I am reading a answer by t.b. ,see here Connections between metrics, norms and scalar products (for understanding e.g. Banach and Hilbert spaces)
He(maybe she) said that "The first observation I would like to mention is that a normed vector space has an abundance of convex open sets. Indeed, the ball of radius $r$ around any point is convex. In a metric vector space, however, there is no reason that there be any convex open sets except the empty set and the space itself—this is due to the fact that the metric is not required to be homogeneous, only translation-invariant. One standard example for this is the space $L_{0}([0,1])$ of all (classes of) Lebesgue measurable functions modulo null sets, equipped with the topology of convergence in measure to be explicit, my preferred metric is $\displaystyle d(f,g) = \int \frac{|f - g|}{1 + |f-g|}$."
I can't understand the words that "In a metric vector space, however, there is no reason that there be any convex open sets except the empty set and the space itself—this is due to the fact that the metric is not required to be homogeneous, only translation-invariant."
And I don't understand his example.
Can someone show me a simple example? i.e. Construct a metric vector space, and s.t. there is no convex set in it except empty set and itself.
Thanks a lot.