Example #1
0
def ipynbformat(lines):
    """Converts raw file lines to the JSON content lines used in ipynb"""

    line = repr(lines[0])[1:-1].replace('"', r'\"')
    alllines = line + '",\n'
    for i in range(1, len(lines) - 1):
        line = repr(lines[i])[1:-1].replace('"', r'\"')
        alllines += '    "' + line + '",\n'
    line = repr(lines[-1])[1:-1].replace('"', r'\"')
    alllines += '    "' + line

    return alllines.replace(r"\'", r"'")
Example #2
0
def ipynbformat(lines):
    """Converts raw file lines to the JSON content lines used in ipynb"""
    
    line = repr(lines[0])[1:-1].replace('"', r'\"')
    alllines = line + '",\n'
    for i in range(1, len(lines)-1):
        line = repr(lines[i])[1:-1].replace('"', r'\"')
        alllines += '    "' + line + '",\n'
    line = repr(lines[-1])[1:-1].replace('"', r'\"')
    alllines += '    "' + line
    
    return alllines.replace(r"\'", r"'")
Example #3
0
def r_a_ratio(ucell):
    """
    Calculates the r/a ratio by identifying the shortest interatomic spacing, r,
    for a unit cell.
    
    Parameters
    ----------
    ucell : atomman.System
        The unit cell system to evaluate.
        
    Returns
    -------
    float
        The shortest interatomic spacing, r, divided by the unit cell's a
        lattice parameter.
    """
    r_a = ucell.box.a
    for i in range(ucell.natoms):
        for j in range(i):
            dmag = np.linalg.norm(ucell.dvect(i,j))
            if dmag < r_a:
                r_a = dmag
    return r_a / ucell.box.a
Example #4
0
def r_a_ratio(ucell):
    """
    Calculates the r/a ratio by identifying the shortest interatomic spacing, r,
    for a unit cell.
    
    Parameters
    ----------
    ucell : atomman.System
        The unit cell system to evaluate.
        
    Returns
    -------
    float
        The shortest interatomic spacing, r, divided by the unit cell's a
        lattice parameter.
    """
    r_a = ucell.box.a
    for i in range(ucell.natoms):
        for j in range(i):
            dmag = np.linalg.norm(ucell.dvect(i, j))
            if dmag < r_a:
                r_a = dmag
    return r_a / ucell.box.a
Example #5
0
def parsefunctions(lines):
    """
    Parses out the lines of a Python script corresponding to primary functions.
    """
    name = None
    for i in range(len(lines)):
        if lines[i].strip() != '':

            if lines[i][0] != ' ' and name is not None:
                yield name, lines[start:i]
                name = None

            if lines[i][:4] == 'def ':
                start = i
                name = lines[i][4:].split('(')[0].strip()
Example #6
0
def parsefunctions(lines):
    """
    Parses out the lines of a Python script corresponding to primary functions.
    """
    name = None
    for i in range(len(lines)):
        if lines[i].strip() != '':
        
            if lines[i][0] != ' ' and name is not None:
                yield name, lines[start:i]
                name = None
                
            if lines[i][:4] == 'def ':
                start = i
                name = lines[i][4:].split('(')[0].strip()
def peierlsnabarrostress(pnsolution,
                         delta_tau,
                         tausteps=1,
                         cdiffstress=False,
                         fullstress=True,
                         min_method='Powell',
                         min_options={}):
    """
    Applies stress to a semi-discrete Peierls-Nabarro solution.
    """
    total_energies = []
    tau_xys = []
    tau_yys = []
    tau_yzs = []

    # Loop over stress states
    for i in range(0, tausteps + 1):
        tau = i * delta_tau
        pnsolution.solve(tau=tau,
                         cdiffstress=cdiffstress,
                         fullstress=fullstress,
                         min_method=min_method,
                         min_options=min_options)
        sys.stdout.flush()

        # Save values
        total_energies.append(pnsolution.total_energy())
        tau_xys.append(tau[1, 0])
        tau_yys.append(tau[1, 1])
        tau_yzs.append(tau[1, 2])

        # Save solution to file
        model = pnsolution.model()
        with open(os.path.join(str(i) + '.json'), 'w') as f:
            model.json(fp=f)

    # Initialize results dict
    results_dict = {}
    results_dict['total_energy'] = total_energies
    results_dict['tau_xy'] = tau_xys
    results_dict['tau_yy'] = tau_yys
    results_dict['tau_yz'] = tau_yzs

    return results_dict
Example #8
0
def elastic_constants_static(lammps_command,
                             system,
                             potential,
                             mpi_command=None,
                             strainrange=1e-6,
                             etol=0.0,
                             ftol=0.0,
                             maxiter=10000,
                             maxeval=100000,
                             dmax=uc.set_in_units(0.01, 'angstrom')):
    """
    Repeatedly runs the ELASTIC example distributed with LAMMPS until box
    dimensions converge within a tolerance.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    strainrange : float, optional
        The small strain value to apply when calculating the elastic
        constants (default is 1e-6).
    etol : float, optional
        The energy tolerance for the structure minimization. This value is
        unitless. (Default is 0.0).
    ftol : float, optional
        The force tolerance for the structure minimization. This value is in
        units of force. (Default is 0.0).
    maxiter : int, optional
        The maximum number of minimization iterations to use (default is 10000).
    maxeval : int, optional
        The maximum number of minimization evaluations to use (default is 
        100000).
    dmax : float, optional
        The maximum distance in length units that any atom is allowed to relax
        in any direction during a single minimization iteration (default is
        0.01 Angstroms).
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'a_lat'** (*float*) - The relaxed a lattice constant.
        - **'b_lat'** (*float*) - The relaxed b lattice constant.
        - **'c_lat'** (*float*) - The relaxed c lattice constant.
        - **'alpha_lat'** (*float*) - The alpha lattice angle.
        - **'beta_lat'** (*float*) - The beta lattice angle.
        - **'gamma_lat'** (*float*) - The gamma lattice angle.
        - **'E_coh'** (*float*) - The cohesive energy of the relaxed system.
        - **'stress'** (*numpy.array*) - The measured stress state of the
          relaxed system.
        - **'C_elastic'** (*atomman.ElasticConstants*) - The relaxed system's
          elastic constants.
        - **'system_relaxed'** (*atomman.System*) - The relaxed system.
    """

    # Convert hexagonal cells to orthorhombic to avoid LAMMPS tilt issues
    if am.tools.ishexagonal(system.box):
        system = system.rotate([[2, -1, -1, 0], [0, 1, -1, 0], [0, 0, 0, 1]])

