How it works...

1. The signatures for this method constructor are (Column-major dense matrix):

DenseMatrix(int numRows, int numCols, double[] values)
DenseMatrix(int numRows, int numCols, double[] values, boolean isTransposed)

1. The method inherits from the following which makes their concrete methods available to all routines:
   

   • interface class java.lang.Object

   • java.io.Serializable

   • Matrix

2. There are several method calls that are of interest:

   1. Generate the diagonal matrix from the supplied values in the vector:

static DenseMatrix(Vector vector) 

1. 1. Create an identity matrix. An identity matrix is a matrix that has diagonals as 1 and any other element as 0:

static eye(int n) 

1. 1. Keep track of whether the matrix is transposed:

boolean isTransposed()

1. 1. Create a matrix with a set of random numbers - drawn from uniform distribution:

static DenseMatrix rand(int numRows, int numCols, java.util.Random rng) 

1. 1. Create a matrix with a set of random numbers - drawn from gaussian distribution:

static DenseMatrix randn(int numRows, int numCols, java.util.Random rng) 

1. 1. Transpose the matrix:

DenseMatrix transpose() 

1. 1. Make a deep copy of the vector:

DenseVector Copy() 

1. 1. Convert to a SparseVector. You will do this if your vector is long and the density decreases after a number of operations (for example, zero out non-contributing members):

SparseVector toSparse() 

1. 1. Find the number of non-zero elements. This is useful so you can convert on-the-fly to a SparseVector if the density ID is low:

Int numNonzeros()

1. 1. Get all the values stored in Matrix:

Double[] Values()