def _match_sub(disc_clsdict, gold_clsdict, phn_corpus, names, label, verbose,
n_jobs):
em = eval_from_psets
if verbose:
print ' matching ({2}): subsampled {0} files in {1} sets'\
.format(sum(map(len, names)), len(names), label)
with verb_print(' matching ({0}): prepping psets'.format(label), verbose,
True, True, True):
pdiscs = [
make_pdisc(disc_clsdict.restrict(fs, True), False, False)
for fs in names
]
pgolds = [
make_pgold(gold_clsdict.restrict(fs, True), False, False)
for fs in names
]
psubs = [
make_psubs(disc_clsdict.restrict(fs, True), phn_corpus, 3, 20,
False, False) for fs in names
]
with verb_print(' matching ({0}): calculating scores'.format(label),
verbose, False, True, False):
tp, tr = izip(*Parallel(
n_jobs=n_jobs, verbose=5 if verbose else 0, pre_dispatch='n_jobs')(
delayed(em)(pdisc, pgold, psub)
for pdisc, pgold, psub in zip(pdiscs, pgolds, psubs)))
tp, tr = np.fromiter(tp, dtype=np.double), np.fromiter(tr, dtype=np.double)
tp, tr = praggregate(tp, tr)
return tp, tr
def _match_sub(disc_clsdict, gold_clsdict, phn_corpus, names, label,
verbose, n_jobs):
em = eval_from_psets
if verbose:
print ' matching ({2}): subsampled {0} files in {1} sets'\
.format(sum(map(len, names)), len(names), label)
with verb_print(' matching ({0}): prepping psets'.format(label),
verbose, True, True, True):
pdiscs = [make_pdisc(disc_clsdict.restrict(fs, True),
False, False)
for fs in names]
pgolds = [make_pgold(gold_clsdict.restrict(fs, True),
False, False)
for fs in names]
psubs = [make_psubs(disc_clsdict.restrict(fs, True),
phn_corpus, 3, 20, False, False)
for fs in names]
with verb_print(' matching ({0}): calculating scores'
.format(label), verbose, False, True, False):
tp, tr = izip(*Parallel(n_jobs=n_jobs,
verbose=5 if verbose else 0,
pre_dispatch='n_jobs')
(delayed(em)(pdisc, pgold, psub)
for pdisc, pgold, psub in zip(pdiscs, pgolds, psubs)))
tp, tr = np.fromiter(tp, dtype=np.double), np.fromiter(tr, dtype=np.double)
tp, tr = praggregate(tp, tr)
return tp, tr