6、基于highcharts实现的线性拟合，计算部分在java中实现，画的是正态概率图
内容导读
互联网集市收集整理的这篇技术教程文章主要介绍了6、基于highcharts实现的线性拟合，计算部分在java中实现，画的是正态概率图，小编现在分享给大家，供广大互联网技能从业者学习和参考。文章包含6432字，纯文字阅读大概需要10分钟。
内容图文
1、坐标点类
package
cn.test.domain;
public
class
Point {
double
x;
double
y;
public
Point(){
}
public Point(double x, double y) {
super();
this.x = x;
this.y = y;
}
publicdouble getX() {
return x;
}
publicvoid setX(double x) {
this.x = x;
}
publicdouble getY() {
return y;
}
publicvoid setY(double y) {
this.y = y;
}
}
2、拟合类，带计算部分
package
cn.test.normcdf;
import
java.io.IOException;
import
java.text.NumberFormat;
import
java.util.ArrayList;
import
java.util.Collections;
import
java.util.List;
import
javax.servlet.ServletException;
import
javax.servlet.http.HttpServlet;
import
javax.servlet.http.HttpServletRequest;
import
javax.servlet.http.HttpServletResponse;
import
net.sf.json.JSONArray;
import
net.sf.json.JSONObject;
import
org.apache.commons.math3.distribution.NormalDistribution;
import
cn.test.domain.Point;
public
class TestNormCdf extends HttpServlet {
private ArrayList<Double> cyis = null;
private ArrayList<Double> axis = null;
publicvoid doGet(HttpServletRequest request, HttpServletResponse response)
throws ServletException, IOException {
axis = new ArrayList<Double>();
cyis = new ArrayList<Double>();
// 初始化横坐标值
axis = initial(axis);
/* axis = stand(axis); */// 计算纵坐标值
//NormalDistribution normal = new NormalDistribution();
// 先排序 Collections.sort(axis);
int n = axis.size();
/* for (int i = 0; i < axis.size(); i++) {
cyis.add(normal.inverseCumulativeProbability((i + 1 - 0.5) / n));
}*/for (int i = 0; i < axis.size(); i++) {
cyis.add((i + 1 - 0.5) / n);
}
double sumX = getSum(axis);
double sumY = getSum(cyis);
double sumP2X = getPowSum(axis);
double sumXY = getSumXY(axis, cyis);
double a =(sumXY - (1 / axis.size()) * sumX * sumY) / (sumP2X - (1 /axis.size()) * sumX * sumX);
double b = (1 / axis.size()) * (sumY - a*sumX);
double pointx1 = axis.get(0);
double pointx2 = axis.get(n - 1);
double pointy1 = b+a * pointx1;
double pointy2 = b+a * pointx2;
//cyis = stand2(cyis);/*double x1 = axis.get((int) (n * 0.75));
double x2 = axis.get((int) (n * 0.25));
double y1 = cyis.get((int) (n * 0.75));
double y2 = cyis.get((int) (n * 0.25));
double dx = x1 - x2;
double dy = y1 - y2;
double a = dy / dx;
double pointx1 = axis.get(0);
double pointx2 = axis.get(n - 1);
double centreX = 0.5 * (x1 + x2);
double centreY = 0.5 * (y1 + y2);
double pointy1 = centreY - a * (centreX - pointx1);
double pointy2 = centreY + a * (pointx2 - centreX);*/
Double[][] array = new Double[axis.size() + 2][2];
NumberFormat ddf1 = NumberFormat.getNumberInstance();
ddf1.setMaximumFractionDigits(4);
for (int i = 0; i < axis.size(); i++) {
array[i][0] = Double.valueOf(ddf1.format(axis.get(i)));
array[i][1] = Double.valueOf(ddf1.format(cyis.get(i)));
}
array[axis.size()][0] = Double.valueOf(ddf1.format(pointx1));
array[axis.size()][1] = Double.valueOf(ddf1.format(pointy1));
array[axis.size() + 1][0] = Double.valueOf(ddf1.format(pointx2));
array[axis.size() + 1][1] = Double.valueOf(ddf1.format(pointy2));
response.getWriter().write(JSONArray.fromObject(array).toString());
}
public ArrayList<Double> stand2(ArrayList<Double> cyis) {