    # Get lammps units
    lammps_units = lmp.style.unit(potential.units)

    # Get lammps version date
    lammps_date = lmp.checkversion(lammps_command)['date']

    # Define lammps variables
    lammps_variables = {}
    system_info = system.dump('atom_data',
                              f='init.dat',
                              units=potential.units,
                              atom_style=potential.atom_style)
    lammps_variables['atomman_system_info'] = system_info
    lammps_variables['atomman_pair_info'] = potential.pair_info(system.symbols)
    lammps_variables['strainrange'] = strainrange
    lammps_variables['etol'] = etol
    lammps_variables['ftol'] = uc.get_in_units(ftol, lammps_units['force'])
    lammps_variables['maxiter'] = maxiter
    lammps_variables['maxeval'] = maxeval
    lammps_variables['dmax'] = uc.get_in_units(dmax, lammps_units['length'])

    # Fill in template files
    template_file = 'cij.template'
    lammps_script = 'cij.in'
    with open(template_file) as f:
        template = f.read()
    with open(lammps_script, 'w') as f:
        f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))
    template_file2 = 'potential.template'
    lammps_script2 = 'potential.in'
    with open(template_file2) as f:
        template = f.read()
    with open(lammps_script2, 'w') as f:
        f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))

    # Run LAMMPS
    output = lmp.run(lammps_command, lammps_script, mpi_command)

    # Pull out initial state
    thermo = output.simulations[0]['thermo']
    pxx0 = uc.set_in_units(thermo.Pxx.values[-1], lammps_units['pressure'])
    pyy0 = uc.set_in_units(thermo.Pyy.values[-1], lammps_units['pressure'])
    pzz0 = uc.set_in_units(thermo.Pzz.values[-1], lammps_units['pressure'])
    pyz0 = uc.set_in_units(thermo.Pyz.values[-1], lammps_units['pressure'])
    pxz0 = uc.set_in_units(thermo.Pxz.values[-1], lammps_units['pressure'])
    pxy0 = uc.set_in_units(thermo.Pxy.values[-1], lammps_units['pressure'])

    # Negative strains
    cij_n = np.empty((6, 6))
    for i in range(6):
        j = 1 + i * 2
        # Pull out strained state
        thermo = output.simulations[j]['thermo']
        pxx = uc.set_in_units(thermo.Pxx.values[-1], lammps_units['pressure'])
        pyy = uc.set_in_units(thermo.Pyy.values[-1], lammps_units['pressure'])
        pzz = uc.set_in_units(thermo.Pzz.values[-1], lammps_units['pressure'])
        pyz = uc.set_in_units(thermo.Pyz.values[-1], lammps_units['pressure'])
        pxz = uc.set_in_units(thermo.Pxz.values[-1], lammps_units['pressure'])
        pxy = uc.set_in_units(thermo.Pxy.values[-1], lammps_units['pressure'])

        # Calculate cij_n using stress changes
        cij_n[i] = np.array([
            pxx - pxx0, pyy - pyy0, pzz - pzz0, pyz - pyz0, pxz - pxz0,
            pxy - pxy0
        ]) / strainrange

    # Positive strains
    cij_p = np.empty((6, 6))
    for i in range(6):
        j = 2 + i * 2
        # Pull out strained state
        thermo = output.simulations[j]['thermo']
        pxx = uc.set_in_units(thermo.Pxx.values[-1], lammps_units['pressure'])
        pyy = uc.set_in_units(thermo.Pyy.values[-1], lammps_units['pressure'])
        pzz = uc.set_in_units(thermo.Pzz.values[-1], lammps_units['pressure'])
        pyz = uc.set_in_units(thermo.Pyz.values[-1], lammps_units['pressure'])
        pxz = uc.set_in_units(thermo.Pxz.values[-1], lammps_units['pressure'])
        pxy = uc.set_in_units(thermo.Pxy.values[-1], lammps_units['pressure'])

        # Calculate cij_p using stress changes
        cij_p[i] = -np.array([
            pxx - pxx0, pyy - pyy0, pzz - pzz0, pyz - pyz0, pxz - pxz0,
            pxy - pxy0
        ]) / strainrange

    # Average symmetric values
    cij = (cij_n + cij_p) / 2
    for i in range(6):
        for j in range(i):
            cij[i, j] = cij[j, i] = (cij[i, j] + cij[j, i]) / 2

    # Define results_dict
    results_dict = {}
    results_dict['raw_cij_negative'] = cij_n
    results_dict['raw_cij_positive'] = cij_p
    results_dict['C'] = am.ElasticConstants(Cij=cij)

    return results_dict
Example #9
0
def relax_static(lammps_command, system, potential, mpi_command=None,
                 p_xx=0.0, p_yy=0.0, p_zz=0.0, p_xy=0.0, p_xz=0.0, p_yz=0.0,
                 dispmult=0.0, etol=0.0, ftol=0.0,  maxiter=10000,
                 maxeval=100000, dmax=uc.set_in_units(0.01, 'angstrom'),
                 maxcycles=100, ctol=1e-10):
    """
    Repeatedly runs the ELASTIC example distributed with LAMMPS until box
    dimensions converge within a tolerance.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    p_xx : float, optional
        The value to relax the x tensile pressure component to (default is
        0.0).
    p_yy : float, optional
        The value to relax the y tensile pressure component to (default is
        0.0).
    p_zz : float, optional
        The value to relax the z tensile pressure component to (default is
        0.0).
    p_xy : float, optional
        The value to relax the xy shear pressure component to (default is
        0.0).
    p_xz : float, optional
        The value to relax the xz shear pressure component to (default is
        0.0).
    p_yz : float, optional
        The value to relax the yz shear pressure component to (default is
        0.0).
    dispmult : float, optional
        Multiplier for applying a random displacement to all atomic positions
        prior to relaxing. Default value is 0.0.
    etol : float, optional
        The energy tolerance for the structure minimization. This value is
        unitless. (Default is 0.0).
    ftol : float, optional
        The force tolerance for the structure minimization. This value is in
        units of force. (Default is 0.0).
    maxiter : int, optional
        The maximum number of minimization iterations to use (default is 10000).
    maxeval : int, optional
        The maximum number of minimization evaluations to use (default is 
        100000).
    dmax : float, optional
        The maximum distance in length units that any atom is allowed to relax
        in any direction during a single minimization iteration (default is
        0.01 Angstroms).
    pressure_unit : str, optional
        The unit of pressure to calculate the elastic constants in (default is
        'GPa').
    maxcycles : int, optional
        The maximum number of times the minimization algorithm is called.
        Default value is 100.
    ctol : float, optional
        The relative tolerance used to determine if the lattice constants have
        converged (default is 1e-10).
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'relaxed_system'** (*float*) - The relaxed system.
        - **'E_coh'** (*float*) - The cohesive energy of the relaxed system.
        - **'measured_pxx'** (*float*) - The measured x tensile pressure of the
          relaxed system.
        - **'measured_pyy'** (*float*) - The measured y tensile pressure of the
          relaxed system.
        - **'measured_pzz'** (*float*) - The measured z tensile pressure of the
          relaxed system.
        - **'measured_pxy'** (*float*) - The measured xy shear pressure of the
          relaxed system.
        - **'measured_pxz'** (*float*) - The measured xz shear pressure of the
          relaxed system.
        - **'measured_pyz'** (*float*) - The measured yz shear pressure of the
          relaxed system.
    """
    
