flask将{"y":123.2885100,"x":42.7373900,"label":8}格式的json文件传给map.js,写名为dbscan的函数绘制聚类图
时间: 2023-11-04 12:06:21 浏览: 139
DBSCAN,对数据进行聚类.m
在Flask中,可以通过以下代码将JSON数据传递给前端的JavaScript代码:
```python
from flask import Flask, render_template, jsonify
app = Flask(__name__)
@app.route('/')
def index():
data = {"y":123.2885100,"x":42.7373900,"label":8}
return render_template('index.html', data=data)
if __name__ == '__main__':
app.run(debug=True)
```
在前端的`index.html`文件中,可以通过以下代码将JSON数据传递给JavaScript代码:
```html
<script>
var data = {{ data|tojson }};
</script>
```
然后,在JavaScript中可以定义名为`dbscan`的函数,使用d3.js和Leaflet.js绘制聚类图。以下是一个示例:
```javascript
function dbscan(data) {
// Initialize Leaflet map
var map = L.map('map').setView([data.y, data.x], 13);
// Add OpenStreetMap tile layer
L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', {
attribution: 'Map data © <a href="https://www.openstreetmap.org/">OpenStreetMap</a> contributors, ' +
'<a href="https://creativecommons.org/licenses/by-sa/2.0/">CC-BY-SA</a>, ' +
'Imagery © <a href="https://www.mapbox.com/">Mapbox</a>',
maxZoom: 18,
}).addTo(map);
// Use d3.js to load data and perform DBSCAN clustering
d3.json('/data.json').then(function(data) {
var dbscan = new DBSCAN();
var labels = dbscan.run(data, 0.1, 5);
// Define colors for each cluster label
var colors = ['#ff0000', '#00ff00', '#0000ff', '#ffff00', '#ff00ff', '#00ffff', '#000000', '#ffffff'];
// Create a marker for each data point, colored by cluster label
data.forEach(function(d, i) {
var color = colors[labels[i]];
var marker = L.circleMarker([d.y, d.x], {
radius: 5,
fillColor: color,
color: '#000000',
weight: 1,
opacity: 1,
fillOpacity: 0.8,
}).addTo(map);
// Add a popup with the cluster label
marker.bindPopup('Label: ' + labels[i]);
});
});
}
```
调用这个函数: `dbscan(data)` 即可在地图上绘制聚类图。
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