# -*- coding: utf-8 -*-
from aiida.orm.data.array import ArrayData
from aiida.orm.calculation.inline import optional_inline
__copyright__ = u"Copyright (c), 2015, ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE (Theory and Simulation of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (NCCR MARVEL)), Switzerland and ROBERT BOSCH LLC, USA. All rights reserved."
__license__ = "MIT license, see LICENSE.txt file"
__version__ = "0.4.1"
__contributors__ = "Andrea Cepellotti, Andrius Merkys, Giovanni Pizzi"
@optional_inline
def _get_aiida_structure_inline(trajectory=None,parameters=None):
"""
Creates :py:class:`aiida.orm.data.structure.StructureData` using ASE.
:note: requires ASE module.
"""
from aiida.orm.data.structure import StructureData
kwargs = {}
if parameters is not None:
kwargs = parameters.get_dict()
return {'structure': trajectory.step_to_structure(**kwargs)}
[docs]class TrajectoryData(ArrayData):
"""
Stores a trajectory (a sequence of crystal structures with timestamps, and
possibly with velocities).
"""
def _internal_validate(self, steps, cells, symbols, positions, times, velocities):
"""
Internal function to validate the type and shape of the arrays. See
the documentation of py:meth:`.set_trajectory` for a description of the
valid shape and type of the parameters.
"""
import numpy
if not isinstance(steps, numpy.ndarray) or steps.dtype != int:
raise TypeError("TrajectoryData.steps must be a numpy array of integers")
if not isinstance(cells, numpy.ndarray) or cells.dtype != float:
raise TypeError("TrajectoryData.cells must be a numpy array of floats")
if not isinstance(symbols, numpy.ndarray):
raise TypeError("TrajectoryData.symbols must be a numpy array")
if any([not isinstance(i,basestring) for i in symbols]):
raise TypeError("TrajectoryData.symbols must be a numpy array of strings")
if not isinstance(positions, numpy.ndarray) or positions.dtype != float:
raise TypeError("TrajectoryData.positions must be a numpy array of floats")
if times is not None:
if not isinstance(times, numpy.ndarray) or times.dtype != float:
raise TypeError("TrajectoryData.times must be a numpy array of floats")
if velocities is not None:
if not isinstance(velocities, numpy.ndarray) or velocities.dtype != float:
raise TypeError("TrajectoryData.velocities must be a numpy array of floats, or None")
numsteps = steps.size
if steps.shape != (numsteps,):
raise ValueError("TrajectoryData.steps must be a 1d array")
if cells.shape != (numsteps,3,3):
raise ValueError("TrajectoryData.cells must have shape (s,3,3), "
"with s=number of steps")
numatoms = symbols.size
if symbols.shape != (numatoms,):
raise ValueError("TrajectoryData.symbols must be a 1d array")
if positions.shape != (numsteps,numatoms,3):
raise ValueError("TrajectoryData.positions must have shape (s,n,3), "
"with s=number of steps and n=number of symbols")
if times is not None:
if times.shape != (numsteps,):
raise ValueError("TrajectoryData.times must have shape (s,), "
"with s=number of steps")
if velocities is not None:
if velocities.shape != (numsteps,numatoms,3):
raise ValueError("TrajectoryData.velocities, if not None, must "
"have shape (s,n,3), "
"with s=number of steps and n=number of symbols")
[docs] def set_trajectory(self, steps, cells, symbols, positions, times=None, velocities=None):
r"""
Store the whole trajectory, after checking that types and dimensions
are correct.
Velocities are optional, if they are not passed, nothing is stored.
:param steps: integer array with dimension ``s``, where ``s`` is the
number of steps. Typically represents an internal counter
within the code. For instance, if you want to store a
trajectory with one step every 10, starting from step 65,
the array will be ``[65,75,85,...]``.
No checks are done on duplicate elements
or on the ordering, but anyway this array should be
sorted in ascending order, without duplicate elements.
If your code does not provide an internal counter, just
provide for instance ``arange(s)``.
:param cells: float array with dimension :math:`s \times 3 \times 3`,
where ``s`` is the
length of the ``steps`` array. Units are angstrom.
In particular,
``cells[i,j,k]`` is the ``k``-th component of the ``j``-th
cell vector at the time step with index ``i`` (identified
by step number ``step[i]`` and with timestamp ``times[i]``).
:param symbols: string array with dimension ``n``, where ``n`` is the
number of atoms (i.e., sites) in the structure.
