napari_track_edit.data_views.lazy_array_wrapper
===============================================

.. py:module:: napari_track_edit.data_views.lazy_array_wrapper


Classes
-------

.. autoapisummary::

   napari_track_edit.data_views.lazy_array_wrapper.LazyArrayWrapper


Functions
---------

.. autoapisummary::

   napari_track_edit.data_views.lazy_array_wrapper._is_fancy_index


Module Contents
---------------

.. py:function:: _is_fancy_index(index)

   Return True if index is a fancy index (tuple containing array-likes).


.. py:class:: LazyArrayWrapper(data)

   Wrapper around lazy/read-only arrays that materializes fancy indexing.

   Lazy array backends like tracksdata's GraphArrayView return view objects
   from __getitem__ rather than numpy values. This breaks napari code that
   does fancy indexing (e.g. ``data[tuple_of_arrays] == value``).

   This wrapper intercepts fancy indexing and materializes one
   first-dimension slice at a time, returning numpy values. All other
   indexing patterns and attribute access are delegated to the underlying
   array.

   The wrapper intentionally does not implement __setitem__, preserving the
   read-only nature of the underlying array for detection via
   ``hasattr(data, "__setitem__")``.


   .. py:attribute:: _data


   .. py:property:: wrapped

      The underlying array object.


   .. py:property:: shape


   .. py:property:: dtype


   .. py:property:: ndim


   .. py:property:: size


   .. py:method:: __len__()


   .. py:method:: __array__(dtype=None, copy=None)


   .. py:method:: __getitem__(index)


   .. py:method:: _materialize_fancy(index)

      Materialize fancy indexing by reading individual coordinates.

      Each coordinate tuple is looked up via scalar indexing on the
      underlying array, which is fast when the array has an internal
      cache (e.g. GraphArrayView's NDChunkCache).



   .. py:method:: __getattr__(name)


   .. py:method:: __repr__()