88 lines
3.7 KiB
Markdown
88 lines
3.7 KiB
Markdown
# orx-marching-squares
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Tools for extracting contours from functions
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## How to use it?
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`orx-marching-squares` provides the `findContours()` function
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```kotlin
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fun f(v: Vector2) = v.distanceTo(drawer.bounds.center) - 200.0
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val contours = findContours(::f, drawer.bounds, 16.0)
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drawer.contours(contours)
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```
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With a small adjustment to the given function one can use `findContours` to find iso contours. The trick is to add a cosine over the distance function.
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```kotlin
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fun f(v: Vector2) = cos((v.distanceTo(drawer.bounds.center) / 100.0) * 2 * PI)
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val contours = findContours(::f, drawer.bounds.offsetEdges(32.0), 16.0)
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drawer.contours(contours)
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```
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<!-- __demos__ -->
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## Demos
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### FindContours01
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A simple demonstration of using the `findContours` method provided by `orx-marching-squares`.
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`findContours` lets one generate contours by providing a mathematical function to be
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sampled within the provided area and with the given cell size. Contours are generated
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between the areas in which the function returns positive and negative values.
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In this example, the `f` function returns the distance of a point to the center of the window minus 200.0.
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Therefore, sampled locations which are less than 200 pixels away from the center return
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negative values and all others return positive values, effectively generating a circle of radius 200.0.
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Try increasing the cell size to see how the precision of the circle reduces.
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The circular contour created in this program has over 90 segments. The number of segments depends on the cell
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size, and the resulting radius.
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[source code](src/jvmDemo/kotlin/FindContours01.kt)
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### FindContours02
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This Marching Square demonstration shows the effect of wrapping a distance function
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within a cosine (or sine). These mathematical functions return values that periodically
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alternate between negative and positive, creating nested contours as the distance increases.
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The `/ 100.0) * 2 * PI` part of the formula is only a scaling factor, more or less
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equivalent to 0.06. Increasing or decreasing this value will change how close the generated
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parallel curves are to each other.
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[source code](src/jvmDemo/kotlin/FindContours02.kt)
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### FindContours03
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Demonstrates how Marching Squares can be used to generate animations, by using a time-related
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variable like `seconds`. The evaluated function is somewhat more complex than previous ones,
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but one can arrive to such functions by exploration and experimentation, nesting trigonometrical
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functions and making use of `seconds`, v.x and v.y.
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[source code](src/jvmDemo/kotlin/FindContours03.kt)
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### FindContours04
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Demonstrates using Marching Squares while reading the pixel colors of a loaded image.
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Notice how the area defined when calling `findContours` is larger than the window.
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Using point coordinates from such an area to read from image pixels might cause problems when points are
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outside the image bounds, therefore the `f` function checks whether the requested `v` is within bounds,
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and only reads from the image when it is.
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The `seconds` built-in variable is used to generate an animated effect, serving as a shifting cut-off point
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that specifies at which brightness level to create curves.
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[source code](src/jvmDemo/kotlin/FindContours04.kt)
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