def read_stream(self, id_stream):
stream = get_conftools_streams().instance(id_stream)
for i, log_item in enumerate(stream.read_all()):
timestamp = i * 1.0
yield 'y0', timestamp, log_item.y0
yield 'y1', timestamp, log_item.y1
yield 'u', timestamp, log_item.u
def read_stream(self, id_stream):
stream = get_conftools_streams().instance(id_stream)
for i, log_item in enumerate(stream.read_all()):
timestamp = i * 1.0
yield 'y0', timestamp, log_item.y0
yield 'y1', timestamp, log_item.y1
yield 'u', timestamp, log_item.u
def define_jobs_context(self, context):
distances_library = get_conftools_uncertain_image_distances()
distances = distances_library.expand_names(self.options.distances)
distances = natsorted(distances)
streams_library = get_conftools_streams()
streams = streams_library.expand_names(self.options.streams)
streams = natsorted(streams)
# id_comb = ','.join(streams) + '-' + ','.join(distances)
create_diststats_jobs(context, distances=distances, streams=streams,
maxd=self.options.maxd)
def define_jobs_context(self, context):
distances_library = get_conftools_uncertain_image_distances()
distances = distances_library.expand_names(self.options.distances)
streams_library = get_conftools_streams()
streams = streams_library.expand_names(self.options.streams)
discdds_library = get_conftools_discdds()
discdds = discdds_library.expand_names(self.options.dds)
for c, id_discdds in iterate_context_names(context, discdds):
create_predstats_jobs(context=c, distances=distances,
id_discdds=id_discdds,
streams=streams, maxd=10)
def video_visualize_diffeo_stream1_robot(id_robot, boot_root, out):
""" Creates a video for the stream. """
my_stream = 'robotstream-%s' % id_robot
bootstream = ['diffeo_agents.library.BootStream',
dict(id_robot=id_robot,
boot_root=boot_root)]
limit_stream = ['diffeo2dds_learn.library.LimitStream',
dict(n=1000, stream=bootstream)]
streams = get_conftools_streams()
streams.add_spec(my_stream, "", limit_stream)
return video_visualize_diffeo_stream1(my_stream, out)
def define_jobs_context(self, context):
distances_library = get_conftools_uncertain_image_distances()
distances = distances_library.expand_names(self.options.distances)
distances = natsorted(distances)
streams_library = get_conftools_streams()
streams = streams_library.expand_names(self.options.streams)
streams = natsorted(streams)
# id_comb = ','.join(streams) + '-' + ','.join(distances)
create_diststats_jobs(context,
distances=distances,
streams=streams,
maxd=self.options.maxd)
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 define_jobs_context(self, context):
distances_library = get_conftools_uncertain_image_distances()
distances = distances_library.expand_names(self.options.distances)
streams_library = get_conftools_streams()
streams = streams_library.expand_names(self.options.streams)
discdds_library = get_conftools_discdds()
discdds = discdds_library.expand_names(self.options.dds)
for c, id_discdds in iterate_context_names(context, discdds):
create_predstats_jobs(context=c,
distances=distances,
id_discdds=id_discdds,
streams=streams,
maxd=10)
def make_logcases(id_stream, n, delta, id_tcs, id_discdds, discdds, seed):
stream = get_conftools_streams().instance(id_stream)
stream_data = stream.read_all()
miniplans = iterate_testcases(stream_data, delta)
sampled = reservoir_sample(miniplans, N=n, seed=seed)
for i, m in enumerate(sampled):
id_tc = id_tcs[i]
I0 = UncertainImage(m.y0)
I1 = UncertainImage(m.y1)
assert len(m.u) == delta
plan = discdds.commands_to_indices(m.u)
tc = TestCase(id_tc=id_tc, id_discdds=id_discdds, y0=I0, y1=I1, true_plan=plan)
# TODO: add field desc
# desc = 'Sampled from stream %s, i=%s for seed %s.' % (i, seed)
yield tc
def video_visualize_diffeo_stream1_robot(id_robot, boot_root, out):
""" Creates a video for the stream. """