    # Get lammps units
    lammps_units = lmp.style.unit(potential.units)
    
    # Get lammps version date
    lammps_date = lmp.checkversion(lammps_command)['date']
    
    # Save initial configuration as a dump file
    system.dump('atom_dump', f='initial.dump')
    
    # Apply small random distortions to atoms
    system.atoms.pos += dispmult * np.random.rand(*system.atoms.pos.shape) - dispmult / 2
    
    # Initialize parameters
    old_vects = system.box.vects
    converged = False
    
    # Run minimizations up to maxcycles times
    for cycle in range(maxcycles):
        old_system = deepcopy(system)
        
        # Define lammps variables
        lammps_variables = {}
        system_info = system.dump('atom_data', f='init.dat',
                                  units=potential.units,
                                  atom_style=potential.atom_style)
        lammps_variables['atomman_system_info'] = system_info
        lammps_variables['atomman_pair_info'] = potential.pair_info(system.symbols)
        lammps_variables['p_xx'] = uc.get_in_units(p_xx, lammps_units['pressure'])
        lammps_variables['p_yy'] = uc.get_in_units(p_yy, lammps_units['pressure'])
        lammps_variables['p_zz'] = uc.get_in_units(p_zz, lammps_units['pressure'])
        lammps_variables['p_xy'] = uc.get_in_units(p_xy, lammps_units['pressure'])
        lammps_variables['p_xz'] = uc.get_in_units(p_xz, lammps_units['pressure'])
        lammps_variables['p_yz'] = uc.get_in_units(p_yz, lammps_units['pressure'])
        lammps_variables['etol'] = etol
        lammps_variables['ftol'] = uc.get_in_units(ftol, lammps_units['force'])
        lammps_variables['maxiter'] = maxiter
        lammps_variables['maxeval'] = maxeval
        lammps_variables['dmax'] = uc.get_in_units(dmax, lammps_units['length'])
        
        # Set dump_modify_format based on lammps_date
        if lammps_date < datetime.date(2016, 8, 3):
            lammps_variables['dump_modify_format'] = '"%d %d %.13e %.13e %.13e %.13e"'
        else:
            lammps_variables['dump_modify_format'] = 'float %.13e'
        
        # Write lammps input script
        template_file = 'minbox.template'
        lammps_script = 'minbox.in'
        with open(template_file) as f:
            template = f.read()
        with open(lammps_script, 'w') as f:
            f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))
        
        # Run LAMMPS and extract thermo data
        logfile = 'log-' + str(cycle) + '.lammps'
        output = lmp.run(lammps_command, lammps_script, mpi_command, logfile=logfile)
        thermo = output.simulations[0]['thermo']
        
        # Clean up dump files
        os.remove('0.dump')
        last_dump_file = str(thermo.Step.values[-1]) + '.dump'
        renamed_dump_file = 'relax_static-' + str(cycle) + '.dump'
        shutil.move(last_dump_file, renamed_dump_file)
        
        # Load relaxed system
        system = am.load('atom_dump', renamed_dump_file, symbols=system.symbols)
        
        # Test if box dimensions have converged
        if np.allclose(old_vects, system.box.vects, rtol=ctol, atol=0):
            converged = True
            break
        else:
            old_vects = system.box.vects
    
    # Check for convergence
    if converged is False:
        raise RuntimeError('Failed to converge after ' + str(maxcycles) + ' cycles')
    
    # Zero out near-zero tilt factors
    lx = system.box.lx
    ly = system.box.ly
    lz = system.box.lz
    xy = system.box.xy
    xz = system.box.xz
    yz = system.box.yz
    if np.isclose(xy/ly, 0.0, rtol=0.0, atol=1e-10):
        xy = 0.0
    if np.isclose(xz/lz, 0.0, rtol=0.0, atol=1e-10):
        xz = 0.0
    if np.isclose(yz/lz, 0.0, rtol=0.0, atol=1e-10):
        yz = 0.0
    system.box.set(lx=lx, ly=ly, lz=lz, xy=xy, xz=xz, yz=yz)
    system.wrap()
    
    # Build results_dict
    results_dict = {}
    results_dict['dumpfile_initial'] = 'initial.dump'
    results_dict['symbols_initial'] = system.symbols
    results_dict['dumpfile_final'] = renamed_dump_file
    results_dict['symbols_final'] = system.symbols
    results_dict['E_coh'] = uc.set_in_units(thermo.PotEng.values[-1] / system.natoms,
                                       lammps_units['energy'])
                                       
    results_dict['lx'] = uc.set_in_units(lx, lammps_units['length'])
    results_dict['ly'] = uc.set_in_units(ly, lammps_units['length'])
    results_dict['lz'] = uc.set_in_units(lz, lammps_units['length'])
    results_dict['xy'] = uc.set_in_units(xy, lammps_units['length'])
    results_dict['xz'] = uc.set_in_units(xz, lammps_units['length'])
    results_dict['yz'] = uc.set_in_units(yz, lammps_units['length'])
    
    results_dict['measured_pxx'] = uc.set_in_units(thermo.Pxx.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pyy'] = uc.set_in_units(thermo.Pyy.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pzz'] = uc.set_in_units(thermo.Pzz.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pxy'] = uc.set_in_units(thermo.Pxy.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pxz'] = uc.set_in_units(thermo.Pxz.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pyz'] = uc.set_in_units(thermo.Pyz.values[-1],
                                                   lammps_units['pressure'])
    
    return results_dict
Example #10
0
def relax_static(lammps_command,
                 system,
                 potential,
                 mpi_command=None,
                 p_xx=0.0,
                 p_yy=0.0,
                 p_zz=0.0,
                 p_xy=0.0,
                 p_xz=0.0,
                 p_yz=0.0,
                 dispmult=0.0,
                 etol=0.0,
                 ftol=0.0,
                 maxiter=10000,
                 maxeval=100000,
                 dmax=uc.set_in_units(0.01, 'angstrom'),
                 maxcycles=100,
                 ctol=1e-10):
    """
    Repeatedly runs the ELASTIC example distributed with LAMMPS until box
    dimensions converge within a tolerance.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    p_xx : float, optional
        The value to relax the x tensile pressure component to (default is
        0.0).
    p_yy : float, optional
        The value to relax the y tensile pressure component to (default is
        0.0).
    p_zz : float, optional
        The value to relax the z tensile pressure component to (default is
        0.0).
    p_xy : float, optional
        The value to relax the xy shear pressure component to (default is
        0.0).
    p_xz : float, optional
        The value to relax the xz shear pressure component to (default is
        0.0).
    p_yz : float, optional
        The value to relax the yz shear pressure component to (default is
        0.0).
    dispmult : float, optional
        Multiplier for applying a random displacement to all atomic positions
        prior to relaxing. Default value is 0.0.
    etol : float, optional
        The energy tolerance for the structure minimization. This value is
        unitless. (Default is 0.0).
    ftol : float, optional
        The force tolerance for the structure minimization. This value is in
        units of force. (Default is 0.0).
    maxiter : int, optional
        The maximum number of minimization iterations to use (default is 10000).
    maxeval : int, optional
        The maximum number of minimization evaluations to use (default is 
        100000).
    dmax : float, optional
        The maximum distance in length units that any atom is allowed to relax
        in any direction during a single minimization iteration (default is
        0.01 Angstroms).
    pressure_unit : str, optional
        The unit of pressure to calculate the elastic constants in (default is
        'GPa').
    maxcycles : int, optional
        The maximum number of times the minimization algorithm is called.
        Default value is 100.
    ctol : float, optional
        The relative tolerance used to determine if the lattice constants have
        converged (default is 1e-10).
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'relaxed_system'** (*float*) - The relaxed system.
        - **'E_coh'** (*float*) - The cohesive energy of the relaxed system.
        - **'measured_pxx'** (*float*) - The measured x tensile pressure of the
          relaxed system.
        - **'measured_pyy'** (*float*) - The measured y tensile pressure of the
          relaxed system.
        - **'measured_pzz'** (*float*) - The measured z tensile pressure of the
          relaxed system.
        - **'measured_pxy'** (*float*) - The measured xy shear pressure of the
          relaxed system.
        - **'measured_pxz'** (*float*) - The measured xz shear pressure of the
          relaxed system.
        - **'measured_pyz'** (*float*) - The measured yz shear pressure of the
          relaxed system.
    """

