def solve(g, n_eqs, func):
print('------------------------------------------------------------------')
print('Solving problem of size', n_eqs)
msg = 'Size: ' + str(n_eqs)
fname = '{0:03d}a'.format(n_eqs)
to_pdf(g, list(irange(n_eqs)), irange(n_eqs, 2*n_eqs), msg, fname)
#
res = func(g, set(irange(n_eqs)))
#
print('Explored', res.explored, 'nodes')
msg = 'OPT = {}, BT: {}'.format(res.ub, res.explored)
fname = '{0:03d}b'.format(n_eqs)
to_pdf(g, res.rowp, res.colp, msg, fname)
print_timestamp()
def solve(g, n_eqs):
from plot_ordering import to_pdf
from six.moves import xrange as range
print('------------------------------------------------------------------')
print('Solving problem of size', n_eqs)
fname = '{0:03d}a'.format(n_eqs)
to_pdf(g, list(range(n_eqs)), range(n_eqs, 2 * n_eqs), fname=fname)
#
rowp, colp = hellerman_rarick_p_3_5(g, set(range(n_eqs)))
#
fname = '{0:03d}b'.format(n_eqs)
to_pdf(g, rowp, colp, fname=fname)
#
print('Plot written!')
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 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)