基于MATLAB的数据处理与统计作图概要
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Smooth函数:
load count.dat;
c=smooth(count(:));
C1=reshape(c,24,3);
subplot(3,1,1);plot(count,':');
hold on;
plot(C1,'-');
C2=zeros(24,3);
for I=1:3
C2(:,I)=smooth(count(:,I));
end;
subplot(3,1,2);plot(count,':');hold on; plot(C2,'-');
subplot(3,1,3);plot(C2-C1,'o-');
>> x=15*rand(150,1);
y=sin(x)+0.5*(rand(size(x))-0.5);
y(ceil(length(x)*rand(2,1)))=3; noise=normrnd(0,15,150,1);
y=y+noise;
>> yy1=smooth(x,y,0.1,'loess'); >> yy2=smooth(x,y,0.1,'rloess'); >> yy3=smooth(x,y,0.1,'moving'); >> yy4=smooth(x,y,0.1,'lowess'); >> yy5=smooth(x,y,0.1,'sgolay'); >> yy6=smooth(x,y,0.1,'rlowess');
>> [xx,ind]=sort(x);
subplot(3,2,1);plot(xx,y(ind),'b-.',xx,yy1(ind),'r-'); subplot(3,2,2);plot(xx,y(ind),'b-.',xx,yy2(ind),'r-'); subplot(3,2,3);plot(xx,y(ind),'b-.',xx,yy3(ind),'r-'); subplot(3,2,4);plot(xx,y(ind),'b-.',xx,yy4(ind),'r-'); subplot(3,2,5);plot(xx,y(ind),'b-.',xx,yy5(ind),'r-'); subplot(3,2,6);plot(xx,y(ind),'b-.',xx,yy6(ind),'r-');
Smoothts函数:
>> x=122+rand(500,4);
p=x(:,4)';
out1=smoothts(p,'b',30);
out2=smoothts(p,'b',100);
out3=smoothts(p,'g',30);
out4=smoothts(p,'g',100,100);
out5=smoothts(p,'e',30);
out6=smoothts(p,'e',100);
subplot(2,2,1);plot(p);
subplot(2,2,2);plot(out1,'k');hold on;plot(out2,'m.'); subplot(2,2,3);plot(out3,'k');hold on;plot(out4,'m.'); subplot(2,2,4);plot(out5,'k');hold on;plot(out6,'m.');
Medfilt1函数:
x=linspace(0,2*pi,250)';
y=sin(x)*150;
y(ceil(length(x)*rand(2,1)))=3; noise=normrnd(0,15,250,1);
y=y+noise;
subplot(1,2,1);plot(x,y);
yy=medfilt1(y,50);
subplot(1,2,2);plot(x,y,'r-.'); hold on;plot(x,yy,'.');
直方图:
Hist函数:
x=randn(499,1);
y=randn(499,3);
subplot(3,1,1);hist(x); subplot(3,1,2);hist(x,100); subplot(3,1,3);hist(y,25);
Histc函数:
x=-3.9:0.1:3.9;
y=randn(10000,1); subplot(1,2,1);hist(y,x); n=histc(y,x);
c=cumsum(n);
subplot(1,2,2);bar(x,c);
Histfit函数:
>> r=normrnd(10,1,10,1); >> histfit(r);
>> h=get(gca,'Children');
盒子图:
>> N=1024;x1=normrnd(5,1,N,1);
>> x2=normrnd(6,1,N,1);x=[x1 x2];subplot(2,2,1);sym1='*';notch1=1;boxplot(x,notch1,sym1); >> subplot(2,2,2);notch2=0;boxplot(x,notch2);
x=randn(100,25);subplot(2,1,1);boxplot(x);
误差条图:
>> x=0:pi/10:pi;
y=sin(x);
e=std(y)*ones(size(x)); errorbar(x,y,e)
最小二乘法拟合直线:>> x=1:10;
>> y1=x+rand(1,10); >> scatter(x,y1,25,'b','*') >> hold on;
>> y2=2*x+randn(1,10); >> plot(x,y2,'mo')
>> y3=3*x+randn(1,10); >> plot(x,y3,'rx:');
>> y4=4*x+randn(1,10); >> plot(x,y4,'g+--');