def __init__(self, stream=None, event_close=None, log_lvl=logging.WARNING):
plt.rcParams['toolbar'] = 'None'
plt.ioff()
self.plot_config = PlotNordicConfig
self.draw_state = DrawState(
self.plot_config['timeline_width_init'],
self.plot_config['event_processing_rect_height'],
self.plot_config['event_submit_markersize'])
self.ani = None
self.close_event_flag = False
self.processed_events = ProcessedEvents()
if stream is not None:
timeouts = {
'descriptions': 1,
'events': 0
}
self.in_stream = stream
self.in_stream.set_timeouts(timeouts)
if event_close is not None:
self.event_close = event_close
self.logger = logging.getLogger('Plot Nordic')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def __init__(self, events_filename, events_types_filename, log_lvl):
self.data_name = events_filename.split('.')[0]
self.processed_data = ProcessedEvents()
self.processed_data.read_data_from_files(events_filename, events_types_filename)
self.logger = logging.getLogger('Stats Nordic')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def __init__(self,
own_recv_socket_dict,
own_send_socket_dict=None,
remote_socket_dict=None,
config=RttNordicConfig,
event_filename=None,
event_types_filename=None,
log_lvl=logging.INFO):
self.config = config
self.event_filename = event_filename
self.event_types_filename = event_types_filename
self.csvfile = None
timeouts = {'descriptions': None, 'events': None}
self.in_stream = Stream(own_recv_socket_dict, timeouts)
if own_send_socket_dict is not None and remote_socket_dict is not None:
self.sending = True
self.out_stream = Stream(own_send_socket_dict,
timeouts,
remote_socket_dict=remote_socket_dict)
else:
self.sending = False
self.timestamp_overflows = 0
self.after_half = False
self.processed_events = ProcessedEvents()
self.temp_events = []
self.submitted_event_type = None
self.raw_data = EventsData([], {})
self.event_processing_start_id = None
self.event_processing_end_id = None
self.submit_event = None
self.start_event = None
self.bufs = list()
self.bcnt = 0
self.logger = logging.getLogger('Profiler model creator')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def __init__(self, stream,
event_close,
sending_events=False,
config=RttNordicConfig,
event_filename=None,
event_types_filename=None,
log_lvl=logging.INFO):
self.config = config
self.event_filename = event_filename
self.event_types_filename = event_types_filename
self.csvfile = None
self.event_close = event_close
timeouts = {
'descriptions': 1,
'events': 1
}
self.stream = stream
self.stream.set_timeouts(timeouts)
self.sending = sending_events
self.timestamp_overflows = 0
self.after_half = False
self.processed_events = ProcessedEvents()
self.temp_events = []
self.submitted_event_type = None
self.raw_data = EventsData([], {})
self.event_processing_start_id = None
self.event_processing_end_id = None
self.submit_event = None
self.start_event = None
self.bufs = list()
self.bcnt = 0
self.logger = logging.getLogger('Profiler model creator')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter('[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def __init__(self, log_lvl=logging.WARNING):
plt.rcParams['toolbar'] = 'None'
plt.ioff()
self.plot_config = PlotNordicConfig
self.draw_state = DrawState(
self.plot_config['timeline_width_init'],
self.plot_config['event_processing_rect_height'],
self.plot_config['event_submit_markersize'])
self.processed_events = ProcessedEvents()
self.submitted_event_type = None
self.temp_events = []
self.logger = logging.getLogger('RTT Plot Nordic')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
class ModelCreator:
def __init__(self,
own_recv_socket_dict,
own_send_socket_dict=None,
remote_socket_dict=None,
config=RttNordicConfig,
event_filename=None,
event_types_filename=None,
log_lvl=logging.INFO):
self.config = config
self.event_filename = event_filename
self.event_types_filename = event_types_filename
self.csvfile = None
timeouts = {'descriptions': None, 'events': None}
self.in_stream = Stream(own_recv_socket_dict, timeouts)
if own_send_socket_dict is not None and remote_socket_dict is not None:
self.sending = True
self.out_stream = Stream(own_send_socket_dict,
timeouts,
remote_socket_dict=remote_socket_dict)
else:
self.sending = False
self.timestamp_overflows = 0
self.after_half = False
self.processed_events = ProcessedEvents()
self.temp_events = []
self.submitted_event_type = None
self.raw_data = EventsData([], {})
self.event_processing_start_id = None
self.event_processing_end_id = None
self.submit_event = None
self.start_event = None
self.bufs = list()
self.bcnt = 0
self.logger = logging.getLogger('Profiler model creator')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def shutdown(self):
if self.csvfile is not None:
self.processed_events.finish_writing_data_to_files(
self.csvfile, self.event_filename, self.event_types_filename)
def _get_buffered_data(self, num_bytes):
buf = bytearray()
while len(buf) < num_bytes:
tbuf = self.bufs[0]
size = num_bytes - len(buf)
if len(tbuf) <= size:
buf.extend(tbuf)
del self.bufs[0]
else:
buf.extend(tbuf[0:size])
self.bufs[0] = tbuf[size:]
self.bcnt -= num_bytes
return buf
def _read_bytes(self, num_bytes):
while True:
if self.bcnt >= num_bytes:
break
try:
buf = self.in_stream.recv_ev()
except StreamError as err:
self.logger.error("Receiving error: {}".format(err))
self.close()
if len(buf) > 0:
self.bufs.append(buf)
self.bcnt += len(buf)
return self._get_buffered_data(num_bytes)
def _timestamp_from_ticks(self, clock_ticks):
ts_ticks_aggregated = self.timestamp_overflows * self.config[
'timestamp_raw_max']
ts_ticks_aggregated += clock_ticks
ts_s = ts_ticks_aggregated * self.config['ms_per_timestamp_tick'] / 1000
return ts_s
def transmit_all_events_descriptions(self):
try:
bytes = self.in_stream.recv_desc()
except StreamError as err:
self.logger.error("Receiving error: {}. Exiting".format(err))
sys.exit()
desc_buf = bytes.decode()
f = StringIO(desc_buf)
reader = csv.reader(f, delimiter=',')
for row in reader:
# Empty field is send after last event description
if len(row) == 0:
break
name = row[0]
id = int(row[1])
data_type = row[2:len(row) // 2 + 1]
data = row[len(row) // 2 + 1:]
self.raw_data.registered_events_types[id] = EventType(
name, data_type, data)
if name not in ('event_processing_start', 'event_processing_end'):
self.processed_events.registered_events_types[id] = EventType(
name, data_type, data)
self.event_processing_start_id = \
self.raw_data.get_event_type_id('event_processing_start')
self.event_processing_end_id = \
self.raw_data.get_event_type_id('event_processing_end')
if self.sending:
event_types_dict = dict(
(k, v.serialize()) for k, v in
self.processed_events.registered_events_types.items())
json_et_string = json.dumps(event_types_dict)
try:
self.out_stream.send_desc(json_et_string.encode())
except StreamError as err:
self.logger.error("Error: {}. Unable to send data".format(err))
