import $ivy.`com.github.haifengl::smile-scala:3.1.0`
import $ivy.`org.slf4j:slf4j-simple:2.0.13` 

import java.awt.Color.{BLACK, BLUE, CYAN, DARK_GRAY, GRAY, GREEN, LIGHT_GRAY, MAGENTA, ORANGE, PINK, RED, WHITE, YELLOW}
import smile.interpolation._
import smile.plot.swing._
import smile.plot.show
import smile.plot.Render._

val x = Array(0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0)
val y = Array(0.0, 0.8415, 0.9093, 0.1411, -0.7568, -0.9589, -0.2794)

val controls = Array.ofDim[Double](x.length, 2)
for (i <- 0 until x.length) {
  controls(i)(0) = x(i);
  controls(i)(1) = y(i);
}

val linear = new LinearInterpolation(x, y)

val data = (0 to 60).map { i =>
      val x = i * 0.1
      val y = linear.interpolate(x)
      Array(x, y)
}.toArray

val canvas = plot(controls, '*')
canvas.add(LinePlot.of(data, Line.Style.SOLID, BLUE, "Linear"))
show(canvas)

val cubic = new CubicSplineInterpolation1D(x, y)

val data = (0 to 60).map { i =>
      val x = i * 0.1
      val y = cubic.interpolate(x)
      Array(x, y)
}.toArray

canvas.add(LinePlot.of(data, Line.Style.DASH, RED, "Cubic"))
show(canvas)

val kriging = new KrigingInterpolation1D(x, y)
val data = Array.ofDim[Double](61, 2)
for (i <- 0 to 60) {
  data(i)(0) = i * 0.1
  data(i)(1) = kriging.interpolate(data(i)(0))
}

canvas.add(LinePlot.of(data, Line.Style.DOT, CYAN, "Kriging"))
show(canvas)

val rbf = new RBFInterpolation1D(x, y, new smile.math.rbf.GaussianRadialBasis())
val data = Array.ofDim[Double](61, 2)
for (i <- 0 to 60) {
  data(i)(0) = i * 0.1
  data(i)(1) = rbf.interpolate(data(i)(0))
}

canvas.add(LinePlot.of(data, Line.Style.DOT_DASH, GREEN, "RBF"))
show(canvas)

val shepard = new ShepardInterpolation1D(x, y, 3)
val data = Array.ofDim[Double](61, 2)
for (i <- 0 to 60) {
  data(i)(0) = i * 0.1
  data(i)(1) = shepard.interpolate(data(i)(0))
}

canvas.add(LinePlot.of(data, Line.Style.LONG_DASH, PINK, "Shepard"))
show(canvas)

val x1 = Array(1950.0, 1960, 1970, 1980, 1990)
val x2 = Array(10.0, 20, 30)
val y = Array(
            Array(150.697, 199.592, 187.625),
            Array(179.323, 195.072, 250.287),
            Array(203.212, 179.092, 322.767),
            Array(226.505, 153.706, 426.730),
            Array(249.633, 120.281, 598.243)
        )

val canvas = heatmap(y, Palette.jet(256))
canvas.setTitle("Original")
show(canvas)

val cubic = new CubicSplineInterpolation2D(x1, x2, y)

val data = Array.ofDim[Double](101, 101)
for (i <- 0 to 100; j <- 0 to 100)
    data(i)(j) = cubic.interpolate(1950 + i*0.4, 10 + j*0.2)

val cubicPlot = heatmap(data, Palette.jet(256))
cubicPlot.setTitle("Cubic")
show(cubicPlot)

val bicubic = new BicubicInterpolation(x1, x2, y)

for (i <- 0 to 100; j <- 0 to 100)
    data(i)(j) = bicubic.interpolate(1950 + i*0.4, 10 + j*0.2)

val bicubicPlot = heatmap(data, Palette.jet(256))
bicubicPlot.setTitle("Bicubic")
show(bicubicPlot)

val zz = Array.ofDim[Double](101, 101)
val ww = Array.ofDim[Double](101, 101)
for (i <- 0 to 100; j <- 0 to 100) {
  zz(i)(j) = if (java.lang.Math.random() < 0.2) Double.NaN else data(i)(j)
  ww(i)(j) = zz(i)(j)
}

val canvas = heatmap(ww, Palette.jet(256))
canvas.setTitle("Missing Values")
show(canvas)

LaplaceInterpolation.interpolate(zz)
val canvas = heatmap(zz, Palette.jet(256))
canvas.setTitle("Laplace")
show(canvas)