Given a potentially large image (or two-dimensional array of numbers), I'd like to loop over all the pixels (or numbers) and eg count all the black ones (or 0 values).
I know I can simply use a for comprehension like
for (y <- 0 until img.height; x <- 0 until img.width) {
...
}
but then I need a mutable variable for the count. Which may not really be a problem, but suppose I don't want this and would like to use a more functional style, how do I do this without creating a large data structure with width x height elements (in other words keeping the memory-efficiency of the 0 until img.height
and 0 until img.width
ranges)?
Map over the collection, transforming inner ones into subcounts, and then sum those :
scala> val m = Array(
Array("B","B","W"),
Array("W","W","B"),
Array("W","W","W")
)
m: Array[Array[String]] = Array(Array(B, B, W), Array(W, W, B), Array(W, W, W))
scala> m.map(_.count(_ == "B")).sum
res0: Int = 3
EDIT
You can create a Stream
using
Stream.tabulate(img.height, img.width)(identity)
and then use
stream.count(isBlack)
Note that Stream.tabulate
accepts up to 5 dimensions (as its first argument).
You can use for comprehension with ranges to convert an image to a sequence of pixels:
for {
y <- 0 until img.height
x <- 0 until img.width
} yield image(x, y)
But this will create a full sequence in memory. To make it lazy you may take views of the ranges:
for {
y <- (0 until img.height).view
x <- (0 until img.width).view
} yield image(x, y)
With that you may call higher-level functions on this sequence to calculate what you need:
(
for {
y <- (0 until img.height).view
x <- (0 until img.width).view
} yield image(x, y)
).count(_.isBlack)
You may, of course, add this conversion to a pixel sequence as an implicit method of your image class:
implicit class ImageOperations(image: Image) {
def toPixelSeq = for {
y <- (0 until img.height).view
x <- (0 until img.width).view
} yield image(x, y)
}
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