/circlify

Circle packing similar to squarify for treemap

Primary LanguagePythonMIT LicenseMIT

PyPi version Python compatibility Build Status Coverage Codacy

circlify

Pure Python implementation of circle packing layout algorithm.

Circles are first arranged via a version of A1.0 by Huang et al (see https://home.mis.u-picardie.fr/~cli/Publis/circle.pdf for details) and then enclosed in a circle created around them using Matoušek-Sharir-Welzl algorithm used in d3js (see https://beta.observablehq.com/@mbostock/miniball, http://www.inf.ethz.ch/personal/emo/PublFiles/SubexLinProg_ALG16_96.pdf, and https://github.com/d3/d3-hierarchy/blob/master/src/pack/enclose.js)

Installation

Using pip:

pip install circlify

or using the source:

git clone git://github.com/elmotec/circlify.git
cd circlify
python setup.py install

The last step may require sudo if you don't have root access.

Usage

The main function circlify is supported by a small data class circlify.Circle and takes 3 parameters:

  • A list of positive values sorted from largest to smallest.
  • (optional) A target enclosure where the packed circles should fit. It defaults to the unit circle (0, 0, 1).
  • (optional) A boolean indicating if the target enclosure should be appended to the output.

The function returns a list of circlify.Circle objects, each one corresponding to the coordinates and radius of cirlces proportional to the corresponding input value.

Example

>>> from pprint import pprint as pp
>>> import circlify as circ
>>> circles = circ.circlify([19, 17, 13, 11, 7, 5, 3, 2, 1], show_enclosure=True)
>>> pp(circles)
[Circle(x=0.0, y=0.0, r=1.0, level=0, ex=None),
 Circle(x=0.09222041925800777, y=0.8617116738294696, r=0.09068624109026069, level=1, ex={'datum': 1}),
 Circle(x=-0.40283175658099674, y=0.7512387781681531, r=0.12824971207048294, level=1, ex={'datum': 2}),
 Circle(x=0.3252787490004198, y=0.7776370388468007, r=0.15707317711577193, level=1, ex={'datum': 3}),
 Circle(x=0.48296614887228806, y=0.4541723195782383, r=0.20278059970175755, level=1, ex={'datum': 5}),
 Circle(x=-0.6132109517981927, y=0.4490810687795324, r=0.23993324126007678, level=1, ex={'datum': 7}),
 Circle(x=-0.045884607890591435, y=-0.6977206243364218, r=0.3007722353441051, level=1, ex={'datum': 11}),
 Circle(x=-0.04661299415374866, y=0.4678014425767657, r=0.32697389223002427, level=1, ex={'datum': 13}),
 Circle(x=-0.411432317820337, y=-0.13064957525245907, r=0.3739089508053733, level=1, ex={'datum': 17}),
 Circle(x=0.35776879346704843, y=-0.13064957525245907, r=0.39529216048201216, level=1, ex={'datum': 19})]

A simple matplotlib representation. See circlify.bubbles helper function (requires matplotlib):

visualization of circlify circle packing of first 9 prime numbers.

Starting with version 0.10, circlify also handle hierarchical input so that:

>>> from pprint import pprint as pp
>>> import circlify as circ
>>> data = [
        0.05, {'id': 'a2', 'datum': 0.05},
        {'id': 'a0', 'datum': 0.8, 'children': [0.3, 0.2, 0.2, 0.1], },
        {'id': 'a1', 'datum': 0.1, 'children': [
            {'id': 'a1_1', 'datum': 0.05}, {'datum': 0.04}, 0.01],
        },
    ]
>>> circles = circ.circlify(data, show_enclosure=True)
>>> pp(circles)
[Circle(x=0.0, y=0.0, r=1.0, level=0, ex=None),
 Circle(x=-0.565803075997749, y=0.41097786651145324, r=0.18469903125906464, level=1, ex={'datum': 0.05}),
 Circle(x=-0.3385727489559141, y=0.7022188441650276, r=0.18469903125906464, level=1, ex={'id': 'a2', 'datum': 0.05}),
 Circle(x=-0.7387961250362587, y=0.0, r=0.2612038749637415, level=1, ex={'id': 'a1', 'datum': 0.1, 'children': [{'id': 'a1_1', 'datum': 0.05}, {'datum': 0.04}, 0.01]}),
 Circle(x=0.2612038749637414, y=0.0, r=0.7387961250362586, level=1, ex={'id': 'a0', 'datum': 0.8, 'children': [0.3, 0.2, 0.2, 0.1]}),
 Circle(x=-0.7567888163564136, y=0.14087823651338607, r=0.0616618704777984, level=2, ex={'datum': 0.01}),
 Circle(x=-0.8766762590444033, y=0.0, r=0.1233237409555968, level=2, ex={'datum': 0.04}),
 Circle(x=-0.6154723840806618, y=0.0, r=0.13788013400814464, level=2, ex={'id': 'a1_1', 'datum': 0.05}),
 Circle(x=0.6664952237042423, y=0.3369290873460549, r=0.2117455702848763, level=2, ex={'datum': 0.1}),
 Circle(x=-0.11288314691830154, y=-0.230392881357073, r=0.2994534572692975, level=2, ex={'datum': 0.2}),
 Circle(x=0.15631936804871832, y=0.30460197676548245, r=0.2994534572692975, level=2, ex={'datum': 0.2}),
 Circle(x=0.5533243963620484, y=-0.230392881357073, r=0.36675408601105247, level=2, ex={'datum': 0.3})]

A simple matplotlib representation. See circlify.bubbles helper function (requires matplotlib):

visualization of circlify nested circle packing for a hierarchical input.

Note that the area of the circles are proportional to the values passed in input only if the circles are at the same hierarchical level. For instance: circles a1_1 and a2 both have a value of 0.05, yet a1_1 is smaller than a2 because a1_1 is fitted within its parent circle a1 one level below the level of a2. In other words, the level 1 circles a1 and a2 are both proportional to their respective values but a1_1 is proportional to the values on level 2 witin a1.