def check_recording(self, values):
#print "check recording on %s" % self.name
if not os.path.exists(self.sensor_data_dir):
os.makedirs(self.sensor_data_dir)
if self.listener.get_start_recording_request() and not self.recording:#check whether it is already recouding
self.listener.reset_start_recording_request()
self.recording = True
print 'start recording.......'
self.next_store_dir = next_file_name(prefix='store', suffix='', path=self.sensor_data_dir)
path,self.new_store_name = os.path.split(self.next_store_dir)
if not os.path.exists(self.next_store_dir):
os.makedirs(self.next_store_dir)
self.target = open(self.next_store_dir + '/out.csv', 'w')
if self.listener.get_stop_recording_request():
self.listener.reset_stop_recording_request()
self.recording = False
self.target.close()
self.announce_new_record()
#self.send_payload(payload=';'.join(payload))
if self.recording:
print "recording...."
print(self.sensors_dir + self.name)
self.target.write(','.join(values) + '\n')
def check_recording(self, values):
#print "check recording on %s" % self.name
if not os.path.exists(self.sensor_data_dir):
os.makedirs(self.sensor_data_dir)
if self.listener.get_start_recording_request(
) and not self.recording: #check whether it is already recouding
self.listener.reset_start_recording_request()
self.recording = True
print 'start recording.......'
self.next_store_dir = next_file_name(prefix='store',
suffix='',
path=self.sensor_data_dir)
path, self.new_store_name = os.path.split(self.next_store_dir)
if not os.path.exists(self.next_store_dir):
os.makedirs(self.next_store_dir)
self.target = open(self.next_store_dir + '/out.csv', 'w')
if self.listener.get_stop_recording_request():
self.listener.reset_stop_recording_request()
self.recording = False
self.target.close()
self.announce_new_record()
#self.send_payload(payload=';'.join(payload))
if self.recording:
print "recording...."
print(self.sensors_dir + self.name)
self.target.write(','.join(values) + '\n')
def run_swarm_ng(working_dir, sensors_dir, sensor, store, swarmconfig):
store_dir = sensors_dir + sensor + '/stores/' + store + '/'
swarms_dir = store_dir + '/swarms/'
swarm_dir = next_file_name(prefix='swarm', suffix='', path=swarms_dir)
path, swarm = os.path.split(swarm_dir)
swarm_dir = swarm_dir + '/'
egg_file = swarm_dir + "eggs.csv"
store_file = store_dir + 'out.csv'
swarmconfig['streamDef']['streams'][0]['source'] = 'file://' + egg_file
print swarmconfig['streamDef']['streams'][0]['source']
if not os.path.exists(swarms_dir):
os.makedirs(swarms_dir)
if not os.path.exists(swarm_dir):
os.makedirs(swarm_dir)
fieldNames = map(lambda x: x['fieldName'], swarmconfig['includedFields'])
fieldTypes = map(lambda x: x['fieldType'], swarmconfig['includedFields'])
prepare_swarm(field_names=fieldNames,
field_types=fieldTypes,
egg_file=egg_file,
store_file=store_file)
#swarm_config = {} # complete swarm config here
#nupic_config = permutations_runner.runWithJsonFile(os.getcwd() + "/nupic/search_def.json",{'maxWorkers': 6, 'overwrite': True}, "test", os.getcwd() + "/working")
nupic_config = permutations_runner.runWithConfig(swarmconfig, {
'maxWorkers': 6,
'overwrite': True
},
outDir=swarm_dir,
outputLabel='',
permWorkDir=swarm_dir,
verbosity=1)
#dump the model params generated by this swarm in 2 different file formats
pickle_file = open(swarm_dir + 'model_params.pkl', 'w')
pickle.dump(nupic_config, pickle_file, pickle.HIGHEST_PROTOCOL)
pickle_file.close()
json_file = open(swarm_dir + 'model_params.json', 'w')
json.dump(nupic_config, json_file)
json_file.close()
#dump the swarmconfig used for this swarm in 2 different file formats
pickle_file = open(swarm_dir + 'swarm_config.pkl', 'w')
pickle.dump(swarmconfig, pickle_file, pickle.HIGHEST_PROTOCOL)
pickle_file.close()
json_file = open(swarm_dir + 'swarm_config.json', 'w')
json.dump(swarmconfig, json_file)
json_file.close()
return swarm
def run_swarm_ng(working_dir,sensors_dir, sensor, store, swarmconfig):
store_dir = sensors_dir + sensor + '/stores/' + store +'/'
swarms_dir = store_dir + '/swarms/'
swarm_dir = next_file_name(prefix='swarm',suffix='',path=swarms_dir)
path,swarm = os.path.split(swarm_dir)
swarm_dir = swarm_dir + '/'
egg_file = swarm_dir + "eggs.csv"
store_file = store_dir + 'out.csv'
swarmconfig['streamDef']['streams'][0]['source'] = 'file://' + egg_file
print swarmconfig['streamDef']['streams'][0]['source']
if not os.path.exists(swarms_dir):
os.makedirs(swarms_dir)
if not os.path.exists(swarm_dir):
os.makedirs(swarm_dir)
fieldNames = map(lambda x: x['fieldName'],swarmconfig['includedFields'])
fieldTypes = map(lambda x: x['fieldType'],swarmconfig['includedFields'])
prepare_swarm(field_names=fieldNames, field_types= fieldTypes, egg_file=egg_file, store_file = store_file)
#swarm_config = {} # complete swarm config here
#nupic_config = permutations_runner.runWithJsonFile(os.getcwd() + "/nupic/search_def.json",{'maxWorkers': 6, 'overwrite': True}, "test", os.getcwd() + "/working")
nupic_config = permutations_runner.runWithConfig(swarmconfig,
{'maxWorkers': 6,
'overwrite': True
},
outDir= swarm_dir,
outputLabel='',
permWorkDir= swarm_dir,
verbosity=1)
#dump the model params generated by this swarm in 2 different file formats
pickle_file = open(swarm_dir + 'model_params.pkl', 'w')
pickle.dump(nupic_config,pickle_file,pickle.HIGHEST_PROTOCOL)
pickle_file.close()
json_file = open(swarm_dir +'model_params.json', 'w')
json.dump(nupic_config, json_file)
json_file.close()
#dump the swarmconfig used for this swarm in 2 different file formats
pickle_file = open(swarm_dir + 'swarm_config.pkl', 'w')
pickle.dump(swarmconfig,pickle_file,pickle.HIGHEST_PROTOCOL)
pickle_file.close()
json_file = open(swarm_dir+ 'swarm_config.json', 'w')
json.dump(swarmconfig, json_file)
json_file.close()
return swarm