int n = cyis.size();
NormalDistribution normal = new NormalDistribution();
for (int i = 0; i < cyis.size(); i++) {
cyis.set(i, normal.cumulativeProbability(cyis.get(i)));
}
return cyis;
}
/*
* public ArrayList<Double> stand(ArrayList<Double> list) { double average =
* getAverage(list); double std = getStdVariance(list); for (int i = 0; i <
* list.size(); i++) { list.set(i, (list.get(i) - average) / std); } return
* list; }
*
* public double getStdVariance(ArrayList<Double> list) { double std = 0.0;
* double average = getAverage(list); for (int i = 0; i < list.size(); i++)
* { std += Math.pow((list.get(i) - average), 2); } return std /
* list.size(); }
*
* public double getAverage(ArrayList<Double> list) { return getSum(list) /
* list.size(); }
*/publicdouble getSum(ArrayList<Double> list) {
double sum = 0.0;
for (Double value : list) {
sum += value;
}
return sum;
}
publicdouble getSumXY(ArrayList<Double> X, ArrayList<Double> Y) {
double sum = 0.0;
for (int i = 0; i < X.size(); i++) {
sum += X.get(i) * Y.get(i);
}
return sum;
}
publicdouble getPowSum(ArrayList<Double> list) {
double sum = 0.0;
for (Double value : list) {
sum += Math.pow(value, 2);
}
return sum;
}
public ArrayList<Double> initial(ArrayList<Double> axis) {
axis = new ArrayList<Double>();
axis.add(9.0);
axis.add(11.0);
axis.add(15.0);
axis.add(20.0);
axis.add(30.0);
axis.add(40.0);
axis.add(35.0);
axis.add(80.0);
axis.add(50.0);
axis.add(60.0);
axis.add(55.0);
axis.add(45.0);
axis.add(65.0);
axis.add(70.0);
axis.add(58.0);
axis.add(72.0);
axis.add(66.0);
axis.add(59.0);
return axis;
}
publicvoid doPost(HttpServletRequest request, HttpServletResponse response)
throws ServletException, IOException {
doGet(request, response);
}
}
3、html部分代码
<
script
src
="http://cdn.hcharts.cn/jquery/jquery-1.8.3.min.js"
></
script
>
<
script
src
="${pageContext.request.contextPath}/js/highcharts.js"
></
script
>
<
script
type
="text/javascript"
>
$(
function
(){
$.post(
"
/Test_Polyfit/TestNormCdf
"
,
null
,
function
(data){
var
array
=
eval(data);
$(
"
#container
"
).highcharts({
chart:{
zoomType:
‘
xy
‘
},
title:{
text:
‘
Normal Probability of Wait Time
‘
},
xAxis:{
title:{
enabled:
true
,
text:
‘
Wait Time
‘
},
startOnTick:
true
,
endOnTick:
true
,
showLastLabel:
true
},
yAxis:{
title:{
text:
‘
Probability in normal distribution
‘
},
min:
0
,
max:
1
,
staggerLines:
20
,
allowDecimals:
true
},
legend:{
layout:
‘
vertical
‘
,
align:
‘
left
‘
,
verticalAlign:
‘
top
‘
,
x:
100
,
y:
70
,
floating:
true
,
backgroundColor:
‘
#FFFFFF
‘
,
borderWidth:
1
},
plotOptions: {
scatter: {
marker: {
radius:
5
,
states: {
hover: {
enabled:
true
,
lineColor:
‘
rgb(100,100,100)
‘
}
}
},
states: {
hover: {
marker: {
enabled:
false
}
}
},
tooltip: {
headerFormat:
‘
<b>{series.name}</b><br>
‘
,
pointFormat:
‘
{point.x} cm, {point.y} kg
‘
}
}
},
series: [{
type:
‘
scatter
‘
,
name:
‘
point
‘
,
color:
‘
rgba(223, 83, 83, .5)
‘
,
data: array
},{
type:
‘
line
‘
,
name:
‘
polyfitline
‘
,
color:
‘
black
‘
,
data: [array.pop(),array.pop()]
}]
});
});
});
</
script
>
</
head
>
<
body
>
<
div
id
="container"
></
div
>
4、最后实现的效果
原文：http://www.cnblogs.com/weizhen/p/5823877.html
内容总结
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