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Effacer les filtres

Select row from matrix based on month with datenum

1 vue (au cours des 30 derniers jours)
David du Preez
David du Preez le 8 Juin 2017
Hi. I have 2 matrices. A(12x1) contains month averages(Jan-Dec) and B(437x14) which contains daily values for specific days from 2007-2016. column 1 of matrix B contains datenum values. Is it possible to select a row from B if the value in column 9 is less than the corresponding monthly average from A.
For example: A(1,1) is for January and the average is 227.24. B(1,1) is 2/01/2006 and B(1,9) is 226.01. Then I would want to select that row and create a new matrix containing it as it is less than the corresponding monthly average.

Réponse acceptée

Andrei Bobrov
Andrei Bobrov le 8 Juin 2017
Modifié(e) : Andrei Bobrov le 8 Juin 2017
Please attach file with your datas (A and B):
out = B(A(month(datetime(B(:,1),'InputFormat','yyyy-MM-dd'))) > B(:,9),:);

Plus de réponses (1)

Peter Perkins
Peter Perkins le 9 Juin 2017
Andrei's solution also works out nicely with timetables:
>> monthlyAvg = timetable(rand(3,1),'RowTimes',datetime(2017,1:3,1,'Format','MMM-yyyy')')
monthlyAvg =
3×1 timetable
Time Var1
________ ________
Jan-2017 0.078169
Feb-2017 0.38762
Mar-2017 0.17663
>> dailyData = timetable(rand(90,1),'RowTimes',datetime(2017,1,1:90)')
dailyData =
90×1 timetable
Time Var1
___________ _________
01-Jan-2017 0.66487
02-Jan-2017 0.65827
[snip]
30-Mar-2017 0.11071
31-Mar-2017 0.64954
>> dayToMonth = dailyData.Time.Month
dayToMonth =
1
1
[snip]
3
3
>> prunedData = dailyData(dailyData.Var1 < monthlyAvg.Var1(dayToMonth),:)
prunedData =
20×1 timetable
Time Var1
___________ _________
15-Jan-2017 0.018667
02-Feb-2017 0.056749
05-Feb-2017 0.30348
06-Feb-2017 0.050802
08-Feb-2017 0.14254
12-Feb-2017 0.052114
14-Feb-2017 0.1085
16-Feb-2017 0.37547
19-Feb-2017 0.05188
21-Feb-2017 0.17325
26-Feb-2017 0.18982
28-Feb-2017 0.29788
03-Mar-2017 0.13819
05-Mar-2017 0.090778
10-Mar-2017 0.12096
14-Mar-2017 0.069508
16-Mar-2017 0.13549
21-Mar-2017 0.0411
29-Mar-2017 0.0070522
30-Mar-2017 0.11071

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