Matlab 命令记录

>> x=cell(2,3)

x =

  2×3 cell 数组

    {0×0 double}    {0×0 double}    {0×0 double}
    {0×0 double}    {0×0 double}    {0×0 double}

% 这个例子
>> title={{'pitch-RAO'} {'T'}    {'heave-波能俘获效率'} }

title =

  1×3 cell 数组

    {1×1 cell}    {1×1 cell}    {1×1 cell}

>> title(1)

ans =

  1×1 cell 数组

    {1×1 cell}

>> title{1}

ans =

  1×1 cell 数组

    {'pitch-RAO'}

>> title(1)(1)
错误:  无效的数组索引。
 
>> title(1){1}
错误:  无效的数组索引。
 
>> title{1}{1}

ans =

    'pitch-RAO'

>> title{1}(1)

ans =

  1×1 cell 数组

    {'pitch-RAO'}

set(gca,'xticklabel',get(gca,'xtick'),'yticklabel',get(gca,'ytick'));  

clc
clear
close all
x=[5:20];
y=x.^2;
figure()
% 图1:先将标签修改为文本，然后修改区间显示，文本标签重新调整位置，已经不是真实值
subplot(1,2,1)
plot(x,y,'-*',LineWidth=2)
set(gca,'xticklabel',get(gca,'xtick'),'yticklabel',get(gca,'ytick'));
xlim([0 30]);
title('图1')

% 图2:先调整区间，然后将区间转化为文本，显示正常
subplot(1,2,2)
plot(x,y,'-*',LineWidth=2)
xlim([0 30]);
set(gca,'xticklabel',get(gca,'xtick'),'yticklabel',get(gca,'ytick'));
title('图2')

xlim
% 获得当前x轴的范围，如[5 20]
xlim([0 20])
% 设定x轴范围为[0 20]

xlim([0 inf])
% 设定x轴范围为从0开始到默认最大；-inf即为默认最小

x1 = sort(rand(1, 10));                                 % Create Data
y1 = rand(size(x1));                                    % Create Data
x2 = sort(rand(1, 15));                                 % Create Data
y2 = rand(size(x2));                                    % Create Data

xi = linspace(0, 1, 50);                                % Create Vector Of Common X-Values

y1i = interp1(x1(:), y1(:), xi(:), 'linear', 'extrap'); % Interploate Or Extrapolate To New ‘x’ Values
y2i = interp1(x2(:), y2(:), xi(:), 'linear', 'extrap'); % Interploate Or Extrapolate To New ‘x’ Values

y_mean = mean([y1i y2i], 2);                            % Mean Of Y Values

figure(1)
plot(x1, y1, '-b')
hold on
plot(x2, y2, '-g')
plot(xi, y_mean, '-r', 'LineWidth',2)
hold off
grid
legend('Data 1', 'Data 2', 'Data Mean', 'Location','N')

% ---------------------------------------------------------------------------- %
% DESCRIPTION                                                                  %
% -----------                                                                  %
% Returns an average curve of multiple curves by linear interpolation. The     %
% returned average curve also has unique and sorted abscissae.                 %
% ---------------------------------------------------------------------------- %
% INPUT                                                                        %
% -----                                                                        %
% abscissae:                                                                   %
% If this argument is a scalar, it specifies the number of abscissae on which  %
% the average curve is evaluated, automatically ranging from the global        %
% minimum to the global maximum abscissa considering all curves. If this       %
% argument is a vector, the average curve is evaluated in the abscissae        %
% specified by it.                                                             %
%                                                                              %
% curves:                                                                      %
% A cell array of length n containing the data of each curve, where n is the   %
% number of curves. The data of each curve is defined by a two-column matrix,  %
% where the first column corresponds to the abscissae and the second column    %
% corresponds to the ordinates. Each curve may have a different number of      %
% points.                                                                      %
% ---------------------------------------------------------------------------- %
% OUTPUT                                                                       %
% ------                                                                       %
% curve:                                                                       %
% The abscissae and ordinates of the average curve in a two-column matrix.     %
% ---------------------------------------------------------------------------- %

function curve = avgcurve(abscissae, curves)

% determine abscissae
if isscalar(abscissae)
    xmin = +Inf;
    xmax = -Inf;
    for i = 1 : length(curves)
        imin = min(curves{i}(:,1));
        imax = max(curves{i}(:,1));
        if imin < xmin, xmin = imin; end
        if imax > xmax, xmax = imax; end
    end
    x = linspace(xmin, xmax, abscissae)';
else
    x = abscissae(:);
end

% compute ordinates
y = zeros(size(x));
k = zeros(size(x));
for i = 1 : length(curves)
    [xi, ii] = unique(curves{i}(:,1), "first");
    yi = curves{i}(ii,2);
    interp = interp1(xi, yi, x, "linear");
    k = k + ~isnan(interp);
    interp(isnan(interp)) = 0;
    y = y + interp;
end
y = y ./ k;

% done
curve = [x y];