我有this data我希望进行主成分分析。
特别是对于我想要关联颜色的每个数据点。
这是我的代码:
for ii=1:size(SBF_ens,1)
SBF(ii) = SBF_ens(ii, max(find(SBF_ens(ii,:)~=0)) ); %value at the moment of the measurement
end
%matrix of data
toPCA =[
wind_trend_72h_ens-nanmean(wind_trend_72h_ens);
wind_trend_24h_ens-nanmean(wind_trend_24h_ens);
wind_trend_12to18h_ens-nanmean(wind_trend_12to18h_ens);
wind_trend_0to12h_ens-nanmean(wind_trend_0to12h_ens);
wind_trend_last6h_ens-nanmean(wind_trend_last6h_ens);
Mwind12h_ens-nanmean(Mwind12h_ens);
Mwind24h_ens-nanmean(Mwind24h_ens);
SBF-nanmean(SBF)]';
variables = { 'wt72h','wt24h','wt12to18h','wt0to12h','wtLast6h','Mw12h', 'Mw24h', 'SBF'}; %labels
%PCA algorithm
C = corr(toPCA,toPCA);
w = 1./var(toPCA);
[wcoeff,score,latent,tsquared,explained] = pca(toPCA,'VariableWeights',w);
coefforth = diag(sqrt(w))*wcoeff;
metric=decstd_ens; %metric for colorbar
hbi=biplot(coefforth(:,1:2),'scores',score(:,1:2),'varlabels',...
variables,'ObsLabels', num2str([1:length(toPCA)]'),...
'markersize', 15);
%plotting
cm = autumn;
colormap(cm);
for ii = length(hbi)-length(toPCA):length(hbi)
userdata = get(hbi(ii), 'UserData');
if ~isempty(userdata)
indCol = ceil( size(cm,1) * abs(metric(userdata))/max(abs(metric)) );%maps decstd between 0 and 1 and find the colormap index
if indCol==0 %just avoid 0
indCol=1;
end
col = cm(indCol,:); %color corresponding to the index
set(hbi(ii), 'Color', col); %modify the dot's color
end
end
for ii = 1:length(hbi)-length(toPCA)-1 %dots corresponding to the original dimensions are in black
set(hbi(ii), 'Color', 'k');
end
c=colorbar;
ylabel(c,'decstd') %is this true?
xlabel(['1^{st} PCA component ', num2str(explained(1)), ' of variance explained'])
ylabel(['2^{nd} PCA component ', num2str(explained(2)), ' of variance explained'])
除了色条范围外,一切都很好。实际上decstd
的值介于0和2之间。实际上我完全不了解颜色条上的值是什么。
有人理解吗?
是否可以重新启动彩条中的数据?那么要了解它们是什么?
答案 0 :(得分:3)
size(autumn)
向您显示autumn
colourmap(实际上是所有colourmaps)的默认长度为64
。当您致电colorbar
时,默认情况下会使用1
到n
的刻度标签,其中n
是您的彩色地图的长度,在本例中为64
。
如果您希望colourbar ticklabels的映射与您用于使数据适合1
和64
之间的映射(即您的此行indCol = ceil( size(cm,1) * abs(metric(userdata))/max(abs(metric)) );
)匹配,那么你需要自己设置这个
numTicks = 6;
cAxisTicks = linspace(min(metric), max(metric), numTicks); % or whatever the correct limits are for your data
caxis([min(metric), max(metric)]);
set(c,'YTick', cAxisTicks );