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/*
* Copyright (c) 2022. 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.core.spec.Option
import org.jetbrains.letsPlot.intern.*
import org.jetbrains.letsPlot.intern.layer.*
import org.jetbrains.letsPlot.scale.scaleGrey
import org.jetbrains.letsPlot.util.Base64
import org.jetbrains.letsPlot.util.pngj.ImageInfo
import org.jetbrains.letsPlot.util.pngj.ImageLineByte
import org.jetbrains.letsPlot.util.pngj.OutputPngStream
import org.jetbrains.letsPlot.util.pngj.PngWriter
/**
* Displays image specified by RasterData.
*
* This geom is not as flexible as `geomRaster()` or `geomTile()`
* but vastly superior in the terms of rendering efficiency.
*
* ## Notes
*
* This geom doesn't understand any aesthetics.
* It doesn't support color scales either.
*
* ## Examples
*
* - [image_101.ipynb](https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/kotlin_examples/cookbook/image_101.ipynb)
* - [image_extent.ipynb](https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/kotlin_examples/cookbook/image_extent.ipynb)
* - [image_fisher_boat.ipynb](https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/kotlin_examples/cookbook/image_fisher_boat.ipynb)
* - [image_grayscale.ipynb](https://nbviewer.org/github/JetBrains/lets-plot-docs/blob/master/source/kotlin_examples/cookbook/image_grayscale.ipynb)
*
* @param rasterData Specifies image type, size and pixel values. See [RasterData.create].
*
* @param norm default = true.
* - true - luminance values in grey-scale image will be scaled to `[0-255]` range using a linear scaler.
* - false - disables scaling of luminance values in grey-scale image.
* This parameter is ignored for RGB(A) images.
* @param vmin default = null.
* Defines the data range used for luminance normalization in grey-scale images.
* This parameter is ignored for RGB(A) images or if parameter `norm = false`.
* @param vmax default = null.
* Defines the data range used for luminance normalization in grey-scale images.
* This parameter is ignored for RGB(A) images or if parameter `norm = false`.
* @param extent default = listOf(-0.5, ncol-0.5, -0.5, nrow-0.5).
* List of 4 numbers: (left, right, bottom, top).
* Defines image's bounding box in terms of the "data coordinates".
* - `left, right`: coordinates of pixels outer edge along the x-axis for pixels in the 1-st and the last column.
* - `bottom, top`: coordinates of pixels outer edge along the y-axis for pixels in the 1-st and the last row.
* @param showLegend default = true.
* Greyscale images only.
* false - do not show legend for this layer.
* @param colorBy default="paint_c" ("fill", "color", "paint_a", "paint_b", "paint_c").
* Define the color-aesthetic used by the legend shown for a greyscale image.
*
* @return Layer object.
*/
fun geomImshow(
rasterData: RasterData,
norm: Boolean = true,
vmin: Number? = null,
vmax: Number? = null,
extent: List? = null,
showLegend: Boolean = true,
colorBy: String = "paint_c",
): Feature {
require(extent == null || extent.size == 4) { "Invalid `extent`: list of 4 numbers expected: ${extent!!.size}" }
val colorAesthetics = listOf("fill", "color", "paint_a", "paint_b", "paint_c")
require(colorBy in colorAesthetics) { "Invalid colorBy value \"$colorBy\". Use: \"color\", \"fill\", \"paint_a\", \"paint_b\" or \"paint_c\"." }
var raster = rasterData.createRaster()
require(raster.nChannels in 1..4) {
"Invalid rasterData: num of channels expected to be 1 (G) or 2 (GA) for greyscale image, 3 (RGB) or 4 (RGBA) for color image, but was ${raster.nChannels}"
}
val cmap: String? = null // TODO: add palettes support
val greyscale = raster.nChannels == 1
var greyScaleDataMin: Double = Double.NaN
var greyScaleDataMax: Double = Double.NaN
if (greyscale) {
var hasNan = raster.hasNan()
val maxLum = if (!(hasNan && cmap != null)) 255 else 254 // index 255 reserved for NaN-s
normalize2d(raster, norm, vmin?.toFloat(), vmax?.toFloat(), maxLum).let {
