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#!/usr/bin/env python
# Eclipse SUMO, Simulation of Urban MObility; see https://eclipse.dev/sumo
# Copyright (C) 2007-2023 German Aerospace Center (DLR) and others.
# This program and the accompanying materials are made available under the
# terms of the Eclipse Public License 2.0 which is available at
# https://www.eclipse.org/legal/epl-2.0/
# This Source Code may also be made available under the following Secondary
# Licenses when the conditions for such availability set forth in the Eclipse
# Public License 2.0 are satisfied: GNU General Public License, version 2
# or later which is available at
# https://www.gnu.org/licenses/old-licenses/gpl-2.0-standalone.html
# SPDX-License-Identifier: EPL-2.0 OR GPL-2.0-or-later
# @file plot_trajectories.py
# @author Jakob Erdmann
# @author Mirko Barthauer
# @date 2018-08-18
"""
This script plots fcd data for each vehicle using either
- distance vs speed
- time vs speed
- time vs distance
Individual trajectories can be clicked in interactive mode to print the vehicle Id on the console
"""
from __future__ import absolute_import
from __future__ import print_function
import os
import sys
from collections import defaultdict
import matplotlib
if 'matplotlib.backends' not in sys.modules:
if 'TEXTTEST_SANDBOX' in os.environ or (os.name == 'posix' and 'DISPLAY' not in os.environ):
matplotlib.use('Agg')
import matplotlib.pyplot as plt # noqa
import math # noqa
from sumolib.xml import parse_fast_nested # noqa
from sumolib.miscutils import uMin, uMax, parseTime # noqa
from sumolib.options import ArgumentParser # noqa
from sumolib.visualization import helpers # noqa
KEYS = {
't': 'Time',
's': 'Speed',
'd': 'Distance',
'a': 'Acceleration',
'i': 'Angle',
'x': 'x-Position',
'y': 'y-Position',
'k': 'kilometrage',
'g': 'gap',
}
def getOptions(args=None):
optParser = ArgumentParser(conflict_handler="resolve")
helpers.addInteractionOptions(optParser)
helpers.addPlotOptions(optParser)
optParser.add_option("-t", "--trajectory-type", category="processing", dest="ttype", default="ds",
help="select two letters from [t, s, d, a, i, x, y, k, g] to plot"
+ " Time, Speed, Distance, Acceleration, Angle,"
+ " x-Position, y-Position, Kilometrage, leaderGap."
+ " Default 'ds' plots Distance vs. Speed")
optParser.add_option("--persons", category="processing", action="store_true",
default=False, help="plot person trajectories")
optParser.add_option("-s", "--show", category="processing", action="store_true",
default=False, help="show plot directly")
optParser.add_option("--csv-output", category="output", dest="csv_output", help="write plot as csv", metavar="FILE")
optParser.add_option("-b", "--ballistic", category="processing", action="store_true", default=False,
help="perform ballistic integration of distance")
optParser.add_option("--filter-route", category="processing", dest="filterRoute",
help="only export trajectories that pass the given list of edges (regardless of gaps)")
optParser.add_option("--filter-edges", category="processing", dest="filterEdges",
help="only consider data for the given list of edges")
optParser.add_option("--filter-ids", category="processing", dest="filterIDs",
help="only consider data for the given list of vehicle (or person) ids")
optParser.add_option("-p", "--pick-distance", category="processing", dest="pickDist", type=float, default=1,
help="pick lines within the given distance in interactive plot mode")
optParser.add_option("-i", "--invert-distance-angle", category="processing", dest="invertDistanceAngle", type=float,
help="invert distance for trajectories with a average angle near FLOAT")
optParser.add_option("--label", category="processing", help="plot label (default input file name")
optParser.add_option("--invert-yaxis", category="processing", dest="invertYAxis", action="store_true",
default=False, help="Invert the Y-Axis")
optParser.add_option("--legend", category="processing", action="store_true", default=False, help="Add legend")
optParser.add_option("-v", "--verbose", category="processing", action="store_true",
default=False, help="tell me what you are doing")
options, args = optParser.parse_known_args(args=args)
if len(args) < 1:
sys.exit("mandatory argument FCD_FILE missing")
options.fcdfiles = args
# keep old presets from before integration of common options
options.nolegend = not options.legend
if options.show:
sys.stderr.write("Option --show is now set by default and will be removed in the future." +
"Use --blind to disable the plot window\n")
if options.filterRoute is not None:
options.filterRoute = options.filterRoute.split(',')
if options.filterEdges is not None:
options.filterEdges = set(options.filterEdges.split(','))
if options.filterIDs is not None:
options.filterIDs = set(options.filterIDs.split(','))
return options
