X = np.random.rand(10,2)

X = X[np.argsort(X[:,0],0)]
O = np.zeros((0,2))
n = X.shape[0]
l = np.argmax(X[:,0])
p = l + 0
for i in range(n-1):
    O=np.vstack([O,X[p]])
    q=(p+1) % n
    for j in range(n):
        bool = (((X[q][1]-X[p][1])  *  (X[j][0] - X[q][0])  - (X[q][0]-X[p][0]) * (X[j][1]-X[q][1])) < 0)
        q = np.where(bool, j, q)
    p=np.where(q==l,q-1,q)

area = 0.5*np.abs(np.dot(O[:,0],np.roll(O[:,1],1))-np.dot(O[:,1],np.roll(O[:,0],1)))

H = X[ConvexHull(X).vertices]
harea = ConvexHull(X).volume
print(harea)
print(area)