TimeSeries / TopPeriods / 0.2.1
README.md
Top Periods
This algorithm calls calculates the largest periodic sequences within a dataset, while also removing signal noise via the Autocorrelate algorithm.
Table of Contents
Inputs
All TimeSeries algorithms have a json object input, as well as array input formatting.
Json Format
{
"data":Double[],
"numOfPeriods": Int
}
{
"data": [1,2,3,4,3,4,6,7,5,4,2,1,1],
"numOfPeriods": 4
}
- data - (required) - The timeseries input data you wish to calculate periods from, this algorithm assumes the values are evenly spaced. (
dx(1) == dx(n)
) - numOfPeriods (optional) - The maximum number of periods to return, defaults to 3.
Array Format
There are two separate input formats for this algorithm.
Basic format
data: Double[]
[1,2,3,4,3,4,6,7,5,4,2,1,1]
- data - (required) - The timeseries input data you wish to calculate periods from, this algorithm assumes the values are evenly spaced. (
dx(1) == dx(n)
)
Advanced Format
[data: Double[], numOfPeriods: Int]
[[1,2,3,4,3,4,6,7,5,4,2,1,1], 4]
- data - (required) - The timeseries input data you wish to calculate periods from, this algorithm assumes the values are evenly spaced. (
dx(1) == dx(n)
) - numOfPeriods (optional) - The maximum number of periods to return, defaults to 3.
Outputs
This algorithm has json output for json input, and array output for array input.
JSON Format
{
"topPeriods": Int[]
}
{
"topPeriods": [4,3,2]
}
- topPeriods - The largest periodic sequences in descending order, the number of sequences depends on the numOfPeriods parameter.
Array Format
topPeriods: Double[]
[1,2,3,4,3,4,6,7,5,4,2,1,1]
- topPeriods - The largest periodic sequences in descending order, the number of sequences depends on the numOfPeriods parameter.
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