .94717325E+01 .92367246E+01 .90021609E+01 .87686001E+01 + .85365874E+01 .83066514E+01 .80793026E+01 .78550308E+01 .76343035E+01 + .74175636E+01 .72052280E+01 .69976861E+01 .67952984E+01 .65983952E+01 + .64072758E+01 .62222076E+01 .60434252E+01 .58711303E+01 .57054911E+01 + .55466426E+01 .53946862E+01 .52496902E+01 .51116906E+01 .49806911E+01 + .48566645E+01 .47395534E+01 .46292712E+01 .45257038E+01 .44287105E+01 + .43381258E+01 .42537607E+01 .41754049E+01 .41028282E+01 .40357822E+01 + .39740031E+01 .39172124E+01 .38651203E+01 .38174267E+01 .37738238E+01 + .37339979E+01 .36976315E+01 .36644056E+01 .36340010E+01 .36061008E+01 + .35803917E+01 .35565663E+01 .35343243E+01 .35133745E+01 .34934357E+01 + .34742388E+01 .34555274E+01 .34370596E+01 .34186083E+01 .33999627E+01 + .33809285E+01 .33613290E+01 .33410052E+01 .33198164E+01 .32976401E+01 + .32743723E+01 .32499276E+01 .32242387E+01 .31972561E+01 .31689481E+01 + .31393000E+01 .31083133E+01 .30760055E+01 .30424087E+01 .30075693E+01 + .29715463E+01 .29344112E+01 .28962459E+01 .28571426E+01 .28172018E+01 + .27765317E+01 .27352466E+01 .26934662E+01 .26513138E+01 .26089155E+01 + .25663991E+01 .25238927E+01 .24815236E+01 .24394173E+01 .23976966E+01 + .23564804E+01 .23158831E+01 .22760134E+01 .22369739E+01 .21988600E+01 + .21617599E+01 .21257533E+01 .20909116E+01 .20572974E+01 .20249638E+01 + .19939548E+01 .19643045E+01 .19360379E+01 .19091701E+01 .18837069E+01 + .18596450E+01 .18369720E+01 .18156670E+01 .17957010E+01 .17770368E+01 + .17596305E+01 .17434311E+01 .17283816E+01 .17144193E+01 .17014768E+01 + .16894823E+01 .16783607E+01 .16680338E+01 .16584212E+01 .16494415E+01 + .16410120E+01 .16330504E+01 .16254746E+01 .16182040E+01 .16111597E+01 + .16042653E+01 .15974473E+01 .15906355E+01 .15837638E+01 .15767703E+01 + .15695978E+01 .15621941E+01 .15545123E+01 .15465111E+01 .15381544E+01 + .15294125E+01 .15202610E+01 .15106817E+01 .15006619E+01 .14901947E+01 + .14792788E+01 .14679182E+01 .14561221E+01 .14439046E+01 .14312844E+01 + .14182846E+01 .14049321E+01 .13912574E+01 .13772942E+01 .13630791E+01 + .13486509E+01 .13340503E+01 .13193195E+01 .13045019E+01 .12896412E+01 + .12747815E+01 .12599666E+01 .12452397E+01 .12306428E+01 .12162167E+01 + .12020006E+01 .11880314E+01 .11743437E+01 .11609697E+01 .11479386E+01 + .11352766E+01 .11230067E+01 .11111486E+01 .10997186E+01 .10887293E+01 + .10781902E+01 .10681067E+01 .10584813E+01 .10493127E+01 .10405964E+01 + .10323246E+01 .10244865E+01 .10170685E+01 .10100542E+01 .10034245E+01 + .99715846E+00 .99123280E+00 .98562260E+00 .98030145E+00 .97524173E+00 + .97041488E+00 .96579171E+00 .96134265E+00 .95703806E+00 .95284844E+00 + .94874473E+00 .94469858E+00 .94068254E+00 .93667031E+00 .93263696E+00 + .92855909E+00 .92441506E+00 .92018509E+00 .91585142E+00 .91139842E+00 + .90681263E+00 .90208291E+00 .89720039E+00 .89215854E+00 .88695315E+00 + .88158229E+00 .87604630E+00 .87034770E+00 .86449110E+00 .85848313E+00 + .85233229E+00 .84604884E+00 .83964465E+00 .83313300E+00 .82652847E+00 + .81984671E+00 .81310428E+00 .80631845E+00 .79950703E+00 .79268813E+00 + .78588003E+00 .77910097E+00 .77236895E+00 .76570159E+00 .75911593E+00 + .75262828E+00 .74625407E+00 .74000773E+00 .73390251E+00 .72795041E+00 + .72216209E+00 .71654675E+00 .71111209E+00 .70586428E+00 .70080787E+00 + .69594584E+00 .69127954E+00 .68680877E+00 .68253173E+00 .67844513E+00 + .67454418E+00 .67082274E+00 .66727331E+00 .66388721E+00 .66065462E+00 + .65756473E+00 .65460586E+00 .65176555E+00 .64903076E+00 .64638795E+00 + .64382325E+00 .64132257E+00 .63887178E+00 .63645678E+00 .63406371E+00 + .63167900E+00 .62928956E+00 .62688288E+00 .62444710E+00 .62197118E+00 + .61944494E+00 .61685919E+00 .61420575E+00 .61147755E+00 .60866866E+00 + .60577434E+00 .60279104E+00 .59971643E+00 .59654939E+00 .59329003E+00 + .58993961E+00 .58650056E+00 .58297643E+00 .57937181E+00 .57569230E+00 + .57194440E+00 .56813547E+00 .56427363E+00 .56036764E+00 .55642683E+00 + .55246099E+00 .54848026E+00 .54449503E+00 .54051583E+00 .53655322E+00 + .53261771E+00 .52871961E+00 .52486898E+00 .52107551E+00 .51734843E+00 + .51369641E+00 .51012750E+00 .50664907E+00 .50326768E+00 .49998911E+00 + .49681824E+00 .49375908E+00 .49081468E+00 .48798715E+00 .48527763E+00 + .48268632E+00 .48021244E+00 .47785431E+00 .47560930E+00 .47347392E+00 + .47144387E+00 .46951402E+00 .46767855E+00 .46593095E+00 .46426412E+00 + .46267047E+00 .46114194E+00 .45967012E+00 .45824632E+00 .45686169E+00 + .45550723E+00 .45417395E+00 .45285292E+00 .45153535E+00 .45021267E+00 + .44887661E+00 .44751931E+00 .44613331E+00 .44471171E+00 .44324816E+00 + .44173692E+00 .44017295E+00 .43855190E+00 .43687017E+00 .43512491E+00 + .43331405E+00 .43143631E+00 .42949120E+00 .42747899E+00 .42540073E+00 + .42325823E+00 .42105400E+00 .41879126E+00 .41647384E+00 .41410622E+00 + .41169341E+00 .40924089E+00 .40675462E+00 .40424088E+00 .40170629E+00 + .39915769E+00 .39660209E+00 .39404660E+00 .39149835E+00 .38896445E+00 + .38645189E+00 .38396749E+00 .38151784E+00 .37910923E+00 .37674758E+00 + .37443844E+00 .37218685E+00 .36999739E+00 .36787409E+00 .36582039E+00 + .36383915E+00 .36193261E+00 .36010239E+00 .35834945E+00 .35667414E+00 + .35507613E+00 .35355450E+00 .35210772E+00 .35073362E+00 .34942953E+00 + .34819219E+00 .34701788E+00 .34590241E+00 .34484117E+00 .34382921E+00 + .34286125E+00 .34193178E+00 .34103506E+00 .34016522E+00 .33931629E+00 + .33848229E+00 .33765725E+00 .33683525E+00 .33601054E+00 .33517754E+00 + .33433091E+00 .33346559E+00 .33257683E+00 .33166028E+00 .33071198E+00 + .32972841E+00 .32870651E+00 .32764370E+00 .32653791E+00 .32538758E+00 + .32419168E+00 .32294968E+00 .32166161E+00 .32032797E+00 .31894980E+00 + .31752862E+00 .31606640E+00 .31456556E+00 .31302895E+00 .31145977E+00 + .30986158E+00 .30823823E+00 .30659385E+00 .30493275E+00 .30325946E+00 + .30157859E+00 .29989486E+00 .29821301E+00 .29653778E+00 .29487386E+00 + .29322581E+00 .29159807E+00 .28999490E+00 .28842031E+00 .28687807E+00 + .28537164E+00 .28390415E+00 .28247839E+00 .28109677E+00 .27976132E+00 + .27847363E+00 .27723491E+00 .27604592E+00 .27490700E+00 .27381809E+00 + .27277867E+00 .27178784E+00 .27084428E+00 .26994630E+00 .26909186E+00 + .26827855E+00 .26750369E+00 .26676430E+00 .26605715E+00 .26537882E+00 + .26472568E+00 .26409398E+00 .26347988E+00 .26287945E+00 .26228874E+00 + .26170381E+00 .26112076E+00 .26053579E+00 .25994520E+00 .25934545E+00 + .25873320E+00 .25810531E+00 .25745888E+00 .25679129E+00 .25610022E+00 + .25538363E+00 .25463983E+00 .25386744E+00 .25306545E+00 .25223318E+00 + .25137030E+00 .25047684E+00 .24955316E+00 .24859996E+00 .24761829E+00 + .24660949E+00 .24557519E+00 .24451731E+00 .24343801E+00 .24233971E+00 + .24122498E+00 .24009659E+00 .23895746E+00 .23781060E+00 .23665912E+00 + .23550617E+00 .23435492E+00 .23320855E+00 .23207016E+00 .23094281E+00 + .22982945E+00 .22873289E+00 .22765579E+00 .22660063E+00 .22556967E+00 + .22456498E+00 .22358834E+00 .22264131E+00 .22172517E+00 .22084092E+00 + .21998928E+00 .21917068E+00 .21838526E+00 .21763287E+00 .21691308E+00 + .21622517E+00 .21556818E+00 .21494086E+00 .21434175E+00 .21376913E+00 + .21322111E+00 .21269560E+00 .21219035E+00 .21170297E+00 .21123098E+00 + .21077179E+00 .21032276E+00 .20988120E+00 .20944443E+00 .20900979E+00 + .20857462E+00 .20813639E+00 .20769262E+00 .20724095E+00 .20677916E+00 + .20630522E+00 .20581722E+00 .20531350E+00 .20479256E+00 .20425315E+00 + .20369424E+00 .20311502E+00 .20251496E+00 .20189372E+00 .20125124E+00 + .20058769E+00 .19990349E+00 .19919926E+00 .19847589E+00 .19773443E+00 + .19697618E+00 .19620258E+00 .19541527E+00 .19461602E+00 .19380673E+00 + .19298941E+00 .19216618E+00 .19133918E+00 .19051063E+00 .18968276E+00 + .18885780E+00 .18803797E+00 .18722542E+00 .18642227E+00 .18563052E+00 + .18485209E+00 .18408877E+00 .18334220E+00 .18261388E+00 .18190512E+00 + .18121707E+00 .18055068E+00 .17990670E+00 .17928569E+00 .17868800E+00 + .17811376E+00 .17756291E+00 .17703518E+00 .17653009E+00 .17604697E+00 + .17558497E+00 .17514306E+00 .17472002E+00 .17431452E+00 .17392507E+00 + .17355005E+00 .17318776E+00 .17283640E+00 .17249410E+00 .17215895E+00 + .17182901E+00 .17150232E+00 .17117693E+00 .17085094E+00 .17052245E+00 + .17018966E+00 .16985084E+00 .16950435E+00 .16914867E+00 .16878242E+00 + .16840433E+00 .16801331E+00 .16760841E+00 .16718886E+00 .16675406E+00 + .16630358E+00 .16583717E+00 .16535477E+00 .16485650E+00 .16434264E+00 + .16381366E+00 .16327018E+00 .16271301E+00 .16214308E+00 .16156147E+00 + .16096939E+00 .16036817E+00 .15975923E+00 .15914407E+00 .15852427E+00 + .15790145E+00 .15727728E+00 .15665345E+00 .15603163E+00 .15541350E+00 + .15480071E+00 .15419486E+00 .15359747E+00 .15301002E+00 .15243388E+00 + .15187030E+00 .15132044E+00 .15078533E+00 .15026585E+00 .14976275E+00 + .14927662E+00 .14880791E+00 .14835691E+00 .14792374E+00 .14750838E+00 + .14711065E+00 .14673019E+00 .14636653E+00 .14601903E+00 .14568691E+00 + .14536927E+00 .14506509E+00 .14477325E+00 .14449251E+00 .14422157E+00 + .14395905E+00 .14370352E+00 .14345350E+00 .14320750E+00 .14296399E+00 + .14272149E+00 .14247848E+00 .14223350E+00 .14198515E+00 .14173206E+00 + .14147294E+00 .14120659E+00 .14093190E+00 .14064788E+00 .14035363E+00 + .14004840E+00 .13973155E+00 .13940258E+00 .13906112E+00 .13870694E+00 + .13833997E+00 .13796025E+00 .13756799E+00 .13716350E+00 .13674725E+00 + .13631982E+00 .13588193E+00 .13543440E+00 .13497814E+00 .13451417E+00 + .13404360E+00 .13356759E+00 .13308736E+00 .13260419E+00 .13211937E+00 + .13163425E+00 .13115013E+00 .13066836E+00 .13019023E+00 .12971703E+00 + .12924998E+00 .12879027E+00 .12833900E+00 .12789721E+00 .12746584E+00 + .12704575E+00 .12663767E+00 .12624224E+00 .12585999E+00 .12549130E+00 + .12513646E+00 .12479563E+00 .12446883E+00 .12415596E+00 .12385682E+00 + .12357106E+00 .12329824E+00 .12303778E+00 .12278902E+00 .12255119E+00 + .12232344E+00 .12210482E+00 .12189434E+00 .12169092E+00 .12149346E+00 + .12130080E+00 .12111176E+00 .12092515E+00 .12073978E+00 .12055446E+00 + .12036801E+00 .12017930E+00 .11998723E+00 .11979076E+00 .11958890E+00 + .11938073E+00 .11916544E+00 .11894226E+00 .11871055E+00 .11846975E+00 + .11821943E+00 .11795923E+00 .11768892E+00 .11740838E+00 .11711760E+00 + .11681667E+00 .11650581E+00 .11618532E+00 .11585561E+00 .11551720E+00 + .11517070E+00 .11481679E+00 .11445623E+00 .11408986E+00 .11371858E+00 + .11334333E+00 .11296511E+00 .11258491E+00 .11220379E+00 .11182279E+00 + .11144296E+00 .11106534E+00 .11069096E+00 .11032079E+00 .10995580E+00 + .10959689E+00 .10924491E+00 .10890064E+00 .10856478E+00 .10823798E+00 + .10792077E+00 .10761362E+00 .10731688E+00 .10703084E+00 .10675565E+00 + .10649140E+00 .10623807E+00 .10599552E+00 .10576356E+00 .10554186E+00 + .10533004E+00 .10512760E+00 .10493399E+00 .10474857E+00 .10457063E+00 + .10439942E+00 .10423412E+00 .10407387E+00 .10391779E+00 .10376497E+00 + .10361446E+00 .10346535E+00 .10331669E+00 .10316756E+00 .10301705E+00 + .10286430E+00 .10270846E+00 .10254874E+00 .10238439E+00 .10221475E+00 + .10203918E+00 .10185715E+00 .10166820E+00 .10147193E+00 .10126804E+00 + .10105631E+00 .10083661E+00 .10060889E+00 .10037320E+00 .10012965E+00 + .99878467E-01 .99619932E-01 .99354416E-01 .99082363E-01 .98804288E-01 + .98520765E-01 .98232428E-01 .97939960E-01 .97644087E-01 .97345569E-01 + .97045195E-01 .96743772E-01 .96442116E-01 .96141050E-01 .95841391E-01 + .95543942E-01 .95249488E-01 .94958785E-01 .94672554E-01 .94391474E-01 + .94116174E-01 .93847229E-01 .93585152E-01 .93330392E-01 .93083329E-01 + .92844268E-01 .92613442E-01 .92391008E-01 .92177045E-01 .91971556E-01 + .91774467E-01 .91585628E-01 .91404815E-01 .91231735E-01 .91066024E-01 + .90907255E-01 .90754941E-01 .90608543E-01 .90467470E-01 .90331093E-01 + .90198744E-01 .90069732E-01 .89943339E-01 .89818838E-01 .89695492E-01 + .89572566E-01 .89449332E-01 .89325075E-01 .89199102E-01 .89070749E-01 + .88939383E-01 .88804416E-01 .88665301E-01 .88521548E-01 .88372720E-01 + .88218440E-01 .88058396E-01 .87892342E-01 .87720097E-01 .87541550E-01 + .87356660E-01 .87165453E-01 .86968025E-01 .86764537E-01 .86555218E-01 + .86340357E-01 .86120303E-01 .85895462E-01 .85666290E-01 .85433289E-01 + .85197004E-01 .84958012E-01 .84716921E-01 .84474359E-01 .84230970E-01 + .83987410E-01 .83744335E-01 .83502399E-01 .83262247E-01 .83024506E-01 + .82789784E-01 .82558658E-01 .82331673E-01 .82109336E-01 .81892108E-01 + .81680401E-01 .81474576E-01 .81274938E-01 .81081732E-01 .80895145E-01 + .80715299E-01 .80542258E-01 .80376020E-01 .80216523E-01 .80063643E-01 + .79917196E-01 .79776941E-01 .79642582E-01 .79513768E-01 .79390103E-01 + .79271145E-01 .79156412E-01 .79045389E-01 .78937532E-01 .78832272E-01 + .78729025E-01 .78627196E-01 .78526182E-01 .78425382E-01 .78324201E-01 + .78222055E-01 .78118379E-01 .78012628E-01 .77904287E-01 .77792874E-01 + .77677943E-01 .77559095E-01 .77435971E-01 .77308267E-01 .77175728E-01 + .77038154E-01 .76895403E-01 .76747386E-01 .76594073E-01 .76435492E-01 + .76271726E-01 .76102913E-01 .75929245E-01 .75750968E-01 .75568374E-01 + gradient corrections used for XC + 5 + core charge-density (partial) + .13681950E+01 .13676960E+01 .13662001E+01 .13637105E+01 .13602325E+01 + .13557734E+01 .13503429E+01 .13439524E+01 .13366153E+01 .13283473E+01 + .13191655E+01 .13090892E+01 .12981393E+01 .12863384E+01 .12737107E+01 + .12602820E+01 .12460794E+01 .12311314E+01 .12154677E+01 .11991194E+01 + .11821181E+01 .11644970E+01 .11462895E+01 .11275301E+01 .11082538E+01 + .10884962E+01 .10682931E+01 .10476808E+01 .10266957E+01 .10053741E+01 + .98375267E+00 .96186759E+00 .93975503E+00 .91745077E+00 .89499021E+00 + .87240826E+00 .84973926E+00 .82701690E+00 .80427415E+00 .78154320E+00 + .75885536E+00 .73624104E+00 .71372967E+00 .69134969E+00 .66912843E+00 + .64709213E+00 .62526592E+00 .60367371E+00 .58233824E+00 .56128104E+00 + .54052238E+00 .52008130E+00 .49997559E+00 .48022178E+00 .46083513E+00 + .44182968E+00 .42321820E+00 .40501225E+00 .38722216E+00 .36985707E+00 + .35292495E+00 .33643262E+00 .32038578E+00 .30478902E+00 .28964588E+00 + .27495886E+00 .26072949E+00 .24695832E+00 .23364498E+00 .22078822E+00 + .20838596E+00 .19643530E+00 .18493258E+00 .17387344E+00 .16325283E+00 + .15306507E+00 .14330386E+00 .13396240E+00 .12503332E+00 .11650883E+00 + .10838067E+00 .10064023E+00 .93278522E-01 .86286250E-01 .79653846E-01 + .73371505E-01 .67429216E-01 .61816797E-01 .56523934E-01 .51540202E-01 + .46855108E-01 .42458109E-01 .38338647E-01 .34486174E-01 .30890174E-01 + .27540191E-01 .24425850E-01 .21536879E-01 .18863125E-01 .16394577E-01 + .14121382E-01 .12033860E-01 .10122516E-01 .83780589E-02 .67914092E-02 + .53537108E-02 .40563408E-02 .28909177E-02 .18493086E-02 .92363545E-03 + .10628041E-03 -.61011044E-03 -.12326237E-02 -.17680763E-02 -.22230146E-02 + -.26037134E-02 -.29161762E-02 -.31661368E-02 -.33590603E-02 -.35001462E-02 + -.35943310E-02 -.36462916E-02 -.36604501E-02 -.36409780E-02 -.35918012E-02 + -.35166058E-02 -.34188439E-02 -.33017396E-02 -.31682957E-02 -.30213004E-02 + -.28633344E-02 -.26967780E-02 -.25238182E-02 -.23464568E-02 -.21665171E-02 + -.19856525E-02 -.18053531E-02 -.16269545E-02 -.14516446E-02 -.12804716E-02 + -.11143516E-02 -.95407590E-03 -.80031868E-03 -.65364406E-03 -.51451335E-03 + -.38329201E-03 -.26025656E-03 -.14560117E-03 -.39444206E-04 .58165516E-04 + .14724263E-03 .22785937E-03 .30013989E-03 .36425487E-03 .42041630E-03 + .46887251E-03 .50990347E-03 .54381628E-03 .57094091E-03 .59162620E-03 + .60623608E-03 .61514601E-03 .61873968E-03 .61740593E-03 .61153588E-03 + .60152031E-03 .58774722E-03 .57059965E-03 .55045362E-03 .52767640E-03 + .50262485E-03 .47564400E-03 .44706580E-03 .41720805E-03 .38637350E-03 + .35484906E-03 .32290522E-03 .29079555E-03 .25875641E-03 .22700669E-03 + .19574775E-03 .16516340E-03 .13542004E-03 .10666685E-03 .79036088E-04 + .52643451E-04 .27588517E-04 .39552464E-05 -.18187465E-04 -.38785178E-04 + -.57797264E-04 -.75196221E-04 -.90966959E-04 -.10510606E-03 -.11762104E-03 + -.12852953E-03 -.13785858E-03 -.14564378E-03 -.15192858E-03 -.15676343E-03 + -.16020507E-03 -.16231575E-03 -.16316249E-03 -.16281641E-03 -.16135195E-03 + -.15884628E-03 -.15537859E-03 -.15102952E-03 -.14588056E-03 -.14001345E-03 + -.13350974E-03 -.12645021E-03 -.11891448E-03 -.11098056E-03 -.10272445E-03 + -.94219808E-04 -.85537643E-04 -.76746000E-04 -.67909727E-04 -.59090263E-04 + -.50345446E-04 -.41729367E-04 -.33292247E-04 -.25080349E-04 -.17135911E-04 + -.94971159E-05 -.21980781E-05 .47311376E-05 .11264479E-04 .17379846E-04 + .23059012E-04 .28287521E-04 .33054577E-04 .37352910E-04 .41178632E-04 + .44531079E-04 .47412645E-04 .49828605E-04 .51786930E-04 .53298094E-04 + .54374884E-04 .55032195E-04 .55286832E-04 .55157309E-04 .54663646E-04 + .53827166E-04 .52670302E-04 .51216402E-04 .49489534E-04 .47514310E-04 + .45315700E-04 .42918863E-04 .40348986E-04 .37631124E-04 .34790051E-04 + .31850126E-04 .28835162E-04 .25768303E-04 .22671916E-04 .19567494E-04 + .16475560E-04 .13415592E-04 .10405948E-04 .74638126E-05 .46051404E-05 + .18446197E-05 -.80436009E-06 -.33297302E-05 -.57207550E-05 -.79680369E-05 + -.10063512E-04 -.12000439E-04 -.13773381E-04 -.15378177E-04 -.16811912E-04 + -.18072880E-04 -.19160536E-04 -.20075451E-04 -.20819258E-04 -.21394593E-04 + -.21805038E-04 -.22055054E-04 -.22149917E-04 -.22095649E-04 -.21898951E-04 + -.21567128E-04 -.21108022E-04 -.20529940E-04 -.19841582E-04 -.19051971E-04 + -.18170387E-04 -.17206293E-04 -.16169276E-04 -.15068980E-04 -.13915042E-04 + -.12717039E-04 -.11484427E-04 -.10226489E-04 -.89522887E-05 -.76706186E-05 + -.63899617E-05 -.51184500E-05 -.38638299E-05 -.26334298E-05 -.14341327E-05 + -.27235171E-06 .84599016E-06 .19154768E-05 .29312118E-05 .38888277E-05 + .47844919E-05 .56149089E-05 .63773192E-05 .70694955E-05 .76897350E-05 + .82368500E-05 .87101545E-05 .91094496E-05 .94350052E-05 .96875413E-05 + .98682052E-05 .99785491E-05 .10020505E-04 .99963570E-05 .99087173E-05 + .97604944E-05 .95548661E-05 .92952495E-05 .89852710E-05 .86287366E-05 + .82296019E-05 .77919423E-05 .73199237E-05 .68177739E-05 .62897539E-05 + .57401315E-05 .51731543E-05 .45930247E-05 .40038758E-05 .34097487E-05 + .28145712E-05 .22221377E-05 .16360907E-05 .10599042E-05 .49686829E-06 + -.49924253E-07 -.57759018E-06 -.10834658E-05 -.15651156E-05 -.20203391E-05 + -.24471763E-05 -.28439110E-05 -.32090729E-05 -.35414382E-05 -.38400286E-05 + -.41041086E-05 -.43331819E-05 -.45269862E-05 -.46854867E-05 -.48088688E-05 + -.48975294E-05 -.49520671E-05 -.49732722E-05 -.49621152E-05 -.49197348E-05 + -.48474253E-05 -.47466238E-05 -.46188963E-05 -.44659241E-05 -.42894897E-05 + -.40914626E-05 -.38737848E-05 -.36384571E-05 -.33875243E-05 -.31230618E-05 + -.28471617E-05 -.25619196E-05 -.22694215E-05 -.19717316E-05 -.16708804E-05 + -.13688530E-05 -.10675792E-05 -.76892250E-06 -.47467171E-06 -.18653188E-06 + .93883276E-07 .36505838E-06 .62558254E-06 .87415472E-06 .11095882E-05 + .13308143E-05 .15368851E-05 .17269757E-05 .19003854E-05 .20565379E-05 + .21949813E-05 .23153868E-05 .24175471E-05 .25013741E-05 .25668952E-05 + .26142503E-05 .26436874E-05 .26555573E-05 .26503093E-05 .26284844E-05 + .25907101E-05 .25376938E-05 .24702158E-05 .23891225E-05 .22953197E-05 + .21897645E-05 .20734587E-05 .19474411E-05 .18127798E-05 .16705653E-05 + .15219029E-05 .13679056E-05 .12096872E-05 .10483551E-05 .88500422E-06 + .72071043E-06 .55652452E-06 .39346658E-06 .23252066E-06 .74629737E-07 + -.79308789E-07 -.22844732E-06 -.37199180E-06 -.50920504E-06 -.63940961E-06 + -.76199029E-06 -.87639606E-06 -.98214167E-06 -.10788088E-05 -.11660466E-05 + -.12435721E-05 -.13111700E-05 -.13686922E-05 -.14160567E-05 -.14532461E-05 + -.14803064E-05 -.14973448E-05 -.15045271E-05 -.15020754E-05 -.14902650E-05 + -.14694216E-05 -.14399174E-05 -.14021681E-05 -.13566289E-05 -.13037909E-05 + -.12441768E-05 -.11783371E-05 -.11068459E-05 -.10302970E-05 -.94929926E-06 + -.86447308E-06 -.77644588E-06 -.68584828E-06 -.59331011E-06 -.49945662E-06 + -.40490476E-06 -.31025967E-06 -.21611128E-06 -.12303110E-06 -.31569232E-07 + .57748417E-07 .14442274E-06 .22798375E-06 .30799272E-06 .38404404E-06 + .45576684E-06 .52282633E-06 .58492498E-06 .64180332E-06 .69324058E-06 + .73905504E-06 .77910418E-06 .81328449E-06 .84153118E-06 .86381756E-06 + .88015426E-06 .89058820E-06 .89520145E-06 .89410978E-06 .88746118E-06 + .87543410E-06 .85823565E-06 .83609958E-06 .80928424E-06 .77807038E-06 + .74275888E-06 .70366841E-06 .66113309E-06 .61550004E-06 .56712696E-06 + .51637968E-06 .46362976E-06 .40925205E-06 .35362235E-06 .29711509E-06 + .24010107E-06 .18294532E-06 .12600496E-06 .69627264E-07 .14147759E-07 + -.40111547E-07 -.92843792E-07 -.14375878E-06 -.19258433E-06 -.23906756E-06 + -.28297591E-06 -.32409812E-06 -.36224500E-06 -.39725006E-06 -.42897001E-06 + -.45728507E-06 -.48209916E-06 -.50333994E-06 -.52095868E-06 -.53493001E-06 + -.54525155E-06 -.55194338E-06 -.55504739E-06 -.55462656E-06 -.55076402E-06 + -.54356216E-06 -.53314150E-06 -.51963959E-06 -.50320973E-06 -.48401975E-06 + -.46225056E-06 -.43809484E-06 -.41175555E-06 -.38344448E-06 -.35338073E-06 + -.32178926E-06 -.28889934E-06 -.25494308E-06 -.22015395E-06 -.18476531E-06 + -.14900903E-06 -.11311405E-06 -.77305110E-07 -.41801433E-07 -.68155287E-08 + .27447957E-07 .60793314E-07 .93034769E-07 .12399739E-06 .15351793E-06 + .18144553E-06 .20764243E-06 .23198447E-06 .25436154E-06 .27467801E-06 + .29285294E-06 .30882027E-06 .32252892E-06 .33394275E-06 .34304049E-06 + .34981549E-06 .35427554E-06 .35644241E-06 .35635150E-06 .35405130E-06 + .34960280E-06 .34307888E-06 .33456359E-06 .32415143E-06 .31194653E-06 + .29806180E-06 .28261809E-06 .26574327E-06 .24757131E-06 .22824130E-06 + .20789655E-06 .18668360E-06 .16475125E-06 .14224962E-06 .11932921E-06 + .96139976E-07 .72830407E-07 .49546673E-07 .26431773E-07 .36247299E-08 + -.18740176E-07 -.40534125E-07 -.61634436E-07 -.81925182E-07 -.10129776E-06 + -.11965142E-06 -.13689368E-06 -.15294077E-06 -.16771791E-06 -.18115966E-06 + -.19321005E-06 -.20382276E-06 -.21296125E-06 -.22059870E-06 -.22671807E-06 + -.23131193E-06 -.23438237E-06 -.23594076E-06 -.23600750E-06 -.23461175E-06 + -.23179103E-06 -.22759086E-06 -.22206431E-06 -.21527152E-06 -.20727921E-06 + -.19816014E-06 -.18799253E-06 -.17685950E-06 -.16484845E-06 -.15205045E-06 + -.13855963E-06 -.12447250E-06 -.10988738E-06 -.94903693E-07 -.79621403E-07 + -.64140357E-07 -.48559691E-07 -.32977235E-07 -.17488949E-07 -.21883673E-08 + .12833922E-07 .27490772E-07 .41698943E-07 .55379535E-07 .68458384E-07 + .80866426E-07 .92540020E-07 .10342123E-06 .11345807E-06 .12260472E-06 + .13082167E-06 .13807584E-06 .14434069E-06 .14959622E-06 .15382900E-06 + .15703211E-06 .15920506E-06 .16035369E-06 .16048999E-06 .15963194E-06 + .15780325E-06 .15503317E-06 .15135615E-06 .14681154E-06 .14144331E-06 + .13529963E-06 .12843256E-06 .12089759E-06 .11275333E-06 .10406100E-06 + .94884087E-07 .85287862E-07 .75338981E-07 .65105041E-07 .54654154E-07 + .44054522E-07 .33374019E-07 .22679784E-07 .12037823E-07 .15126319E-08 + -.88331734E-08 -.18939204E-07 -.28747623E-07 -.38203459E-07 -.47254879E-07 + -.55853459E-07 -.63954411E-07 -.71516793E-07 -.78503690E-07 -.84882368E-07 + -.90624396E-07 -.95705746E-07 -.10010686E-06 -.10381269E-06 -.10681271E-06 + -.10910090E-06 -.11067571E-06 -.11153996E-06 -.11170080E-06 -.11116954E-06 + -.10996154E-06 -.10809603E-06 -.10559591E-06 -.10248761E-06 -.98800764E-07 + -.94568078E-07 -.89825012E-07 -.84609535E-07 -.78961853E-07 -.72924121E-07 + -.66540155E-07 -.59855131E-07 -.52915295E-07 -.45767653E-07 -.38459679E-07 + -.31039013E-07 -.23553171E-07 -.16049254E-07 -.85736709E-08 -.11718662E-08 + .61119401E-08 .13235002E-07 .20156282E-07 .26836672E-07 .33239202E-07 + .39329224E-07 .45074589E-07 .50445798E-07 .55416137E-07 .59961796E-07 + .64061959E-07 .67698890E-07 .70857979E-07 .73527788E-07 .75700062E-07 + .77369726E-07 .78534869E-07 .79196695E-07 .79359469E-07 .79030439E-07 + .78219742E-07 .76940295E-07 .75207668E-07 .73039951E-07 .70457594E-07 + .67483252E-07 .64141602E-07 .60459169E-07 .56464125E-07 .52186096E-07 + .47655955E-07 .42905616E-07 .37967819E-07 .32875920E-07 .27663675E-07 + .22365030E-07 .17013912E-07 .11644017E-07 .62886154E-08 .98035002E-09 + -.42489487E-08 -.93684454E-08 -.14348472E-07 -.19160688E-07 -.23778234E-07 + -.28175873E-07 -.32330112E-07 -.36219324E-07 -.39823850E-07 -.43126080E-07 + -.46110537E-07 -.48763931E-07 -.51075210E-07 -.53035587E-07 -.54638563E-07 + -.55879925E-07 -.56757740E-07 -.57272329E-07 -.57426230E-07 -.57224146E-07 + -.56672886E-07 -.55781287E-07 -.54560129E-07 -.53022041E-07 -.51181392E-07 + -.49054178E-07 -.46657901E-07 -.44011436E-07 -.41134893E-07 -.38049481E-07 + -.34777357E-07 -.31341477E-07 -.27765446E-07 -.24073361E-07 -.20289659E-07 + -.16438960E-07 -.12545917E-07 -.86350647E-08 -.47306693E-08 -.85658746E-09 + .29638742E-08 .67080927E-08 .10354256E-07 .13881483E-07 .17269938E-07 + .20500935E-07 .23557035E-07 .26422131E-07 .29081528E-07 .31522012E-07 + .33731907E-07 .35701122E-07 .37421190E-07 .38885296E-07 .40088291E-07 + .41026702E-07 .41698723E-07 .42104208E-07 .42244640E-07 .42123103E-07 + .41744235E-07 .41114181E-07 .40240528E-07 .39132243E-07 .37799593E-07 + .36254067E-07 .34508283E-07 .32575899E-07 .30471515E-07 .28210563E-07 + .25809209E-07 .23284239E-07 .20652949E-07 .17933030E-07 .15142458E-07 + .12299377E-07 .94219886E-08 .65284367E-08 .36367011E-08 .76448864E-09 + -.20708706E-08 -.48525235E-08 -.75641896E-08 -.10190252E-07 -.12715843E-07 + -.15126924E-07 -.17410360E-07 -.19553985E-07 -.21546662E-07 -.23378338E-07 + -.25040091E-07 -.26524161E-07 -.27823991E-07 -.28934240E-07 -.29850805E-07 + -.30570824E-07 -.31092681E-07 -.31415990E-07 -.31541587E-07 -.31471506E-07 + -.31208947E-07 -.30758242E-07 -.30124811E-07 -.29315117E-07 -.28336607E-07 + -.27197656E-07 -.25907504E-07 -.24476182E-07 -.22914446E-07 -.21233696E-07 + -.19445902E-07 -.17563519E-07 -.15599409E-07 -.13566750E-07 -.11478958E-07 + -.93495989E-08 -.71923027E-08 -.50206814E-08 -.28482455E-08 -.68832285E-09 + .14460198E-08 .35420528E-08 .55874571E-08 .75703930E-08 .94795661E-08 + .11304289E-07 .13034536E-07 .14660999E-07 .16175132E-07 .17569192E-07 + .18836275E-07 .19970351E-07 .20966282E-07 .21819848E-07 .22527755E-07 + .23087645E-07 .23498096E-07 .23758620E-07 .23869653E-07 .23832536E-07 + .23649501E-07 .23323639E-07 .22858875E-07 .22259928E-07 .21532276E-07 + .20682107E-07 .19716277E-07 .18642256E-07 .17468077E-07 .16202275E-07 + .14853832E-07 .13432115E-07 .11946814E-07 .10407878E-07 .88254519E-08 + .72098100E-08 .55712944E-08 .39202488E-08 .22669566E-08 .62157842E-09 + -.10059081E-08 -.26057666E-08 -.41685584E-08 -.56851958E-08 -.71469932E-08 + -.85457147E-08 -.98736182E-08 -.11123496E-07 -.12288713E-07 -.13363238E-07 + -.14341672E-07 -.15219277E-07 -.15991990E-07 -.16656444E-07 -.17209978E-07 + -.17650643E-07 -.17977205E-07 -.18189145E-07 -.18286649E-07 -.18270602E-07 + -.18142572E-07 -.17904790E-07 -.17560130E-07 -.17112081E-07 -.16564719E-07 + -.15922676E-07 -.15191103E-07 -.14375631E-07 -.13482331E-07 -.12517674E-07 + -.11488483E-07 -.10401887E-07 -.92652762E-08 -.80862521E-08 -.68725780E-08 + -.56321299E-08 -.43728474E-08 -.31026842E-08 -.18295592E-08 -.56130924E-09 + .69435835E-09 .19299107E-08 .31380331E-08 .43116711E-08 .54440703E-08 + .65288132E-08 .75598547E-08 .85315540E-08 .94387041E-08 .10276558E-07 + .11040851E-07 .11727823E-07 .12334232E-07 .12857371E-07 .13295074E-07 + .13645724E-07 .13908258E-07 .14082165E-07 .14167479E-07 .14164778E-07 + .14075170E-07 .13900281E-07 .13642236E-07 .13303645E-07 .12887576E-07 + .12397533E-07 .11837429E-07 .11211558E-07 .10524561E-07 .97813978E-08 + .89873084E-08 .81477813E-08 .72685147E-08 .63553801E-08 .54143841E-08 + .44516300E-08 .34732798E-08 .24855153E-08 .14945008E-08 .50634509E-09 + -.47293461E-09 -.14374486E-08 -.23814688E-08 -.32994621E-08 -.41861213E-08 + -.50363950E-08 -.58455154E-08 -.66090238E-08 -.73227938E-08 -.79830533E-08 + -.85864022E-08 -.91298293E-08 -.96107260E-08 -.10026897E-07 -.10376569E-07 + atomic pseudo charge-density + .40000000E+01 .39865777E+01 .39466377E+01 .38811433E+01 .37916420E+01 + .36801845E+01 .35492225E+01 .34014950E+01 .32399100E+01 .30674335E+01 + .28869885E+01 .27013712E+01 .25131849E+01 .23247937E+01 .21382919E+01 + .19554911E+01 .17779180E+01 .16068237E+01 .14431992E+01 .12877965E+01 + .11411517E+01 .10036103E+01 .87535141E+00 .75641220E+00 .64671001E+00 + .54606321E+00 .45420994E+00 .37082490E+00 .29553413E+00 .22792793E+00 + .16757210E+00 .11401744E+00 .66807913E-01 .25487409E-01 -.10394612E-01 + -.41278562E-01 -.67591071E-01 -.89742138E-01 -.10812299E+00 -.12310456E+00 + -.13503646E+00 -.14424640E+00 -.15104001E+00 -.15570097E+00 -.15849133E+00 + -.15965211E+00 -.15940402E+00 -.15794831E+00 -.15546772E+00 -.15212749E+00 + -.14807638E+00 -.14344771E+00 -.13836047E+00 -.13292033E+00 -.12722065E+00 + -.12134348E+00 -.11536052E+00 -.10933401E+00 -.10331756E+00 -.97357004E-01 + -.91491144E-01 -.85752437E-01 -.80167666E-01 -.74758549E-01 -.69542302E-01 + -.64532148E-01 -.59737801E-01 -.55165888E-01 -.50820352E-01 -.46702805E-01 + -.42812854E-01 -.39148390E-01 -.35705858E-01 -.32480486E-01 -.29466501E-01 + -.26657315E-01 -.24045694E-01 -.21623904E-01 -.19383841E-01 -.17317148E-01 + -.15415313E-01 -.13669756E-01 -.12071903E-01 -.10613252E-01 -.92854249E-02 + -.80802150E-02 -.69896243E-02 -.60058943E-02 -.51215314E-02 -.43293260E-02 + -.36223673E-02 -.29940535E-02 -.24380983E-02 -.19485349E-02 -.15197159E-02 + -.11463120E-02 -.82330764E-03 -.54599586E-03 -.30997081E-03 -.11111957E-03 + .54387194E-04 .19010535E-03 .29932800E-03 .38509665E-03 .45021268E-03 + .49724900E-03 .52856177E-03 .54630216E-03 .55242795E-03 .54871497E-03 + .53676839E-03 .51803365E-03 .49380712E-03 .46524642E-03 .43338037E-03 + .39911853E-03 .36326031E-03 .32650377E-03 .28945387E-03 .25263036E-03 + .21647525E-03 .18135985E-03 .14759141E-03 .11541928E-03 .85040816E-04 + .56606764E-04 .30226352E-04 .59719919E-05 -.16116354E-04 -.36027141E-04 + -.53773520E-04 -.69389928E-04 -.82928949E-04 -.94458459E-04 -.10405902E-03 + -.11182151E-03 -.11784499E-03 -.12223478E-03 -.12510073E-03 -.12655567E-03 + -.12671407E-03 -.12569076E-03 -.12359997E-03 -.12055430E-03 -.11666399E-03 + -.11203621E-03 -.10677448E-03 -.10097820E-03 -.94742231E-04 -.88156609E-04 + -.81306283E-04 -.74270942E-04 -.67124899E-04 -.59937023E-04 -.52770714E-04 + -.45683928E-04 -.38729233E-04 -.31953896E-04 -.25400000E-04 -.19104585E-04 + -.13099806E-04 -.74131135E-05 -.20674438E-05 .29185776E-05 .75304221E-05 + .11757438E-04 .15592625E-04 .19032404E-04 .22076388E-04 .24727147E-04 + .26989979E-04 .28872677E-04 .30385308E-04 .31539981E-04 .32350635E-04 + .32832821E-04 .33003493E-04 .32880805E-04 .32483918E-04 .31832808E-04 + .30948085E-04 .29850818E-04 .28562372E-04 .27104248E-04 .25497933E-04 + .23764761E-04 .21925781E-04 .20001631E-04 .18012428E-04 .15977661E-04 + .13916095E-04 .11845684E-04 .97834913E-05 .77456253E-05 .57471751E-05 + .38021614E-05 .19234941E-05 .12293798E-06 -.15889121E-05 -.32026485E-05 + -.47100596E-05 -.61041317E-05 -.73790420E-05 -.85301460E-05 -.95539569E-05 + -.10448119E-04 -.11211374E-04 -.11843524E-04 -.12345387E-04 -.12718747E-04 + -.12966301E-04 -.13091602E-04 -.13099000E-04 -.12993572E-04 -.12781064E-04 + -.12467816E-04 -.12060693E-04 -.11567014E-04 -.10994484E-04 -.10351114E-04 + -.96451558E-05 -.88850290E-05 -.80792508E-05 -.72363684E-05 -.63648931E-05 + -.54732369E-05 -.45696518E-05 -.36621723E-05 -.27585615E-05 -.18662606E-05 + -.99234299E-06 -.14347216E-06 .67413606E-06 .14547465E-05 .21931331E-05 + .28846026E-05 .35250133E-05 .41107897E-05 .46389311E-05 .51070171E-05 + .55132071E-05 .58562363E-05 .61354066E-05 .63505743E-05 .65021328E-05 + .65909923E-05 .66185560E-05 .65866927E-05 .64977074E-05 .63543081E-05 + .61595714E-05 .59169057E-05 .56300130E-05 .53028493E-05 .49395841E-05 + .45445596E-05 .41222492E-05 .36772171E-05 .32140765E-05 .27374510E-05 + .22519347E-05 .17620554E-05 .12722380E-05 .78677129E-06 .30977508E-06 + -.15482897E-06 -.60334483E-06 -.10323267E-05 -.14386008E-05 -.18192846E-05 + -.21718029E-05 -.24939006E-05 -.27836530E-05 -.30394730E-05 -.32601147E-05 + -.34446746E-05 -.35925898E-05 -.37036332E-05 -.37779061E-05 -.38158282E-05 + -.38181253E-05 -.37858143E-05 -.37201867E-05 -.36227899E-05 -.34954069E-05 + -.33400340E-05 -.31588583E-05 -.29542334E-05 -.27286543E-05 -.24847319E-05 + -.22251674E-05 -.19527264E-05 -.16702126E-05 -.13804427E-05 -.10862214E-05 + -.79031713E-06 -.49543860E-06 -.20421280E-06 .80835994E-07 .35730573E-06 + .62293455E-06 .87561703E-06 .11134188E-05 .13345890E-05 .15375714E-05 + .17210128E-05 .18837700E-05 .20249147E-05 .21437361E-05 .22397418E-05 + .23126566E-05 .23624198E-05 .23891799E-05 .23932885E-05 .23752919E-05 + .23359216E-05 .22760829E-05 .21968428E-05 .20994165E-05 .19851530E-05 + .18555195E-05 .17120855E-05 .15565066E-05 .13905072E-05 .12158635E-05 + .10343865E-05 .84790465E-06 .65824737E-06 .46722828E-06 .27662940E-06 + .88185931E-07 -.96428306E-07 -.27561447E-06 -.44786132E-06 -.61175681E-06 + -.76599844E-06 -.90940250E-06 -.10409120E-05 -.11596031E-05 -.12646906E-05 + -.13555318E-05 -.14316288E-05 -.14926300E-05 -.15383297E-05 -.15686666E-05 + -.15837213E-05 -.15837121E-05 -.15689899E-05 -.15400323E-05 -.14974360E-05 + -.14419091E-05 -.13742618E-05 -.12953968E-05 -.12062995E-05 -.11080263E-05 + -.10016944E-05 -.88846949E-06 -.76955446E-06 -.64617751E-06 -.51958041E-06 + -.39100686E-06 -.26169110E-06 -.13284687E-06 -.56567587E-08 .11873791E-06 + .23924662E-06 .35483853E-06 .46455060E-06 .56749495E-06 .66286537E-06 + .74994293E-06 .82810073E-06 .89680762E-06 .95563110E-06 .10042391E-05 + .10424010E-05 .10699876E-05 .10869699E-05 .10934176E-05 .10894963E-05 + .10754638E-05 .10516660E-05 .10185318E-05 .97656733E-06 .92634993E-06 + .86852113E-06 .80377954E-06 .73287323E-06 .65659178E-06 .57575821E-06 + .49122066E-06 .40384412E-06 .31450207E-06 .22406824E-06 .13340862E-06 + .43373545E-07 -.45209782E-07 -.13154447E-06 -.21487070E-06 -.29447198E-06 + -.36968088E-06 -.43988425E-06 -.50452780E-06 -.56312000E-06 -.61523545E-06 + -.66051743E-06 -.69867990E-06 -.72950871E-06 -.75286218E-06 -.76867098E-06 + -.77693736E-06 -.77773372E-06 -.77120057E-06 -.75754389E-06 -.73703197E-06 + -.70999169E-06 -.67680437E-06 -.63790116E-06 -.59375810E-06 -.54489085E-06 + -.49184910E-06 -.43521085E-06 -.37557652E-06 -.31356289E-06 -.24979711E-06 + -.18491069E-06 -.11953347E-06 -.54287909E-07 .10216647E-07 .73389332E-07 + .13466292E-06 .19349867E-06 .24939075E-06 .30187039E-06 .35050951E-06 + .39492395E-06 .43477623E-06 .46977785E-06 .49969099E-06 .52432989E-06 + .54356153E-06 .55730595E-06 .56553599E-06 .56827660E-06 .56560363E-06 + .55764217E-06 .54456455E-06 .52658783E-06 .50397094E-06 .47701156E-06 + .44604260E-06 .41142848E-06 .37356115E-06 .33285592E-06 .28974721E-06 + .24468411E-06 .19812594E-06 .15053779E-06 .10238605E-06 .54134036E-07 + .62377485E-08 -.40858297E-07 -.86724999E-07 -.13095241E-06 -.17315324E-06 + -.21296604E-06 -.25005819E-06 -.28412845E-06 -.31490922E-06 -.34216852E-06 + -.36571146E-06 -.38538147E-06 -.40106106E-06 -.41267227E-06 -.42017671E-06 + -.42357521E-06 -.42290716E-06 -.41824948E-06 -.40971522E-06 -.39745192E-06 + -.38163962E-06 -.36248861E-06 -.34023695E-06 -.31514777E-06 -.28750638E-06 + -.25761720E-06 -.22580063E-06 -.19238970E-06 -.15772682E-06 -.12216035E-06 + -.86041260E-07 -.49719795E-07 -.13542196E-07 .22152473E-07 .57035389E-07 + .90790880E-07 .12311917E-06 .15373892E-06 .18238958E-06 .20883345E-06 + .23285758E-06 .25427531E-06 .27292764E-06 .28868422E-06 .30144412E-06 + .31113631E-06 .31771980E-06 .32118358E-06 .32154617E-06 .31885504E-06 + .31318563E-06 .30464021E-06 .29334649E-06 .27945601E-06 .26314228E-06 + .24459889E-06 .22403726E-06 .20168446E-06 .17778076E-06 .15257718E-06 + .12633296E-06 .99313001E-07 .71785264E-07 .44018215E-07 .16278288E-07 + -.11172588E-07 -.38079379E-07 -.64196236E-07 -.89288663E-07 -.11313554E-06 + -.13553101E-06 -.15628613E-06 -.17523044E-06 -.19221325E-06 -.20710472E-06 + -.21979681E-06 -.23020392E-06 -.23826335E-06 -.24393555E-06 -.24720411E-06 + -.24807556E-06 -.24657898E-06 -.24276534E-06 -.23670668E-06 -.22849515E-06 + -.21824179E-06 -.20607522E-06 -.19214012E-06 -.17659568E-06 -.15961382E-06 + -.14137741E-06 -.12207837E-06 -.10191572E-06 -.81093609E-07 -.59819294E-07 + -.38301156E-07 -.16746712E-07 .46393247E-08 .25656936E-07 .46112607E-07 + .65821059E-07 .84606867E-07 .10230597E-06 .11876703E-06 .13385271E-06 + .14744070E-06 .15942470E-06 .16971515E-06 .17823984E-06 .18494433E-06 + .18979218E-06 .19276508E-06 .19386268E-06 .19310238E-06 .19051891E-06 + .18616370E-06 .18010418E-06 .17242290E-06 .16321656E-06 .15259483E-06 + .14067917E-06 .12760150E-06 .11350279E-06 .98531640E-07 .82842700E-07 + .66595175E-07 .49951237E-07 .33074453E-07 .16128219E-07 -.72577625E-09 + -.17329056E-07 -.33527803E-07 -.49174248E-07 -.64127974E-07 -.78257139E-07 + -.91439597E-07 -.10356391E-06 -.11453026E-06 -.12425121E-06 -.13265235E-06 + -.13967283E-06 -.14526574E-06 -.14939835E-06 -.15205219E-06 -.15322310E-06 + -.15292097E-06 -.15116952E-06 -.14800585E-06 -.14347989E-06 -.13765379E-06 + -.13060111E-06 -.12240601E-06 -.11316226E-06 -.10297228E-06 -.91945972E-07 + -.80199652E-07 -.67854818E-07 -.55036943E-07 -.41874230E-07 -.28496367E-07 + -.15033277E-07 -.16138861E-08 .11635077E-07 .24590251E-07 .37132763E-07 + .49149288E-07 .60533043E-07 .71184711E-07 .81013270E-07 .89936746E-07 + .97882862E-07 .10478959E-06 .11060558E-06 .11529055E-06 .11881544E-06 + .12116261E-06 .12232579E-06 .12231003E-06 .12113146E-06 .11881704E-06 + .11540410E-06 .11093987E-06 .10548093E-06 .99092491E-07 .91847710E-07 + .83826869E-07 .75116526E-07 .65808610E-07 .55999479E-07 .45788955E-07 + .35279324E-07 .24574344E-07 .13778238E-07 .29947066E-08 -.76740497E-08 + -.18128276E-07 -.28271574E-07 -.38011770E-07 -.47261731E-07 -.55940124E-07 + -.63972103E-07 -.71289941E-07 -.77833567E-07 -.83551041E-07 -.88398935E-07 + -.92342635E-07 -.95356547E-07 -.97424227E-07 -.98538416E-07 -.98700985E-07 + -.97922800E-07 -.96223506E-07 -.93631217E-07 -.90182152E-07 -.85920176E-07 + -.80896292E-07 -.75168063E-07 -.68798986E-07 -.61857809E-07 -.54417817E-07 + -.46556076E-07 -.38352659E-07 -.29889847E-07 -.21251322E-07 -.12521359E-07 + -.37840174E-08 .48776497E-08 .13382368E-07 .21651391E-07 .29609210E-07 + .37184230E-07 .44309397E-07 .50922773E-07 .56968061E-07 .62395062E-07 + .67160077E-07 .71226235E-07 .74563758E-07 .77150151E-07 .78970324E-07 + .80016644E-07 .80288910E-07 .79794261E-07 .78547019E-07 .76568461E-07 + .73886532E-07 .70535495E-07 .66555530E-07 .61992277E-07 .56896336E-07 + .51322727E-07 .45330316E-07 .38981204E-07 .32340106E-07 .25473698E-07 + .18449969E-07 .11337555E-07 .42050839E-08 -.28794736E-08 -.98494415E-08 + -.16640052E-07 -.23189038E-07 -.29437186E-07 -.35328866E-07 -.40812512E-07 + -.45841055E-07 -.50372323E-07 -.54369371E-07 -.57800775E-07 -.60640853E-07 + -.62869847E-07 -.64474033E-07 -.65445776E-07 -.65783533E-07 -.65491787E-07 + -.64580939E-07 -.63067132E-07 -.60972029E-07 -.58322543E-07 -.55150519E-07 + -.51492371E-07 -.47388682E-07 -.42883771E-07 -.38025227E-07 -.32863421E-07 + -.27450993E-07 -.21842328E-07 -.16093019E-07 -.10259328E-07 -.43976434E-08 + .14360549E-08 .71867203E-08 .12800750E-07 .18226475E-07 .23414627E-07 + .28318775E-07 .32895734E-07 .37105930E-07 .40913739E-07 .44287771E-07 + .47201122E-07 .49631572E-07 .51561743E-07 .52979202E-07 .53876527E-07 + .54251311E-07 .54106131E-07 .53448462E-07 .52290552E-07 .50649243E-07 + .48545767E-07 .46005485E-07 .43057604E-07 .39734853E-07 .36073132E-07 + .32111137E-07 .27889957E-07 .23452663E-07 .18843870E-07 .14109304E-07 + .92953505E-08 .44486096E-08 -.38454644E-09 -.51584109E-08 -.98283672E-08 + -.14351299E-07 -.18685979E-07 -.22793441E-07 -.26637321E-07 -.30184169E-07 + -.33403735E-07 -.36269219E-07 -.38757483E-07 -.40849228E-07 -.42529135E-07 + -.43785962E-07 -.44612604E-07 -.45006116E-07 -.44967688E-07 -.44502592E-07 + -.43620082E-07 -.42333262E-07 -.40658921E-07 -.38617326E-07 -.36231996E-07 + -.33529441E-07 -.30538878E-07 -.27291922E-07 -.23822258E-07 -.20165306E-07 + -.16357859E-07 -.12437720E-07 -.84433384E-08 -.44134316E-08 -.38662064E-09 + .35989364E-08 .75059000E-08 .11298093E-07 .14940832E-07 .18401234E-07 + .21648514E-07 .24654246E-07 .27392612E-07 .29840613E-07 .31978257E-07 + .33788713E-07 .35258437E-07 .36377263E-07 .37138462E-07 .37538764E-07 + .37578356E-07 .37260840E-07 .36593157E-07 .35585490E-07 .34251130E-07 + .32606315E-07 .30670044E-07 .28463867E-07 .26011653E-07 .23339341E-07 + .20474668E-07 .17446888E-07 .14286482E-07 .11024851E-07 .76940136E-08 + .43262926E-08 .95400876E-09 -.23908262E-08 -.56768089E-08 -.88734341E-08 + -.11951374E-07 -.14882742E-07 -.17641344E-07 -.20202900E-07 -.22545264E-07 + -.24648601E-07 -.26495553E-07 -.28071378E-07 -.29364057E-07 -.30364384E-07 + -.31066017E-07 -.31465510E-07 -.31562315E-07 -.31358754E-07 -.30859967E-07 + -.30073833E-07 -.29010868E-07 -.27684093E-07 -.26108889E-07 -.24302823E-07 + -.22285459E-07 -.20078151E-07 -.17703825E-07 -.15186743E-07 -.12552259E-07 + -.98265679E-08 -.70364516E-08 -.42090155E-08 -.13714314E-08 .14493211E-08 + .42267068E-08 .69348812E-08 .95489280E-08 .12045084E-07 .14400953E-07 + .16595700E-07 .18610236E-07 .20427375E-07 .22031979E-07 .23411080E-07 + .24553978E-07 .25452321E-07 .26100155E-07 .26493958E-07 .26632648E-07 + .26517566E-07 .26152438E-07 .25543316E-07 .24698497E-07 .23628420E-07 + .22345546E-07 .20864215E-07 .19200499E-07 .17372025E-07 .15397796E-07 + .13297997E-07 .11093789E-07 .88071036E-08 .64604261E-08 .40765756E-08 + .16784879E-08 -.71100283E-09 -.30693782E-08 -.53746454E-08 -.76055391E-08 + -.97417153E-08 -.11763934E-07 -.13654229E-07 -.15396065E-07 -.16974480E-07 + -.18376205E-07 -.19589781E-07 -.20605640E-07 -.21416183E-07 -.22015826E-07 + -.22401035E-07 -.22570340E-07 -.22524323E-07 -.22265595E-07 -.21798749E-07 + -.21130301E-07 -.20268601E-07 -.19223743E-07 -.18007448E-07 -.16632937E-07 + -.15114794E-07 -.13468809E-07 -.11711822E-07 -.98615529E-08 -.79364227E-08 + -.59553751E-08 -.39376911E-08 -.19028042E-08 .12988462E-09 .21411892E-08 + .41123172E-08 .60250428E-08 .78618736E-08 .96062079E-08 .11242483E-07 + .12756310E-07 .14134601E-07 .15365675E-07 .16439358E-07 .17347061E-07 + .18081847E-07 .18638478E-07 .19013451E-07 .19205011E-07 .19213151E-07 + .19039596E-07 .18687766E-07 .18162730E-07 .17471142E-07 .16621162E-07 + .15622363E-07 .14485631E-07 .13223043E-07 .11847748E-07 .10373827E-07 + .88161544E-08 .71902497E-08 .55121243E-08 .37981263E-08 .20647829E-08 + .32864295E-09 -.13938797E-08 -.30866595E-08 -.47340081E-08 -.63208176E-08 + -.78326971E-08 -.92561016E-08 -.10578451E-07 -.11788240E-07 -.12875136E-07 + -.13830065E-07 -.14645284E-07 -.15314441E-07 -.15832624E-07 -.16196389E-07 + -.16403779E-07 -.16454334E-07 -.16349071E-07 -.16090471E-07 -.15682433E-07 + -.15130227E-07 -.14440433E-07 -.13620859E-07 -.12680467E-07 -.11629267E-07 + 19.8421228800786942 T + Non local Part + 0 2 1.55770284366884382 + 8.48191151414740752 -0.636078516188222226E-01 -0.636078516188222226E-01 0.376965742998787998E-02 + Reciprocal Space Part + .87079657E+01 .86905268E+01 .86383852E+01 .85520639E+01 .84324261E+01 + .82806628E+01 .80982759E+01 .78870568E+01 .76490608E+01 .73865785E+01 + .71021037E+01 .67982989E+01 .64779593E+01 .61439752E+01 .57992933E+01 + .54468791E+01 .50896789E+01 .47305835E+01 .43723936E+01 .40177873E+01 + .36692907E+01 .33292513E+01 .29998152E+01 .26829081E+01 .23802200E+01 + .20931942E+01 .18230205E+01 .15706325E+01 .13367087E+01 .11216776E+01 + .92572621E+00 .74881221E+00 .59067848E+00 .45087066E+00 .32875652E+00 + .22354716E+00 .13431939E+00 .60038835E-01 -.41655140E-03 -.48233192E-01 + -.84639053E-01 -.11088174E+00 -.12820783E+00 -.13784377E+00 -.14097860E+00 + -.13874855E+00 -.13222400E+00 -.12239850E+00 -.11018019E+00 -.96385516E-01 + -.81735140E-01 -.66852083E-01 -.52261834E-01 -.38394355E-01 -.25587745E-01 + -.14093369E-01 -.40822094E-02 .43477954E-02 .11163663E-01 .16388781E-01 + .20094049E-01 .22388976E-01 .23412932E-01 .23326746E-01 .22304805E-01 + .20527794E-01 .18176188E-01 .15424571E-01 .12436845E-01 .93623490E-02 + .63329000E-02 .34607215E-02 .83723118E-03 -.14673812E-02 -.34038583E-02 + -.49429505E-02 -.60739569E-02 -.68028370E-02 -.71499932E-02 -.71478312E-02 + -.68381952E-02 -.62697733E-02 -.54955578E-02 -.45704368E-02 -.35489799E-02 + -.24834728E-02 -.14222372E-02 -.40826592E-03 .52181480E-03 .13384515E-02 + .20195476E-02 .25505425E-02 .29242131E-02 .31402290E-02 .32045017E-02 + .31283679E-02 .29276511E-02 .26216452E-02 .22320639E-02 .17819939E-02 + Real Space Part + .10679849E+02 .10674516E+02 .10658521E+02 .10631882E+02 .10594629E+02 + .10546798E+02 .10488435E+02 .10419590E+02 .10340316E+02 .10250666E+02 + .10150691E+02 .10040442E+02 .99199643E+01 .97892993E+01 .96484877E+01 + .94975699E+01 .93365905E+01 .91656025E+01 .89846735E+01 .87938923E+01 + .85933769E+01 .83832826E+01 .81638104E+01 .79352160E+01 .76978177E+01 + .74520045E+01 .71982421E+01 .69370789E+01 .66691491E+01 .63951751E+01 + .61159665E+01 .58324186E+01 .55455066E+01 .52562794E+01 .49658496E+01 + .46753825E+01 .43860825E+01 .40991787E+01 .38159080E+01 .35374987E+01 + .32651527E+01 .30000279E+01 .27432213E+01 .24957525E+01 .22585487E+01 + .20324314E+01 .18181051E+01 .16161478E+01 .14270049E+01 .12509847E+01 + .10882570E+01 .93885502E+00 .80267855E+00 .67950082E+00 .56897697E+00 + .47065459E+00 .38398603E+00 .30834185E+00 .24302540E+00 .18728774E+00 + .14034296E+00 .10138309E+00 .69592617E-01 .44162070E-01 .24300516E-01 + .92466753E-02 -.17214853E-02 -.92788061E-02 -.14046714E-01 -.16588732E-01 + -.17407693E-01 -.16944568E-01 -.15578795E-01 -.13629958E-01 -.11360623E-01 + -.89801560E-02 -.66492956E-02 -.44852808E-02 -.25673264E-02 -.94224811E-03 + .36993817E-03 .13706046E-02 .20774200E-02 .25196886E-02 .27342003E-02 + .27616467E-02 .26436316E-02 .24202815E-02 .21284366E-02 .18003892E-02 + .14631174E-02 .11379537E-02 .84061912E-03 .58155029E-03 .36644718E-03 + .19697068E-03 .71525435E-04 -.13929925E-04 -.65094077E-04 -.88595362E-04 + Reciprocal Space Part + -.33459269E+02 -.32885812E+02 -.31175324E+02 -.28357261E+02 -.24480084E+02 + -.19610327E+02 -.13831310E+02 -.72415472E+01 .47142272E-01 .79117577E+01 + .16220445E+02 .24834975E+02 .33613317E+02 .42412261E+02 .51090027E+02 + .59508819E+02 .67537255E+02 .75052646E+02 .81943063E+02 .88109160E+02 + .93465720E+02 .97942900E+02 .10148714E+03 .10406175E+03 .10564715E+03 + .10624077E+03 .10585660E+03 .10452449E+03 .10228909E+03 .99208571E+02 + .95353099E+02 .90803154E+02 .85647663E+02 .79982052E+02 .73906232E+02 + .67522572E+02 .60933898E+02 .54241560E+02 .47543611E+02 .40933123E+02 + .34496680E+02 .28313063E+02 .22452162E+02 .16974111E+02 .11928669E+02 + .73548473E+01 .32807727E+01 -.27621319E+00 -.33092347E+01 -.58213610E+01 + -.78249039E+01 -.93405595E+01 -.10396421E+02 -.11026891E+02 -.11271526E+02 + -.11173833E+02 -.10780072E+02 -.10138054E+02 -.92960043E+01 -.83014828E+01 + -.72003946E+01 -.60361114E+01 -.48487123E+01 -.36743572E+01 -.25447982E+01 + -.14870336E+01 -.52310141E+00 .32999049E+00 .10602053E+01 .16603003E+01 + .21275436E+01 .24633402E+01 .26727834E+01 .27641476E+01 .27483410E+01 + .26383351E+01 .24485880E+01 .21944773E+01 .18917574E+01 .15560536E+01 + .12024051E+01 .84486462E+00 .49616263E+00 .16743966E+00 -.13195032E+00 + -.39456569E+00 -.61493394E+00 -.78954326E+00 -.91677435E+00 -.99677914E+00 + -.10313144E+01 -.10235387E+01 -.97778206E+00 -.89929746E+00 -.79400304E+00 + -.66822444E+00 -.52844495E+00 -.38107084E+00 -.23221848E+00 -.87528095E-01 + Real Space Part + .47043595E+03 .47061811E+03 .47114518E+03 .47195957E+03 .47296738E+03 + .47404142E+03 .47502541E+03 .47573899E+03 .47598368E+03 .47554935E+03 + .47422109E+03 .47178640E+03 .46804221E+03 .46280172E+03 .45590085E+03 + .44720395E+03 .43660875E+03 .42405037E+03 .40950423E+03 .39298784E+03 + .37456135E+03 .35432699E+03 .33242725E+03 .30904200E+03 .28438464E+03 + .25869730E+03 .23224536E+03 .20531141E+03 .17818879E+03 .15117498E+03 + .12456500E+03 .98644898E+02 .73685748E+02 .49938027E+02 .27626718E+02 + .69471588E+01 -.11938243E+02 -.28902388E+02 -.43854906E+02 -.56742633E+02 + -.67549163E+02 -.76293525E+02 -.83028062E+02 -.87835614E+02 -.90826098E+02 + -.92132623E+02 -.91907271E+02 -.90316654E+02 -.87537414E+02 -.83751758E+02 + -.79143172E+02 -.73892400E+02 -.68173791E+02 -.62152082E+02 -.55979677E+02 + -.49794451E+02 -.43718116E+02 -.37855127E+02 -.32292132E+02 -.27097928E+02 + -.22323878E+02 -.18004740E+02 -.14159842E+02 -.10794541E+02 -.79018948E+01 + -.54644709E+01 -.34562340E+01 -.18444414E+01 -.59149265E+00 .34331959E+00 + .10021984E+01 .14274044E+01 .16600147E+01 .17388937E+01 .16998820E+01 + .15752010E+01 .13930648E+01 .11774834E+01 .94823819E+00 .72100557E+00 + .50760296E+00 .31633056E+00 .15238184E+00 .18296902E-01 -.85564833E-01 + -.16055420E+00 -.20928196E+00 -.23520343E+00 -.24224903E+00 -.23450846E+00 + -.21597247E+00 -.19033347E+00 -.16084311E+00 -.13022316E+00 -.10062372E+00 + -.73622006E-01 -.50254001E-01 -.31070866E-01 -.16212387E-01 -.54900275E-02 + Non local Part + 1 2 1.55770284366884382 + 2.65859659160385764 -0.504801881867953453E-01 -0.504801881867953453E-01 0.892956271679604986E-02 + Reciprocal Space Part + .00000000E+00 .55360975E+00 .11020032E+01 .16400357E+01 .21627048E+01 + .26652186E+01 .31430596E+01 .35920450E+01 .40083810E+01 .43887098E+01 + .47301505E+01 .50303314E+01 .52874138E+01 .55001078E+01 .56676786E+01 + .57899444E+01 .58672657E+01 .59005262E+01 .58911063E+01 .58408488E+01 + .57520191E+01 .56272596E+01 .54695387E+01 .52820975E+01 .50683934E+01 + .48320418E+01 .45767578E+01 .43062991E+01 .40244089E+01 .37347632E+01 + .34409202E+01 .31462743E+01 .28540152E+01 .25670915E+01 .22881811E+01 + .20196669E+01 .17636193E+01 .15217840E+01 .12955770E+01 .10860853E+01 + .89407229E+00 .71998985E+00 .56399389E+00 .42596477E+00 .30553088E+00 + .20209532E+00 .11486458E+00 .42878783E-01 -.14957234E-01 -.59842780E-01 + -.93050595E-01 -.11589722E+00 -.12971495E+00 -.13582584E+00 -.13551809E+00 + -.13002523E+00 -.12050824E+00 -.10804072E+00 -.93597327E-01 -.78045331E-01 + -.62139262E-01 -.46518532E-01 -.31707803E-01 -.18119864E-01 -.60607310E-02 + .42633380E-02 .12737265E-01 .19327344E-01 .24070560E-01 .27063374E-01 + .28450306E-01 .28412605E-01 .27157313E-01 .24906934E-01 .21889935E-01 + .18332245E-01 .14449871E-01 .10442718E-01 .64896733E-02 .27449375E-02 + -.66440255E-03 -.36396321E-02 -.61105795E-02 -.80348118E-02 -.93959825E-02 + -.10201473E-01 -.10479476E-01 -.10275671E-01 -.96496464E-02 -.86712031E-02 + -.74166865E-02 -.59654538E-02 -.43965915E-02 -.27859668E-02 -.12036827E-02 + .28801366E-03 .16363396E-02 .27990903E-02 .37452630E-02 .44552150E-02 + Real Space Part + .00000000E+00 .64359942E+00 .12860893E+01 .19263130E+01 .25630221E+01 + .31948350E+01 .38202017E+01 .44373750E+01 .50443910E+01 .56390587E+01 + .62189597E+01 .67814592E+01 .73237268E+01 .78427678E+01 .83354645E+01 + .87986250E+01 .92290406E+01 .96235469E+01 .99790905E+01 .10292796E+02 + .10562036E+02 .10784491E+02 .10958218E+02 .11081699E+02 .11153897E+02 + .11174283E+02 .11142876E+02 .11060254E+02 .10927558E+02 .10746490E+02 + .10519290E+02 .10248709E+02 .99379673E+01 .95907014E+01 .92109083E+01 + .88028781E+01 .83711229E+01 .79203026E+01 .74551481E+01 .69803858E+01 + .65006629E+01 .60204776E+01 .55441132E+01 .50755794E+01 .46185613E+01 + .41763765E+01 .37519415E+01 .33477477E+01 .29658468E+01 .26078460E+01 + .22749116E+01 .19677819E+01 .16867871E+01 .14318761E+01 .12026495E+01 + .99839626E+00 .81813432E+00 .66065330E+00 .52455802E+00 .40831211E+00 + .31028032E+00 .22876897E+00 .16206345E+00 .10846228E+00 .66307278E-01 + .34009364E-01 .10069850E-01 -.69027801E-02 -.18180606E-01 -.24908286E-01 + -.28099078E-01 -.28634490E-01 -.27267117E-01 -.24626205E-01 -.21225416E-01 + -.17472311E-01 -.13679034E-01 -.10073742E-01 -.68123372E-02 -.39901212E-02 + -.16530358E-02 .19178102E-03 .15663369E-02 .25131785E-02 .30879320E-02 + .33530317E-02 .33726336E-02 .32086679E-02 .29179506E-02 .25502513E-02 + .21471944E-02 .17418610E-02 .13589554E-02 .10154019E-02 .72124547E-03 + .48074009E-03 .29352474E-03 .15580136E-03 .61447592E-04 .30138377E-05 + Reciprocal Space Part + .00000000E+00 -.26932227E+01 -.52971472E+01 -.77244363E+01 -.98916316E+01 + -.11720983E+02 -.13142152E+02 -.14093748E+02 -.14524661E+02 -.14395175E+02 + -.13677819E+02 -.12357950E+02 -.10434056E+02 -.79177661E+01 -.48335806E+01 + -.12183197E+01 .28796906E+01 .74016747E+01 .12279682E+02 .17438045E+02 + .22794994E+02 .28264383E+02 .33757491E+02 .39184855E+02 .44458102E+02 + .49491724E+02 .54204777E+02 .58522445E+02 .62377462E+02 .65711339E+02 + .68475389E+02 .70631527E+02 .72152827E+02 .73023834E+02 .73240630E+02 + .72810652E+02 .71752282E+02 .70094218E+02 .67874635E+02 .65140188E+02 + .61944855E+02 .58348663E+02 .54416332E+02 .50215862E+02 .45817101E+02 + .41290320E+02 .36704841E+02 .32127729E+02 .27622587E+02 .23248472E+02 + .19058953E+02 .15101330E+02 .11416015E+02 .80360965E+01 .49870782E+01 + .22867940E+01 -.54504994E-01 -.20339040E+01 -.36554301E+01 -.49295269E+01 + -.58724172E+01 -.65053728E+01 -.68539157E+01 -.69469702E+01 -.68159914E+01 + -.64940905E+01 -.60151778E+01 -.54131449E+01 -.47211011E+01 -.39706812E+01 + -.31914370E+01 -.24103219E+01 -.16512754E+01 -.93491359E+00 -.27832313E+00 + .30503924E+00 .80534852E+00 .12163201E+01 .15350341E+01 .17616860E+01 + .18992752E+01 .19532440E+01 .19310803E+01 .18418981E+01 .16960073E+01 + .15044873E+01 .12787746E+01 .10302757E+01 .77001425E+00 .50831954E+00 + .25456290E+00 .16945576E-01 -.19765940E+00 -.38381089E+00 -.53754978E+00 + -.65639825E+00 -.73931205E+00 -.78659086E+00 -.79975259E+00 -.78137851E+00 + Real Space Part + .00000000E+00 .32174412E+02 .64081200E+02 .95454901E+02 .12603438E+03 + .15556504E+03 .18380101E+03 .21050740E+03 .23546257E+03 .25846040E+03 + .27931254E+03 .29785062E+03 .31392841E+03 .32742382E+03 .33824076E+03 + .34631080E+03 .35159451E+03 .35408254E+03 .35379625E+03 .35078802E+03 + .34514103E+03 .33696853E+03 .32641275E+03 .31364309E+03 .29885400E+03 + .28226227E+03 .26410388E+03 .24463049E+03 .22410561E+03 .20280043E+03 + .18098955E+03 .15894661E+03 .13693992E+03 .11522816E+03 .94056367E+02 + .73652166E+02 .54222369E+02 .35950069E+02 .18992243E+02 .34779240E+01 + -.10493014E+02 -.22850445E+02 -.33553946E+02 -.42592145E+02 -.49981475E+02 + -.55764394E+02 -.60007127E+02 -.62796996E+02 -.64239417E+02 -.64454665E+02 + -.63574472E+02 -.61738574E+02 -.59091275E+02 -.55778129E+02 -.51942809E+02 + -.47724232E+02 -.43254004E+02 -.38654223E+02 -.34035686E+02 -.29496509E+02 + -.25121167E+02 -.20979967E+02 -.17128906E+02 -.13609921E+02 -.10451462E+02 + -.76693710E+01 -.52679941E+01 -.32414933E+01 -.15752887E+01 -.24758462E+00 + .76907715E+00 .15062828E+01 .19982770E+01 .22805946E+01 .23888267E+01 + .23575419E+01 .22193827E+01 .20043426E+01 .17392288E+01 .14473034E+01 + .11480951E+01 .85736431E+00 .58720519E+00 .34626103E+00 .14003133E+00 + -.28753785E-01 -.15971487E+00 -.25438251E+00 -.31575466E+00 -.34786993E+00 + -.35541133E+00 -.34335220E+00 -.31665261E+00 -.28001124E+00 -.23767485E+00 + -.19330460E+00 -.14989599E+00 -.10974754E+00 -.74471444E-01 -.45038872E-01 + PAW radial sets + 323 0.989218471734281124 +(5E20.12) + augmentation charges (non sperical) + -.118612867153E+00 -.756362247412E-03 -.532145531503E-01 -.130926919871E-02 -.756362247412E-03 + -.210856503823E-04 -.122603249007E-03 .363423839020E-05 -.532145531503E-01 -.122603249007E-03 + -.179689875812E-01 -.555432069872E-03 -.130926919871E-02 .363423839020E-05 -.555432069872E-03 + .498671741032E-04 + uccopancies in atom + .200000000162E+01 .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 + .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 + .666666667141E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 .000000000000E+00 + .000000000000E+00 + grid + .353278105438E-04 .364765828105E-04 .376627102856E-04 .388874076671E-04 .401519291522E-04 + .414575697215E-04 .428056664648E-04 .441975999512E-04 .456347956421E-04 .471187253514E-04 + .486509087530E-04 .502329149365E-04 .518663640144E-04 .535529287814E-04 .552943364272E-04 + .570923703053E-04 .589488717596E-04 .608657420098E-04 .628449440985E-04 .648885049016E-04 + .669985172040E-04 .691771418426E-04 .714266099194E-04 .737492250864E-04 .761473659044E-04 + .786234882792E-04 .811801279764E-04 .838199032186E-04 .865455173661E-04 .893597616862E-04 + .922655182109E-04 .952657626888E-04 .983635676325E-04 .101562105465E-03 .104864651768E-03 + .108274588638E-03 .111795408149E-03 .115430715926E-03 .119184234844E-03 .123059808833E-03 + .127061406819E-03 .131193126789E-03 .135459199986E-03 .139863995240E-03 .144412023447E-03 + .149107942186E-03 .153956560487E-03 .158962843759E-03 .164131918874E-03 .169469079417E-03 + .174979791106E-03 .180669697392E-03 .186544625235E-03 .192610591076E-03 .198873806993E-03 + .205340687067E-03 .212017853948E-03 .218912145639E-03 .226030622496E-03 .233380574462E-03 + .240969528530E-03 .248805256452E-03 .256895782699E-03 .265249392676E-03 .273874641209E-03 + .282780361308E-03 .291975673207E-03 .301469993709E-03 .311273045829E-03 .321394868748E-03 + .331845828098E-03 .342636626573E-03 .353778314896E-03 .365282303127E-03 .377160372357E-03 + .389424686766E-03 .402087806084E-03 .415162698451E-03 .428662753701E-03 .442601797068E-03 + .456994103352E-03 .471854411533E-03 .487197939863E-03 .503040401457E-03 .519398020380E-03 + .536287548263E-03 .553726281459E-03 .571732078754E-03 .590323379658E-03 .609519223288E-03 + .629339267864E-03 .649803810846E-03 .670933809712E-03 .692750903429E-03 .715277434606E-03 + .738536472381E-03 .762551836040E-03 .787348119413E-03 .812950716063E-03 .839385845286E-03 + .866680578963E-03 .894862869287E-03 .923961577387E-03 .954006502881E-03 .985028414399E-03 + .101705908109E-02 .105013130516E-02 .108427895544E-02 .111953700213E-02 .115594155253E-02 + .119352988810E-02 .123234050257E-02 .127241314140E-02 .131378884247E-02 .135650997813E-02 + .140062029854E-02 .144616497653E-02 .149319065382E-02 .154174548883E-02 .159187920594E-02 + .164364314647E-02 .169709032120E-02 .175227546473E-02 .180925509145E-02 .186808755348E-02 + .192883310041E-02 .199155394099E-02 .205631430683E-02 .212318051821E-02 .219222105197E-02 + .226350661166E-02 .233711019991E-02 .241310719324E-02 .249157541920E-02 .257259523611E-02 + .265624961535E-02 .274262422631E-02 .283180752413E-02 .292389084032E-02 .301896847624E-02 + .311713779968E-02 .321849934462E-02 .332315691413E-02 .343121768671E-02 .354279232604E-02 + .365799509430E-02 .377694396919E-02 .389976076474E-02 .402657125610E-02 .415750530828E-02 + .429269700920E-02 .443228480697E-02 .457641165169E-02 .472522514185E-02 .487887767547E-02 + .503752660617E-02 .520133440431E-02 .537046882339E-02 .554510307185E-02 .572541599040E-02 + .591159223525E-02 .610382246712E-02 .630230354657E-02 .650723873558E-02 .671883790569E-02 + .693731775293E-02 .716290201977E-02 .739582172419E-02 .763631539635E-02 .788462932276E-02 + .814101779859E-02 .840574338805E-02 .867907719326E-02 .896129913194E-02 .925269822400E-02 + .955357288758E-02 .986423124464E-02 .101849914365E-01 .105161819495E-01 .108581419519E-01 + .112112216404E-01 .115757825996E-01 .119521981717E-01 .123408538391E-01 .127421476193E-01 + .131564904721E-01 .135843067208E-01 .140260344867E-01 .144821261375E-01 .149530487510E-01 + .154392845931E-01 .159413316118E-01 .164597039470E-01 .169949324574E-01 .175475652638E-01 + .181181683104E-01 .187073259445E-01 .193156415151E-01 .199437379906E-01 .205922585965E-01 + .212618674747E-01 .219532503631E-01 .226671152982E-01 .234041933402E-01 .241652393213E-01 + .249510326191E-01 .257623779547E-01 .266001062165E-01 .274650753115E-01 .283581710436E-01 + .292803080210E-01 .302324305924E-01 .312155138146E-01 .322305644506E-01 .332786220011E-01 + .343607597686E-01 .354780859567E-01 .366317448050E-01 .378229177610E-01 .390528246900E-01 + .403227251240E-01 .416339195521E-01 .429877507520E-01 .443856051652E-01 .458289143166E-01 + .473191562810E-01 .488578571964E-01 .504465928270E-01 .520869901769E-01 .537807291563E-01 + .555295443019E-01 .573352265534E-01 .591996250870E-01 .611246492098E-01 .631122703148E-01 + .651645238996E-01 .672835116512E-01 .694714035982E-01 .717304403333E-01 .740629353074E-01 + .764712771991E-01 .789579323611E-01 .815254473456E-01 .841764515121E-01 .869136597208E-01 + .897398751118E-01 .926579919768E-01 .956709987225E-01 .987819809310E-01 .101994124520E+00 + .105310719005E+00 .108735160869E+00 .112270957040E+00 .115921728481E+00 .119691213902E+00 + .123583273585E+00 .127601893339E+00 .131751188583E+00 .136035408556E+00 .140458940676E+00 + .145026315024E+00 .149742208992E+00 .154611452068E+00 .159639030781E+00 .164830093811E+00 + .170189957261E+00 .175724110099E+00 .181438219781E+00 .187338138056E+00 .193429906954E+00 + .199719764979E+00 .206214153496E+00 .212919723327E+00 .219843341560E+00 .226992098585E+00 + .234373315355E+00 .241994550880E+00 .249863609972E+00 .257988551235E+00 .266377695319E+00 + .275039633439E+00 .283983236179E+00 .293217662568E+00 .302752369466E+00 .312597121246E+00 + .322761999795E+00 .333257414835E+00 .344094114590E+00 .355283196787E+00 .366836120023E+00 + .378764715502E+00 .391081199148E+00 .403798184116E+00 .416928693710E+00 .430486174720E+00 + .444484511190E+00 .458938038641E+00 .473861558747E+00 .489270354497E+00 .505180205845E+00 + .521607405869E+00 .538568777456E+00 .556081690535E+00 .574164079857E+00 .592834463369E+00 + .612111961177E+00 .632016315122E+00 .652567909002E+00 .673787789445E+00 .695697687463E+00 + .718320040705E+00 .741678016440E+00 .765795535274E+00 .790697295655E+00 .816408799161E+00 + .842956376619E+00 .870367215068E+00 .898669385601E+00 .927891872115E+00 .958064600989E+00 + .989218471734E+00 .102138538864E+01 .105459829343E+01 + aepotential + .249296618412E+05 .247076583257E+05 .244443255599E+05 .241414371172E+05 .238011681064E+05 + .234259054160E+05 .230182276498E+05 .225808680933E+05 .221166790321E+05 .216285959644E+05 + .211196020425E+05 .205926935296E+05 .200508469868E+05 .194969885786E+05 .189339660140E+05 + .183645234482E+05 .177912796436E+05 .172167095020E+05 .166431291099E+05 .160726841798E+05 + .155073419145E+05 .149488860093E+05 .143989147023E+05 .138588415092E+05 .133298984061E+05 + .128131411287E+05 .123094562646E+05 .118195698156E+05 .113440569063E+05 .108833523432E+05 + .104377617399E+05 .100074729506E+05 .959256758265E+04 .919303239296E+04 .880877039590E+04 + .843961154725E+04 .808532289425E+04 .774561810756E+04 .742016634235E+04 .710860038888E+04 + .681052409519E+04 .652551907131E+04 .625315067621E+04 .599297332353E+04 .574453513086E+04 + .550738195528E+04 .528106086162E+04 .506512306412E+04 .485912638819E+04 .466263730249E+04 + .447523256840E+04 .429650053920E+04 .412604216570E+04 .396347173509E+04 .380841738005E+04 + .366052140119E+04 .351944041296E+04 .338484535875E+04 .325642140535E+04 .313386774487E+04 + .301689731751E+04 .290523647712E+04 .279862460324E+04 .269681368551E+04 .259956787532E+04 + .250666302499E+04 .241788621528E+04 .233303528113E+04 .225191833487E+04 .217435329790E+04 + .210016743837E+04 .202919692087E+04 .196128636819E+04 .189628843674E+04 .183406340726E+04 + .177447879164E+04 .171740895648E+04 .166273476188E+04 .161034321676E+04 .156012715054E+04 + .151198490272E+04 .146582002337E+04 .142154099431E+04 .137906095998E+04 .133829747604E+04 + .129917226882E+04 .126161100972E+04 .122554310047E+04 .119090147066E+04 .115762238690E+04 + .112564527212E+04 .109491253468E+04 .106536940758E+04 .103696379654E+04 .100964613669E+04 + .983369256582E+03 .958088251357E+03 .933760361363E+03 .910344858922E+03 .887802940737E+03 + .866097626532E+03 .845193663442E+03 .825057435693E+03 .805656879371E+03 .786961401872E+03 + .768941805860E+03 .751570217559E+03 .734820018832E+03 .718665782978E+03 .703083214326E+03 + .688049090980E+03 .673541210507E+03 .659538338921E+03 .646020162215E+03 .632967240499E+03 + .620360964749E+03 .608183515718E+03 .596417825223E+03 .585047539244E+03 .574056983177E+03 + .563431128839E+03 .553155563184E+03 .543216458754E+03 .533600545498E+03 .524295084194E+03 + .515287841173E+03 .506567064354E+03 .498121460542E+03 .489940173731E+03 .482012764716E+03 + .474329191586E+03 .466879791201E+03 .459655261667E+03 .452646645612E+03 .445845314309E+03 + .439242952579E+03 .432831544450E+03 .426603359477E+03 .420550939758E+03 .414667087568E+03 + .408944853585E+03 .403377525679E+03 .397958618253E+03 .392681862072E+03 .387541194587E+03 + .382530750726E+03 .377644854114E+03 .372878008707E+03 .368224890830E+03 .363680341587E+03 + .359239359657E+03 .354897094389E+03 .350648839276E+03 .346490025719E+03 .342416217091E+03 + .338423103118E+03 .334506494502E+03 .330662317854E+03 .326886610852E+03 .323175517677E+03 + .319525284662E+03 .315932256206E+03 .312392870893E+03 .308903657842E+03 .305461233272E+03 + .302062297267E+03 .298703630762E+03 .295382092719E+03 .292094617500E+03 .288838212437E+03 + .285609955593E+03 .282406993707E+03 .279226540330E+03 .276065874141E+03 .272922337452E+03 + .269793334886E+03 .266676332242E+03 .263568855544E+03 .260468490264E+03 .257372880728E+03 + .254279729706E+03 .251186798183E+03 .248091905310E+03 .244992928548E+03 .241887803987E+03 + .238774526866E+03 .235651152274E+03 .232515796051E+03 .229366635883E+03 .226201912602E+03 + .223019931688E+03 .219819064985E+03 .216597752635E+03 .213354505238E+03 .210087906247E+03 + .206796614606E+03 .203479367655E+03 .200134984304E+03 .196762368500E+03 .193360513013E+03 + .189928503567E+03 .186465523338E+03 .182970857876E+03 .179443900479E+03 .175884158076E+03 + .172291257693E+03 .168664953559E+03 .165005134953E+03 .161311834879E+03 .157585239680E+03 + .153825699735E+03 .150033741355E+03 .146210080040E+03 .142355635261E+03 .138471546918E+03 + .134559193631E+03 .130620212984E+03 .126656523815E+03 .122670350542E+03 .118664249404E+03 + .114641136335E+03 .110604315898E+03 .106557510391E+03 .102504887754E+03 .984510863142E+02 + .944012336261E+02 .903609557846E+02 .863363724670E+02 .823340718078E+02 .783610579892E+02 + .744246633582E+02 .705324162159E+02 .666918555610E+02 .629102856287E+02 .591944669183E+02 + .555502477826E+02 .519821532120E+02 .484929672536E+02 .450833747318E+02 .417517679306E+02 + .384943726247E+02 .353058986338E+02 .321809414460E+02 .291163276325E+02 .261144334538E+02 + .231871492547E+02 .203596538297E+02 .176726025177E+02 .151810751243E+02 .129490421749E+02 + .110393419236E+02 .950085943829E+01 .835601596774E+01 .759220035195E+01 .716026979128E+01 + .698171586735E+01 .696337537316E+01 .701521042419E+01 .706481632887E+01 .706399956522E+01 + .698712622280E+01 .682461424434E+01 .657568967629E+01 .624298209986E+01 .582958804938E+01 + .533805380599E+01 .477041519949E+01 .412860165824E+01 .341481131402E+01 .263171136544E+01 + .178246368857E+01 .870634878579E+00 -.999438728779E-01 -.112531868169E+01 -.220152969452E+01 + -.332469269108E+01 -.449104609659E+01 -.569696875391E+01 -.693897492955E+01 -.821369210611E+01 + -.951782536530E+01 -.108481102767E+02 -.122012545007E+02 -.135738669876E+02 -.149623728146E+02 + -.163629115444E+02 -.177712178383E+02 -.191824854283E+02 -.205912200739E+02 -.219910944781E+02 + -.233748284178E+02 -.247341312735E+02 -.260597521130E+02 -.273417019240E+02 -.285696929862E+02 + -.297338408481E+02 -.308256300402E+02 -.318391145291E+02 -.327722934381E+02 -.336286096960E+02 + -.344184453032E+02 -.351602594335E+02 -.358801411316E+02 -.366068307978E+02 -.373574862777E+02 + -.381118849160E+02 -.387867273418E+02 -.392441857634E+02 -.393634904186E+02 -.391349287009E+02 + -.386756216504E+02 -.381417407639E+02 -.376357898778E+02 -.371876084285E+02 -.367857308718E+02 + -.364089017521E+02 -.360404072746E+02 -.356705440643E+02 -.352947736909E+02 -.349113812250E+02 + -.345198086599E+02 -.341197549222E+02 -.337108274651E+02 + core charge-density + .566100405752E-04 .603274790726E-04 .642889041986E-04 .685103164325E-04 .730087642691E-04 + .778024127357E-04 .829106163764E-04 .883539969928E-04 .941545264508E-04 .100335614880E-03 + .106922204616E-03 .113940870262E-03 .121419925256E-03 .129389535376E-03 .137881839620E-03 + .146931078955E-03 .156573733420E-03 .166848668143E-03 .177797288839E-03 .189463707397E-03 + .201894918215E-03 .215140985966E-03 .229255245539E-03 .244294514933E-03 .260319321939E-03 + .277394145493E-03 .295587672651E-03 .314973072166E-03 .335628285763E-03 .357636338214E-03 + .381085667437E-03 .406070475885E-03 .432691104597E-03 .461054431344E-03 .491274294413E-03 + .523471943665E-03 .557776520581E-03 .594325569167E-03 .633265579655E-03 .674752567074E-03 + .718952686923E-03 .766042890258E-03 .816211620710E-03 .869659556058E-03 .926600397160E-03 + .987261707239E-03 .105188580466E-02 .112073071253E-02 .119407116880E-02 .127219970037E-02 + .135542776555E-02 .144408696885E-02 .153853035261E-02 .163913377046E-02 .174629734739E-02 + .186044703187E-02 .198203624583E-02 .211154763822E-02 .224949494879E-02 .239642498860E-02 + .255291974450E-02 .271959861504E-02 .289712078585E-02 .308618775280E-02 .328754600198E-02 + .350198985578E-02 .373036449505E-02 .397356916791E-02 .423256059621E-02 .450835659128E-02 + .480203989148E-02 .511476223442E-02 .544774867755E-02 .580230218169E-02 .617980847259E-02 + .658174119662E-02 .700966738736E-02 .746525326090E-02 .795027035842E-02 .846660205552E-02 + .901625045908E-02 .960134371288E-02 .102241437348E-01 .108870544090E-01 .115926302582E-01 + .123435856218E-01 .131428043661E-01 .139933501568E-01 .148984773211E-01 .158616423311E-01 + .168865159410E-01 .179769960102E-01 .191372210475E-01 .203715845116E-01 .216847499059E-01 + .230816667048E-01 .245675871519E-01 .261480839698E-01 .278290690246E-01 .296168129868E-01 + .315179660337E-01 .335395796374E-01 .356891294839E-01 .379745395704E-01 .404042075275E-01 + .429870312127E-01 .457324366235E-01 .486504071769E-01 .517515144015E-01 .550469500898E-01 + .585485599535E-01 .622688788272E-01 .662211674610E-01 .704194509412E-01 .748785587749E-01 + .796141666712E-01 .846428400460E-01 .899820792747E-01 .956503667062E-01 .101667215451E+00 + .108053219945E+00 .114830108271E+00 .122020796239E+00 .129649443177E+00 .137741509388E+00 + .146323815234E+00 .155424601742E+00 .165073592657E+00 .175302057823E+00 .186142877738E+00 + .197630609132E+00 .209801551371E+00 .222693813452E+00 .236347381338E+00 .250804185329E+00 + .266108167138E+00 .282305346272E+00 .299443885308E+00 .317574153560E+00 .336748788604E+00 + .357022755061E+00 .378453399961E+00 .401100503966E+00 .425026327615E+00 .450295651730E+00 + .476975810973E+00 .505136719518E+00 .534850887654E+00 .566193428081E+00 .599242050517E+00 + .634077043169E+00 .670781239474E+00 .709439968420E+00 .750140986642E+00 .792974390370E+00 + .838032505174E+00 .885409751349E+00 .935202482669E+00 .987508796104E+00 .104242831002E+01 + .110006190827E+01 .116051144745E+01 .122387942461E+01 .129026860260E+01 .135978159017E+01 + .143252037390E+01 .150858579919E+01 .158807699749E+01 .167109075688E+01 .175772083353E+01 + .184805720162E+01 .194218523933E+01 .204018484914E+01 .214212951079E+01 .224808526583E+01 + .235810963304E+01 .247225045485E+01 .259054467535E+01 .271301705146E+01 .283967879975E+01 + .297052618226E+01 .310553903613E+01 .324467925296E+01 .338788921520E+01 .353509019870E+01 + .368618075190E+01 .384103506433E+01 .399950133877E+01 .416140018359E+01 .432652304404E+01 + .449463069343E+01 .466545180749E+01 .483868164752E+01 .501398088047E+01 .519097456619E+01 + .536925134438E+01 .554836285615E+01 .572782343649E+01 .590711011606E+01 .608566297177E+01 + .626288586635E+01 .643814761788E+01 .661078363938E+01 .678009808823E+01 .694536656274E+01 + .710583938103E+01 .726074547323E+01 .740929691345E+01 .755069411170E+01 .768413167876E+01 + .780880496809E+01 .792391728912E+01 .802868777438E+01 .812235987040E+01 .820421040778E+01 + .827355919064E+01 .832977902881E+01 .837230611874E+01 .840065066096E+01 .841440758325E+01 + .841326722016E+01 .839702578152E+01 .836559542526E+01 .831901373419E+01 .825745238298E+01 + .818122477058E+01 .809079238605E+01 .798676967249E+01 .786992715557E+01 .774119261011E+01 + .760165005169E+01 .745253636003E+01 .729523536819E+01 .713126928576E+01 .696228736593E+01 + .679005177517E+01 .661642067944E+01 .644332862203E+01 .627276433335E+01 .610674618159E+01 + .594729554133E+01 .579640842184E+01 .565602576681E+01 .552800287068E+01 .541407839925E+01 + .531584353892E+01 .523471177953E+01 .517188984282E+01 .512835026211E+01 .510480613184E+01 + .510168858572E+01 .511912762968E+01 .515693703459E+01 .521460405617E+01 .529128475754E+01 + .538580562001E+01 .549667189770E+01 .562208280769E+01 .575995323743E+01 .590794134470E+01 + .606348131935E+01 .622382063669E+01 .638606123530E+01 .654720408632E+01 .670419655739E+01 + .685398184633E+01 .699354961718E+01 .711998685544E+01 .723052788809E+01 .732260249172E+01 + .739388103439E+01 .744231565540E+01 .746617657427E+01 .746408272963E+01 .743502607482E+01 + .737838899666E+01 .729395447390E+01 .718190874815E+01 .704283644131E+01 .687770821462E+01 + .668786122365E+01 .647497277612E+01 .624102774402E+01 .598828041327E+01 .571921157222E+01 + .543648174187E+01 .514288153425E+01 .484128019032E+01 .453457339482E+01 .422563149315E+01 + .391724924503E+01 .361209824281E+01 .331268309860E+01 .302130245731E+01 .274001582420E+01 + .247061708263E+01 .221461541805E+01 .197322413413E+01 .174735759662E+01 .153763606876E+01 + .134439807766E+01 .116771931577E+01 .100743688382E+01 .863177180939E+00 .734385201328E+00 + .620352489207E+00 .520241312105E+00 .433105012361E+00 .357908953755E+00 .293558971531E+00 + .238939332961E+00 .192952602310E+00 .154550561105E+00 .122752025089E+00 .966509456742E-01 + .754197389551E-01 .583105713293E-01 .446553155083E-01 .338641489723E-01 .254227504169E-01 + .188882123217E-01 .138839144900E-01 .100936595806E-01 + kinetic energy-density + .667223264162E+01 .673711797765E+01 .680446051695E+01 .687434851945E+01 .694687595542E+01 + .702214224715E+01 .710025264340E+01 .718131851959E+01 .726545770326E+01 .735279480889E+01 + .744346157547E+01 .753759722098E+01 .763534880551E+01 .773687160651E+01 .784232950769E+01 + .795189540556E+01 .806575163262E+01 .818409040251E+01 .830711427710E+01 .843503666033E+01 + .856808232008E+01 .870648794174E+01 .885050271727E+01 .900038897044E+01 .915642282528E+01 + .931889491632E+01 .948811114834E+01 .966439350589E+01 .984808091773E+01 .100395301784E+02 + .102391169326E+02 .104472367229E+02 .106643061077E+02 .108907638526E+02 .111270721976E+02 + .113737182071E+02 .116312152061E+02 .119001043069E+02 .121809560330E+02 .124743720445E+02 + .127809869719E+02 .131014703626E+02 .134365287498E+02 .137869078483E+02 .141533948854E+02 + .145368210760E+02 .149380642484E+02 .153580516325E+02 .157977628176E+02 .162582328917E+02 + .167405557713E+02 .172458877376E+02 .177754511847E+02 .183305385986E+02 .189125167802E+02 + .195228313211E+02 .201630113570E+02 .208346746071E+02 .215395327218E+02 .222793969540E+02 + .230561841768E+02 .238719232645E+02 .247287618625E+02 .256289735654E+02 .265749655308E+02 + .275692865534E+02 .286146356255E+02 .297138710144E+02 .308700198863E+02 .320862885081E+02 + .333660730613E+02 .347129711045E+02 .361307937197E+02 .376235783832E+02 .391956026049E+02 + .408513983733E+02 .425957674600E+02 .444337976250E+02 .463708797814E+02 .484127261615E+02 + .505653895529E+02 .528352836548E+02 .552292046175E+02 .577543538336E+02 .604183620400E+02 + .632293148117E+02 .661957795124E+02 .693268337816E+02 .726320956402E+02 .761217552952E+02 + .798066087313E+02 .836980931813E+02 .878083245648E+02 .921501369964E+02 .967371244646E+02 + .101583684778E+03 .106705065895E+03 .112117414743E+03 .117837828637E+03 .123884409424E+03 + .130276320461E+03 .137033846552E+03 .144178456977E+03 .151732871716E+03 .159721131020E+03 + .168168668441E+03 .177102387447E+03 .186550741762E+03 .196543819548E+03 .207113431542E+03 + .218293203301E+03 .230118671632E+03 .242627385346E+03 .255859010429E+03 .269855439723E+03 + .284660907211E+03 .300322106967E+03 .316888316840E+03 .334411526903E+03 .352946572698E+03 + .372551273268E+03 .393286573957E+03 .415216693909E+03 .438409278191E+03 .462935554406E+03 + .488870493624E+03 .516292975418E+03 .545285956739E+03 .575936644299E+03 .608336670067E+03 + .642582269425E+03 .678774461430E+03 .717019230563E+03 .757427709234E+03 .800116360219E+03 + .845207158092E+03 .892827768584E+03 .943111724662E+03 .996198598018E+03 .105223416443E+04 + .111137056136E+04 .117376643592E+04 .123958708122E+04 .130900455875E+04 .138219780446E+04 + .145935271573E+04 .154066221641E+04 .162632629657E+04 .171655202365E+04 .181155352120E+04 + .191155191114E+04 .201677521519E+04 .212745821087E+04 .224384223707E+04 .236617494387E+04 + .249470998100E+04 .262970661903E+04 .277142929698E+04 .292014708990E+04 .307613308942E+04 + .323966369031E+04 .341101777559E+04 .359047579274E+04 .377831871320E+04 .397482686744E+04 + .418027864771E+04 .439494907065E+04 .461910819220E+04 .485301936717E+04 .509693734651E+04 + .535110620572E+04 .561575709823E+04 .589110582872E+04 .617735024215E+04 .647466742549E+04 + .678321072048E+04 .710310654759E+04 .743445104313E+04 .777730651347E+04 .813169771335E+04 + .849760795736E+04 .887497507731E+04 .926368724144E+04 .966357865505E+04 .100744251666E+05 + .104959398071E+05 .109277682965E+05 .113694845538E+05 .118205862555E+05 .122804904900E+05 + .127485295625E+05 .132239470112E+05 .137058938992E+05 .141934254546E+05 .146854981352E+05 + .151809671997E+05 .156785848725E+05 .161769991918E+05 .166747536369E+05 .171702876279E+05 + .176619379985E+05 .181479415367E+05 .186264386884E+05 .190954785183E+05 .195530250094E+05 + .199969647834E+05 .204251163067E+05 .208352406373E+05 .212250537526E+05 .215922404774E+05 + .219344700116E+05 .222494130342E+05 .225347603288E+05 .227882428528E+05 .230076531342E+05 + .231908678498E+05 .233358714016E+05 .234407802719E+05 .235038678982E+05 .235235897755E+05 + .234986084530E+05 .234278180618E+05 .233103679754E+05 .231456851799E+05 .229334949056E+05 + .226738390590E+05 .223670919806E+05 .220139730591E+05 .216155557379E+05 .211732724746E+05 + .206889152456E+05 .201646312393E+05 .196029134408E+05 .190065858947E+05 .183787835298E+05 + .177229265428E+05 .170426894747E+05 .163419652635E+05 .156248247191E+05 .148954720435E+05 + .141581971857E+05 .134173261542E+05 .126771693102E+05 .119419713654E+05 .112158605938E+05 + .105028007380E+05 .980654499989E+04 .913059236999E+04 .847814611827E+04 .785207438837E+04 + .725487344929E+04 .668863511301E+04 .615502069364E+04 .565524417361E+04 .519006672766E+04 + .475980357784E+04 .436434266402E+04 .400317320563E+04 .367542131406E+04 .337988973053E+04 + .311509948092E+04 .287933226802E+04 .267067318949E+04 .248705363715E+04 .232629412847E+04 + .218614659385E+04 .206433545994E+04 .195859678351E+04 .186671469198E+04 .178655445016E+04 + .171609157853E+04 .165343658116E+04 .159685499112E+04 .154478259599E+04 .149583585719E+04 + .144881767535E+04 .140271877451E+04 .135671507596E+04 .131016150708E+04 .126258274155E+04 + .121366139499E+04 .116322420862E+04 .111122674356E+04 .105773708455E+04 .100291901627E+04 + .947015091482E+03 .890329959869E+03 .833214272270E+03 .776049418457E+03 .719233299337E+03 + .663167278558E+03 .608244406410E+03 .554838966220E+03 .503297358442E+03 .453930336633E+03 + .407006601755E+03 .362747806752E+03 .321325033168E+03 .282856907413E+03 .247409252478E+03 + .214996590257E+03 .185585245619E+03 .159098177908E+03 .135421633456E+03 .114413857777E+03 + .959157099433E+02 .797613979036E+02 .657850515169E+02 .538188522131E+02 .436847873034E+02 + .351899916323E+02 .281331203679E+02 .223174729841E+02 .175614967879E+02 .137029357329E+02 + .105987319431E+02 .812353742881E+01 .616817860109E+01 .463832203023E+01 .345324816958E+01 + .254463542651E+01 .185531926861E+01 .133803588607E+01 + pspotential + -.284668580974E+02 -.284683169301E+02 -.284697298194E+02 -.284710982122E+02 -.284724235102E+02 + -.284737070698E+02 -.284749502063E+02 -.284761541924E+02 -.284773202611E+02 -.284784496066E+02 + -.284795433857E+02 -.284806027180E+02 -.284816286891E+02 -.284826223489E+02 -.284835847157E+02 + -.284845167748E+02 -.284854194805E+02 -.284862937574E+02 -.284871405012E+02 -.284879605786E+02 + -.284887548297E+02 -.284895240675E+02 -.284902690805E+02 -.284909906311E+02 -.284916894586E+02 + -.284923662782E+02 -.284930217837E+02 -.284936566461E+02 -.284942715156E+02 -.284948670220E+02 + -.284954437749E+02 -.284960023654E+02 -.284965433652E+02 -.284970673288E+02 -.284975747926E+02 + -.284980662764E+02 -.284985422834E+02 -.284990033014E+02 -.284994498023E+02 -.284998822437E+02 + -.285003010685E+02 -.285007067055E+02 -.285010995703E+02 -.285014800653E+02 -.285018485803E+02 + -.285022054928E+02 -.285025511684E+02 -.285028859612E+02 -.285032102143E+02 -.285035242597E+02 + -.285038284193E+02 -.285041230047E+02 -.285044083177E+02 -.285046846506E+02 -.285049522867E+02 + -.285052115003E+02 -.285054625570E+02 -.285057057141E+02 -.285059412208E+02 -.285061693187E+02 + -.285063902416E+02 -.285066042160E+02 -.285068114613E+02 -.285070121901E+02 -.285072066083E+02 + -.285073949154E+02 -.285075773047E+02 -.285077539632E+02 -.285079250725E+02 -.285080908082E+02 + -.285082513405E+02 -.285084068344E+02 -.285085574497E+02 -.285087033412E+02 -.285088446592E+02 + -.285089815489E+02 -.285091141512E+02 -.285092426028E+02 -.285093670362E+02 -.285094875796E+02 + -.285096043574E+02 -.285097174903E+02 -.285098270953E+02 -.285099332857E+02 -.285100361716E+02 + -.285101358596E+02 -.285102324533E+02 -.285103260530E+02 -.285104167563E+02 -.285105046579E+02 + -.285105898494E+02 -.285106724202E+02 -.285107524569E+02 -.285108300437E+02 -.285109052623E+02 + -.285109781925E+02 -.285110489115E+02 -.285111174947E+02 -.285111840153E+02 -.285112485448E+02 + -.285113111527E+02 -.285113719068E+02 -.285114308734E+02 -.285114881171E+02 -.285115437009E+02 + -.285115976866E+02 -.285116501346E+02 -.285117011040E+02 -.285117506529E+02 -.285117988383E+02 + -.285118457160E+02 -.285118913411E+02 -.285119357679E+02 -.285119790499E+02 -.285120212399E+02 + -.285120623903E+02 -.285121025528E+02 -.285121417791E+02 -.285121801201E+02 -.285122176271E+02 + -.285122543509E+02 -.285122903425E+02 -.285123256531E+02 -.285123603339E+02 -.285123944366E+02 + -.285124280136E+02 -.285124611175E+02 -.285124938019E+02 -.285125261211E+02 -.285125581306E+02 + -.285125898869E+02 -.285126214480E+02 -.285126528730E+02 -.285126842231E+02 -.285127155610E+02 + -.285127469515E+02 -.285127784618E+02 -.285128101613E+02 -.285128421220E+02 -.285128744192E+02 + -.285129071308E+02 -.285129403386E+02 -.285129741276E+02 -.285130085872E+02 -.285130438109E+02 + -.285130798969E+02 -.285131169482E+02 -.285131550734E+02 -.285131943868E+02 -.285132350088E+02 + -.285132770666E+02 -.285133206943E+02 -.285133660339E+02 -.285134132352E+02 -.285134624572E+02 + -.285135138679E+02 -.285135676456E+02 -.285136239791E+02 -.285136830688E+02 -.285137451272E+02 + -.285138103801E+02 -.285138790671E+02 -.285139514428E+02 -.285140277778E+02 -.285141083597E+02 + -.285141934943E+02 -.285142835068E+02 -.285143787430E+02 -.285144795711E+02 -.285145863826E+02 + -.285146995943E+02 -.285148196500E+02 -.285149470220E+02 -.285150822131E+02 -.285152257590E+02 + -.285153782298E+02 -.285155402330E+02 -.285157124155E+02 -.285158954666E+02 -.285160901204E+02 + -.285162971590E+02 -.285165174159E+02 -.285167517787E+02 -.285170011938E+02 -.285172666691E+02 + -.285175492789E+02 -.285178501680E+02 -.285181705563E+02 -.285185117440E+02 -.285188751165E+02 + -.285192621507E+02 -.285196744202E+02 -.285201136023E+02 -.285205814849E+02 -.285210799732E+02 + -.285216110981E+02 -.285221770239E+02 -.285227800576E+02 -.285234226581E+02 -.285241074462E+02 + -.285248372152E+02 -.285256149423E+02 -.285264438010E+02 -.285273271733E+02 -.285282686643E+02 + -.285292721163E+02 -.285303416243E+02 -.285314815531E+02 -.285326965547E+02 -.285339915870E+02 + -.285353719343E+02 -.285368432283E+02 -.285384114710E+02 -.285400830591E+02 -.285418648095E+02 + -.285437639871E+02 -.285457883340E+02 -.285479461006E+02 -.285502460786E+02 -.285526976368E+02 + -.285553107581E+02 -.285580960799E+02 -.285610649366E+02 -.285642294047E+02 -.285676023510E+02 + -.285711974839E+02 -.285750294079E+02 -.285791136815E+02 -.285834668789E+02 -.285881066552E+02 + -.285930518163E+02 -.285983223931E+02 -.286039397193E+02 -.286099265159E+02 -.286163069793E+02 + -.286231068758E+02 -.286303536416E+02 -.286380764889E+02 -.286463065191E+02 -.286550768420E+02 + -.286644227033E+02 -.286743816188E+02 -.286849935181E+02 -.286963008955E+02 -.287083489715E+02 + -.287211858626E+02 -.287348627628E+02 -.287494341353E+02 -.287649579152E+02 -.287814957256E+02 + -.287991131063E+02 -.288178797557E+02 -.288378697884E+02 -.288591620081E+02 -.288818401970E+02 + -.289059934240E+02 -.289317163713E+02 -.289591096822E+02 -.289882803316E+02 -.290193420199E+02 + -.290524155945E+02 -.290876294986E+02 -.291251202524E+02 -.291650329680E+02 -.292075219026E+02 + -.292527510523E+02 -.293008947930E+02 -.293521385709E+02 -.294066796496E+02 -.294647279184E+02 + -.295265067689E+02 -.295922540467E+02 -.296622230833E+02 -.297366838166E+02 -.298159240051E+02 + -.299002505394E+02 -.299899908538E+02 -.300854944348E+02 -.301871344177E+02 -.302953092527E+02 + -.304104444074E+02 -.305329940542E+02 -.306634426595E+02 -.308023063576E+02 -.309501339324E+02 + -.311075071620E+02 -.312750401800E+02 -.314533773784E+02 -.316431892087E+02 -.318451650241E+02 + -.320600018433E+02 -.322883876156E+02 -.325309772422E+02 -.327883593234E+02 -.330610114486E+02 + -.333492420108E+02 -.336531172581E+02 -.339723739182E+02 -.343063205135E+02 -.346537343042E+02 + -.350127645096E+02 -.353808527148E+02 -.357546711895E+02 -.361300477034E+02 -.365017781319E+02 + -.368631244736E+02 -.372047033483E+02 -.375125520335E+02 -.377657440182E+02 -.379353182676E+02 + -.379879388728E+02 -.378969924352E+02 -.376572675510E+02 -.372895576252E+02 -.368609887562E+02 + -.364580390768E+02 -.360705398248E+02 -.356893343561E+02 -.353112759338E+02 -.349371692255E+02 + -.345669009212E+02 -.341257373489E+02 -.337108274651E+02 + core charge-density (pseudized) + .158850907132E-07 .169349744559E-07 .180542475326E-07 .192474960507E-07 .205196092244E-07 + .218757994079E-07 .233216234522E-07 .248630054739E-07 .265062611287E-07 .282581234892E-07 + .301257706327E-07 .321168550529E-07 .342395350151E-07 .365025079838E-07 .389150462599E-07 + .414870349726E-07 .442290125832E-07 .471522140648E-07 .502686169368E-07 .535909903417E-07 + .571329473648E-07 .609090008129E-07 .649346226787E-07 .692263075359E-07 .738016401239E-07 + .786793673994E-07 .838794753501E-07 .894232708855E-07 .953334691390E-07 .101634286542E-06 + .108351540046E-06 .115512752907E-06 .123147267460E-06 .131286365342E-06 .139963395669E-06 + .149213911678E-06 .159075816404E-06 .169589517985E-06 .180798095227E-06 .192747474115E-06 + .205486615992E-06 .219067718171E-06 .233546427810E-06 .248982069915E-06 .265437890425E-06 + .282981315349E-06 .301684227038E-06 .321623258718E-06 .342880108482E-06 .365541874040E-06 + .389701409594E-06 .415457706293E-06 .442916297843E-06 .472189692914E-06 .503397836133E-06 + .536668599544E-06 .572138306547E-06 .609952290465E-06 .650265490033E-06 .693243084236E-06 + .739061169114E-06 .787907479286E-06 .839982157176E-06 .895498573063E-06 .954684199344E-06 + .101778154256E-05 .108504913706E-05 .115676260427E-05 .123321578204E-05 .131472192859E-05 + .140161500606E-05 .149425104883E-05 .159300962235E-05 .169829537834E-05 .181053971277E-05 + .193020253346E-05 .205777414445E-05 .219377725496E-05 .233876912105E-05 .249334382893E-05 + .265813472909E-05 .283381703132E-05 .302111057124E-05 .322078275972E-05 .343365172714E-05 + .366058967549E-05 .390252645204E-05 .416045335916E-05 .443542721593E-05 .472857468816E-05 + .504109690465E-05 .537427437842E-05 .572947225328E-05 .610814589706E-05 .651184686453E-05 + .694222925437E-05 .740105648627E-05 .789020852588E-05 .841168958728E-05 .896763634441E-05 + .956032668519E-05 .101921890442E-04 .108658123520E-04 .115839566421E-04 .123495643585E-04 + .131657724114E-04 .140359250280E-04 .149635874541E-04 .159525605604E-04 .170068964137E-04 + .181309148776E-04 .193292213099E-04 .206067254291E-04 .219686614285E-04 .234206094181E-04 + .249685182840E-04 .266187300582E-04 .283780058984E-04 .302535537841E-04 .322530580431E-04 + .343847108279E-04 .366572456728E-04 .390799732669E-04 .416628195906E-04 .444163665717E-04 + .473518954273E-04 .504814328676E-04 .538178003533E-04 .573746666051E-04 .611666035821E-04 + .652091461570E-04 .695188557326E-04 .741133880594E-04 .790115655314E-04 .842334542561E-04 + .898004462130E-04 .957353468361E-04 .102062468380E-03 .108807729446E-03 .115998761083E-03 + .123665019889E-03 .131837908571E-03 .140550904475E-03 .149839696579E-03 .159742331544E-03 + .170299369380E-03 .181554049396E-03 .193552467086E-03 .206343762684E-03 .219980322147E-03 + .234517991391E-03 .250016304646E-03 .266538727861E-03 .284152918146E-03 .302931000300E-03 + .322949861560E-03 .344291465748E-03 .367043188107E-03 .391298172159E-03 .417155710061E-03 + .444721647953E-03 .474108817981E-03 .505437498701E-03 .538835905735E-03 .574440714657E-03 + .612397618202E-03 .652861920041E-03 .695999167499E-03 .741985825749E-03 .791009996188E-03 + .843272181843E-03 .898986102869E-03 .958379565380E-03 .102169538706E-02 .108919238320E-02 + .116114641712E-02 .123785151900E-02 .131962107766E-02 .140678910979E-02 .149971161181E-02 + .159876799938E-02 .170436264031E-02 .181692648675E-02 .193691881296E-02 .206482906523E-02 + .220117883122E-02 .234652393586E-02 .250145667215E-02 .266660817484E-02 .284265094610E-02 + .303030154244E-02 .323032343282E-02 .344353003832E-02 .367078796445E-02 .391302043770E-02 + .417121095843E-02 .444640718317E-02 .473972504961E-02 .505235315859E-02 .538555742793E-02 + .574068603353E-02 .611917465425E-02 .652255203717E-02 .695244590122E-02 .741058919732E-02 + .789882674413E-02 .841912225897E-02 .897356580441E-02 .956438167099E-02 .101939367177E-01 + .108647491919E-01 .115794980501E-01 .123410328028E-01 .131523839044E-01 .140167737110E-01 + .149376280269E-01 .159185882611E-01 .169635242136E-01 .180765475092E-01 .192620256957E-01 + .205245970213E-01 .218691859007E-01 .233010190786E-01 .248256424935E-01 .264489388384E-01 + .281771458098E-01 .300168750282E-01 .319751316050E-01 .340593343169E-01 .362773363404E-01 + .386374464823E-01 .411484508237E-01 .438196346781E-01 .466608047400E-01 .496823112734E-01 + .528950701615E-01 .563105846042E-01 .599409662088E-01 .637989551781E-01 .678979392487E-01 + .722519709725E-01 .768757828747E-01 .817847999463E-01 .869951488479E-01 .925236631107E-01 + .983878835213E-01 .104606052760E+00 .111197103239E+00 .118180636950E+00 .125576895976E+00 + .133406722150E+00 .141691504177E+00 .150453110317E+00 .159713804529E+00 .169496143740E+00 + .179822853659E+00 .190716680317E+00 .202200214208E+00 .214295683694E+00 .227024713996E+00 + .240408047883E+00 .254465223863E+00 .269214207487E+00 .284670971153E+00 .300849017672E+00 + .317758842779E+00 .335407331821E+00 .353797086014E+00 .372925673998E+00 .392784804976E+00 + .413359420546E+00 .434626703479E+00 .456555003242E+00 .479102680107E+00 .502216872244E+00 + .525832193516E+00 .549869373680E+00 .574233857642E+00 .598814386387E+00 .623481589187E+00 + .648086625061E+00 .672459920978E+00 .696410065316E+00 .719722927378E+00 .742161087375E+00 + .763463676005E+00 .783346738217E+00 .801504251502E+00 .817609944243E+00 .831320073323E+00 + .842277330789E+00 .850116055018E+00 .854468920152E+00 .854975265373E+00 .851291199249E+00 + .843101569433E+00 .830133819226E+00 .812173654295E+00 .789082308931E+00 .760815025548E+00 + .727440137991E+00 .689157874534E+00 .646317668655E+00 .599432387566E+00 .549187469489E+00 + .496442519212E+00 .442222478719E+00 .387695112852E+00 .334131296257E+00 .282844548501E+00 + .235106556397E+00 .192036190812E+00 .154460937507E+00 .122751901168E+00 .966509456742E-01 + .754197389551E-01 .583105713293E-01 .446553155083E-01 .338641489723E-01 .254227504169E-01 + .188882123217E-01 .138839144900E-01 .100936595806E-01 + pseudo wavefunction + .575355356415E-04 .594064477253E-04 .613381972024E-04 .633327623533E-04 .653921857868E-04 + .675185765325E-04 .697141122004E-04 .719810412106E-04 .743216850967E-04 .767384408824E-04 + .792337835369E-04 .818102685089E-04 .844705343442E-04 .872173053874E-04 .900533945721E-04 + .929817063013E-04 .960052394220E-04 .991270902962E-04 .102350455972E-03 .105678637457E-03 + .109115043101E-03 .112663192082E-03 .116326718016E-03 .120109372672E-03 .124015029819E-03 + .128047689192E-03 .132211480586E-03 .136510668086E-03 .140949654437E-03 .145532985548E-03 + .150265355149E-03 .155151609602E-03 .160196752857E-03 .165405951581E-03 .170784540448E-03 + .176338027603E-03 .182072100302E-03 .187992630735E-03 .194105682043E-03 .200417514522E-03 + .206934592042E-03 .213663588656E-03 .220611395446E-03 .227785127571E-03 .235192131559E-03 + .242839992828E-03 .250736543454E-03 .258889870194E-03 .267308322765E-03 .276000522397E-03 + .284975370659E-03 .294242058578E-03 .303810076049E-03 .313689221556E-03 .323889612204E-03 + .334421694082E-03 .345296252956E-03 .356524425323E-03 .368117709807E-03 .380087978939E-03 + .392447491317E-03 .405208904153E-03 .418385286245E-03 .431990131351E-03 .446037372013E-03 + .460541393824E-03 .475517050162E-03 .490979677395E-03 .506945110594E-03 .523429699744E-03 + .540450326492E-03 .558024421429E-03 .576169981949E-03 .594905590672E-03 .614250434477E-03 + .634224324152E-03 .654847714681E-03 .676141726189E-03 .698128165574E-03 .720829548839E-03 + .744269124145E-03 .768470895626E-03 .793459647966E-03 .819260971781E-03 .845901289826E-03 + .873407884057E-03 .901808923562E-03 .931133493415E-03 .961411624459E-03 .992674324057E-03 + .102495360785E-02 .105828253254E-02 .109269522973E-02 .112822694092E-02 .116491405352E-02 + .120279413821E-02 .124190598731E-02 .128228965460E-02 .132398649626E-02 .136703921328E-02 + .141149189515E-02 .145739006503E-02 .150478072633E-02 .155371241090E-02 .160423522870E-02 + .165640091909E-02 .171026290385E-02 .176587634186E-02 .182329818560E-02 .188258723945E-02 + .194380421993E-02 .200701181784E-02 .207227476250E-02 .213965988796E-02 .220923620153E-02 + .228107495436E-02 .235524971443E-02 .243183644189E-02 .251091356682E-02 .259256206952E-02 + .267686556349E-02 .276391038097E-02 .285378566135E-02 .294658344250E-02 .304239875489E-02 + .314132971901E-02 .324347764574E-02 .334894714010E-02 .345784620834E-02 .357028636854E-02 + .368638276474E-02 .380625428484E-02 .393002368229E-02 .405781770175E-02 .418976720886E-02 + .432600732415E-02 .446667756139E-02 .461192197039E-02 .476188928438E-02 .491673307231E-02 + .507661189599E-02 .524168947234E-02 .541213484098E-02 .558812253715E-02 .576983277035E-02 + .595745160873E-02 .615117116944E-02 .635118981518E-02 .655771235717E-02 .677095026461E-02 + .699112188101E-02 .721845264752E-02 .745317533347E-02 .769553027439E-02 .794576561781E-02 + .820413757691E-02 .847091069247E-02 .874635810329E-02 .903076182533E-02 .932441303995E-02 + .962761239135E-02 .994067029381E-02 .102639072487E-01 .105976541719E-01 .109422527315E-01 + .112980556968E-01 .116654272983E-01 .120447435995E-01 .124363928804E-01 .128407760336E-01 + .132583069731E-01 .136894130563E-01 .141345355194E-01 .145941299272E-01 .150686666365E-01 + .155586312758E-01 .160645252384E-01 .165868661936E-01 .171261886122E-01 .176830443099E-01 + .182580030081E-01 .188516529119E-01 .194646013071E-01 .200974751761E-01 .207509218330E-01 + .214256095793E-01 .221222283799E-01 .228414905610E-01 .235841315294E-01 .243509105150E-01 + .251426113360E-01 .259600431889E-01 .268040414619E-01 .276754685752E-01 .285752148462E-01 + .295041993818E-01 .304633709985E-01 .314537091706E-01 .324762250072E-01 .335319622594E-01 + .346219983579E-01 .357474454814E-01 .369094516585E-01 .381092019006E-01 .393479193701E-01 + .406268665822E-01 .419473466418E-01 .433107045170E-01 .447183283484E-01 .461716507967E-01 + .476721504277E-01 .492213531363E-01 .508208336098E-01 .524722168313E-01 .541771796234E-01 + .559374522328E-01 .577548199563E-01 .596311248087E-01 .615682672319E-01 .635682078464E-01 + .656329692451E-01 .677646378278E-01 .699653656785E-01 .722373724825E-01 .745829474842E-01 + .770044514849E-01 .795043188773E-01 .820850597180E-01 .847492618341E-01 .874995929625E-01 + .903388029198E-01 .932697257982E-01 .962952821862E-01 .994184814074E-01 .102642423774E+00 + .105970302852E+00 .109405407722E+00 .112951125248E+00 .116610942317E+00 .120388448077E+00 + .124287336121E+00 .128311406648E+00 .132464568547E+00 .136750841429E+00 .141174357551E+00 + .145739363643E+00 .150450222608E+00 .155311415056E+00 .160327540676E+00 .165503319382E+00 + .170843592230E+00 .176353322051E+00 .182037593757E+00 .187901614291E+00 .193950712150E+00 + .200190336440E+00 .206626055381E+00 .213263554212E+00 .220108632399E+00 .227167200068E+00 + .234445273557E+00 .241948969987E+00 .249684500724E+00 .257658163593E+00 .265876333703E+00 + .274345452710E+00 .283072016330E+00 .292062559898E+00 .301323641738E+00 .310861824101E+00 + .320683651362E+00 .330795625188E+00 .341204176307E+00 .351915632491E+00 .362936182330E+00 + .374271834305E+00 .385928370642E+00 .397911295339E+00 .410225775742E+00 .422876576925E+00 + .435867988095E+00 .449203740138E+00 .462886913351E+00 .476919834292E+00 .491303960597E+00 + .506039752485E+00 .521126529587E+00 .536562311577E+00 .552343640997E+00 .568465386534E+00 + .584920524858E+00 .601699899070E+00 .618791951638E+00 .636182429658E+00 .653854060191E+00 + .671786193400E+00 .689954411226E+00 .708330099434E+00 .726879981021E+00 .745565609229E+00 + .764342818847E+00 .783161135014E+00 .801963139531E+00 .820683795679E+00 .839249733873E+00 + .857578502086E+00 .875577787069E+00 .893144614848E+00 .910164542018E+00 .926510852941E+00 + .942043782108E+00 .956609785792E+00 .970040892551E+00 .982154168203E+00 .992751337468E+00 + .100161861137E+01 .100852677652E+01 .101323160906E+01 .101547468225E+01 .101498464091E+01 + .101147901878E+01 .100466111560E+01 .994375951175E+00 + ae wavefunction + .723210491674E-03 .746578583504E-03 .770700951777E-03 .795601892046E-03 .821306479222E-03 + .847840592364E-03 .875230940233E-03 .903505087646E-03 .932691482648E-03 .962819484530E-03 + .993919392710E-03 .102602247652E-02 .105916100589E-02 .109336828301E-02 .112867867496E-02 + .116512764731E-02 .120275179882E-02 .124158889712E-02 .128167791559E-02 .132305907123E-02 + .136577386383E-02 .140986511623E-02 .145537701585E-02 .150235515746E-02 .155084658728E-02 + .160089984836E-02 .165256502735E-02 .170589380272E-02 .176093949434E-02 .181775711461E-02 + .187640342107E-02 .193693697064E-02 .199941817539E-02 .206390935997E-02 .213047482081E-02 + .219918088694E-02 .227009598271E-02 .234329069219E-02 .241883782559E-02 .249681248751E-02 + .257729214718E-02 .266035671067E-02 .274608859525E-02 .283457280576E-02 .292589701322E-02 + .302015163557E-02 .311742992074E-02 .321782803195E-02 .332144513543E-02 .342838349055E-02 + .353874854230E-02 .365264901643E-02 .377019701702E-02 .389150812670E-02 .401670150953E-02 + .414590001658E-02 .427923029422E-02 .441682289522E-02 .455881239271E-02 .470533749697E-02 + .485654117518E-02 .501257077409E-02 .517357814572E-02 .533971977604E-02 .551115691676E-02 + .568805572017E-02 .587058737709E-02 .605892825797E-02 .625326005711E-02 .645376994004E-02 + .666065069409E-02 .687410088207E-02 .709432499912E-02 .732153363272E-02 .755594362580E-02 + .779777824289E-02 .804726733939E-02 .830464753379E-02 .857016238277E-02 .884406255928E-02 + .912660603329E-02 .941805825521E-02 .971869234197E-02 .100287892654E-01 .103486380429E-01 + .106785359304E-01 .110187886169E-01 .113697104211E-01 .117316244893E-01 .121048629944E-01 + .124897673360E-01 .128866883414E-01 .132959864662E-01 .137180319953E-01 .141532052432E-01 + .146018967537E-01 .150645074973E-01 .155414490675E-01 .160331438739E-01 .165400253324E-01 + .170625380517E-01 .176011380142E-01 .181562927528E-01 .187284815203E-01 .193181954522E-01 + .199259377210E-01 .205522236809E-01 .211975810029E-01 .218625497970E-01 .225476827224E-01 + .232535450820E-01 .239807149024E-01 .247297829946E-01 .255013529962E-01 .262960413920E-01 + .271144775113E-01 .279573034995E-01 .288251742619E-01 .297187573775E-01 .306387329797E-01 + .315857936016E-01 .325606439823E-01 .335640008323E-01 .345965925527E-01 .356591589072E-01 + .367524506409E-01 .378772290432E-01 .390342654498E-01 .402243406813E-01 .414482444099E-01 + .427067744540E-01 .440007359916E-01 .453309406888E-01 .466982057375E-01 .481033527959E-01 + .495472068255E-01 .510305948176E-01 .525543444026E-01 .541192823346E-01 .557262328435E-01 + .573760158460E-01 .590694450081E-01 .608073256492E-01 .625904524789E-01 .644196071575E-01 + .662955556690E-01 .682190454976E-01 .701908025956E-01 .722115281337E-01 .742818950192E-01 + .764025441734E-01 .785740805545E-01 .807970689137E-01 .830720292724E-01 .853994321068E-01 + .877796932277E-01 .902131683422E-01 .927001472824E-01 .952408478902E-01 .978354095427E-01 + .100483886305E+00 .103186239701E+00 .105942331082E+00 .108751913586E+00 .111614623678E+00 + .114529972255E+00 .117497335304E+00 .120515944107E+00 .123584874990E+00 .126703038594E+00 + .129869168677E+00 .133081810436E+00 .136339308348E+00 .139639793532E+00 .142981170636E+00 + .146361104253E+00 .149777004875E+00 .153226014404E+00 .156704991228E+00 .160210494897E+00 + .163738770409E+00 .167285732154E+00 .170846947546E+00 .174417620387E+00 .177992574025E+00 + .181566234348E+00 .185132612703E+00 .188685288794E+00 .192217393669E+00 .195721592871E+00 + .199190069873E+00 .202614509914E+00 .205986084362E+00 .209295435754E+00 .212532663666E+00 + .215687311579E+00 .218748354949E+00 .221704190648E+00 .224542628026E+00 .227250881804E+00 + .229815567059E+00 .232222696565E+00 .234457680772E+00 .236505330719E+00 .238349864209E+00 + .239974915563E+00 .241363549317E+00 .242498278209E+00 .243361085852E+00 .243933454457E+00 + .244196398032E+00 .244130501447E+00 .243715965781E+00 .242932660377E+00 .241760182005E+00 + .240177921559E+00 .238165138679E+00 .235701044686E+00 .232764894196E+00 .229336085751E+00 + .225394271769E+00 .220919478069E+00 .215892233186E+00 .210293707615E+00 .204105863065E+00 + .197311611722E+00 .189894985412E+00 .181841314484E+00 .173137416083E+00 .163771791405E+00 + .153734831344E+00 .143019029848E+00 .131619204110E+00 .119532720583E+00 .106759725623E+00 + .933033793783E-01 .791700913290E-01 .643697556467E-01 .489159842705E-01 .328263352823E-01 + .161225338086E-01 -.116931769311E-02 -.190185432589E-01 -.373897150652E-01 -.562424965567E-01 + -.755315101746E-01 -.952062316141E-01 -.115210910670E+00 -.135484516518E+00 -.155960703517E+00 + -.176567793429E+00 -.197228772403E+00 -.217861306439E+00 -.238377786432E+00 -.258685421094E+00 + -.278686400098E+00 -.298278147634E+00 -.317353677390E+00 -.335802046575E+00 -.353508895291E+00 + -.370357053514E+00 -.386227201622E+00 -.400998577469E+00 -.414549728634E+00 -.426759310469E+00 + -.437506929404E+00 -.446674028239E+00 -.454144807390E+00 -.459807173979E+00 -.463553709570E+00 + -.465282646961E+00 -.464898846615E+00 -.462314763759E+00 -.457451397642E+00 -.450239215005E+00 + -.440619040214E+00 -.428542904958E+00 -.413974850650E+00 -.396891676910E+00 -.377283629551E+00 + -.355155021405E+00 -.330524779042E+00 -.303426907952E+00 -.273910868147E+00 -.242041851308E+00 + -.207900949827E+00 -.171585207413E+00 -.133207540559E+00 -.928965205479E-01 -.507960069887E-01 + -.706462660247E-02 .381249046254E-01 .845866118155E-01 .132122232827E+00 .180522312943E+00 + .229567399836E+00 .279029316983E+00 .328672503777E+00 .378255433412E+00 .427532158406E+00 + .476254091096E+00 .524172202057E+00 .571039898221E+00 .616616860053E+00 .660673895312E+00 + .702998092998E+00 .743396069181E+00 .781691750831E+00 .817716502043E+00 .851295258407E+00 + .882238299672E+00 .910345743397E+00 .935421491735E+00 .957287299205E+00 .975791213531E+00 + .990810701652E+00 .100225314042E+01 .101005569012E+01 .101418535258E+01 .101463927777E+01 + .101144510801E+01 .100466111560E+01 .994375951175E+00 + pseudo wavefunction + .138848147713E-05 .143363143073E-05 .148024954817E-05 .152838357046E-05 .157808279106E-05 + .162939810629E-05 .168238206754E-05 .173708893499E-05 .179357473326E-05 .185189730873E-05 + .191211638882E-05 .197429364312E-05 .203849274656E-05 .210477944463E-05 .217322162069E-05 + .224388936550E-05 .231685504901E-05 .239219339443E-05 .246998155480E-05 .255029919199E-05 + .263322855826E-05 .271885458052E-05 .280726494727E-05 .289855019843E-05 .299280381807E-05 + .309012233011E-05 .319060539717E-05 .329435592268E-05 .340148015621E-05 .351208780231E-05 + .362629213282E-05 .374421010294E-05 .386596247091E-05 .399167392177E-05 .412147319496E-05 + .425549321623E-05 .439387123372E-05 .453674895855E-05 .468427270993E-05 .483659356497E-05 + .499386751345E-05 .515625561753E-05 .532392417672E-05 .549704489814E-05 .567579507240E-05 + .586035775516E-05 .605092195456E-05 .624768282482E-05 .645084186605E-05 .666060713066E-05 + .687719343636E-05 .710082258618E-05 .733172359563E-05 .757013292719E-05 .781629473250E-05 + .807046110236E-05 .833289232491E-05 .860385715220E-05 .888363307535E-05 .917250660878E-05 + .947077358361E-05 .977873945059E-05 .100967195929E-04 .104250396492E-04 .107640358469E-04 + .111140553467E-04 .114754565982E-04 .118486097064E-04 .122338968115E-04 .126317124796E-04 + .130424641070E-04 .134665723375E-04 .139044714931E-04 .143566100184E-04 .148234509404E-04 + .153054723424E-04 .158031678534E-04 .163170471539E-04 .168476364977E-04 .173954792507E-04 + .179611364475E-04 .185451873656E-04 .191482301190E-04 .197708822706E-04 .204137814640E-04 + .210775860774E-04 .217629758970E-04 .224706528134E-04 .232013415404E-04 .239557903567E-04 + .247347718727E-04 .255390838211E-04 .263695498740E-04 .272270204861E-04 .281123737658E-04 + .290265163739E-04 .299703844525E-04 .309449445827E-04 .319511947751E-04 .329901654910E-04 + .340629206980E-04 .351705589586E-04 .363142145555E-04 .374950586529E-04 .387143004951E-04 + .399731886447E-04 .412730122609E-04 .426151024191E-04 .440008334734E-04 .454316244639E-04 + .469089405685E-04 .484342946036E-04 .500092485720E-04 .516354152616E-04 .533144598965E-04 + .550481018409E-04 .568381163590E-04 .586863364318E-04 .605946546324E-04 .625650250632E-04 + .645994653551E-04 .667000587319E-04 .688689561416E-04 .711083784571E-04 .734206187480E-04 + .758080446262E-04 .782731006675E-04 .808183109118E-04 .834462814443E-04 .861597030606E-04 + .889613540173E-04 .918541028731E-04 .948409114207E-04 .979248377142E-04 .101109039194E-03 + .104396775914E-03 .107791413872E-03 .111296428448E-03 .114915407952E-03 .118652057294E-03 + .122510201760E-03 .126493790920E-03 .130606902659E-03 .134853747338E-03 .139238672088E-03 + .143766165242E-03 .148440860915E-03 .153267543723E-03 .158251153660E-03 .163396791131E-03 + .168709722144E-03 .174195383669E-03 .179859389171E-03 .185707534319E-03 .191745802874E-03 + .197980372773E-03 .204417622402E-03 .211064137063E-03 .217926715664E-03 .225012377598E-03 + .232328369866E-03 .239882174401E-03 .247681515644E-03 .255734368344E-03 .264048965612E-03 + .272633807228E-03 .281497668203E-03 .290649607612E-03 .300098977705E-03 .309855433294E-03 + .319928941443E-03 .330329791440E-03 .341068605095E-03 .352156347338E-03 .363604337150E-03 + .375424258823E-03 .387628173562E-03 .400228531432E-03 .413238183671E-03 .426670395356E-03 + .440538858462E-03 .454857705282E-03 .469641522262E-03 .484905364210E-03 .500664768938E-03 + .516935772296E-03 .533734923645E-03 .551079301749E-03 .568986531105E-03 .587474798722E-03 + .606562871331E-03 .626270113061E-03 .646616503561E-03 .667622656585E-03 .689309839028E-03 + .711699990427E-03 .734815742920E-03 .758680441650E-03 .783318165627E-03 .808753749025E-03 + .835012802915E-03 .862121737409E-03 .890107784211E-03 .918999019551E-03 .948824387471E-03 + .979613723446E-03 .101139777830E-02 .104420824237E-02 .107807776989E-02 .111304000356E-02 + .114912959911E-02 .118638225005E-02 .122483471218E-02 .126452482815E-02 .130549155155E-02 + .134777497086E-02 .139141633267E-02 .143645806444E-02 .148294379626E-02 .153091838171E-02 + .158042791736E-02 .163151976091E-02 .168424254740E-02 .173864620342E-02 .179478195889E-02 + .185270235589E-02 .191246125433E-02 .197411383369E-02 .203771659049E-02 .210332733071E-02 + .217100515649E-02 .224081044631E-02 .231280482772E-02 .238705114166E-02 .246361339709E-02 + .254255671485E-02 .262394725904E-02 .270785215452E-02 .279433938855E-02 .288347769449E-02 + .297533641527E-02 .306998534399E-02 .316749453861E-02 .326793410732E-02 .337137396094E-02 + .347788352781E-02 .358753142647E-02 .370038509052E-02 .381651033932E-02 .393597088755E-02 + .405882778553E-02 .418513878099E-02 .431495759219E-02 .444833308019E-02 .458530830718E-02 + .472591946529E-02 .487019465868E-02 .501815251889E-02 .516980063105E-02 .532513374505E-02 + .548413174236E-02 .564675732521E-02 .581295338964E-02 .598264003926E-02 .615571118988E-02 + .633203070846E-02 .651142802188E-02 .669369312193E-02 .687857088273E-02 .706575459498E-02 + .725487860842E-02 .744550995872E-02 .763713883827E-02 .782916775105E-02 .802089917058E-02 + .821152149574E-02 .840009307223E-02 .858552401783E-02 .876655555604E-02 .894173652625E-02 + .910939669822E-02 .926761647490E-02 .941419252015E-02 .954659879722E-02 .966194244997E-02 + .975691390319E-02 .982773050077E-02 .987007294359E-02 .987901373415E-02 .984893678510E-02 + .977344730712E-02 .964527106365E-02 .945614207061E-02 .919667783672E-02 .885624129362E-02 + .842278866608E-02 .788270269565E-02 .722061087326E-02 .641918867735E-02 .545894827979E-02 + .431801379800E-02 .297188497289E-02 .139319217287E-02 -.448553094467E-03 -.258720639694E-02 + -.506022962024E-02 -.790891121518E-02 -.111785546697E-01 -.149186192039E-01 -.191827929812E-01 + -.240289749478E-01 -.295191367867E-01 -.357190314954E-01 -.426977099021E-01 -.505268012579E-01 + -.592795092078E-01 -.690292703957E-01 -.798480203107E-01 -.918040104754E-01 -.104959123678E+00 + -.119365640755E+00 -.135052537078E+00 -.152079847668E+00 + ae wavefunction + -.536934453859E-05 -.554283679026E-05 -.572192904881E-05 -.590680169358E-05 -.609764089026E-05 + -.629463877488E-05 -.649799364359E-05 -.670791014832E-05 -.692459949849E-05 -.714827966909E-05 + -.737917561507E-05 -.761751949247E-05 -.786355088640E-05 -.811751704595E-05 -.837967312645E-05 + -.865028243916E-05 -.892961670862E-05 -.921795633789E-05 -.951559068196E-05 -.982281832946E-05 + -.101399473930E-04 -.104672958085E-04 -.108051916432E-04 -.111539734135E-04 -.115139904123E-04 + -.118856030458E-04 -.122691831813E-04 -.126651145043E-04 -.130737928877E-04 -.134956267708E-04 + -.139310375502E-04 -.143804599824E-04 -.148443425977E-04 -.153231481275E-04 -.158173539430E-04 + -.163274525071E-04 -.168539518402E-04 -.173973759985E-04 -.179582655672E-04 -.185371781670E-04 + -.191346889761E-04 -.197513912662E-04 -.203878969549E-04 -.210448371726E-04 -.217228628465E-04 + -.224226453000E-04 -.231448768698E-04 -.238902715395E-04 -.246595655907E-04 -.254535182727E-04 + -.262729124892E-04 -.271185555052E-04 -.279912796712E-04 -.288919431682E-04 -.298214307715E-04 + -.307806546346E-04 -.317705550946E-04 -.327921014965E-04 -.338462930403E-04 -.349341596486E-04 + -.360567628560E-04 -.372151967208E-04 -.384105887585E-04 -.396441008986E-04 -.409169304631E-04 + -.422303111689E-04 -.435855141531E-04 -.449838490212E-04 -.464266649193E-04 -.479153516296E-04 + -.494513406894E-04 -.510361065335E-04 -.526711676611E-04 -.543580878243E-04 -.560984772421E-04 + -.578939938353E-04 -.597463444862E-04 -.616572863188E-04 -.636286280026E-04 -.656622310770E-04 + -.677600112965E-04 -.699239399964E-04 -.721560454777E-04 -.744584144105E-04 -.768331932539E-04 + -.792825896932E-04 -.818088740907E-04 -.844143809508E-04 -.871015103953E-04 -.898727296496E-04 + -.927305745357E-04 -.956776509712E-04 -.987166364702E-04 -.101850281645E-03 -.105081411705E-03 + -.108412927949E-03 -.111847809248E-03 -.115389113513E-03 -.119039979150E-03 -.122803626483E-03 + -.126683359162E-03 -.130682565527E-03 -.134804719940E-03 -.139053384073E-03 -.143432208139E-03 + -.147944932068E-03 -.152595386619E-03 -.157387494410E-03 -.162325270874E-03 -.167412825110E-03 + -.172654360643E-03 -.178054176055E-03 -.183616665503E-03 -.189346319090E-03 -.195247723081E-03 + -.201325559962E-03 -.207584608305E-03 -.214029742439E-03 -.220665931907E-03 -.227498240686E-03 + -.234531826147E-03 -.241771937751E-03 -.249223915435E-03 -.256893187684E-03 -.264785269257E-03 + -.272905758533E-03 -.281260334465E-03 -.289854753099E-03 -.298694843630E-03 -.307786503967E-03 + -.317135695765E-03 -.326748438899E-03 -.336630805319E-03 -.346788912276E-03 -.357228914847E-03 + -.367956997739E-03 -.378979366308E-03 -.390302236747E-03 -.401931825406E-03 -.413874337166E-03 + -.426135952835E-03 -.438722815493E-03 -.451641015734E-03 -.464896575730E-03 -.478495432072E-03 + -.492443417301E-03 -.506746240072E-03 -.521409463873E-03 -.536438484230E-03 -.551838504315E-03 + -.567614508895E-03 -.583771236517E-03 -.600313149877E-03 -.617244404277E-03 -.634568814079E-03 + -.652289817096E-03 -.670410436812E-03 -.688933242371E-03 -.707860306229E-03 -.727193159410E-03 + -.746932744273E-03 -.767079364717E-03 -.787632633752E-03 -.808591418363E-03 -.829953781613E-03 + -.851716921913E-03 -.873877109413E-03 -.896429619485E-03 -.919368663237E-03 -.942687315069E-03 + -.966377437233E-03 -.990429601424E-03 -.101483300741E-02 -.103957539876E-02 -.106464297566E-02 + -.109002030507E-02 -.111569022805E-02 -.114163376471E-02 -.116783001666E-02 -.119425606737E-02 + -.122088688052E-02 -.124769519669E-02 -.127465142868E-02 -.130172355576E-02 -.132887701736E-02 + -.135607460649E-02 -.138327636352E-02 -.141043947082E-02 -.143751814883E-02 -.146446355430E-02 + -.149122368142E-02 -.151774326652E-02 -.154396369741E-02 -.156982292811E-02 -.159525539999E-02 + -.162019197054E-02 -.164455985064E-02 -.166828255181E-02 -.169127984444E-02 -.171346772851E-02 + -.173475841814E-02 -.175506034127E-02 -.177427815611E-02 -.179231278583E-02 -.180906147281E-02 + -.182441785436E-02 -.183827206105E-02 -.185051083943E-02 -.186101770044E-02 -.186967309504E-02 + -.187635461816E-02 -.188093724242E-02 -.188329358242E-02 -.188329419051E-02 -.188080788474E-02 + -.187570210923E-02 -.186784332698E-02 -.185709744495E-02 -.184333027040E-02 -.182640799755E-02 + -.180619772262E-02 -.178256798498E-02 -.175538933148E-02 -.172453490022E-02 -.168988101939E-02 + -.165130781581E-02 -.160869982728E-02 -.156194661142E-02 -.151094334343E-02 -.145559139361E-02 + -.139579887503E-02 -.133148115055E-02 -.126256128768E-02 -.118897044893E-02 -.111064820449E-02 + -.102754275349E-02 -.939611039582E-03 -.846818745856E-03 -.749140153709E-03 -.646557849671E-03 + -.539062263517E-03 -.426651020394E-03 -.309328089220E-03 -.187102709897E-03 -.599880838515E-04 + .720001825600E-04 .208845882540E-03 .350534246572E-03 .497054178393E-03 .648400632914E-03 + .804577064382E-03 .965597871782E-03 .113149078626E-02 .130229918063E-02 .147808432308E-02 + .165892762793E-02 .184493295336E-02 .203622894624E-02 .223297134696E-02 .243534507736E-02 + .264356588222E-02 .285788129106E-02 .307857069465E-02 .330594435780E-02 .354034119917E-02 + .378212515797E-02 .403167994363E-02 .428940193867E-02 .455569100166E-02 .483093890027E-02 + .511551509457E-02 .540974958539E-02 .571391254373E-02 .602819044082E-02 .635265840777E-02 + .668724856637E-02 .703171409088E-02 .738558878481E-02 .774814198662E-02 .811832865644E-02 + .849473454000E-02 .887551635833E-02 .925833702998E-02 .964029599629E-02 .100178547868E-01 + .103867580288E-01 .107419501671E-01 .110774882165E-01 .113864509092E-01 .116608446298E-01 + .118915065430E-01 .120680053329E-01 .121785399967E-01 .122098372057E-01 .121470479066E-01 + .119736441032E-01 .116713171792E-01 .112198796429E-01 .105971727185E-01 .977898257453E-02 + .873896786599E-02 .744860013681E-02 .587711563848E-02 .399147119709E-02 .175628797936E-02 + -.866239019038E-03 -.391647408054E-02 -.743746940754E-02 -.114749637066E-01 -.160771276901E-01 + -.212941062664E-01 -.271776042085E-01 -.337807161610E-01 -.411579574899E-01 -.493653243621E-01 + -.584602786172E-01 -.685016626504E-01 -.795495976261E-01 -.916654172796E-01 -.104911674326E+00 + -.119352243438E+00 -.135052537078E+00 -.152079847668E+00 + pseudo wavefunction + .291401328267E-08 .310660741021E-08 .331193054558E-08 .353082397944E-08 .376418460535E-08 + .401296859474E-08 .427819531469E-08 .456095150469E-08 .486239572944E-08 .518376312600E-08 + .552637046455E-08 .589162154379E-08 .628101294285E-08 .669614015334E-08 .713870411675E-08 + .761051819386E-08 .811351559483E-08 .864975730028E-08 .922144050602E-08 .983090762574E-08 + .104806558889E-07 .111733475729E-07 .119118209112E-07 .126991017233E-07 .135384158119E-07 + .144332021812E-07 .153871271269E-07 .164040992594E-07 .174882855184E-07 .186441282465E-07 + .198763633914E-07 .211900399110E-07 .225905404609E-07 .240836034492E-07 .256753465491E-07 + .273722917656E-07 .291813921584E-07 .311100603318E-07 .331661988066E-07 .353582324001E-07 + .376951427462E-07 .401865050959E-07 .428425275519E-07 .456740928944E-07 .486928031728E-07 + .519110272435E-07 .553419514499E-07 .589996336526E-07 .628990608296E-07 .670562104837E-07 + .714881161091E-07 .762129369843E-07 .812500325772E-07 .866200418695E-07 .923449679216E-07 + .984482680290E-07 .104954949835E-06 .111891673797E-06 .119286862426E-06 .127170816744E-06 + .135575840437E-06 .144536372221E-06 .154089126946E-06 .164273246033E-06 .175130457852E-06 + .186705248698E-06 .199045045072E-06 .212200408000E-06 .226225240208E-06 .241177006976E-06 + .257116971601E-06 .274110446410E-06 .292227060376E-06 .311541044413E-06 .332131535525E-06 + .354082901063E-06 .377485084413E-06 .402433973521E-06 .429031793789E-06 .457387526929E-06 + .487617357500E-06 .519845148962E-06 .554202951188E-06 .590831541524E-06 .629881001606E-06 + .671511332296E-06 .715893109266E-06 .763208181910E-06 .813650418444E-06 .867426500254E-06 + .924756768742E-06 .985876128147E-06 .105103500802E-05 .112050038933E-05 .119455689838E-05 + .127350797300E-05 .135767710584E-05 .144740916984E-05 .154307183128E-05 .164505705620E-05 + .175378271646E-05 .186969430185E-05 .199326674539E-05 .212500636934E-05 .226545295966E-05 + .241518197771E-05 .257480691811E-05 .274498182232E-05 .292640395847E-05 .311981667823E-05 + .332601246248E-05 .354583616833E-05 .378018849066E-05 .403002965244E-05 .429638333898E-05 + .458034089216E-05 .488306578181E-05 .520579837264E-05 .554986100620E-05 .591666341865E-05 + .630770851660E-05 .672459853464E-05 .716904159982E-05 .764285872985E-05 .814799129391E-05 + .868650896637E-05 .926061820619E-05 .987267129663E-05 .105251759823E-04 .112208057432E-04 + .119624107473E-04 .127530295272E-04 .135959014285E-04 .144944798800E-04 .154524465418E-04 + .164737263873E-04 .175625037821E-04 .187232396258E-04 .199606896253E-04 .212799237765E-04 + .226863471325E-04 .241857219440E-04 .257841912628E-04 .274883041044E-04 .293050422725E-04 + .312418489565E-04 .333066592171E-04 .355079324866E-04 .378546872150E-04 .403565378054E-04 + .430237339888E-04 .458672027984E-04 .488985933180E-04 .521303243834E-04 .555756354354E-04 + .592486407301E-04 .631643871285E-04 .673389157022E-04 .717893274054E-04 .765338530833E-04 + .815919281008E-04 .869842718977E-04 .927329727939E-04 .988615783914E-04 .105395191942E-03 + .112360575071E-03 .119786257283E-03 .127702652682E-03 .136142184401E-03 .145139417227E-03 + .154731198977E-03 .164956811193E-03 .175858129767E-03 .187479796156E-03 .199869399874E-03 + .213077673012E-03 .227158697560E-03 .242170126392E-03 .258173418790E-03 .275234091470E-03 + .293421986129E-03 .312811554584E-03 .333482162664E-03 .355518414075E-03 .379010495548E-03 + .404054544654E-03 .430753041771E-03 .459215227769E-03 .489557549103E-03 .521904132075E-03 + .556387288181E-03 .593148052553E-03 .632336757633E-03 .674113644380E-03 .718649513420E-03 + .766126418722E-03 .816738406546E-03 .870692302575E-03 .928208550323E-03 .989522104105E-03 + .105488338007E-02 .112455926899E-02 .119883421475E-02 .127801136268E-02 .136241378226E-02 + .145238576868E-02 .154829422848E-02 .165053015436E-02 .175951019478E-02 .187567832433E-02 + .199950762094E-02 .213150215675E-02 .227219900947E-02 .242217040155E-02 .258202597513E-02 + .275241521072E-02 .293402999840E-02 .312760737056E-02 .333393240565E-02 .355384131315E-02 + .378822470998E-02 .403803109964E-02 .430427056539E-02 .458801868954E-02 .489042071142E-02 + .521269593699E-02 .555614241356E-02 .592214188380E-02 .631216503324E-02 .672777704632E-02 + .717064348614E-02 .764253651345E-02 .814534146086E-02 .868106377808E-02 .925183636437E-02 + .985992730423E-02 .105077480221E-01 .111978618716E-01 .119329931739E-01 .127160367202E-01 + .135500677497E-01 .144383524159E-01 .153843587512E-01 .163917681354E-01 .174644872754E-01 + .186066606954E-01 .198226837362E-01 .211172160564E-01 .224951956216E-01 .239618531636E-01 + .255227270816E-01 .271836787499E-01 .289509081858E-01 .308309700202E-01 .328307896988E-01 + .349576798280E-01 .372193565604E-01 .396239558955E-01 .421800497506E-01 .448966616271E-01 + .477832816749E-01 .508498809210E-01 .541069243959E-01 .575653828518E-01 .612367427231E-01 + .651330139336E-01 .692667351008E-01 .736509756357E-01 .782993341711E-01 .832259326911E-01 + .884454056628E-01 .939728833996E-01 .998239688107E-01 .106014706613E+00 .112561544003E+00 + .119481281715E+00 .126791014304E+00 .134508058440E+00 .142649867935E+00 .151233934173E+00 + .160277670588E+00 .169798279848E+00 .179812602404E+00 .190336945154E+00 .201386889071E+00 + .212977074828E+00 .225120965693E+00 .237830587274E+00 .251116244142E+00 .264986213837E+00 + .279446419435E+00 .294500082568E+00 .310147359718E+00 .326384965564E+00 .343205788327E+00 + .360598503251E+00 .378547191656E+00 .397030974266E+00 .416023668739E+00 .435493482341E+00 + .455402751380E+00 .475707739190E+00 .496358503829E+00 .517298844985E+00 .538466336475E+00 + .559792445834E+00 .581202735295E+00 .602617128586E+00 .623950214870E+00 .645111544538E+00 + .666005851127E+00 .686533109442E+00 .706588312368E+00 .726060818994E+00 .744833096173E+00 + .762778647533E+00 .779758902369E+00 .795618827667E+00 .810181037401E+00 .823238213856E+00 + .834543737580E+00 .843795379495E+00 .850759109048E+00 + ae wavefunction + -.227639975927E-06 -.241553083020E-06 -.256238531448E-06 -.271743785200E-06 -.288119039224E-06 + -.305417391637E-06 -.323695026587E-06 -.343011408299E-06 -.363429487022E-06 -.385015917681E-06 + -.407841292027E-06 -.431980385198E-06 -.457512417605E-06 -.484521333149E-06 -.513096094823E-06 + -.543330998835E-06 -.575326008437E-06 -.609187108752E-06 -.645026683949E-06 -.682963918224E-06 + -.723125222119E-06 -.765644685826E-06 -.810664561235E-06 -.858335774579E-06 -.908818471664E-06 + -.962282597814E-06 -.101890851477E-05 -.107888765696E-05 -.114242322970E-05 -.120973095201E-05 + -.128103984706E-05 -.135659308322E-05 -.143664886909E-05 -.152148140599E-05 -.161138190170E-05 + -.170665964933E-05 -.180764317575E-05 -.191468146391E-05 -.202814525399E-05 -.214842842850E-05 + -.227594948673E-05 -.241115311447E-05 -.255451185510E-05 -.270652788873E-05 -.286773492636E-05 + -.303870022660E-05 -.322002674287E-05 -.341235540958E-05 -.361636757635E-05 -.383278759983E-05 + -.406238560344E-05 -.430598041586E-05 -.456444269986E-05 -.483869828392E-05 -.512973170970E-05 + -.543859000934E-05 -.576638672758E-05 -.611430620447E-05 -.648360813551E-05 -.687563242730E-05 + -.729180436770E-05 -.773364013080E-05 -.820275263846E-05 -.870085780133E-05 -.922978116380E-05 + -.979146497909E-05 -.103879757420E-04 -.110215122090E-04 -.116944139365E-04 -.124091703718E-04 + -.131684305304E-04 -.139750132996E-04 -.148319184057E-04 -.157423380908E-04 -.167096695415E-04 + -.177375281191E-04 -.188297614430E-04 -.199904643804E-04 -.212239950010E-04 -.225349915590E-04 + -.239283905651E-04 -.254094460215E-04 -.269837498904E-04 -.286572538768E-04 -.304362926072E-04 + -.323276082937E-04 -.343383769763E-04 -.364762364443E-04 -.387493159417E-04 -.411662677688E-04 + -.437363009004E-04 -.464692167451E-04 -.493754471826E-04 -.524660950179E-04 -.557529770072E-04 + -.592486696121E-04 -.629665576550E-04 -.669208860529E-04 -.711268148224E-04 -.756004775571E-04 + -.803590435918E-04 -.854207840798E-04 -.908051422247E-04 -.965328079196E-04 -.102625797063E-03 + -.109107535840E-03 -.116002950260E-03 -.123338561283E-03 -.131142585864E-03 -.139445044266E-03 + -.148277874034E-03 -.157675051007E-03 -.167672717809E-03 -.178309320241E-03 -.189625752061E-03 + -.201665508629E-03 -.214474849945E-03 -.228102973627E-03 -.242602198405E-03 -.258028158739E-03 + -.274440011195E-03 -.291900653263E-03 -.310476955313E-03 -.330240006432E-03 -.351265374934E-03 + -.373633384344E-03 -.397429405728E-03 -.422744167254E-03 -.449674081948E-03 -.478321594601E-03 + -.508795548883E-03 -.541211575720E-03 -.575692504072E-03 -.612368795275E-03 -.651379002161E-03 + -.692870254233E-03 -.736998770214E-03 -.783930399325E-03 -.833841192722E-03 -.886918006549E-03 + -.943359138131E-03 -.100337499686E-02 -.106718881141E-02 -.113503737486E-02 -.120717182952E-02 + -.128385849317E-02 -.136537972838E-02 -.145203485685E-02 -.154414112049E-02 -.164203469122E-02 + -.174607173112E-02 -.185662950504E-02 -.197410754735E-02 -.209892888474E-02 -.223154131687E-02 + -.237241875665E-02 -.252206263177E-02 -.268100334926E-02 -.284980182450E-02 -.302905107608E-02 + -.321937788792E-02 -.342144453961E-02 -.363595060592E-02 -.386363482621E-02 -.410527704411E-02 + -.436170021744E-02 -.463377249841E-02 -.492240938313E-02 -.522857592952E-02 -.555328904201E-02 + -.589761982068E-02 -.626269597230E-02 -.664970427950E-02 -.705989312401E-02 -.749457505857E-02 + -.795512942174E-02 -.844300498806E-02 -.895972264571E-02 -.950687809174E-02 -.100861445343E-01 + -.106992753895E-01 -.113481069581E-01 -.120345610684E-01 -.127606476645E-01 -.135284673243E-01 + -.143402136813E-01 -.151981757303E-01 -.161047399864E-01 -.170623924716E-01 -.180737204949E-01 + -.191414141916E-01 -.202682677838E-01 -.214571805211E-01 -.227111572555E-01 -.240333086037E-01 + -.254268506438E-01 -.268951040903E-01 -.284414928881E-01 -.300695421604E-01 -.317828754443E-01 + -.335852111384E-01 -.354803580901E-01 -.374722102372E-01 -.395647402230E-01 -.417619918931E-01 + -.440680715826E-01 -.464871380971E-01 -.490233912878E-01 -.516810591191E-01 -.544643831232E-01 + -.573776021360E-01 -.604249342075E-01 -.636105565785E-01 -.669385836182E-01 -.704130426186E-01 + -.740378473440E-01 -.778167692409E-01 -.817534062181E-01 -.858511489161E-01 -.901131443956E-01 + -.945422571848E-01 -.991410276437E-01 -.103911627616E+00 -.108855813361E+00 -.113974875783E+00 + -.119269587988E+00 -.124740150247E+00 -.130386132443E+00 -.136206414151E+00 -.142199122499E+00 + -.148361568035E+00 -.154690178833E+00 -.161180433171E+00 -.167826791131E+00 -.174622625584E+00 + -.181560153093E+00 -.188630365378E+00 -.195822962130E+00 -.203126286096E+00 -.210527261502E+00 + -.218011337039E+00 -.225562434682E+00 -.233162905552E+00 -.240793493705E+00 -.248433308057E+00 + -.256059801489E+00 -.263648754700E+00 -.271174260698E+00 -.278608704786E+00 -.285922735197E+00 + -.293085222036E+00 -.300063207002E+00 -.306821852678E+00 -.313324406286E+00 -.319532196442E+00 + -.325404680492E+00 -.330899553158E+00 -.335972915728E+00 -.340579493099E+00 -.344672879444E+00 + -.348205795003E+00 -.351130344271E+00 -.353398274261E+00 -.354961236692E+00 -.355771058893E+00 + -.355780026498E+00 -.354941178483E+00 -.353208612980E+00 -.350537801067E+00 -.346885905329E+00 + -.342212100159E+00 -.336477891180E+00 -.329647431712E+00 -.321687834653E+00 -.312569478552E+00 + -.302266306889E+00 -.290756119819E+00 -.278020857663E+00 -.264046875488E+00 -.248825207961E+00 + -.232351823470E+00 -.214627866128E+00 -.195659883790E+00 -.175460039600E+00 -.154046303832E+00 + -.131442622052E+00 -.107679054871E+00 -.827918840025E-01 -.568236791368E-01 -.298233205159E-01 + -.184597323164E-02 .270469885701E-01 .567881062803E-01 .873040050703E-01 .118515596879E+00 + .150338306883E+00 .182682313261E+00 .215452796875E+00 .248550212706E+00 .281870620849E+00 + .315306154149E+00 .348745752676E+00 .382076353569E+00 .415184746117E+00 .447960165155E+00 + .480297179596E+00 .512097397715E+00 .543267510319E+00 .573711993632E+00 .603322782157E+00 + .631972546868E+00 .659516791165E+00 .685802866227E+00 .710679504466E+00 .734002703277E+00 + .755638014234E+00 .775461066058E+00 .793357766636E+00 .809224792331E+00 .822970439701E+00 + .834515700400E+00 .843795379495E+00 .850759109048E+00 + pseudo wavefunction + .188259325656E-09 .200701836025E-09 .213966701744E-09 .228108274249E-09 .243184497194E-09 + .259257143867E-09 .276392070301E-09 .294659485112E-09 .314134237172E-09 .334896122293E-09 + .357030210184E-09 .380627193015E-09 .405783757020E-09 .432602978655E-09 .461194746947E-09 + .491676213752E-09 .524172273773E-09 .558816076302E-09 .595749570786E-09 .635124088452E-09 + .677100962369E-09 .721852188493E-09 .769561130406E-09 .820423270627E-09 .874647011580E-09 + .932454529506E-09 .994082684803E-09 .105978399254E-08 .112982765710E-08 .120450067525E-08 + .128410901202E-08 .136897885444E-08 .145945794800E-08 .155591702150E-08 .165875130612E-08 + .176838215480E-08 .188525876868E-08 .200986003770E-08 .214269650275E-08 .228431244760E-08 + .243528812901E-08 .259624215430E-08 .276783401601E-08 .295076679410E-08 .314579003675E-08 + .335370283154E-08 .357535707967E-08 .381166098646E-08 .406358278269E-08 .433215469178E-08 + .461847715923E-08 .492372336155E-08 .524914401326E-08 .559607249152E-08 .596593029951E-08 + .636023289086E-08 .678059587908E-08 .722874165731E-08 .770650645568E-08 .821584786499E-08 + .875885285776E-08 .933774633931E-08 .995490026410E-08 .106128433544E-07 .113142714617E-07 + .120620586123E-07 .128592687834E-07 .137091684574E-07 .146152400060E-07 .155811959585E-07 + .166109942135E-07 .177088542561E-07 .188792744464E-07 .201270504508E-07 .214572948920E-07 + .228754582969E-07 .243873514295E-07 .259991690995E-07 .277175155448E-07 .295494314911E-07 + .315024230005E-07 .335844922259E-07 .358041701992E-07 .381705517848E-07 .406933329453E-07 + .433828504679E-07 .462501243186E-07 .493069027933E-07 .525657106550E-07 .560399004512E-07 + .597437072231E-07 .636923068306E-07 .679018781323E-07 .723896692744E-07 .771740683610E-07 + .822746787944E-07 .877123995959E-07 .935095110327E-07 .996897659063E-07 .106278486872E-06 + .113302670191E-06 .120791096338E-06 .128774447922E-06 .137285435397E-06 .146358931079E-06 + .156032112024E-06 .166344612347E-06 .177338685603E-06 .189059377909E-06 .201554712490E-06 + .214875886441E-06 .229077480474E-06 .244217682537E-06 .260358526204E-06 .277566144822E-06 + .295911042451E-06 .315468382706E-06 .336318296692E-06 .358546211276E-06 .382243199059E-06 + .407506351473E-06 .434439176528E-06 .463152022837E-06 .493762531665E-06 .526396118840E-06 + .561186488509E-06 .598276180831E-06 .637817155864E-06 .679971416021E-06 .724911669647E-06 + .772822038440E-06 .823898811601E-06 .878351249803E-06 .936402442264E-06 .998290220443E-06 + .106426813207E-05 .113460647955E-05 .120959342687E-05 .128953617969E-05 .137476224337E-05 + .146562076397E-05 .156248395791E-05 .166574863599E-05 .177583782802E-05 .189320251473E-05 + .201832347399E-05 .215171324889E-05 .229391824580E-05 .244552097081E-05 .260714241377E-05 + .277944458969E-05 .296313324782E-05 .315896075937E-05 .336772919581E-05 .359029361017E-05 + .382756553466E-05 .408051670906E-05 .435018305473E-05 .463766891071E-05 .494415154892E-05 + .527088598687E-05 .561921011746E-05 .599055017661E-05 .638642657091E-05 .680846008894E-05 + .725837852142E-05 .773802371682E-05 .824935910117E-05 .879447769232E-05 .937561064095E-05 + .999513633285E-05 .106555900890E-04 .113596745027E-04 .121102704547E-04 .129104488515E-04 + .137634831326E-04 .146728625977E-04 .156423066068E-04 .166757797093E-04 .177775077628E-04 + .189519951060E-04 .202040428520E-04 .215387683771E-04 .229616260786E-04 .244784294863E-04 + .260953748122E-04 .278190660317E-04 .296565415935E-04 .316153028623E-04 .337033444036E-04 + .359291862279E-04 .383019081186E-04 .408311861731E-04 .435273316971E-04 .464013325996E-04 + .494648974426E-04 .527305023115E-04 .562114406801E-04 .599218764523E-04 .638769003772E-04 + .680925900398E-04 .725860736440E-04 .773755978153E-04 .824805996618E-04 .879217833433E-04 + .937212014151E-04 .999023412187E-04 .106490216612E-03 .113511465340E-03 .120994452360E-03 + .128969379448E-03 .137468401441E-03 .146525749442E-03 .156177861381E-03 .166463520291E-03 + .177424000698E-03 .189103223502E-03 .201547919779E-03 .214807803882E-03 .228935756279E-03 + .243988016516E-03 .260024386720E-03 .277108446041E-03 .295307776404E-03 .314694199941E-03 + .335344028437E-03 .357338325072E-03 .380763178723E-03 .405709990999E-03 .432275776138E-03 + .460563473773E-03 .490682274495E-03 .522747957989E-03 .556883243367E-03 .593218151151E-03 + .631890376108E-03 .673045669922E-03 .716838232348E-03 .763431109165E-03 .812996594826E-03 + .865716637226E-03 .921783241464E-03 .981398868826E-03 .104477682649E-02 .111214164262E-02 + .118372942048E-02 .125978816423E-02 .134057806758E-02 .142637175521E-02 .151745446512E-02 + .161412415806E-02 .171669153832E-02 .182547996737E-02 .194082524924E-02 .206307526326E-02 + .219258941639E-02 .232973788293E-02 .247490059520E-02 .262846594337E-02 .279082913687E-02 + .296239017320E-02 .314355135267E-02 .333471426917E-02 .353627619812E-02 .374862579194E-02 + .397213798232E-02 .420716797543E-02 .445404421192E-02 .471306014793E-02 .498446469549E-02 + .526845114184E-02 .556514434534E-02 .587458598281E-02 .619671759756E-02 .653136116924E-02 + .687819689722E-02 .723673785601E-02 .760630114682E-02 .798597513191E-02 .837458229890E-02 + .877063726069E-02 .917229935323E-02 .957731924895E-02 .998297895804E-02 .103860245445E-01 + .107825908400E-01 .111681173956E-01 .115372548753E-01 .118837610617E-01 .122003856210E-01 + .124787427655E-01 .127091709518E-01 .128805787801E-01 .129802763102E-01 .129937910905E-01 + .129046683256E-01 .126942547801E-01 .123414662634E-01 .118225388591E-01 .111107644916E-01 + .101762119689E-01 .898543534943E-02 .750117238625E-02 .568203694441E-02 .348221074715E-02 + .851141640091E-03 -.226674211916E-02 -.593228912367E-02 -.102118375499E-01 -.151773626963E-01 + -.209065329490E-01 -.274826407059E-01 -.349943660481E-01 -.435353202661E-01 -.532033034353E-01 + -.640991948492E-01 -.763253771158E-01 -.899835741667E-01 -.105171960694E+00 -.121981376528E+00 + -.140490455867E+00 -.160752140242E+00 -.182838197398E+00 + ae wavefunction + .329908017899E-08 .350070879538E-08 .371353032623E-08 .393823260492E-08 .417554304096E-08 + .442623111551E-08 .469111103129E-08 .497104452448E-08 .526694384922E-08 .557977494597E-08 + .591056080576E-08 .626038504303E-08 .663039569071E-08 .702180923184E-08 .743591488320E-08 + .787407914718E-08 .833775064943E-08 .882846528060E-08 .934785166202E-08 .989763695626E-08 + .104796530450E-07 .110958430977E-07 .117482685572E-07 .124391165681E-07 .131707078780E-07 + .139455052412E-07 .147661223583E-07 .156353333861E-07 .165560830548E-07 .175314974331E-07 + .185648953814E-07 .196598007399E-07 .208199552982E-07 .220493325979E-07 .233521526224E-07 + .247328974311E-07 .261963278005E-07 .277475009372E-07 .293917893326E-07 .311349008342E-07 + .329829000119E-07 .349422309040E-07 .370197412336E-07 .392227081895E-07 .415588658745E-07 + .440364345292E-07 .466641516475E-07 .494513051048E-07 .524077684326E-07 .555440383768E-07 + .588712748880E-07 .624013437039E-07 .661468616893E-07 .701212451142E-07 .743387610605E-07 + .788145821596E-07 .835648448764E-07 .886067115712E-07 .939584365812E-07 .996394365846E-07 + .105670365522E-06 .112073194371E-06 .118871296086E-06 .126089536039E-06 .133754368318E-06 + .141893938246E-06 .150538191549E-06 .159718990577E-06 .169470238034E-06 .179828008724E-06 + .190830689788E-06 .202519130018E-06 .214936798801E-06 .228129955327E-06 .242147828705E-06 + .257042809702E-06 .272870654832E-06 .289690703594E-06 .307566109690E-06 .326564087128E-06 + .346756172139E-06 .368218501929E-06 .391032111332E-06 .415283248495E-06 .441063710808E-06 + .468471202359E-06 .497609714270E-06 .528589929370E-06 .561529652727E-06 .596554269675E-06 + .633797233063E-06 .673400581564E-06 .715515490979E-06 .760302860615E-06 .807933936922E-06 + .858590976703E-06 .912467952376E-06 .969771301889E-06 .103072072606E-05 .109555003626E-05 + .116450805559E-05 .123785957678E-05 .131588638035E-05 .139888831671E-05 .148718445608E-05 + .158111431043E-05 .168103913172E-05 .178734329115E-05 .190043574433E-05 .202075158739E-05 + .214875370975E-05 .228493454907E-05 .242981795469E-05 .258396116581E-05 .274795691142E-05 + .292243563898E-05 .310806787948E-05 .330556675685E-05 .351569065019E-05 .373924601751E-05 + .397709039049E-05 .423013554987E-05 .449935089198E-05 .478576699710E-05 .509047941113E-05 + .541465265242E-05 .575952445644E-05 .612641027142E-05 .651670801861E-05 .693190313178E-05 + .737357389105E-05 .784339706665E-05 .834315388946E-05 .887473636521E-05 .944015395058E-05 + .100415406097E-04 .106811622710E-04 .113614247036E-04 .120848818358E-04 .128542445362E-04 + .136723898809E-04 .145423709291E-04 .154674270325E-04 .164509947032E-04 .174967190638E-04 + .186084659092E-04 .197903344043E-04 .210466704466E-04 .223820807216E-04 .238014474792E-04 + .253099440608E-04 .269130512058E-04 .286165741680E-04 .304266606703E-04 .323498197291E-04 + .343929413762E-04 .365633173085E-04 .388686624936E-04 .413171377592E-04 .439173733939E-04 + .466784937828E-04 .496101431055E-04 .527225121145E-04 .560263660175E-04 .595330734786E-04 + .632546367534E-04 .672037229692E-04 .713936965562E-04 .758386528320E-04 .805534527382E-04 + .855537587174E-04 .908560717189E-04 .964777693090E-04 .102437144857E-03 .108753447759E-03 + .115446924650E-03 .122538861549E-03 .130051626865E-03 .138008715186E-03 .146434791756E-03 + .155355737528E-03 .164798694679E-03 .174792112435E-03 .185365793069E-03 .196550937879E-03 + .208380192963E-03 .220887694586E-03 .234109113894E-03 .248081700728E-03 .262844326268E-03 + .278437524200E-03 .294903530092E-03 .312286318645E-03 .330631638438E-03 .349987043795E-03 + .370401923370E-03 .391927525004E-03 .414616976437E-03 .438525301396E-03 .463709430588E-03 + .490228207127E-03 .518142385893E-03 .547514626344E-03 .578409478292E-03 .610893360173E-03 + .645034529359E-03 .680903044093E-03 .718570716657E-03 .758111057440E-03 .799599209646E-03 + .843111874437E-03 .888727226421E-03 .936524819495E-03 .986585483195E-03 .103899120984E-02 + .109382503292E-02 .115117089748E-02 .121111352320E-02 .127373826159E-02 .133913094834E-02 + .140737775294E-02 .147856502718E-02 .155277915525E-02 .163010640797E-02 .171063280434E-02 + .179444398399E-02 .188162509437E-02 .197226069717E-02 .206643469870E-02 .216423030948E-02 + .226573003870E-02 .237101572979E-02 .248016864360E-02 .259326959640E-02 .271039916068E-02 + .283163793710E-02 .295706690745E-02 .308676787920E-02 .322082403378E-02 .335932059220E-02 + .350234561239E-02 .364999093291E-02 .380235327479E-02 .395953550720E-02 .412164806889E-02 + .428881051644E-02 .446115314045E-02 .463881855679E-02 .482196315214E-02 .501075825528E-02 + .520539093344E-02 .540606438254E-02 .561299798267E-02 .582642719909E-02 .604660358714E-02 + .627379516452E-02 .650828731395E-02 .675038417942E-02 .700041028844E-02 .725871197647E-02 + .752565817955E-02 .780164027316E-02 .808707077981E-02 .838238086423E-02 .868801655628E-02 + .900443360736E-02 .933209082854E-02 .967144170169E-02 .100229240120E-01 .103869472209E-01 + .107638772809E-01 .111540185848E-01 .115575927342E-01 .119747138083E-01 .124053598104E-01 + .128493399678E-01 .133062575600E-01 .137754679559E-01 .142560315452E-01 .147466612667E-01 + .152456644480E-01 .157508787005E-01 .162596016357E-01 .167685142012E-01 .172735974648E-01 + .177700427009E-01 .182521546525E-01 .187132478523E-01 .191455358726E-01 .195400133505E-01 + .198863305955E-01 .201726605474E-01 .203855578566E-01 .205098099183E-01 .205282799298E-01 + .204217424344E-01 .201687124905E-01 .197452704861E-01 .191248856466E-01 .182782422416E-01 + .171730730409E-01 .157740040676E-01 .140424119477E-01 .119362882257E-01 .941009223694E-02 + .641455956391E-02 .289643672970E-02 -.120182972349E-02 -.594230845433E-02 -.113915061558E-01 + -.176199584845E-01 -.247017208792E-01 -.327140327375E-01 -.417371826148E-01 -.518544026197E-01 + -.631516436073E-01 -.757171941354E-01 -.896411710603E-01 -.105014918512E+00 -.121930338317E+00 + -.140479159189E+00 -.160752140242E+00 -.182838197398E+00 + End of Dataset diff --git a/atomate/vasp/workflows/base/aimd.py b/atomate/vasp/workflows/base/aimd.py new file mode 100644 index 000000000..096aea5e6 --- /dev/null +++ b/atomate/vasp/workflows/base/aimd.py @@ -0,0 +1,162 @@ +import math +import warnings +from copy import deepcopy +from typing import Dict, List, Optional, Union +import numpy as np +from monty.serialization import loadfn, dumpfn + +from atomate.utils.utils import get_logger +from atomate.vasp.config import DB_FILE, VASP_CMD +from atomate.vasp.firetasks import pass_vasp_result +from atomate.vasp.analysis.lattice_dynamics import ( + FIT_METHOD, + MESH_DENSITY, +) +from atomate.vasp.fireworks.core import TransmuterFW, OptimizeFW +from atomate.vasp.fireworks.aimd import ARCMDFW, CollectMDSegmentsFW +from atomate.common.powerups import add_additional_fields_to_taskdocs +from fireworks import Workflow +from pymatgen.core.structure import Structure +from pymatgen.io.vasp.sets import ARCMDSet, VaspInputSet +from pymatgen.symmetry.analyzer import SpacegroupAnalyzer +from pymatgen.transformations.advanced_transformations import ( + CubicSupercellTransformation, +) + +__author__ = "Junsoo Park" +__email__ = "junsoo.park@nasa.gov" +__date__ = "December 2023" + +logger = get_logger(__name__) + +vasp_to_db_params = { + "store_volumetric_data": tuple(), + "vasp_drone_params": {"parse_bader": False, "parse_locpot": False} +} + +_DEFAULT_SETTINGS = {"VASP_CMD": VASP_CMD, "DB_FILE": DB_FILE} +_WF_VERSION = 0.1 + + +def get_aimd_wf( + structure: Structure, + common_settings: Dict = None, + ensemble='NVT', + start_temp=start_temp, + end_temp=end_temp, + simulation_time = simulation_time, + time_step = time_step, + copy_vasp_outputs = True, + supercell_matrix_kwargs: Optional[dict] = None +): + """ + This workflow will perform AIMD on VASP, + + Args: + structure: Initial structure. + common_settings: Common settings dict. Supports "VASP_CMD", "DB_FILE", + and "user_incar_settings" keys. + vasp_input_set: Vasp input set for perturbed structure calculations. + copy_vasp_outputs: Whether or not to copy previous vasp outputs. + supercell_matrix_kwargs: Options that control the size of the supercell. + Will be passed directly to CubicSupercellTransformation in + pymatgen.transformations.advanced_transformations. Note, a diagonal + supercell is required to calculate lattice thermal conductivity. + ensemble: NVT, NPT, etc. + """ + + parent_structure = structure.as_dict() + supercell_matrix_kwargs = supercell_matrix_kwargs or {} + common_settings = _get_common_settings(common_settings) + db_file = common_settings["DB_FILE"] + + logger.debug('Transforming supercell!') + logger.debug('KWARGS: \n {}'.format(supercell_matrix_kwargs)) + st = CubicSupercellTransformation(**supercell_matrix_kwargs) + supercell = st.apply_transformation(structure) + supercell_matrix = st.transformation_matrix + logger.debug('SUPERCELL MATRIX: \n {}'.format(supercell_matrix)) + + nsteps_total = ceil(simulation_time/time_step) + nsteps_each = 500 + nfws = ceil(nsteps_total/nsteps_each) + parents=None + + vasp_input_set = ARCMDSet( + structure=supercell, + ensemble=ensemble, + start_temp=start_temp, + end_temp=end_temp, + nsteps=nsteps_each, + time_step=time_step, + reciprocal_density=1, + small_gap_multiply=None + ) + for ifw in range(nfws): + if ifw>0: + vasp_input_set.update() + parents = aimd_wf.fws[-1] + start_temp = end_temp + + aimd_fw = ARCMDFW( start_structure, + start_temp, + end_temp, + nsteps_fw, + name="AIMD_segment_{}".format(ifw+1), + vasp_input_set=vasp_input_set, + vasp_cmd=VASP_CMD, + wall_time=1080000, + db_file=DB_FILE, + parents=parents, + copy_vasp_outputs=copy_vasp_outputs, + override_default_vasp_params=None, + **kwargs,) + pass_task = pass_vasp_result( + pass_dict={ + "parent_structure": parent_structure, + "supercell_matrix": supercell_matrix, + "forces": ">>output.ionic_steps.:-1.forces", + "stress": ">>output.ionic_steps.:-1.stress", + "configurations": ">>output.ionic_steps.:-1.structure", + "final_configuration": ">>output.ionic_steps.-1.structure" + }, + mod_spec_cmd="_push", + mod_spec_key="aimd", + ) + aimd_fw.tasks.append(pass_task) + if ifw==0: + wf = Workflow.from_Firework(aimd_fw) + else: + wf.append_wf(Workflow.from_Firework(aimd_fw), wf.fws[-1].fw_id) + + collect_fw = CollectMDSegmentsFW( + db_file=db_file, + parents=wf.fws[-nfws:] + ) + wf.append_wf( + Workflow.from_Firework(collect_fw), [fw.fw_id for fw in wf.fws[-nfws:]] + ) + + # Add workflow metadata to all relevant *ToDb tasks. + wf_meta = {"wf_name": "AIMDWF", "wf_version": _WF_VERSION} + for task_name in ["VaspToDb"]: + wf = add_additional_fields_to_taskdocs( + wf, {"wf_meta": wf_meta}, task_name_constraint=task_name + ) + + return wf + + +def _get_common_settings(common_settings: Optional[Dict]): + common_settings = common_settings or {} + for k, v in _DEFAULT_SETTINGS.items(): + if k not in common_settings: + common_settings[k] = v + + user_incar_settings = deepcopy(_aimd_user_incar_settings) + user_incar_settings.update(common_settings.get("user_incar_settings", {})) + common_settings["user_incar_settings"] = user_incar_settings + + return common_settings + + diff --git a/atomate/vasp/workflows/base/lattice_dynamics.py b/atomate/vasp/workflows/base/lattice_dynamics.py new file mode 100644 index 000000000..1aa1568a4 --- /dev/null +++ b/atomate/vasp/workflows/base/lattice_dynamics.py @@ -0,0 +1,460 @@ +import math +import warnings +from copy import deepcopy +from typing import Dict, List, Optional, Union + +import numpy as np +from monty.serialization import loadfn, dumpfn + +from atomate.utils.utils import get_logger +from atomate.vasp.config import DB_FILE, SHENGBTE_CMD, VASP_CMD +from atomate.vasp.firetasks import pass_vasp_result +from atomate.vasp.analysis.lattice_dynamics import ( + FIT_METHOD, + MESH_DENSITY, + IMAGINARY_TOL, + T_QHA, + T_KLAT, + T_RENORM, + RENORM_METHOD, + RENORM_NCONFIG, + RENORM_MAX_ITER, + RENORM_CONV_THRESH, +) +from atomate.vasp.fireworks.core import TransmuterFW, OptimizeFW +from atomate.vasp.fireworks.lattice_dynamics import ( + FitForceConstantsFW, + LatticeThermalConductivityFW, + RenormalizationFW, +) +from atomate.common.powerups import add_additional_fields_to_taskdocs +from fireworks import Workflow +from pymatgen.core.structure import Structure +from pymatgen.io.vasp.sets import MPStaticSet, VaspInputSet +from pymatgen.symmetry.analyzer import SpacegroupAnalyzer +from pymatgen.transformations.advanced_transformations import ( + CubicSupercellTransformation, +) + +__author__ = "Alex Ganose, Rees Chang, Junsoo Park" +__email__ = "aganose@lbl.gov, rc564@cornell.edu, jsyony37@lbl.gov" +__date__ = "February 2020" + +logger = get_logger(__name__) + +_static_user_incar_settings = { + "PREC": "Accurate", + "ADDGRID": True, + "LCHARG": False, + "ENCUT": 600, + "ISMEAR": 0, + "SIGMA": 0.1, + "ISPIN": 2, + "EDIFF": 1e-7, + "LAECHG": False, + "LREAL": False, + "LASPH": True, + "LVTOT": False, + "LVHAR": False, +} + +vasp_to_db_params = { + "store_volumetric_data": tuple(), + "vasp_drone_params": {"parse_bader": False, "parse_locpot": False} +} + +_DEFAULT_SETTINGS = {"VASP_CMD": VASP_CMD, "DB_FILE": DB_FILE} +_WF_VERSION = 0.1 + + +def get_lattice_dynamics_wf( + structure: Structure, + fit_method:str = FIT_METHOD, + disp_cut: float = None, + bulk_modulus: float = None, + common_settings: Dict = None, + vasp_input_set: Optional[VaspInputSet] = None, + copy_vasp_outputs: bool = False, + supercell_matrix_kwargs: Optional[dict] = None, + num_supercell_kwargs: Optional[dict] = None, + perturbed_structure_kwargs: Optional[dict] = None, + calculate_lattice_thermal_conductivity: bool = True, + thermal_conductivity_temperature: Union[float, Dict] = T_KLAT, + renormalize: bool = False, + renormalize_temperature: Union[float, List, Dict] = T_RENORM, + renormalize_method: str = RENORM_METHOD, + renormalize_nconfig: int = RENORM_NCONFIG, + renormalize_conv_thresh: float = RENORM_CONV_THRESH, + renormalize_max_iter: int = RENORM_MAX_ITER, + renormalize_thermal_expansion_iter: bool = False, + mesh_density: float = MESH_DENSITY, + shengbte_cmd: str = SHENGBTE_CMD, + shengbte_fworker: Optional[str] = None, +): + """ + This workflow will calculate interatomic force constants and vibrational + properties using the hiPhive package. + + A summary of the workflow is as follows: + + 1. Calculate a supercell transformation matrix that brings the + structure as close as cubic as possible, with all lattice lengths + greater than 5 nearest neighbor distances. + 2. Perturb the atomic sites for each supercell using a Monte Carlo + rattle procedure. The atoms are perturbed roughly according to a + normal deviation. A number of standard deviation perturbation distances + are included. Multiple supercells may be generated for each perturbation + distance. + 3. Run static VASP calculations on each perturbed supercell to calculate + atomic forces. + 4. Aggregate the forces and conduct the fit atomic force constants using + the minimization schemes in hiPhive. + 5. Output the interatomic force constants, and phonon band structure and + density of states to the database. + 6. Optional: Perform phonon renormalization at finite temperature - useful + when unstable modes exist + 7. Optional: Solve the lattice thermal conductivity using ShengBTE and + output to the database. + + Args: + structure: Initial structure. + disp_cut: determines the mean displacement of perturbed + structure to be included in harmonic (<) or anharmonic (>) fitting + bulk_modulus: bulk modulus in GPa, necessary for thermal expansion + common_settings: Common settings dict. Supports "VASP_CMD", "DB_FILE", + and "user_incar_settings" keys. + vasp_input_set: Vasp input set for perturbed structure calculations. + copy_vasp_outputs: Whether or not to copy previous vasp outputs. + supercell_matrix_kwargs: Options that control the size of the supercell. + Will be passed directly to CubicSupercellTransformation in + pymatgen.transformations.advanced_transformations. Note, a diagonal + supercell is required to calculate lattice thermal conductivity. + num_supercell_kwargs: Options that control the number of supercells + generated per perturbation standard deviation distance. See the + docstring of ``get_num_supercells`` for more details. + perturbed_structure_kwargs: Options that control the number of + and magnitude of atomic displacements. Currently, the options are + "rattle_std", "n_configs_per_std", and "min_nn_scale". See the + docstring for ``get_perturbed_structure_wf`` for more details. + calculate_lattice_thermal_conductivity: If True and force constant + fitting does not return imaginary modes, then use ShengBTE to + calculate the lattice thermal conductivity. + renormalize: If True and force constant fitting returns imaginary modes, + then use HiPhiveRenorm to obtain phonons and force constants at + finite temperatures, which at some temperatures are hopefully real. + thermal_conductivity_temperature: The temperature at which to calculate + lattice thermal conductivity for. Can be given as a single float, or + a dictionary with the keys "min", "max", "step". + renormalize_temperature: The temperature at which to perform phonon + renormalization. Can be given as a single float, list, or a dictionary + with the keys "min", "max", "step". + shengbte_cmd: Command to run ShengBTE. Supports env_chk. + shengbte_fworker: If None, the ShengBTE firework's fworker will be set + to all the previous fireworks' fworker. If str, the ShengBTE + firework's fworker will be set to shengbte_fworker. + """ + supercell_matrix_kwargs = supercell_matrix_kwargs or {} + num_supercell_kwargs = num_supercell_kwargs or {} + perturbed_structure_kwargs = perturbed_structure_kwargs or {} + common_settings = _get_common_settings(common_settings) + db_file = common_settings["DB_FILE"] + + + if calculate_lattice_thermal_conductivity: + if supercell_matrix_kwargs.get("force_diagonal", False): + warnings.warn( + "Diagonal transformation required to calculate lattice thermal " + "conductivity using ShengBTE. Forcing diagonal matrix." + ) + supercell_matrix_kwargs["force_diagonal"] = True + + logger.debug('Transforming supercell!') + logger.debug('KWARGS: \n {}'.format(supercell_matrix_kwargs)) + st = CubicSupercellTransformation(**supercell_matrix_kwargs) + supercell = st.apply_transformation(structure) + supercell_matrix = st.transformation_matrix + logger.debug('SUPERCELL MATRIX: \n {}'.format(supercell_matrix)) + + if "n_configs_per_std" not in perturbed_structure_kwargs: + n_supercells = get_num_supercells(supercell, **num_supercell_kwargs) + perturbed_structure_kwargs["n_configs_per_std"] = n_supercells + + # 1. Perturb supercell and calculate forces + wf = get_perturbed_structure_wf( + structure, + supercell_matrix=supercell_matrix, + vasp_input_set=vasp_input_set, + common_settings=common_settings, + copy_vasp_outputs=copy_vasp_outputs, + pass_forces=True, + **perturbed_structure_kwargs, + ) + + # 2. Fit interatomic force constants from perturbed structures + allow_fizzled = {"_allow_fizzled_parents": True} + fw_fit_force_constant = FitForceConstantsFW( + db_file=db_file, + spec=allow_fizzled, + fit_method=fit_method, + disp_cut=disp_cut, + bulk_modulus=bulk_modulus, + temperature_qha=T_QHA, + mesh_density=mesh_density, + imaginary_tol=IMAGINARY_TOL, + ) + wf.append_wf(Workflow.from_Firework(fw_fit_force_constant), wf.leaf_fw_ids) + fitting_fw_id = wf.fws[-1].fw_id + + # 3. Renormalization FW (pass_inputs like bulk modulus) + if renormalize: + for temperature in renormalize_temperature: + nconfig = renormalize_nconfig*(1+temperature//100) + fw_renormalization = RenormalizationFW( + db_file=db_file, + temperature=temperature, + renorm_method=renormalize_method, + nconfig=nconfig, + conv_thresh=renormalize_conv_thresh, + max_iter=renormalize_max_iter, + renorm_TE_iter=renormalize_thermal_expansion_iter, + bulk_modulus=bulk_modulus, + mesh_density=mesh_density, + ) + wf.append_wf( + Workflow.from_Firework(fw_renormalization), [fitting_fw_id] + ) + + # 4. Lattice thermal conductivity calculation + if calculate_lattice_thermal_conductivity: + if renormalize: + temperatures = renormalize_temperature + else: + temperatures = thermal_conductivity_temperature + # Because of the way ShengBTE works, a temperature array that is not + # evenly spaced out (T_step) requires submission for each temperature + if not renormalize: + if type(temperatures)==dict: + pass + elif type(temperatures) in [list,np.ndarray]: + assert all(np.diff(temperatures)==np.diff(temperatures)[0]) + fw_lattice_conductivity = LatticeThermalConductivityFW( + db_file=db_file, + shengbte_cmd=shengbte_cmd, + renormalized=renormalize, + temperature=temperatures + ) + if shengbte_fworker: + fw_lattice_conductivity.spec["_fworker"] = shengbte_fworker + wf.append_wf( + Workflow.from_Firework(fw_lattice_conductivity), [fitting_fw_id] + ) + else: + push = 1 + for t,T in enumerate(temperatures): + if T == 0: + push = 0 + continue + fw_lattice_conductivity = LatticeThermalConductivityFW( + db_file=db_file, + shengbte_cmd=shengbte_cmd, + renormalized=renormalize, + temperature=T + ) + if shengbte_fworker: + fw_lattice_conductivity.spec["_fworker"] = shengbte_fworker + if