my_stream = 'robotstream-%s' % id_robot
bootstream = [
'diffeo_agents.library.BootStream',
dict(id_robot=id_robot, boot_root=boot_root)
]
limit_stream = [
'diffeo2dds_learn.library.LimitStream',
dict(n=1000, stream=bootstream)
]
streams = get_conftools_streams()
streams.add_spec(my_stream, "", limit_stream)
return video_visualize_diffeo_stream1(my_stream, out)
def make_logcases(id_stream, n, delta, id_tcs, id_discdds, discdds, seed):
stream = get_conftools_streams().instance(id_stream)
stream_data = stream.read_all()
miniplans = iterate_testcases(stream_data, delta)
sampled = reservoir_sample(miniplans, N=n, seed=seed)
for i, m in enumerate(sampled):
id_tc = id_tcs[i]
I0 = UncertainImage(m.y0)
I1 = UncertainImage(m.y1)
assert len(m.u) == delta
plan = discdds.commands_to_indices(m.u)
tc = TestCase(id_tc=id_tc,
id_discdds=id_discdds,
y0=I0,
y1=I1,
true_plan=plan)
# TODO: add field desc
# desc = 'Sampled from stream %s, i=%s for seed %s.' % (i, seed)
yield tc
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
def read_stream(self, id_stream):
stream = get_conftools_streams().instance(id_stream)
for i, log_item in enumerate(stream.read_all()):
signal = 'data'
timestamp = i * 1.0
yield signal, timestamp, log_item
#
#
# for_all_imagestreams = fancy_test_decorator(lister=image_stream_lister,
# arguments=lambda id_image_stream:
# (id_image_stream, testconfig().image_streams.instance(id_image_stream)),
# attributes=lambda id_image_stream: dict(image_stream=id_image_stream),
# debug=True)
#
# def stream_lister():
# config = testconfig()
# keys = config.streams.keys()
# keys = [k for k in keys if k.startswith('test_')]
# return keys
#
# for_all_streams = fancy_test_decorator(lister=stream_lister,
# arguments=lambda x: (x, testconfig().streams.instance(x)),
# attributes=lambda x: dict(stream=x),
# debug=True)
from comptests.registrar import comptests_for_all
from diffeo2dds_learn import get_conftools_streams, get_conftools_image_streams
from diffeo2dds_learn.configuration.config_master import (
get_conftools_diffeoaction_estimators,
get_conftools_diffeosystem_estimators,
)
for_all_streams = comptests_for_all(get_conftools_streams())
for_all_image_streams = comptests_for_all(get_conftools_image_streams())
for_all_diffeoaction_estimators = comptests_for_all(get_conftools_diffeoaction_estimators())
for_all_diffeosystem_estimators = comptests_for_all(get_conftools_diffeosystem_estimators())
#
#
# for_all_imagestreams = fancy_test_decorator(lister=image_stream_lister,
# arguments=lambda id_image_stream:
# (id_image_stream, testconfig().image_streams.instance(id_image_stream)),
# attributes=lambda id_image_stream: dict(image_stream=id_image_stream),
# debug=True)
#
# def stream_lister():
# config = testconfig()
# keys = config.streams.keys()
# keys = [k for k in keys if k.startswith('test_')]
# return keys
#
# for_all_streams = fancy_test_decorator(lister=stream_lister,
# arguments=lambda x: (x, testconfig().streams.instance(x)),
# attributes=lambda x: dict(stream=x),
# debug=True)
from comptests.registrar import comptests_for_all
from diffeo2dds_learn import (get_conftools_streams,
get_conftools_image_streams)
from diffeo2dds_learn.configuration.config_master import get_conftools_diffeoaction_estimators, \
get_conftools_diffeosystem_estimators
for_all_streams = comptests_for_all(get_conftools_streams())
for_all_image_streams = comptests_for_all(get_conftools_image_streams())
for_all_diffeoaction_estimators = comptests_for_all(get_conftools_diffeoaction_estimators())
for_all_diffeosystem_estimators = comptests_for_all(get_conftools_diffeosystem_estimators())
def read_stream(self, id_stream):
stream = get_conftools_streams().instance(id_stream)
for i, log_item in enumerate(stream.read_all()):
signal = 'data'
timestamp = i * 1.0
yield signal, timestamp, log_item