sys.exit()
def _read_single_event(self):
id = int.from_bytes(self._read_bytes(1),
byteorder=self.config['byteorder'],
signed=False)
et = self.raw_data.registered_events_types[id]
buf = self._read_bytes(4)
timestamp_raw = (int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=False))
if self.after_half \
and timestamp_raw < 0.4 * self.config['timestamp_raw_max']:
self.timestamp_overflows += 1
self.after_half = False
if timestamp_raw > 0.6 * self.config['timestamp_raw_max']:
self.after_half = True
timestamp = self._timestamp_from_ticks(timestamp_raw)
def process_int32(self, data):
buf = self._read_bytes(4)
data.append(
int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=True))
def process_uint32(self, data):
buf = self._read_bytes(4)
data.append(
int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=False))
def process_int16(self, data):
buf = self._read_bytes(2)
data.append(
int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=True))
def process_uint16(self, data):
buf = self._read_bytes(2)
data.append(
int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=False))
def process_int8(self, data):
buf = self._read_bytes(1)
data.append(
int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=True))
def process_uint8(self, data):
buf = self._read_bytes(1)
data.append(
int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=False))
def process_string(self, data):
buf = self._read_bytes(1)
buf = self._read_bytes(
int.from_bytes(buf,
byteorder=self.config['byteorder'],
signed=False))
data.append(buf.decode())
READ_BYTES = {
"u8": process_uint8,
"s8": process_int8,
"u16": process_uint16,
"s16": process_int16,
"u32": process_uint32,
"s32": process_int32,
"s": process_string,
"t": process_uint32
}
data = []
for event_data_type in et.data_types:
READ_BYTES[event_data_type](self, data)
return Event(id, timestamp, data)
def _send_event(self, tracked_event):
event_string = tracked_event.serialize()
try:
self.out_stream.send_ev(event_string.encode())
except StreamError as err:
if err.args[1] != 'closed':
self.logger.error("Error. Unable to send data: {}".format(err))
# Receiver has been closed
self.close()
def _write_event_to_file(self, csvfile, tracked_event):
try:
csvfile.write(tracked_event.serialize() + '\r\n')
except IOError:
self.logger.error("Problem with accessing csv file")
self.close()
def transmit_events(self):
if self.event_filename and self.event_types_filename:
self.csvfile = self.processed_events.init_writing_data_to_files(
self.event_filename, self.event_types_filename)
while True:
event = self._read_single_event()
if event.type_id == self.event_processing_start_id:
self.start_event = event
for i in range(len(self.temp_events) - 1, -1, -1):
# comparing memory addresses of event processing start
# and event submit to identify matching events
if self.temp_events[i].data[0] == self.start_event.data[0]:
self.submit_event = self.temp_events[i]
self.submitted_event_type = self.submit_event.type_id
del self.temp_events[i]
break
elif event.type_id == self.event_processing_end_id:
# comparing memory addresses of event processing start and
# end to identify matching events
if self.submitted_event_type is not None and event.data[0] \
== self.start_event.data[0]:
tracked_event = TrackedEvent(self.submit_event,
self.start_event.timestamp,
event.timestamp)
if self.csvfile is not None:
self._write_event_to_file(self.csvfile, tracked_event)
if self.sending:
self._send_event(tracked_event)
self.submitted_event_type = None
elif not self.processed_events.is_event_tracked(event.type_id):
tracked_event = TrackedEvent(event, None, None)
if self.csvfile is not None:
self._write_event_to_file(self.csvfile, tracked_event)
if self.sending:
self._send_event(tracked_event)
else:
self.temp_events.append(event)
def start(self):
self.transmit_all_events_descriptions()
self.transmit_events()
def close(self):
self.logger.info("Real time transmission closed")
self.shutdown()
self.logger.info("Events data saved to files")
sys.exit()
class StatsNordic():
def __init__(self, events_filename, events_types_filename, log_lvl):
self.data_name = events_filename.split('.')[0]
self.processed_data = ProcessedEvents()
self.processed_data.raw_data.read_data_from_files(
events_filename, events_types_filename)
self.processed_data.match_event_processing()
self.logger = logging.getLogger('Stats Nordic')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def calculate_stats_preset1(self):
self.time_between_events("hid_report_sent_event", EventState.PROC_END,
"motion_event", EventState.SUBMIT, 4000)
self.time_between_events("motion_event", EventState.SUBMIT,
"hid_report_sent_event", EventState.PROC_END,
4000)
plt.show()
def _get_timestamps(self, event_name, event_state):
event_type_id = self.processed_data.raw_data.get_event_type_id(
event_name)
if event_type_id == None:
self.logger.error("Event name not found: " + event_name)
return None
trackings = list(
filter(lambda x: x.submit.type_id == event_type_id,
self.processed_data.tracked_events))
if type(event_state) is not EventState:
self.logger.error("Event state should be EventState enum")
return None
if event_state == EventState.SUBMIT:
timestamps = list(map(lambda x: x.submit.timestamp, trackings))
if event_state == EventState.PROC_START:
timestamps = list(map(lambda x: x.proc_start_time, trackings))
if event_state == EventState.PROC_END:
timestamps = list(map(lambda x: x.proc_end_time, trackings))
return timestamps
def time_between_events(self, start_event_name, start_event_state,
end_event_name, end_event_state, hist_bin_cnt):
if not self.processed_data.tracking_execution:
if start_event_state != EventState.SUBMIT or \
end_event_state != EventState.SUBMIT:
self.logger.error("Events processing is not tracked: " + \
start_event_name + "->" + end_event_name)
return
start_times = self._get_timestamps(start_event_name, start_event_state)
end_times = self._get_timestamps(end_event_name, end_event_state)
if start_times is None or end_times is None:
return
times_between = []
for start in start_times:
for end in end_times:
if start < end:
#converting times to ms - multiply by 1000
times_between.append((end - start) * 1000)
break
plt.figure()
stats_text = "Max time: "
stats_text += "{0:.3f}".format(max(times_between)) + "ms\n"
stats_text += "Min time: "
stats_text += "{0:.3f}".format(min(times_between)) + "ms\n"
stats_text += "Mean time: "
stats_text += "{0:.3f}".format(np.mean(times_between)) + "ms\n"
ax = plt.gca()
stats_textbox = ax.text(0.05,
0.95,
stats_text,
transform=ax.transAxes,
fontsize=12,
verticalalignment='top',
bbox=dict(boxstyle='round',
alpha=0.5,
facecolor='linen'))
plt.xlabel('Duration[ms]')
plt.ylabel('Number of occurences')
event_status_str = {
EventState.SUBMIT: "submission",
EventState.PROC_START: "processing start",
EventState.PROC_END: "processing end"
}
title = "From " + start_event_name + ' ' + \
