Add Fast Walsh-Hadamard Transform (FWHT) for bitwise convolutions (#15084)

* Add Fast Walsh-Hadamard Transform (FWHT) for bitwise convolutions

* Potential fix for pull request finding

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

* refactor: remove unnecessary whitespace in fast_walsh_hadamard_transform.py

* Move fast_walsh_hadamard_transform.py to bit_manipulation

---------

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Christian Clauss <cclauss@me.com>

Author: 3 people

bit_manipulation/fast_walsh_hadamard_transform.py

@@ -0,0 +1,209 @@
+"""
+Fast Walsh-Hadamard Transform (FWHT) for Bitwise Convolutions.
+
+Reference: https://en.wikipedia.org/wiki/Fast_Walsh%E2%80%93Hadamard_transform
+Reference: https://cp-algorithms.com/algebra/walsh-hadamard-transform.html
+
+Computes bitwise XOR, AND, and OR convolutions of two numeric sequences in O(N log N)
+time, where N is a positive power of 2.
+"""
+
+
+def fwht_xor(sequence: list[int], inverse: bool = False) -> list[int]:
+    """
+    Perform Fast Walsh-Hadamard Transform (or inverse) for XOR operation.
+
+    Time Complexity: O(N log N)
+
+    >>> fwht_xor([1, 2, 3, 4])
+    [10, -2, -4, 0]
+    >>> fwht_xor([10, -2, -4, 0], inverse=True)
+    [1, 2, 3, 4]
+    >>> fwht_xor([1, 2, 3])
+    Traceback (most recent call last):
+        ...
+    ValueError: Length of sequence must be a positive power of 2.
+    >>> fwht_xor([])
+    Traceback (most recent call last):
+        ...
+    ValueError: Length of sequence must be a positive power of 2.
+    >>> fwht_xor([1, 2, 3, 5], inverse=True)
+    Traceback (most recent call last):
+        ...
+    ValueError: Inverse XOR transform requires elements divisible by sequence length.
+    """
+    sequence_length = len(sequence)
+    if sequence_length == 0 or (sequence_length & (sequence_length - 1)) != 0:
+        raise ValueError("Length of sequence must be a positive power of 2.")
+
+    result = list(sequence)
+    half_block = 1
+    while half_block < sequence_length:
+        block_size = half_block * 2
+        for block_start in range(0, sequence_length, block_size):
+            for offset in range(half_block):
+                left_index = block_start + offset
+                right_index = left_index + half_block
+                left_val = result[left_index]
+                right_val = result[right_index]
+                result[left_index] = left_val + right_val
+                result[right_index] = left_val - right_val
+        half_block *= 2
+
+    if inverse:
+        if any(element % sequence_length != 0 for element in result):
+            raise ValueError(
+                "Inverse XOR transform requires elements divisible by sequence length."
+            )
+        result = [element // sequence_length for element in result]
+    return result
+
+
+def xor_convolution(sequence_a: list[int], sequence_b: list[int]) -> list[int]:
+    """
+    Compute bitwise XOR convolution C[k] = sum_{i ^ j = k} (A[i] * B[j]).
+
+    Time Complexity: O(N log N)
+
+    >>> xor_convolution([1, 2], [3, 4])
+    [11, 10]
+    >>> xor_convolution([1, 2], [3])
+    Traceback (most recent call last):
+        ...
+    ValueError: Input sequences must have equal length.
+    """
+    if len(sequence_a) != len(sequence_b):
+        raise ValueError("Input sequences must have equal length.")
+
+    transformed_a = fwht_xor(sequence_a)
+    transformed_b = fwht_xor(sequence_b)
+    pointwise_product = [
+        transformed_a[index] * transformed_b[index] for index in range(len(sequence_a))
+    ]
+    return fwht_xor(pointwise_product, inverse=True)
+
+
+def fwht_or(sequence: list[int], inverse: bool = False) -> list[int]:
+    """
+    Perform Fast Walsh-Hadamard Transform for OR operation.
+
+    Time Complexity: O(N log N)
+
+    >>> fwht_or([1, 2])
