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"""

Wavelet tree is a data-structure designed to efficiently answer various range queries

for arrays. Wavelets trees are different from other binary trees in the sense that

the nodes are split based on the actual values of the elements and not on indices,

such as the with segment trees or fenwick trees. You can read more about them here:

1. https://users.dcc.uchile.cl/~jperez/papers/ioiconf16.pdf

2. https://www.youtube.com/watch?v=4aSv9PcecDw&t=811s

3. https://www.youtube.com/watch?v=CybAgVF-MMc&t=1178s

"""

from __future__ import annotations

test_array = [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]

class Node:

def __init__(self, length: int) -> None:

self.minn: int = -1

self.maxx: int = -1

self.map_left: list[int] = [-1] * length

self.left: Node | None = None

self.right: Node | None = None

def __repr__(self) -> str:

"""

>>> node = Node(length=27)

>>> repr(node)

'min_value: -1, max_value: -1'

>>> repr(node) == str(node)

True

"""

return f"min_value: {self.minn}, max_value: {self.maxx}"

def build_tree(arr: list[int]) -> Node | None:

"""

Builds the tree for arr and returns the root

of the constructed tree

>>> build_tree(test_array)

min_value: 0, max_value: 9

"""

root = Node(len(arr))

root.minn, root.maxx = min(arr), max(arr)

# Leaf node case where the node contains only one unique value

if root.minn == root.maxx:

return root

"""

Take the mean of min and max element of arr as the pivot and

partition arr into left_arr and right_arr with all elements <= pivot in the

left_arr and the rest in right_arr, maintaining the order of the elements,

then recursively build trees for left_arr and right_arr

"""

pivot = (root.minn + root.maxx) // 2

left_arr: list[int] = []

right_arr: list[int] = []

for index, num in enumerate(arr):

if num <= pivot:

left_arr.append(num)

else:

right_arr.append(num)

root.map_left[index] = len(left_arr)

root.left = build_tree(left_arr)

root.right = build_tree(right_arr)

return root

def rank_till_index(node: Node | None, num: int, index: int) -> int:

"""

Returns the number of occurrences of num in interval [0, index] in the list

>>> root = build_tree(test_array)

>>> rank_till_index(root, 6, 6)

>>> rank_till_index(root, 2, 0)

>>> rank_till_index(root, 1, 10)

>>> rank_till_index(root, 17, 7)

>>> rank_till_index(root, 0, 9)

"""

if index < 0 or node is None:

return 0

# Leaf node cases

if node.minn == node.maxx:

return index + 1 if node.minn == num else 0

pivot = (node.minn + node.maxx) // 2

if num <= pivot:

# go the left subtree and map index to the left subtree

return rank_till_index(node.left, num, node.map_left[index] - 1)

else:

# go to the right subtree and map index to the right subtree

return rank_till_index(node.right, num, index - node.map_left[index])

def rank(node: Node | None, num: int, start: int, end: int) -> int:

"""

Returns the number of occurrences of num in interval [start, end] in the list

>>> root = build_tree(test_array)

>>> rank(root, 6, 3, 13)

>>> rank(root, 2, 0, 19)

>>> rank(root, 9, 2 ,2)

>>> rank(root, 0, 5, 10)

"""

if start > end:

return 0

rank_till_end = rank_till_index(node, num, end)

rank_before_start = rank_till_index(node, num, start - 1)

return rank_till_end - rank_before_start

def quantile(node: Node | None, index: int, start: int, end: int) -> int:

"""

Returns the index'th smallest element in interval [start, end] in the list

index is 0-indexed

>>> root = build_tree(test_array)

>>> quantile(root, 2, 2, 5)

>>> quantile(root, 5, 2, 13)

>>> quantile(root, 0, 6, 6)

>>> quantile(root, 4, 2, 5)

-1

"""

if index > (end - start) or start > end or node is None:

return -1

# Leaf node case

if node.minn == node.maxx:

return node.minn

# Number of elements in the left subtree in interval [start, end]

num_elements_in_left_tree = node.map_left[end] - (

node.map_left[start - 1] if start else 0

)

if num_elements_in_left_tree > index:

return quantile(

node.left,

index,

(node.map_left[start - 1] if start else 0),

node.map_left[end] - 1,

)

else:

return quantile(

node.right,

index - num_elements_in_left_tree,

start - (node.map_left[start - 1] if start else 0),

end - node.map_left[end],

)

def range_counting(

node: Node | None, start: int, end: int, start_num: int, end_num: int

) -> int:

"""

Returns the number of elements in range [start_num, end_num]

in interval [start, end] in the list

>>> root = build_tree(test_array)

>>> range_counting(root, 1, 10, 3, 7)

>>> range_counting(root, 2, 2, 1, 4)

>>> range_counting(root, 0, 19, 0, 100)

>>> range_counting(root, 1, 0, 1, 100)

>>> range_counting(root, 0, 17, 100, 1)

"""

if (

start > end

or node is None

or start_num > end_num

or node.minn > end_num

or node.maxx < start_num

return 0

if start_num <= node.minn and node.maxx <= end_num:

return end - start + 1

left = range_counting(

node.left,

(node.map_left[start - 1] if start else 0),

node.map_left[end] - 1,

start_num,

end_num,

)

right = range_counting(

node.right,

start - (node.map_left[start - 1] if start else 0),

end - node.map_left[end],

start_num,

end_num,

)

return left + right

if __name__ == "__main__":

import doctest

doctest.testmod()

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