diff scripts/safety-analysis.py @ 559:806df5f61c03

adapted safety-analysis script to use multi-threading
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 15 Jul 2014 01:25:33 -0400
parents a80ef6931fd8
children 6d89520e269f
line wrap: on
line diff
--- a/scripts/safety-analysis.py	Mon Jul 14 17:44:09 2014 -0400
+++ b/scripts/safety-analysis.py	Tue Jul 15 01:25:33 2014 -0400
@@ -14,7 +14,7 @@
 parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file', required = True)
 parser.add_argument('--prediction-method', dest = 'predictionMethod', help = 'prediction method (constant velocity (vector computation), constant velocity, normal adaptation, point set prediction)', choices = ['cvd', 'cv', 'na', 'ps'])
 parser.add_argument('--display-cp', dest = 'displayCollisionPoints', help = 'display collision points', action = 'store_true')
-parser.add_argument('-n', dest = 'nProcesses', help = 'number of processes to run in parallel', type = int)
+parser.add_argument('-n', dest = 'nProcesses', help = 'number of processes to run in parallel', type = int, default = 1)
 args = parser.parse_args()
 
 params = storage.ProcessParameters(args.configFilename)
@@ -25,8 +25,10 @@
 else:
     predictionMethod = params.predictionMethod
 
-accelerationDistribution = lambda: random.triangular(-params.maxNormalAcceleration, params.maxNormalAcceleration, 0.)
-steeringDistribution = lambda: random.triangular(-params.maxNormalSteering, params.maxNormalSteering, 0.)
+def accelerationDistribution(): 
+    return random.triangular(-params.maxNormalAcceleration, params.maxNormalAcceleration, 0.)
+def steeringDistribution():
+    return random.triangular(-params.maxNormalSteering, params.maxNormalSteering, 0.)
 
 if predictionMethod == 'cvd': # TODO add cve: constant velocity exact (Sohail's)
     predictionParameters = prediction.CVDirectPredictionParameters()
@@ -58,7 +60,7 @@
 interactions = events.createInteractions(objects)
 for inter in interactions:
     inter.computeIndicators()
-    inter.computeCrossingsCollisions(predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, params.nProcesses)
+    inter.computeCrossingsCollisions(predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones, nProcesses = args.nProcesses)
 
 storage.saveIndicators(params.databaseFilename, interactions)