"""
Overview:
Dimension operations for multi-dimensional array structures.
This module provides utilities for working with nested list/tuple structures
that represent multi-dimensional arrays (cubes). It includes functions for:
- Determining the shape of cube arrays
- Switching/transposing dimensions
- Swapping 2D array dimensions
These operations are useful for manipulating nested data structures without
requiring external dependencies like NumPy.
"""
__all__ = [
'cube_shape', 'dimension_switch', 'swap_2d',
]
def _s_cube_shape(c, path):
"""
Internal recursive function to calculate the shape of a cube array.
:param c: The current level of the nested structure to analyze.
:type c: list or tuple or any
:param path: The current path in the nested structure for error reporting.
:type path: tuple
:return: The shape tuple of the current level and all nested levels.
:rtype: tuple
:raises ValueError: If the structure is not a valid cube (inconsistent shapes at the same level).
"""
if isinstance(c, (list, tuple)):
n = len(c)
if n == 0:
return (0,)
else:
first = c[0]
first_shape = _s_cube_shape(first, (*path, 0))
for i, item in enumerate(c[1:], start=1):
item_shape = _s_cube_shape(item, (*path, i))
if first_shape != item_shape:
raise ValueError(f'Mismatching between {repr((*path, 0))} and {repr((*path, 1))}, '
f'this is not a cube!', ((*path, 0), first_shape), ((*path, 1), item_shape))
return (n, *first_shape)
else:
return ()
[docs]
def cube_shape(c):
"""
Get the shape of a cube array (nested list/tuple structure).
This function analyzes a nested list or tuple structure and returns its shape
as a tuple of dimensions. The structure must be a valid "cube" where all
elements at the same nesting level have consistent shapes.
:param c: The cube array to analyze (nested list/tuple structure).
:type c: list or tuple
:return: Shape of the cube as a tuple of dimension sizes.
:rtype: tuple
:raises ValueError: If the structure is not a valid cube (inconsistent shapes).
Examples::
>>> import numpy
>>> from hbutils.collection import cube_shape
>>> a = numpy.random.randint(-5, 15, (3, 5, 7, 9)).tolist()
>>> cube_shape(a)
(3, 5, 7, 9)
>>> # 2D example
>>> cube_shape([[1, 2, 3], [4, 5, 6]])
(2, 3)
>>> # Invalid cube (mismatched dimensions)
>>> cube_shape([[1, 2], [3, 4, 5]])
Traceback (most recent call last):
...
ValueError: Mismatching between (0,) and (1,), this is not a cube!
"""
return _s_cube_shape(c, ())
[docs]
def dimension_switch(c, dimensions):
"""
Switch (transpose) the dimensions of a cube array according to a specified order.
This function rearranges the dimensions of a multi-dimensional nested structure
according to the provided dimension order. It's similar to NumPy's transpose
operation but works with nested Python lists/tuples.
:param c: Multi-dimensional array (nested list/tuple structure).
:type c: list or tuple
:param dimensions: New order of dimensions as a tuple/list of indices (0 to N-1).
Each index should appear exactly once.
:type dimensions: tuple or list
:return: Array with switched dimensions.
:rtype: list
:raises ValueError: If dimensions parameter is invalid (missing indices, duplicates, or out of range).
Examples::
>>> import numpy
>>> from hbutils.collection import cube_shape, dimension_switch
>>> a = numpy.random.randint(-5, 15, (3, 5, 7, 9)).tolist()
>>> cube_shape(a)
(3, 5, 7, 9)
>>> b = dimension_switch(a, (3, 0, 2, 1))
>>> cube_shape(b)
(9, 3, 7, 5)
>>> # 2D transpose example
>>> arr = [[1, 2, 3], [4, 5, 6]]
>>> dimension_switch(arr, (1, 0))
[[1, 4], [2, 5], [3, 6]]
"""
shape = cube_shape(c)
n = len(shape)
if sorted(set(dimensions)) != list(range(len(shape))):
raise ValueError(f'Invalid dimensions - {repr(dimensions)}.', dimensions)
def _recursive(p, path):
"""
Recursive helper function to build the switched array.
:param p: Current depth level in the recursion.
:type p: int
:param path: Current path of indices being built.
:type path: tuple
:return: Element or nested list at the current recursion level.
:rtype: any or list
"""
if p >= n:
actual_path = [None] * n
for i, di in enumerate(dimensions):
actual_path[di] = path[i]
oc = c
for ip in actual_path:
oc = oc[ip]
return oc
else:
return [_recursive(p + 1, (*path, i)) for i in range(shape[dimensions[p]])]
return _recursive(0, ())
[docs]
def swap_2d(c):
"""
Swap the dimensions of a 2D array (transpose rows and columns).
This is a convenience function that transposes a 2D nested list/tuple structure
by swapping its two dimensions. It's equivalent to calling dimension_switch(c, (1, 0)).
:param c: 2D array (nested list/tuple structure).
:type c: list or tuple
:return: Transposed 2D array.
:rtype: list
Examples::
>>> from hbutils.collection import swap_2d
>>> swap_2d([
... [9, 6, 4, 11, 5, -2, 1],
... [0, 0, 11, 5, 8, -4, 9],
... [0, 2, 13, 7, 0, 13, 0]
... ])
[[9, 0, 0],
[6, 0, 2],
[4, 11, 13],
[11, 5, 7],
[5, 8, 0],
[-2, -4, 13],
[1, 9, 0]]
>>> # Simple example
>>> swap_2d([[1, 2, 3], [4, 5, 6]])
[[1, 4], [2, 5], [3, 6]]
"""
return dimension_switch(c, (1, 0))