SparseMatrix

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1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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6. final def eq(arg0: AnyRef): Boolean

   

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7. def equals(arg0: Any): Boolean

   

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8. def finalize(): Unit

   

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9. def fromCOO(numRows: Int, numCols: Int, entries: Iterable[(Int, Int, Double)]): SparseMatrix

   

   Generate a SparseMatrix from Coordinate List (COO) format.

   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.

   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

10. final def getClass(): Class[_]

    

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11. def hashCode(): Int

    

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12. final def isInstanceOf[T0]: Boolean

    

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13. final def ne(arg0: AnyRef): Boolean

    

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14. final def notify(): Unit

    

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15. final def notifyAll(): Unit

    

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16. def spdiag(vector: Vector): SparseMatrix

    

    Generate a diagonal matrix in SparseMatrix format from the supplied values.

    Generate a diagonal matrix in SparseMatrix format from the supplied values.

    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

17. def speye(n: Int): SparseMatrix

    

    Generate an Identity Matrix in SparseMatrix format.

    Generate an Identity Matrix in SparseMatrix format.

    n

    number of rows and columns of the matrix

    returns

    SparseMatrix with size n x n and values of ones on the diagonal

18. def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): SparseMatrix

    

    Generate a SparseMatrix consisting of i.i.d.

    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

    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)

19. def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): SparseMatrix

    

    Generate a SparseMatrix consisting of i.i.d.

    Generate a SparseMatrix consisting of i.i.d. gaussian random numbers.

    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)

20. final def synchronized[T0](arg0: ⇒ T0): T0

    

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21. def toString(): String

    

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22. final def wait(): Unit

    

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23. final def wait(arg0: Long, arg1: Int): Unit

    

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24. final def wait(arg0: Long): Unit

    

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