Voronoi

A simple Python library for generating various kinds of Voronoi diagrams.

Installation

To get the library (and its requirements), run:

git clone https://github.com/xiaoxiae/Voronoi.git
cd Voronoi
pip install -r requirements.txt

Examples

from voronoi import *

generate(
    path = "1.png",
    width = 3840,
    height = 2160,
    regions = 70,
    colors = [(0, 0, 0), (15, 15, 15), (23, 23, 23), (30, 30, 30)],
    color_algorithm = ColorAlgorithm.no_adjacent_same,
)

from voronoi import *

generate(
    path = "2.png",
    regions = 30,
    colors = ["#91db57", "#57d3db", "#5770db", "#a157db"],
    border_size = 20,
)

from voronoi import *

generate(
    path = "3.png",
    regions = 50,
    colors = ["#78c9b1", "#3eab71", "#27904d", "#006127"],
    distance_algorithm = DistanceAlgorithm.manhattan,
    color_algorithm = ColorAlgorithm.no_adjacent_same,
)

from voronoi import *

generate(
    path = "4.png",
    regions = 50,
    colors = ["#1d63db", "#155ad0", "#0c4dbd", "#10459f"],
    distance_algorithm = DistanceAlgorithm.chebyshev,
    border_size = 20,
    border_color = "#093987",
    color_algorithm = ColorAlgorithm.no_adjacent_same,
)

from voronoi import *

generate(
    path = "5.png",
    regions = 30,
    colors = ["#ffbec6", "#ffa4b4", "#ff7a92", "#ff5270", "#ff1e44"],
    distance_algorithm=DistanceAlgorithm.euclidean45degrees,
    color_algorithm = ColorAlgorithm.no_adjacent_same,
)

from voronoi import *

generate(
    path = "6.png",
    regions = 20,
    distance_algorithm = [DistanceAlgorithm.manhattan, DistanceAlgorithm.euclidean],
    colors = ["#ff7b00", "#ff9500", "#ffb700", "#ffea00"],
    color_algorithm = ColorAlgorithm.no_adjacent_same,
    border_size = 10,
)

generate function arguments

• path: the path (including an extension) to save the resulting file to
• regions: the number of distinct regions in the diagram
• colors: a list of tuples denoting the RGB of the color, or strings denoting the color in hex
• width: the width of the image; defaults to 1920
• height: the height of the image; defaults to 1080
• region_algorithm: the algorithm that determines the centers of the regions:
  • RegionAlgorithm.uniform attempts to make the centers equidistant to one another; default
  • RegionAlgorithm.randomized makes the center positions entirely random
• distance_algorithm: the algorithm that determines the way the distance is measured; if a list of the algorithms is provided, a random one is picked for each point
  • DistanceAlgorithm.euclidean: standard euclidean distance (hypotenuse); default
  • DistanceAlgorithm.manhattan: Manhattan (taxicab) distance (4 directions)
  • DistanceAlgorithm.chebyshev: Chebyshev distance (8 directions)
  • DistanceAlgorithm.euclidean45degrees: euclidean distance, but lines can only point in 45 degree increments
• color_algorithm: the algorithm that determines the colors of the regions
  • DistanceAlgorithm.random: pick the colors randomly
  • DistanceAlgorithm.no_adjacent_same: pick the colors such that no two adjacent regions have the same color
  • DistanceAlgorithm.least_possible: same as no_adjacent_same, but attempt to do so in the least number of colors
• seed: the seed for the random number generator; no seed by default
• border_size: the thickness of the border (in pixels); defaults to 0 (no border)
• mask: a path to an image mask so only specific areas are used
• mask_color: the color of the mask to fill, ignoring everything else; defaults to #000000
• animate: creates images in the folder path of the regions filling in; defaults to False
• background: background of the animation/masking/borders; defaults to #FFFFFF