Mercurial > hg
view tests/test-ancestor.py @ 28600:0d6137891114
graphmod: allow for different styles for different edge types
Rather than draw all edges as solid lines, allow for using different styles for
different edge types. For example you could use dotted lines for edges that
do not connect to a parent, and dashed lines when connecting to a grandparent
(implying missing nodes in between).
For example, setting the following configuration:
[ui]
graphstyle.grandparent = :
graphstyle.missing = .
would result in a graph like this:
o changeset: 32:d06dffa21a31
|\ parent: 27:886ed638191b
| : parent: 31:621d83e11f67
| :
o : changeset: 31:621d83e11f67
|\: parent: 21:d42a756af44d
| : parent: 30:6e11cd4b648f
| :
o : changeset: 30:6e11cd4b648f
|\ \ parent: 28:44ecd0b9ae99
| . : parent: 29:cd9bb2be7593
| . :
o . : changeset: 28:44ecd0b9ae99
|\ \ \ parent: 1:6db2ef61d156
| . . : parent: 26:7f25b6c2f0b9
| . . :
o . . : changeset: 26:7f25b6c2f0b9
|\ \ \ \ parent: 18:1aa84d96232a
| | . . : parent: 25:91da8ed57247
| | . . :
| o-----+ changeset: 25:91da8ed57247
| | . . : parent: 21:d42a756af44d
| | . . : parent: 24:a9c19a3d96b7
| | . . :
| o . . : changeset: 24:a9c19a3d96b7
| |\ \ \ \ parent: 0:e6eb3150255d
| | . . . : parent: 23:a01cddf0766d
| | . . . :
| o---+ . : changeset: 23:a01cddf0766d
| | . . . : parent: 1:6db2ef61d156
| | . . . : parent: 22:e0d9cccacb5d
| | . . . :
| o-------+ changeset: 22:e0d9cccacb5d
| . . . . : parent: 18:1aa84d96232a
|/ / / / / parent: 21:d42a756af44d
| . . . :
| . . . o changeset: 21:d42a756af44d
| . . . |\ parent: 19:31ddc2c1573b
| . . . | | parent: 20:d30ed6450e32
| . . . | |
+-+-------o changeset: 20:d30ed6450e32
| . . . | parent: 0:e6eb3150255d
| . . . | parent: 18:1aa84d96232a
| . . . |
| . . . o changeset: 19:31ddc2c1573b
| . . . .\ parent: 15:1dda3f72782d
| . . . . | parent: 17:44765d7c06e0
| . . . . |
o---+---+ | changeset: 18:1aa84d96232a
. . . . | parent: 1:6db2ef61d156
/ / / / / parent: 15:1dda3f72782d
. . . . .
Edge styles can be altered by setting the following one-character config options::
[ui]
graphstyle.parent = |
graphstyle.grandparent = :
graphstyle.missing = .
The default configuration leaves all 3 types set to |, leaving graph styles
unaffected.
This is part of the work towards moving smartlog upstream; currently smartlog
injects extra nodes into the graph to indicate grandparent relationships (nodes
elided).
author | Martijn Pieters <mjpieters@fb.com> |
---|---|
date | Sat, 19 Mar 2016 16:46:15 -0700 |
parents | 4056fdf71aff |
children | 18e738038d78 |
line wrap: on
line source
from __future__ import absolute_import import binascii import getopt import math import os import random import sys import time from mercurial.node import nullrev from mercurial import ( ancestor, commands, hg, ui, util, ) def buildgraph(rng, nodes=100, rootprob=0.05, mergeprob=0.2, prevprob=0.7): '''nodes: total number of nodes in the graph rootprob: probability that a new node (not 0) will be a root mergeprob: probability that, excluding a root a node will be a merge prevprob: probability that p1 will be the previous node return value is a graph represented as an adjacency list. ''' graph = [None] * nodes for i in xrange(nodes): if i == 0 or rng.random() < rootprob: graph[i] = [nullrev] elif i == 1: graph[i] = [0] elif rng.random() < mergeprob: if i == 2 or rng.random() < prevprob: # p1 is prev p1 = i - 1 else: p1 = rng.randrange(i - 1) p2 = rng.choice(range(0, p1) + range(p1 + 1, i)) graph[i] = [p1, p2] elif rng.random() < prevprob: graph[i] = [i - 1] else: graph[i] = [rng.randrange(i - 1)] return graph def buildancestorsets(graph): ancs = [None] * len(graph) for i in xrange(len(graph)): ancs[i] = set([i]) if graph[i] == [nullrev]: continue for p in graph[i]: ancs[i].update(ancs[p]) return ancs class naiveincrementalmissingancestors(object): def __init__(self, ancs, bases): self.ancs = ancs self.bases = set(bases) def addbases(self, newbases): self.bases.update(newbases) def removeancestorsfrom(self, revs): for base in self.bases: if base != nullrev: revs.difference_update(self.ancs[base]) revs.discard(nullrev) def missingancestors(self, revs): res = set() for rev in revs: if rev != nullrev: res.update(self.ancs[rev]) for base in self.bases: if base != nullrev: res.difference_update(self.ancs[base]) return sorted(res) def test_missingancestors(seed, rng): # empirically observed to take around 1 second graphcount = 100 testcount = 10 inccount = 10 nerrs = [0] # the default mu and sigma give us a nice distribution of mostly # single-digit