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import sys
import numpy as np
import matplotlib.pyplot as plt
import json
import dateutil
import numbers
def graph(dataseries):
for name, series in dataseries.items():
times = map(lambda d: d['seconds'], series)
print 'plotting', name
if name.endswith('threshold trigger'):
# HACK: hardcoded.
for v in series:
plt.axhline(y=v['data'], color='red')
first = series[0]['data'] # we expect homogenous data...
if isinstance(first, numbers.Number):
values = map(lambda d: int(d['data']), series)
plt.plot(times, values, label=name)
elif first.get('type') and first.get('type').startswith("note"):
# HACK: hardcoded to reconize notes
# booleans should default to this visualization?
# should be a way to use a predicate function to get this for any value
# XXX: also does not work with multiple different overlapping messages a the same time
# need a way to establish their "identity"? A "group by" construct might be fine, ref Eve lang
values = map(lambda d: d['data']['type'], series)
span_start = None
for time, data in zip(times, values):
value = data == "noteon"
if value:
plt.axvline(x=time, color='black')
if span_start:
span_start = { 'time': time, 'data': data }
plt.axvline(x=time, color='black')
if span_start:
plt.axvspan(span_start['time'], time, alpha=0.5)
span_start = None
# TODO: handle case where we (seemingly) start on, then transition off?
print "Unknown data type", values[0]
def edgeid(e):
tgt = e['tgt']
src = e['src']
return "%s %s -> %s %s" % (src['node'], src['port'], tgt['port'], tgt['node'])
def parse_isotime(s):
def analyze_data(trace):
start_time = None
edge_data = {}
for event in trace['events']:
payload = event['payload']
edge = edgeid(payload)
time = dateutil.parser.parse(payload['time'])
if not start_time:
# XXX: picks the first one, assumes events ordered ascending
start_time = time
if not edge_data.get(edge):
edge_data[edge] = []
d = {
'time': time,
'seconds': (time - start_time).total_seconds(),
'data': payload['data'],
#print edge, d['seconds']
return edge_data
def main():
filename = sys.argv[1]
file = open(filename, "r")
contents =
trace = json.loads(contents)
series = analyze_data(trace)
if __name__ == "__main__":