Combining Similar Time Arrays into a Single Updated Time Array

I have two structures: Structure A and Structure B.

Both structures have 130 field variables. These variables are time/values on two different DAQs. Structure A uses DAQ A. Structure B uses DAQ B. As such, they have similar but not the same outputs. Sometimes Structure A Field variables have a time/value drop out while Structure B field variables do not.

How do I combine Field Variable 1 from Structure A and Structure B into a single field variable into structure C without any time/value repeats? Then repeat this process for all of the variables.

Assumption: The data values are the same value at the same time even if the indices do not line up. They end at the same time, but are not the same sizes.

Inputs:

StructureA.FieldVariable1.Time

StructureA.FieldVariable1.Value

StructureB.FieldVariable1.Time;

StructureB.FieldVariable1.Value

Output:

StructureC.FieldVariable1.Time

StructureC.FieldVariable1.Value

Ex:

FROM:

Structure A Field Variable 1 Structure B Field Variable 1

Time Data Time Data

1 0.1 2 0.2

2 0.2 3 0.3

4 0.4 5 0.5

5 0.5 6 0.6

6 0.6 7 0.7

8 0.8 8 0.8

10 1.0 9 0.9

Left blank on purpose 10 1.0

Structure C Field Variable 1

Time Data

1 0.1 (Filled in from Structure A)

2 0.2 (same value so filled in from either structure)

3 0.3 (Filled in from Structure B)

4 0.4

5 0.5

6 0.6

7 0.7

8 0.8

9 0.9

10 1.0

Answer 1

[Star Strider]

There are some core MATTLAB approaches for this, depending on the result you want.

You would have to convert them to timetable arrays, and after that you can use either retime or synchronize depending on the result you want. I am not sufficiently clear on that to suggest a specific apprroach.

Example —

AFV_1 = table(seconds([1;2;4;5;6;8;10]),[1;2;4;5;6;8;10]/10, VariableNames=["Time","Data"]);
BFV_1 = table(seconds([2;3;4;5;6;7;8;9;10]),[2;3;4;5;6;7;8;9;10]/10, VariableNames=["Time","Data"]);
AFV_1TT = table2timetable(AFV_1)

AFV_1TT = 7x1 timetable
     Time     Data
    ______    ____

    1 sec     0.1 
    2 sec     0.2 
    4 sec     0.4 
    5 sec     0.5 
    6 sec     0.6 
    8 sec     0.8 
    10 sec      1 

BFV_1TT = table2timetable(BFV_1)

BFV_1TT = 9x1 timetable
     Time     Data
    ______    ____

    2 sec     0.2 
    3 sec     0.3 
    4 sec     0.4 
    5 sec     0.5 
    6 sec     0.6 
    7 sec     0.7 
    8 sec     0.8 
    9 sec     0.9 
    10 sec      1 

CFV_TT = synchronize(AFV_1TT, BFV_1TT)

CFV_TT = 10x2 timetable
     Time     Data_AFV_1TT    Data_BFV_1TT
    ______    ____________    ____________

    1 sec         0.1             NaN     
    2 sec         0.2             0.2     
    3 sec         NaN             0.3     
    4 sec         0.4             0.4     
    5 sec         0.5             0.5     
    6 sec         0.6             0.6     
    7 sec         NaN             0.7     
    8 sec         0.8             0.8     
    9 sec         NaN             0.9     
    10 sec          1               1     

CFV_TT2 = table;
CFV_TT2.Time = CFV_TT.Time;
CFV_TT2.Data = mean(CFV_TT{:,[1 2]}, 2, 'omitnan')

CFV_TT2 = 10x2 table
     Time     Data
    ______    ____

     1 sec    0.1 
     2 sec    0.2 
     3 sec    0.3 
     4 sec    0.4 
     5 sec    0.5 
     6 sec    0.6 
     7 sec    0.7 
     8 sec    0.8 
     9 sec    0.9 
    10 sec      1 

Make appropriate changes to get the result you want.

.

[David]

Appreciate the insight. It helps to have a starting point and functions i can look at. I ran into the problem of my time data being in the microsecond regime but matlab only seems to go down to milliseconds.

I would also have to do checks on the other data to ensure it matches with the current data before importing the data to fill in the gaps. I don't think missing 0.2s here or there is significant in the grand scheme of 400 seconds. It's a nice to have, but the amount of effort required versus benefit gained isn't there, and I need to spend my time elsewhere.

I think at this point, I'm just going to check which is the longer array, use that, and move on. Thanks!

[Star Strider]

My pleasure!

The datetime function can do microseconds. You have to specify the seconds field as ss.SSSSSS with s denoting seconds and the S denoting fractions of a second.

Example —

T = datetime(2025, 04, 25, 10, 22, 42.123456, Format='dd-MMM-yyyy HH:mm:ss.SSSSSS')

T = datetime
   25-Apr-2025 10:22:42.123455

format longG
s = second(T)

s = 
                 42.123456

Note that the microseconds are preserved, even if they aren't all displayed correctly in the original datetime call.

I'm not sure what other problems you may be having, however datetime is a powerful function and the timetable functions can make your tasks immeasurably easier.

.