counts (including 0) with some higher ones def lognormrandom(mu, sigma): return int(math.floor(rng.lognormvariate(mu, sigma))) def samplerevs(nodes, mu=1.1, sigma=0.8): count = min(lognormrandom(mu, sigma), len(nodes)) return rng.sample(nodes, count) def err(seed, graph, bases, seq, output, expected): if nerrs[0] == 0: print >> sys.stderr, 'seed:', hex(seed)[:-1] if gerrs[0] == 0: print >> sys.stderr, 'graph:', graph print >> sys.stderr, '* bases:', bases print >> sys.stderr, '* seq: ', seq print >> sys.stderr, '* output: ', output print >> sys.stderr, '* expected:', expected nerrs[0] += 1 gerrs[0] += 1 for g in xrange(graphcount): graph = buildgraph(rng) ancs = buildancestorsets(graph) gerrs = [0] for _ in xrange(testcount): # start from nullrev to include it as a possibility graphnodes = range(nullrev, len(graph)) bases = samplerevs(graphnodes) # fast algorithm inc = ancestor.incrementalmissingancestors(graph.__getitem__, bases) # reference slow algorithm naiveinc = naiveincrementalmissingancestors(ancs, bases) seq = [] revs = [] for _ in xrange(inccount): if rng.random() < 0.2: newbases = samplerevs(graphnodes) seq.append(('addbases', newbases)) inc.addbases(newbases) naiveinc.addbases(newbases) if rng.random() < 0.4: # larger set so that there are more revs to remove from revs = samplerevs(graphnodes, mu=1.5) seq.append(('removeancestorsfrom', revs)) hrevs = set(revs) rrevs = set(revs) inc.removeancestorsfrom(hrevs) naiveinc.removeancestorsfrom(rrevs) if hrevs != rrevs: err(seed, graph, bases, seq, sorted(hrevs), sorted(rrevs)) else: revs = samplerevs(graphnodes) seq.append(('missingancestors', revs)) h = inc.missingancestors(revs) r = naiveinc.missingancestors(revs) if h != r: err(seed, graph, bases, seq, h, r) # graph is a dict of child->parent adjacency lists for this graph: # o 13 # | # | o 12 # | | # | | o 11 # | | |\ # | | | | o 10 # | | | | | # | o---+ | 9 # | | | | | # o | | | | 8 # / / / / # | | o | 7 # | | | | # o---+ | 6 # / / / # | | o 5 # | |/ # | o 4 # | | # o | 3 # | | # | o 2 # |/ # o 1 # | # o 0 graph = {0: [-1], 1: [0], 2: [1], 3: [1], 4: [2], 5: [4], 6: [4], 7: [4], 8: [-1], 9: [6, 7], 10: [5], 11: [3, 7], 12: [9], 13: [8]} def genlazyancestors(revs, stoprev=0, inclusive=False): print ("%% lazy ancestor set for %s, stoprev = %s, inclusive = %s" % (revs, stoprev, inclusive)) return ancestor.lazyancestors(graph.get, revs, stoprev=stoprev, inclusive=inclusive) def printlazyancestors(s, l): print 'membership: %r' % [n for n in l if n in s] print 'iteration: %r' % list(s) def test_lazyancestors(): # Empty revs s = genlazyancestors([]) printlazyancestors(s, [3, 0, -1]) # Standard example s = genlazyancestors([11, 13]) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) # Standard with ancestry in the initial set (1 is ancestor of 3) s = genlazyancestors([1, 3]) printlazyancestors(s, [1, -1, 0]) # Including revs s = genlazyancestors([11, 13], inclusive=True) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) # Test with stoprev s = genlazyancestors([11, 13], stoprev=6) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) s = genlazyancestors([11, 13], stoprev=6, inclusive=True) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) # The C gca algorithm requires a real repo. These are textual descriptions of # DAGs that have been known to be problematic. dagtests = [ '+2*2*2/*3/2', '+3*3/*2*2/*4*4/*4/2*4/2*2', ] def test_gca(): u = ui.ui() for i, dag in enumerate(dagtests): repo = hg.repository(u, 'gca%d' % i, create=1) cl = repo.changelog if not util.safehasattr(cl.index, 'ancestors'): # C version not available return commands.debugbuilddag(u, repo, dag) # Compare the results of the Python and C versions. This does not # include choosing a winner when more than one gca exists -- we make # sure both return exactly the same set of gcas. for a in cl: for b in cl: cgcas = sorted(cl.index.ancestors(a, b)) pygcas = sorted(ancestor.ancestors(cl.parentrevs, a, b)) if cgcas != pygcas: print "test_gca: for dag %s, gcas for %d, %d:" % (dag, a, b) print " C returned: %s" % cgcas print " Python returned: %s" % pygcas def main(): seed = None opts, args = getopt.getopt(sys.argv[1:], 's:', ['seed=']) for o, a in opts: if o in ('-s', '--seed'): seed = long(a, base=0) # accepts base 10 or 16 strings if seed is None: try: seed = long(binascii.hexlify(os.urandom(16)), 16) except AttributeError: seed = long(time.time() * 1000) rng = random.Random(seed) test_missingancestors(seed, rng) test_lazyancestors() test_gca() if __name__ == '__main__': main()