    # Get lammps units
    lammps_units = lmp.style.unit(potential.units)

    # Get lammps version date
    lammps_date = lmp.checkversion(lammps_command)['date']

    # Save initial configuration as a dump file
    system.dump('atom_dump', f='initial.dump')

    # Apply small random distortions to atoms
    system.atoms.pos += dispmult * np.random.rand(
        *system.atoms.pos.shape) - dispmult / 2

    # Initialize parameters
    old_vects = system.box.vects
    converged = False

    # Run minimizations up to maxcycles times
    for cycle in range(maxcycles):
        old_system = deepcopy(system)

        # Define lammps variables
        lammps_variables = {}
        system_info = system.dump('atom_data',
                                  f='init.dat',
                                  units=potential.units,
                                  atom_style=potential.atom_style)
        lammps_variables['atomman_system_info'] = system_info
        lammps_variables['atomman_pair_info'] = potential.pair_info(
            system.symbols)
        lammps_variables['p_xx'] = uc.get_in_units(p_xx,
                                                   lammps_units['pressure'])
        lammps_variables['p_yy'] = uc.get_in_units(p_yy,
                                                   lammps_units['pressure'])
        lammps_variables['p_zz'] = uc.get_in_units(p_zz,
                                                   lammps_units['pressure'])
        lammps_variables['p_xy'] = uc.get_in_units(p_xy,
                                                   lammps_units['pressure'])
        lammps_variables['p_xz'] = uc.get_in_units(p_xz,
                                                   lammps_units['pressure'])
        lammps_variables['p_yz'] = uc.get_in_units(p_yz,
                                                   lammps_units['pressure'])
        lammps_variables['etol'] = etol
        lammps_variables['ftol'] = uc.get_in_units(ftol, lammps_units['force'])
        lammps_variables['maxiter'] = maxiter
        lammps_variables['maxeval'] = maxeval
        lammps_variables['dmax'] = uc.get_in_units(dmax,
                                                   lammps_units['length'])

        # Set dump_modify_format based on lammps_date
        if lammps_date < datetime.date(2016, 8, 3):
            lammps_variables[
                'dump_modify_format'] = '"%d %d %.13e %.13e %.13e %.13e"'
        else:
            lammps_variables['dump_modify_format'] = 'float %.13e'

        # Write lammps input script
        template_file = 'minbox.template'
        lammps_script = 'minbox.in'
        with open(template_file) as f:
            template = f.read()
        with open(lammps_script, 'w') as f:
            f.write(
                iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))

        # Run LAMMPS and extract thermo data
        logfile = 'log-' + str(cycle) + '.lammps'
        output = lmp.run(lammps_command,
                         lammps_script,
                         mpi_command,
                         logfile=logfile)
        thermo = output.simulations[0]['thermo']

        # Clean up dump files
        os.remove('0.dump')
        last_dump_file = str(thermo.Step.values[-1]) + '.dump'
        renamed_dump_file = 'relax_static-' + str(cycle) + '.dump'
        shutil.move(last_dump_file, renamed_dump_file)

        # Load relaxed system
        system = am.load('atom_dump',
                         renamed_dump_file,
                         symbols=system.symbols)

        # Test if box dimensions have converged
        if np.allclose(old_vects, system.box.vects, rtol=ctol, atol=0):
            converged = True
            break
        else:
            old_vects = system.box.vects

    # Check for convergence
    if converged is False:
        raise RuntimeError('Failed to converge after ' + str(maxcycles) +
                           ' cycles')

    # Zero out near-zero tilt factors
    lx = system.box.lx
    ly = system.box.ly
    lz = system.box.lz
    xy = system.box.xy
    xz = system.box.xz
    yz = system.box.yz
    if np.isclose(xy / ly, 0.0, rtol=0.0, atol=1e-10):
        xy = 0.0
    if np.isclose(xz / lz, 0.0, rtol=0.0, atol=1e-10):
        xz = 0.0
    if np.isclose(yz / lz, 0.0, rtol=0.0, atol=1e-10):
        yz = 0.0
    system.box.set(lx=lx, ly=ly, lz=lz, xy=xy, xz=xz, yz=yz)
    system.wrap()

    # Build results_dict
    results_dict = {}
    results_dict['dumpfile_initial'] = 'initial.dump'
    results_dict['symbols_initial'] = system.symbols
    results_dict['dumpfile_final'] = renamed_dump_file
    results_dict['symbols_final'] = system.symbols
    results_dict['E_coh'] = uc.set_in_units(
        thermo.PotEng.values[-1] / system.natoms, lammps_units['energy'])

    results_dict['lx'] = uc.set_in_units(lx, lammps_units['length'])
    results_dict['ly'] = uc.set_in_units(ly, lammps_units['length'])
    results_dict['lz'] = uc.set_in_units(lz, lammps_units['length'])
    results_dict['xy'] = uc.set_in_units(xy, lammps_units['length'])
    results_dict['xz'] = uc.set_in_units(xz, lammps_units['length'])
    results_dict['yz'] = uc.set_in_units(yz, lammps_units['length'])

    results_dict['measured_pxx'] = uc.set_in_units(thermo.Pxx.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pyy'] = uc.set_in_units(thermo.Pyy.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pzz'] = uc.set_in_units(thermo.Pzz.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pxy'] = uc.set_in_units(thermo.Pxy.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pxz'] = uc.set_in_units(thermo.Pxz.values[-1],
                                                   lammps_units['pressure'])
    results_dict['measured_pyz'] = uc.set_in_units(thermo.Pyz.values[-1],
                                                   lammps_units['pressure'])

