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Lets-Plot Kotlin API without dependencies.
/*
* Copyright (c) 2021. JetBrains s.r.o.
* Use of this source code is governed by the MIT license that can be found in the LICENSE file.
*/
package org.jetbrains.letsPlot.geom
import org.jetbrains.letsPlot.Stat
import org.jetbrains.letsPlot.intern.GeomKind
import org.jetbrains.letsPlot.intern.Layer
import org.jetbrains.letsPlot.intern.Options
import org.jetbrains.letsPlot.intern.layer.*
import org.jetbrains.letsPlot.intern.layer.geom.SmoothAesthetics
import org.jetbrains.letsPlot.intern.layer.geom.SmoothMapping
import org.jetbrains.letsPlot.intern.layer.stat.SmoothStatParameters
import org.jetbrains.letsPlot.pos.positionIdentity
import org.jetbrains.letsPlot.tooltips.TooltipOptions
@Suppress("ClassName")
/**
* Adds a smoothed conditional mean.
*
* ## Examples
*
* - [geom_smooth.ipynb](https://nbviewer.jupyter.org/github/JetBrains/lets-plot-kotlin/blob/master/docs/examples/jupyter-notebooks/geom_smooth.ipynb)
*
* - [scatter_plot.ipynb](https://nbviewer.jupyter.org/github/JetBrains/lets-plot-kotlin/blob/master/docs/examples/jupyter-notebooks/scatter_plot.ipynb)
*
* @param data The data to be displayed in this layer. If null, the default, the data
* is inherited from the plot data as specified in the call to [letsPlot][org.jetbrains.letsPlot.letsPlot].
* @param stat default = `Stat.smooth()`. The statistical transformation to use on the data for this layer.
* Supported transformations: `Stat.identity`, `Stat.bin()`, `Stat.count()`, etc. see [Stat][org.jetbrains.letsPlot.Stat].
* @param position Position adjustment: `positionIdentity`, `positionStack()`, `positionDodge()`, etc. see
* [Position](https://lets-plot.org/kotlin/-lets--plot--kotlin/org.jetbrains.letsPlot.pos/).
* @param showLegend default = true.
* false - do not show legend for this layer.
* @param sampling Result of the call to the `samplingXxx()` function.
* To prevent any sampling for this layer pass value `samplingNone`.
* For more info see [sampling.md](https://github.com/JetBrains/lets-plot-kotlin/blob/master/docs/sampling.md).
* @param tooltips Result of the call to the `layerTooltips()` function.
* Specifies appearance, style and content.
* @param orientation Specifies the axis that the layer's stat and geom should run along, default = "x".
* Possible values: "x", "y".
* @param x X-axis value.
* @param y Predicted (smoothed) value.
* @param ymin Lower pointwise confidence interval around the mean.
* @param ymax Upper pointwise confidence interval around the mean.
* @param alpha Transparency level of a layer. Understands numbers between 0 and 1.
* @param color Color of the geometry.
* String in the following formats:
* - RGB/RGBA (e.g. "rgb(0, 0, 255)")
* - HEX (e.g. "#0000FF")
* - color name (e.g. "red")
* - role name ("pen", "paper" or "brush")
*
* Or an instance of the `java.awt.Color` class.
* @param fill Filling color for the confidence interval around the line.
* String in the following formats:
* - RGB/RGBA (e.g. "rgb(0, 0, 255)")
* - HEX (e.g. "#0000FF")
* - color name (e.g. "red")
* - role name ("pen", "paper" or "brush")
*
* Or an instance of the `java.awt.Color` class.
* @param size Lines width.
* Defines line width for conditional mean and confidence bounds lines.
* @param linetype Type of the line of conditional mean line.
* Codes and names: 0 = "blank", 1 = "solid", 2 = "dashed", 3 = "dotted", 4 = "dotdash",
* 5 = "longdash", 6 = "twodash"
* @param method default = "lm".
* Smoothing method: lm (Linear Model) or loess (Locally Estimated Scatterplot Smoothing).
* @param n default = 80. Number of points to evaluate smoother at.
* @param se default = true. To display confidence interval around smooth.
* @param level default = 0.95. Level of confidence interval to use.
* @param span default = 0.5.
* Only for LOESS method. The fraction of source points closest to the current point
* is taken into account for computing a least-squares regression. A sensible value is usually 0.25 to 0.5.
* @param deg default = 1. Degree of polynomial for linear regression model.
* @param seed Random seed for LOESS sampling.
* @param maxN default = 1000. Maximum number of data-points for LOESS method.
* If this quantity exceeded random sampling is applied to data.
* @param colorBy default = "color" ("fill", "color", "paint_a", "paint_b", "paint_c").
* Defines the color aesthetic for the geometry.
* @param fillBy default = "fill" ("fill", "color", "paint_a", "paint_b", "paint_c").
* Defines the fill aesthetic for the geometry.
* @param mapping Set of aesthetic mappings.
* Aesthetic mappings describe the way that variables in the data are
* mapped to plot "aesthetics".
*/
class geomSmooth(
data: Map<*, *>? = null,
stat: StatOptions = Stat.smooth(),
position: PosOptions = positionIdentity,
showLegend: Boolean = true,
sampling: SamplingOptions? = null,
tooltips: TooltipOptions? = null,
orientation: String? = null,
override val x: Number? = null,
override val y: Number? = null,
override val ymin: Number? = null,
override val ymax: Number? = null,
override val size: Number? = null,
override val linetype: Any? = null,
override val color: Any? = null,
override val fill: Any? = null,
override val alpha: Number? = null,
override val method: String? = null,
override val n: Int? = null,
override val level: Number? = null,
override val se: Boolean? = null,
override val span: Number? = null,
override val deg: Int? = null,
override val seed: Long? = null,
override val maxN: Int? = null,
override val colorBy: String? = null,
override val fillBy: String? = null,
mapping: SmoothMapping.() -> Unit = {}
) : SmoothAesthetics,
SmoothStatParameters,
WithColorOption,
WithFillOption,
Layer(
mapping = SmoothMapping().apply(mapping).seal(),
data = data,
geom = GeomOptions(GeomKind.SMOOTH),
stat = stat,
position = position,
showLegend = showLegend,
sampling = sampling,
tooltips = tooltips,
orientation = orientation
) {
override fun seal(): Options {
return super.seal() +
super.seal() +
super.seal() +
super.seal()
}
}