The same array is used for each step. Normally, the string
should be a valid chemical symbol, but actually any unique
string works and can be used as the name of the atomic kind
(see also the :py:meth:`.step_to_structure()` method).
:param positions: float array with dimension :math:`s \times 3 \times 3`,
where ``s`` is the
length of the ``steps`` array and ``n`` is the length
of the ``symbols`` array. Units are angstrom.
In particular,
``positions[i,j,k]`` is the ``k``-th component of the
``j``-th atom (or site) in the structure at the time step
with index ``i`` (identified
by step number ``step[i]`` and with timestamp ``times[i]``).
:param times: if specified, float array with dimension ``s``, where
``s`` is the length of the ``steps`` array. Contains the
timestamp of each step in picoseconds (ps).
:param velocities: if specified, must be a float array with the same
dimensions of the ``positions`` array.
The array contains the velocities in the atoms.
.. todo :: Choose suitable units for velocities
"""
self._internal_validate(steps,cells,symbols,positions,times,velocities)
self.set_array('steps', steps)
self.set_array('cells', cells)
self.set_array('symbols', symbols)
self.set_array('positions', positions)
if times is not None:
self.set_array('times', times)
else:
# Delete times array, if it was present
try:
self.delete_array('times')
except KeyError:
pass
if velocities is not None:
self.set_array('velocities', velocities)
else:
# Delete velocities array, if it was present
try:
self.delete_array('velocities')
except KeyError:
pass
def _validate(self):
"""
Verify that the required arrays are present and that their type and
dimension are correct.
"""
#check dimensions, types
from aiida.common.exceptions import ValidationError
try:
self._internal_validate(self.get_steps(),
self.get_cells(),
self.get_symbols(),self.get_positions(),
self.get_times(),
self.get_velocities())
# Should catch TypeErrors, ValueErrors, and KeyErrors for missing arrays
except Exception as e:
raise ValidationError("The TrajectoryData did not validate. "
"Error: {} with message {}".format(
type(e).__name__, e.message))
@property
def numsteps(self):
"""
Return the number of stored steps, or zero if nothing has been stored yet.
"""
try:
return self.get_shape('steps')[0]
except (AttributeError, KeyError, IndexError):
return 0
@property
def numsites(self):
"""
Return the number of stored sites, or zero if nothing has been stored yet.
"""
try:
return self.get_shape('symbols')[0]
except (AttributeError, KeyError, IndexError):
return 0
[docs] def get_steps(self):
"""
Return the array of steps, if it has already been set.
:raises: KeyError if the trajectory has not been set yet.
"""
return self.get_array('steps')
[docs] def get_times(self):
"""
Return the array of times (in ps), if it has already been set.
:raises: KeyError if the trajectory has not been set yet.
"""
try:
return self.get_array('times')
except (AttributeError, KeyError):
return None
[docs] def get_cells(self):
"""
Return the array of cells, if it has already been set.
:raises: KeyError if the trajectory has not been set yet.
"""
return self.get_array('cells')
[docs] def get_symbols(self):
"""
Return the array of symbols, if it has already been set.
:raises: KeyError if the trajectory has not been set yet.
"""
return self.get_array('symbols')
[docs] def get_positions(self):
"""
Return the array of positions, if it has already been set.
:raises: KeyError if the trajectory has not been set yet.
"""
return self.get_array('positions')
[docs] def get_velocities(self):
"""
Return the array of velocities, if it has already been set.
.. note :: This function (differently from all other ``get_*``
functions, will not raise an exception if the velocities are not
set, but rather return ``None`` (both if no trajectory was not set yet,
and if it the trajectory was set but no velocities were specified).
"""
try:
return self.get_array('velocities')
except (AttributeError, KeyError):
return None
[docs] def get_step_index(self, step):
"""
Given a value for the step (i.e., a value among those of the ``steps``
array), return the array index of that step, that can be used in other
methods such as :py:meth:`.get_step_data` or
:py:meth:`.step_to_structure`.
Note that this function returns the first index found (i.e. if multiple
steps are present with the same value,
only the index of the first one is returned).
:raise: ValueError if no step with the given value is found.
"""
import numpy
try:
return numpy.where(self.get_steps()==step)[0][0]
except IndexError:
raise ValueError("{} not among the steps".format(step))
[docs] def get_step_data(self, index):
r"""
Return a tuple with all information concerning
the step with given index (0 is the first step, 1 the second step
and so on). If you know only the step value, use the :py:meth:`.get_step_index`
method to get the corresponding index.
