How can I merge my data set based on the time in MATLAB?

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I want to merge the two data into one. But as they are in two different times that's why I cannot just combine them.

I need to add them by keeping the time as it is. How can I do this?

data_1_y_axes=[0,1,3,5,4,6,8,9,7]
time_1_x_axes=[.02,0.03,.05,.06,.07,0.08,0.09,.1,.2]
data_2_y_axes=[0,2,4,5,2,7,5,7,5]
time_2_x_axes=[.002,0.004,.006,.009,.02,0.04,0.06,.07,.09]
plot(time_1_x_axes,data_1_y_axes)
hold on
plot(time_2_x_axes,data_2_y_axes)

My expected data will be as follows:

New_data=[ 0, 2,4,5,2+0,1,7,3,5+5,7+4,6,5+8,9,7]
New_time=[.002,.004,.006,.009,.02,.03,.04,.05,.06,.07,.08,.09,.1,.2]

How can I do this? This is my sample image. I want to add these two plots into one

plot matrix matlab sum arrays
3 Answers

Here is another way to do it without using a for loop. This will run much faster:

data_1_y_axes=[0,1,3,5,4,6,8,9,7]
time_1_x_axes=[.02,0.03,.05,.06,.07,0.08,0.09,.1,.2]
data_2_y_axes=[0,2,4,5,2,7,5,7,5]
time_2_x_axes=[.002,0.004,.006,.009,.02,0.04,0.06,.07,.09]

[time_merged,i1,i2] = intersect(time_1_x_axes, time_2_x_axes)
data_merged = data_1_y_axes(i1) + data_2_y_axes(i2)

[time1_remaining, ir1] = setdiff(time_1_x_axes, time_merged)
[time2_remaining, ir2] = setdiff(time_2_x_axes, time_merged)

[time_merged, idx] = sort([time_merged time_1_x_axes(ir1) time_2_x_axes(ir2)])
data_merged = [data_merged data_1_y_axes(ir1) data_2_y_axes(ir2)]
data_merged = data_merged(idx)

plot(time_merged,data_merged)
user_305810

You could combine the x and y axis arrays, then aggregate by x-axis values using

  • unique to get unique x values and their indices within the y values) and
  • accumarray to add up all of the y values with a common x axis index

Using your example data, this would look like:

y1 =[0,1,3,5,4,6,8,9,7];
x1 =[.02,0.03,.05,.06,.07,0.08,0.09,.1,.2];
y2 =[0,2,4,5,2,7,5,7,5];
x2 =[.002,0.004,.006,.009,.02,0.04,0.06,.07,.09];

x = [x1, x2]; % Combine x axis data
y = [y1, y2]; % Combine y axis data
[x, ~, idx] = unique( x(:) ); % Get unique x, and their indices
y = accumarray( idx, y );     % Add up y values according to x value index
user_39785450

Aggregating Sample Values With Different Sampling Times

The following approach combines the data into a single vectors, Time_Vector and Data_Vector. Then the unique() function is used to find the unique sample times that exist within Time_Vector. A for-loop is used to evaluate the indices where the same sample time exists by using the find() function. After finding these indices the corresponding values are obtained by using matrix indexing (finds all the values that occur at a given sample time). The aggregate is then taken of this array by using the sum() function.

Output Plot and Array Results

data_1_y_axes = [0,1,3,5,4,6,8,9,7];
time_1_x_axes = [0.02,0.03,0.05,0.06,0.07,0.08,0.09,0.1,0.2];
data_2_y_axes = [0,2,4,5,2,7,5,7,5];
time_2_x_axes = [0.002,0.004,0.006,0.009,0.02,0.04,0.06,0.07,0.09];


Data_Vector = [data_1_y_axes data_2_y_axes];
Time_Vector = [time_1_x_axes time_2_x_axes];

Unique_Times = unique(Time_Vector);
for Sample_Index = 1: length(Unique_Times)
    Time_Value = Unique_Times(Sample_Index);
    Indices_With_Matching_Time = find(Time_Vector == Time_Value);
    Output_Data(Sample_Index) = sum(Data_Vector(Indices_With_Matching_Time));
end

plot(Unique_Times,Output_Data);

Ran using MATLAB R2019b

user_136690870
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