mirror of
https://github.com/kuhyx/WUT_Computer_Science.git
synced 2026-07-04 16:03:11 +02:00
87 lines
3.7 KiB
Python
87 lines
3.7 KiB
Python
import numpy as np
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import scipy.io
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import os
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class MatrixGenerator:
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@staticmethod
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def generate_spd_matrix(n: int) -> np.ndarray:
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A = np.random.rand(n, n)
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spd_matrix = np.dot(A, A.T) + n * MatrixGenerator.generate_identity_matrix(n) # Adding n*I ensures positive definiteness
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return spd_matrix
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@staticmethod
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def generate_identity_matrix(size):
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return np.eye(size)
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@staticmethod
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def generate_alternating_vector(size):
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return np.tile([1, 2], int(np.ceil(size / 2)))[:size]
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@staticmethod
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def get_matrix_from_file(file_path, problem):
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mat_contents = scipy.io.loadmat(file_path)
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problem_record = mat_contents['Problem'][0][0]
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A = problem_record[problem]
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if scipy.sparse.issparse(A):
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A_dense = A.todense()
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else:
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A_dense = A
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return np.array(A_dense)
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@staticmethod
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def generate_matrix_and_vector(type, size=None):
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if type == 'spd':
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if size is None:
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raise ValueError("Size must be provided for SPD matrix generation.")
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try:
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matrix, vector, lambda_min, lambda_max = MatrixGenerator.load_from_file("spd_"+str(size)+".npz")
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except FileNotFoundError as e:
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matrix = MatrixGenerator.generate_spd_matrix(size)
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vector = np.random.uniform(-1, 1, size)
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lambda_min, lambda_max = MatrixGenerator.calculate_eigenvalues(matrix)
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MatrixGenerator.save_to_file(matrix, vector, lambda_min, lambda_max, "spd_"+str(size)+".npz")
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elif type == 'nemeth12':
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try:
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matrix, vector, lambda_min, lambda_max = MatrixGenerator.load_from_file("nemeth12.npz")
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except FileNotFoundError as e:
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matrix = -1 * MatrixGenerator.get_matrix_from_file("nemeth12.mat", 1)
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size = matrix.shape[0]
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vector = MatrixGenerator.generate_alternating_vector(size)
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lambda_min, lambda_max = MatrixGenerator.calculate_eigenvalues(matrix)
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MatrixGenerator.save_to_file(matrix, vector, lambda_min, lambda_max, "nemeth12.npz")
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elif type == 'poli3':
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try:
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matrix, vector, lambda_min, lambda_max = MatrixGenerator.load_from_file("poli3.npz")
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except FileNotFoundError as e:
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matrix = MatrixGenerator.get_matrix_from_file("poli3.mat", 2)
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size = matrix.shape[0]
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vector = MatrixGenerator.generate_alternating_vector(size)
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lambda_min, lambda_max = MatrixGenerator.calculate_eigenvalues(matrix)
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MatrixGenerator.save_to_file(matrix, vector, lambda_min, lambda_max, "poli3.npz")
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else:
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raise ValueError("Invalid type specified. Choose 'spd', 'nemeth12', or 'poli3'.")
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return matrix, vector, lambda_min, lambda_max
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@staticmethod
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def calculate_eigenvalues(A):
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eigenvalues = np.linalg.eigvals(A)
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lambda_min = np.min(eigenvalues)
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lambda_max = np.max(eigenvalues)
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return lambda_min, lambda_max
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@staticmethod
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def save_to_file(matrix, vector, lambda_min, lambda_max, file_path):
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np.savez(file_path, matrix=matrix, vector=vector, lambda_min=lambda_min, lambda_max=lambda_max)
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def load_from_file(file_path):
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if not os.path.exists(file_path):
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raise FileNotFoundError(f"The file {file_path} does not exist.")
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data = np.load(file_path)
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matrix = data['matrix']
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vector = data['vector']
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lambda_min = data['lambda_min']
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lambda_max = data['lambda_max']
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return matrix, vector, lambda_min, lambda_max
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