def parseConfig(config_file): config_parser = ConfigParser.RawConfigParser() config_parser.read(config_file) data = { 'K' : 2, 'L' : 0, 'gt' : None, 'alpha' : None, 'beta' : None, 'gamma' : None } if config_parser.sections() == []: raise IOError("Invalid configuration file.") if config_parser.has_section('Ground Truth'): config.readVisualization(config_parser, 'Ground Truth', os.path.dirname(config_file), options) config.readFilter(config_parser, 'Ground Truth', os.path.dirname(config_file), options) config.readAlgorithm(config_parser, 'Ground Truth', os.path.dirname(config_file), options) config.readMgsSamples(config_parser, 'Ground Truth', os.path.dirname(config_file), options) data['gt'] = config.readVector(config_parser, 'Ground Truth', 'gt', float) data['L'] = len(data['gt']) data['alpha'], data['beta'], data['gamma'] = \ config.getParameters(config_parser, 'Ground Truth', os.path.dirname(config_file), data['K'], data['L']) config.readStrategy(config_parser, 'Ground Truth', options) result = loadResult() if not result['states']: result['states'] = config.readSeeds(config_parser, 'Ground Truth', 'seeds') result = sample(result, data) if config_parser.has_section('Experiment'): config.readVisualization(config_parser, 'Experiment', os.path.dirname(config_file), options) config.readFilter(config_parser, 'Experiment', os.path.dirname(config_file), options) config.readAlgorithm(config_parser, 'Experiment', os.path.dirname(config_file), options) config.readMgsSamples(config_parser, 'Experiment', os.path.dirname(config_file), options) data['L'] = int(config_parser.get('Experiment', 'bins')) data['alpha'], data['beta'], data['gamma'] = \ config.getParameters(config_parser, 'Experiment', os.path.dirname(config_file), data['K'], data['L']) config.readStrategy(config_parser, 'Experiment', options) result = loadResult() result = sample(result, data) if options['video']: save_video() if options['save']: saveResult(result) else: if options['savefig']: importMatplotlib('Agg') from matplotlib.pyplot import savefig vis.plotSampling(result, options, data) # savefig(options['savefig'], bbox_inches='tight', pad_inches=0) savefig(options['savefig']) else: importMatplotlib() from matplotlib.pyplot import show vis.plotSampling(result, options, data) show()
def parseConfig(config_file): config_parser = ConfigParser.RawConfigParser() config_parser.read(config_file) if config_parser.sections() == []: raise IOError("Invalid configuration file.") if config_parser.has_section('Counts'): config.readVisualization(config_parser, 'Counts', os.path.dirname(config_file), options) config.readAlgorithm(config_parser, 'Counts', os.path.dirname(config_file), options) config.readMgsSamples(config_parser, 'Counts', os.path.dirname(config_file), options) counts = config.readCounts(config_parser, 'Counts') K, L = len(counts), len(counts[0]) alpha, beta, gamma = config.getParameters(config_parser, 'Counts', os.path.dirname(config_file), K, L) result = call_posterior(counts, alpha, beta, gamma) if options['save']: saveResult(result) else: if options['savefig']: importMatplotlib('Agg') from matplotlib.pyplot import savefig vis.plotBinning(result, options) savefig(options['savefig'], bbox_inches='tight', pad_inches=0) else: importMatplotlib() from matplotlib.pyplot import show vis.plotBinning(result, options) show() if config_parser.has_section('Trials'): config.readVisualization(config_parser, 'Trials', os.path.dirname(config_file), options) config.readAlgorithm(config_parser, 'Trials', os.path.dirname(config_file), options) config.readMgsSamples(config_parser, 'Trials', os.path.dirname(config_file), options) binsize = config_parser.getint('Trials', 'binsize') timings = config.readMatrix(config_parser, 'Trials', 'timings', int) srange = None if config_parser.has_option('Trials', 'range'): srange = config.readVector(config_parser, 'Trials', 'range', int) x, counts = timingsToCounts(timings, binsize, srange) K, L = len(counts), len(counts[0]) alpha, beta, gamma = config.getParameters(config_parser, 'Trials', os.path.dirname(config_file), K, L) result = call_posterior(counts, alpha, beta, gamma) if options['save']: saveResult(result) else: if options['savefig']: importMatplotlib('Agg') from matplotlib.pyplot import savefig vis.plotBinningSpikes(x, timings, result, options) savefig(options['savefig'], bbox_inches='tight', pad_inches=0) else: importMatplotlib() from matplotlib.pyplot import show vis.plotBinningSpikes(x, timings, result, options) show()
'.log', format='%(levelname)s - %(asctime)s: %(message)s', level=logging.DEBUG) global Waypoints, NewWaypoint, enMision, distanciaAnewWayp, distanciaLlegadaWayp, modo, velocidadBote, actualAvoid, limiteBateria, modoAvoid, avoidDistancia, home, limite_distancia, limite_distancia2 separador = "----------------" Waypoints = [] NewWaypointEv = [] enMision = 0 distanciaAnewWayp = 0 actualAvoid = 0 modo = "INICIO" modoAvoid = "NORMAL" home = [] config.getParameters() distanciaLlegadaWayp = config.distanciaLlegadaWayp limiteBateria = config.limiteBateria velocidadBote = config.velocidadBote limite_distancia = config.limite_distancia limite_distancia2 = config.limite_distancia2 avoidDistancia = config.avoidDistancia def clearMission(vehiculo): ## se cancela la mision del vehiculo;param vehiculo ;return # mensj("Se cancela mision.",0) cmds = vehiculo.commands vehiculo.commands.clear()