利用 python+plotly 制作双波源干涉现象的3D Surface Plots三维图像

本人在学习完制作双波源干涉现象的的二维Contour Plots图像之后，发现 plotly 还有3D 图像制作，也就是3D Surface Plots，这个更能展示双波源干涉现象的结果，果然学之。中间有些地方要说明一下，3D Surface Plots图表默认的底部是正方形，所以我采用了100*100的干涉图，然后加上一层透明的图标，让图像压扁，不然图标的上下限就是波动位置，看起来非常不雅观。

下面分享代码和结果：

下面是 python部分的代码：

#!/usr/bin/python
# coding=utf-8

import plotly.plotly

z = []
with open("/Users/Vicky/Documents/workspace/fission/long/intervene.log") as apidata:
    for i in apidata:
        data = i.split("\n")[0].split(",")
        z.append(data)
matrix = [[20 for zij in zi] for zi in z]#为了让立体图压扁
plotly.offline.plot([
     dict(
            z=z,
            type="surface"
    ),
    dict(
            z=matrix,
            showscale=False,
            opacity=0.01,#透明度
            type="surface"
    )
], filename="2222.html")

下面是 java 部分的代码，是为了生成数据：

package practise;

import java.awt.Point;
import java.util.ArrayList;
import java.util.List;
import source.SourceCode;

public class Intervene extends SourceCode {
	public List<List<Double>> data = new ArrayList<>();

	public static void main(String[] args) {
		Intervene intervene = new Intervene();
		intervene.testDemo001();
	}

	public void testDemo001() {
		Point point1 = new Point(25, 25);
		Point point2 = new Point(75, 75);
		int lamda = 6;
		for (int i = 0; i < 100; i++) {// y 轴
			List<Double> distance = new ArrayList<>();
			for (int j = 0; j < 100; j++) {// x 轴
				Point point = new Point(j, i);
				double x = point.distance(point1) % lamda / lamda;
				double y = point.distance(point2) % lamda / lamda;
				double xx = Math.sin(x * 2 * Math.PI);
				double yy = Math.sin(y * 2 * Math.PI);
				distance.add(xx + yy);
			}
			data.add(distance);
		}
		StringBuffer content = new StringBuffer();
		int size = data.size();
		for (int i = 0; i < size; i++) {
			String text = data.get(i).toString();
			text = text.substring(1, text.length() - 1);
			if (i == 0)
				content.append(text);
			content.append(LINE + text);
		}
		logLong("intervene.log", content.toString());
	}
}

下面是3D Surface Plots图的截图：

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