def _preprocess(self):
# Set time offsets
starttime = min([ trace.get_init_time() for trace in self.traces ])
for trace in self.traces:
trace.time_offset = trace.get_init_time() - starttime
trace_times = [ trace.get_next_event_time() for trace in self.traces ]
if self.export_data:
place_counters = [place_counter_name(p)
for p in self.project.nets[0].places()
if p.trace_tokens]
ri = ExportRunInstance(
self,
[ t for t in self.project.nets[0].transitions() if t.trace_fire ],
[ (p, i) for p in self.project.nets[0].places()
for i, tracing in enumerate(p.trace_tokens_functions)
if tracing.return_numpy_type != 'O' ],
ExportRunInstance.basic_header + place_counters)
else:
ri = RunInstance(
self.project, self.process_count)
index = 0
timeline = Table([("process", "<i4"), ("pointer", "<i4")], 100)
full_timeline = Table([("process", "<i4"), ("pointer", "<i4")], 100)
while True:
# Searching for trace with minimal event time
minimal_time_index = utils.index_of_minimal_value(trace_times)
if minimal_time_index is None:
break
trace = self.traces[minimal_time_index]
full_timeline.add_row((minimal_time_index, trace.pointer))
# Timeline update
if trace.is_next_event_visible():
timeline.add_row(full_timeline[index])
trace.process_event(ri)
trace_times[minimal_time_index] = trace.get_next_event_time()
index += 1
self.data = Table([], 0)
if self.export_data:
self.data = ri.get_table()
timeline.trim()
full_timeline.trim()
self.timeline, self.full_timeline = timeline, full_timeline
self.missed_receives = ri.missed_receives
def tokens_count(table, processes, places, collapse=True):
required = ["Event", "Process", "Time"] + \
[place_counter_name(place) for place in places]
header = table.header
if not all(item in header for item in required):
return
f_eq = lambda x, y: x == y
filters = [("Event", f_eq, 'C')]
names, values = [], []
for place in places:
columns = ["Time", place_counter_name(place)]
for p in processes:
names.append("{0}@{1}".format(place.get_name_or_id(), p))
counts = table.select(columns, filters + [("Process", f_eq, p)])
values.append((counts[columns[0]], counts[columns[1]]))
return ("Number of tokens",
charts.place_chart(names, values, "Number of tokens in places",
"Time", "Count"))
def tokens_count(table, processes, places, collapse=True):
required = ["Event", "Process", "Time"] + \
[place_counter_name(place) for place in places]
header = table.header
if not all(item in header for item in required):
return
f_eq = lambda x, y: x == y
filters = [("Event", f_eq, 'C')]
names, values = [], []
for place in places:
columns = ["Time", place_counter_name(place)]
for p in processes:
names.append("{0}@{1}".format(place.get_name_or_id(), p))
counts = table.select(columns, filters + [("Process", f_eq, p)])
values.append((counts[columns[0]], counts[columns[1]]))
return ("Number of tokens",
charts.place_chart(
names, values, "Number of tokens in places", "Time", "Count"))