    return results_dict
Example #11
0
def relax_box(lammps_command,
              system,
              potential,
              mpi_command=None,
              strainrange=1e-6,
              p_xx=0.0,
              p_yy=0.0,
              p_zz=0.0,
              p_xy=0.0,
              p_xz=0.0,
              p_yz=0.0,
              tol=1e-10,
              diverge_scale=3.):
    """
    Quickly refines static orthorhombic system by evaluating the elastic
    constants and the virial pressure.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    strainrange : float, optional
        The small strain value to apply when calculating the elastic
        constants (default is 1e-6).
    p_xx : float, optional
        The value to relax the x tensile pressure component to (default is
        0.0).
    p_yy : float, optional
        The value to relax the y tensile pressure component to (default is
        0.0).
    p_zz : float, optional
        The value to relax the z tensile pressure component to (default is
        0.0).
    tol : float, optional
        The relative tolerance used to determine if the lattice constants have
        converged (default is 1e-10).
    diverge_scale : float, optional
        Factor to identify if the system's dimensions have diverged.  Divergence
        is identified if either any current box dimension is greater than the
        original dimension multiplied by diverge_scale, or if any current box
        dimension is less than the original dimension divided by diverge_scale.
        (Default is 3.0).
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'a_lat'** (*float*) - The relaxed a lattice constant.
        - **'b_lat'** (*float*) - The relaxed b lattice constant.
        - **'c_lat'** (*float*) - The relaxed c lattice constant.
        - **'alpha_lat'** (*float*) - The alpha lattice angle.
        - **'beta_lat'** (*float*) - The beta lattice angle.
        - **'gamma_lat'** (*float*) - The gamma lattice angle.
        - **'E_coh'** (*float*) - The cohesive energy of the relaxed system.
        - **'stress'** (*numpy.array*) - The measured stress state of the
          relaxed system.
        - **'C_elastic'** (*atomman.ElasticConstants*) - The relaxed system's
          elastic constants.
        - **'system_relaxed'** (*atomman.System*) - The relaxed system.
    
    Raises
    ------
    RuntimeError
        If system diverges or no convergence reached after 100 cycles.
    """

    # Flag for if values have converged
    converged = False

    # Define current and old systems
    system_current = deepcopy(system)
    system_old = None

    system.dump('atom_dump', f='initial.dump')

    for cycle in range(100):

        # Run LAMMPS and evaluate results based on system_old
        results = calc_cij(lammps_command,
                           system_current,
                           potential,
                           mpi_command=mpi_command,
                           p_xx=p_xx,
                           p_yy=p_yy,
                           p_zz=p_zz,
                           strainrange=strainrange,
                           cycle=cycle)
        system_new = results['system_new']

        # Compare new and current to test for convergence
        if np.allclose(system_new.box.vects,
                       system_current.box.vects,
                       rtol=tol,
                       atol=0):
            converged = True
            break

        # Compare old and new to test for double-value convergence
        elif system_old is not None and np.allclose(
                system_new.box.vects, system_old.box.vects, rtol=tol, atol=0):
            # Update current to average of old and new
            system_current.box_set(
                a=(system_new.box.a + system_old.box.a) / 2.,
                b=(system_new.box.b + system_old.box.b) / 2.,
                c=(system_new.box.c + system_old.box.c) / 2.,
                scale=True)
            # Calculate Cij for the averaged system
            results = calc_cij(lammps_command,
                               system_current,
                               potential,
                               mpi_command=mpi_command,
                               p_xx=p_xx,
                               p_yy=p_yy,
                               p_zz=p_zz,
                               strainrange=strainrange,
                               cycle=cycle + 1)
            system_new = results['system_new']
            converged = True
            break

        # Test for divergence
        elif system_new.box.a < system.box.a / diverge_scale:
            raise RuntimeError('Divergence of box dimensions')
        elif system_new.box.a > system.box.a * diverge_scale:
            raise RuntimeError('Divergence of box dimensions')
        elif system_new.box.b < system.box.b / diverge_scale:
            raise RuntimeError('Divergence of box dimensions')
        elif system_new.box.b > system.box.b * diverge_scale:
            raise RuntimeError('Divergence of box dimensions')
        elif system_new.box.c < system.box.c / diverge_scale:
            raise RuntimeError('Divergence of box dimensions')
        elif system_new.box.c > system.box.c * diverge_scale:
            raise RuntimeError('Divergence of box dimensions')
        elif results['E_coh'] == 0.0:
            raise RuntimeError('Divergence: cohesive energy is 0')

        # If not converged or diverged, current -> old and new -> current
        else:
            system_old, system_current = system_current, system_new

    # Return values when converged
    if converged:
        system_new.dump('atom_dump', f='final.dump')

        # Build results_dict
        results_dict = {}
        results_dict['dumpfile_initial'] = 'initial.dump'
        results_dict['symbols_initial'] = system.symbols
        results_dict['dumpfile_final'] = 'final.dump'
        results_dict['symbols_final'] = system.symbols

        results_dict['lx'] = system_new.box.lx
        results_dict['ly'] = system_new.box.ly
        results_dict['lz'] = system_new.box.lz
        results_dict['xy'] = system_new.box.xy
        results_dict['xz'] = system_new.box.xz
        results_dict['yz'] = system_new.box.yz

        results_dict['E_coh'] = results['E_coh']
        results_dict['measured_pxx'] = results['measured_pxx']
        results_dict['measured_pyy'] = results['measured_pyy']
        results_dict['measured_pzz'] = results['measured_pzz']
        results_dict['measured_pxy'] = results['measured_pxy']
        results_dict['measured_pxz'] = results['measured_pxz']
        results_dict['measured_pyz'] = results['measured_pyz']

        return results_dict
    else:
        raise RuntimeError('Failed to converge after 100 cycles')
Example #12
0
def calc_cij(lammps_command,
             system,
             potential,
             mpi_command=None,
             p_xx=0.0,
             p_yy=0.0,
             p_zz=0.0,
             strainrange=1e-6,
             cycle=0):
    """
    Runs cij.in LAMMPS script to evaluate Cij, and E_coh of the current system,
    and define a new system with updated box dimensions to test.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    strainrange : float, optional
        The small strain value to apply when calculating the elastic
        constants (default is 1e-6).
    p_xx : float, optional
        The value to relax the x tensile pressure component to (default is
        0.0).
    p_yy : float, optional
        The value to relax the y tensile pressure component to (default is
        0.0).
    p_zz : float, optional
        The value to relax the z tensile pressure component to (default is
        0.0).
    cycle : int, optional
        Indicates the iteration cycle of quick_a_Cij().  This is used to
        uniquely save the LAMMPS input and output files.
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'E_coh'** (*float*) - The cohesive energy of the supplied system.
        - **'stress'** (*numpy.array*) - The measured stress state of the
          supplied system.
        - **'C_elastic'** (*atomman.ElasticConstants*) - The supplied system's
          elastic constants.
        - **'system_new'** (*atomman.System*) - System with updated box
          dimensions.
    
