How to use movsum with datetime?
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I have a 79880x43 table, where the first column is datetime (yyyy-mm-dd hh:mm:ss) and columns 2-43 are stations. In each row there's preciptation measurements with one hour time step. Now I need to use movsum on the whole table together, so it calculates the sum of two hours of sample points (two rows) etc and also sums the time because I need the timestamp too for further analsys. So far I have used:
t = timetable2table(tt)
k = hours(2)
date = t(:,1)
t.date = [ ] % removed the the date column from the table
movsum(t,k,'omitnan','Samplepoints',date);
But this gives me an error: "Error using movsum Invalid data type. First input must be numeric or logical."
I have also attached a picture of my original table.
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Answers (2)
Seth Furman
on 19 Mar 2021
@SaaraL I should first mention that the function call in your original question should work if you pass a numeric vector or matrix instead of a table as the first argument. You can convert your timetable or table to a numeric matrix using table2array.
k = hours(2);
movsum(table2array(tt),k,'omitnan','SamplePoints',tt.date)
If you want to get the corresponding row-times for the start of each window you can use movmin. Using the values in Walter's example
>> k = hours(3);
>> tt = timetable(datetime(2021,3,17,2:12,1,11)',[-8,-2,-2,-2,-7,-9,3,-6,2,-9,4]');
>> tt.Time(movmin(1:height(tt),k,'SamplePoints',tt.Time),1)
ans =
11×1 datetime array
17-Mar-2021 02:01:11
17-Mar-2021 02:01:11
17-Mar-2021 03:01:11
17-Mar-2021 04:01:11
17-Mar-2021 05:01:11
17-Mar-2021 06:01:11
17-Mar-2021 07:01:11
17-Mar-2021 08:01:11
17-Mar-2021 09:01:11
17-Mar-2021 10:01:11
17-Mar-2021 11:01:11
Likewise, if you want to get the corresponding row-times for the end of each window you can use movmax. Using the values in Walter's example
>> k = hours(3);
>> tt = timetable(datetime(2021,3,17,2:12,1,11)',[-8,-2,-2,-2,-7,-9,3,-6,2,-9,4]');
>> tt.Time(movmax(1:height(tt),k,'SamplePoints',tt.Time),1)
ans =
11×1 datetime array
17-Mar-2021 03:01:11
17-Mar-2021 04:01:11
17-Mar-2021 05:01:11
17-Mar-2021 06:01:11
17-Mar-2021 07:01:11
17-Mar-2021 08:01:11
17-Mar-2021 09:01:11
17-Mar-2021 10:01:11
17-Mar-2021 11:01:11
17-Mar-2021 12:01:11
17-Mar-2021 12:01:11
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Walter Roberson
on 15 Mar 2021
Keep it as a time table and use retime() . If you need the hours to be paired up, 1+2, 3+4, then it is easy enough. If you need sliding, 1+2, 2+3, 3+4, then you can do that as two cases using disjoint pairs, with a 1 hour starting difference between the two.
But you cannot add timestamps -- only durations, or timestamp plus duration.
14 Comments
Peter Perkins
on 7 Dec 2021
I'm late to this party, but a couple of comments:
The answer to Walter's "Ah. You can pass in a vector of new times instead of using regular and hours(2)" is that retime(...,'regular', 'sum', 'timestep', hours(2)) basically says to itself, "Ha! They want a time step of two hours, so I'm going to put the bin edges at nice locations", and that means at 0 hours, 2 hours, etc. But you have always been able to pass in a time vector top retime to, and as Walter says, just retime to 0,2,4 and then to 1,3,5, and combine.
But really, I think you need to stick with timetables and just use smoothdata. I think this becomes a one-liner:
>> tt = timetable((1:10)',(11:20)','RowTimes',datetime(2021,12,7,0:9,0,0))
tt =
10×2 timetable
Time Var1 Var2
____________________ ____ ____
07-Dec-2021 00:00:00 1 11
07-Dec-2021 01:00:00 2 12
07-Dec-2021 02:00:00 3 13
07-Dec-2021 03:00:00 4 14
07-Dec-2021 04:00:00 5 15
07-Dec-2021 05:00:00 6 16
07-Dec-2021 06:00:00 7 17
07-Dec-2021 07:00:00 8 18
07-Dec-2021 08:00:00 9 19
07-Dec-2021 09:00:00 10 20
>> smoothdata(tt,'movmean',[hours(1) 0]) % current and prev hour
ans =
10×2 timetable
Time Var1 Var2
____________________ ____ ____
07-Dec-2021 00:00:00 1 11
07-Dec-2021 01:00:00 1.5 11.5
07-Dec-2021 02:00:00 2.5 12.5
07-Dec-2021 03:00:00 3.5 13.5
07-Dec-2021 04:00:00 4.5 14.5
07-Dec-2021 05:00:00 5.5 15.5
07-Dec-2021 06:00:00 6.5 16.5
07-Dec-2021 07:00:00 7.5 17.5
07-Dec-2021 08:00:00 8.5 18.5
07-Dec-2021 09:00:00 9.5 19.5
>> smoothdata(tt,'movmean',[hours(2) 0]) % current and prev two hours
ans =
10×2 timetable
Time Var1 Var2
____________________ ____ ____
07-Dec-2021 00:00:00 1 11
07-Dec-2021 01:00:00 1.5 11.5
07-Dec-2021 02:00:00 2 12
07-Dec-2021 03:00:00 3 13
07-Dec-2021 04:00:00 4 14
07-Dec-2021 05:00:00 5 15
07-Dec-2021 06:00:00 6 16
07-Dec-2021 07:00:00 7 17
07-Dec-2021 08:00:00 8 18
07-Dec-2021 09:00:00 9 19
Walter Roberson
on 7 Dec 2021
Ah! Though I think you would use 'movsum' rather than 'movmean' for the purpose of the original poster.
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