Function timeNormalizeDataArray

Normalize a data array of time series data based on an aggregate time step.

This method is useful for "filling in" gaps of data in situations where something expects the data include placeholders for the gaps. Charting applications often expect this, for example.

Each element in the data array is expected to provide a date property that is a Date object. When gaps are discovered in the array, "filler" objects will be inserted with an approprate date value and all other properties copied from the previous element but set to null.

Here's an example where a new element is added to an array to fill in a missing time slot:

const queryData = [
    {date : new Date('2018-05-05T11:00Z'), Generation : 357, Consumption: 345},
    {date : new Date('2018-05-05T12:00Z'), Generation : 1023, Consumption: 678}
]

timeNormalizeDataArray(queryData, Aggregations.ThirtyMinute);
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Then queryData would look like this:

[
    {date : new Date('2018-05-05T11:00Z'), Generation : 357, Consumption: 345},
    {date : new Date('2018-05-05T11:30Z'), Generation : null, Consumption: null},
    {date : new Date('2018-05-05T12:00Z'), Generation : 1023, Consumption: 678}
]
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