anneal['anneal_prior'] = False
output_path = create_output_path(basename = job_name)
model = BSC_ET(D, H, Hprime, gamma, to_learn=['W','sigma','pi','mu'])
data = {'y':patches}
out_fname = output_path + "/data.h5"
#setting up logging/output
print_list = ('T', 'Q', 'pi', 'sigma', 'N', 'MAE', 'L')
dlog.set_handler(print_list, TextPrinter)
h5store_list = ('W', 'pi', 'sigma', 'y', 'MAE', 'N','L','Q','mu')
dlog.set_handler(h5store_list, StoreToH5, output_path +'/result.h5')
###### Initialize model #######
# Initialize (Random) model parameters
model_params = model.standard_init(data)
#model_params['mu'] = np.mean(data['y'],axis=0)
# Create and start EM annealing
em = EM(model=model, anneal=anneal)
em.data = data
em.lparams = model_params
em.run()
if not channel_splitted:
# Take care of not channel splitted case
size = data_file.root.patches.shape[1] / 2
my_y = my_y[:, 0:size, :] - my_y[:, size:, :]
# We flatten everything here in the D dimension
my_y = my_y.reshape(my_N, -1)
my_y_rc = my_y_rc.reshape(my_N, -1)
_, D = my_y.shape
#========================= Configure DataLogger ===============================
print_list = ('T', 'pi', 'sigma', 'N', 'N_use')
store_list = ('*')
dlog.set_handler(print_list, StoreToTxt, output_path + '/terminal.txt')
dlog.set_handler(store_list, StoreToH5, result_path)
#========================= Enable tracing? =====================================
if enable_tracing:
dlog.progress("Tracing enabled")
tracing.set_tracefile(output_path + "/trace-%04d.txt")
#=========== Create annealing schedule if not done in param file ===============
if 'anneal' not in dir():
anneal = LinearAnnealing(anneal_steps)
anneal['T'] = [(anneal_start, temp_start), (anneal_end, temp_end)]
anneal['Ncut_factor'] = [(cut_start, 0.), (cut_end, 1.)]
anneal['anneal_prior'] = anneal_prior
anneal['W_noise'] = [(noise_decrease, W_noise), (noise_end, 0.)]
anneal['pi_noise'] = [(noise_decrease, pi_noise), (noise_end, 0.)]
# ============================================================================
# Main
if __name__ == "__main__":
comm = MPI.COMM_WORLD
pprint("=" * 78)
pprint(" Running %d parallel processes" % comm.size)
pprint("=" * 78)
# Configure DataLogger
# use('GTKAgg')
dlog.start_gui(GUI)
# dlog.set_handler('freeEnergy', YTPlotter)
dlog.set_handler(("T", "Qmean", "pi", "sigma", "Wmin", "Wmean", "Wmax"), TextPrinter)
dlog.set_handler("W", RFViewer, rf_shape=(D2, D2), symmetric=0, global_maximum=0)
# dlog.set_handler('y', RFViewer, rf_shape=(D2, D2))
# Choose annealing schedule
anneal = LinearAnnealing(Tsteps)
anneal["T"] = [(10, Tstart), (-10, Tend)]
anneal["Ncut_factor"] = [(2 / 3, 0.0), (-10, 1.0)]
anneal["W_noise"] = [(-10, 0.01), (-1, 0.0)]
# Prepare ground-truth GFs (bars)
W_gt = np.zeros((H, D2, D2))
for i in xrange(D2):
W_gt[i, i, :] = 10.0
W_gt[D2 + i, :, i] = 10.0
W_gt = W_gt.reshape((H, D))
#============================================================================
# Main
if __name__ == "__main__":
comm = MPI.COMM_WORLD
pprint("="*78)
pprint(" Running %d parallel processes" % comm.size)
pprint("="*78)
#Configure DataLogger
#use('GTKAgg')
dlog.start_gui(GUI)
#dlog.set_handler('freeEnergy', YTPlotter)
dlog.set_handler(('T', 'Qmean', 'pi', 'sigma', 'Wmin', 'Wmean', 'Wmax'), TextPrinter)
dlog.set_handler('W', RFViewer, rf_shape=(D2, D2), symmetric=1, global_maximum=1)
dlog.set_handler('y', RFViewer, rf_shape=(D2, D2))
dlog.set_handler(['pi'], YTPlotter)
dlog.set_handler(['sigma'], YTPlotter)
# Choose annealing schedule
anneal = LinearAnnealing(Tsteps)
anneal['T'] = [(10, Tstart) , (-20, Tend)]
anneal['Ncut_factor'] = [(0, 0.), (2./3, 1.2)]
anneal['W_noise'] = [(-10, 0.01), (-1, 0.01)]
# Prepare ground-truth GFs (bars)
W_gt = np.zeros( (H, D2, D2) )
for i in xrange(D2):
W_gt[ i, i, :] = -10.