event_status_str[start_event_state] + "\nto " + \
end_event_name + ' ' + event_status_str[end_event_state] + \
' (' + self.data_name + ')'
plt.title(title)
plt.hist(times_between, bins=hist_bin_cnt)
plt.yscale('log')
plt.grid(True)
class StatsNordic():
def __init__(self, events_filename, events_types_filename, log_lvl):
self.data_name = events_filename.split('.')[0]
self.processed_data = ProcessedEvents()
self.processed_data.raw_data.read_data_from_files(
events_filename, events_types_filename)
self.processed_data.match_event_processing()
self.logger = logging.getLogger('Stats Nordic')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def calculate_stats_preset1(self, start_meas, end_meas):
self.time_between_events("hid_mouse_event_dongle", EventState.SUBMIT,
"hid_report_sent_event_device",
EventState.SUBMIT, 0.05, start_meas, end_meas)
self.time_between_events("hid_mouse_event_dongle", EventState.SUBMIT,
"hid_report_sent_event_device",
EventState.SUBMIT, 0.05, start_meas, end_meas)
self.time_between_events("hid_report_sent_event_dongle",
EventState.SUBMIT,
"hid_report_sent_event_dongle",
EventState.SUBMIT, 0.05, start_meas, end_meas)
self.time_between_events("hid_mouse_event_dongle", EventState.SUBMIT,
"hid_report_sent_event_dongle",
EventState.SUBMIT, 0.05, start_meas, end_meas)
self.time_between_events("hid_mouse_event_device", EventState.SUBMIT,
"hid_mouse_event_dongle", EventState.SUBMIT,
0.05, start_meas, end_meas)
plt.show()
def _get_timestamps(self, event_name, event_state, start_meas, end_meas):
event_type_id = self.processed_data.raw_data.get_event_type_id(
event_name)
if event_type_id == None:
self.logger.error("Event name not found: " + event_name)
return None
trackings = list(
filter(lambda x: x.submit.type_id == event_type_id,
self.processed_data.tracked_events))
if type(event_state) is not EventState:
self.logger.error("Event state should be EventState enum")
return None
if event_state == EventState.SUBMIT:
timestamps = np.fromiter(map(lambda x: x.submit.timestamp,
trackings),
dtype=np.float)
elif event_state == EventState.PROC_START:
timestamps = np.fromiter(map(lambda x: x.proc_start_time,
trackings),
dtype=np.float)
elif event_state == EventState.PROC_END:
timestamps = np.fromiter(map(lambda x: x.proc_end_time, trackings),
dtype=np.float)
timestamps = timestamps[np.where((timestamps > start_meas)
& (timestamps < end_meas))]
return timestamps
def calculate_times_between(self, start_times, end_times):
if end_times[0] <= start_times[0]:
end_times = end_times[1:]
if len(start_times) > len(end_times):
start_times = start_times[:-1]
return (end_times - start_times) * 1000
def prepare_stats_txt(self, times_between):
stats_text = "Max time: "
stats_text += "{0:.3f}".format(max(times_between)) + "ms\n"
stats_text += "Min time: "
stats_text += "{0:.3f}".format(min(times_between)) + "ms\n"
stats_text += "Mean time: "
stats_text += "{0:.3f}".format(np.mean(times_between)) + "ms\n"
stats_text += "Std dev of time: "
stats_text += "{0:.3f}".format(np.std(times_between)) + "ms\n"
stats_text += "Median time: "
stats_text += "{0:.3f}".format(np.median(times_between)) + "ms\n"
stats_text += "Number of records: {}".format(len(times_between)) + "\n"
return stats_text
def time_between_events(self,
start_event_name,
start_event_state,
end_event_name,
end_event_state,
hist_bin_width=0.01,
start_meas=0,
end_meas=float('inf')):
self.logger.info("Stats calculating: {}->{}".format(
start_event_name, end_event_name))
if not self.processed_data.tracking_execution:
if start_event_state != EventState.SUBMIT or \
end_event_state != EventState.SUBMIT:
self.logger.error("Events processing is not tracked: " + \
start_event_name + "->" + end_event_name)
return
start_times = self._get_timestamps(start_event_name, start_event_state,
start_meas, end_meas)
end_times = self._get_timestamps(end_event_name, end_event_state,
start_meas, end_meas)
if start_times is None or end_times is None:
return
if len(start_times) == 0:
self.logger.error("No events logged: " + start_event_name)
return
if len(end_times) == 0:
self.logger.error("No events logged: " + stop_event_name)
return
if len(start_times) != len(end_times):
self.logger.error(
"Number of start_times and end_times is not equal")
self.logger.error("Got {} start_times and {} end_times".format(
len(start_times), len(end_times)))
return
times_between = self.calculate_times_between(start_times, end_times)
stats_text = self.prepare_stats_txt(times_between)
plt.figure()
ax = plt.gca()
stats_textbox = ax.text(0.05,
0.95,
stats_text,
transform=ax.transAxes,
fontsize=12,
verticalalignment='top',
bbox=dict(boxstyle='round',
alpha=0.5,
facecolor='linen'))
plt.xlabel('Duration[ms]')
plt.ylabel('Number of occurrences')
event_status_str = {
EventState.SUBMIT: "submission",
EventState.PROC_START: "processing start",
EventState.PROC_END: "processing end"
}
title = "From " + start_event_name + ' ' + \
event_status_str[start_event_state] + "\nto " + \
end_event_name + ' ' + event_status_str[end_event_state] + \
' (' + self.data_name + ')'
plt.title(title)
plt.hist(times_between,
bins=(int)((max(times_between) - min(times_between)) /
hist_bin_width))
plt.yscale('log')
plt.grid(True)
dir_name = "{}{}_{}_{}/".format(OUTPUT_FOLDER, self.data_name,
int(start_meas), int(end_meas))
if not os.path.exists(dir_name):
os.makedirs(dir_name)
plt.savefig(dir_name +
title.lower().replace(' ', '_').replace('\n', '_') +
'.png')
def main():
descr = "Merge data from Peripheral and Central. Synchronization events" \
" should be registered at the beginning and at the end of" \
" measurements (used to compensate clock drift)."
parser = argparse.ArgumentParser(description=descr)
parser.add_argument("peripheral_dataset", help="Name of Peripheral dataset")
parser.add_argument("peripheral_sync_event",
help="Event used for synchronization - Peripheral")
parser.add_argument("central_dataset", help="Name of Central dataset")
parser.add_argument("central_sync_event",
help="Event used for synchronization - Central")
parser.add_argument("result_dataset", help="Name for result dataset")
args = parser.parse_args()
evt_peripheral = ProcessedEvents()
evt_peripheral.read_data_from_files(args.peripheral_dataset + ".csv",
args.peripheral_dataset + ".json")
evt_central = ProcessedEvents()
evt_central.read_data_from_files(args.central_dataset + ".csv",
args.central_dataset + ".json")
# Compensating clock drift - based on synchronization events
sync_evt_peripheral = evt_peripheral.get_event_type_id(args.peripheral_sync_event)
sync_evt_central = evt_central.get_event_type_id(args.central_sync_event)
sync_peripheral = list(filter(lambda x: x.submit.type_id == sync_evt_peripheral,
evt_peripheral.tracked_events))
sync_central = list(filter(lambda x: x.submit.type_id == sync_evt_central,
evt_central.tracked_events))
ts_peripheral = np.array(list(map(lambda x: list([x.submit.timestamp, x.proc_start_time, x.proc_end_time]),
