def test_nonsing_none_forbidden(n_eqs, seed):
log('seed =', seed)
rng = Random(seed)
g, eqs = create_rnd_bipartite(n_eqs, n_eqs, seed, rng, nonsing=True, c=3)
#serialize((g, eqs), DATADIR + 'ilp_poor_performance_c=5_r=2997.pkl.gz')
#plot_bipartite(g, eqs, forbidden)
solve_problem(g, eqs)
log()
def difficult(size):
print('Solving patterns leading to many ties (backtracking) of size', size)
msg = 'Size: ' + str(size)
fname = '{0:03d}a'.format(size)
g = create_difficult_pattern(size)
to_pdf(g, list(irange(size)), irange(size, 2 * size), msg, fname)
#
solve_problem(g, set(irange(size)))
#
explored, g, _, rowp, colp, ub = _worst_cases[0]
msg = 'OPT = {}, BT: {}'.format(ub, explored)
fname = '{0:03d}b'.format(size)
to_pdf(g, rowp, colp, msg, fname)
_worst_cases[:] = []
print_timestamp()
def naughty_brute_force():
for size in irange(3, 6):
print_timestamp()
print('Testing (naughty) bipartite graphs of size', size)
# serialized in test_utils, but optimums can be serialized here
#opts = [ ]
#opts = marshal_load('data/all_bips/opt_n'+str(size)+'.bin')
#all_edgelists = marshal_load('data/all_bips/bip_n'+str(size)+'.bin')
opts = marshal_load('data/bip_filt/opt_n' + str(size) + '.bin')
all_edgelists = marshal_load('data/bip_filt/filt_n' + str(size) +
'.bin')
print('Loaded', len(all_edgelists), 'graphs')
print_timestamp()
#for edgelist in all_edgelists:
for i, (edgelist, opt) in enumerate(izip(all_edgelists, opts)):
assert len(edgelist) % 2 == 0
g = Graph()
g.add_edges_from(e for e in izip(edgelist[::2], edgelist[1::2]))
assert len(g) == 2 * size
g.graph['name'] = str(i)
_, _, _, tear_set, _ = solve_problem(g, set(irange(size)))
assert opt == len(tear_set)
#---
#solve_problem(g, set(irange(size)))
#---
#opt = len(solve_problem(g, set(irange(size)))[3])
#opts.append(opt)
#---
#to_pdf(g, rowp, colp)
#assert len(opts) == len(all_edgelists)
#marshal_dump(opts, '/tmp/opt_n'+str(size)+'.bin')
print([t[0] for t in _worst_cases])
#print('Len:', len(_worst_cases))
_worst_cases.sort(key=sort_patterns)
# for i, (explored, g, _, rowp, colp, ub) in enumerate(_worst_cases, 1):
# msg = 'Index: ' + g.graph['name']
# fname = '{0:03d}a'.format(i)
# to_pdf(g, list(irange(size)), irange(size, 2*size), msg, fname)
# msg = 'OPT = {}, BT: {}'.format(ub, explored)
# fname = '{0:03d}b'.format(i)
# to_pdf(g, rowp, colp, msg, fname)
_worst_cases[:] = []
print_timestamp()
print()
def solve_difficult_for_bb():
filepath = 'data/worst_of_10M_runs/bb_bad_perf_n=10_c=0.5_1.pkl.gz'
g, eqs, _ = deserialize(filepath)
rowp, colp = solve_problem(g, eqs)[0:2]
to_pdf(g, rowp, colp)
def test_to_hessenberg_none_forbidden(n_eqs, n_vars, seed):
log('seed =', seed)
rng = Random(seed)
g, eqs = create_rnd_bipartite(n_eqs, n_vars, seed, rng, nonsing=False, c=3)
solve_problem(g, eqs)
log()