def run_nns(testset, s_vectors, ticks=None, verbose=True):
if ticks is None:
ticks = range(len(s_vectors))
ticks, N = set(ticks), len(ticks)
avgs, stds = [], []
nnset = learners.NNSet()
for t, s_vector in enumerate(s_vectors):
nnset.add((), s_vector)
if t in ticks:
if verbose:
gfx.print_progress(len(avgs), N)
errors = []
for s_vector_goal in testset:
distances, idx = nnset.nn_y(s_vector_goal, k=1)
s_vector = nnset.ys[idx[0]]
errors.append(dist(s_vector_goal, s_vector))
avgs.append(np.mean(errors))
stds.append(np.std(errors))
if verbose:
gfx.print_progress(N, N)
return avgs, stds
def run_nns(testset, s_vectors, ticks=None, verbose=True):
if ticks is None:
ticks = range(len(s_vectors))
ticks, N = set(ticks), len(ticks)
avgs, stds = [], []
nnset = learners.NNSet()
for t, s_vector in enumerate(s_vectors):
nnset.add((), s_vector)
if t in ticks:
if verbose:
gfx.print_progress(len(avgs), N)
errors = []
for s_vector_goal in testset:
distances, idx = nnset.nn_y(s_vector_goal, k=1)
s_vector = nnset.ys[idx[0]]
errors.append(dist(s_vector_goal, s_vector))
avgs.append(np.mean(errors))
stds.append(np.std(errors))
if verbose:
gfx.print_progress(N, N)
return avgs, stds
def run_exploration(env, ex, N, mesh=None, verbose=False, prefix=""):
explorations, s_vectors, s_goals = [], [], []
for i in range(N):
if verbose and i % 100 == 0:
gfx.print_progress(i, N, prefix=prefix)
exploration = ex.explore()
feedback = env.execute(exploration["m_signal"])
ex.receive(exploration, feedback)
s_vectors.append(tools.to_vector(feedback["s_signal"], env.s_channels))
if "s_goal" in exploration:
s_goals.append(tools.to_vector(exploration["s_goal"], env.s_channels))
if mesh is not None:
mesh.add(feedback["s_signal"], m_signal=exploration["m_signal"])
explorations.append((exploration, feedback))
if verbose:
gfx.print_progress(N, N, prefix=prefix)
return explorations, s_vectors, s_goals
def run_exploration(env, ex, N, mesh=None, verbose=False, prefix=''):
explorations, s_vectors, s_goals = [], [], []
for i in range(N):
if verbose and i % 100 == 0:
gfx.print_progress(i, N, prefix=prefix)
exploration = ex.explore()
feedback = env.execute(exploration['m_signal'])
ex.receive(exploration, feedback)
s_vectors.append(tools.to_vector(feedback['s_signal'], env.s_channels))
if 's_goal' in exploration:
s_goals.append(
tools.to_vector(exploration['s_goal'], env.s_channels))
if mesh is not None:
mesh.add(feedback['s_signal'], m_signal=exploration['m_signal'])
explorations.append((exploration, feedback))
if verbose:
gfx.print_progress(N, N, prefix=prefix)
return explorations, s_vectors, s_goals