Ejemplo n.º 1
0
    def test_init(self):
        filepath = os.path.join(test_dir, 'CHGCAR.nospin')
        chg = Chgcar.from_file(filepath)
        self.assertAlmostEqual(chg.get_integrated_diff(0, 2)[0, 1], 0)
        filepath = os.path.join(test_dir, 'CHGCAR.spin')
        chg = Chgcar.from_file(filepath)
        self.assertAlmostEqual(chg.get_integrated_diff(0, 1)[0, 1],
                               -0.0043896932237534022)
        #test sum
        chg += chg
        self.assertAlmostEqual(chg.get_integrated_diff(0, 1)[0, 1],
                               -0.0043896932237534022 * 2)

        filepath = os.path.join(test_dir, 'CHGCAR.noncubic')
        chg = Chgcar.from_file(filepath)
        ans = [0.221423, 0.462059, 0.470549, 0.434775, 0.860738, 2.1717482]
        myans = chg.get_integrated_diff(0, 3, 6)
        self.assertTrue(np.allclose(myans[:, 1], ans))
Ejemplo n.º 2
0
    def test_init(self):
        filepath = os.path.join(test_dir, 'CHGCAR.nospin')
        chg = Chgcar.from_file(filepath)
        self.assertAlmostEqual(chg.get_integrated_diff(0, 2)[0, 1], 0)
        filepath = os.path.join(test_dir, 'CHGCAR.spin')
        chg = Chgcar.from_file(filepath)
        self.assertAlmostEqual(chg.get_integrated_diff(0, 1)[0, 1],
                               -0.0043896932237534022)
        #test sum
        chg += chg
        self.assertAlmostEqual(chg.get_integrated_diff(0, 1)[0, 1],
                               -0.0043896932237534022 * 2)

        filepath = os.path.join(test_dir, 'CHGCAR.Fe3O4')
        chg = Chgcar.from_file(filepath)
        ans = [1.93313368, 3.91201473, 4.11858277, 4.1240093, 4.10634989,
               3.38864822]
        myans = chg.get_integrated_diff(0, 3, 6)
        self.assertTrue(np.allclose(myans[:, 1], ans))
Ejemplo n.º 3
0
    def test_init(self):
        filepath = os.path.join(test_dir, 'CHGCAR.nospin')
        chg = Chgcar.from_file(filepath)
        self.assertAlmostEqual(chg.get_integrated_diff(0, 2)[0, 1], 0)
        filepath = os.path.join(test_dir, 'CHGCAR.spin')
        chg = Chgcar.from_file(filepath)
        self.assertAlmostEqual(chg.get_integrated_diff(0, 1)[0, 1],
                               -0.0043896932237534022)
        #test sum
        chg += chg
        self.assertAlmostEqual(chg.get_integrated_diff(0, 1)[0, 1],
                               -0.0043896932237534022 * 2)

