def publisher(queue, event, port):
""" Simple method that starts a publisher on the port 5555.
:param multiprocessing.Queue queue: Queue of messages to be broadcasted
:param multiprocessing.Event event: Event to stop the publisher
:param int port: port in which to broadcast data
.. TODO:: The publisher's port should be determined in a configuration file.
"""
logger = get_logger(name=__name__)
port_pub = port
context = zmq.Context()
socket = context.socket(zmq.PUB)
socket.bind("tcp://*:%s" % port_pub)
sleep(1) # It takes a time for subscribers to propagate to the publisher.
# Without this sleep the first packages may be lost
logger.info('Bound socket on {}'.format(port_pub))
while not event.is_set():
while not queue.empty():
data = queue.get(
) # Should be a dictionary {'topic': topic, 'data': data}
logger.debug('Sending {} on {}'.format(data['data'],
data['topic']))
socket.send_string(data['topic'], zmq.SNDMORE)
socket.send_pyobj(data['data'])
if general_stop_event.is_set():
break
sleep(0.05) # Sleeps 5 milliseconds to be polite with the CPU
sleep(1) # Gives enough time to the subscribers to update their status
socket.close()
logger.info('Stopped the publisher')
def accumulate_links(self):
self._accumulate_links_event.clear()
socket = subscribe(self.publisher.port, 'particle_links')
while not self._accumulate_links_event.is_set():
if general_stop_event.is_set():
break
topic = socket.recv_string()
data = socket.recv_pyobj()
if self.locations.shape[0] == 0:
self.locations = data[0]
else:
self.locations = self.locations.append(data[0])
def accumulate_links(self):
""" Asynchronous method to store the links in this class. It looked like a good idea to keep this information in
a single location, regardless of whether another process is listening on the topic. This in principle can be
used to analyse data retrospectively.
.. todo:: Still needs to clear the memory after several calls. Need to fit better in the architecture of the
program
"""
self._accumulate_links_event.clear()
socket = subscribe(self.publisher.port, 'particle_links')
while not self._accumulate_links_event.is_set():
if general_stop_event.is_set():
break
topic = socket.recv_string()
data = socket.recv_pyobj()
if self.locations.shape[0] == 0:
self.locations = data[0]
else:
self.locations = self.locations.append(data[0])
def calculate_histogram(self):
self.calculating_histograms = True
locations = self.locations.copy()
t1 = tp.filter_stubs(locations, self.config['process']['min_traj_length'])
# t2 = t1[((t1['mass'] > self.config['process']['min_mass']) & (t1['size'] < self.config['process']['max_size']) &
# (t1['ecc'] < self.config['process']['max_ecc']))]
im = tp.imsd(t1, self.config['process']['um_pixel'], self.config['process']['fps'])
self.histogram_values = []
for pcle in im:
if general_stop_event.is_set():
break
data = im[pcle]
t = data.index[~np.isnan(data.values)]
val = data.values[~np.isnan(data.values)]
try:
slope, intercept, r, p, stderr = stats.linregress(np.log(t), np.log(val))
self.histogram_values.append([slope, intercept])
except:
pass
self.calculating_histograms = False
self.publisher.publish('histogram', self.histogram_values)
def calculate_histogram(self):
""" Starts a new thread to calculate the histogram of fit-parameters based on the mean-squared displacement of
individual particles. It publishes the data on topic `histogram`.
.. warning:: This method is incredibly expensive. Since it runs on a thread it can block other pieces of code,
especially the GUI, which runs on the same process.
.. TODO:: The histogram loops over all the particles. It would be better to skeep particles for which there is
no new data
.. TODO:: Make this method able to run on a separate process. So far is not possible because it relies on data
stored on the class itself (`self.locations`).
"""
self.calculating_histograms = True
locations = self.locations.copy()
t1 = tp.filter_stubs(locations,
self.config['process']['min_traj_length'])
t2 = t1[((t1['mass'] > self.config['process']['min_mass']) &
(t1['size'] < self.config['process']['max_size']) &
(t1['ecc'] < self.config['process']['max_ecc']))]
im = tp.imsd(t2, self.config['process']['um_pixel'],
self.config['process']['fps'])
self.histogram_values = []
for pcle in im:
if general_stop_event.is_set():
break
data = im[pcle]
t = data.index[~np.isnan(data.values)]
val = data.values[~np.isnan(data.values)]
try:
slope, intercept, r, p, stderr = stats.linregress(
np.log(t), np.log(val))
self.histogram_values.append([slope, intercept])
except:
pass
self.calculating_histograms = False
self.publisher.publish('histogram', self.histogram_values)