withtol - Time tolerance for timetable row subscripting - MATLAB (original) (raw)

Time tolerance for timetable row subscripting

Syntax

Description

S = withtol([rowTimes](#bvdk4l7-rowTimes),[tol](#bvdk4l7-tol)) creates a subscript to select rows of a timetable. S selects all rows whose row times match a time in rowTimes within the tolerance specified by tol. The rowTimes argument is a datetime or duration array, or a cell array of character vectors that specify dates and times. tol must be a nonnegative duration value.

If rowTimes contains datetime values, then you can only use S to subscript into a timetable whose row times are datetime values. Similarly, if rowTimes contains duration values, then you can only use S to subscript into a timetable whose row times are duration values.

example

S = withtol([EF](#mw%5F50dacd6c-1a30-4fe4-abc5-a48f311c6830),[tol](#bvdk4l7-tol)) creates a row subscript using an event filter. To use event filters, the timetable you subscript into must have an attached event table. For more information on specifying a time tolerance using event filters, see eventfilter. (since R2023a)

Examples

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Create a timetable that contains temperature and pressure data with row times in hours. There is a slight random variance in the row times. Select rows with row times that match corresponding times in a time vector within a tolerance of five seconds.

Time = datetime(2015,12,18) + hours(1:10)' + seconds(randn(10,1)); Temp = [37.3 39.1 42.3 42.6 43 43.9 44.1 43.3 42.5 42]'; Pressure = [29.4 29.6 30.0 30.0 30.1 29.9 29.9 29.8 29.6 29.7]'; TT = timetable(Time,Temp,Pressure)

TT=10×2 timetable Time Temp Pressure ____________________ ____ ________

18-Dec-2015 01:00:00    37.3      29.4  
18-Dec-2015 02:00:01    39.1      29.6  
18-Dec-2015 02:59:57    42.3        30  
18-Dec-2015 04:00:00    42.6        30  
18-Dec-2015 05:00:00      43      30.1  
18-Dec-2015 05:59:58    43.9      29.9  
18-Dec-2015 06:59:59    44.1      29.9  
18-Dec-2015 08:00:00    43.3      29.8  
18-Dec-2015 09:00:03    42.5      29.6  
18-Dec-2015 10:00:02      42      29.7  

Create a time vector spanning the hours from 3:00 to 8:00.

newTimes = datetime(2015,12,18) + hours(3:8)

newTimes = 1×6 datetime 18-Dec-2015 03:00:00 18-Dec-2015 04:00:00 18-Dec-2015 05:00:00 18-Dec-2015 06:00:00 18-Dec-2015 07:00:00 18-Dec-2015 08:00:00

Select rows of TT with row times that match times in newTimes within five seconds.

S = withtol(newTimes,seconds(5)); TT2 = TT(S,:)

TT2=6×2 timetable Time Temp Pressure ____________________ ____ ________

18-Dec-2015 02:59:57    42.3        30  
18-Dec-2015 04:00:00    42.6        30  
18-Dec-2015 05:00:00      43      30.1  
18-Dec-2015 05:59:58    43.9      29.9  
18-Dec-2015 06:59:59    44.1      29.9  
18-Dec-2015 08:00:00    43.3      29.8  

Input Arguments

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Times to match in a timetable, specified as a datetime array, duration array, cell array of character vectors, or string array. rowTimes contains times that do not exactly match times in the row times of a timetable, but that might be within a specified tolerance.

If rowTimes is a cell array of character vectors or string array, then the elements of the array specify dates and times that thedatetime or duration functions can convert.

Tolerance for matching times to the row times of a timetable, specified as a duration, character vector, or string scalar. The tolerance value cannot be less than zero.

If tol is a character vector or string scalar, thentol specifies a time that theduration function can convert.

Since R2023a

Event filter.

Extended Capabilities

Version History

Introduced in R2016b

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When you call withtol, you can specify a time tolerance that find rows around the events found by an event filter. To use event filters, you must first attach an event table to the input timetable. For more information on event tables and event filters, see eventtable and eventfilter.

timetable subscripting when subscripting with awithtol subscript is significantly faster in R2023a than in R2022b.

• When you use a withtol subscript with a timetable that has 107 rows, performance in R2023a is about 44x faster than in R2022b.
  function timingTest()
  rng default
  % 10^7 rows
  N = 10000000;
  rowtimes = seconds(0:N-1);
  tt = timetable(rand(N,1),RowTimes=rowtimes);
  % 100 values chosen in steps of 10
  n = 1000;
  t = seconds(0:10:n-1);
  tt.Time = tt.Time + .1*seconds(rand(N,1));
  wt = withtol(t,seconds(.1));

tic
tt2 = tt(wt,:);
toc
end
The approximate execution times are:
R2022b: 3.92 s
R2023a: 0.09 s

The code was timed on a Windows® 10, AMD® EPYC 74F3 24-Core Processor @ 3.19 GHz test system by calling each version of the timingTest function.