def combine(self, merge_points=False, tolerance=0.0):
"""Combine all blocks into a single unstructured grid.
Parameters
----------
merge_points : bool, optional
Merge coincidental points.
tolerance : float, optional
The absolute tolerance to use to find coincident points when
``merge_points=True``.
Returns
-------
pyvista.UnstructuredGrid
Combined blocks.
Examples
--------
Combine blocks within a multiblock without merging points.
>>> import pyvista
>>> block = pyvista.MultiBlock([
... pyvista.Cube(clean=False),
... pyvista.Cube(center=(1, 0, 0), clean=False)
... ])
>>> merged = block.combine()
>>> merged.n_points
48
Combine blocks and merge points
>>> merged = block.combine(merge_points=True)
>>> merged.n_points
12
"""
alg = _vtk.vtkAppendFilter()
for block in self:
if isinstance(block, _vtk.vtkMultiBlockDataSet):
block = CompositeFilters.combine(block,
merge_points=merge_points,
tolerance=tolerance)
alg.AddInputData(block)
alg.SetMergePoints(merge_points)
alg.SetTolerance(tolerance)
alg.Update()
return wrap(alg.GetOutputDataObject(0))
def cast_to_unstructured_grid(self) -> 'pyvista.UnstructuredGrid':
"""Get a new representation of this object as an :class:`pyvista.UnstructuredGrid`."""
alg = _vtk.vtkAppendFilter()
alg.AddInputData(self)
alg.Update()
return _get_output(alg)
def __init__(self, *args, **kwargs) -> None:
"""Initialize the unstructured grid."""
super().__init__()
deep = kwargs.pop('deep', False)
if not len(args):
return
if len(args) == 1:
if isinstance(args[0], _vtk.vtkUnstructuredGrid):
if deep:
self.deep_copy(args[0])
else:
self.shallow_copy(args[0])
elif isinstance(args[0], (str, pathlib.Path)):
self._from_file(args[0])
elif isinstance(args[0], _vtk.vtkStructuredGrid):
vtkappend = _vtk.vtkAppendFilter()
vtkappend.AddInputData(args[0])
vtkappend.Update()
self.shallow_copy(vtkappend.GetOutput())
else:
itype = type(args[0])
raise TypeError(f'Cannot work with input type {itype}')
#Cell dictionary creation
elif len(args) == 2 and isinstance(args[0], dict) and isinstance(args[1], np.ndarray):
self._from_cells_dict(args[0], args[1], deep)
self._check_for_consistency()
elif len(args) == 3: # and VTK9:
arg0_is_arr = isinstance(args[0], np.ndarray)
arg1_is_arr = isinstance(args[1], np.ndarray)
arg2_is_arr = isinstance(args[2], np.ndarray)
if all([arg0_is_arr, arg1_is_arr, arg2_is_arr]):
self._from_arrays(None, args[0], args[1], args[2], deep)
self._check_for_consistency()
else:
raise TypeError('All input types must be np.ndarray')
elif len(args) == 4:
arg0_is_arr = isinstance(args[0], np.ndarray)
arg1_is_arr = isinstance(args[1], np.ndarray)
arg2_is_arr = isinstance(args[2], np.ndarray)
arg3_is_arr = isinstance(args[3], np.ndarray)
if all([arg0_is_arr, arg1_is_arr, arg2_is_arr, arg3_is_arr]):
self._from_arrays(args[0], args[1], args[2], args[3], deep)
self._check_for_consistency()
else:
raise TypeError('All input types must be np.ndarray')
else:
err_msg = 'Invalid parameters. Initialization with arrays ' +\
'requires the following arrays:\n'
if _vtk.VTK9:
raise TypeError(err_msg + '`cells`, `cell_type`, `points`')
else:
raise TypeError(err_msg + '(`offset` optional), `cells`, `cell_type`, `points`')