Validation check programming information
- Last UpdatedSep 25, 2024
- 2 minute read
The parameters to the Validation Check procedure provide information that can be used when coding the constraints.
|
Parameter |
Description |
|---|---|
|
columnName |
The column in the dtMeterData table for which statistics are being calculated in this run of check() |
|
dtMeterData |
The historical meter data that is included in the analysis. This data is in the Internal Storage profile. Each row is a record and includes the data columns that are displayed in the Meter Data Editor. Invalid data has been excluded from the analysis. |
|
granularity |
A string that provides the primary history granularity: "Minutely", "Hourly", etc. |
|
min |
The minimum value for this column over the time range. |
|
max |
The maximum value for this column over the time range. |
|
avg |
The average value for this column over the time range. |
|
fwa |
The flow-weighted average for this column over the time range. This is calculated using the "volume" column for flow. |
|
std dev # |
The standard deviation configured for this analysis. |
|
kurtosis |
The kurtosis allows the user to gauge the presence of outliers in the dataset. A 'peaked' or 'high' kurtosis has a number of outliers in the dataset. A flat, or low, kurtosis indicates that there are fewer outliers in the dataset. If the data is 'peaked', it has a number of outliers, with the majority of the data forming a 'peak' on the graph. This makes it easy to identify the proper validation limit, as most of the data congregates within one area and the rest of it is likely to be invalid. In the event that the data is 'flat', this means that the data is more uniform with fewer outliers, appearing flatter. This makes it likely that the proper validation limits should be further apart. Additionally, a dataset that is extremely flat makes it difficult to differentiate between valid and invalid data. |
|
skew |
How skewed the distribution is. Skew, in effect, measures symmetry. A skewed dataset will not appear symmetrical in any way, making the proper validation limits difficult to identify because they may not be clustered together. |
|
currentLow |
The current low threshold value entered for this column. |
|
currentHigh |
The current high threshold value entered for this column. |
|
low |
The recommended new low value to allow the configured percent of data to pass the validation check. |
|
high |
The recommended new high value to allow the configured percent of data to pass the validation check. |