data classes module

class data_classes.LinkedList(input_array, linked_array=None)

Bases: ndarray

NumPy ndarray subclass that keeps a second “linked” array in sync for element-wise updates and structural operations (sort, delete, reshape).

linked_array

Secondary array kept in sync with the primary array.

Type:

array_like or None

sync_sort()

Sort values and apply the same permutation to linked_array.

sync_delete(index)

Delete items by index in both arrays and return a new object when a linked_array is present.

sync_reshape(size)

Reshape both arrays consistently and return a new object when a linked_array is present.

sync_delete(index)

Delete the specified index/indices from the array and its linked array.

Parameters:

index (int, slice, or array_like) – Indices to remove. Passed to np.delete.

Returns:

A new LinkedList with the specified entries removed when a linked_array is present; otherwise, a regular ndarray.

Return type:

LinkedList or ndarray

sync_reshape(size)

Reshape both the array and the linked array to the specified size.

Parameters:

size (tuple of int) – New shape to apply to both arrays. Must be compatible with the number of elements.

Returns:

A new LinkedList if a linked_array exists; otherwise, a regular ndarray.

Return type:

LinkedList or ndarray

sync_sort()

Sort the array in ascending order and apply the same permutation to the linked array.

Returns:

In-place operation; no return value.

Return type:

None

sync_split(indices_or_sections, axis=0)

Split both the array and the linked array into multiple sub-arrays.

Parameters:

• indices_or_sections (int or 1-D array_like) – If an integer, it indicates the number of equal splits to make. If an array, it indicates the indices at which to split.

• axis (int, optional) – Axis along which to split. Default is 0.

Returns:

A list of LinkedList objects if a linked_array exists; otherwise, a list of regular ndarray arrays.

Return type:

list of LinkedList or ndarray