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Find2waveForR1addR2.m
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Find2waveForR1addR2.m
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Pt_Subs_input = 'D:\yunxia\ML\huigui\data for calibration\input';%存放待处理数据的路径
Nm_Vd_input = [];%存放文件名的结构体
Fd_Subs_input = dir(Pt_Subs_input);%提取所有文件
fL = size(Fd_Subs_input,1);%统计文件个数
for i = 3:fL
Nm_Vd_input{i-2,1} = Fd_Subs_input(i).name;%单独提取出文件名属性
end
Pt_Subs_output = 'D:\yunxia\ML\huigui\data for calibration\output';%存放待处理数据的路径
Nm_Vd_output = [];%存放文件名的结构体
Fd_Subs_output = dir(Pt_Subs_output);%提取所有文件
fL = size(Fd_Subs_output,1);%统计文件个数
for i = 3:fL
Nm_Vd_output{i-2,1} = Fd_Subs_output(i).name;%单独提取出文件名属性
end
for i=1:1:(fL-2)
nm_vd_output = Nm_Vd_output{i,1};
Local_output = strcat('D:\yunxia\ML\huigui\data for calibration\output\',nm_vd_output);
datas_out = xlsread(Local_output);
Fit_out_vector = datas_out(2,:);
Index_noNaN = find(~isnan(Fit_out_vector));%找到非缺失的列
Fit_out_vector = Fit_out_vector(:,Index_noNaN);
nm_vd_input = Nm_Vd_input{i,1};
Local_input = strcat('D:\yunxia\ML\huigui\data for calibration\input\',nm_vd_input);
datas = xlsread(Local_input);
datas = datas(:,2:end);
datas = datas(:,Index_noNaN);
%------------第二轮筛选，剔除datas中含NaN的列
[Index_noNaN_row,Index_noNaN_column] = find(isnan(datas));
datas(:,unique(Index_noNaN_column)) = [];
Fit_out_vector(:,unique(Index_noNaN_column)) = [];
Fit_out_vector = Fit_out_vector';
%----------这里我先试一下波长从350---500的----------------
datas = datas(51:651,:);%只算400-1000
%-----------------------------------------------
Fit_in_vector = zeros(size(datas,2),1);
R_matrix = zeros(size(datas,1),size(datas,1));
wave_selected = zeros(2,1);
R_max = 0;%这里对相关性随便令个小的值
for i = 1:1:size(datas,1)
i
tic
for j = i:1:size(datas,1)
%Fit_in_vector = (datas(i,:) - datas(j,:))./(datas(i,:) - datas(k,:));%computing according ()
% Fit_in_vector = datas(i,:)./datas(j,:);
Fit_in_vector = (datas(i,:) - datas(j,:))./(datas(i,:) + datas(j,:));
Fit_in_vector = Fit_in_vector';
%[R,P] = corrcoef(Fit_in_vector,Fit_out_vector);
[R,P] = corr(Fit_in_vector,Fit_out_vector, 'type' , 'Spearman');
R_matrix(i,j) = R;
if abs(R) > abs(R_max)
R_max = R;
wave_selected = [i;j];
end
end
toc
end
%上面求出的是一个上三角矩阵，下面把它对称的部分补齐
for i = 1:size(R_matrix,1)
for j = 1:i
R_matrix(i,j,:) = R_matrix(j,i,:);
end
end
R_matrix = abs(R_matrix);
wave_selected = wave_selected + 400;
%--------------------------------------------------------------------
savename = strcat('D:\yunxia\ML\huigui\resultR1addR2\','R_matrix',nm_vd_output);
savename = savename(1:end-5);
save(savename,'R_matrix');
savename = strcat('D:\yunxia\ML\huigui\resultR1addR2\','R_max',nm_vd_output);
savename = savename(1:end-5);
save(savename,'R_max');
savename = strcat('D:\yunxia\ML\huigui\resultR1addR2\','wave_selected',nm_vd_output);
savename = savename(1:end-5);
save(savename,'wave_selected');
%------------producing figure------------------
R_matrix_figure = zeros(1000,1000);
R_matrix_figure(400:1000,400:1000) = abs(R_matrix);
% x = [1:size(datas,1)];
% y = [1:size(datas,1)];
x = [1:1000];
y = [1:1000];
rgb = pcolor(x,y,R_matrix_figure);
colorbar
set(rgb, 'LineStyle','none');
axis([400 1000 400 1000]);
end
% Local_output = 'D:\yunxia\ML\回归\回归\data for calibration\baigurang fan\白骨壤chl.xlsx';
% datas_out = xlsread(Local_output);
% Fit_out_vector = datas_out(2,:);
% Index_noNaN = find(~isnan(Fit_out_vector));%找到非缺失的列
% Fit_out_vector = Fit_out_vector(:,Index_noNaN);
%
%
% Local_input = 'D:\yunxia\ML\回归\回归\data for calibration\baigurang fan\baigurang-fan.mn.xlsx';
% datas = xlsread(Local_input);
% datas = datas(:,2:end);
% datas = datas(:,Index_noNaN);
% %------------第二轮筛选，剔除datas中含NaN的列
% [Index_noNaN_row,Index_noNaN_column] = find(isnan(datas));
% datas(:,unique(Index_noNaN_column)) = [];
% Fit_out_vector(:,unique(Index_noNaN_column)) = [];
%
% Fit_out_vector = Fit_out_vector';
% %----------这里我先试一下波长从350---500的----------------
% %datas = datas(1:150,:);
% %-----------------------------------------------
% Fit_in_vector = zeros(size(datas,2),1);
% R_matrix = zeros(size(datas,1),size(datas,1));
% wave_selected = zeros(2,1);
% R_max = 0;%这里对相关性随便令个小的值
% for i = 1:1:size(datas,1)
% i
% tic
% for j = 1:1:size(datas,1)
% %Fit_in_vector = (datas(i,:) - datas(j,:))./(datas(i,:) - datas(k,:));%computing according ()
% Fit_in_vector = datas(i,:)./datas(j,:);
% Fit_in_vector = Fit_in_vector';
% %[R,P] = corrcoef(Fit_in_vector,Fit_out_vector);
% [R,P] = corr(Fit_in_vector,Fit_out_vector, 'type' , 'Spearman');
% R_matrix(i,j) = R;
% if abs(R) > abs(R_max)
% R_max = R;
% wave_selected = [i;j];
% end
% end
% toc
% end
% save('R_matrix_R1toR2','R_matrix');
% save('R_max_R1toR2','R_max');
% %------------producing figure------------------
% R_matrix_figure = zeros(2500,2500);
% R_matrix_figure(350:2500,350:2500) = abs(R_matrix);
% % x = [1:size(datas,1)];
% % y = [1:size(datas,1)];
% x = [1:2500];
% y = [1:2500];
% rgb = pcolor(x,y,R_matrix_figure);
% colorbar
% set(rgb, 'LineStyle','none');
% axis([350 2500 350 2500]);