If no velocities were specified, None is returned as the last element.
:return: A tuple in the format
``(step, time, cell, symbols, positions, velocities)``,
where ``step`` is an integer, ``time`` is a float, ``cell`` is a
:math:`3 \times 3` matrix, ``symbols`` is an array of length ``n``,
positions is a :math:`n \times 3` array, and velocities is either
``None`` or a :math:`n \times 3` array
:param index: The index of the step that you want to retrieve, from
0 to ``self.numsteps - 1``.
:raise: IndexError if you require an index beyond the limits.
:raise: KeyError if you did not store the trajectory yet.
"""
if index >= self.numsteps:
raise IndexError("You have only {} steps, but you are looking beyond"
" (index={})".format(self.numsteps,index))
vel = self.get_velocities()
if vel is not None:
vel = vel[index,:,:]
time = self.get_times()
if time is not None:
time = time[index]
return (self.get_steps()[index], time, self.get_cells()[index,:,:],
self.get_symbols(), self.get_positions()[index,:,:], vel)
[docs] def step_to_structure(self, index, custom_kinds=None):
"""
Return an AiiDA :py:class:`aiida.orm.data.structure.StructureData` node
(not stored yet!) with the coordinates of the given step, identified by
its index. If you know only the step value, use the :py:meth:`.get_step_index`
method to get the corresponding index.
.. note:: The periodic boundary conditions are always set to True.
:param index: The index of the step that you want to retrieve, from
0 to ``self.numsteps- 1``.
:param custom_kinds: (Optional) If passed must be a list of
:py:class:`aiida.orm.data.structure.Kind` objects. There must be one
kind object for each different string in the ``symbols`` array, with
``kind.name`` set to this string.
If this parameter is omitted, the automatic kind generation of AiiDA
:py:class:`aiida.orm.data.structure.StructureData` nodes is used,
meaning that the strings in the ``symbols`` array must be valid
chemical symbols.
"""
from aiida.orm.data.structure import StructureData, Kind, Site
# ignore step, time, and velocities
_, _, cell, symbols, positions, _ = self.get_step_data(index)
if custom_kinds is not None:
kind_names = []
for k in custom_kinds:
if not isinstance(k, Kind):
raise TypeError("Each element of the custom_kinds list must "
"be a aiida.orm.data.structure.Kind object")
kind_names.append(k.name)
if len(kind_names) != len(set(kind_names)):
raise ValueError("Multiple kinds with the same name passed "
"as custom_kinds")
if set(kind_names) != set(symbols):
raise ValueError("If you pass custom_kinds, you have to "
"pass one Kind object for each symbol "
"that is present in the trajectory. You "
"passed {}, but the symbols are {}".format(
sorted(kind_names), sorted(symbols)))
struc = StructureData(cell=cell)
if custom_kinds is not None:
for k in custom_kinds:
struc.append_kind(k)
for s, p in zip(symbols, positions):
struc.append_site(Site(kind_name=s, position=p))
else:
for s,p in zip(symbols,positions):
# Automatic species generation
struc.append_atom(symbols=s, position=p)
return struc
def _prepare_cif(self,step=None):
"""
Write the given trajectory to a string of format CIF.
"""
import CifFile
from aiida.orm.data.cif \
import ase_loops,cif_from_ase,pycifrw_from_cif
cif = ""
steps = self.get_steps()
if step is not None:
steps = [step]
for i in steps:
structure = self.step_to_structure(i-1)
ciffile = pycifrw_from_cif(cif_from_ase(structure.get_ase()),
ase_loops)
cif = cif + ciffile.WriteOut()
return cif
def _get_aiida_structure(self,store=False,**kwargs):
"""
Creates :py:class:`aiida.orm.data.structure.StructureData`.
:param converter: specify the converter. Default 'ase'.
:param store: If True, intermediate calculation gets stored in the
AiiDA database for record. Default False.
:return: :py:class:`aiida.orm.data.structure.StructureData` node.
"""
from aiida.orm.data.parameter import ParameterData
import trajectory # This same module
param = ParameterData(dict=kwargs)
conv_f = getattr(trajectory,'_get_aiida_structure_inline')
ret_dict = conv_f(trajectory=self,parameters=param,store=store)
return ret_dict['structure']
def _get_cif(self,index=None,**kwargs):
"""
Creates :py:class:`aiida.orm.data.cif.CifData`
"""
struct = self._get_aiida_structure(index=index,**kwargs)
cif = struct._get_cif(**kwargs)
return cif