#!/usr/bin/env python # Eclipse SUMO, Simulation of Urban MObility; see https://eclipse.org/sumo # Copyright (C) 2008-2020 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_net_dump.py # @author Daniel Krajzewicz # @author Laura Bieker # @author Robert Hilbrich # @date 2016-08-05 from __future__ import absolute_import from __future__ import print_function import os import sys from xml.sax.handler import ContentHandler if 'SUMO_HOME' in os.environ: sys.path.append(os.path.join(os.environ['SUMO_HOME'], 'tools')) else: sys.exit("please declare environment variable 'SUMO_HOME'") import sumolib # noqa from sumolib.visualization import helpers # noqa import matplotlib.pyplot as plt # noqa import matplotlib # noqa class WeightsReader(ContentHandler): """Reads the dump file""" def __init__(self, value): self._edge2value = {} self._value = value self._intervals = [] def startElement(self, name, attrs): if name == 'interval': self._time = float(attrs['begin']) self._edge2value[self._time] = {} self._intervals.append(self._time) elif name == 'edge': id = attrs['id'] if self._value in attrs: self._edge2value[self._time][id] = float(attrs[self._value]) def main(args=None): """The main function; parses options and plots""" # ---------- build and read options ---------- from optparse import OptionParser optParser = OptionParser() optParser.add_option("-n", "--net", dest="net", metavar="FILE", help="Defines the network to read") optParser.add_option("-i", "--dump-inputs", dest="dumps", metavar="FILE", help="Defines the dump-output files to use as input") optParser.add_option("-m", "--measures", dest="measures", default="speed,entered", help="Define which measure to plot") optParser.add_option("--min-width", dest="minWidth", type="float", default=.5, help="Defines the minimum edge width") optParser.add_option("--max-width", dest="maxWidth", type="float", default=3, help="Defines the maximum edge width") optParser.add_option("--log-colors", dest="logColors", action="store_true", default=False, help="If set, colors are log-scaled") optParser.add_option("--log-widths", dest="logWidths", action="store_true", default=False, help="If set, widths are log-scaled") optParser.add_option("--min-color-value", dest="colorMin", type="float", default=None, help="If set, defines the minimum edge color value") optParser.add_option("--max-color-value", dest="colorMax", type="float", default=None, help="If set, defines the maximum edge color value") optParser.add_option("--min-width-value", dest="widthMin", type="float", default=None, help="If set, defines the minimum edge width value") optParser.add_option("--max-width-value", dest="widthMax", type="float", default=None, help="If set, defines the maximum edge width value") optParser.add_option("-v", "--verbose", dest="verbose", action="store_true", default=False, help="If set, the script says what it's doing") optParser.add_option("--color-bar-label", dest="colorBarLabel", default="", help="The label to put on the color bar") # standard plot options helpers.addInteractionOptions(optParser) helpers.addPlotOptions(optParser) helpers.addNetOptions(optParser) # Override the help string for the output option outputOpt = optParser.get_option("--output") outputOpt.help = ("Comma separated list of filename(s) the figure shall be written to; " + "for multiple time intervals use '%s' in the filename as a " + "placeholder for the beginning of the time interval") # parse options, _ = optParser.parse_args(args=args) if options.net is None: print("Error: a network to load must be given.") return 1 if options.verbose: print("Reading network from '%s'" % options.net) net = sumolib.net.readNet(options.net) if options.measures is None: print("Error: a dump file must be given.") return 1 dumps = options.dumps.split(",") times = [] hc = None colorDump = dumps[0] colorMeasure = options.measures.split(",")[0] if colorDump: if options.verbose: print("Reading colors from '%s'" % colorDump) hc = WeightsReader(colorMeasure) sumolib.output.parse_sax(colorDump, hc) times = hc._edge2value hw = None if len(dumps) > 1: widthDump = dumps[1] widthMeasure = options.measures.split(",")[1] if options.verbose: print("Reading widths from '%s'" % widthDump) hw = WeightsReader(widthMeasure) sumolib.output.parse_sax(widthDump, hw) times = hw._edge2value # Should we also save the figure to a file / list of files (comma # separated)? Then we need to check the output filename(s) if options.output: options.nolegend = True optOutputNames = options.output # If we have multiple intervals to be plotted, make sure we have # proper output filenames (with a %s as a placeholder in it) if len(times) > 1 and optOutputNames.find('%s') < 0: print('Warning: multiple time intervals detected, but ' + 'the output filename(s) do not contain a \'%s\' placeholder. ' + 'Continuing by using a default placeholder.') # Modify each filename by putting a '-%s' right before the # extension filenames = optOutputNames.split(',') for i in range(0, len(filenames)): filename, extension = os.path.splitext(filenames[i]) filenames[i] = filename + '-%s' + extension optOutputNames = ','.join(filenames) # Now go through each time interval and create the figures for t in times: if options.verbose: print("Processing interval with a beginning of %s" % t) colors = {} maxColorValue = None minColorValue = None for e in net._id2edge: if hc and t in hc._edge2value and e in hc._edge2value[t]: if options.colorMax is not None and hc._edge2value[t][e] > options.colorMax: hc._edge2value[t][e] = options.colorMax if options.colorMin is not None and hc._edge2value[t][e] < options.colorMin: hc._edge2value[t][e] = options.colorMin if maxColorValue is None or maxColorValue < hc._edge2value[t][e]: maxColorValue = hc._edge2value[t][e] if minColorValue is None or minColorValue > hc._edge2value[t][e]: minColorValue = hc._edge2value[t][e] colors[e] = hc._edge2value[t][e] if options.colorMax is not None: maxColorValue = options.colorMax if options.colorMin is not None: minColorValue = options.colorMin if options.logColors: helpers.logNormalise(colors, maxColorValue) else: helpers.linNormalise(colors, minColorValue, maxColorValue) for e in colors: colors[e] = helpers.getColor(options, colors[e], 1.) if options.verbose: print("Color values are between %s and %s" % (minColorValue, maxColorValue)) widths = {} maxWidthValue = None minWidthValue = None for e in net._id2edge: if hw and t in hw._edge2value and e in hw._edge2value[t]: v = abs(hw._edge2value[t][e]) if options.widthMax is not None and v > options.widthMax: v = options.widthMax if options.widthMin is not None and v < options.widthMin: v = options.widthMin if maxWidthValue is None or maxWidthValue < v: maxWidthValue = v if minWidthValue is None or minWidthValue > v: minWidthValue = v widths[e] = v if options.widthMax is not None: maxWidthValue = options.widthMax if options.widthMin is not None: minWidthValue = options.widthMin if options.logWidths: helpers.logNormalise(widths, options.colorMax) else: helpers.linNormalise(widths, minWidthValue, maxWidthValue) for e in widths: widths[e] = options.minWidth + widths[e] * \ (options.maxWidth - options.minWidth) if options.verbose: print("Width values are between %s and %s" % (minWidthValue, maxWidthValue)) fig, ax = helpers.openFigure(options) ax.set_aspect("equal", None, 'C') helpers.plotNet(net, colors, widths, options) # drawing the legend, at least for the colors norm = matplotlib.colors.LogNorm if options.logColors else matplotlib.colors.Normalize sm = plt.cm.ScalarMappable(cmap=matplotlib.cm.get_cmap(options.colormap), norm=norm(vmin=minColorValue, vmax=maxColorValue)) # "fake up the array of the scalar mappable. Urgh..." # (pelson, http://stackoverflow.com/questions/8342549/matplotlib-add-colorbar-to-a-sequence-of-line-plots) sm._A = [] color_bar = plt.colorbar(sm) color_bar.set_label(options.colorBarLabel) # Should we also save the figure to a file / list of files (comma # separated)? expandedOutputNames = None if options.output: # If we have a "%s" in the name of the output then replace it with the # interval begin of the current interval expandedOutputNames = optOutputNames if expandedOutputNames.find('%s') >= 0: expandedOutputNames = expandedOutputNames.replace("%s", str(t)) # Can be used to print additional text in the figure: # # m, s = divmod(int(t), 60) # h, m = divmod(m, 60) # timeStr = "%02d:%02d:%02d" % (h, m, s) # ax.text(0.2, 0.2, timeStr, bbox={ # 'facecolor': 'white', 'pad': 10}, size=16) helpers.closeFigure(fig, ax, options, False, expandedOutputNames) return 0 if __name__ == "__main__": sys.exit(main(sys.argv))