amplifyの作法 その12

概要

amplifyの作法、調べてみた。
qubo使ってみた。

参考にしたページ

サンプルコード

from amplify import (BinaryPoly, BinaryQuadraticModel, gen_symbols, Solver, decode_solution, )
from amplify.client import FixstarsClient
from typing import Set, Tuple, Container, Dict, Sequence, Collection, Mapping
from dataclasses import dataclass
import networkx as nx

def to_dict(q: np.ndarray) -> Dict[Tuple[int, int], float]:
	assert len(q.shape) == 2 and  q.shape[0] == q.shape[1]
	return dict(zip(zip(*np.nonzero(q)), q[q != 0]))



def qubo_spp(cost: np.ndarray, set_flag: np.ndarray, p = 10.):
	assert cost.shape[0] == set_flag.shape[1]
	b = np.ones(set_flag.shape[0])
	return np.diagflat(cost - p * 2 * b.dot(set_flag)) + p * np.einsum("ij,ik->jk", set_flag, set_flag)

c = np.array([3, 2, 1, 1, 3, 2])
a = np.array([[1, 0, 1, 0, 0, 1], [0, 1, 1, 0, 1, 1], [0, 0, 1, 1, 1, 0], [1, 1, 0, 1, 0, 1]])
q = qubo_spp(c, a)
assert q.tolist() == [[-17, 10, 10, 10, 0, 20], [10, -18, 10, 10, 10, 20], [10, 10, -29, 10, 20, 20], [10, 10, 10, -19, 10, 10],	[0, 10, 20, 10, -17, 10], [20, 20, 20, 10, 10, -28]]
q = to_dict(q)
print(q)
f = BinaryPoly(q)
model0 = BinaryQuadraticModel(f)
solver = Solver(client)
result = solver.solve(model0)
values = result[0].values
print(values)
#	assert is_contain(sample, np.array([1,0,0,0,1,0]))

以上。