def make_uniform_mdp(problem,N,A):
boundary = problem.gen_model.boundary.boundary
grid = [(l,u,N) for (l,u) in boundary]
discretizer = RegularGridInterpolator(grid)
action_limits = problem.action_limits
action_cuts = [np.linspace(l,u,A) for (l,u) in action_limits]
actions = discrete.make_points(action_cuts)
num_samples = 150
builder = MDPBuilder(problem,
discretizer,
actions,
num_samples)
mdp_obj = builder.build_mdp()
return (mdp_obj,discretizer)
def build_basis(disc):
N = disc.num_nodes()
n = disc.num_real_nodes()
points = np.empty((N,2))
points[:n,:] = disc.get_cutpoints()
points[n:,:] = np.zeros((N-n,2))
K = 5
W = make_points([np.linspace(0,2.0*np.pi/10,K)]*2)
B = []
B.append(np.cos(W.dot(points.T)))
B.append(np.sin(W[1:,:].dot(points.T)))
B = np.vstack(B).T
c = np.random.randn(49)
print c
Z = B[:n,:].dot(c)
plt.imshow(Z.reshape((21,21)),interpolation='none')
plt.show()
[z[i],z[i]+w[i]],'-k')
plt.show()
if __name__ == '__main__':
Nx = 33
Ny = 33
Tx = 33 # Resolution for terrain
Ty = 33
xdesc = (-2,6,Nx)
ydesc = (-2,6,Ny)
txdesc = (-2,6,Tx)
tydesc = (-2,6,Ty)
(P,(X,Y)) = make_points([np.linspace(*xdesc),np.linspace(*ydesc)],True)
(_,(TX,TY)) = make_points([np.linspace(*txdesc),np.linspace(*tydesc)],True)
x = P[:,0]
y = P[:,1]
H = height_map_mesh(xdesc,ydesc)
h = H.flatten()
TH = height_map_mesh(txdesc,tydesc)
#(Nx,Ny,Nz) = normal_map(x,y)
# Basic surface
fig = plt.figure()
ax = plt.subplot(1,2,1,projection='3d')
setup = marsh.load('cdiscrete/test.mcts')
sim = marsh.load('cdiscrete/test.mcts.sim')
(ret,traj,dec,costs) = sim
(N,D,T) = traj.shape
xl = np.min(traj[:,0,:])
xh = np.max(traj[:,0,:])
vl = np.min(traj[:,1,:])
vh = np.max(traj[:,1,:])
knn = neighbors.KNeighborsRegressor(n_neighbors=1)
X = np.array([traj[:,0,0], traj[:,1,0]]).T
knn.fit(X,ret)
G = 150
(P,(X,Y)) = make_points([np.linspace(xl,xh,G),
np.linspace(vl,vh,G)],True)
Z = knn.predict(P)
plt.pcolormesh(X,Y,np.reshape(Z,(G,G)))
for i in xrange(N):
plt.plot(traj[i,0,:],
traj[i,1,:],
'x-k')
plt.show()
