object Histogram
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- case class ContinuousBinPlotRenderer(bins: Seq[ContinuousBin], binRenderer: ContinuousBinRenderer, spacing: Double, boundBuffer: Double) extends PlotRenderer with Product with Serializable
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case class
HistogramBinRenderer(binPoints: Seq[Point], binWidth: Double, barRenderer: BarRenderer, spacing: Double) extends PlotRenderer with Product with Serializable
this render assumes the binning of the data has already been applied; i.e in cases where the plot ranges need to be pre-calculated
this render assumes the binning of the data has already been applied; i.e in cases where the plot ranges need to be pre-calculated
- binPoints
each point x:left edge y:count of total
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case class
HistogramRenderer(data: Seq[Double], barRenderer: BarRenderer, binCount: Int, spacing: Double, boundBuffer: Double, binningFunction: (Seq[Double], Bounds, Int) ⇒ Seq[Point]) extends PlotRenderer with Product with Serializable
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- @deprecated
- Deprecated
(Since version v0.6.1) Use HistogramBinRenderer instead to prevent double binning and separation of data and view bounds
Value Members
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!=(arg0: Any): Boolean
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def
##(): Int
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def
apply(values: Seq[Double], bins: Int = automaticBinCount, barRenderer: Option[BarRenderer] = None, spacing: Option[Double] = None, boundBuffer: Option[Double] = None, binningFunction: (Seq[Double], Bounds, Int) ⇒ Seq[Point] = createBins, xbounds: Option[Bounds] = None, ybounds: Option[Bounds] = None, color: Option[Color] = None, name: Option[String] = None)(implicit theme: Theme): Plot
Create a histogram.
Create a histogram.
- values
The data.
- bins
The number of bins to divide the data into.
- barRenderer
The renderer to render bars for each bin.
- spacing
The spacing between bars.
- boundBuffer
Extra padding to place at the top of the plot.
- binningFunction
A function taking the raw data, the x bounds, and a bin count that returns a sequence of points with x points representing left bin boundaries and y points representing bin heights
- xbounds
optionally use an explicit xbounds instead of an automatic bounds
- color
series name to use if using the default barRenderer
- returns
A histogram plot.
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final
def
asInstanceOf[T0]: T0
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clone(): AnyRef
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def
createBins(values: Seq[Double], xbounds: Bounds, binCount: Int): Seq[Point]
Create binCount bins from the given data and xbounds.
Create binCount bins from the given data and xbounds.
- values
the raw data
- xbounds
the bounds over which to bin
- binCount
the number of bins to create
- returns
a sequence of points, where the x coordinates represent the left edge of the bins and the y coordinates represent their heights
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def
cumulative(values: Seq[Double], xbounds: Bounds, binCount: Int): Seq[Point]
Create binCount bins from the given data and xbounds, cumulatively such that each bin includes the data in all previous bins
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def
cumulativeDensity(values: Seq[Double], xbounds: Bounds, binCount: Int): Seq[Point]
Create binCount bins from the given data and xbounds, cumulatively such that each bin includes the data in all previous bins, and normalized so that bins approximate a CDF
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def
defaultBinCount(nSamples: Int): Int
auto select number of bins Note:Rice rule: 1k => 20bins (less decimating than Sturges)
- val defaultBinCount: Int
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def
density(values: Seq[Double], xbounds: Bounds, binCount: Int): Seq[Point]
Create binCount bins from the given data and xbounds, computing the bin heights such that they represent the average probability density over each bin interval
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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- def fromBins(bins: Seq[ContinuousBin], binRenderer: Option[ContinuousBinRenderer] = None, spacing: Option[Double] = None, boundBuffer: Option[Double] = None)(implicit theme: Theme): Plot
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def
getClass(): Class[_]
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hashCode(): Int
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isInstanceOf[T0]: Boolean
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final
def
ne(arg0: AnyRef): Boolean
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def
normalize(values: Seq[Double], xbounds: Bounds, binCount: Int): Seq[Point]
Create binCount bins from the given data and xbounds, normalizing the heights such that their sum is 1
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final
def
notify(): Unit
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notifyAll(): Unit
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