evt_peripheral.tracked_events)))
sync_ts_peripheral = list(map(lambda x: x.submit.timestamp, sync_peripheral))
sync_ts_central = list(map(lambda x: x.submit.timestamp, sync_central))
sync_diffs_central = np.subtract(sync_ts_central[1:], sync_ts_central[:-1])
sync_diffs_peripheral = np.subtract(sync_ts_peripheral[1:], sync_ts_peripheral[:-1])
rounded_diffs_central = list(map(lambda x: round(x, 1), sync_diffs_central))
rounded_diffs_peripheral = list(map(lambda x: round(x, 1), sync_diffs_peripheral))
shift_c = rounded_diffs_central.index(rounded_diffs_peripheral[0])
shift_p = rounded_diffs_peripheral.index(rounded_diffs_central[0])
if shift_c < shift_p:
sync_ts_central = sync_ts_central[shift_c:]
elif shift_p < shift_c:
sync_ts_peripheral = sync_ts_peripheral[shift_p:]
if len(sync_ts_central) < len(sync_ts_peripheral):
sync_ts_peripheral = sync_ts_peripheral[:len(sync_ts_central)]
elif len(sync_ts_peripheral) < len(sync_ts_central):
sync_ts_central = sync_ts_central[:len(sync_ts_peripheral)]
new_ts_peripheral = ts_peripheral.copy()
new_ts_peripheral[list(list(elem is not None for elem in row) for row in new_ts_peripheral)] = \
sync_peripheral_ts(ts_peripheral, sync_ts_peripheral, sync_ts_central)
assert len(new_ts_peripheral) == len(ts_peripheral)
# Reindexing, renaming and compensating time differences for peripheral events
max_central_id = max([int(i) for i in evt_central.registered_events_types])
assert len(new_ts_peripheral) == len(evt_peripheral.tracked_events)
evt_peripheral.tracked_events = list(map(lambda x, y:
TrackedEvent(Event(x.submit.type_id + max_central_id + 1, y[0], x.submit.data),
y[1],
y[2]),
evt_peripheral.tracked_events, new_ts_peripheral))
evt_peripheral.registered_events_types = {k + max_central_id + 1 :
EventType(v.name + "_peripheral", v.data_types, v.data_descriptions)
for k, v in evt_peripheral.registered_events_types.items()}
evt_central.registered_events_types = {
k : EventType(v.name + "_central",
v.data_types, v.data_descriptions)
for k, v in evt_central.registered_events_types.items()}
# Filter out events that are out of synchronization period
TIME_DIFF = 0.5
start_time = sync_ts_central[0] - TIME_DIFF
end_time = sync_ts_central[-1] + TIME_DIFF
evt_peripheral.tracked_events = list(filter(lambda x:
x.submit.timestamp >= start_time and (x.proc_end_time <= end_time if x.proc_end_time is not None \
else x.submit.timestamp <= end_time),
evt_peripheral.tracked_events))
evt_central.tracked_events = list(filter(lambda x:
x.submit.timestamp >= start_time and (x.proc_end_time <= end_time if x.proc_end_time is not None \
else x.submit.timestamp <= end_time),
evt_central.tracked_events))
# Filter out events that were out of interpolation range
evt_peripheral.tracked_events = list(filter(lambda x:
INTERP_OUT_OF_RANGE_VAL not in (x.submit.timestamp, x.proc_start_time, x.proc_end_time),
evt_peripheral.tracked_events))
all_registered_events_types = evt_peripheral.registered_events_types.copy()
all_registered_events_types.update(evt_central.registered_events_types)
result_events = ProcessedEvents()
result_events.tracked_events = evt_peripheral.tracked_events + evt_central.tracked_events
result_events.registered_events_types = all_registered_events_types
result_events.write_data_to_files(args.result_dataset + ".csv",
args.result_dataset + ".json")
print('Profiler data merged successfully')
class PlotNordic():
def __init__(self, log_lvl=logging.WARNING):
plt.rcParams['toolbar'] = 'None'
plt.ioff()
self.plot_config = PlotNordicConfig
self.draw_state = DrawState(
self.plot_config['timeline_width_init'],
self.plot_config['event_processing_rect_height'],
self.plot_config['event_submit_markersize'])
self.processed_events = ProcessedEvents()
self.finish_event = None
self.submitted_event_type = None
self.temp_events = []
self.logger = logging.getLogger('RTT Plot Nordic')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def read_data_from_files(self, events_filename, events_types_filename):
self.processed_events.raw_data.read_data_from_files(
events_filename, events_types_filename)
if not self.processed_events.raw_data.verify():
self.logger.warning("Missing event descriptions")
def write_data_to_files(self, events_filename, events_types_filename):
self.processed_events.raw_data.write_data_to_files(
events_filename, events_types_filename)
def on_click_start_stop(self, event):
if self.draw_state.paused:
if self.draw_state.l_line is not None:
self.draw_state.l_line.remove()
self.draw_state.l_line = None
self.draw_state.l_line_coord = None
if self.draw_state.r_line is not None:
self.draw_state.r_line.remove()
self.draw_state.r_line = None
self.draw_state.r_line_coord = None
if self.draw_state.duration_marker is not None:
self.draw_state.duration_marker.remove()
self.draw_state.paused = not self.draw_state.paused
def _prepare_plot(self, selected_events_types):
self.draw_state.ax = plt.gca()
self.draw_state.ax.set_navigate(False)
fig = plt.gcf()
fig.set_size_inches(self.plot_config['window_width_inch'],
self.plot_config['window_height_inch'],
forward=True)
fig.canvas.draw()
plt.xlabel("Time [s]")
plt.title("Custom events")
plt.grid(True)
minimum = selected_events_types[0]
maximum = selected_events_types[0]
ticks = []
labels = []
for j in selected_events_types:
if j not in (self.processed_events.event_processing_start_id,
self.processed_events.event_processing_end_id):
if j > maximum:
maximum = j
if j < minimum:
minimum = j
ticks.append(j)
labels.append(self.processed_events.raw_data.
registered_events_types[j].name)
plt.yticks(ticks, labels)
# min and max range of y axis are bigger by one so markers fit nicely
# on plot
self.draw_state.y_max = maximum + 1
self.draw_state.y_height = maximum - minimum + 2
plt.ylim([minimum - 1, maximum + 1])
self.draw_state.selected_event_textbox = self.draw_state.ax.text(
0.05,
0.95,
self.draw_state.selected_event_text,
fontsize=10,
transform=self.draw_state.ax.transAxes,
verticalalignment='top',
bbox=dict(boxstyle='round', alpha=0.5, facecolor='linen'))
self.draw_state.selected_event_textbox.set_visible(False)
fig.canvas.mpl_connect('scroll_event', self.scroll_event)
fig.canvas.mpl_connect('button_press_event', self.button_press_event)
fig.canvas.mpl_connect('button_release_event',
self.button_release_event)
fig.canvas.mpl_connect('resize_event', PlotNordic.resize_event)
fig.canvas.mpl_connect('close_event', self.close_event)
plt.tight_layout()
return fig
def _get_relative_coords(self, event):
# relative position of plot - x0, y0, width, height
ax_loc = self.draw_state.ax.get_position().bounds
window_size = plt.gcf().get_size_inches() * \
plt.gcf().dpi # window size - width, height
x_rel = (event.x - ax_loc[0] * window_size[0]) \
/ ax_loc[2] / window_size[0]
y_rel = (event.y - ax_loc[1] * window_size[1]) \
/ ax_loc[3] / window_size[1]
return x_rel, y_rel
def scroll_event(self, event):