greyScaleDataMin = it.first
greyScaleDataMax = it.second
}
hasNan = raster.hasNan()
if (hasNan && cmap.isNullOrEmpty()) {
// add alpha
raster = raster.addChannel()
require(raster.nChannels == 2)
raster.updatePixels { pix ->
pix[1] = when (pix[0].isNaN()) {
true -> vmin?.toFloat() ?: Float.NaN
false -> 255f
}
}
} else if (hasNan && !cmap.isNullOrEmpty()) {
raster.updateChannels { it.takeUnless { it.isNaN() } ?: 255f }
}
} else {
if (raster.isDTypeF) {
raster.updateChannels { it * 255f + 0.5f }
}
}
raster.updateChannels { it.coerceIn(0.0f, 255.0f) }
var (extX0, extX1, extY0, extY1) =
extent?.map(Number::toDouble)
?: listOf(-.5, raster.width - .5, -.5, raster.height - .5)
val flipColumns: Boolean = extX0 > extX1
if (flipColumns) {
extX0 = extX1.also { extX1 = extX0 }
}
val flipRows = extY0 > extY1
if (flipRows) {
extY0 = extY1.also { extY1 = extY0 }
}
val outputStream = OutputPngStream()
val png = PngWriter(
outputStream, ImageInfo(
raster.width,
raster.height,
bitdepth = 8,
alpha = (raster.nChannels == 4 || raster.nChannels == 2),
greyscale = raster.nChannels < 3
)
)
val iLine = ImageLineByte(png.imgInfo)
val px = raster.pixel()
val rows = (0 until raster.height).let { it.takeIf { !flipRows } ?: it.reversed() }
val columns = (0 until raster.width).let { it.takeIf { !flipColumns } ?: it.reversed() }
for (row in rows) {
var p = 0
for (col in columns) {
px.atXY(col, row).channels().forEach {
iLine.scanline[p++] = it.toInt().toByte()
}
}
png.writeRow(iLine)
}
png.end()
// Show Legend (color-bar) if applicable.
val layerMapping: Options = if (greyscale && showLegend) {
// Provide two imaginable data-points to build a legend.
Options.of(
colorBy to listOf(greyScaleDataMin, greyScaleDataMax)
)
} else {
Options.empty()
}
val legendTitle = ""
val colorScale: Scale? = if (greyscale && showLegend) {
if (cmap != null) when (norm) {
true -> null // ToDo
else -> null // ToDo
} else {
val start = if (norm) 0.0 else greyScaleDataMin / 255
val end = if (norm) 1.0 else greyScaleDataMax / 255
scaleGrey(aesthetic = colorBy, start = start, end = end, name = legendTitle)
}
} else {
null
}
val geomLayer = object : Layer(
geom = GeomOptions(GeomKind.IMAGE),
data = null,
mapping = layerMapping,
stat = Stat.identity,
position = null,
showLegend = showLegend,
inheritAes = false,
sampling = null,
orientation = null,
tooltips = null,
labels = null
) {
override fun seal(): Options {
return Options.of(
Option.Geom.Image.HREF to "data:image/png;base64," + Base64.encode(outputStream.byteArray),
Option.Geom.Image.XMIN to extX0,
Option.Geom.Image.YMIN to extY0,
Option.Geom.Image.XMAX to extX1,
Option.Geom.Image.YMAX to extY1,
Option.Layer.COLOR_BY to colorBy // for the legend
)
}
}
return colorScale?.let {
geomLayer + it
} ?: geomLayer
}
/**
* Updates channels in the given `Raster` object.
*
* @return The used `min` and `max` data values (i.e. values before normalization)
*/
private fun normalize2d(raster: Raster, norm: Boolean, vMin: Float?, vMax: Float?, maxLum: Int): Pair {
@Suppress("NAME_SHADOWING")
val vMin = vMin ?: raster.pixels.filterNot(Float::isNaN).min()
@Suppress("NAME_SHADOWING")
val vMax = vMax ?: raster.pixels.filterNot(Float::isNaN).max()
require(vMin <= vMax) { "vmin value must be less then vmax value, was: $vMin > $vMax" }
raster.updateChannels { it.coerceIn(vMin, vMax) }
if (norm == false) {
// no normalization - just round values to the nearest int.
raster.updateChannels { it + 0.5f }
} else {
@Suppress("IntroduceWhenSubject")
when {
vMin == vMax -> raster.updateChannels { 127f }
else -> {
val ratio = maxLum / (vMax - vMin)
raster.updateChannels { (it - vMin) * ratio + 0.5f }
}
}
}
return Pair(vMin.toDouble(), vMax.toDouble())
}
class RasterData private constructor(
private val data: Any,
private val width: Int,
private val height: Int,
private val nChannels: Int
) {
companion object {
/**
* Creates [RasterData] from 2D or 3D collection.
