Dear Scilab user,
I’m working on big 10-minutes meteorological data and I’m trying to use the retime function to get “daily means”.
The function has a strange behaviour that I cannot understand.
Here’s an example :
---> r = retime(ts_meteo(1:52600,:), 'daily', nanmean)
r =
366x2 timeseries
Time Temperature Humidite
___________________ ___________ _________
2023-03-02 00:00:00 3.7777778 75.428889
2023-03-03 00:00:00 4.8194444 72.328819
2023-03-04 00:00:00 1.7430556 79.397014
... ... ...
2024-02-28 00:00:00 3.3333333 98.117083
2024-02-29 00:00:00 6.8194444 76.605556
2024-03-01 00:00:00 6.7410072 75.556115
retime() function is working well for the first 52600 lines of the matrix but :
---> r = retime(ts_meteo(1:52610,:), 'daily', nanmean)
r =
367x2 timeseries
Time Temperature Humidite
___________________ ___________ _________
2023-03-02 00:00:00 3.7777778 75.428889
2023-03-02 00:10:00 4.8194444 72.328819
2023-03-02 00:20:00 1.7430556 79.397014
... ... ...
2023-03-04 12:40:00 6.8194444 76.605556
2023-03-04 12:50:00 6.8724832 74.209128
2023-03-04 13:00:00 Nan Nan
retime() fails with 10 more lines. The time vector is wrong. But the means seems to be the same at least at the beginning.
Below, the detail of the 10 additional lines is shown. However everything looks normal…
--> ts_meteo2 = ts_meteo(52600:52610,:)
ts_meteo2 =
11x2 timeseries
Time Temperature Humidite
___________________ ___________ ________
2024-03-01 23:00:00 8 54.91
2024-03-01 23:10:00 9 55.2
2024-03-01 23:20:00 8 55.48
2024-03-01 23:30:00 9 55.7
2024-03-01 23:40:00 8 55.76
2024-03-01 23:50:00 9 55.46
2024-03-02 00:00:00 8 55.69
2024-03-02 00:10:00 9 55.06
2024-03-02 00:20:00 9 55.26
2024-03-02 00:30:00 9 55.52
2024-03-02 00:40:00 9 55.73
The problem occurs just after end of february. Is this due to the bisextile year ?
Or, is there a limitation of the number of days (366 ?) in the function retime() ?
Thanks a lot for your help.
Regards,
Laurent