Copy of the original GrampsCrossing.py by Peter Hewett (see https://www.gramps-project.org/bugs/view.php?id=6184) that finds layouts with less edge crossings, for relationship graphs generated by GRAMPS. Modified to handle everything in memory (i.e., without actually outputting DOT and PDF files) until the best result is reached. Now also suppor…

GrampsCrossing.py

#!/usr/bin/python
#
# Peter Hewett (Modified by Filipe Correia)
# Copyright GPL 2012
#
# reorder Gramps dot file to minimise crossings in rel chart
# usage:
#    run rel_graph in Gramps to produce .gv file
#    copy .gv file and this .py file to the same directory
#    in that directory, run
#      $./GrampsCrossing.py yourfile.gv
#    output is: span, iteration, crossings1, crossings2
#    it takes several minutes, depending on file size
#    it doesn't alter your .gv file
#    it leaves optimised .dot file and corresponding pdf in directory
#
import math
import subprocess
import sys
import signal

dot_markup = ""

def signal_handler(thesignal, frame):
    print 'Ctrl+C pressed! Writing files and aborting...'
    write_files(dot_markup)
    sys.exit(0)
signal.signal(signal.SIGINT, signal_handler)

def parse():
    with open(sys.argv[1], 'r') as f:
        src=f.readlines()
    f.close()

    # find end of header section
    for i,l in enumerate(src):
        i=i+1    
        if 'node ' in l:
            break

    # parse input file
    dot_header=src[0:i+1]
    dot_body=src[i+1:]
    dot_links=[]
    dot_people=[]
    dot_spouses=[]
    dot_families=[]

    j = 0
    while j < len(dot_body):
        l = dot_body[j]
        if ' -> ' in dot_body[j]:
            dot_links.append(l)
        elif l.startswith('  I'):
            dot_people.append(l)
        elif l.startswith('  subgraph'):
            for y,k in enumerate(dot_body[j:]):
                if k.startswith('  }'):
                    break
            dot_spouses.append(''.join(dot_body[j:j+y+1]))
            j += y
        else:
            dot_families.append(l)
        j += 1

    return dot_header, dot_people, dot_families, dot_spouses, dot_links

# function to return number of crossings for given dot file
def crossings(df, output_files=False):    
    if output_files:
        cmd = 'dot -v -Tpdf > gcf1.pdf'
        f=open('gcf1.dot', 'w')
        f.write(''.join(df))
        f.close()
    else:
        cmd = 'dot -v -Tpdf > /dev/null' # silent

    result = subprocess.Popen(cmd, shell=True, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
    try:
        result.stdin.write(''.join(df))
        result.stdin.close()
    except IOError, e:
        print e
        print ''.join(list(result.stderr))


    for l in result.stderr:
        if 'crossings' in l:
            break

    p1 = l.find(':')
    return int(l[p1+1:p1+4])

def write_files(dot_markup):
    crossings(dot_markup, output_files=True)

if __name__=="__main__":
    header, people, families, spouses, links = parse()

    nsize=len(people)
    span0 = int(math.log(nsize-1)/math.log(2))
    print nsize, span0
    span=2**span0

    new_people=[]
    nr_cross_best = crossings(header + people + links + spouses + families)
    nr_cross_new = nr_cross_best
    while span >= 1:
        for i in range(nsize-span):
            new_people = people[:]
            tmp = new_people[i]
            new_people[i] = new_people[i+span]
            new_people[i+span] = tmp
            dot_markup = header + new_people + links + spouses + families
            nr_cross_new = crossings(dot_markup)
            print span, i, nr_cross_best, nr_cross_new
            if nr_cross_new < nr_cross_best:
                people = new_people[:]
                nr_cross_best=nr_cross_new
            if nr_cross_best == 0:
                break
        span = span/2
    write_files(dot_markup)

A version with improvements and compatible with Python 3 is now available here: https://github.com/hewettp/GrampsCrossing