pprint("Pi learned, but not noisified.")
if ("sigma" in to_learn) and (sigma_noise_intensity == 0):
pprint("Sigma learned, but not noisified.")
if (not gamma <= Hprime) or (not Hprime <= H):
pprint("gamma < Hprime < H has to be fullfilled. Aborting.")
run_algorithm = False
pprint("============================= ........ =============================\n")
# if not run_algorithm:
# exit(1)
# ------------------------------ Controls end ---------------------------------
# Configure DataLogger
dlog.start_gui(GUI)
print_list = ("Done", "T", "Q", "pi", "sigma", "N", "MAE")
dlog.set_handler(print_list, TextPrinter)
# dlog.set_handler(print_list, StoreToTxt, output_path +'terminal.txt')
# dlog.set_handler('Q', YTPlotter)
dlog.set_handler("W", RFViewer, rf_shape=(D2, D2))
dlog.set_handler(("W", "pi", "sigma", "mu", "y", "MAE", "N"), StoreToH5, output_path + "result.h5")
# dlog.set_handler(('W', 'pi', 'sigma', 'mu', 'y', 'MAE', 'N'), StoreToH5, output_path +'test_set.h5')
dlog.set_handler(["pi"], YTPlotter)
dlog.set_handler(["sigma"], YTPlotter)
dlog.set_handler("y", RFViewer, rf_shape=(D2, D2))
# Prepare ground-truth GFs (bars)
W_gt = np.zeros((H, D2, D2))
for i in xrange(D2):
W_gt[i, i, :] = bar_value
W_gt[D2 + i, :, i] = bar_value
if neg_bars > 0.0:
sys.path.insert(0, "..")
from time import sleep
import numpy as np
from pulp.utils.parallel import pprint
from pulp.utils.datalog import dlog, StoreToH5, TextPrinter
from pulp.visualize.gui import GUI, RFViewer, YTPlotter
# Parameters
rf_shape = (26, 26)
H = 16
# Configure Data-Logger
dlog.start_gui(GUI)
dlog.set_handler('W', RFViewer, rf_shape=rf_shape)
dlog.set_handler('S', YTPlotter)
dlog.set_handler('C', YTPlotter)
dlog.set_handler(('T', 'S', 'C'), TextPrinter)
# And GO!
D = rf_shape[0] * rf_shape[1]
Wshape = (H, D)
i = 0
for T in np.linspace(0., 20, 50):
i = i + 1
pprint("%i th iteration..." % i)
W = np.random.normal(size=Wshape)
dlog.append_all({
my_y = my_y[:, 0:size, :] - my_y[:, size:, :]
# We flatten everything here in the D dimension
my_y = my_y.reshape(my_N, -1)
my_y_rc = my_y_rc.reshape(my_N, -1)
_, D = my_y.shape
#========================= Configure DataLogger ===============================
print_list = ('T', 'pi', 'sigma', 'N', 'N_use')
store_list = ('*')
dlog.set_handler(print_list, StoreToTxt, output_path+'/terminal.txt')
dlog.set_handler(store_list, StoreToH5, result_path)
#========================= Enable tracing? =====================================
if enable_tracing:
dlog.progress("Tracing enabled")
tracing.set_tracefile(output_path+"/trace-%04d.txt")
#=========== Create annealing schedule if not done in param file ===============
if 'anneal' not in dir():
anneal = LinearAnnealing(anneal_steps)
anneal['T'] = [(anneal_start, temp_start), (anneal_end, temp_end)]
anneal['Ncut_factor'] = [(cut_start, 0.),(cut_end, 1.)]