        filepath = os.path.join(test_dir, 'CHGCAR.Fe3O4')
        chg = Chgcar.from_file(filepath)
        ans = [1.93313368, 3.91201473, 4.11858277, 4.1240093, 4.10634989,
               3.38864822]
        myans = chg.get_integrated_diff(0, 3, 6)
        self.assertTrue(np.allclose(myans[:, 1], ans))
Ejemplo n.º 4
0
 def __init__(self, chgcar_filename, potcar_filename=None):
     """
     Args:
         chgcar_filename:
             The filename of the CHGCAR.
         potcar_filename:
             Optional: the filename of the corresponding POTCAR file. Used
             for calculating the charge transfer. If None, the
             get_charge_transfer method will raise a ValueError.
     """
     temp_dir = tempfile.mkdtemp()
     self.chgcar = Chgcar.from_file(chgcar_filename)
     self.potcar = Potcar.from_file(potcar_filename) \
         if potcar_filename is not None else None
     self.natoms = self.chgcar.poscar.natoms
     try:
         shutil.copy(chgcar_filename, os.path.join(temp_dir, "CHGCAR"))
         current_dir = os.getcwd()
         os.chdir(temp_dir)
         rs = subprocess.Popen(["bader", "CHGCAR"],
                               stdout=subprocess.PIPE,
                               stdin=subprocess.PIPE,
                               close_fds=True)
         rs.communicate()
         data = []
         with open("ACF.dat") as f:
             raw = f.readlines()
             headers = [s.lower() for s in raw.pop(0).split()]
             raw.pop(0)
             while True:
                 l = raw.pop(0).strip()
                 if l.startswith("-"):
                     break
                 vals = map(float, l.split()[1:])
                 data.append(dict(zip(headers[1:], vals)))
             for l in raw:
                 toks = l.strip().split(":")
                 if toks[0] == "VACUUM CHARGE":
                     self.vacuum_charge = float(toks[1])
                 elif toks[0] == "VACUUM VOLUME":
                     self.vacuum_volume = float(toks[1])
                 elif toks[0] == "NUMBER OF ELECTRONS":
                     self.nelectrons = float(toks[1])
         self.data = data
         os.chdir(current_dir)
     except Exception as ex:
         print str(ex)
     finally:
         shutil.rmtree(temp_dir)
Ejemplo n.º 5
0
 def __init__(self, chgcar_filename, potcar_filename=None):
     """
     Args:
         chgcar_filename:
             The filename of the CHGCAR.
         potcar_filename:
             Optional: the filename of the corresponding POTCAR file. Used
             for calculating the charge transfer. If None, the
             get_charge_transfer method will raise a ValueError.
     """
     temp_dir = tempfile.mkdtemp()
     self.chgcar = Chgcar.from_file(chgcar_filename)
     self.potcar = Potcar.from_file(potcar_filename) \
         if potcar_filename is not None else None
     self.natoms = self.chgcar.poscar.natoms
     try:
         shutil.copy(chgcar_filename, os.path.join(temp_dir, "CHGCAR"))
         current_dir = os.getcwd()
         os.chdir(temp_dir)
         rs = subprocess.Popen(["bader", "CHGCAR"],
                               stdout=subprocess.PIPE,
                               stdin=subprocess.PIPE, close_fds=True)
         rs.communicate()
         data = []
         with open("ACF.dat") as f:
             raw = f.readlines()
             headers = [s.lower() for s in raw.pop(0).split()]
             raw.pop(0)
             while True:
                 l = raw.pop(0).strip()
                 if l.startswith("-"):
                     break
                 vals = map(float, l.split()[1:])
                 data.append(dict(zip(headers[1:], vals)))
             for l in raw:
                 toks = l.strip().split(":")
                 if toks[0] == "VACUUM CHARGE":
                     self.vacuum_charge = float(toks[1])
                 elif toks[0] == "VACUUM VOLUME":
                     self.vacuum_volume = float(toks[1])
                 elif toks[0] == "NUMBER OF ELECTRONS":
                     self.nelectrons = float(toks[1])
         self.data = data
         os.chdir(current_dir)
     except Exception as ex:
         print str(ex)
     finally:
         shutil.rmtree(temp_dir)
Ejemplo n.º 6
0
    parser = argparse.ArgumentParser()
    parser.add_argument("-s1", type=str, default="", help="POSCAR for endpoint 1")
    parser.add_argument("-s2", type=str, default="", help="POSCAR for endpoint 2")
    parser.add_argument("-chg", type=str, default="", help="CHGCAR for interpolation (if not specified, use free volume metric)")
    parser.add_argument("-o", type=str, default="", help="Output POSCAR with images superimposed")
    args = parser.parse_args()
    s1 = Poscar.from_file(args.s1).structure
    s2 = Poscar.from_file(args.s2).structure

    # Find diffusing species site indices
    mg_sites = []
    for site_i, site in enumerate(s1.sites):
        if site.specie == Element("Mg"):
            mg_sites.append(site_i)

    # Interpolate
    if args.chg != "":
        print("Using CHGCAR potential mode.")
        chg = Chgcar.from_file(args.chg)
        pf = NEBPathfinder(s1, s2, relax_sites=mg_sites, v=ChgcarPotential(chg).get_v(), n_images=10)
    else:
        print("Using free volume mode")
        print("WARNING: This mode is not optimized and a lot of numerical parameters are not good, so the output might be bad!")
        pf = NEBPathfinder(s1, s2, relax_sites=mg_sites, v=FreeVolumePotential(s1, (40,40,40)).get_v(), n_images=10, h=0.001)