+    [1, 3]
+    >>> fwht_or([1, 3], inverse=True)
+    [1, 2]
+    >>> fwht_or([1, 2, 3])
+    Traceback (most recent call last):
+        ...
+    ValueError: Length of sequence must be a positive power of 2.
+    """
+    sequence_length = len(sequence)
+    if sequence_length == 0 or (sequence_length & (sequence_length - 1)) != 0:
+        raise ValueError("Length of sequence must be a positive power of 2.")
+
+    result = list(sequence)
+    half_block = 1
+    while half_block < sequence_length:
+        block_size = half_block * 2
+        for block_start in range(0, sequence_length, block_size):
+            for offset in range(half_block):
+                left_index = block_start + offset
+                right_index = left_index + half_block
+                if not inverse:
+                    result[right_index] += result[left_index]
+                else:
+                    result[right_index] -= result[left_index]
+        half_block *= 2
+
+    return result
+
+
+def or_convolution(sequence_a: list[int], sequence_b: list[int]) -> list[int]:
+    """
+    Compute bitwise OR convolution C[k] = sum_{i | j = k} (A[i] * B[j]).
+
+    Time Complexity: O(N log N)
+
+    >>> or_convolution([1, 2], [3, 4])
+    [3, 18]
+    >>> or_convolution([1, 2], [3])
+    Traceback (most recent call last):
+        ...
+    ValueError: Input sequences must have equal length.
+    """
+    if len(sequence_a) != len(sequence_b):
+        raise ValueError("Input sequences must have equal length.")
+
+    transformed_a = fwht_or(sequence_a)
+    transformed_b = fwht_or(sequence_b)
+    pointwise_product = [
+        transformed_a[index] * transformed_b[index] for index in range(len(sequence_a))
+    ]
+    return fwht_or(pointwise_product, inverse=True)
+
+
+def fwht_and(sequence: list[int], inverse: bool = False) -> list[int]:
+    """
+    Perform Fast Walsh-Hadamard Transform for AND operation.
+
+    Time Complexity: O(N log N)
+
+    >>> fwht_and([1, 2])
+    [3, 2]
+    >>> fwht_and([3, 2], inverse=True)
+    [1, 2]
+    >>> fwht_and([1, 2, 3])
+    Traceback (most recent call last):
+        ...
+    ValueError: Length of sequence must be a positive power of 2.
+    """
+    sequence_length = len(sequence)
+    if sequence_length == 0 or (sequence_length & (sequence_length - 1)) != 0:
+        raise ValueError("Length of sequence must be a positive power of 2.")
+
+    result = list(sequence)
+    half_block = 1
+    while half_block < sequence_length:
+        block_size = half_block * 2
+        for block_start in range(0, sequence_length, block_size):
+            for offset in range(half_block):
+                left_index = block_start + offset
+                right_index = left_index + half_block
+                if not inverse:
+                    result[left_index] += result[right_index]
+                else:
+                    result[left_index] -= result[right_index]
+        half_block *= 2
+
+    return result
+
+
+def and_convolution(sequence_a: list[int], sequence_b: list[int]) -> list[int]:
+    """
+    Compute bitwise AND convolution C[k] = sum_{i & j = k} (A[i] * B[j]).
+
+    Time Complexity: O(N log N)
+
+    >>> and_convolution([1, 2], [3, 4])
+    [13, 8]
+    >>> and_convolution([1, 2], [3])
+    Traceback (most recent call last):
+        ...
+    ValueError: Input sequences must have equal length.
+    """
+    if len(sequence_a) != len(sequence_b):
+        raise ValueError("Input sequences must have equal length.")
+
+    transformed_a = fwht_and(sequence_a)
+    transformed_b = fwht_and(sequence_b)
+    pointwise_product = [
+        transformed_a[index] * transformed_b[index] for index in range(len(sequence_a))
+    ]
+    return fwht_and(pointwise_product, inverse=True)
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()