Effacer les filtres
Effacer les filtres

Select multiple time ranges and variables in Timetable and create logical flag or filter

20 vues (au cours des 30 derniers jours)
Hello there,
A:
I would like to select multiple time ranges simultaneously in a Timetable.
I am trying to Flag these periods in a column of its own.
Currently, I have to do this twice, with two separate columns, as below, I would rather have one single flag:
Data{1}.Timestamp_Filter1 = Data{1}.Timestamp >= datetime("2020-01-01") & Data{1}.Timestamp <= datetime("2020-01-02");
Data{1}.Timestamp_Filter2 = Data{1}.Timestamp >= datetime("2022-01-01") & Data{1}.Timestamp <= datetime("2022-01-02");
I have already refered to:
B:
Similarly, but not for time ranges
Data{1}.angle_Filter3 = Data{idx}.angle >= 10 & Data{1}.angle <= 20;
Data{1}.angle_Filter4 = Data{idx}.angle >= 30 & Data{1}.angle <= 40;
How, can I do this once?
Support would be apprecaited. Thank you very much!

Réponse acceptée

Seth Furman
Seth Furman le 28 Fév 2022
In this case we already know how to compute the rows we want using logical vectors, which we can use to index into the timetable directly.
TT = readtimetable("outages.csv")
TT = 1468×5 timetable
OutageTime Region Loss Customers RestorationTime Cause ________________ _____________ ______ __________ ________________ ___________________ 2002-02-01 12:18 {'SouthWest'} 458.98 1.8202e+06 2002-02-07 16:50 {'winter storm' } 2003-01-23 00:49 {'SouthEast'} 530.14 2.1204e+05 NaT {'winter storm' } 2003-02-07 21:15 {'SouthEast'} 289.4 1.4294e+05 2003-02-17 08:14 {'winter storm' } 2004-04-06 05:44 {'West' } 434.81 3.4037e+05 2004-04-06 06:10 {'equipment fault'} 2002-03-16 06:18 {'MidWest' } 186.44 2.1275e+05 2002-03-18 23:23 {'severe storm' } 2003-06-18 02:49 {'West' } 0 0 2003-06-18 10:54 {'attack' } 2004-06-20 14:39 {'West' } 231.29 NaN 2004-06-20 19:16 {'equipment fault'} 2002-06-06 19:28 {'West' } 311.86 NaN 2002-06-07 00:51 {'equipment fault'} 2003-07-16 16:23 {'NorthEast'} 239.93 49434 2003-07-17 01:12 {'fire' } 2004-09-27 11:09 {'MidWest' } 286.72 66104 2004-09-27 16:37 {'equipment fault'} 2004-09-05 17:48 {'SouthEast'} 73.387 36073 2004-09-05 20:46 {'equipment fault'} 2004-05-21 21:45 {'West' } 159.99 NaN 2004-05-22 04:23 {'equipment fault'} 2002-09-01 18:22 {'SouthEast'} 95.917 36759 2002-09-01 19:12 {'severe storm' } 2003-09-27 07:32 {'SouthEast'} NaN 3.5517e+05 2003-10-04 07:02 {'severe storm' } 2003-11-12 06:12 {'West' } 254.09 9.2429e+05 2003-11-17 02:04 {'winter storm' } 2004-09-18 05:54 {'NorthEast'} 0 0 NaT {'equipment fault'}
rowTimes = TT.Properties.RowTimes;
isJan = month(rowTimes) == 1;
is1stThrough3rd = 1 <= day(rowTimes) & day(rowTimes) <= 3;
is2000s = 2000 <= year(rowTimes) & year(rowTimes) <= 2009;
isJan1stThrough3rd2000s = isJan & is1stThrough3rd & is2000s;
TT(isJan1stThrough3rd2000s, :)
ans = 5×5 timetable
OutageTime Region Loss Customers RestorationTime Cause ________________ _____________ ______ __________ ________________ ____________________ 2005-01-02 03:26 {'MidWest' } 603.69 1.3631e+05 2005-01-14 05:15 {'winter storm' } 2006-01-02 04:55 {'NorthEast'} NaN 33134 2006-01-02 15:12 {'wind' } 2005-01-02 15:57 {'SouthEast'} 0 0 2005-01-02 16:29 {'energy emergency'} 2006-01-01 11:54 {'West' } 734.11 4.26e+06 2006-01-11 01:21 {'winter storm' } 2007-01-01 16:01 {'West' } 180.24 81389 2007-01-02 03:21 {'severe storm' }

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