Python 比较两个时间序列在图形上是否相似

pip install matplotlib
pip install numpy

import matplotlib.pyplot as plt

# 生成时间序列数据
x = [1, 2, 3, 4, 5]
y1 = [10, 15, 13, 17, 20]
y2 = [8, 12, 14, 18, 22]

# 绘制两个时间序列的折线图
plt.plot(x, y1, label='y1')
plt.plot(x, y2, label='y2')

# 设置图形属性
plt.xlabel('Time')
plt.ylabel('Value')
plt.title('Comparison of two time series')
plt.legend()

# 显示图形
plt.show()

import numpy as np

# 生成时间序列数据
x = [1, 2, 3, 4, 5]
y1 = [10, 15, 13, 17, 20]
y2 = [8, 12, 14, 18, 22]

# 计算相关系数
corr = np.corrcoef(y1, y2)[0, 1]

# 输出结果
print('Correlation coefficient:', corr)

import numpy as np

# 生成时间序列数据
x = [1, 2, 3, 4, 5]
y1 = [10, 15, 13, 17, 20]
y2 = [8, 12, 14, 18, 22]

# 动态时间规整算法
def dtw_distance(ts_a, ts_b, d=lambda x, y: abs(x - y)):
DTW = {}

# 初始化边界条件
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

# 计算DTW矩阵
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距离
return DTW[len(ts_a)-1, len(ts_b)-1]

# 计算两个时间序列之间的DTW距离
dtw_dist = dtw_distance(y1, y2)

# 输出结果
print('DTW distance:', dtw_dist)