x_rel, _ = self._get_relative_coords(event)
if event.button == 'up':
if self.draw_state.paused:
self.draw_state.timeline_max = self.draw_state.timeline_max - (1 - x_rel) * \
(self.draw_state.timeline_width - self.draw_state.timeline_width *
self.plot_config['timeline_scale_factor'])
self.draw_state.timeline_width = self.draw_state.timeline_width * \
self.plot_config['timeline_scale_factor']
if event.button == 'down':
if self.draw_state.paused:
self.draw_state.timeline_max = self.draw_state.timeline_max + (1 - x_rel) * \
(self.draw_state.timeline_width / self.plot_config['timeline_scale_factor'] -
self.draw_state.timeline_width)
self.draw_state.timeline_width = self.draw_state.timeline_width / \
self.plot_config['timeline_scale_factor']
self.draw_state.ax.set_xlim(
self.draw_state.timeline_max - self.draw_state.timeline_width,
self.draw_state.timeline_max)
plt.draw()
def _find_closest_event(self, x_coord, y_coord):
if self.processed_events.tracking_execution:
filtered_id = list(
filter(lambda x: x.submit.type_id == round(y_coord),
self.processed_events.tracked_events))
if len(filtered_id) == 0:
return None
matching_processing = list(
filter(lambda x: x.proc_start_time < x_coord < x.proc_end_time,
filtered_id))
if matching_processing:
return matching_processing[0]
dists = list(
map(
lambda x: min([
abs(x.submit.timestamp - x_coord),
abs(x.proc_start_time - x_coord),
abs(x.proc_end_time - x_coord)
]), filtered_id))
return filtered_id[np.argmin(dists)]
else:
filtered_id = list(
filter(lambda x: x.type_id == round(y_coord),
self.processed_events.raw_data.events))
if len(filtered_id) == 0:
return None
dists = list(map(lambda x: abs(x.timestamp - x_coord),
filtered_id))
return filtered_id[np.argmin(dists)]
@staticmethod
def _stringify_time(time_seconds):
if time_seconds > 0.1:
return '%.5f' % (time_seconds) + ' s'
return '%.5f' % (1000 * time_seconds) + ' ms'
def button_press_event(self, event):
x_rel, y_rel = self._get_relative_coords(event)
if event.button == MouseButton.LEFT.value:
self.draw_state.pan_x_start1 = x_rel
if event.button == MouseButton.MIDDLE.value:
if self.draw_state.selected_event_submit is not None:
for i in self.draw_state.selected_event_submit:
i.remove()
self.draw_state.selected_event_submit = None
if self.draw_state.selected_event_processing is not None:
self.draw_state.selected_event_processing.remove()
self.draw_state.selected_event_processing = None
self.draw_state.selected_event_textbox.set_visible(False)
if x_rel > 1 or x_rel < 0 or y_rel > 1 or y_rel < 0:
plt.draw()
return
coord_x = self.draw_state.timeline_max - \
(1 - x_rel) * self.draw_state.timeline_width
coord_y = self.draw_state.y_max - \
(1 - y_rel) * self.draw_state.y_height
selected_event = self._find_closest_event(coord_x, coord_y)
if selected_event is None:
return
if self.processed_events.tracking_execution:
event_submit = selected_event.submit
else:
event_submit = selected_event
self.draw_state.selected_event_submit = self.draw_state.ax.plot(
event_submit.timestamp,
event_submit.type_id,
markersize=2 * self.draw_state.event_submit_markersize,
color='g',
marker='o',
linestyle=' ')
if self.processed_events.tracking_execution:
self.draw_state.selected_event_processing = matplotlib.patches.Rectangle(
(selected_event.proc_start_time,
selected_event.submit.type_id -
self.draw_state.event_processing_rect_height),
selected_event.proc_end_time -
selected_event.proc_start_time,
2 * self.draw_state.event_processing_rect_height,
color='g')
self.draw_state.ax.add_artist(
self.draw_state.selected_event_processing)
self.draw_state.selected_event_text = \
self.processed_events.raw_data.registered_events_types[event_submit.type_id].name + '\n'
self.draw_state.selected_event_text += 'Submit: ' + \
PlotNordic._stringify_time(event_submit.timestamp) + '\n'
if self.processed_events.tracking_execution:
self.draw_state.selected_event_text += 'Processing start: ' + \
PlotNordic._stringify_time(
selected_event.proc_start_time) + '\n'
self.draw_state.selected_event_text += 'Processing end: ' + \
PlotNordic._stringify_time(
selected_event.proc_end_time) + '\n'
self.draw_state.selected_event_text += 'Processing time: ' + \
PlotNordic._stringify_time(selected_event.proc_end_time - \
selected_event.proc_start_time) + '\n'
ev_type = self.processed_events.raw_data.registered_events_types[
event_submit.type_id]
for i in range(0, len(ev_type.data_descriptions)):
if ev_type.data_descriptions[i] == 'mem_address':
continue
self.draw_state.selected_event_text += ev_type.data_descriptions[
i] + ' = '
self.draw_state.selected_event_text += str(
event_submit.data[i]) + '\n'
self.draw_state.selected_event_textbox.set_visible(True)
self.draw_state.selected_event_textbox.set_text(
self.draw_state.selected_event_text)
plt.draw()
if event.button == MouseButton.RIGHT.value:
self.draw_state.pan_x_start2 = x_rel
def button_release_event(self, event):
x_rel, y_rel = self._get_relative_coords(event)
if event.button == MouseButton.LEFT.value:
if self.draw_state.paused:
if abs(x_rel - self.draw_state.pan_x_start1) < 0.01:
if self.draw_state.l_line is not None:
self.draw_state.l_line.remove()
self.draw_state.l_line = None
self.draw_state.l_line_coord = None
if 0 <= x_rel <= 1:
if 0 <= y_rel <= 1:
self.draw_state.l_line_coord = self.draw_state.timeline_max - \
(1 - x_rel) * self.draw_state.timeline_width
self.draw_state.l_line = plt.axvline(
self.draw_state.l_line_coord)
plt.draw()
else:
self.draw_state.timeline_max = self.draw_state.timeline_max - \
(x_rel - self.draw_state.pan_x_start1) * \
self.draw_state.timeline_width
self.draw_state.ax.set_xlim(
self.draw_state.timeline_max -
self.draw_state.timeline_width,
self.draw_state.timeline_max)
plt.draw()
if event.button == MouseButton.RIGHT.value:
if self.draw_state.paused:
if abs(x_rel - self.draw_state.pan_x_start2) < 0.01:
if self.draw_state.r_line is not None:
self.draw_state.r_line.remove()
self.draw_state.r_line = None
self.draw_state.r_line_coord = None
if 0 <= x_rel <= 1:
if 0 <= y_rel <= 1:
self.draw_state.r_line_coord = self.draw_state.timeline_max - \
(1 - x_rel) * self.draw_state.timeline_width
self.draw_state.r_line = plt.axvline(
self.draw_state.r_line_coord, color='r')
plt.draw()
if self.draw_state.r_line_coord is not None and self.draw_state.l_line_coord is not None:
if self.draw_state.duration_marker is not None:
self.draw_state.duration_marker.remove()
bigger_coord = max(self.draw_state.r_line_coord,
self.draw_state.l_line_coord)
smaller_coord = min(self.draw_state.r_line_coord,
self.draw_state.l_line_coord)
self.draw_state.duration_marker = plt.annotate(
s=PlotNordic._stringify_time(bigger_coord - smaller_coord),
xy=(smaller_coord, 0.5),
xytext=(bigger_coord, 0.5),
arrowprops=dict(arrowstyle='<->'))
else:
if self.draw_state.duration_marker is not None:
self.draw_state.duration_marker.remove()
self.draw_state.duration_marker = None
@staticmethod
