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