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Documentation > Calculated Fields > Batch calculations
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Batch Calculated Fields

When batch calculation option is disabled - you write a function that works with 1 value at a time. But when a batch calculation is enabled you work with the whole raw telemetry array. With the enabled Batch calculation checkbox, you receive more control over how raw telemetry is converted into the required metric. For example you can write a function that has access to the previous telemetry value, you can filter or exclude telemetry value from calculation if needed, you can group telemetries by timestamp and apply transformation on group.

Once raw telemetry array was transformed and returned from the calculation function, system will apply required aggregation on that array.

Basic syntax

Let’s assume that you create following variable for telemetry data:

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var temperatureReadings = none(thermostat.temperature);

In this case temperatureReadings variable would be an array of telemetry objects:

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

In case of attributes you also has an array with 1 object that represent an attribute. Here is an example how to use attributes insude your script:

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

Examples

Filter raw telemetry

You can exclude some telemetry values from metric calculation. In this example we will exclude all temperature values that bigger than 40:

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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

Here is an example how to transform raw telemetry array based on attribute value:

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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

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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');

// ... execute transformation

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

In this example we demonstrate how to detect gaps im timeseries stream and fill it with 0 values:

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var temperatureReadings = none(thermostat.temperature);

var timeGap = 30 * 60 * 1000; // 30 minutes
for (var i = 1; i < temperatureReadings.length; i++) {
    var tsDelta = temperatureReadings[i].ts - temperatureReadings[i - 1].ts;
    if (tsDelta > timeGap) {
        var newTs = (temperatureReadings[i].ts + temperatureReadings[i - 1].ts) / 2;
        temperatureReadings.splice(i, 0, {ts: newTs, value: 0})
    }
}

return temperatureReadings;

Next Steps