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import mdp
import sys

#mdp.numx_rand.seed(1266090063)
mdp.numx_rand.seed(None)

def uniform(min_, max_, dims):
	"""Return a random number between min_ and max_ ."""
	return mdp.numx_rand.random(dims)*(max_-min_)+min_
	
def circumference_distr(center, radius, n):
	"""Return n random points uniformly distributed on a circumference."""
	phi = uniform(0, 2*mdp.numx.pi, (n,1))
	x = radius*mdp.numx.cos(phi)+center[0]
	y = radius*mdp.numx.sin(phi)+center[1]
	return mdp.numx.concatenate((x,y), axis=1)
	

def circle_distr(center, radius, n):
	"""Return n random points uniformly distributed on a circle."""
	phi = uniform(0, 2*mdp.numx.pi, (n,1))
	sqrt_r = mdp.numx.sqrt(uniform(0, radius*radius, (n,1)))
	x = sqrt_r*mdp.numx.cos(phi)+center[0]
	y = sqrt_r*mdp.numx.sin(phi)+center[1]
	return mdp.numx.concatenate((x,y), axis=1)


def rectangle_distr(center, w, h, n):
	"""Return n random points uniformly distributed on a rectangle."""
	x = uniform(-w/2., w/2., (n,1))+center[0]
	y = uniform(-h/2., h/2., (n,1))+center[1]
	return mdp.numx.concatenate((x,y), axis=1)






def node_belongs_to_cluster(node):
	n_clusters = len(gng.graph.connected_components())
	for clus in range(0, n_clusters, 1):
		gnode = gng.graph.connected_components()[clus]
		n_cluster_members = len(gnode)
		for j in range(0, n_cluster_members, 1):
			if gnode[j] is node:
				return clus
	return -1
		
		
		
		
		
def get_str(x):
	st=""
	for i in range(0, len(x), 1):
		st = "%s %f" % (st, x[i])
	return st


N = 50
cf1 = circumference_distr([16,-0.5], 2, N)
cf2 = circumference_distr([3,-2], 0.3, N)
cl1 = circle_distr([-5,3], 0.5, N/2)
cl2 = circle_distr([3.5,2.5], 0.7, N)
r1 = rectangle_distr([-1.5,0], 1, 4, N)
r2 = rectangle_distr([+1.5,0], 1, 4, N)
r3 = rectangle_distr([0,+1.5], 2, 1, N/2)
r4 = rectangle_distr([0,-1.5], 2, 1, N/2)
x = mdp.numx.concatenate([cf1, cf2, cl1, cl2, r1,r2,r3,r4], axis=0)
x = mdp.numx.take(x,mdp.numx_rand.permutation(x.shape[0]), axis=0)
print x
exit()