object SparseMatrixD extends Serializable
The SparseMatrixD
object is the companion object for the SparseMatrixD
class.
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type
RowMap = SortedLinkedHashMap[Int, Double]
Shorthand type definition for rows in sparse matrix
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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def
apply(fileName: String): SparseMatrixD
Create a matrix by reading from a text file, e.g., a CSV file.
Create a matrix by reading from a text file, e.g., a CSV file.
- fileName
the name of file holding the data
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def
apply(u: Vector[VectoD]): SparseMatrixD
Create a matrix and assign values from the Scala
Vector
of vectors 'u'.Create a matrix and assign values from the Scala
Vector
of vectors 'u'. Assumes vectors are column-wise.- u
the Vector of vectors to assign
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def
apply(u: Array[VectoD], columnwise: Boolean = true): SparseMatrixD
Create a matrix and assign values from the array of vectors 'u'.
Create a matrix and assign values from the array of vectors 'u'.
- u
the array of vectors to assign
- columnwise
whether the vectors are treated as column or row vectors
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asInstanceOf[T0]: T0
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eq(arg0: AnyRef): Boolean
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equals(arg0: Any): Boolean
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def
eye(m: Int, n: Int = 0): SparseMatrixD
Create an 'm-by-n' sparse identity matrix I (ones on main diagonal, zeros elsewhere).
Create an 'm-by-n' sparse identity matrix I (ones on main diagonal, zeros elsewhere). If 'n' is <= 0, set it to 'm' for a square identity matrix.
- m
the row dimension of the matrix
- n
the column dimension of the matrix (defaults to 0 => square matrix)
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def
finalize(): Unit
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