import logging
from traits.api import (HasTraits, Instance, Enum, Str, ListStr,
cached_property, Property)
from traitsui.api import View, Group, Item, VGroup
from apptools.persistence.state_pickler import set_state
from simphony.cuds.abc_modeling_engine import ABCModelingEngine
from .cuds_source import CUDSSource
logger = logging.getLogger(__name__)
[docs]class EngineSource(CUDSSource):
"""A mayavi source for reading data from a SimPhoNy Engine
"""
#: The version of this class. Used for persistence.
__version__ = 0
#: the SimPhoNy Modeling Engine from which datasets are loaded.
engine = Instance(ABCModelingEngine)
#: Label for the engine, if provided, it is use for representation
#: purpose in the Mayavi pipeline GUI).
engine_name = Str
#: The name of the CUDS container that is currently loaded.
dataset = Enum(values="datasets")
#: datasets in the engine. This should be read-only.
datasets = Property(ListStr, depends_on="engine")
view = View(
VGroup(
Group(Item(name="dataset")),
Group(
Item(name="point_scalars_name"),
Item(name="point_vectors_name"),
Item(name="cell_scalars_name"),
Item(name="cell_vectors_name"),
Item(name="data"))))
# Read-only attribute ##################################################
@cached_property
def _get_datasets(self):
'''Available dataset names in the engine'''
return self.engine.get_dataset_names()
# Public interface #####################################################
def __init__(self, engine=None, dataset=None,
point_scalars=None, point_vectors=None,
cell_scalars=None, cell_vectors=None, **traits):
"""Constructor
Parameters
----------
engine : ABCModelingEngine
The SimPhoNy Modeling Engine where dataset is loaded from.
Default is None.
dataset : str
Name of the dataset to be extracted from engine.
Default is the first available dataset if engine is defined,
otherwise it is an empty string
point_scalars : str
CUBA name of the data to be selected as point scalars.
Default is the first available point scalars.
point_vectors : str
CUBA name of the data to be selected as point vectors.
Default is the first available point vectors.
cell_scalars : str
CUBA name of the data to be selected as cell scalars.
Default is the first available cell scalars.
cell_vectors : str
CUBA name of the data to be selected as cell vectors.
Default is the first available cell vectors.
Notes
-----
To turn off visualisation for a point/cell scalar/vector data,
assign the attribute to an empty string (i.e. point_scalars="")
Other optional keyword parameters are parsed to CUDSSource
Examples
--------
>>> source = EngineSource(engine=some_engine)
>>> source.datasets
["particles", "lattice"]
>>> source.dataset = "particles"
>>> # Alternatively
>>> source = EngineSource(engine=some_engine, dataset="particles")
>>> from mayavi import mlab
>>> mlab.pipline.glypy(source)
"""
# required by Traits
super(EngineSource, self).__init__(**traits)
self.engine = engine
# if dataset is not defined, default is already set by DEnum
if dataset:
self.dataset = dataset
if any((point_scalars, point_vectors, cell_scalars, cell_vectors)):
# the vtk_data may not be loaded for performance purpose
# however if point_scalars/... is defined that means the
# user wants to load the vtk data, so we load it here
if self._cuds is None:
self._update_cuds()
self._select_attributes(point_scalars=point_scalars,
point_vectors=point_vectors,
cell_scalars=cell_scalars,
cell_vectors=cell_vectors)
def start(self):
""" Load dataset from the engine and start the visualisation """
# if the EngineSource is restored from saved visualisation
# `engine` is not defined
if not self.running and self.engine:
self._update_cuds()
super(EngineSource, self).start()
# Trait Change Handlers ################################################
def _engine_changed(self):
# update the cuds if the source is started
if self.running:
self._update_cuds()
def _dataset_changed(self):
self._update_cuds()
# Private interface ####################################################
def _update_cuds(self):
if self.datasets:
self.cuds = self.engine.get_dataset(self.dataset)
else:
logger.warning("No dataset is available from the engine")
def _get_name(self):
""" Returns the name to display on the tree view. Note that
this is not a property getter.
"""
engine_name = self.engine_name or "engine"
return '{} (CUDS from {})'.format(self.dataset, engine_name)
def __get_pure_state__(self):
state = super(EngineSource, self).__get_pure_state__()
# Skip pickling the engine
state.pop("engine", None)
# Remove unselected dataset names from the cache
state["_traits_cache_datasets"] = [self.dataset]
logger.warning("The ABCModelingEngine instance is not pickled")
return state
def __set_pure_state__(self, state):
logger.warning(("The ABCModelingEngine instance is not restored. "
"Please assign the data source `engine` attribute"))
# set the dataset names first because data_changed will
# call _get_name()
set_state(self, state, first=["_traits_cache_datasets"],
ignore=["*"])
super(EngineSource, self).__set_pure_state__(state)
