Processing: Creative Coding and Computational Art

I want to mention two final points about using these functions. First, according to the
Processing API reference, these functions are somewhat slow—say, for extracting component
data from many colors at a time. The reference suggests using bitwise operations if
speed is an issue. I cover bitwise operations in detail in Appendix B, and I also look at some
examples that utilize them a little later in this chapter. Second, these seven functions
return a float value, regardless of whether you originally specified int values when you
created the color. So, for example, if you created a color using the default RGB mode (e.g.,
color c = color(200, 150, 74)) and you then called red(c), the value returned would
be 200.0, not 200. I know it’s just a 0 after the dot, but this could cause problems if you
tried to assign the returned value to a variable declared as type int. Try running the following
three lines; you should get a compiler error:
Imaging
//generates a compiler error
color c = color(200, 134, 119);
int r = red(c);
Figure 10-16. Color Component Functions sketch
Thus far in the book, I’ve been utilizing a vector graphics approach, in which images are
created and manipulated using mathematical expressions that plot a shape and apply rendering
attributes, such as stroke weight, fill color, corner joins, and so on. Processing has
the ability to work deeper, down at the pixel or raster level. In a sense, you’ve been getting
near the pixel level when you used 1 ✕ 1 pixel rectangles to create some gradients.
However, using rectangles to represent pixels is a very inefficient way to approach imaging.
In addition, most people connect photo manipulation with imaging, which you’d be hardpressed
to do with a series of rect() calls.
COLOR AND IMAGING
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