帮我用python写一段代码,能够读取一份ais数据集,进行轨迹段的聚类,并且进行轨迹预测,要求输出结果可视化
时间: 2023-05-14 15:04:55 浏览: 129
非常好的问题!以下是一段Python代码,可以读取AIS数据集,进行轨迹段的聚类,并进行轨迹预测,并输出结果可视化:
```python
import pandas as pd
import numpy as np
from sklearn.cluster import DBSCAN
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier
import matplotlib.pyplot as plt
# 读取AIS数据集
ais_data = pd.read_csv('ais_data.csv')
# 轨迹段聚类
X = ais_data[['longitude', 'latitude']]
X = StandardScaler().fit_transform(X)
dbscan = DBSCAN(eps=0.5, min_samples=5)
dbscan.fit(X)
labels = dbscan.labels_
# 轨迹预测
clf = KNeighborsClassifier(n_neighbors=3)
clf.fit(X, labels)
ais_data['cluster'] = clf.predict(X)
# 结果可视化
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
for i in range(len(np.unique(labels))):
plt.scatter(ais_data[ais_data['cluster'] == i]['longitude'], ais_data[ais_data['cluster'] == i]['latitude'], c=colors[i % len(colors)])
plt.show()
```
希望这段代码能够帮助你完成任务!