view tests/test-ancestor.py @ 25665:dc05a10e1e45 stable

archive: don't assume '.' is being archived for changessincelatesttag

Hardcoding '.' is wrong, and yielded strange results when archiving old
revisions.  For example, when archiving the cset that adds the signature to 3.4
(c48850339988), the resulting value was previously 51 (the number of commits on
stable between 3.4 and today), even though it was a direct descendant of a tag,
with a {latesttagdistance} of 2.  This still includes all other _ancestor_ paths
not included in {latesttag}.

Note that archiving wdir() currently blows up several lines above this when
building the 'base' variable.  Since wdir() isn't documented, ignore that it
needs work to handle wdir() here for now.

from mercurial import ancestor, commands, hg, ui, util
from mercurial.node import nullrev
import binascii, getopt, math, os, random, sys, time

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()