pip install matplotlib
pip install numpy

import matplotlib.pyplot as plt

# 生成時間序列數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y1 = [10, 15, 13, 17, 20]
y2 = [8, 12, 14, 18, 22]

# 繪制兩個時間序列的折線圖
plt.plot(x, y1, label='y1')
plt.plot(x, y2, label='y2')

# 設(shè)置圖形屬性
plt.xlabel('Time')
plt.ylabel('Value')
plt.title('Comparison of two time series')
plt.legend()

# 顯示圖形
plt.show()

import numpy as np

# 生成時間序列數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y1 = [10, 15, 13, 17, 20]
y2 = [8, 12, 14, 18, 22]

# 計算相關(guān)系數(shù)
corr = np.corrcoef(y1, y2)[0, 1]

# 輸出結(jié)果
print('Correlation coefficient:', corr)

import numpy as np

# 生成時間序列數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y1 = [10, 15, 13, 17, 20]
y2 = [8, 12, 14, 18, 22]

# 動態(tài)時間規(guī)整算法
def dtw_distance(ts_a, ts_b, d=lambda x, y: abs(x - y)):
    DTW = {}

    # 初始化邊界條件
    for i in range(len(ts_a)):
        DTW[(i, -1)] = float('inf')
    for i in range(len(ts_b)):
        DTW[(-1, i)] = float('inf')
    DTW[(-1, -1)] = 0

    # 計算DTW矩陣
    for i in range(len(ts_a)):
        for j in range(len(ts_b)):
            cost = d(ts_a[i], ts_b[j])
            DTW[(i, j)] = cost + min(DTW[(i-1, j)], DTW[(i, j-1)], DTW[(i-1, j-1)])

    # 返回DTW距離
    return DTW[len(ts_a)-1, len(ts_b)-1]

# 計算兩個時間序列之間的DTW距離
dtw_dist = dtw_distance(y1, y2)

# 輸出結(jié)果
print('DTW distance:', dtw_dist)