Matlab 石油计算机综合应用课程总结复习

图形函数
➢ figure ➢ plot ➢ plot3 ➢ scatter ➢ scatter3 ➢ meshgrid ➢ mesh(Xm,Ym,Zm) ➢ contour(Xm,Ym,Zm); ➢ surface(Xm,Ym,Zm); ➢ scatter(x,y);
插值与拟合
➢ yi = interp1(x,Y,xi) ➢ y=interp2(Xm,Ym,Zm,2000,200) ➢ ZI = griddata(x,y,z,XI,YI)
Matlab 石油计算机综合应用
课程总结复习
Matlab 基本函数
➢ x=[1 2 3 4 5 6 ] ➢ x=1:6 ➢ x=1:2:6 ➢ x=linspace(1，9，9） ➢ x=logspace(1，3，3） ➢ zeros(3,4) ➢ ones(3,4) ➢ eye(4) ➢ x=1:27;reshape(x,[3,3,3]) ➢ find(x>5) ➢ [i,j]=ind2sub(size(y),5] ➢ sub=sub2ind(size(y),[2,2])
➢
➢ figure ➢ scatter(X(:,1),X(:,2)) ➢ text(X(:,1),X(:,2),int2str((1:5)'))
➢
➢ figure ➢ dendrogram(Z)
判别分析
➢ load fisheriris ➢ SL = meas(51:end,1); ➢ SW = meas(51:end,2); ➢ group = species(51:end); ➢ h1 = gscatter(SL,SW,group,'rb','v^',[],'off'); ➢ set(h1,'LineWidth',2) ➢ legend('Fisher versicolor','Fisher virginica','Location','NW')
➢ ➢
➢ [X,Y] = meshgrid(linspace(4.5,8,100),linspace(2,4,100)); ➢ [C,err,P,logp,coeff] = classify([X(:) Y(:)],[SL SW],group,'quadratic'); ➢ hold ➢ contour(X,Y,reshape(P(:,1),[100,100]))
聚类分析
➢ X = [1 2;2.5 4.5;2 2;4 1.5;4 2.5] ➢ Y = pdist(X) ➢ Z = linkage(Y) ➢ T = cluster(Z,'cutoff',0.8) ➢ T = cluster(Z,'maxclust',2)
➢
➢ c = cophenet(Z,Y) ➢ I = inconsistent(Z)
➢
➢ sample=meas(1:51,1:2); ➢ training=meas(51:end,1:2); ➢ grouptraining=species(51:end); ➢ [groupsample,err,Psample] =
classify(sample,training,grouptraining,'quadratic');
统计
➢ 描述性统计 ➢ mean,median,mode,std, ➢ y = prctile(x,[25 50 75]) ➢ y = quantile(x,[0.25 0.50 0.75]) ➢ y = skewness(X) ➢ k = kurtosis(X)
分布函数
R = normrnd(mu,sigma) R = normrnd(mu,sigma,v) R = normrnd(mu,sigma,m,n) [muhat,sigmahat] = normfit(data) Y = normpdf(X,mu,sigma) P = normcdf(X,mu,sigma) [P,PLO,PUP] = normcdf(X,mu,sigma,pcov,alpha) X = norminv(P,mu,sigma) h = normplot(X) histfit(data) histfit(data,nbins) h = histfit(data,nbins)
回归和趋势面分析
➢= griddata(x,y,z,XI,YI)
主成份分析和因子分析
➢ [COEFF,SCORE] = princomp(X) ➢ [Loadings,specificVar,T,stats] = ...
factoran(stocks,3,'rotate','none');