api / koma.matrix.common / MatrixBase

MatrixBase

abstract class MatrixBase<T> :Matrix<T>

Constructors

Name	Summary
<init>	MatrixBase()

Inherited Properties

Name	Summary
T	open val T:Matrix<T> Transpose operator.
size	open val size:Int

Functions

Name	Summary
castOrCopy	fun <DType, TOuter :Matrix<DType>, TInner> castOrCopy(mat:Matrix<DType>, makeOuter: (TInner) ->TOuter, outerFac:MatrixFactory<TOuter>):TOuter Attempts to downcast a matrix to its specific subclass, accepting both inner wrapped types and outer types. Requires the TOuter constructor to be passed in because reified generics don't support ctor calls. If the passed mat cannot be cast, instead copies the data manually into a newly allocated matrix of the correct type.
equals	open fun equals(other:Any?):Boolean
hashCode	open fun hashCode():Int
toString	open fun toString():String

Inherited Functions

Name	Summary
LU	abstract fun LU():Triple<Matrix<T>,Matrix<T>,Matrix<T>> LU Decomposition. Returns p, l, u matrices as a triple.
QR	abstract fun QR():Pair<Matrix<T>,Matrix<T>>
SVD	abstract fun SVD():Triple<Matrix<T>,Matrix<T>,Matrix<T>>
T	open fun T():Matrix<T> Transpose operator.
argMax	abstract fun argMax():Int Row major 1D index.
argMin	abstract fun argMin():Int Row major 1D index.
asColVector	open fun asColVector():Matrix<T> Returns the given vector as a row vector. Will call transpose() on row vectors
asRowVector	open fun asRowVector():Matrix<T> Returns the given vector as a row vector. Will call transpose() on column vectors
chol	abstract fun chol():Matrix<T> (lower triangular) Cholesky decomposition of the matrix. Matrix must be positive-semi definite.
copy	abstract fun copy():Matrix<T> Returns a copy of this matrix (same values, new memory)
cumSum	open fun cumSum():Matrix<T> Calculates the cumulative (ongoing) sum of a matrix's elements. For example, cumsum(mat[1,2,3]) would return mat[1,3,6]. Assumes matrix type is convertible to double.
det	abstract fun det():T Determinant of the matrix
diag	abstract fun diag():Matrix<T>
div	abstract operator fun div(other:Int):Matrix<T> abstract operator fun div(other:T):Matrix<T>
elementSum	abstract fun elementSum():T Sum of all the elements in the matrix.
elementTimes	abstract fun elementTimes(other:Matrix<T>):Matrix<T> Element-wise multiplication with another matrix
epow	abstract fun epow(other:T):Matrix<T> Element-wise exponentiation of each element in the matrixabstract infix fun epow(other:Int):Matrix<T>
expm	abstract fun expm():Matrix<T> Compute the matrix exponential e^x (NOT elementwise)
filterCols	open fun filterCols(f: (col:Matrix<T>) ->Boolean):Matrix<T> Builds a new matrix with a subset of the columns of this matrix, using only the columns for which the function f returns true.
filterColsIndexed	open fun filterColsIndexed(f: (colIndex:Int, col:Matrix<T>) ->Boolean):Matrix<T> Builds a new matrix with a subset of the columns of this matrix, using only the columns for which the function f returns true.
filterRows	open fun filterRows(f: (row:Matrix<T>) ->Boolean):Matrix<T> Builds a new matrix with a subset of the rows of this matrix, using only the rows for which the function f returns true.
filterRowsIndexed	open fun filterRowsIndexed(f: (rowIndex:Int, row:Matrix<T>) ->Boolean):Matrix<T> Builds a new matrix with a subset of the rows of this matrix, using only the rows for which the function f returns true.
forEachCol	open fun forEachCol(f: (Matrix<T>) ->Unit):Unit Passes each col from left to right into a function.
forEachRow	open fun forEachRow(f: (Matrix<T>) ->Unit):Unit Passes each row from top to bottom into a function.
getBaseArray	open fun getBaseArray():Any
getBaseMatrix	abstract fun getBaseMatrix():Any Returns the underlying matrix object from the back-end this Matrix is wrapping. This should be used sparingly (as it breaks encapsulation), but it can increase performance by using computation specifically designed for a particular back-end. Code using this method should not rely on a particular back-end, and should always fallback to slow generic code if an unrecognized matrix is returned here (e.g. use get and set) to access the elements generically).
getByte	open fun getByte(vararg indices:Int):Byte
getCol	abstract fun getCol(col:Int):Matrix<T>
getDouble	abstract fun getDouble(i:Int, j:Int):Double open fun getDouble(vararg indices:Int):Double
getDoubleData	abstract fun getDoubleData():DoubleArray Retrieves the data formatted as doubles in row-major order This method is only for performance over potentially boxing get(Double) methods. This method may or may not return a copy, and thus should be treated as read-only unless backend behavior is known.
getFactory	abstract fun getFactory():MatrixFactory<Matrix<T>> Because sometimes all you have is a Matrix, but you really want a MatrixFactory.