def resize_event(event):
plt.tight_layout()
def close_event(self, event):
if self.finish_event is not None:
self.finish_event.set()
plt.close('all')
sys.exit()
def animate_events_real_time(self, fig, selected_events_types, one_line):
rects = []
events = []
xranges = []
for i in range(0, len(selected_events_types)):
xranges.append([])
while not self.queue.empty():
event = self.queue.get()
if event is None:
self.logger.info("Stopped collecting new events")
self.close_event(None)
if self.processed_events.tracking_execution:
if event.type_id == self.processed_events.event_processing_start_id:
self.processed_events.start_event = event
for i in range(len(self.temp_events) - 1, -1, -1):
# comparing memory addresses of event processing start
# and event submit to identify matching events
if self.temp_events[i].data[
0] == self.processed_events.start_event.data[
0]:
self.processed_events.submit_event = self.temp_events[
i]
events.append(self.temp_events[i])
self.submitted_event_type = self.processed_events.submit_event.type_id
del self.temp_events[i]
break
elif event.type_id == self.processed_events.event_processing_end_id:
# comparing memory addresses of event processing start and
# end to identify matching events
if self.submitted_event_type is not None and event.data[0] \
== self.processed_events.start_event.data[0]:
rects.append(
matplotlib.patches.Rectangle(
(self.processed_events.start_event.timestamp,
self.processed_events.submit_event.type_id -
self.draw_state.event_processing_rect_height /
2),
event.timestamp -
self.processed_events.start_event.timestamp,
self.draw_state.event_processing_rect_height,
edgecolor='black'))
self.processed_events.tracked_events.append(
TrackedEvent(
self.processed_events.submit_event,
self.processed_events.start_event.timestamp,
event.timestamp))
self.submitted_event_type = None
else:
self.temp_events.append(event)
if event.timestamp > time.time() - self.start_time + self.draw_state.added_time - \
0.2 * self.draw_state.timeline_width:
self.draw_state.added_time += 0.05
if event.timestamp < time.time() - self.start_time + self.draw_state.added_time - \
0.8 * self.draw_state.timeline_width:
self.draw_state.added_time -= 0.05
events.append(event)
else:
events.append(event)
self.processed_events.raw_data.events.append(event)
# translating plot
if not self.draw_state.synchronized_with_events:
# ignore translating plot for stale events
if not self.draw_state.stale_events_displayed:
self.draw_state.stale_events_displayed = True
else:
# translate plot for new events
if len(events) != 0:
self.draw_state.added_time = events[-1].timestamp - \
0.3 * self.draw_state.timeline_width
self.draw_state.synchronized_with_events = True
if not self.draw_state.paused:
self.draw_state.timeline_max = time.time() - self.start_time + \
self.draw_state.added_time
self.draw_state.ax.set_xlim(
self.draw_state.timeline_max - self.draw_state.timeline_width,
self.draw_state.timeline_max)
# plotting events
y = list(map(lambda x: x.type_id, events))
x = list(map(lambda x: x.timestamp, events))
self.draw_state.ax.plot(
x,
y,
marker='o',
linestyle=' ',
color='r',
markersize=self.draw_state.event_submit_markersize)
self.draw_state.ax.add_collection(PatchCollection(rects))
plt.gcf().canvas.flush_events()
def plot_events_real_time(self,
queue,
finish_event,
selected_events_types=None,
one_line=False):
self.start_time = time.time()
self.queue = queue
self.finish_event = finish_event
self.processed_events.raw_data.registered_events_types = queue.get()
self.processed_events.match_event_processing()
if selected_events_types is None:
selected_events_types = list(
self.processed_events.raw_data.registered_events_types.keys())
self.processed_events.event_processing_start_id = \
self.processed_events.raw_data.get_event_type_id('event_processing_start')
self.processed_events.event_processing_end_id = \
self.processed_events.raw_data.get_event_type_id('event_processing_end')
if (self.processed_events.event_processing_start_id is None) or (
self.processed_events.event_processing_end_id is None):
self.processed_events.tracking_execution = False
fig = self._prepare_plot(selected_events_types)
self.start_stop_ax = plt.axes([0.8, 0.025, 0.1, 0.04])
self.start_stop_button = Button(self.start_stop_ax, 'Start/Stop')
self.start_stop_button.on_clicked(self.on_click_start_stop)
plt.sca(self.draw_state.ax)
self.ani = animation.FuncAnimation(
fig,
self.animate_events_real_time,
fargs=[selected_events_types, one_line],
interval=self.plot_config['refresh_time'])
plt.show()
def plot_events_from_file(self,
selected_events_types=None,
one_line=False):
self.draw_state.paused = True
if len(self.processed_events.raw_data.events) == 0 or \
len(self.processed_events.raw_data.registered_events_types) == 0:
self.logger.error("Please read some events data before plotting")
if selected_events_types is None:
selected_events_types = list(
self.processed_events.raw_data.registered_events_types.keys())
self.processed_events.match_event_processing()
self._prepare_plot(selected_events_types)
x = list(
map(lambda x: x.submit.timestamp,
self.processed_events.tracked_events))
y = list(
map(lambda x: x.submit.type_id,
self.processed_events.tracked_events))
self.draw_state.ax.plot(
x,
y,
marker='o',
linestyle=' ',
color='r',
markersize=self.draw_state.event_submit_markersize)
if self.processed_events.tracking_execution:
rects = []
for ev in self.processed_events.tracked_events:
rects.append(
matplotlib.patches.Rectangle(
(ev.proc_start_time, ev.submit.type_id -
self.draw_state.event_processing_rect_height / 2),
ev.proc_end_time - ev.proc_start_time,
self.draw_state.event_processing_rect_height,
edgecolor='black'))
self.draw_state.ax.add_collection(PatchCollection(rects))
self.draw_state.timeline_max = max(x) + 1
self.draw_state.timeline_width = max(x) - min(x) + 2
self.draw_state.ax.set_xlim([min(x) - 1, max(x) + 1])
plt.draw()
plt.show()
class PlotNordic():
def __init__(self, stream=None, event_close=None, log_lvl=logging.WARNING):
plt.rcParams['toolbar'] = 'None'
plt.ioff()
self.plot_config = PlotNordicConfig
self.draw_state = DrawState(
self.plot_config['timeline_width_init'],
self.plot_config['event_processing_rect_height'],
self.plot_config['event_submit_markersize'])
self.ani = None
self.close_event_flag = False
self.processed_events = ProcessedEvents()
if stream is not None:
timeouts = {
'descriptions': 1,
'events': 0
}
self.in_stream = stream
self.in_stream.set_timeouts(timeouts)
if event_close is not None:
self.event_close = event_close
self.logger = logging.getLogger('Plot Nordic')
self.logger_console = logging.StreamHandler()
self.logger.setLevel(log_lvl)
self.log_format = logging.Formatter(
'[%(levelname)s] %(name)s: %(message)s')
self.logger_console.setFormatter(self.log_format)
self.logger.addHandler(self.logger_console)
def read_data_from_files(self, events_filename, events_types_filename):
