All tests pass.

Fixing plotting, and copying static files for all domains that have an example script

rlpy/Domains/Bicycle.py

@@ -182,10 +182,11 @@ def showDomain(self, a=0, s=None):
             ax.set_xlabel("Days")
         for i in range(n):
             handles[i].set_ydata(self.episode_data[i])
-            ax = handles[i].get_axes()
+            ax = handles[i].axes
             ax.relim()
             ax.autoscale_view()
-        plt.draw()
+        plt.figure("Domain").canvas.draw()
+        plt.figure("Domain").canvas.flush_events()
 
 
 class BicycleRiding(BicycleBalancing):

rlpy/Domains/BlocksWorld.py

@@ -109,6 +109,7 @@ def showDomain(self, a=0):
                     # Put it in the back of the list
                     undrawn_blocks = np.hstack((undrawn_blocks, [A]))
         if self.domain_fig is None:
+            plt.figure("Domain")
             self.domain_fig = plt.imshow(
                 world,
                 cmap='BlocksWorld',
@@ -121,7 +122,8 @@ def showDomain(self, a=0):
             plt.show()
         else:
             self.domain_fig.set_data(world)
-            plt.draw()
+            plt.figure("Domain").canvas.draw()
+            plt.figure("Domain").canvas.flush_events()
 
     def showLearning(self, representation):
         pass  # cant show 6 dimensional value function

rlpy/Domains/FiftyChain.py

@@ -172,6 +172,7 @@ def showDomain(self, a=0):
         s = self.state
         # Draw the environment
         if self.circles is None:
+            plt.figure("Domain")
             self.domain_fig = plt.subplot(3, 1, 1)
             plt.figure(1, (self.chainSize * 2 / 10.0, 2))
             self.domain_fig.set_xlim(0, self.chainSize * 2 / 10.0)
@@ -193,7 +194,8 @@ def showDomain(self, a=0):
         for p in self.GOAL_STATES:
             self.circles[p].set_facecolor('g')
         self.circles[s].set_facecolor('k')
-        plt.draw()
+        plt.figure("Domain").canvas.draw()
+        plt.figure("Domain").canvas.flush_events()
 
     def showLearning(self, representation):
         allStates = np.arange(0, self.chainSize)

rlpy/Domains/GridWorld.py

@@ -130,7 +130,8 @@ def showDomain(self, a=0, s=None):
                s[0],
                'k>',
                markersize=20.0 - self.COLS)
-        plt.draw()
+        plt.figure("Domain").canvas.draw()
+        plt.figure("Domain").canvas.flush_events()
 
     def showLearning(self, representation):
         if self.valueFunction_fig is None:

rlpy/Domains/HIVTreatment.py

@@ -130,10 +130,11 @@ def showDomain(self, a=0, s=None):
             ax.set_xlabel("Days")
         for i in range(n):
             handles[i].set_ydata(self.episode_data[i])
-            ax = handles[i].get_axes()
+            ax = handles[i].axes
             ax.relim()
             ax.autoscale_view()
-        plt.draw()
+        plt.figure("Domain").canvas.draw()
+        plt.figure("Domain").canvas.flush_events()
 
 
 def dsdt(s, t, eps1, eps2):

rlpy/Domains/IntruderMonitoring.py

@@ -228,6 +228,7 @@ def showDomain(self, a):
         s = self.state
         # Draw the environment
         if self.domain_fig is None:
+            plt.figure("Domain")
             self.domain_fig = plt.imshow(
                 self.map,
                 cmap='IntruderMonitoring',
@@ -264,4 +265,5 @@ def showDomain(self, a):
             alpha=.7,
             markeredgecolor='k',
             markeredgewidth=2)
-        plt.draw()
+        plt.figure("Domain").canvas.draw()
+        plt.figure("Domain").canvas.flush_events()

rlpy/Domains/PST.py

@@ -205,6 +205,7 @@ def __init__(self, NUM_UAV=3):
     def showDomain(self, a=0):
         s = self.state
         if self.domain_fig is None:
+            plt.figure("Domain")
             self.domain_fig = plt.figure(
                 1, (UAVLocation.SIZE * self.dist_between_locations + 1, self.NUM_UAV + 1))
             plt.show()
@@ -382,7 +383,8 @@ def showDomain(self, a=0):
             if numHealthySurveil > 0:
                 self.location_rect_vis[
                     len(self.location_rect_vis) - 1].set_color('green')
-        plt.draw()
+        plt.figure("Domain").canvas.draw()
+        plt.figure("Domain").canvas.flush_events()
         sleep(0.5)
 
     def showLearning(self, representation):

