def dship(table_file, **kwargs):
"""Build models from dshiped table file
"""
chained = chain_files(table_file)
loaded = stream.load(chained)
basename = '-'.join(os.path.basename(f).split('.')[0] for f in table_file)
for k1 in loaded:
for k2 in loaded[k1]:
assert k2 == 'NULL'
model = loaded[k1][k2]
save_model(model, 'data/%s_%s.model' % (basename, k1))
def classify_all(file_names, models,
use_duration=True,
window=semi_markov.WINDOW):
"""Return classify results per terminal type
:param file_names: samples to read from
:param models: the models
:param use_duration: use duration density or not
:param window: smoothing window size when using duration
:return: {terminal: [(path, result)]}
"""
results = defaultdict(list)
for line in chain_files(file_names):
ret = query_line(line, models, use_duration, window)
if ret:
results[ret.term].append((ret.path, ret.result))
return results