self.processed_events.read_data_from_files(
events_filename, events_types_filename)
if not self.processed_events.verify():
self.logger.warning("Missing event descriptions")
def on_click_start_stop(self, event):
if self.draw_state.paused:
if self.draw_state.l_line is not None:
self.draw_state.l_line.remove()
self.draw_state.l_line = None
self.draw_state.l_line_coord = None
if self.draw_state.r_line is not None:
self.draw_state.r_line.remove()
self.draw_state.r_line = None
self.draw_state.r_line_coord = None
if self.draw_state.duration_marker is not None:
self.draw_state.duration_marker.remove()
self.draw_state.paused = not self.draw_state.paused
def _prepare_plot(self, selected_events_types):
self.draw_state.ax = plt.gca()
self.draw_state.ax.set_navigate(False)
fig = plt.gcf()
fig.set_size_inches(
self.plot_config['window_width_inch'],
self.plot_config['window_height_inch'],
forward=True)
fig.canvas.draw()
plt.xlabel("Time [s]")
plt.title("Custom events")
plt.grid(True)
minimum = min(selected_events_types)
maximum = max(selected_events_types)
ticks = []
labels = []
for j in selected_events_types:
ticks.append(j)
labels.append(self.processed_events.registered_events_types[j].name)
plt.yticks(ticks, labels)
# min and max range of y axis are bigger by one so markers fit nicely
# on plot
self.draw_state.y_max = maximum + 1
self.draw_state.y_height = maximum - minimum + 2
plt.ylim([minimum - 1, maximum + 1])
self.draw_state.selected_event_textbox = self.draw_state.ax.text(
0.05,
0.95,
self.draw_state.selected_event_text,
fontsize=10,
transform=self.draw_state.ax.transAxes,
verticalalignment='top',
bbox=dict(
boxstyle='round',
alpha=0.5,
facecolor='linen'))
self.draw_state.selected_event_textbox.set_visible(False)
fig.canvas.mpl_connect('scroll_event', self.scroll_event)
fig.canvas.mpl_connect('button_press_event', self.button_press_event)
fig.canvas.mpl_connect('button_release_event',
self.button_release_event)
fig.canvas.mpl_connect('resize_event', PlotNordic.resize_event)
fig.canvas.mpl_connect('close_event', self.close_event)
plt.tight_layout()
return fig
def _get_relative_coords(self, event):
# relative position of plot - x0, y0, width, height
ax_loc = self.draw_state.ax.get_position().bounds
window_size = plt.gcf().get_size_inches() * \
plt.gcf().dpi # window size - width, height
x_rel = (event.x - ax_loc[0] * window_size[0]) \
/ ax_loc[2] / window_size[0]
y_rel = (event.y - ax_loc[1] * window_size[1]) \
/ ax_loc[3] / window_size[1]
return x_rel, y_rel
def scroll_event(self, event):
x_rel, _ = self._get_relative_coords(event)
if event.button == 'up':
if self.draw_state.paused:
self.draw_state.timeline_max = self.draw_state.timeline_max - (1 - x_rel) * \
(self.draw_state.timeline_width - self.draw_state.timeline_width *
self.plot_config['timeline_scale_factor'])
self.draw_state.timeline_width = self.draw_state.timeline_width * \
self.plot_config['timeline_scale_factor']
if event.button == 'down':
if self.draw_state.paused:
self.draw_state.timeline_max = self.draw_state.timeline_max + (1 - x_rel) * \
(self.draw_state.timeline_width / self.plot_config['timeline_scale_factor'] -
self.draw_state.timeline_width)
self.draw_state.timeline_width = self.draw_state.timeline_width / \
self.plot_config['timeline_scale_factor']
self.draw_state.ax.set_xlim(
self.draw_state.timeline_max -
self.draw_state.timeline_width,
self.draw_state.timeline_max)
plt.draw()
def _find_closest_event(self, x_coord, y_coord):
filtered_id = list(filter(lambda x: x.submit.type_id == round(y_coord),
self.processed_events.tracked_events))
if len(filtered_id) == 0:
return None
if not self.processed_events.is_event_tracked(round(y_coord)):
dists = list(map(lambda x: abs(x.submit.timestamp - x_coord), filtered_id))
return filtered_id[np.argmin(dists)]
else:
matching_processing = list(
filter(
lambda x: x.proc_start_time < x_coord < x.proc_end_time,
filtered_id))
if matching_processing:
return matching_processing[0]
dists = list(map(lambda x: min([abs(x.submit.timestamp - x_coord),
abs(x.proc_start_time - x_coord), abs(x.proc_end_time - x_coord)]), filtered_id))
return filtered_id[np.argmin(dists)]
@staticmethod
def _stringify_time(time_seconds):
if time_seconds > 0.1:
return '%.5f' % (time_seconds) + ' s'
return '%.5f' % (1000 * time_seconds) + ' ms'
def button_press_event(self, event):
x_rel, y_rel = self._get_relative_coords(event)
if event.button == MouseButton.LEFT.value:
self.draw_state.pan_x_start1 = x_rel
if event.button == MouseButton.MIDDLE.value:
if self.draw_state.selected_event_submit is not None:
for i in self.draw_state.selected_event_submit:
i.remove()
self.draw_state.selected_event_submit = None
if self.draw_state.selected_event_processing is not None:
self.draw_state.selected_event_processing.remove()
self.draw_state.selected_event_processing = None
self.draw_state.selected_event_textbox.set_visible(False)
if x_rel > 1 or x_rel < 0 or y_rel > 1 or y_rel < 0:
plt.draw()
return
coord_x = self.draw_state.timeline_max - \
(1 - x_rel) * self.draw_state.timeline_width
coord_y = self.draw_state.y_max - \
(1 - y_rel) * self.draw_state.y_height
selected_event = self._find_closest_event(coord_x, coord_y)
if selected_event is None:
return
event_submit = selected_event.submit
self.draw_state.selected_event_submit = self.draw_state.ax.plot(
event_submit.timestamp,
event_submit.type_id,
markersize=2*self.draw_state.event_submit_markersize,
color='g',
marker='o',
linestyle=' ')
if selected_event.proc_start_time is not None:
self.draw_state.selected_event_processing = matplotlib.patches.Rectangle(
(selected_event.proc_start_time,
selected_event.submit.type_id -
self.draw_state.event_processing_rect_height),
selected_event.proc_end_time -
selected_event.proc_start_time,
2*self.draw_state.event_processing_rect_height,
color='g')
self.draw_state.ax.add_artist(
self.draw_state.selected_event_processing)
self.draw_state.selected_event_text = \
self.processed_events.registered_events_types[event_submit.type_id].name + '\n'
self.draw_state.selected_event_text += 'Submit: ' + \
PlotNordic._stringify_time(event_submit.timestamp) + '\n'
if selected_event.proc_start_time is not None:
self.draw_state.selected_event_text += 'Processing start: ' + \
PlotNordic._stringify_time(
selected_event.proc_start_time) + '\n'
self.draw_state.selected_event_text += 'Processing end: ' + \
PlotNordic._stringify_time(
selected_event.proc_end_time) + '\n'
self.draw_state.selected_event_text += 'Processing time: ' + \
PlotNordic._stringify_time(selected_event.proc_end_time - \
selected_event.proc_start_time) + '\n'
ev_type = self.processed_events.registered_events_types[event_submit.type_id]
for i in range(0, len(ev_type.data_descriptions)):
if ev_type.data_descriptions[i] == EM_MEM_ADDRESS_DATA_DESC:
continue
self.draw_state.selected_event_text += ev_type.data_descriptions[i] + ' = '
