changing spaces. Debugging ploting

PythonClient/benchmarks/benchmark.py

@@ -14,7 +14,7 @@ sldist = lambda c1, c2: math.sqrt((c2[0] - c1[0])**2 + (c2[1] - c1[1])**2)
 class Benchmark(object,):
 
 	# Param @name to be used for saving purposes
-	def __init__(self,city_name,name):
+	def __init__(self,city_name,name,starting_position=0):
 		self._city_name = city_name # The name of the city that is going to be used.
 		self._base_name = name # Sends a base name, the rest will be saved with respect to what the episode was about
 		self._dict_stats = {'exp_id':-1,
@@ -45,6 +45,11 @@ class Benchmark(object,):
 		'pos_y':-1
 		}
 
+		# Returns a experiment class that is build from a benchmark inherited class
+		self._experiments = self._build_experiments() 
+
+		self._suffix_name  = self._get_experiments_names(self._experiments) 
+		
 
 	def run_navigation_episode(self, agent,carla, time_out, target):
 
@@ -104,12 +109,10 @@ class Benchmark(object,):
 			return (0, measurement_vec, time_out,distance)
 
 
-	def benchmark_agent(self,agent,carla,starting_position=0):
+	def benchmark_agent(self,agent,carla):
 
+		# The fixed name considering all the experiments being run
 
-
-		experiments = self._build_experiments() # Returns a experiment class that is build from a benchmark inherited class
-		self._suffix_name  = self._get_experiments_names(experiments[starting_position:]) # The fixed name considering all the experiments being run
 		with open(self._base_name + self._suffix_name , 'wb') as ofd:
 
 			w = csv.DictWriter(ofd, self._dict_stats.keys())
@@ -126,7 +129,7 @@ class Benchmark(object,):
 		self.write_experiment() # write the experiment being run
 
 
-		for experiment in experiments[starting_position:]:
+		for experiment in self._experiments[starting_position:]:
 
 
 
@@ -208,7 +211,7 @@ class Benchmark(object,):
 		with open('rewards_' + self._base_name + self._suffix_name , 'a+') as rfd:
 
 			rw = csv.DictWriter(rfd, self._dict_rewards.keys())
-			rw.writeheader()
+			
 
 
 			for i in range(len(reward_vec)):

PythonClient/benchmarks/corl.py

@@ -1,3 +1,11 @@
+# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de
+# Barcelona (UAB), and the INTEL Visual Computing Lab.
+#
+# This work is licensed under the terms of the MIT license.
+# For a copy, see <https://opensource.org/licenses/MIT>.
+
+# CORL experiment set.
+
 
 from .benchmark import Benchmark
 from .experiment import Experiment
@@ -74,9 +82,13 @@ class CoRL(Benchmark):
 
 
     def _build_experiments(self):
+        """ Creates the whole set of experiment objects,
+            The experiments created depend on the selected Town.
+        """
 
+        # We set the camera
+        # This single RGB camera is used on every experiment
         
-		# We set the camera that is going to be used for all experiments
         camera = Camera('CameraRGB')
         camera.set(CameraFOV=100)
 
@@ -136,5 +148,7 @@ class CoRL(Benchmark):
                 experiments_vector.append(experiment)
 
         return experiments_vector
-	def _get_details(self): # Function to get automatic information from the experiment for writing purposes
+
+    def _get_details(self): 
+        # Function to get automatic information from the experiment for writing purposes
         return 'corl_' + self._city_name

PythonClient/benchmarks/metrics.py

@@ -278,12 +278,7 @@ def plot_summary(file,summary_weathers):
 			print 'Avg completion', summaries[sw]['completion']/summaries[sw]['num_weathers']
 			print 'Avg infractions'
 			print_infractions(summaries[sw]['infractions']/summaries[sw]['num_weathers'])
-			#
-			#
-			#infractions_vec = [sum(x) for x in zip(infractions, infractions_vec)]
-			#print 'Non_Colisions/Km', (infractions[1]+  infractions[0])/2.0 ,'Lane Cross/Km ',infractions[0],'Side Cross/Km ',infractions[1],'Col Gen /Km ',infractions[2]\
-			#,'Col Ped /Km ',infractions[3],'Col Ped /Km ',infractions[4], 'Acidents/Km ', (infractions[4] +infractions[2] + infractions[3])/3,\
-			#'total', 1/((infractions[4] +infractions[2] + infractions[3] + infractions[1] + infractions[0])/5.0)
+
 
 	return summaries