EOS1实现3种版本的向量内积） ,返回double精度数值） ,比较使用不同大下和密度的向量来对比相关的速度） ,-In large-scale optimization problems, different vectors and matrices are typically sparse, i.e. only very few elements are non-zero. Typically vectors with thousands of elements may contain only about 4-6 non-zeroes, on average. Such vectors can be stored as normal unpacked vectors (such as DVector class). Often sparse vectors can be stored more efficiently as packed vectors, where only the index and value of the non-zero elements are stored in an array.