我有一个光谱数据(在x轴上有1000个变量,峰值强度为y),以及我从一个函数中得到的各个特定x位置的感兴趣峰的列表(一个称为峰值的矩阵)。在这里,我想画一条线,从每个山峰的最大值到X轴--或者,最终,在每个山峰上方放置一个垂直箭头--但我读到它很麻烦,所以只需要一条垂直线是受欢迎的。但是,使用下面的代码,我得到了“使用行值必须是数字类型的向量的错误”。有什么想法吗?
X = spectra;
[Peak,intensity]=PeakDetection(X);
nrow = length(Peak);
Peak2=Peak; % to put inside the real xaxis value
plot(xaxis,X);
hold on
for i = 1 : nbrow
Peak2(:,i) = round(xaxis(:,i)); % to get the real xaxis value and round it
xline = Peak2(:,i);
line('XData',xline,'YData',X,'Color','red','LineWidth',2);
end
hold off
发布于 2017-01-18 11:47:35
简单注释:
下面是一个简单的注释峰值的方法:
plot(x,y,x_peak,y_peak+0.1,'v','MarkerFaceColor','r');
其中x
和y
是您的数据,x_peak
和y_peak
是要注释的峰值的坐标。添加0.1
只是为了更好地放置注释,应该根据您的数据进行校准。
例如(带有一些任意数据):
x = 1:1000;
y = sin(0.01*x).*cos(0.05*x);
[y_peak,x_peak] = PeakDetection(y); % this is just a sketch based on your code...
plot(x,y,x_peak,y_peak+0.1,'v','MarkerFaceColor','r');
结果:
行注释:
这只是稍微复杂一点,因为我们需要4个值的每一行。同样,假设x_peak
和y_peak
与以前一样:
plot(x,y);
hold on
ax = gca;
ymin = ax.YLim(1);
plot([x_peak;x_peak],[ymin*ones(1,numel(y_peak));y_peak],'r')
% you could write instead:
% line([x_peak;x_peak],[ymin*ones(1,numel(y_peak));y_peak],'Color','r')
% but I prefer the PLOT function.
hold off
其结果是:
箭头注释:
如果您真的想要这些箭头,那么首先需要将峰值位置转换为规范化的数字单位。在这里,如何做到这一点:
plot(x,y);
ylim([-1.5 1.5]) % only for a better look of the arrows
peaks = [x_peak.' y_peak.'];
ax = gca;
% This prat converts the axis unites to the figure normalized unites
% AX is a handle to the figure
% PEAKS is a n-by-2 matrix, where the first column is the x values and the
% second is the y values
pos = ax.Position;
% NORMPEAKS is a matrix in the same size of PEAKS, but with all the values
% converted to normalized units
normpx = pos(3)*((peaks(:,1)-ax.XLim(1))./range(ax.XLim))+ pos(1);
normpy = pos(4)*((peaks(:,2)-ax.YLim(1))./range(ax.YLim))+ pos(2);
normpeaks = [normpx normpy];
for k = 1:size(normpeaks,1)
annotation('arrow',[normpeaks(k,1) normpeaks(k,1)],...
[normpeaks(k,2)+0.1 normpeaks(k,2)],...
'Color','red','LineWidth',2)
end
其结果是:
https://stackoverflow.com/questions/41647411
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