def compute_dist_stats(id_distance, id_stream, delta):
distances_library = get_conftools_uncertain_image_distances()
distance = distances_library.instance(id_distance)
stream = get_conftools_streams().instance(id_stream)
it = stream.read_all()
results = []
for logitem in iterate_testcases(it, delta):
assert_allclose(len(logitem.u), delta)
y0 = UncertainImage(logitem.y0)
y1 = UncertainImage(logitem.y1)
d = distance.distance(y0, y1)
results.append(d)
logger.info('%s: found %d of %d steps in %s' %
(id_distance, len(results), delta, id_stream))
return results
def compute_dist_stats(id_distance, id_stream, delta):
distances_library = get_conftools_uncertain_image_distances()
distance = distances_library.instance(id_distance)
stream = get_conftools_streams().instance(id_stream)
it = stream.read_all()
results = []
for logitem in iterate_testcases(it, delta):
assert_allclose(len(logitem.u), delta)
y0 = UncertainImage(logitem.y0)
y1 = UncertainImage(logitem.y1)
d = distance.distance(y0, y1)
results.append(d)
logger.info('%s: found %d of %d steps in %s' %
(id_distance, len(results), delta, id_stream))
return results
def compute_predstats(id_discdds, id_stream, delta, id_distances):
dds = get_conftools_discdds().instance(id_discdds)
stream = get_conftools_streams().instance(id_stream)
distances_library = get_conftools_uncertain_image_distances()
distances = dict(map(lambda x: (x, distances_library.instance(x)), id_distances))
dtype = [(x, 'float32') for x in id_distances]
results = []
for logitem in iterate_testcases(stream.read_all(), delta):
assert_allclose(len(logitem.u), delta)
y0 = UncertainImage(logitem.y0)
y1 = UncertainImage(logitem.y1)
py0 = dds.predict(y0, dds.commands_to_indices(logitem.u))
ds = []
for name in id_distances:
d = distances[name].distance(y1, py0)
# d0 = distances[name].distance(y1, y0)
ds.append(d)
a = np.array(tuple(ds), dtype=dtype)
results.append(a)
return results
def compute_predstats(id_discdds, id_stream, delta, id_distances):
dds = get_conftools_discdds().instance(id_discdds)
stream = get_conftools_streams().instance(id_stream)
distances_library = get_conftools_uncertain_image_distances()
distances = dict(
map(lambda x: (x, distances_library.instance(x)), id_distances))
dtype = [(x, 'float32') for x in id_distances]
results = []
for logitem in iterate_testcases(stream.read_all(), delta):
assert_allclose(len(logitem.u), delta)
y0 = UncertainImage(logitem.y0)
y1 = UncertainImage(logitem.y1)
py0 = dds.predict(y0, dds.commands_to_indices(logitem.u))
ds = []
for name in id_distances:
d = distances[name].distance(y1, py0)
# d0 = distances[name].distance(y1, y0)
ds.append(d)
a = np.array(tuple(ds), dtype=dtype)
results.append(a)
return results
