Trevas - Temporal operators

Temporal operators in Trevas

The version 1.4.1 of Trevas introduces preliminary support for date and time types and operators.

The specification describes temporal types such as date, time_period, time, and duration. However, Trevas authors find these descriptions unsatisfactory. This blog post outlines our implementation choices and how they differ from the spec.

In the specification, time_period (and the types date) is described as a compound type with a start and end (or a start and a duration). This complicates the implementation and brings little value to the language as one can simply operate on a combination of dates or date and duration directly. For this reason, we defined an algebra between the temporal types and did not yet implement the time_period.

result (operators)	date	duration	number
date	n/a	date (+, -)	n/a
duration	date (+, -)	duration (+, -)	duration (*)
number	n/a	duration (*)	n/a

The period_indicator function relies on period-awareness for types that are not defined enough at the moment to be implemented.

Java mapping

The VTL type date is represented internally as the types java.time.Instant, java.time.ZonedDateTime and java.time.OffsetDateTime

Instant represent a specific moment in time. Note that this type does not include timezone information and is therefore not usable with all the operators. One can use the types ZonedDateTime and OffsetDateTime when timezone or time saving is required.

The VTL type duration is represented internally as the type org.threeten.extra.PeriodDuration from the threeten extra package. It represents a duration using both calendar units (years, months, days) and a temporal amount (hours, minutes, seconds and nanoseconds).

Function flow_to_stock

The flow_to_stock function converts a data set with flow interpretation into a stock interpretation. This transformation is useful when you want to aggregate flow data (e.g., sales or production rates) into cumulative stock data (e.g., total inventory).

Syntax:

result := flow_to_stock(op)

Parameters:

• op - The input data set with flow interpretation. The data set must have an identifier of type time, additional identifiers, and at least one measure of type number.

Result:

The function returns a data set with the same structure as the input, but with the values converted to stock interpretation.

Function stock_to_flow

The stock_to_flow function converts a data set with stock interpretation into a flow interpretation. This transformation is useful when you want to derive flow data from cumulative stock data.

Syntax:

result := stock_to_flow(op)

Parameters:

• op - The input data set with stock interpretation. The data set must have an identifier of type time, additional identifiers, and at least one measure of type number.

Result:

The function returns a data set with the same structure as the input, but with the values converted to flow interpretation.

Function timeshift

The timeshift function shifts the time component of a specified range of time in the data set. This is useful for analyzing data at different time offsets, such as comparing current values to past values.

Syntax:

result := timeshift(op, shiftNumber)

Parameters:

• op - The operand data set containing time series.
• shiftNumber - An integer representing the number of periods to shift. Positive values shift forward in time, while negative values shift backward.

Result:

The function returns a data set with the time identifiers shifted by the specified number of periods.