ValidateAbsLimit
About the function
Validates time series using absolute limits. Values outside the specified limits, are marked with ! (Not Ok). Values with control towards upper or lower limit are set to validated and marked with V01, meaning validation method 1. You can see this code if you turn on value information in Nimbus.
Syntax
- ValidateAbsLimit(t,t|d,t|d)
Description
| # | Type | Description |
|---|---|---|
| 1 | t | Time series to validate. |
| 2 | t d | Time series for lower limit. Numerical value for lower limit. |
| 3 | t d | Time series for upper limit. Numerical value for lower limit. |
Example 1
Waterlevel_hour_VEE = @ValidateAbsLimit(@t('Waterlevel_hour_raw'),@t('RsvLowerLimitProfile'),@t('RsvUpperLimitProfile'))
This example validates the input time series against lower and upper limit time series. If the limit time series have a repetitive frequency, you can use the PROFILE function to repeat values from a given period and resolution.
Example 2
RsvLowerLimitProfile = @PROFILE(@t('RsvLowerLimit'),'YEAR')
@t('RsvLowerLimit') is a breakpoint time series with monthly values.
You can also use a vector of numbers and use the TIME_MASK function to place the values right in time.
Example 3
LowerLimit = @TIME_MASK('YEAR',{'YEAR','YEAR+1m','YEAR+2m','YEAR+3m','YEAR+4m','YEAR+5m','YEAR+6m','YEAR+7m','YEAR+8m','YEAR+9m','YEAR+10m','YEAR+11m'},@D('RsvLowerLimitMonthly'),'VARINT')
If the lower and upper limits are constant, you can use the function syntax @ValidateAbsLimit(t,d,d).
Example 4
Waterlevel_hour_VEE = @ValidateAbsLimit(@RESET_STATUS(@t('Waterlevel_hour_raw')),207,210)
In this example, all existing statuses on the input data series are removed before the function adds its status values. This is done using the RESET_STATUS function on the input data series. All values outside the upper level value 210 or the lower limit value 207, are marked with ! (Not OK) and the validation method V01.
