Creating a derived time series - AquaticInformatics/aquarius-sdk-net GitHub Wiki

The Provisioning API provides a few operations for creating various derived time-series.

POST /locations/{LocationUniqueId}/timeseries/calculated
POST /locations/{LocationUniqueId}/timeseries/statistical

Creating a statistical derived time-series

The ComputationIdentifier request property is required to define the type of statistic. The following ComputationIdentifier string values are supported:

  • Min
  • Max
  • Sum
  • Mean
  • Median
  • Selected Value
  • Tidal High
  • Tidal Lower High
  • Tidal Higher Low
  • Tidal Low
  • Decumulated
  • Max At Event Time
  • Total Amount

The ComputationPeriodIdentifier and TimeStepCount request properties define the interval over which the statistic will be computed. The following ComputationPeriodIdentifier string values are allowed:

  • Annual
  • Monthly
  • Weekly
  • Daily
  • Hourly
  • Minutes
  • Points
  • Water Year

Examples:

ComputationIdentifier ComputationPeriodIdentifier TimeStepCount Description
Mean Daily 1 Compute a daily mean
Sum Hourly 12 Compute a half-day sum

Configuration limitations

The Provisioning API derived time-series operations do not represent the full flexibity of derived time-series. As of 2018.4, some derived time-series can still only be configured via the Springboard UI.

These derived process types are currently only configurable from the Springboard UI:

  • No processing
  • Pass through
  • Rating-model derived
  • Fill Missing Data
  • Conditional Data Selection
  • Reference Datum Conversion

The Springboard UI also allows a derived time-series to change its processing over time. Time-based processing plans cannot currently be configured via the Provisioning API.

This example derived time-series can be configured via the Springboard UI but not via the Provisioning API.

  • Before 2016, just pass-through the values from a historical time-series.
  • From 2016-onwards, calculate a value from two other time-series.