self.draw_state.selected_event_text += str(event_submit.data[i]) + '\n'
self.draw_state.selected_event_textbox.set_visible(True)
self.draw_state.selected_event_textbox.set_text(
self.draw_state.selected_event_text)
plt.draw()
if event.button == MouseButton.RIGHT.value:
self.draw_state.pan_x_start2 = x_rel
def button_release_event(self, event):
x_rel, y_rel = self._get_relative_coords(event)
if event.button == MouseButton.LEFT.value:
if self.draw_state.paused:
if abs(x_rel - self.draw_state.pan_x_start1) < 0.01:
if self.draw_state.l_line is not None:
self.draw_state.l_line.remove()
self.draw_state.l_line = None
self.draw_state.l_line_coord = None
if 0 <= x_rel <= 1:
if 0 <= y_rel <= 1:
self.draw_state.l_line_coord = self.draw_state.timeline_max - \
(1 - x_rel) * self.draw_state.timeline_width
self.draw_state.l_line = plt.axvline(
self.draw_state.l_line_coord)
plt.draw()
else:
self.draw_state.timeline_max = self.draw_state.timeline_max - \
(x_rel - self.draw_state.pan_x_start1) * \
self.draw_state.timeline_width
self.draw_state.ax.set_xlim(
self.draw_state.timeline_max -
self.draw_state.timeline_width,
self.draw_state.timeline_max)
plt.draw()
if event.button == MouseButton.RIGHT.value:
if self.draw_state.paused:
if abs(x_rel - self.draw_state.pan_x_start2) < 0.01:
if self.draw_state.r_line is not None:
self.draw_state.r_line.remove()
self.draw_state.r_line = None
self.draw_state.r_line_coord = None
if 0 <= x_rel <= 1:
if 0 <= y_rel <= 1:
self.draw_state.r_line_coord = self.draw_state.timeline_max - \
(1 - x_rel) * self.draw_state.timeline_width
self.draw_state.r_line = plt.axvline(
self.draw_state.r_line_coord, color='r')
plt.draw()
if self.draw_state.r_line_coord is not None and self.draw_state.l_line_coord is not None:
if self.draw_state.duration_marker is not None:
self.draw_state.duration_marker.remove()
bigger_coord = max(
self.draw_state.r_line_coord,
self.draw_state.l_line_coord)
smaller_coord = min(
self.draw_state.r_line_coord,
self.draw_state.l_line_coord)
self.draw_state.duration_marker = plt.annotate(
text=PlotNordic._stringify_time(
bigger_coord - smaller_coord), xy=(
smaller_coord, 0.5), xytext=(
bigger_coord, 0.5), arrowprops=dict(
arrowstyle='<->'))
else:
if self.draw_state.duration_marker is not None:
self.draw_state.duration_marker.remove()
self.draw_state.duration_marker = None
@staticmethod
def resize_event(event):
plt.tight_layout()
def close_event(self, event):
self.close_event_flag = True
def animate_events_real_time(self, fig):
rects = []
events = []
#Receive events
while True:
try:
data = self.in_stream.recv_ev()
except StreamError as err:
if err.args[1] == StreamError.TIMEOUT_MSG:
break
self.logger.error("Receiving error: {}. Exiting".format(err))
self.close_event(None)
sys.exit()
data_str = data.decode()
tracked_event = TrackedEvent.deserialize(data_str)
events.append(tracked_event.submit)
self.processed_events.tracked_events.append(tracked_event)
if tracked_event.proc_start_time is not None:
assert tracked_event.proc_end_time is not None
rects.append(
matplotlib.patches.Rectangle(
(tracked_event.proc_start_time,
tracked_event.submit.type_id -
self.draw_state.event_processing_rect_height/2),
tracked_event.proc_end_time -
tracked_event.proc_start_time,
self.draw_state.event_processing_rect_height,
edgecolor='black'))
# translating plot
if not self.draw_state.synchronized_with_events:
# ignore translating plot for stale events
if not self.draw_state.stale_events_displayed:
self.draw_state.stale_events_displayed = True
else:
# translate plot for new events
if len(events) != 0:
self.draw_state.added_time = events[-1].timestamp - \
0.3 * self.draw_state.timeline_width
self.draw_state.synchronized_with_events = True
if not self.draw_state.paused:
self.draw_state.timeline_max = time.time() - self.start_time + \
self.draw_state.added_time
self.draw_state.ax.set_xlim(
self.draw_state.timeline_max -
self.draw_state.timeline_width,
self.draw_state.timeline_max)
# plotting events
y = list(map(lambda x: x.type_id, events))
x = list(map(lambda x: x.timestamp, events))
self.draw_state.ax.plot(
x,
y,
marker='o',
linestyle=' ',
color='r',
markersize=self.draw_state.event_submit_markersize)
self.draw_state.ax.add_collection(PatchCollection(rects))
plt.gcf().canvas.flush_events()
if self.event_close.is_set():
self.close_event(None)
if self.close_event_flag:
sys.exit()
def plot_events_real_time(self, selected_events_types=None):
self.start_time = time.time()
#Receive event descriptions
while True:
try:
bytes = self.in_stream.recv_desc()
break
except StreamError as err:
if err.args[1] == StreamError.TIMEOUT_MSG:
if self.event_close.is_set():
self.logger.info("Module closed before receiving event descriptions.")
sys.exit()
continue
self.logger.error("Receiving error: {}. Exiting".format(err))
sys.exit()
data_str = bytes.decode()
event_types_dict = json.loads(data_str)
self.processed_events.registered_events_types = dict((int(k), EventType.deserialize(v))
for k, v in event_types_dict.items())
if self.processed_events.registered_events_types is None:
self.logger.error("Event descriptors not sent properly")
sys.exit()
if selected_events_types is None:
selected_events_types = list(
self.processed_events.registered_events_types.keys())
fig = self._prepare_plot(selected_events_types)
self.start_stop_ax = plt.axes([0.8, 0.025, 0.1, 0.04])
self.start_stop_button = Button(self.start_stop_ax, 'Start/Stop')
self.start_stop_button.on_clicked(self.on_click_start_stop)
plt.sca(self.draw_state.ax)
self.ani = animation.FuncAnimation(
fig,
self.animate_events_real_time,
interval=self.plot_config['refresh_time'])
plt.show()
def plot_events_from_file(
self, selected_events_types=None, one_line=False):
self.draw_state.paused = True
if len(self.processed_events.tracked_events) == 0 or \
len(self.processed_events.registered_events_types) == 0:
self.logger.error("Please read some events data before plotting")
if selected_events_types is None:
selected_events_types = list(
self.processed_events.registered_events_types.keys())
self._prepare_plot(selected_events_types)
x = list(map(lambda x: x.submit.timestamp, self.processed_events.tracked_events))
y = list(map(lambda x: x.submit.type_id, self.processed_events.tracked_events))
self.draw_state.ax.plot(
x,
y,
marker='o',
linestyle=' ',
color='r',
markersize=self.draw_state.event_submit_markersize)
rects = []
for ev in self.processed_events.tracked_events:
if ev.proc_start_time is None:
continue
rects.append(
matplotlib.patches.Rectangle(
(ev.proc_start_time,
ev.submit.type_id - self.draw_state.event_processing_rect_height/2),
ev.proc_end_time - ev.proc_start_time,
self.draw_state.event_processing_rect_height,
edgecolor='black'))
self.draw_state.ax.add_collection(PatchCollection(rects))
self.draw_state.timeline_max = max(x) + 1
self.draw_state.timeline_width = max(x) - min(x) + 2
self.draw_state.ax.set_xlim([min(x) - 1, max(x) + 1])
plt.draw()
plt.show()
