object NumericTimeSeries
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- def nonStrictMinus[T](lhDefault: Option[T], rhDefault: Option[T])(lhO: Option[T], rhO: Option[T])(implicit n: Numeric[T]): Option[T]
Non strict 'minus' operator: wherever one of the timeseries is undefined it falls back to the given default value.
Non strict 'minus' operator: wherever one of the timeseries is undefined it falls back to the given default value. If both defaults are None, the operator is equivalent to #strictMinus.
- lhDefault
the optional default for the left hand value
- rhDefault
the optional default for the right hand value
- lhO
the optional left hand value
- rhO
the optional right hand value
- def nonStrictPlus[T, U >: T](lhO: Option[T], rhO: Option[T])(implicit n: Numeric[U]): Option[U]
Non strict 'plus' operator: wherever one of the time series is undefined, its entry is considered as 0.
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- def slidingIntegral[T](entries: Seq[TSEntry[T]], window: Long, sampleRate: Long, timeUnit: TimeUnit = TimeUnit.MILLISECONDS)(implicit n: Numeric[T]): Seq[TSEntry[Double]]
First samples the entries and then calculates a sliding integral.
First samples the entries and then calculates a sliding integral. This means the resulting entries represent the value of the integral over the window
[t - window, t]of the original series.The sampling controls the resolution of the returned entries and hence the (im-)precision of the integral. Therefore, the sampling rate cannot be larger than the window size. Otherwise, the output becomes very un-intuitive and will generally not make any sense.
- entries
entries over which to integrate
- window
width of the window
- sampleRate
frequency of resampling
- timeUnit
time unit used to convert validities to seconds
- returns
a sequence of entries representing the integral over the windows
- Note
For optimal (im-)precision and maximally intuitive output, a
windowthat is a multiple of thesampleRateis recommended.
- def stepIntegral[T](entries: Seq[TSEntry[T]], timeUnit: TimeUnit = TimeUnit.MILLISECONDS)(implicit n: Numeric[T]): Seq[TSEntry[Double]]
Compute an integral of the passed entries, such that each entry is equal to its own value plus the sum of the entries that came before.
Compute an integral of the passed entries, such that each entry is equal to its own value plus the sum of the entries that came before. The time is integrated as seconds, you may provide the unit with which the validities are converted to seconds.
- entries
entries over which to integrate
- timeUnit
time unit used to convert validities to seconds
- Note
The result is still a step function.
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Deprecated Value Members
- def rolling[T](ts: TimeSeries[T], aggregator: (Seq[T]) => T, windowMs: Long, compress: Boolean = true)(implicit n: Numeric[T]): TimeSeries[T]
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- @deprecated
- Deprecated
Please use the new windowing functions. See WindowSlider.scala