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Cellular Patch shows how to use jit.convolve to effectively simulate rules for a cellular automata.
This patch, by jvkr, shows how to use jit.convolve to effectively simulate rules for a cellular automata. The weights of the cells in the convolution kernel control the neighbor rules for the CA algorithm. The 'solidarity' slider controls a scaling factor for the convolution. Times ar changing but can also be invoked, and the amount of conservatism changes the responsiveness of the system.

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jit.convolve External Convolve two matrices
The jit.convolve object convolves a matrix with another matrix(convolution kernel). This may be used for typical image processing tasks like blurring, sharpening, and edge detection. By default, the convolution kernel is a 3 by 3 float32 matrix
jit.fastblur External Optimized blur/sharpen
The jit.fastblur object performs several special-case convolution blur/sharpen operations on incoming matrices. Although it is less flexible than thejit.convolve object, the jit.fastblur object will be quicker and easier to set up for the equivalent convolution, in most cases.
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