Batch Calculation Fields

In a standard Simple calculation, Trendz applies aggregation to telemetry before your function runs — you receive a single scalar value per time bucket. In Batch mode, your function receives the full raw telemetry array across the entire selected time range and is responsible for transforming it. Trendz then applies the final aggregation — grouped by the configured Grouping Interval — to the array you return.

If your function returns an empty array, no telemetry points are saved for that run.

  Simple:
  raw telemetry ──▶ Trendz aggregates ──▶ function(scalar) ──▶ result

  Batch:
  raw telemetry ──▶ function([{ts, value}, …]) ──▶ transformed array ──▶ Trendz aggregates ──▶ result

To enable batch mode, select Batch in the FIELD TYPE dropdown in the Calculated Field Function tab.

Input format

When batch mode is enabled, each telemetry variable holds an array of timestamp/value objects:

[
  { "ts": 1622505600000, "value": 17 },
  { "ts": 1622592000000, "value": 21 },
  { "ts": 1622678400000, "value": 35 }
]

Field	Type	Description
`ts`	number	Unix timestamp in milliseconds.
`value`	number \| string	Raw telemetry value at that timestamp.

Declare a telemetry variable using none():

var temperatureReadings = none(thermostat.temperature);
// temperatureReadings is [{ts, value}, …]

Attributes are also returned as a single-element array. Unwrap the value before use:

var unit = uniq(thermostat.measureUnit);
if (unit.length) {
    unit = unit[0].value;
}

Examples

Filter raw telemetry

Exclude values above a threshold before aggregation:

var temperatureReadings = none(thermostat.temperature);

var filteredReadings = [];
for (var i = 0; i < temperatureReadings.length; i++) {
    var tsValue = temperatureReadings[i];
    if (tsValue.value <= 40) {
        filteredReadings.push(tsValue);
    }
}

return filteredReadings;

Modify raw telemetry

Normalize Fahrenheit readings to Celsius based on an attribute value:

var temperatureReadings = none(thermostat.temperature);

var unit = uniq(thermostat.measureUnit);
if (unit.length) {
    unit = unit[0].value;
}

for (var i = 0; i < temperatureReadings.length; i++) {
    var tsValue = temperatureReadings[i];
    if (unit === 'Fahrenheit') {
        tsValue.value = 5 / 9 * (tsValue.value - 32);
    }
}

return temperatureReadings;

Group multiple telemetries by timestamp

Combine readings from multiple telemetry keys into a single object per timestamp — useful for multi-stream synchronization before computing a formula:

  voltageTelemetry     [{ts: T1, value: 220}, {ts: T2, value: 225}, …]
  temperatureTelemetry [{ts: T1, value: 22},  {ts: T2, value: 24},  …]
  pressureTelemetry    [{ts: T1, value: 1.01},{ts: T2, value: 1.02}, …]
          │
          ▼  groupTelemetryByTime()
          │
  groupedTelemetry = {
    T1: { ts: T1, voltage: 220, temperature: 22, pressure: 1.01 },
    T2: { ts: T2, voltage: 225, temperature: 24, pressure: 1.02 },
  }

var voltageTelemetry     = none(energyMeter.voltage);
var temperatureTelemetry = none(energyMeter.temperature);
var pressureTelemetry    = none(energyMeter.pressure);

var groupedTelemetry = {};

groupTelemetryByTime(voltageTelemetry,     groupedTelemetry, 'voltage');
groupTelemetryByTime(temperatureTelemetry, groupedTelemetry, 'temperature');
groupTelemetryByTime(pressureTelemetry,    groupedTelemetry, 'pressure');

// … apply custom transformation on groupedTelemetry

groupTelemetryByTime = function (telemetry, groupedTelemetry, keyName) {
    for (var i = 0; i < telemetry.length; i++) {
        var ts = telemetry[i].ts;
        if (!groupedTelemetry[ts]) {
            groupedTelemetry[ts] = { ts: ts };
        }
        groupedTelemetry[ts][keyName] = telemetry[i].value;
    }
};

Fill gaps in telemetry stream

Detect gaps larger than a threshold and insert synthetic 0 values at fixed-interval steps to preserve time-series continuity. A while loop handles gaps that span multiple intervals — the delta is recalculated after each insertion so the loop continues until the gap is fully filled:

  time  ─────────────────────────────────────────────────────▶

  before  T1      T2                        T5      T6
           ●───────●                          ●───────●
                        ↑ gap > 60 min (spans 3 intervals)

  after   T1      T2    T3(0)  T4(0)  T5(0) T5      T6
           ●───────●──────●──────●──────●─────●───────●

var temperatureReadings = none(thermostat.temperature);
if (!temperatureReadings || !temperatureReadings.length) {
    return [];
}

var timeGap = 60 * 60 * 1000; // 60 minutes in milliseconds

for (var i = 1; i < temperatureReadings.length; i++) {
    var tsDelta = temperatureReadings[i].ts - temperatureReadings[i - 1].ts;
    while (tsDelta > timeGap) {
        var newTs = temperatureReadings[i - 1].ts + timeGap;
        temperatureReadings.splice(i, 0, { ts: newTs, value: 0 });
        tsDelta = temperatureReadings[i].ts - temperatureReadings[i - 1].ts;
    }
}

return temperatureReadings;