问题
Which is the best way to implement a sparse vector in Java?
Of course the good thing would be to have something that can be manipulated quite easily (normalization, scalar product and so on)
Thanks in advance
回答1:
MTJ has a Sparse Vector class. It has norm functions (1-norm 2-norm and ∞-norm) and dot product functions.
回答2:
JScience has a SparseVector implementation that is part of its linear algebra package.
回答3:
You can also try to look at la4j's CompressedVector implementation. It uses pair of arrays: array of values and array of their indicies. And with binary search on top of that it just flies. So, this implementation guarantees O(log n)
running time for get
/set
operations.
Just a brief example
Vector a = new CompressedVector(new double[]{ 1.0, 2.0, 3.0 }).
// calculates L_1 norm of the vector
double n = a.norm();
// calculates the sum of vectors elements
double s = a.fold(Vectors.asSumAccumulator(0.0));
来源:https://stackoverflow.com/questions/1934254/which-is-the-best-way-to-implement-a-sparse-vector-in-java