fittype曲线拟合_MATLAB

前言

一、fittype函数

二、使用方法

1.语法描述

2.官方实例

3.个人实例

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前言

MATLAB曲线拟合的方法有许多种，大致分为两种，一种是自己编写代码调用函数的形式，另一种是用MATLAB已有的cftool拟合工具箱。按照上述的方法能解决大多数的问题，但是在一些特定情况下，需要自己定义的一些函数形式进行曲线拟合，这时候需要用到fittype函数来进行拟合。

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一、fittype函数

自定义曲线和曲面拟合的拟合类型

二、使用方法

1.语法描述

1、aFittype = fittype(libraryModelName)
//creates the fittype object aFittype for the model specified by libraryModelName

2、aFittype = fittype(expression)
//creates a fit type for the model specified by the MATLAB® expression.
3、aFittype = fittype(expression,Name,Value)
//constructs the fit type with additional options specified by one or more Name,Value pair //arguments.

4、aFittype = fittype(linearModelTerms)
//creates a fit type for a custom linear model with terms specified by the expressions in //linearModelTerms.
5、aFittype = fittype(linearModelTerms,Name,Value)
//constructs the fit type with additional options specified by one or more Name,Value pair //arguments.

6、aFittype = fittype(anonymousFunction)
//creates a fit type for the model specified by anonymousFunction.
7、aFittype = fittype(anonymousFunction,Name,Value)
//constructs the fit type with additional options specified by one or more Name,Value pair //arguments.

2.官方实例

1、f = fittype('poly3')
   //运行结果
     f = 
     Linear model Poly3:
     f(p1,p2,p3,p4,x) = p1*x^3 + p2*x^2 + p3*x + p4

2、f = fittype('rat33')
   //运行结果
     f = 
     General model Rat33:
     f(p1,p2,p3,p4,q1,q2,q3,x) = (p1*x^3 + p2*x^2 + p3*x + p4) /
               (x^3 + q1*x^2 + q2*x + q3)

3、g = fittype('a*u+b*exp(n*u)',...
            'problem','n',...
            'independent','u')
   //运行结果
     g = 
     General model:
     g(a,b,n,u) = a*u+b*exp(n*u)

4、g = fittype('a*time^2+b*time+c','independent','time','dependent','height')
   //运行结果
     g = 
     General model:
     g(a,b,c,time) = a*time^2+b*time+c

5、x = linspace(1,100);  
   y = 5 + 7*log(x);
   myfittype = fittype('a + b*log(x)',...
                       'dependent',{'y'},'independent',{'x'},...
                       'coefficients',{'a','b'})

   //运行结果
     myfittype = 
     General model:
     myfittype(a,b,x) = a + b*log(x)

3.个人实例

        实现功能为：调取excel表格中某些范围里的数据，将其中一些作为自变量输入，另一些作为因变量输入，编写自己的函数模型，之后定义横纵坐标范围，拟合曲线图并给出拟合参数值。

close all;
clc;
clear;

syms m1 m2 t n p;
m1='B1:F1';
m2='B1:F1';
x = xlsread('C:\packpage installation\MATLAB2016a\User_Yu\data20220611.xlsx',1,m1);
y = xlsread('C:\packpage installation\MATLAB2016a\User_Yu\data20220611.xlsx',1,m2);
plot(x',y','r*');
myfittype=fittype('1./(1+10.^(n.*(p-x)))','independent','x','dependent','y');
myfit = fit(x',y',myfittype,'StartPoint',[0.3 5]);
xi=0.4:0.5:9;
yi=myfit(xi);
plot(x',y','r*',xi,yi,'b-');

结果为：

输出的位置参数值为：

>> myfit

myfit = 

     General model:
     myfit(x) = 1./(1+10.^(n.*(p-x)))
     Coefficients (with 95% confidence bounds):
       n =      0.8775  (-0.1604, 1.915)
       p =       5.346  (4.365, 6.327)

曲线拟合成功

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