帮我写一个将一维时间序列转换为二维递归图的矩阵函数

将一维时间序列转换为二维递归图（也称为相邻矩阵或邻接矩阵）通常涉及创建一个矩阵，其中行和列都代表时间序列中的元素，而矩阵元素表示两个元素之间的关联或临近程度。下面是一个简单的Python函数示例，使用numpy库：

import numpy as np

def time_series_to_adjacency_matrix(seq, threshold=1):
    """
    Function to convert a one-dimensional time series into a two-dimensional recursive adjacency matrix.
    
    Parameters:
    seq (list or array): The one-dimensional time sequence.
    threshold (int or float, optional): The similarity threshold for determining adjacent elements. Defaults to 1.

    Returns:
    adj_matrix (numpy.ndarray): A square matrix where (i, j) element is non-zero if |seq[i] - seq[j]| <= threshold, and zero otherwise.
    """
    n = len(seq)
    adj_matrix = np.zeros((n, n), dtype=int)

    # Iterate over pairs of indices
    for i in range(n):
        for j in range(i+1, n):
            distance = abs(seq[i] - seq[j])  # Compute the absolute difference between elements
            if distance <= threshold:
                adj_matrix[i, j] = adj_matrix[j, i] = 1  # Mark as connected if within threshold

    return adj_matrix

# Example usage:
time_series = [1, 2, 3, 4, 5]
adj_matrix = time_series_to_adjacency_matrix(time_series)

这个函数会返回一个二维矩阵，其中非零元素表示时间序列中的元素在阈值范围内是相邻的。