76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
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import numpy as np
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import threading
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import time
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def determinant_gauss(matrix):
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"""Вычисление детерминанта методом Гаусса"""
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matrix_copy = matrix.astype(np.float64)
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n = matrix_copy.shape[0]
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det = 1.0
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for i in range(n):
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if matrix_copy[i, i] == 0:
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for j in range(i + 1, n):
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if matrix_copy[j, i] != 0:
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matrix_copy[[i, j]] = matrix_copy[[j, i]]
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det *= -1
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break
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det *= matrix_copy[i, i]
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matrix_copy[i, i:] /= matrix_copy[i, i]
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for j in range(i + 1, n):
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factor = matrix_copy[j, i]
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matrix_copy[j, i:] -= factor * matrix_copy[i, i:]
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return det
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def determinant_parallel(matrix, num_threads=2):
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"""Параллельное вычисление детерминанта с использованием потоков"""
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def compute_row(row, matrix_copy):
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n = matrix_copy.shape[0]
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for i in range(row, n, num_threads):
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for j in range(i + 1, n):
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if matrix_copy[i, i] == 0:
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continue
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factor = matrix_copy[j, i] / matrix_copy[i, i]
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matrix_copy[j, i:] -= factor * matrix_copy[i, i:]
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matrix_copy = matrix.astype(np.float64)
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threads = []
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for i in range(num_threads):
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t = threading.Thread(target=compute_row, args=(i, matrix_copy))
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threads.append(t)
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t.start()
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for t in threads:
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t.join()
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return matrix_copy[-1, -1]
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def benchmark(sizes):
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for size in sizes:
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matrix = np.random.randint(1, 11, (size, size))
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start_time = time.time()
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det_regular = determinant_gauss(matrix)
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end_time = time.time()
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regular_time = end_time - start_time
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start_time = time.time()
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det_parallel = determinant_parallel(matrix, num_threads=4)
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end_time = time.time()
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parallel_time = end_time - start_time
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print(f"Размер матрицы: {size}x{size}")
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print(f"Детерминант (последовательно): {det_regular} | Время: {regular_time} секунд")
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print(f"Детерминант (параллельно): {det_parallel} | Время: {parallel_time} секунд")
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print("-" * 50)
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benchmark([100, 300, 500])
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