MATLAB: How to match two different matrices

Question

Hello, I have two matrices of different lengths and this is what the scenario looks like ..

 x = [...]; 
y = [...]; 
size(x) = 5800 * 16 
size(y) = 450 * 14 
% X & Y have dates & times in the first six columns in this form:  
% year, month, day, hour, minute, second 
% Each column represents a variable 
% Each row represents a data sample 
% A model to predict a variable in (X) after some time 
... 
X_time + some_time = predicted_time; % in hours 
% "X_time" is the time of (X) 
% "Y_time" is the time of (Y) 
% Match that predicted time with the time of (Y) within a range of +/- 11 hours 
for i = 1:length(x) 
    for j = 1:length(y) 
        if (predicted_time >= Y_time-11) && (Y_time+11 >= predicted_time) is True 
            MATCHED = [x(i,:) y(j,:) predicted_time]; 
        end 
    end 
end

Please, I want to know how to make this work as I tried a lot but it didn't work properly.

Answer 1

I've made an attempt to fix your code and match the two time-vectors. I've converted your time-vectors to datetime format and fixed your matching-algorithm. The matching works by looping through the modelled time-vector, which is based on the longer time-vector (SET1), and finding the closest match in the smaller time-vector (SET2). A match is only stored if the absolute difference is smaller than 11 hours.

The output, id, is a vector with two columns, where each row [id1 id2] shows the matched indices, i.e. the row of SET1 with the corresponding row of SET2.

NOTE: id is longer than SET2, which would indicate that some elements of SET2 are matched twice.

%%Read Data 
soho = xlsread('start.xlsx');       % initial storms data 
shocks = xlsread('end.xlsx', 1);    % final storms data 
%%Start Time 
%%EDITED  %%
t1=datetime(soho(4:end,1:6));
t2=datetime(shocks(4:end,1:6));
%%ORIGINAL CODE %%
%%Parameters 
% CMEs 
CPA = soho(4:end,7); 
w = soho(4:end,8); 
vl = soho(4:end,9); 
vi = soho(4:end,10); 
vf1 = soho(4:end,11); 
v20Rs = soho(4:end,12); 
a1 = soho(4:end,13); 
mass = soho(4:end,14); 
KE = soho(4:end,15); 
MPA = soho(4:end,16); 
% Shocks  
vfinal = shocks(4:end,11); 
T =shocks(4:end,13); 
N = shocks(4:end,14); 
%%Inistial Values 
AU = 149599999.99979659915;  % Sun-Earth distance in km 
d = 0.76 * AU;               % cessation distance in km 
%%Pre-Allocating Variables 
a_calc = zeros(size(vl)); 
squareRoot = zeros(size(vl)); 
A = zeros(size(vl)); 
B = zeros(size(vl)); 
ts = zeros(size(vl)); 
t_hrs = zeros(size(vl));     % predicted transit time in hours 
t_mn = zeros(size(vl));      % predicted transit time in minutes  
%%G2001 Model 
% calculations 
for i = 1:length(vl) 
    a_calc(i) = power(-10,-3) * ((0.0054*vl(i)) - 2.2); % in km/s2 
    squareRoot(i) = sqrt(power(vl(i),2) + (2*a_calc(i)*d)); 
    A(i) = (-vl(i) + squareRoot(i)) / a_calc(i); 
    B(i) = (AU - d) / squareRoot(i); 
    ts(i) = A(i) + B(i);                                % in seconds 
    t_mn(i) = ts(i) / 60;                               % in minutes 
end
clear i;
t_model=t1+minutes(t_mn);
%%Show the predicted travel time 
% CME-ICME Matching 
%%EDITED FROM HERE AND ON %%
id=nan(numel(t_model),2);
for i=1:numel(t_model)
    [MinDiff ind]=min(abs(t2-t_model(i)));
    if MinDiff<hours(11)
        id(i,1:2)=[i ind];
    else
        id(i,1:2)=[i NaN];
    end
end
id(isnan(id(:,2)),:)=[];
plot(id(:,1),id(:,2),'.')