    Raises
    ------
    RuntimeError
        If any of the new box dimensions are less than zero.
    """

    # Get lammps units
    lammps_units = lmp.style.unit(potential.units)

    # Define lammps variables
    lammps_variables = {}
    system_info = system.dump('atom_data',
                              f='init' + str(cycle) + '.dat',
                              units=potential.units,
                              atom_style=potential.atom_style)
    lammps_variables['atomman_system_info'] = system_info
    lammps_variables['atomman_pair_info'] = potential.pair_info(system.symbols)
    lammps_variables['delta'] = strainrange
    lammps_variables['steps'] = 2

    # Write lammps input script
    template_file = 'cij.template'
    lammps_script = 'cij.in'
    with open(template_file) as f:
        template = f.read()
    with open(lammps_script, 'w') as f:
        f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))

    # Run lammps
    output = lmp.run(lammps_command,
                     lammps_script,
                     mpi_command=mpi_command,
                     return_style='model')
    shutil.move('log.lammps', 'cij-' + str(cycle) + '-log.lammps')

    # Extract LAMMPS thermo data. Each term ranges i=0-12 where i=0 is undeformed
    # The remaining values are for -/+ strain pairs in the six unique directions
    lx = uc.set_in_units(np.array(output.finds('Lx')), lammps_units['length'])
    ly = uc.set_in_units(np.array(output.finds('Ly')), lammps_units['length'])
    lz = uc.set_in_units(np.array(output.finds('Lz')), lammps_units['length'])
    xy = uc.set_in_units(np.array(output.finds('Xy')), lammps_units['length'])
    xz = uc.set_in_units(np.array(output.finds('Xz')), lammps_units['length'])
    yz = uc.set_in_units(np.array(output.finds('Yz')), lammps_units['length'])

    pxx = uc.set_in_units(np.array(output.finds('Pxx')),
                          lammps_units['pressure'])
    pyy = uc.set_in_units(np.array(output.finds('Pyy')),
                          lammps_units['pressure'])
    pzz = uc.set_in_units(np.array(output.finds('Pzz')),
                          lammps_units['pressure'])
    pxy = uc.set_in_units(np.array(output.finds('Pxy')),
                          lammps_units['pressure'])
    pxz = uc.set_in_units(np.array(output.finds('Pxz')),
                          lammps_units['pressure'])
    pyz = uc.set_in_units(np.array(output.finds('Pyz')),
                          lammps_units['pressure'])

    pe = uc.set_in_units(
        np.array(output.finds('PotEng')) / system.natoms,
        lammps_units['energy'])

    # Set the six non-zero strain values
    strains = np.array([(lx[2] - lx[1]) / lx[0], (ly[4] - ly[3]) / ly[0],
                        (lz[6] - lz[5]) / lz[0], (yz[8] - yz[7]) / lz[0],
                        (xz[10] - xz[9]) / lz[0], (xy[12] - xy[11]) / ly[0]])

    # Calculate cij using stress changes associated with each non-zero strain
    cij = np.empty((6, 6))
    for i in range(6):
        delta_stress = np.array([
            pxx[2 * i + 1] - pxx[2 * i + 2], pyy[2 * i + 1] - pyy[2 * i + 2],
            pzz[2 * i + 1] - pzz[2 * i + 2], pyz[2 * i + 1] - pyz[2 * i + 2],
            pxz[2 * i + 1] - pxz[2 * i + 2], pxy[2 * i + 1] - pxy[2 * i + 2]
        ])

        cij[i] = delta_stress / strains[i]

    for i in range(6):
        for j in range(i):
            cij[i, j] = cij[j, i] = (cij[i, j] + cij[j, i]) / 2

    C = am.ElasticConstants(Cij=cij)

    S = C.Sij

    # Extract the current stress state
    stress = -1 * np.array([[pxx[0], pxy[0], pxz[0]], [pxy[0], pyy[0], pyz[0]],
                            [pxz[0], pyz[0], pzz[0]]])

    s_xx = stress[0, 0] + p_xx
    s_yy = stress[1, 1] + p_yy
    s_zz = stress[2, 2] + p_zz

    new_a = system.box.a / (S[0, 0] * s_xx + S[0, 1] * s_yy + S[0, 2] * s_zz +
                            1)
    new_b = system.box.b / (S[1, 0] * s_xx + S[1, 1] * s_yy + S[1, 2] * s_zz +
                            1)
    new_c = system.box.c / (S[2, 0] * s_xx + S[2, 1] * s_yy + S[2, 2] * s_zz +
                            1)

    if new_a <= 0 or new_b <= 0 or new_c <= 0:
        raise RuntimeError('Divergence of box dimensions to <= 0')

    system_new = deepcopy(system)
    system_new.box_set(a=new_a, b=new_b, c=new_c, scale=True)

    results_dict = {}
    results_dict['E_coh'] = pe[0]
    results_dict['system_new'] = system_new
    results_dict['measured_pxx'] = pxx[0]
    results_dict['measured_pyy'] = pyy[0]
    results_dict['measured_pzz'] = pzz[0]
    results_dict['measured_pxy'] = pxy[0]
    results_dict['measured_pxz'] = pxz[0]
    results_dict['measured_pyz'] = pyz[0]
    return results_dict
def elastic_constants_static(lammps_command, system, potential, mpi_command=None,
                             strainrange=1e-6, etol=0.0, ftol=0.0, maxiter=10000,
                             maxeval=100000, dmax=uc.set_in_units(0.01, 'angstrom')):
    """
    Repeatedly runs the ELASTIC example distributed with LAMMPS until box
    dimensions converge within a tolerance.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    strainrange : float, optional
        The small strain value to apply when calculating the elastic
        constants (default is 1e-6).
    etol : float, optional
        The energy tolerance for the structure minimization. This value is
        unitless. (Default is 0.0).
    ftol : float, optional
        The force tolerance for the structure minimization. This value is in
        units of force. (Default is 0.0).
    maxiter : int, optional
        The maximum number of minimization iterations to use (default is 10000).
    maxeval : int, optional
        The maximum number of minimization evaluations to use (default is 
        100000).
    dmax : float, optional
        The maximum distance in length units that any atom is allowed to relax
        in any direction during a single minimization iteration (default is
        0.01 Angstroms).
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'a_lat'** (*float*) - The relaxed a lattice constant.
        - **'b_lat'** (*float*) - The relaxed b lattice constant.
        - **'c_lat'** (*float*) - The relaxed c lattice constant.
        - **'alpha_lat'** (*float*) - The alpha lattice angle.
        - **'beta_lat'** (*float*) - The beta lattice angle.
        - **'gamma_lat'** (*float*) - The gamma lattice angle.
        - **'E_coh'** (*float*) - The cohesive energy of the relaxed system.
        - **'stress'** (*numpy.array*) - The measured stress state of the
          relaxed system.
        - **'C_elastic'** (*atomman.ElasticConstants*) - The relaxed system's
          elastic constants.
        - **'system_relaxed'** (*atomman.System*) - The relaxed system.
    """
    