renormalize: + wf.append_wf( + Workflow.from_Firework(fw_lattice_conductivity), [wf.fws[-(len(temperatures)+push)].fw_id] + ) + else: + wf.append_wf( + Workflow.from_Firework(fw_lattice_conductivity), [fitting_fw_id] + ) + + formula = structure.composition.reduced_formula + wf.name = "{} - lattice dynamics".format(formula) + + # Add workflow metadata to all relevant *ToDb tasks. + wf_meta = {"wf_name": "LatticeDynamicsWF", "wf_version": _WF_VERSION} + for task_name in ["VaspToDb", "ShengBTEToDb", "ForceConstantsToDb"]: + wf = add_additional_fields_to_taskdocs( + wf, {"wf_meta": wf_meta}, task_name_constraint=task_name + ) + + return wf + + +def get_perturbed_structure_wf( + structure: Structure, + supercell_matrix: Optional[np.ndarray], + name: str = "perturbed structure", + vasp_input_set: Optional[VaspInputSet] = None, + common_settings: Optional[Dict] = None, + copy_vasp_outputs: bool = False, + rattle_stds: Optional[List[float]] = None, + n_configs_per_std: int = 1, + min_nn_scale: float = 0.85, + pass_forces: bool = True, +) -> Workflow: + """ + Get static calculations to calculate the forces on each perturbed supercell. + + Args: + structure: Input structure. + supercell_matrix: Supercell transformation matrix + name: Transmuter firework name. + vasp_input_set: Vasp input set for perturbed structure calculations. + common_settings: Common settings dict. Supports "VASP_CMD", "DB_FILE", + and "user_incar_settings" keys. + copy_vasp_outputs: Whether or not to copy previous vasp outputs. + rattle_stds: List of standard deviations (in normal distribution) to + to use when displacing the sites. + n_configs_per_std: Number of structures to generate per rattle standard + deviation. + min_nn_scale: Controls the minimum interatomic distance used for + computing the probability for each rattle move. + pass_forces: Whether to append the force and supercell structure + information into the perturbed_tasks key of the child fireworks. + + Returns: + The workflow. + """ + common_settings = _get_common_settings(common_settings) + vasp_cmd = common_settings["VASP_CMD"] + db_file = common_settings["DB_FILE"] + override_vasp_params = { + "user_incar_settings": common_settings["user_incar_settings"] + } + + if supercell_matrix is None: + supercell_matrix = np.eye(4) + + supercell_matrix = np.asarray(supercell_matrix).tolist() + natoms = len(structure * supercell_matrix) + + if rattle_stds is None: + rattle_stds = np.linspace(0.005, 0.1, 5) + + if vasp_input_set is None: + vasp_input_set = MPStaticSet(structure) + + # find the smallest nearest neighbor distance taking into account PBC +# min_distance = np.min( +# [n.nn_distance for d in structure.get_all_neighbors(10) for n in d] +# ) +# scaled_min_distance = min_distance * min_nn_scale + all_rattle_stds = np.repeat(rattle_stds, n_configs_per_std) + + logger.debug("Using supercell_matrix of: {}".format(supercell_matrix)) + logger.debug("Supercell has {} atoms".format(natoms)) + logger.debug( + "Using {} supercells per displacement".format(n_configs_per_std) + ) + logger.debug("Using {} rattle stds".format(len(rattle_stds))) + logger.debug("Rattle stds: {}".format(rattle_stds)) + + fws = [] + for i, rattle_std in enumerate(all_rattle_stds): + fw_name = "{}: i={}; rattle_std={:.3f}".format(name, i, rattle_std) + + # make sure the minimum distance is at least min_dist - 2 * rattle_std + # as a sanity check +# rattle_min_distance = min_distance - 2 * rattle_std +# rattle_min_distance = min(scaled_min_distance, rattle_min_distance) + + transformations = [ +# "SupercellTransformation", + "PhonopySupercellTransformation", + "FixedRandomDisplacementTransformation", + ] + + transformation_params = [ + {"scaling_matrix": supercell_matrix}, + {"rattle_std": rattle_std}#, "min_distance": rattle_min_distance}, + ] + + fw = TransmuterFW( + name=fw_name, + structure=structure, + transformations=transformations, + transformation_params=transformation_params, + vasp_input_set=vasp_input_set, + override_default_vasp_params=override_vasp_params, + copy_vasp_outputs=copy_vasp_outputs, + vasp_cmd=vasp_cmd, + db_file=db_file, + ) + + # don't store CHGCAR and other volumetric data in the VASP drone + for task in fw.tasks: + if "VaspToDb" in str(task): + task.update(vasp_to_db_params) + + if pass_forces: + pass_dict = { + "parent_structure": structure.as_dict(), + "supercell_matrix": supercell_matrix, + "forces": ">>output.ionic_steps.-1.forces", + "structure": ">>output.ionic_steps.-1.structure", + } + pass_task = pass_vasp_result( + pass_dict=pass_dict, + mod_spec_cmd="_push", + mod_spec_key="perturbed_tasks", + ) + fw.tasks.append(pass_task) + + fws.append(fw) + + wfname = "{}: {}".format(structure.composition.reduced_formula, name) + return Workflow(fws, name=wfname) + + +def get_num_supercells( + supercell_structure: Structure, + symprec: float = 0.01, + min_num_equivalent_sites: int = 100, + max_num_supercells: int = 6, +) -> int: + """ + Get the number of supercells to run per rattle standard deviation. + + The aim is to have each equivalent site represented at least + ``min_num_equivalent_sites`` times. For example, if a symmetry inequivalent + site appears 26 times in the supercell structure, `n_configs` would be 4. + I.e., 4 * 26 > 100. + + Args: + supercell_structure: The ideal supercell structure. + symprec: The symmetry precision for determining if sites are equivalent. + min_num_equivalent_sites: The minimum number of equivalent sites. + max_num_supercells: The maximum number of cells. + + Returns: + The number of supercells needed for all symmetry inequivalent sites to + be represented at least `min_num_equivalent_sites` times. + """ + # get the equivalent sites in the structure and calculate the smallest + # site degeneracy + sga = SpacegroupAnalyzer(supercell_structure, symprec=symprec) + equiv_idxs = sga.get_symmetry_dataset()["equivalent_atoms"] + _, equiv_counts = np.unique(equiv_idxs, return_counts=True) + min_count = np.min(equiv_counts) + + n_cells = math.ceil(min_num_equivalent_sites / min_count) + return min([n_cells, max_num_supercells]) + + +def _get_common_settings(common_settings: Optional[Dict]): + common_settings = common_settings or {} + for k, v in _DEFAULT_SETTINGS.items(): + if k not in common_settings: + common_settings[k] = v + + user_incar_settings = deepcopy(_static_user_incar_settings) + user_incar_settings.update(common_settings.get("user_incar_settings", {})) + common_settings["user_incar_settings"] = user_incar_settings + + return common_settings + + diff --git a/atomate/vasp/workflows/presets/core.py b/atomate/vasp/workflows/presets/core.py index cd082c13f..9556395b9 100644 --- a/atomate/vasp/workflows/presets/core.py +++ b/atomate/vasp/workflows/presets/core.py @@ -1,7 +1,12 @@ +from typing import Optional from uuid import uuid4 import numpy as np +from atomate.vasp.workflows.base.lattice_dynamics import \ + get_lattice_dynamics_wf, vasp_to_db_params +from fireworks import Workflow +from pymatgen.core.structure import Structure from pymatgen.io.vasp.sets import MPRelaxSet, MPStaticSet, MPHSERelaxSet from pymatgen.io.vasp.inputs import Kpoints @@ -19,6 +24,7 @@ add_wf_metadata, add_common_powerups, ) +from atomate.vasp.analysis.lattice_dynamics import FIT_METHOD from atomate.vasp.workflows.base.core import get_wf from atomate.vasp.workflows.base.elastic import get_wf_elastic_constant from atomate.vasp.workflows.base.raman import get_wf_raman_spectra @@ -319,15 +325,8 @@ def wf_elastic_constant(structure, c=None, order=2, sym_reduce=False): uis_optimize = {"ENCUT": 700, "EDIFF": 1e-6, "LAECHG": False} if order > 2: - uis_optimize.update( - { - "EDIFF": 1e-10, - "EDIFFG": -0.001, - "ADDGRID": True, - "LREAL": False, - "ISYM": 0, - } - ) + uis_optimize.update({"EDIFF": 1e-8, "EDIFFG": -0.001, + "ADDGRID": True, "LREAL": False, "ISYM": 0}) # This ensures a consistent k-point mesh across all calculations # We also turn off symmetry to prevent VASP from changing the # mesh internally @@ -827,3 +826,179 @@ def wf_nudged_elastic_band(structures, parent, c=None): ) return wf + + +def wf_lattice_dynamics( + structure: Structure, + fit_method: str = FIT_METHOD, + disp_cut: float = None, + bulk_modulus: float = None, + c: Optional[dict] = None, + supercell_matrix_kwargs: Optional[dict] = None, + num_supercell_kwargs: Optional[dict] = None, + calculate_lattice_thermal_conductivity=True, + thermal_conductivity_temperature=None, + renormalize=False, + renormalize_temperature=None, + renormalize_thermal_expansion_iter=False, + **ld_kwargs +) -> Workflow: + """ + Get a workflow to calculate lattice thermal conductivity, including a tight + structure optimization. + + Args: + structure: The input structure. + c: Workflow common settings dict. Supports the keys: "VASP_CMD", + "DB_FILE", and "user_incar_settings", "ADD_WF_METADATA", and the + options supported by "add_common_powerups". + **ld_kwargs: Keyword arguments to be passed directly to the lattice + dynamics base workflow. + + Returns: + A workflow to calculate lattice thermal conductivity. + """ + + # start with defining the relaxation workflow + optimize_uis = { + "LAECHG": False, + 'ENCUT': 600, + 'ADDGRID': True, + 'EDIFF': 1e-8, + 'EDIFFG': -5e-4, + 'PREC': 'Accurate', + "LREAL": False, + 'LASPH': True, + 'ISPIN': 2, + 'ISMEAR': 0, + 'SIGMA': 0.1, + 'LCHARG': False, + 'LWAVE': False + } + c = c if c is not None else {} + if "USER_INCAR_SETTINGS" not in c: + c["USER_INCAR_SETTINGS"] = {} + + # wf_structure_optimization expects user incar settings in capitals + c["USER_INCAR_SETTINGS"].update(optimize_uis) + c["USER_INCAR_SETTINGS"].update(c.get("user_incar_settings", {})) + wf = wf_structure_optimization(structure, c=c) + + # don't store CHGCAR and other volumetric data in the VASP drone + for task in wf.fws[0].tasks: + if "VaspToDb" in str(task): + task.update(vasp_to_db_params) + + # define lattice dynamics workflow + wf_ld = get_lattice_dynamics_wf( + structure, + fit_method=fit_method, + disp_cut=disp_cut, + bulk_modulus=bulk_modulus, + common_settings=c, + supercell_matrix_kwargs=supercell_matrix_kwargs, + num_supercell_kwargs=num_supercell_kwargs, + calculate_lattice_thermal_conductivity=calculate_lattice_thermal_conductivity, + thermal_conductivity_temperature=thermal_conductivity_temperature, + renormalize=renormalize, + renormalize_temperature=renormalize_temperature, + renormalize_thermal_expansion_iter=bool(renormalize_thermal_expansion_iter and bulk_modulus), + copy_vasp_outputs=True, + **ld_kwargs + ) + + # join the workflows + wf.append_wf(wf_ld, wf.leaf_fw_ids) + + formula = structure.composition.reduced_formula + wf_name = "{} - lattice dynamics".format(formula) + wf.name = wf_name + + wf = add_common_powerups(wf, c) + if c.get("ADD_WF_METADATA", ADD_WF_METADATA): + wf = add_wf_metadata(wf, structure) + + return wf + + +def wf_aimd( + structure: Structure, + c: Optional[dict] = None, + supercell_matrix_kwargs: Optional[dict] = None, + num_supercell_kwargs: Optional[dict] = None, + ensemble='NVT', + simulation_time=10000, + time_step=2, + **aimd_kwargs +) -> Workflow: + """ + Get a workflow to run AIMD on vasp, preceded by a structure optimization. + + Args: + structure: The input structure. + c: Workflow common settings dict. Supports the keys: "VASP_CMD", + "DB_FILE", and "user_incar_settings", "ADD_WF_METADATA", and the + options supported by "add_common_powerups". + **aimd_kwargs: Keyword arguments to be passed directly to the AIMD base workflow. + + Returns: + A workflow to perform AIMD. + """ + + # start with defining the relaxation workflow + optimize_uis = { + "LAECHG": False, + 'ENCUT': 600, + 'ADDGRID': True, + 'EDIFF': 1e-8, + 'EDIFFG': -5e-4, + 'PREC': 'Accurate', + "LREAL": False, + 'LASPH': True, + 'ISPIN': 2, + 'ISMEAR': 0, + 'SIGMA': 0.1, + 'LCHARG': False, + 'LWAVE': False + } + c = c if c is not None else {} + if "USER_INCAR_SETTINGS" not in c: + c["USER_INCAR_SETTINGS"] = {} + + # wf_structure_optimization expects user incar settings in capitals + c["USER_INCAR_SETTINGS"].update(optimize_uis) + c["USER_INCAR_SETTINGS"].update(c.get("user_incar_settings", {})) + wf = wf_structure_optimization(structure, c=c) + + # don't store CHGCAR and other volumetric data in the VASP drone + for task in wf.fws[0].tasks: + if "VaspToDb" in str(task): + task.update(vasp_to_db_params) + + # Define AIMD workflow + wf_aimd = get_aimd_wf( + structure, + common_settings=c, + ensemble=ensemble, + start_temp=start_temp, + end_temp=end_temp, + simulation_time=simulation_time, + time_step=time_step, + copy_vasp_outputs = True, + supercell_matrix_kwargs=supercell_matrix_kwargs, + **aimd_kwargs + ) + + # join the workflows + wf.append_wf(wf_aimd, wf.leaf_fw_ids) + + formula = structure.composition.reduced_formula + wf_name = "{} AIMD - {} - {}K".format(formula,ensemble,end_temp) + wf.name = wf_name + + wf = add_common_powerups(wf, c) + if c.get("ADD_WF_METADATA", ADD_WF_METADATA): + wf = add_wf_metadata(wf, structure) + + return wf + diff --git a/atomate/vasp/workflows/tests/test_csld_workflow.py b/atomate/vasp/workflows/tests/test_csld_workflow.py new file mode 100644 index 000000000..07471c7ab --- /dev/null +++ b/atomate/vasp/workflows/tests/test_csld_workflow.py @@ -0,0 +1,175 @@ +# coding: utf-8 + +from __future__ import division, print_function, unicode_literals, absolute_import + +import os +from monty.os.path import which +import unittest +import numpy as np +import shutil + +from pymatgen import Structure +from atomate.vasp.workflows.base.csld import CompressedSensingLatticeDynamicsWF +from atomate.vasp.firetasks.parse_outputs import ( + CSLDForceConstantsToDB, + ShengBTEToDB, +) +from atomate.utils.testing import AtomateTest, DB_DIR + +import json + +module_dir = os.path.join(os.path.dirname(os.path.abspath(__file__))) +db_dir = os.path.join(module_dir, "..", "..", "..", "common", "test_files") +ref_dir = os.path.join(module_dir, "..", "..", "test_files", "csld_wf") + +__author__ = "Rees Chang" +__email__ = "rc564@cornell.edu" + +csld_present = which("csld_main") + +class TestCompressedSensingLatticeDynamicsWorkflow(AtomateTest): + + @staticmethod + def init(): + with open(os.path.join(ref_dir, "FW.json"), + "r") as f: + sample_task = json.load(f)[0] + wf_uuid = sample_task["spec"]["_tasks"][0]["wf_uuid"] + parent_structure = Structure.from_dict( + sample_task["spec"]["_tasks"][0]["parent_structure"]) + trans_mat = sample_task["spec"]["_tasks"][0]["trans_mat"] + supercell_structure = Structure.from_dict( + sample_task["spec"]["_tasks"][0]["supercell_structure"]) + supercell_smallest_dim = sample_task["spec"]["_tasks"][0]["supercell_smallest_dim"] + perturbed_supercells = sample_task["spec"]["_tasks"][0]["perturbed_supercells"] + for i in range(len(perturbed_supercells)): + perturbed_supercells[i] = Structure.from_dict( + perturbed_supercells[i]) + disps = sample_task["spec"]["_tasks"][0]["disps"] + first_pass = sample_task["spec"]["_tasks"][0]["first_pass"] + static_user_incar_settings = sample_task["spec"]["_tasks"][0]["static_user_incar_settings"] + env_vars = sample_task["spec"]["_tasks"][0]["env_vars"] + shengbte_t_range = sample_task["spec"]["_tasks"][0]["shengbte_t_range"] + shengbte_fworker = sample_task["spec"]["_tasks"][0]["shengbte_fworker"] + + csld_firetask = CSLDForceConstantsToDB( + db_file=os.path.join(DB_DIR, "db.json"), + wf_uuid=wf_uuid, + parent_structure=parent_structure, + trans_mat=trans_mat, + supercell_structure=supercell_structure, + supercell_smallest_dim=supercell_smallest_dim, + perturbed_supercells=perturbed_supercells, + disps=disps, + first_pass=first_pass, + static_user_incar_settings=static_user_incar_settings, + env_vars=env_vars, + shengbte_t_range=shengbte_t_range, + shengbte_fworker=shengbte_fworker, + force_diagonal_transformation=True, + ) + + return csld_firetask + + def test_collect_successful_static_calcs_results(self): + tasks = self.get_task_collection() + csld_firetask = self.init() + with open(os.path.join(ref_dir, "FW.json"), + "r") as f: + sample_task = json.load(f)[1] + tasks.insert_one(sample_task) + + supercells_forces, successful_disps = csld_firetask.collect_successful_static_calcs_results( + tasks) + + self.assertEqual( + float(successful_disps[0]), + 0.1 + ) + self.assertTrue( + isinstance(supercells_forces, list) + ) + self.assertEqual( + supercells_forces[0][0][0], + 0.07831190000000000373 + ) + self.assertEqual( + supercells_forces[0][0][1], + 0.13348752999999999314 + ) + self.assertEqual( + supercells_forces[0][0][2], + -0.7885310199999999714 + ) + self.assertEqual( + len(supercells_forces[0]), + 216 + ) + + def test_set_params(self): + + csld_firetask = self.init() + csld_firetask.set_params( + iteration_number=0, + disps=[0.1], + cluster_diam='11 6.5 5.0', + max_order=3, + submodel1='anh 0 1 2 3', + export_sbte='5 5 5 2 3', + supercells_forces=[np.eye(3)] + ) + + self.assertEqual( + csld_firetask["csld_settings"]["structure"]["prim"], + "Si_supercell_iter0/POSCAR") + self.assertEqual( + csld_firetask["csld_settings"]["model"]["max_order"], + '3' + ) + self.assertEqual( + csld_firetask["csld_settings"]["model"]["cluster_diameter"], + '11 6.5 5.0' + ) + self.assertEqual( + csld_firetask["csld_settings"]["model"]["cluster_filter"], + r"lambda cls: ((cls.order_uniq <= 2) or (cls.bond_counts(2.9) " + r">= 2)) and cls.is_small_in('" + "Si_supercell_iter0" + "/sc.txt')" + ) + self.assertEqual( + csld_firetask["csld_settings"]["training"]["traindat1"], + 'Si_supercell_iter0/SPOSCAR Si_supercell_iter0/disp0.10' + ) + self.assertEqual( + csld_firetask["csld_settings"]["fitting"]["submodel1"], + 'anh 0 1 2 3' + ) + self.assertEqual( + csld_firetask["csld_settings"]["export_potential"]["export_shengbte"], + '5 5 5 2 3' + ) + self.assertEqual( + csld_firetask["forces_paths"], + ['Si_supercell_iter0/disp0.10'] + ) + self.assertTrue( + os.path.isfile(csld_firetask["forces_paths"][0] + "/force.txt") + ) + self.assertTrue( + os.path.isfile('Si_supercell_iter0/POSCAR') + ) + self.assertTrue( + os.path.isfile('Si_supercell_iter0/SPOSCAR') + ) + self.assertTrue( + os.path.isfile('Si_supercell_iter0/sc.txt') + ) + shutil.rmtree('Si_supercell_iter0') + + @unittest.skipIf(not csld_present, "CSLD not present") + def test_run_csld(self): + print('hi') + + + + + diff --git a/atomate/vasp/workflows/tests/test_lattice_dynamics_workflow.py b/atomate/vasp/workflows/tests/test_lattice_dynamics_workflow.py new file mode 100644 index 000000000..55da5cde4 --- /dev/null +++ b/atomate/vasp/workflows/tests/test_lattice_dynamics_workflow.py @@ -0,0 +1,103 @@ + +from pathlib import Path + +from atomate.vasp.workflows import get_lattice_dynamics_wf +from fireworks import FWorker +from fireworks.core.rocket_launcher import rapidfire + +from atomate.vasp.powerups import use_fake_vasp, use_potcar_spec +from atomate.utils.testing import AtomateTest + +from pymatgen.util.testing import PymatgenTest + +__author__ = 'Alex Ganose' +__email__ = 'aganose@lbl.gov' + +module_dir = Path(__file__).resolve().parent +db_dir = module_dir / "../../../common/test_files" +ref_dir = module_dir / "../../test_files" +wf_dir = ref_dir / "lattice_dynamics_wf" + +test_fworker = FWorker( + env={"db_file": db_dir / "db.json", "shengbte_cmd": "ShengBTE"} +) + + +class TestLatticeThermalConductivityWorkflow(AtomateTest): + + def setUp(self, lpad=True): + super().setUp(lpad=lpad) + + self.struct_si = PymatgenTest.get_structure("Si") + + self.wf = get_lattice_dynamics_wf( + self.struct_si, + perturbed_structure_kwargs={"rattle_stds": [0.01]}, + calculate_lattice_thermal_conductivity=True + ) + + # change the cutoffs for fit CSLD + self.wf.fws[-2].tasks[1].update({"cutoffs": [[5., 3., 3.]]}) + + # change shengbte mesh density + self.wf.fws[-1].tasks[1].update( + {"control_kwargs": {"reciprocal_density": 500}} + ) + + def test_wf(self): + self.wf = get_simulated_wf(self.wf) + self.lp.add_wf(self.wf) + rapidfire(self.lp, fworker=test_fworker) + + self.assertEqual(len(self.wf.fws), 3) + + # check static calculation + result = self.get_task_collection().find_one( + {"task_label": "perturbed structure: i=0; rattle_std=0.010"} + ) + self.check_run(result, mode="structure optimization") + + wf = self.lp.get_wf_by_fw_id(1) + self.assertTrue(all([s == 'COMPLETED' for s in wf.fw_states.values()])) + + def check_run(self, d, mode): + return 1 + # if mode not in ["structure optimization", "static dielectric", + # "raman_0_0.005", "raman analysis"]: + # raise ValueError("Invalid mode!") + # + # if mode not in ["raman analysis"]: + # self.assertEqual(d["formula_pretty"], "Si") + # self.assertEqual(d["formula_anonymous"], "A") + # self.assertEqual(d["nelements"], 1) + # self.assertEqual(d["state"], "successful") + # self.assertAlmostEqual(d["calcs_reversed"][0]["output"]["structure"]["lattice"]["a"], 3.867, 2) + # + # if mode in ["structure optimization"]: + # self.assertAlmostEqual(d["output"]["energy"], -10.850, 2) + # self.assertAlmostEqual(d["output"]["energy_per_atom"], -5.425, 2) + # + # elif mode in ["static dielectric"]: + # epsilon = [[13.23245131, -1.98e-06, -1.4e-06], + # [-1.98e-06, 13.23245913, 8.38e-06], + # [-1.4e-06, 8.38e-06, 13.23245619]] + # np.testing.assert_allclose(epsilon, d["output"]["epsilon_static"], rtol=1e-5) + # + # elif mode in ["raman_0_0.005"]: + # epsilon = [[13.16509632, 0.00850098, 0.00597267], + # [0.00850097, 13.25477303, -0.02979572], + # [0.00597267, -0.0297953, 13.28883867]] + # np.testing.assert_allclose(epsilon, d["output"]["epsilon_static"], rtol=1e-5) + + +def get_simulated_wf(wf): + ref_dirs = {"perturbed structure: i=0; rattle_std=0.010": wf_dir / "0"} + + params_to_check = ["ENCUT", "NSW", "EDIFF"] + wf = use_potcar_spec(wf) + wf = use_fake_vasp( + wf, ref_dirs, params_to_check=params_to_check, check_potcar=False + ) + + return wf + diff --git a/requirements-optional.txt b/requirements-optional.txt new file mode 100644 index 000000000..8218f9e81 --- /dev/null +++ b/requirements-optional.txt @@ -0,0 +1,2 @@ +f90nml==1.1.2 +ase==3.19.0 diff --git a/requirements.txt b/requirements.txt index 7dc6288b8..7e75ac112 100644 --- a/requirements.txt +++ b/requirements.txt @@ -15,3 +15,5 @@ pydash==5.0.0 pyyaml==5.4.1 maggma==0.27.0 scikit-image==0.18.1 +pymongo==3.10.1 +maggma==0.23.3