sage: random_element(K)
(0, 0, 0)
+ A random element of the nonnegative orthant should have all
+ components nonnegative::
+
+ sage: set_random_seed()
+ sage: K = Cone([(1,0,0),(0,1,0),(0,0,1)])
+ sage: all([ x >= 0 for x in random_element(K) ])
+ True
+
TESTS:
- Any cone should contain an element of itself::
+ Any cone should contain a random element of itself::
sage: set_random_seed()
- sage: K = random_cone(max_rays = 8)
+ sage: K = random_cone(max_ambient_dim=8)
sage: K.contains(random_element(K))
True
+ A strictly convex cone contains no lines, and thus no negative
+ multiples of any of its elements besides zero::
+
+ sage: set_random_seed()
+ sage: K = random_cone(max_ambient_dim=8, strictly_convex=True)
+ sage: x = random_element(K)
+ sage: x.is_zero() or not K.contains(-x)
+ True
+
+ The sum of random elements of a cone lies in the cone::
+
+ sage: set_random_seed()
+ sage: K = random_cone(max_ambient_dim=8)
+ sage: K.contains(sum([random_element(K) for i in range(10)]))
+ True
+
"""
V = K.lattice().vector_space()
- F = V.base_ring()
- coefficients = [ F.random_element().abs() for i in range(K.nrays()) ]
- vector_gens = map(V, K.rays())
- scaled_gens = [ coefficients[i]*vector_gens[i]
- for i in range(len(vector_gens)) ]
+ scaled_gens = [ V.base_field().random_element().abs()*V(r) for r in K ]
# Make sure we return a vector. Without the coercion, we might
# return ``0`` when ``K`` has no rays.
- v = V(sum(scaled_gens))
- return v
+ return V(sum(scaled_gens))
def positive_operator_gens(K):