def visualize_rbn_state(n=100, working_dir=None):
if not working_dir:
working_dir = get_working_dir()
rbn, rbn_name = glob_load(working_dir + '*-reservoir')[0]
rbn.reset_state()
if not user_denies('Perturb?'):
test_data, _ = glob_load(working_dir + '*-dataset')[0]
test_input, _ = test_data
test_input = test_input[:n]
else:
test_input = np.zeros((n, 1))
rbn.should_perturb = False
rbn_states = rbn._execute(test_input)
plt.matshow(rbn_states, cmap=plt.cm.gray)
plt.axis('off')
#plt.xlabel('State of node n in RBN')
#plt.gca().xaxis.set_label_position('top')
#plt.ylabel('Time')
plt.savefig(raw_input('Name: '), bbox_inches='tight')
# Set pickle working dir
working_dir = get_working_dir()
log.setup(logging.DEBUG, path=working_dir)
log_git_info()
# Create datasets
use_existing_dataset = user_confirms('Use existing dataset in folder?')
if use_existing_dataset:
test_dataset, _ = glob_load(working_dir + '*-dataset')[0]
dataset_description = '[dataset_from_folder]'
else:
datasets, dataset_description = create_dataset()
training_dataset, test_dataset = datasets[:-1], datasets[-1]
if not use_existing_dataset and not user_denies('Pickle test dataset?'):
dump(test_dataset, dataset_description + '-dataset',
folder=working_dir)
# Create or load reservoir and readout layer
if user_confirms('Use readout layer from folder?'):
readout, _ = glob_load(working_dir + '*readout')[0]
else:
rbn_reservoir = create_reservoir()
readout = Oger.nodes.RidgeRegressionNode(
input_dim=rbn_reservoir.output_dim,
output_dim=1,
verbose=True)
# Train and execute newly created flow
flow = mdp.Flow([rbn_reservoir, readout], verbose=1)
# Set pickle working dir
working_dir = get_working_dir()
log.setup(logging.DEBUG, path=working_dir)
log_git_info()
# Create datasets
use_existing_dataset = user_confirms('Use existing dataset in folder?')
if use_existing_dataset:
test_dataset, _ = glob_load(working_dir + '*-dataset')[0]
dataset_description = '[dataset_from_folder]'
else:
datasets, dataset_description = create_dataset()
training_dataset, test_dataset = datasets[:-1], datasets[-1]
if not use_existing_dataset and not user_denies('Pickle test dataset?'):
dump(test_dataset,
dataset_description + '-dataset',
folder=working_dir)
# Create or load reservoir and readout layer
if user_confirms('Use readout layer from folder?'):
readout, _ = glob_load(working_dir + '*readout')[0]
else:
rbn_reservoir = create_reservoir()
readout = Oger.nodes.RidgeRegressionNode(
input_dim=rbn_reservoir.output_dim, output_dim=1, verbose=True)
# Train and execute newly created flow
flow = mdp.Flow([rbn_reservoir, readout], verbose=1)
flow.train([None, training_dataset])
