File:Critical 1000-vertex Erdős–Rényi–Gilbert graph.svg

Page contents not supported in other languages.
This is a file from the Wikimedia Commons
From Wikipedia, the free encyclopedia

Original file(SVG file, nominally 1,000 × 1,000 pixels, file size: 79 KB)

Summary

Description
English: An Erdős–Rényi–Gilbert random graph with 1000 vertices at the critical edge probability , showing the largest connected component in the center.
Date
Source Own work
Author David Eppstein

Licensing

I, the copyright holder of this work, hereby publish it under the following license:
Creative Commons CC-Zero This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication.
The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

Source code

from PADS.SVG import *
from PADS.StrongConnectivity import *
from random import random
from sys import stdout

# ===================================================
# Generate a random graph and random layout
# ===================================================

n = 1000
vertices = range(n)
edgeprob = 1./(n-1)

halfG = {v : set(w for w in vertices if v<w and random() < edgeprob) for v in vertices}
G = {v : set(w for w in vertices if v in halfG[w] or w in halfG[v]) for v in vertices}

# ===================================================
# Pull giant component in and push all the rest out
# ===================================================
weight = {}
SCC = StronglyConnectedComponents(G)
giant = max(len(C) for C in SCC)
for C in StronglyConnectedComponents(G):
    for v in C:
        if len(C) == giant:
            weight[v] = giant
        else:
            weight[v] = -1

# ===================================================
# Social gravity
# ===================================================

D = {v : (random()-0.5) + 1j* (random()-0.5) for v in vertices}
natlength = n**(-0.5)
iterations = 150
increment = 0.01

for i in range(iterations):
    social = 0.25
    forces = {v : -D[v]*social for v in vertices}

    for v in vertices:
        for w in vertices:
            if v != w:
                forces[v] += (natlength/abs(D[v]-D[w]))**2*(D[v]-D[w])

    for v in vertices:
        for w in G[v]:
            forces[v] += abs(D[v]-D[w])*(D[w]-D[v])/natlength

    for v in vertices:
        D[v] += increment * forces[v]

# ===================================================
# Renormalize
# ===================================================

minx = min(D[v].real for v in vertices)
miny = min(D[v].imag for v in vertices)
offset = minx + 1j*miny
for v in vertices:
    D[v] -= offset

maxx = max(D[v].real for v in vertices)
maxy = max(D[v].imag for v in vertices)
rescale = 1./max(maxx,maxy)
for v in vertices:
    D[v] *= rescale

# ===================================================
# Turn layout into drawing
# ===================================================

scale = 1000
radius = 6
margin = 9
bbox = scale*(1+1j)

def place(v):
    return D[v]*(scale-2*margin) + margin*(1+1j)

drawing = SVG(bbox,stdout)

drawing.group(style={"stroke":"#000","stroke-width":"2"})
for v in vertices:
    for w in halfG[v]:
        drawing.segment(place(v),place(w))
drawing.ungroup()

drawing.group(fill=colors.red,stroke=colors.black)
for v in vertices:
    drawing.circle(place(v),radius)
drawing.ungroup()

drawing.close()

Captions

An Erdős–Rényi–Gilbert graph with 1000 vertices at the critical edge probability

Items portrayed in this file

depicts

8 February 2022

image/svg+xml

2bab09c61e6c052133f6acc2c459b2c2dc18eedf

80,529 byte

1,000 pixel

1,000 pixel

File history

Click on a date/time to view the file as it appeared at that time.

Date/TimeThumbnailDimensionsUserComment
current07:33, 9 February 2022Thumbnail for version as of 07:33, 9 February 20221,000 × 1,000 (79 KB)David EppsteinUploaded own work with UploadWizard
The following pages on the English Wikipedia use this file (pages on other projects are not listed):

Metadata