rlpy/Domains/PuddleWorld.py

@@ -112,11 +112,13 @@ def showDomain(self, a=None):
             self.reward_im = plt.imshow(self.reward_map, extent=(0, 1, 0, 1),
                                         origin="lower")
             self.state_mark = plt.plot(s[0], s[1], 'kd', markersize=20)
-            plt.draw()
+            plt.figure("Domain").canvas.draw()
+            plt.figure("Domain").canvas.flush_events()
         else:
             self.domain_fig = plt.figure("Domain")
             self.state_mark[0].set_data([s[0]], [s[1]])
-            plt.draw()
+            plt.figure("Domain").canvas.draw()
+            plt.figure("Domain").canvas.flush_events()
 
     def showLearning(self, representation):
         a = np.zeros((2))

rlpy/Domains/Swimmer.py

@@ -130,7 +130,8 @@ def showDomain(self, a=None):
         else:
             self.swimmer_lines.set_data(Rx, Ry)
             self.action_text.set_text(str(a))
-        plt.draw()
+        plt.figure("Swimmer Domain").canvas.draw()
+        plt.figure("Swimmer Domain").canvas.flush_events()
 
     def showLearning(self, representation):
         good_pol = SwimmerPolicy(

rlpy/Domains/SystemAdministrator.py

@@ -130,7 +130,7 @@ def loadNetwork(self, path):
 
         """
         _Neighbors = []
-        f = open(path, 'rb')
+        f = open(path, 'r')
         reader = csv.reader(f, delimiter=',')
         self.computers_num = 0
         for row in reader:
@@ -142,6 +142,8 @@ def loadNetwork(self, path):
 
     def showDomain(self, a=0):
         s = self.state
+        plt.figure("Domain")
+
         if self.networkGraph is None:  # or self.networkPos is None:
             self.networkGraph = nx.Graph()
             # enumerate all computer_ids, simulatenously iterating through
@@ -215,7 +217,8 @@ def showDomain(self, a=0):
                     width=2,
                     style='dotted')
         nx.draw_networkx_labels(self.networkGraph, self.networkPos)
-        plt.draw()
+        plt.figure("Domain").canvas.draw()
+        plt.figure("Domain").canvas.flush_events()
 
     def step(self, a):
         # ns = s[:] # make copy of state so as not to affect original mid-step

setup.py

@@ -6,6 +6,7 @@
 BSD license.
 """
 import sys
+import glob
 import multiprocessing
 try:
     from setuptools import setup, Command, find_packages
@@ -238,8 +239,17 @@ def no_cythonize(extensions, **_ignore):
       zip_safe=False,
       cmdclass=cmdclass,
       long_description=open('README.rst').read(),
-      packages=find_packages(exclude=['tests', 'tests.*']),
       include_package_data=True,
+      data_files=[
+          ('rlpy/Domains/GridWorldMaps', glob.glob('./rlpy/Domains/GridWorldMaps/*.txt')),
+          ('rlpy/Domains/IntruderMonitoringMaps', glob.glob('./rlpy/Domains/IntruderMonitoringMaps/*.txt')),
+          ('rlpy/Domains/SystemAdministratorMaps', glob.glob('./rlpy/Domains/SystemAdministratorMaps/*.txt')),
+          ('rlpy/Domains/PinballConfigs', glob.glob('./rlpy/Domains/PinballConfigs/*.cfg')),
+          ('rlpy/Domains/PacmanPackage/layouts', glob.glob('./rlpy/Domains/PacmanPackage/layouts/*.lay')),
+          ('rlpy/Policies', glob.glob('./rlpy/Policies/*.mat'))
+      ],
+
+      packages=find_packages(exclude=['tests', 'tests.*']),
       install_requires=[
           'numpy >= 1.7',
           'scipy',
@@ -248,7 +258,8 @@ def no_cythonize(extensions, **_ignore):
           'scikit-learn',
           'joblib',
           'hyperopt',
-          'pymongo'
+          'pymongo',
+          'cairocffi'
       ],
       setup_requires=['numpy >= 1.7'],
       ext_modules=extensions,

tests/test_cartpole.py

@@ -30,8 +30,8 @@ def test_cartpole():
 
 
 def check_traj(domain_class, filename):
-    with open(filename) as f:
-        traj = pickle.load(f)
+    with open(filename, 'rb') as f:
+        traj = pickle.load(f, encoding='latin1')
     traj_now = sample_random_trajectory(domain_class)
     for i, e1, e2 in zip(list(range(len(traj_now))), traj_now, traj):
         print(i)
@@ -48,7 +48,7 @@ def check_traj(domain_class, filename):
 
 def save_trajectory(domain_class, filename):
     traj = sample_random_trajectory(domain_class)
-    with open(filename, "w") as f:
+    with open(filename, 'wb') as f:
         pickle.dump(traj, f)