vtkmodules.numpy_interface.vtk_implicit_array#

Notes#

Because AOS overrides are registered on concrete types (vtkFloatArray, vtkAOSDataArrayTemplate[float32], etc.) and SOA overrides on vtkSOADataArrayTemplate[...], those always take precedence over this vtkDataArray-level fallback.

VTKImplicitArray — fallback numpy-compatible mixin for implicit VTK arrays.

VTK implicit arrays (vtkImplicitArray) compute values on the fly from a backend functor rather than storing them in memory. Many backends are defined locally in C++ implementation files and are never exposed to the Python wrapping system. When such an array crosses from C++ to Python, VTK’s FindNearestBaseClass resolves it to vtkDataArray — the nearest wrapped ancestor.

This module registers a fallback mixin on vtkDataArray so that any data array type that does not have a more-specific override (AOS, SOA, or a dedicated implicit-array override) still gets a working numpy interface.

The mixin materialises values by deep-copying to an AOS array on first access and caches the result. A ModifiedEvent observer invalidates the cache so that re-reads after the underlying data changes produce correct results.

Module Contents#

Classes#

VTKImplicitArray

Fallback numpy-compatible mixin for implicit/unknown VTK data arrays.

Functions#

_register_implicit_override

Register VTKImplicitArray as override on vtkDataArray.

Data#

_UNINITIALIZED

API#

vtkmodules.numpy_interface.vtk_implicit_array._UNINITIALIZED#

‘object(…)’

class vtkmodules.numpy_interface.vtk_implicit_array.VTKImplicitArray(*args, **kwargs)#

Bases: vtkmodules.numpy_interface._vtk_array_mixin.VTKDataArrayMixin

Fallback numpy-compatible mixin for implicit/unknown VTK data arrays.

Materialises the array to a contiguous AOS copy (via DeepCopy) on first numpy access and caches the result. The cache is invalidated when VTK fires ModifiedEvent on the array.

This mixin is automatically applied to any vtkDataArray subclass that does not already have a more specific override (AOS or SOA).

Properties

shape : tuple of int (ntuples,) for 1-component, (ntuples, ncomps) otherwise. dtype : numpy.dtype The element data type. dataset : vtkDataSet or None The owning VTK dataset, when the array is attached to one. association : int or None The attribute association (POINT, CELL, etc.).

Examples

Implicit arrays from VTK are automatically wrapped::

implicit_arr = some_filter.GetOutput().GetPointData().GetArray(0)
print(np.sum(implicit_arr))   # materialises once, then cached

See Also

VTKAOSArray : Mixin for array-of-structures VTK arrays (zero-copy). VTKSOAArray : Mixin for structure-of-arrays VTK arrays (zero-copy).

Initialization

_materialise()#

Deep-copy this array into a contiguous AOS numpy array.

property _array_view#
_setup_observer()#

Invalidate the cached numpy array when the VTK array is modified.

property dtype#
property nbytes#
__buffer__(flags)#

Expose the materialised AOS copy via the buffer protocol.

This allows numpy.frombuffer(implicit_arr) and vtk_to_numpy(implicit_arr) to work transparently.

__array__(dtype=None, copy=None)#
__array_ufunc__(ufunc, method, *inputs, **kwargs)#
__array_function__(func, types, args, kwargs)#
__getitem__(index)#
__setitem__(index, value)#
_binop(other, op)#
_rbinop(other, op)#
__add__(other)#
__radd__(other)#
__sub__(other)#
__rsub__(other)#
__mul__(other)#
__rmul__(other)#
__truediv__(other)#
__rtruediv__(other)#
__floordiv__(other)#
__rfloordiv__(other)#
__pow__(other)#
__rpow__(other)#
__mod__(other)#
__rmod__(other)#
__lt__(other)#
__le__(other)#
__eq__(other)#
__ne__(other)#
__ge__(other)#
__gt__(other)#
__neg__()#
__abs__()#
__iter__()#
__repr__()#
__str__()#
vtkmodules.numpy_interface.vtk_implicit_array._register_implicit_override()#

Register VTKImplicitArray as override on vtkDataArray.

This is a fallback: any array type that already has a more-specific override (AOS on vtkFloatArray, SOA on vtkSOADataArrayTemplate, etc.) is unaffected. Only types whose nearest wrapped ancestor is vtkDataArray will use this mixin.