def write_csv(data, fname):
with open(fname, 'w') as f:
for veh, vals in sorted(data.items()):
f.write('"%s"\n' % veh)
for x in zip(*[vals[k] for k in KEYS if k in vals]):
f.write(" ".join(map(str, x)) + "\n")
f.write('\n')
def short_names(filenames):
if len(filenames) == 1:
return filenames
reversedNames = [''.join(reversed(f)) for f in filenames]
prefixLen = len(os.path.commonprefix(filenames))
suffixLen = len(os.path.commonprefix(reversedNames))
return [f[prefixLen:-suffixLen] for f in filenames]
def onpick(event):
mevent = event.mouseevent
print("veh=%s x=%d y=%d" % (event.label, mevent.xdata, mevent.ydata))
def main(options):
fig = plt.figure(figsize=(14, 9), dpi=100)
fig.canvas.mpl_connect('pick_event', onpick)
xdata = None
ydata = None
shortFileNames = short_names(options.fcdfiles)
xdata = options.ttype[0]
ydata = options.ttype[1]
if (len(options.ttype) == 2
and xdata in KEYS
and ydata in KEYS):
xLabel = KEYS[xdata]
yLabel = KEYS[ydata]
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.title(','.join(shortFileNames) if options.label is None else options.label)
else:
sys.exit("unsupported plot type '%s'" % options.ttype)
element = 'vehicle'
location = 'lane'
if options.persons:
element = 'person'
location = 'edge'
routes = defaultdict(list) # vehID -> recorded edges
# vehID -> (times, speeds, distances, accelerations, angles, xPositions, yPositions, kilometrage)
attrs = ['id', 'x', 'y', 'angle', 'speed', location]
if 'k' in options.ttype:
attrs.append('distance')
if 'g' in options.ttype:
attrs.append('leaderGap')
data = defaultdict(lambda: defaultdict(list))
for fileIndex, fcdfile in enumerate(options.fcdfiles):
totalVehs = 0
filteredVehs = 0
for timestep, vehicle in parse_fast_nested(fcdfile, 'timestep', ['time'],
element, attrs):
totalVehs += 1
vehID = vehicle.id
if options.filterIDs and vehID not in options.filterIDs:
continue
if len(options.fcdfiles) > 1:
suffix = shortFileNames[fileIndex]
if len(suffix) > 0:
vehID += "#" + suffix
if options.persons:
edge = vehicle.edge
else:
edge = vehicle.lane[0:vehicle.lane.rfind('_')]
if len(routes[vehID]) == 0 or routes[vehID][-1] != edge:
routes[vehID].append(edge)
if options.filterEdges and edge not in options.filterEdges:
continue
time = parseTime(timestep.time)
speed = float(vehicle.speed)
prevTime = time
prevSpeed = speed
prevDist = 0
if vehID in data:
prevTime = data[vehID]['t'][-1]
prevSpeed = data[vehID]['s'][-1]
prevDist = data[vehID]['d'][-1]
data[vehID]['t'].append(time)
data[vehID]['s'].append(speed)
data[vehID]['i'].append(float(vehicle.angle))
data[vehID]['x'].append(float(vehicle.x))
data[vehID]['y'].append(float(vehicle.y))
if 'k' in options.ttype:
data[vehID]['k'].append(float(vehicle.distance))
if 'g' in options.ttype:
data[vehID]['g'].append(float(vehicle.leaderGap))
if prevTime == time:
data[vehID]['a'].append(0)
else:
data[vehID]['a'].append((speed - prevSpeed) / (time - prevTime))
if options.ballistic:
avgSpeed = (speed + prevSpeed) / 2
else:
avgSpeed = speed
data[vehID]['d'].append(prevDist + (time - prevTime) * avgSpeed)
filteredVehs += 1
if totalVehs == 0 or filteredVehs == 0 or options.verbose:
print("Found %s datapoints in %s and kept %s" % (
totalVehs, fcdfile, filteredVehs))
if filteredVehs == 0:
sys.exit()
def line_picker(line, mouseevent):
if mouseevent.xdata is None:
return False, dict()
# minxy = None
# mindist = 10000
for x, y in zip(line.get_xdata(), line.get_ydata()):
dist = math.sqrt((x - mouseevent.xdata) ** 2 + (y - mouseevent.ydata) ** 2)
if dist < options.pickDist:
return True, dict(label=line.get_label())
# else:
# if dist < mindist:
# print(" ", x,y, dist, (x - mouseevent.xdata) ** 2, (y - mouseevent.ydata) ** 2)
# mindist = dist
# minxy = (x, y)
# print(mouseevent.xdata, mouseevent.ydata, minxy, dist,
# line.get_label())
return False, dict()
minY = uMax
maxY = uMin
minX = uMax
maxX = uMin
addArgs = {"picker": line_picker, "linestyle": options.linestyle}
if options.marker is not None:
addArgs["marker"] = options.marker
for vehID, d in data.items():
if options.filterRoute is not None:
skip = False
route = routes[vehID]
for required in options.filterRoute:
if required not in route:
skip = True
break
if skip:
continue
if options.invertDistanceAngle is not None:
avgAngle = sum(d[4]) / len(d[4])
if abs(avgAngle - options.invertDistanceAngle) < 45:
maxDist = d[2][-1]
for i, v in enumerate(d[2]):
d[2][i] = maxDist - v
minY = min(minY, min(d[ydata]))
maxY = max(maxY, max(d[ydata]))
minX = min(minX, min(d[xdata]))
maxX = max(maxX, max(d[xdata]))
plt.plot(d[xdata], d[ydata], label=vehID, **addArgs)
if options.invertYAxis:
plt.axis([minX, maxX, maxY, minY])
if options.csv_output is not None:
write_csv(data, options.csv_output)
helpers.closeFigure(fig, fig.axes[0], options)
if __name__ == "__main__":
main(getOptions())
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