* @param iterable 2D or 3D collection.
* - (M, N): an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters `norm`, `vmin`, `vmax`.
* - (M, N, 3): an image with RGB values (0-1 float or 0-255 int).
* - (M, N, 4): an image with RGBA values (0-1 float or 0-255 int).
*/
fun create(iterable: Iterable>): RasterData {
val l0 = if (iterable is Collection) iterable else iterable.toList()
val l1 = l0.flatten()
@Suppress("UNCHECKED_CAST")
val l2: List = when (l1[0] is Iterable<*>) {
true -> (l1 as Iterable>).flatten() as List
false -> l1 as List
}
val height = l0.size
val width = l1.size / height
val nChannels = l2.size / (width * height)
return RasterData(l2, width, height, nChannels)
}
/**
* Creates [RasterData] from 2D or 3D array.
* @param arr 2D or 3D array.
* - (M, N): an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters `norm`, `vmin`, `vmax`.
* - (M, N, 3): an image with RGB values (0-1 float or 0-255 int).
* - (M, N, 4): an image with RGBA values (0-1 float or 0-255 int).
*/
fun create(arr: Array>): RasterData {
val l0 = arr.flatten()
@Suppress("UNCHECKED_CAST")
val l1: List = when (l0[0] is Array<*>) {
true -> (l0 as List>).map(Array<*>::asList).flatten() as List
false -> l0 as List
}
val height = arr.size
val width = l0.size / height
val nChannels = l1.size / (width * height)
return RasterData(l1, width, height, nChannels)
}
/**
* Creates [RasterData] from 1D array with pixel data.
* @param arr Array of Numbers (0-1 float or 0-255 int).
* Expected size width * height * nChannels.
* @param width Width of the image in pixels.
* @param height Height of the image in pixels.
* @param nChannels Number of channels per pixel.
* - 1: an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters `norm`, `vmin`, `vmax`.
* - 3: an image with RGB values (0-1 float or 0-255 int).
* - 4: an image with RGBA values (0-1 float or 0-255 int).
*/
fun create(arr: ByteArray, width: Int, height: Int, nChannels: Int) = RasterData(arr, width, height, nChannels)
/**
* Creates [RasterData] from 1D array with pixel data.
* @param arr Array of numbers (0-1 float or 0-255 int).
* Expected size width * height * nChannels.
* @param width Width of the image in pixels.
* @param height Height of the image in pixels.
* @param nChannels Number of channels per pixel.
* - 1: an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters `norm`, `vmin`, `vmax`.
* - 3: an image with RGB values (0-1 float or 0-255 int).
* - 4: an image with RGBA values (0-1 float or 0-255 int).
*/
fun create(arr: IntArray, width: Int, height: Int, nChannels: Int) = RasterData(arr, width, height, nChannels)
/**
* Creates [RasterData] from 1D array with pixel data.
* @param arr Array of numbers (0-1 float or 0-255 int).
* Expected size width * height * nChannels.
* @param width Width of the image in pixels.
* @param height Height of the image in pixels.
* @param nChannels Number of channels per pixel.
* - 1: an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters `norm`, `vmin`, `vmax`.
* - 3: an image with RGB values (0-1 float or 0-255 int).
* - 4: an image with RGBA values (0-1 float or 0-255 int).
*/
fun create(arr: FloatArray, width: Int, height: Int, nChannels: Int) = RasterData(arr, width, height, nChannels)
/**
* Creates [RasterData] from 1D array with pixel data.
* @param arr Array of numbers (0-1 float or 0-255 int).
* Expected size width * height * nChannels.
* @param width Width of the image in pixels.
* @param height Height of the image in pixels.
* @param nChannels Number of channels per pixel.
* - 1: an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters `norm`, `vmin`, `vmax`.
* - 3: an image with RGB values (0-1 float or 0-255 int).
* - 4: an image with RGBA values (0-1 float or 0-255 int).
