Strassen's algorithm: Difference between revisions
A Python implementation
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=={{header|Python}}==
<lang python>"""Matrix multiplication using Strassen's algorithm. Requires Python >= 3.7."""
from __future__ import annotations
from itertools import chain
from typing import List
from typing import NamedTuple
from typing import Optional
class Shape(NamedTuple):
rows: int
cols: int
class Matrix(List):
"""A matrix implemented as a two-dimensional list."""
@classmethod
def block(cls, blocks) -> Matrix:
"""Return a new Matrix assembled from nested blocks."""
m = Matrix()
for hblock in blocks:
for row in zip(*hblock):
m.append(list(chain.from_iterable(row)))
return m
def dot(self, b: Matrix) -> Matrix:
"""Return a new Matrix that is the product of this matrix and matrix `b`.
Uses 'simple' or 'naive' matrix multiplication."""
assert self.shape.cols == b.shape.rows
m = Matrix()
for row in self:
new_row = []
for c in range(len(b[0])):
col = [b[r][c] for r in range(len(b))]
new_row.append(sum(x * y for x, y in zip(row, col)))
m.append(new_row)
return m
def __matmul__(self, b: Matrix) -> Matrix:
return self.dot(b)
def __add__(self, b: Matrix) -> Matrix:
"""Matrix addition."""
assert self.shape == b.shape
rows, cols = self.shape
return Matrix(
[[self[i][j] + b[i][j] for j in range(cols)] for i in range(rows)]
)
def __sub__(self, b: Matrix) -> Matrix:
"""Matrix subtraction."""
assert self.shape == b.shape
rows, cols = self.shape
return Matrix(
[[self[i][j] - b[i][j] for j in range(cols)] for i in range(rows)]
)
def strassen(self, b: Matrix) -> Matrix:
"""Return a new Matrix that is the product of this matrix and matrix `b`.
Uses strassen algorithm."""
rows, cols = self.shape
assert rows == cols, "matrices must be square"
assert self.shape == b.shape, "matrices must be the same shape"
assert rows and (rows & rows - 1) == 0, "shape must be a power of 2"
if rows == 1:
return self.dot(b)
p = rows // 2 # partition
a11 = Matrix([n[:p] for n in self[:p]])
a12 = Matrix([n[p:] for n in self[:p]])
a21 = Matrix([n[:p] for n in self[p:]])
a22 = Matrix([n[p:] for n in self[p:]])
b11 = Matrix([n[:p] for n in b[:p]])
b12 = Matrix([n[p:] for n in b[:p]])
b21 = Matrix([n[:p] for n in b[p:]])
b22 = Matrix([n[p:] for n in b[p:]])
m1 = (a11 + a22).strassen(b11 + b22)
m2 = (a21 + a22).strassen(b11)
m3 = a11.strassen(b12 - b22)
m4 = a22.strassen(b21 - b11)
m5 = (a11 + a12).strassen(b22)
m6 = (a21 - a11).strassen(b11 + b12)
m7 = (a12 - a22).strassen(b21 + b22)
c11 = m1 + m4 - m5 + m7
c12 = m3 + m5
c21 = m2 + m4
c22 = m1 - m2 + m3 + m6
return Matrix.block([[c11, c12], [c21, c22]])
def round(self, ndigits: Optional[int] = None) -> Matrix:
return Matrix([[round(i, ndigits) for i in row] for row in self])
@property
def shape(self) -> Shape:
cols = len(self[0]) if self else 0
return Shape(len(self), cols)
def examples():
a = Matrix(
[
[1, 2],
[3, 4],
]
)
b = Matrix(
[
[5, 6],
[7, 8],
]
)
c = Matrix(
[
[1, 1, 1, 1],
[2, 4, 8, 16],
[3, 9, 27, 81],
[4, 16, 64, 256],
]
)
d = Matrix(
[
[4, -3, 4 / 3, -1 / 4],
[-13 / 3, 19 / 4, -7 / 3, 11 / 24],
[3 / 2, -2, 7 / 6, -1 / 4],
[-1 / 6, 1 / 4, -1 / 6, 1 / 24],
]
)
e = Matrix(
[
[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16],
]
)
f = Matrix(
[
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, 1, 0],
[0, 0, 0, 1],
]
)
print("Naive matrix multiplication:")
print(f" a * b = {a @ b}")
print(f" c * d = {(c @ d).round()}")
print(f" e * f = {e @ f}")
print("Strassen's matrix multiplication:")
print(f" a * b = {a.strassen(b)}")
print(f" c * d = {c.strassen(d).round()}")
print(f" e * f = {e.strassen(f)}")
if __name__ == "__main__":
examples()
</lang>
{{out}}
<pre>
Naive matrix multiplication:
a * b = [[19, 22], [43, 50]]
c * d = [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]]
e * f = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
Strassen's matrix multiplication:
a * b = [[19, 22], [43, 50]]
c * d = [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]]
e * f = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
</pre>
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