class CassandraSubscriber(object):
"""
Subscribes and writes data to a file
"""
def __init__(self, device_name, device_id, rabbitmq_address, metric):
self.subscriber = PikaSubscriber(device_name=device_name,
device_id=device_id,
rabbitmq_address=rabbitmq_address,
metric_name=metric)
self.metric = metric
self.device_name = device_name
self.device_id = device_id
self.num_channels = get_num_channels(device_name, metric)
self.cassandra_dao = CassandraDAO()
def start(self):
"""
Consume and write data to file
:return:
"""
self.cassandra_dao.connect()
self.subscriber.connect()
self.subscriber.consume_messages(self.write_to_cassandra)
def stop(self):
"""
Unsubscribe and close file
:return:
"""
self.subscriber.disconnect()
self.file.close_file(self.write_to_cassandra)
def write_to_cassandra(self, ch, method, properties, body):
buffer_content = json.loads(body)
for record in buffer_content:
timestamp = record["timestamp"]
channel_data = [record["channel_%s" % i] for i in xrange(self.num_channels)]
self.cassandra_dao.store_data(timestamp, self.device_id, self.device_name, self.metric, channel_data)
class CassandraSubscriber(object):
"""
Subscribes and writes data to a file
"""
def __init__(self, device_name, device_id, rabbitmq_address, metric):
self.subscriber = PikaSubscriber(device_name=device_name,
device_id=device_id,
rabbitmq_address=rabbitmq_address,
metric_name=metric)
self.metric = metric
self.device_name = device_name
self.device_id = device_id
self.num_channels = get_num_channels(device_name, metric)
self.cassandra_dao = CassandraDAL()
def start(self):
"""
Consume and write data to file
:return:
"""
self.cassandra_dao.connect()
self.subscriber.connect()
self.subscriber.consume_messages(self.write_to_cassandra)
def stop(self):
"""
Unsubscribe and close file
:return:
"""
self.subscriber.disconnect()
self.file.close_file(self.write_to_cassandra)
def write_to_cassandra(self, ch, method, properties, body):
buffer_content = json.loads(body)
for record in buffer_content:
timestamp = record["timestamp"]
channel_data = [
record["channel_%s" % i] for i in xrange(self.num_channels)
]
self.cassandra_dao.store_data(timestamp, self.device_id,
self.device_name, self.metric,
channel_data)
d.append(float(row['channel_5']) - float(row['channel_3']))
# print(msg['left'])
# print(len(msg))
data.extend(d)
data = data[-N_points-extra:]
if count == 1:
update_plot()
count = 0
else:
count += 1
eeg_subscriber = PikaSubscriber(device_name, device_id, host, metric)
eeg_subscriber.connect()
eeg_subscriber.consume_messages(consume_eeg)
# # loop to update the data
# while True:
# try:
# try:
# x = float(s.readline().strip())
# except ValueError:
# continue
# data.append(x)
# data = data[-100:]
# # set the new data
class FileWriterSubscriber(object):
"""
Subscribes and writes data to a file
"""
def __init__(self, device_name, device_id, rabbitmq_address, metric):
self.subscriber = PikaSubscriber(device_name=device_name,
device_id=device_id,
rabbitmq_address=rabbitmq_address,
metric_name=metric)
self.metric = metric
self.device_name = device_name
self.device_id = device_id
self.csv_writer = None
self.file = None
self.headers = None
def get_headers(self):
"""
Generate the CSV headers for that metric.
:return: CSV headers
"""
num_channels = get_num_channels(self.device_name,self.metric)
headers = ['timestamp'] + ['channel_%s' % i for i in xrange(num_channels)]
return headers
def init_file(self):
"""
Open file and write headers.
:return:
"""
if not os.path.exists("data"):
os.mkdir("data")
file_path = os.path.join("data", "%s_%s_%s.csv" % (self.device_id, self.device_name, self.metric))
self.file = open(file_path, 'wb')
self.csv_writer = csv.writer(self.file)
self.csv_writer.writerow(self.headers)
def start(self):
"""
Consume and write data to file
:return:
"""
self.headers = self.get_headers()
self.init_file()
self.subscriber.connect()
self.subscriber.consume_messages(self.write)
def stop(self):
"""
Unsubscribe and close file
:return:
"""
self.subscriber.disconnect()
self.file.close_file()
def write(self, ch, method, properties, body):
buffer_content = json.loads(body)
for record in buffer_content:
self.csv_writer.writerow([record[column_name] for column_name in self.headers])