getFloat	abstract fun getFloat(i:Int, j:Int):Float open fun getFloat(vararg indices:Int):Float
getGeneric	abstract fun getGeneric(i:Int, j:Int):T open fun getGeneric(vararg indices:Int):T
getInt	abstract fun getInt(i:Int, j:Int):Int open fun getInt(vararg indices:Int):Int
getLinear	open fun getLinear(index:Int):T
getLong	open fun getLong(vararg indices:Int):Long
getRow	abstract fun getRow(row:Int):Matrix<T>
getShort	open fun getShort(vararg indices:Int):Short
inv	abstract fun inv():Matrix<T> Matrix inverse (square matrices)
mapCols	open fun mapCols(f: (Matrix<T>) ->Matrix<T>):Matrix<T> Takes each col in a matrix, passes them through f, and puts the output of f into a col of an output matrix.
mapColsToList	open fun <U> mapColsToList(f: (Matrix<T>) ->U):List<U> Takes each col in a matrix, passes them through f, and puts the outputs into a List. In contrast to this#mapCols, the usage of a list as the output container allows for arbitrary output types, such as taking a double matrix and returning a list of strings.
mapRows	open fun mapRows(f: (Matrix<T>) ->Matrix<T>):Matrix<T> Takes each row in a matrix, passes them through f, and puts the output of f into a row of an output matrix.
mapRowsToList	open fun <U> mapRowsToList(f: (Matrix<T>) ->U):List<U> Takes each row in a matrix, passes them through f, and puts the outputs into a List. In contrast to this#mapRows, the usage of a list as the output container allows for arbitrary output types, such as taking a double matrix and returning a list of strings.
max	abstract fun max():T Maximum value contained in the matrix
mean	abstract fun mean():T Mean (average) of all the elements in the matrix.
min	abstract fun min():T Minimum value contained in the matrix
minus	abstract operator fun minus(other:T):Matrix<T> abstract operator fun minus(other:Matrix<T>):Matrix<T>
normF	abstract fun normF():T Frobenius normal of the matrix
normIndP1	abstract fun normIndP1():T Induced, p=1 normal of the matrix. Equivalent of norm(matrix,1) in scipy.
numCols	abstract fun numCols():Int Number of columns in the matrix
numRows	abstract fun numRows():Int Number of rows in the matrix
pinv	abstract fun pinv():Matrix<T> Pseudo-inverse of (non-square) matrix
plus	abstract operator fun plus(other:T):Matrix<T> abstract operator fun plus(other:Matrix<T>):Matrix<T>
pow	open infix fun pow(exponent:Int):Matrix<T> Multiplies the matrix by itself exponent times (using matrix multiplication).
repr	open fun repr():String
selectCols	open fun selectCols(vararg idxs:Int):Matrix<T> Select a set of cols from a matrix to form the cols of a new matrix. For example, if you wanted a new matrix consisting of the first, second, and fifth cols of an input matrix, you would write input.selectCols(0,1,4).open fun <U :Number> selectCols(idxs:Matrix<U>):Matrix<T>
selectRows	open fun selectRows(vararg idxs:Int):Matrix<T> Select a set of rows from a matrix to form the rows of a new matrix. For example, if you wanted a new matrix consisting of the first, second, and fifth rows of an input matrix, you would write input.selectRows(0,1,4).open fun <U :Number> selectRows(idxs:Matrix<U>):Matrix<T>
setByte	open fun setByte(vararg indices:Int, value:Byte):Nothing
setCol	abstract fun setCol(index:Int, col:Matrix<T>):Unit
setDouble	abstract fun setDouble(i:Int, j:Int, v:Double):Unit open fun setDouble(vararg indices:Int, value:Double):Unit
setFloat	abstract fun setFloat(i:Int, j:Int, v:Float):Unit open fun setFloat(vararg indices:Int, value:Float):Unit
setGeneric	abstract fun setGeneric(i:Int, j:Int, v:T):Unit open fun setGeneric(vararg indices:Int, value:T):Unit
setInt	abstract fun setInt(i:Int, j:Int, v:Int):Unit open fun setInt(vararg indices:Int, value:Int):Unit
setLinear	open fun setLinear(index:Int, value:T):Unit
setLong	open fun setLong(vararg indices:Int, value:Long):Nothing
setRow	abstract fun setRow(index:Int, row:Matrix<T>):Unit
setShort	open fun setShort(vararg indices:Int, value:Short):Nothing
shape	open fun shape():List<Int>
solve	abstract fun solve(other:Matrix<T>):Matrix<T> Solves A*X=B for X, returning X (X is either column vector or a matrix composed of several col vectors). A is the current matrix, B is the passed in other)/other), and X is the returned matrix.
times	abstract operator fun times(other:Matrix<T>):Matrix<T> abstract operator fun times(other:T):Matrix<T>
to2DArray	open fun to2DArray():Array<DoubleArray> Returns a Matrix as a double 2D array. Intended for MATLAB interop.
toIterable	open fun toIterable():Iterable<T>
trace	abstract fun trace():T The matrix trace.
transpose	abstract fun transpose():Matrix<T> Transpose of the matrix
unaryMinus	abstract operator fun unaryMinus():Matrix<T>
wrapRange	open fun wrapRange(range:IntRange, max:Int):IntRange

