def run(self):
global ongoing_clustering
ongoing_clustering = True
self.status_listener = StatusListener(self.observer, self.status)
self.status_listener.start()
try:
self.driver = Driver(self.observer)
self.driver.run(self.parameters)
except Exception, e:
print e
print traceback.format_exc()
class ExecutionThread(ThreadWithExc):
def __init__(self, observer, parameters):
super(ExecutionThread, self).__init__()
self.observer = observer
self.parameters = parameters
self.status = {"status":"Initializing...","value":False}
self.driver = None
self.driver_process = None
def run(self):
global ongoing_clustering
ongoing_clustering = True
self.status_listener = StatusListener(self.observer, self.status)
self.status_listener.start()
try:
self.driver = Driver(self.observer)
self.driver.run(self.parameters)
except Exception, e:
print e
print traceback.format_exc()
finally:
parameters["clustering"]["evaluation"][
"minimum_cluster_size"] = data.minsize[dataset_name]
parameters["clustering"]["evaluation"][
"minimum_clusters"] = data.num_cluster_ranges[dataset_name][0]
parameters["clustering"]["evaluation"][
"maximum_clusters"] = data.num_cluster_ranges[dataset_name][1]
print parameters["clustering"]["evaluation"][
"minimum_clusters"], parameters["clustering"]["evaluation"][
"maximum_clusters"]
if dataset_name in data.criteria:
parameters["clustering"]["evaluation"][
"evaluation_criteria"] = data.criteria[dataset_name]
else:
parameters["clustering"]["evaluation"][
"evaluation_criteria"] = data.criteria["default"]
Driver(Observer()).run(parameters)
for dataset_name in ['concentric_circles']: #data.all_datasets:
results_file = os.path.join(os.path.abspath("./tmp/%s" % dataset_name),
"results/results.json")
results = convert_to_utf8(json.loads(open(results_file).read()))
best = results["best_clustering"]
clustering = Clustering.from_dic(
results["selected"][best]["clustering"])
vtools.show_2D_dataset_clusters(
all_observations[dataset_name], clustering, scale=20,
margin=20).save("clustering_images/%s.jpg" % dataset_name, "JPEG")
print dataset_name, results["selected"][best]["type"], results[
"selected"][best]["clustering"]["number_of_clusters"], results[
"selected"][best]["evaluation"][
"Noise level"], #results["selected"][best]["parameters"]
parameters = None
try:
parameters = ProtocolParameters.get_params_from_json(
tools.remove_comments(open(json_script).read()))
parameters["global"]["workspace"]["base"] = os.path.abspath(
parameters["global"]["workspace"]["base"])
except ValueError, e:
print "Malformed json script."
print e.message
exit()
observer = None
cmd_thread = None
if options.use_mpi:
from pyproct.driver.mpidriver import MPIDriver
from pyproct.driver.observer.MPIObserver import MPIObserver
observer = MPIObserver()
if options.print_messages:
cmd_thread = CmdLinePrinter(observer)
cmd_thread.start()
MPIDriver(observer).run(parameters)
else:
observer = Observer()
if options.print_messages:
cmd_thread = CmdLinePrinter(observer)
cmd_thread.start()
Driver(observer).run(parameters)
if options.print_messages:
cmd_thread.stop()