anneal['anneal_prior'] = anneal_prior
anneal['W_noise'] = [(noise_decrease, W_noise), (noise_end, 0.)]
anneal['pi_noise'] = [(noise_decrease, pi_noise), (noise_end, 0.)]
sys.path.insert(0, "..")
from time import sleep
import numpy as np
from pulp.utils.parallel import pprint
from pulp.utils.datalog import dlog, StoreToH5, TextPrinter
from pulp.visualize.gui import GUI, RFViewer, YTPlotter
# Parameters
rf_shape = (26, 26)
H = 16
# Configure Data-Logger
dlog.start_gui(GUI)
dlog.set_handler('W', RFViewer, rf_shape=rf_shape)
dlog.set_handler('S', YTPlotter)
dlog.set_handler('C', YTPlotter)
dlog.set_handler(('T', 'S', 'C'), TextPrinter)
# And GO!
D = rf_shape[0] * rf_shape[1]
Wshape = (H,D)
i = 0
for T in np.linspace(0., 20, 50):
i = i + 1
pprint( "%i th iteration..." % i)
W = np.random.normal(size=Wshape)
dlog.append_all( {
pprint("Sigma learned, but not noisified.")
if (not gamma <= Hprime) or (not Hprime <= H):
pprint("gamma < Hprime < H has to be fullfilled. Aborting.")
run_algorithm = False
pprint(
"============================= ........ =============================\n"
)
#if not run_algorithm:
# exit(1)
# ------------------------------ Controls end ---------------------------------
# Configure DataLogger
dlog.start_gui(GUI)
print_list = ('Done', 'T', 'Q', 'pi', 'sigma', 'N', 'MAE')
dlog.set_handler(print_list, TextPrinter)
#dlog.set_handler(print_list, StoreToTxt, output_path +'terminal.txt')
#dlog.set_handler('Q', YTPlotter)
dlog.set_handler('W', RFViewer, rf_shape=(D2, D2))
dlog.set_handler(('W', 'pi', 'sigma', 'mu', 'y', 'MAE', 'N'), StoreToH5,
output_path + 'result.h5')
#dlog.set_handler(('W', 'pi', 'sigma', 'mu', 'y', 'MAE', 'N'), StoreToH5, output_path +'test_set.h5')
dlog.set_handler(['pi'], YTPlotter)
dlog.set_handler(['sigma'], YTPlotter)
dlog.set_handler('y', RFViewer, rf_shape=(D2, D2))
# Prepare ground-truth GFs (bars)
W_gt = np.zeros((H, D2, D2))
for i in xrange(D2):
W_gt[i, i, :] = bar_value
W_gt[D2 + i, :, i] = bar_value
#============================================================================
# Main
if __name__ == "__main__":
comm = MPI.COMM_WORLD
pprint("=" * 78)
pprint(" Running %d parallel processes" % comm.size)
pprint("=" * 78)
#Configure DataLogger
#use('GTKAgg')
dlog.start_gui(GUI)
#dlog.set_handler('freeEnergy', YTPlotter)
dlog.set_handler(('T', 'Qmean', 'pi', 'sigma', 'Wmin', 'Wmean', 'Wmax'),
TextPrinter)
dlog.set_handler('W',
RFViewer,
rf_shape=(D2, D2),
symmetric=1,
global_maximum=1)
dlog.set_handler('y', RFViewer, rf_shape=(D2, D2))
dlog.set_handler(['pi'], YTPlotter)
dlog.set_handler(['sigma'], YTPlotter)
# Choose annealing schedule
anneal = LinearAnnealing(Tsteps)
anneal['T'] = [(10, Tstart), (-20, Tend)]
anneal['Ncut_factor'] = [(0, 0.), (2. / 3, 1.2)]
anneal['W_noise'] = [(-10, 0.01), (-1, 0.01)]