数值积分:基于牛顿-柯茨公式的定步长和自适应积分方法 [MATLAB]

MATLAB实现分段积分方法,牛顿-柯茨公式定步长和自适应步长的积分方法

#先上代码后补笔记#

#可以直接复制粘贴使用的MATLAB函数!#

1. 定步长牛顿-柯茨积分公式

function [ integration ] = CompoInt( func, left, right, step, mode )
%   分段积分牛顿-柯茨公式;
%   输入5个参数:被积函数(FUNCTIONHANDLE)\'func\',积分上下界\'left\'/\'right\',步长\'step\',
%   模式mode共三种(\'midpoint\',\'trapezoid\',\'simpson\');
%   返回积分值;
switch mode
    % 仅仅是公式不同
    case \'midpoint\'
        node = left; integration = 0;
        while (node + step <= right)    % 按照给定步长开始分段积分
            pieceInt = step*(func(node + step/2));  % 使用中点积分公式
            integration = integration + pieceInt; node = node + step;
        end
        if (node < right)   % 补齐最后一段积分
            pieceInt = (right - node)*(func((node + right)/2));
            integration = integration + pieceInt;
        end
    case \'trapezoid\'
        node = left; integration = 0;
        while (node + step <= right)
            pieceInt = step*(func(node) + func(node + step))/2; % 使用梯形公式
            integration = integration + pieceInt; node = node + step;
        end
        if (node < right)
            pieceInt = (right - node)*(func(node) + func(right))/2;
            integration = integration + pieceInt;
        end
    case \'simpson\'
        node = left; integration = 0;
        while (node + step <= right)
            pieceInt = step*(func(node) + 4*func(node + step/2) + func(node + step))/6; % 使用辛普森公式
            integration = integration + pieceInt; node = node + step;
        end
        if (node < right)
            pieceInt = (right - node)*(func(node) + 4*func((node + right)/2) + func(right))/6;
            integration = integration + pieceInt;
        end
end

  

2. 自适应分段积分方法

通过函数内调用自身的方法使得积分函数显得简洁明快。因为需要调用自身计算原积分的一段,必须传入参数length标识原积分上下限总长,通过left, right和length三个参数才能够得到某一段的要求精度。

function [ integration ] = AdaptInt( func, left, right, prec, length )
%   自适应分段积分函数AdaptInt;
%   输入五个参数:被积函数(句柄)func,积分上下限right,left,要求精度prec,积分总长length;
%   输出一个参数:积分值integration;
trapeInt = (right - left)*(func(left) + func(right))/2;
midInt = (right - left)*func((left + right)/2);
err = (trapeInt - midInt)/3;    % 由中点公式和梯形公式差估算误差
if (abs(err) < prec && (right - left) < length/5)   % 如果误差符合要求,则使用辛普森公式计算较精确结果
    integration = (right - left)*(func(left) + 4*func((left + right)/2) + func(right))/6;
else    % 否则,二分该段,分别进行自适应分段积分
    integration = AdaptInt(func, left, (left + right)/2, prec/2, length) + AdaptInt(func, (left + right)/2, right, prec/2, length);
end
end