Types

DiffusionMatrix[Rows; Cols] = object data: array[Rows, array[Cols, int]] inset*: int denominator*: int: Uses numerators in a matrix to determine the distribution of errors surrounding a pixel
ThresholdMatrix[N] = array[N, array[N, int]]: Uses a matrix of integers as a threshold map for ordered dithering

Consts

Atkinson = (data: [[0, 0, 1, 1], [1, 1, 1, 0], [0, 1, 0, 0]], inset: 1, denominator: 8): https://en.wikipedia.org/wiki/Atkinson_dithering
Bayer2x2: ThresholdMatrix[2] = [[0, 2], [3, 1]]: Bayer 2x2 dithering
Bayer4x4: ThresholdMatrix[4] = [[1, 9, 3, 11], [13, 5, 15, 7], [4, 12, 2, 10], [16, 8, 14, 6]]: Bayer 4x4 dithering
Bayer8x8: ThresholdMatrix[8] = [[0, 32, 8, 40, 2, 34, 10, 42], [48, 16, 56, 24, 50, 18, 58, 26], [12, 44, 4, 36, 14, 46, 6, 38], [60, 28, 52, 20, 62, 30, 54, 22], [3, 35, 11, 43, 1, 33, 9, 41], [51, 19, 59, 27, 49, 17, 57, 25], [15, 47, 7, 39, 13, 45, 5, 37], [63, 31, 55, 23, 61, 29, 53, 21]]: Bayer 8x8 dithering
Burkes = (data: [[0, 0, 0, 8, 4], [2, 4, 8, 4, 2]], inset: 2, denominator: 32): Burkes dithering
FloydSteinberg = (data: [[0, 0, 7], [3, 5, 1]], inset: 1, denominator: 16): Floyd Steinberg dithering
JarvisJudiceNinke = (data: [[0, 0, 0, 7, 5], [3, 5, 7, 5, 3], [1, 3, 5, 3, 1]], inset: 2, denominator: 48): Jarvis, Judice, and Ninkey dithering
Stucki = (data: [[0, 0, 0, 8, 4], [2, 4, 8, 4, 2], [1, 2, 4, 2, 1]], inset: 2, denominator: 42): Stucki dithering

proc columns[Rows: static int; Cols: static int]( matrix: DiffusionMatrix[Rows, Cols]): int: The number of columns in this matrix
proc maxThreshold[N: static int](thresholds: ThresholdMatrix[N]): int
proc numerator[Rows: static int; Cols: static int]( matrix: DiffusionMatrix[Rows, Cols]; row, column: int): int: The inset of to use when considering where the current pixel is located in the matrix
proc rows[Rows: static int; Cols: static int]( matrix: DiffusionMatrix[Rows, Cols]): int: The number of rows in this matrix
proc threshold[N: static int](thresholds: ThresholdMatrix[N]; x, y: int): int