Package schrodinger :: Package application :: Package matsci :: Package nano :: Module slab
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Module slab

Classes [hide private]
  ParserWrapper
Manages the argparse module to parse user command line arguments.
  CheckInput
Manage checking user input.
  Surface
Manage the building of a surface model.
Functions [hide private]
list
get_lattice_parameters(astructure)
Return the a, b, c, alpha, beta, and gamma lattice parameters.
tuple
get_hkl(astructure)
Return an hkl Miller index triple for the given structure.
Variables [hide private]
  __doc__ = ...
  _version = '$Revision 0.0 $'
  XYZ_VECTORS = [numpy.array(transform.X_AXIS), numpy.array(tran...
  OUTFILE_SUFFIX = '-surface'
  H_INDEX_DEFAULT = 1
  K_INDEX_DEFAULT = 1
  L_INDEX_DEFAULT = 0
  MIN_IDX_DEFAULT = 0
  MAX_IDX_DEFAULT = 1
  H_INDEX_MIN_DEFAULT = 0
  H_INDEX_MAX_DEFAULT = 1
  K_INDEX_MIN_DEFAULT = 0
  K_INDEX_MAX_DEFAULT = 1
  L_INDEX_MIN_DEFAULT = 0
  L_INDEX_MAX_DEFAULT = 1
  ANGSTROM_DEFAULT = False
hash(x)
  NONE = None
hash(x)
  BOTTOM_DEFAULT = 0.0
  SLAB_THICKNESS_DEFAULT = 1.0
  VACUUM_THICKNESS_DEFAULT = 2.0
  NANOPARTICLE_SHAPE = 'parallelepiped'
  PARALLELEPIPED_SIDE_FACES = [1, 2, 4, 5]
  ALLOW_FRAGMENTS = False
hash(x)
  H_INDEX_KEY = 'i_matsci_h_Miller_idx'
  K_INDEX_KEY = 'i_matsci_k_Miller_idx'
  L_INDEX_KEY = 'i_matsci_l_Miller_idx'
  HKL_INDEX_KEYS = [H_INDEX_KEY, K_INDEX_KEY, L_INDEX_KEY]
  C_BUFFER_LEN_ANG = 5.0
Function Details [hide private]

get_lattice_parameters(astructure)

 

Return the a, b, c, alpha, beta, and gamma lattice parameters.

Parameters:
Returns: list
the a, b, c, alpha, beta, and gamma lattice parameters

get_hkl(astructure)

 

Return an hkl Miller index triple for the given structure. If any of the structure properties are missing then by convention return (0, 0, 1).

Parameters:
Returns: tuple
hkl Miller index triple

Variables Details [hide private]

__doc__

Value:
"""
Classes and functions to create surface models.

Copyright Schrodinger, LLC.  All rights reserved."""

XYZ_VECTORS

Value:
[numpy.array(transform.X_AXIS), numpy.array(transform.Y_AXIS), numpy.a\
rray(transform.Z_AXIS)]