*/
fun create(arr: DoubleArray, width: Int, height: Int, nChannels: Int) =
RasterData(arr, width, height, nChannels)
/**
* Creates [RasterData] from 1D array with pixel data.
* @param arr Array of numbers (0-1 float or 0-255 int).
* Expected size width * height * nChannels.
* @param width Width of the image in pixels.
* @param height Height of the image in pixels.
* @param nChannels Number of channels per pixel.
* - 1: an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters `norm`, `vmin`, `vmax`.
* - 3: an image with RGB values (0-1 float or 0-255 int).
* - 4: an image with RGBA values (0-1 float or 0-255 int).
*/
fun create(arr: Array, width: Int, height: Int, nChannels: Int) =
RasterData(arr, width, height, nChannels)
}
override fun toString() = "RasterData($width x $height x $nChannels)"
internal fun createRaster(): Raster {
val isDTypeF: Boolean
val pixelData: FloatArray = when (data) {
is Array<*> -> {
isDTypeF = data[0].let { it is Float || it is Double }
FloatArray(height * width * nChannels).also { arr ->
data.forEachIndexed { i, v -> arr[i] = toFloat(v) }
}
}
is FloatArray -> {
isDTypeF = true
FloatArray(height * width * nChannels).also(data::copyInto)
}
is ByteArray -> {
isDTypeF = false
FloatArray(height * width * nChannels).also { arr ->
data.forEachIndexed { i, v -> arr[i] = toFloat(v) }
}
}
is IntArray -> {
isDTypeF = false
FloatArray(height * width * nChannels).also { arr ->
data.forEachIndexed { i, v -> arr[i] = toFloat(v) }
}
}
is DoubleArray -> {
isDTypeF = true
FloatArray(height * width * nChannels).also { arr ->
data.forEachIndexed { i, v -> arr[i] = toFloat(v) }
}
}
is List<*> -> {
isDTypeF = data[0].let { it is Float || it is Double }
FloatArray(height * width * nChannels).also { arr ->
data.forEachIndexed { i, v -> arr[i] = toFloat(v) }
}
}
else -> error("Invalid bitmap: unsupported data type `${data::class.simpleName}`")
}
return Raster(width, height, nChannels, isDTypeF, pixelData)
}
private fun toFloat(v: Any?): Float {
return when (v) {
is Float -> v
is Byte -> v.toUByte().toFloat() // for bytes 128, 129 method .toFloat() returns -1f, -2f etc
is Number -> v.toFloat()
else -> error("Invalid bitmap: should contain only numbers")
}
}
}
internal class Raster(
val width: Int,
val height: Int,
val nChannels: Int,
val isDTypeF: Boolean,
val pixels: FloatArray
) {
inner class Pixel {
private var pxIndex: Int = 0
fun atXY(x: Int, y: Int): Pixel {
pxIndex = (y * width + x) * nChannels
return this
}
operator fun get(chIndex: Int): Float = pixels[pxIndex + chIndex]
operator fun set(chIndex: Int, v: Float) {
pixels[pxIndex + chIndex] = v
}
fun channels() = when (nChannels) {
1 -> listOf(get(0))
2 -> listOf(get(0), get(1))
3 -> listOf(get(0), get(1), get(2))
4 -> listOf(get(0), get(1), get(2), get(3))
else -> error("Unsupported number of channels: $nChannels")
}
}
fun updatePixels(f: (Pixel) -> Unit) {
val pixel = Pixel()
for (y in 0 until height) {
for (x in 0 until width) {
f(pixel.atXY(x, y))
}
}
}
fun updateChannels(f: (Float) -> Float) {
return updatePixels { ch ->
if (nChannels >= 1) ch[0] = f(ch[0])
if (nChannels >= 2) ch[1] = f(ch[1])
if (nChannels >= 3) ch[2] = f(ch[2])
if (nChannels >= 4) ch[3] = f(ch[3])
}
}
fun addChannel(): Raster {
val newPixels = FloatArray(width * height * (nChannels + 1))
var newI = 0
for (i in pixels.indices) {
newPixels[newI++] = pixels[i]
if (newI % nChannels == 0) {
newPixels[newI++] = Float.NaN
}
}
return Raster(width, height, nChannels + 1, isDTypeF, newPixels)
}
fun pixel() = Pixel()
fun hasNan() = pixels.any(Float::isNaN)
}
