在MATLAB中绘制CDF

Question

如何为下面给出的值生成图1所示的下图？figure 1 可以通过= [43.228 48.85 47.739 50.386 51.283 53.008 49.487 52.257 52.151 51.075 52.289 53.637 54.609 54.063 57.999 62.593 66.404 61.139 64.37 78.885 83.466 93.805 108.709 118.413 117.121 128.186 146.16 166.086 181.826 213.844 230.427 226.252 222.389 196.033 149.09 151.343 145.608 154.639 154.605 163.32 160.643 172.36 168.268 163.015 90.484 125.898 51.594 ]

还如何生成图2所示的图？对于figure

吞吐量= [43.228 48.85 47.739 50.386 51.283 53.008 49.487 52.257 52.151 51.075 52.289 53.637 54.609 54.063 57.999 62.593 66.404 61.139 64.37 78.885 83.466 93.805 108.709 118.413 117.121 128.186 146.16 166.086 181.826 213.844 230.427 226.252 222.389 196.033 149.09 151.343 145.608 154.639 154.605 163.32 160.643 172.36 168.268 163.015 90.484 125.898 51.594]

Rsrp = [-85.9 -84.2 -89.7 -85.4 -79.7 -82.8 -86.4 -87.3 -82.1 -87.4 -87.8 -83.8 -82.9 -83.1 -89.3 -83.6 -89.6 -85.3 -81.2 -87.6 -90.5 -89.7- 85.1 -87.7 -88 -90.7 -82 -80.9 -81 -81.1 -78.8 -85.9 -84.6 -86.3 -87.1 -84.1 -81.9 -84.1 -81.4 -82.8 -83.2 -82.6 -82.7 -83.4 -82.4 -81.8 -81.2- 83.1]

Answer 1

如果您要计算经验性累积分布函数，可以使用eCDF：

%%
Throughput = [43.228 48.85 47.739 50.386 51.283 53.008 49.487 52.257 52.151 51.075 52.289 53.637 54.609 54.063 57.999 62.593 66.404 61.139 64.37 78.885 83.466 93.805 108.709 118.413 117.121 128.186 146.16 166.086 181.826 213.844 230.427 226.252 222.389 196.033 149.09 151.343 145.608 154.639 154.605 163.32 160.643 172.36 168.268 163.015 90.484 125.898 51.594];
ecdf(Throughput)
hold on
ecdf(Throughput+10)
legend("first","second","location","best")
title("empirical CDF")

对于第二张图，您需要指定什么是蓝线...我假设您要绘制30个样本的movingmean：

%these two vectors are not of the same length. Just to show you I've
%removed the last item in Rsrp
Throughput = [43.228 48.85 47.739 50.386 51.283 53.008 49.487 52.257 52.151 51.075 52.289 53.637 54.609 54.063 57.999 62.593 66.404 61.139 64.37 78.885 83.466 93.805 108.709 118.413 117.121 128.186 146.16 166.086 181.826 213.844 230.427 226.252 222.389 196.033 149.09 151.343 145.608 154.639 154.605 163.32 160.643 172.36 168.268 163.015 90.484 125.898 51.594]
Rsrp = [-85.9 -84.2 -89.7 -85.4 -79.7 -82.8 -86.4 -87.3 -82.1 -87.4 -87.8 -83.8 -82.9 -83.1 -89.3 -83.6 -89.6 -85.3 -81.2 -87.6 -90.5 -89.7 -85.1 -87.7 -88 -90.7 -82 -80.9 -81 -81.1 -78.8 -85.9 -84.6 -86.3 -87.1 -84.1 -81.9 -84.1 -81.4 -82.8 -83.2 -82.6 -82.7 -83.4 -82.4 -81.8 -81.2 ]

[Rsrp,I] = sort(Rsrp); % I've sorted Rsrp to perform the moving mean
Throughput = Throughput(I); % reordered the second vector coherently with Rsrp
scatter(Rsrp,Throughput,"markeredgecolor",[.7,.7,.7]) % scatter with gray markers
hold on % overlay plots
M = movmean(Throughput,30); % performing movmean
plot(Rsrp,M,"linewidth",2,"color",[0,0,.8]) % plotting movmean
% axes labels
ylabel("Throughput [Mbits/s]") 
xlabel("Rsrp [dBm]")