Package org.apache.spark.mllib.linalg

Class SparseMatrix

Object
org.apache.spark.mllib.linalg.SparseMatrix
All Implemented Interfaces:
Serializable, Matrix, scala.Serializable
public class SparseMatrix extends Object implements Matrix
Column-major sparse matrix. The entry values are stored in Compressed Sparse Column (CSC) format. For example, the following matrix 

   1.0 0.0 4.0
   0.0 3.0 5.0
   2.0 0.0 6.0
is stored as values: [1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rowIndices=[0, 2, 1, 0, 1, 2], colPointers=[0, 2, 3, 6].

param: numRows number of rows param: numCols number of columns param: colPtrs the index corresponding to the start of a new column (if not transposed) param: rowIndices the row index of the entry (if not transposed). They must be in strictly increasing order for each column param: values nonzero matrix entries in column major (if not transposed) param: isTransposed whether the matrix is transposed. If true, the matrix can be considered Compressed Sparse Row (CSR) format, where colPtrs behaves as rowPtrs, and rowIndices behave as colIndices, and values are stored in row major.

See Also:

  • Constructor Details

    • SparseMatrix

      public SparseMatrix(int numRows, int numCols, int[] colPtrs, int[] rowIndices, double[] values, boolean isTransposed)

    • SparseMatrix

      public SparseMatrix(int numRows, int numCols, int[] colPtrs, int[] rowIndices, double[] values)
      Column-major sparse matrix. The entry values are stored in Compressed Sparse Column (CSC) format. For example, the following matrix 
      
   1.0 0.0 4.0
   0.0 3.0 5.0
   2.0 0.0 6.0
      is stored as values: [1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rowIndices=[0, 2, 1, 0, 1, 2], colPointers=[0, 2, 3, 6].

      Parameters:
      numRows - number of rows
      numCols - number of columns
      colPtrs - the index corresponding to the start of a new column
      rowIndices - the row index of the entry. They must be in strictly increasing order for each column
      values - non-zero matrix entries in column major

  • Method Details

    • fromCOO

      public static SparseMatrix fromCOO(int numRows, int numCols, scala.collection.Iterable<scala.Tuple3<Object,Object,Object>> entries)
      Generate a SparseMatrix from Coordinate List (COO) format. Input must be an array of (i, j, value) tuples. Entries that have duplicate values of i and j are added together. Tuples where value is equal to zero will be omitted.
      Parameters:
      numRows - number of rows of the matrix
      numCols - number of columns of the matrix
      entries - Array of (i, j, value) tuples
      Returns:
      The corresponding SparseMatrix

    • speye

      public static SparseMatrix speye(int n)
      Generate an Identity Matrix in SparseMatrix format.
      Parameters:
      n - number of rows and columns of the matrix
      Returns:
      SparseMatrix with size n x n and values of ones on the diagonal

    • sprand

      public static SparseMatrix sprand(int numRows, int numCols, double density, Random rng)
      Generate a SparseMatrix consisting of i.i.d. uniform random numbers. The number of non-zero elements equal the ceiling of numRows x numCols x density

      Parameters:
      numRows - number of rows of the matrix
      numCols - number of columns of the matrix
      density - the desired density for the matrix
      rng - a random number generator
      Returns:
      SparseMatrix with size numRows x numCols and values in U(0, 1)

    • sprandn

      public static SparseMatrix sprandn(int numRows, int numCols, double density, Random rng)
      Generate a SparseMatrix consisting of i.i.d. gaussian random numbers.
      Parameters:
      numRows - number of rows of the matrix
      numCols - number of columns of the matrix
      density - the desired density for the matrix
      rng - a random number generator
      Returns:
      SparseMatrix with size numRows x numCols and values in N(0, 1)

    • spdiag

      public static SparseMatrix spdiag(Vector vector)
      Generate a diagonal matrix in SparseMatrix format from the supplied values.
      Parameters:
      vector - a Vector that will form the values on the diagonal of the matrix
      Returns:
      Square SparseMatrix with size values.length x values.length and non-zero values on the diagonal

    • fromML

      public static SparseMatrix fromML(SparseMatrix m)
      Convert new linalg type to spark.mllib type. Light copy; only copies references
      Parameters:
      m - (undocumented)
      Returns:
      (undocumented)

    • numRows

      public int numRows()
      Description copied from interface: Matrix
      Number of rows.
      Specified by:
      numRows in interface Matrix

    • numCols

      public int numCols()
      Description copied from interface: Matrix
      Number of columns.
      Specified by:
      numCols in interface Matrix

    • colPtrs

      public int[] colPtrs()

    • rowIndices

      public int[] rowIndices()

    • values

      public double[] values()

    • isTransposed

      public boolean isTransposed()
      Description copied from interface: Matrix
      Flag that keeps track whether the matrix is transposed or not. False by default.
      Specified by:
      isTransposed in interface Matrix

    • equals

      public boolean equals(Object o)
      Overrides:
      equals in class Object

    • hashCode

      public int hashCode()
      Overrides:
      hashCode in class Object

    • apply

      public double apply(int i, int j)
      Description copied from interface: Matrix
      Gets the (i, j)-th element.
      Specified by:
      apply in interface Matrix

    • copy

      public SparseMatrix copy()
      Description copied from interface: Matrix
      Get a deep copy of the matrix.
      Specified by:
      copy in interface Matrix

    • transpose

      public SparseMatrix transpose()
      Description copied from interface: Matrix
      Transpose the Matrix. Returns a new Matrix instance sharing the same underlying data.
      Specified by:
      transpose in interface Matrix
      Returns:
      (undocumented)

    • toDense

      public DenseMatrix toDense()
      Generate a DenseMatrix from the given SparseMatrix. The new matrix will have isTransposed set to false.
      Returns:
      (undocumented)

    • numNonzeros

      public int numNonzeros()
      Description copied from interface: Matrix
      Find the number of non-zero active values.
      Specified by:
      numNonzeros in interface Matrix
      Returns:
      (undocumented)

    • numActives

      public int numActives()
      Description copied from interface: Matrix
      Find the number of values stored explicitly. These values can be zero as well.
      Specified by:
      numActives in interface Matrix
      Returns:
      (undocumented)

    • colIter

      public scala.collection.Iterator<Vector> colIter()
      Description copied from interface: Matrix
      Returns an iterator of column vectors. This operation could be expensive, depending on the underlying storage.
      Specified by:
      colIter in interface Matrix
      Returns:
      (undocumented)

    • asML

      public SparseMatrix asML()
      Description copied from interface: Matrix
      Convert this matrix to the new mllib-local representation. This does NOT copy the data; it copies references.
      Specified by:
      asML in interface Matrix
      Returns:
      (undocumented)