    # Get images
    images = pf.images

    # Plot path
    pf.plot_images(args.o)
Ejemplo n.º 7
0
def main():
    # Set default variables
    options = dict(
        spin_channel='total',
        center_cartesian=[0., 0., 0.],
        x_axis=[1., 0., 0.],
        y_axis=[0., 0., 1.],
        x_repeat=1,  # approximate number of unit cells to interpolate
        y_repeat=1,  # approximate number of unit cells to interpolate
        x_res=500,  # points to interpolate
        y_res=500,  # points to interpolate
        format='xyz',
    )
    options.update(**vars(_build_parser().parse_args()))

    chg = Chgcar.from_file(options['filename'])
    structure = chg.structure
    rprim = chg.structure.lattice.matrix
    # Decide where to obtain center from
    # Cartesian option set
    center = options['center_direct']
    
    if options['center_cartesian'] is not None:
        # Convert from cartesian to reduced coordinates
        center = numpy.linalg.solve(rprim, options['center_cartesian']).tolist()
    
    # Atomic option is set
    if options['center_atom'] is not None:
        # Convert from atom number to reduced coordinates
        center = structure[options['center_atom']].frac_coords.tolist()
    
    plane = numpy.array([options['x_axis'], options['y_axis']], dtype=float)
    repeat = [options['x_repeat'], options['y_repeat']]
    res = [options['x_res'], options['y_res']]
    data = 0
    if options['spin_channel'] == 'total':
        data = chg.data['total']
    if options['spin_channel'] == 'up':
        data = chg.spin_data[Spin.up]
    if options['spin_channel'] == 'down':
        data = chg.spin_data[Spin.down]
    if options['spin_channel'] == 'polarization':
        data = chg.spin_data[Spin.up] - chg.spin_data[Spin.down]
    
    data /= structure.volume
    
    cs = plane_to_cs(plane)
    posinplane = numpy.dot(cs, numpy.dot(structure.frac_coords - center, rprim).T).T
    print('Atom positions in plane:')
    for i, pos in enumerate(posinplane):
        print('  %s: %f %f (z = %f)' % (structure[i].specie, pos[0], pos[1], pos[2]))
    
    # Interpolate
    x, y, z = interpolate_plane(data, rprim, plane=plane, center=center, dim=repeat, res=res)
    print('Cell density:\n  minimum: %f\n  maximum: %f' % (data.min(), data.max()))
    print('In-plane density:\n  minimum: %f\n  maximum: %f' % (z.min(), z.max()))
    print('Note: PAW calculations may contain negative values for the pseudo-density in the core regions.')
    
    suffix = '.gz' if options['gzip'] else ''
    
    if options['format'] == 'xyz':
        out = numpy.array([x.flatten(), y.flatten(), z.flatten()]).T
        with open('chg_%s_in_plane.csv%s' % (options['spin_channel'], suffix), 'w+') as f:
            numpy.savetxt(f, out, delimiter=',', header=' X, Y, Z')
            
    if options['format'] == 'matrix':
        with open('chg_%s_in_plane.mat%s' % (options['spin_channel'], suffix), 'w+') as f:
            numpy.savetxt(f, z, delimiter=' ', header=' Z matrix')

    if options['format'] == 'image':
        import matplotlib
        matplotlib.use('Agg')
        import matplotlib.pyplot as plt
        fig = plt.figure()
        plt.contour(x, y, z, options['contour'], colors='k')
        fig.savefig(options['out'])
Ejemplo n.º 8
0
                        default="",
                        help="Output POSCAR with images superimposed")
    args = parser.parse_args()
    s1 = Poscar.from_file(args.s1).structure
    s2 = Poscar.from_file(args.s2).structure

    # Find diffusing species site indices
    mg_sites = []
    for site_i, site in enumerate(s1.sites):
        if site.specie == Element("Mg"):
            mg_sites.append(site_i)

    # Interpolate
    if args.chg != "":
        print("Using CHGCAR potential mode.")
        chg = Chgcar.from_file(args.chg)
        pf = NEBPathfinder(s1,
                           s2,
                           relax_sites=mg_sites,
                           v=ChgcarPotential(chg).get_v(),
                           n_images=10)
    else:
        print("Using free volume mode")
        print(
            "WARNING: This mode is not optimized and a lot of numerical parameters are not good, so the output might be bad!"
        )
        pf = NEBPathfinder(s1,
                           s2,
                           relax_sites=mg_sites,
                           v=FreeVolumePotential(s1, (40, 40, 40)).get_v(),
                           n_images=10,