    # Convert hexagonal cells to orthorhombic to avoid LAMMPS tilt issues
    if am.tools.ishexagonal(system.box):
        system = system.rotate([[2,-1,-1,0], [0, 1, -1, 0], [0,0,0,1]])
    
    # Get lammps units
    lammps_units = lmp.style.unit(potential.units)
    
    # Get lammps version date
    lammps_date = lmp.checkversion(lammps_command)['date']
    
    # Define lammps variables
    lammps_variables = {}
    system_info = system.dump('atom_data', f='init.dat',
                              units=potential.units,
                              atom_style=potential.atom_style)
    lammps_variables['atomman_system_info'] = system_info
    lammps_variables['atomman_pair_info'] = potential.pair_info(system.symbols)
    lammps_variables['strainrange'] = strainrange
    lammps_variables['etol'] = etol
    lammps_variables['ftol'] = uc.get_in_units(ftol, lammps_units['force'])
    lammps_variables['maxiter'] = maxiter
    lammps_variables['maxeval'] = maxeval
    lammps_variables['dmax'] = uc.get_in_units(dmax, lammps_units['length'])
    
    # Fill in template files
    template_file = 'cij.template'
    lammps_script = 'cij.in'
    with open(template_file) as f:
        template = f.read()
    with open(lammps_script, 'w') as f:
        f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))
    template_file2 = 'potential.template'
    lammps_script2 = 'potential.in'
    with open(template_file2) as f:
        template = f.read()
    with open(lammps_script2, 'w') as f:
        f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))
    
    # Run LAMMPS
    output = lmp.run(lammps_command, lammps_script, mpi_command)
    
    # Pull out initial state
    thermo = output.simulations[0]['thermo']
    pxx0 = uc.set_in_units(thermo.Pxx.values[-1], lammps_units['pressure'])
    pyy0 = uc.set_in_units(thermo.Pyy.values[-1], lammps_units['pressure'])
    pzz0 = uc.set_in_units(thermo.Pzz.values[-1], lammps_units['pressure'])
    pyz0 = uc.set_in_units(thermo.Pyz.values[-1], lammps_units['pressure'])
    pxz0 = uc.set_in_units(thermo.Pxz.values[-1], lammps_units['pressure'])
    pxy0 = uc.set_in_units(thermo.Pxy.values[-1], lammps_units['pressure'])
    
    # Negative strains
    cij_n = np.empty((6,6))
    for i in range(6):
        j = 1 + i * 2
        # Pull out strained state
        thermo = output.simulations[j]['thermo']
        pxx = uc.set_in_units(thermo.Pxx.values[-1], lammps_units['pressure'])
        pyy = uc.set_in_units(thermo.Pyy.values[-1], lammps_units['pressure'])
        pzz = uc.set_in_units(thermo.Pzz.values[-1], lammps_units['pressure'])
        pyz = uc.set_in_units(thermo.Pyz.values[-1], lammps_units['pressure'])
        pxz = uc.set_in_units(thermo.Pxz.values[-1], lammps_units['pressure'])
        pxy = uc.set_in_units(thermo.Pxy.values[-1], lammps_units['pressure'])
        
        # Calculate cij_n using stress changes
        cij_n[i] = np.array([pxx - pxx0, pyy - pyy0, pzz - pzz0,
                             pyz - pyz0, pxz - pxz0, pxy - pxy0])/ strainrange
    
    # Positive strains
    cij_p = np.empty((6,6))
    for i in range(6):
        j = 2 + i * 2
        # Pull out strained state
        thermo = output.simulations[j]['thermo']
        pxx = uc.set_in_units(thermo.Pxx.values[-1], lammps_units['pressure'])
        pyy = uc.set_in_units(thermo.Pyy.values[-1], lammps_units['pressure'])
        pzz = uc.set_in_units(thermo.Pzz.values[-1], lammps_units['pressure'])
        pyz = uc.set_in_units(thermo.Pyz.values[-1], lammps_units['pressure'])
        pxz = uc.set_in_units(thermo.Pxz.values[-1], lammps_units['pressure'])
        pxy = uc.set_in_units(thermo.Pxy.values[-1], lammps_units['pressure'])
        
        # Calculate cij_p using stress changes
        cij_p[i] = -np.array([pxx - pxx0, pyy - pyy0, pzz - pzz0,
                              pyz - pyz0, pxz - pxz0, pxy - pxy0])/ strainrange
    
    # Average symmetric values
    cij = (cij_n + cij_p) / 2
    for i in range(6):
        for j in range(i):
            cij[i,j] = cij[j,i] = (cij[i,j] + cij[j,i]) / 2
    
    # Define results_dict
    results_dict = {}
    results_dict['raw_cij_negative'] = cij_n
    results_dict['raw_cij_positive'] = cij_p
    results_dict['C'] = am.ElasticConstants(Cij=cij)
    
    return results_dict
Example #14
0
def e_vs_r(lammps_command, system, potential,
           mpi_command=None, ucell=None, 
           rmin=uc.set_in_units(2.0, 'angstrom'), 
           rmax=uc.set_in_units(6.0, 'angstrom'), rsteps=200):
    """
    Performs a cohesive energy scan over a range of interatomic spaces, r.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    ucell : atomman.System, optional
        The fundamental unit cell correspodning to system.  This is used to
        convert system dimensions to cell dimensions. If not given, ucell will
        be taken as system.
    rmin : float, optional
        The minimum r spacing to use (default value is 2.0 angstroms).
    rmax : float, optional
        The maximum r spacing to use (default value is 6.0 angstroms).
    rsteps : int, optional
        The number of r spacing steps to evaluate (default value is 200).
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'r_values'** (*numpy.array of float*) - All interatomic spacings,
          r, explored.
        - **'a_values'** (*numpy.array of float*) - All unit cell a lattice
          constants corresponding to the values explored.
        - **'Ecoh_values'** (*numpy.array of float*) - The computed cohesive
          energies for each r value.
        - **'min_cell'** (*list of atomman.System*) - Systems corresponding to
          the minima identified in the Ecoh_values.
    """
    
    # Make system a deepcopy of itself (protect original from changes)
    system = deepcopy(system)
    
    # Set ucell = system if ucell not given
    if ucell is None:
        ucell = system
    
    # Calculate the r/a ratio for the unit cell
    r_a = r_a_ratio(ucell)
    
    # Get ratios of lx, ly, and lz of system relative to a of ucell
    lx_a = system.box.a / ucell.box.a
    ly_a = system.box.b / ucell.box.a
    lz_a = system.box.c / ucell.box.a
    alpha = system.box.alpha
    beta =  system.box.beta
    gamma = system.box.gamma
 
    # Build lists of values
    r_values = np.linspace(rmin, rmax, rsteps)
    a_values = r_values / r_a
    Ecoh_values = np.empty(rsteps)
    
    # Loop over values
    for i in range(rsteps):
        
        # Rescale system's box
        a = a_values[i]
        system.box_set(a = a * lx_a, 
                       b = a * ly_a, 
                       c = a * lz_a, 
                       alpha=alpha, beta=beta, gamma=gamma, scale=True)
        
