def fit_convex_hull(points):
""" Creates a feasible set by taking a convex hull of the points given. Returns P = { x : Ax >= b }
Args:
points (list): Set of numpy points.
Returns:
A (numpy): constraint matrix
b (numpy): constraint vector
"""
hull = ConvexHull(points)
m,n = hull.equations.shape
A = -1 * hull.equations[:,0:n-1]
b = hull.equations[:,n-1]
return np.mat(A), np.mat(b).T
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