        # Get lammps units
        lammps_units = lmp.style.unit(potential.units)
        
        # Define lammps variables
        lammps_variables = {}
        system_info = system.dump('atom_data', f='atom.dat',
                                  units=potential.units,
                                  atom_style=potential.atom_style)
        lammps_variables['atomman_system_info'] = system_info
        lammps_variables['atomman_pair_info'] = potential.pair_info(system.symbols)
        
        # Write lammps input script
        template_file = 'run0.template'
        lammps_script = 'run0.in'
        with open(template_file) as f:
            template = f.read()
        with open(lammps_script, 'w') as f:
            f.write(iprPy.tools.filltemplate(template, lammps_variables,
                                             '<', '>'))
        
        # Run lammps and extract data
        output = lmp.run(lammps_command, lammps_script, mpi_command)
        
        thermo = output.simulations[0]['thermo']
        
        if output.lammps_date < datetime.date(2016, 8, 1):
            Ecoh_values[i] = uc.set_in_units(thermo.peatom.values[-1],
                                             lammps_units['energy'])
        else:
            Ecoh_values[i] = uc.set_in_units(thermo.v_peatom.values[-1],
                                             lammps_units['energy'])
        
        # Rename log.lammps
        shutil.move('log.lammps', 'run0-'+str(i)+'-log.lammps')
    
    # Find unit cell systems at the energy minimums
    min_cells = []
    for i in range(1, rsteps - 1):
        if (Ecoh_values[i] < Ecoh_values[i-1]
            and Ecoh_values[i] < Ecoh_values[i+1]):
            a = a_values[i]
            cell = deepcopy(ucell)
            cell.box_set(a = a,
                         b = a * ucell.box.b / ucell.box.a,
                         c = a * ucell.box.c / ucell.box.a, 
                         alpha=alpha, beta=beta, gamma=gamma, scale=True)
            min_cells.append(cell)
    
    # Collect results
    results_dict = {}
    results_dict['r_values'] = r_values
    results_dict['a_values'] = a_values
    results_dict['Ecoh_values'] = Ecoh_values
    results_dict['min_cell'] = min_cells
    
    return results_dict
Example #15
0
def e_vs_r(lammps_command,
           system,
           potential,
           mpi_command=None,
           ucell=None,
           rmin=uc.set_in_units(2.0, 'angstrom'),
           rmax=uc.set_in_units(6.0, 'angstrom'),
           rsteps=200):
    """
    Performs a cohesive energy scan over a range of interatomic spaces, r.
    
    Parameters
    ----------
    lammps_command :str
        Command for running LAMMPS.
    system : atomman.System
        The system to perform the calculation on.
    potential : atomman.lammps.Potential
        The LAMMPS implemented potential to use.
    mpi_command : str, optional
        The MPI command for running LAMMPS in parallel.  If not given, LAMMPS
        will run serially.
    ucell : atomman.System, optional
        The fundamental unit cell correspodning to system.  This is used to
        convert system dimensions to cell dimensions. If not given, ucell will
        be taken as system.
    rmin : float, optional
        The minimum r spacing to use (default value is 2.0 angstroms).
    rmax : float, optional
        The maximum r spacing to use (default value is 6.0 angstroms).
    rsteps : int, optional
        The number of r spacing steps to evaluate (default value is 200).
    
    Returns
    -------
    dict
        Dictionary of results consisting of keys:
        
        - **'r_values'** (*numpy.array of float*) - All interatomic spacings,
          r, explored.
        - **'a_values'** (*numpy.array of float*) - All unit cell a lattice
          constants corresponding to the values explored.
        - **'Ecoh_values'** (*numpy.array of float*) - The computed cohesive
          energies for each r value.
        - **'min_cell'** (*list of atomman.System*) - Systems corresponding to
          the minima identified in the Ecoh_values.
    """

    # Make system a deepcopy of itself (protect original from changes)
    system = deepcopy(system)

    # Set ucell = system if ucell not given
    if ucell is None:
        ucell = system

    # Calculate the r/a ratio for the unit cell
    r_a = r_a_ratio(ucell)

    # Get ratios of lx, ly, and lz of system relative to a of ucell
    lx_a = system.box.a / ucell.box.a
    ly_a = system.box.b / ucell.box.a
    lz_a = system.box.c / ucell.box.a
    alpha = system.box.alpha
    beta = system.box.beta
    gamma = system.box.gamma

    # Build lists of values
    r_values = np.linspace(rmin, rmax, rsteps)
    a_values = r_values / r_a
    Ecoh_values = np.empty(rsteps)

    # Loop over values
    for i in range(rsteps):

        # Rescale system's box
        a = a_values[i]
        system.box_set(a=a * lx_a,
                       b=a * ly_a,
                       c=a * lz_a,
                       alpha=alpha,
                       beta=beta,
                       gamma=gamma,
                       scale=True)

        # Get lammps units
        lammps_units = lmp.style.unit(potential.units)

        # Define lammps variables
        lammps_variables = {}
        system_info = system.dump('atom_data',
                                  f='atom.dat',
                                  units=potential.units,
                                  atom_style=potential.atom_style)
        lammps_variables['atomman_system_info'] = system_info
        lammps_variables['atomman_pair_info'] = potential.pair_info(
            system.symbols)

        # Write lammps input script
        template_file = 'run0.template'
        lammps_script = 'run0.in'
        with open(template_file) as f:
            template = f.read()
        with open(lammps_script, 'w') as f:
            f.write(
                iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))

        # Run lammps and extract data
        output = lmp.run(lammps_command, lammps_script, mpi_command)

        thermo = output.simulations[0]['thermo']

        if output.lammps_date < datetime.date(2016, 8, 1):
            Ecoh_values[i] = uc.set_in_units(thermo.peatom.values[-1],
                                             lammps_units['energy'])
        else:
            Ecoh_values[i] = uc.set_in_units(thermo.v_peatom.values[-1],
                                             lammps_units['energy'])

        # Rename log.lammps
        shutil.move('log.lammps', 'run0-' + str(i) + '-log.lammps')

    # Find unit cell systems at the energy minimums
    min_cells = []
    for i in range(1, rsteps - 1):
        if (Ecoh_values[i] < Ecoh_values[i - 1]
                and Ecoh_values[i] < Ecoh_values[i + 1]):
            a = a_values[i]
            cell = deepcopy(ucell)
            cell.box_set(a=a,
                         b=a * ucell.box.b / ucell.box.a,
                         c=a * ucell.box.c / ucell.box.a,
                         alpha=alpha,
                         beta=beta,
                         gamma=gamma,
                         scale=True)
            min_cells.append(cell)

    # Collect results
    results_dict = {}
    results_dict['r_values'] = r_values
    results_dict['a_values'] = a_values
    results_dict['Ecoh_values'] = Ecoh_values
    results_dict['min_cell'] = min_cells

    return results_dict