Extension Functions

Name	Summary
all	fun <T>Matrix<T>.all(f: (T) ->Boolean):Boolean Checks to see if all elements cause f to return true.
any	fun <T>Matrix<T>.any(f: (T) ->Boolean):Boolean Checks to see if any element in the matrix causes f to return true.
checkIndices	fun <T>NDArray<T>.checkIndices(indices:IntArray):IntArray
checkLinearIndex	fun <T>NDArray<T>.checkLinearIndex(index:Int):Int
fill	fun <T>Matrix<T>.fill(f: (row:Int, col:Int) ->T):Matrix<T> Fills the matrix with the values returned by the input function.fun <T>NDArray<T>.fill(f: (idx:IntArray) ->T):NDArray<T>
fillBoth	fun <T>NDArray<T>.fillBoth(f: (nd:IntArray, linear:Int) ->T):NDArray<T>
fillLinear	fun <T>NDArray<T>.fillLinear(f: (idx:Int) ->T):NDArray<T>
forEach	fun <T>Matrix<T>.forEach(f: (T) ->Unit):Unit Passes each element in row major order into a function.fun <T>NDArray<T>.forEach(f: (ele:T) ->Unit):Unit Takes each element in a NDArray and passes them through f.
forEachIndexed	fun <T>Matrix<T>.forEachIndexed(f: (row:Int, col:Int, ele:T) ->Unit):Unit Passes each element in row major order into a function along with its index location.fun <T>NDArray<T>.forEachIndexed(f: (idx:Int, ele:T) ->Unit):Unit Takes each element in a NDArray and passes them through f. Index given to f is a linear index, depending on the underlying storage major dimension.
forEachIndexedN	fun <T>NDArray<T>.forEachIndexedN(f: (idx:IntArray, ele:T) ->Unit):Unit Takes each element in a NDArray and passes them through f. Index given to f is the full ND index of the element.
get	operator fun <T>Matrix<T>.get(i:Int, j:Int):T operator fun <T>NDArray<T>.get(vararg indices:IntRange):NDArray<T> operator fun <T>NDArray<T>.get(vararg indices:Int):Toperator fun <T>Matrix<T>.get(i:Int):T Gets the ith element in the matrix. If 2D, selects elements in row-major order.operator fun <T>Matrix<T>.get(rows:IntRange, cols:IntRange):Matrix<T> Allow slicing, e.g. matrix[1..2, 3..4]. Note that the range 1..2 is inclusive, so it will retrieve row 1 and 2. Use 1.until(2) for a non-inclusive range.operator fun <T>Matrix<T>.get(rows:IntRange, cols:Int):Matrix<T> Allows for slicing of the rows and selection of a single columnoperator fun <T>Matrix<T>.get(rows:Int, cols:IntRange):Matrix<T> Allows for slicing of the cols and selection of a single row
linearToNIdx	fun <T>NDArray<T>.linearToNIdx(linear:Int):IntArray Given the 1D index of an element in the underlying storage, find the corresponding ND index. Inverse of nIdxToLinear.
map	fun <T>Matrix<T>.map(f: (T) ->T):Matrix<T> Takes each element in a matrix, passes them through f, and puts the output of f into an output matrix. This process is done in row-major order.fun <T>NDArray<T>.map(f: (T) ->T):DefaultGenericNDArray<T> Takes each element in a NDArray, passes them through f, and puts the output of f into an output NDArray.
mapIndexed	fun <T>Matrix<T>.mapIndexed(f: (row:Int, col:Int, ele:T) ->T):Matrix<T> Takes each element in a matrix, passes them through f, and puts the output of f into an output matrix. This process is done in row-major order.fun <T>NDArray<T>.mapIndexed(f: (idx:Int, ele:T) ->T):DefaultGenericNDArray<T> Takes each element in a NDArray, passes them through f, and puts the output of f into an output NDArray. Index given to f is a linear index, depending on the underlying storage major dimension.
mapIndexedN	fun <T>NDArray<T>.mapIndexedN(f: (idx:IntArray, ele:T) ->T):NDArray<T> Takes each element in a NDArray, passes them through f, and puts the output of f into an output NDArray. Index given to f is the full ND index of the element.
nIdxToLinear	fun <T>NDArray<T>.nIdxToLinear(indices:IntArray):Int Given a ND index into this array, find the corresponding 1D index in the raw underlying 1D storage array.
reshape	fun <T>Matrix<T>.reshape(rows:Int, cols:Int):Matrix<T> Returns a new Matrix with the given shape, populated with the data in this array.fun <T>NDArray<T>.reshape(vararg dims:Int):NDArray<T> Returns a new NDArray with the given shape, populated with the data in this array.
safeNIdxToLinear	fun <T>NDArray<T>.safeNIdxToLinear(indices:IntArray):Int
set	operator fun <T>Matrix<T>.set(i:Int, v:T):Unit Set the ith element in the matrix. If 2D, selects elements in row-major order.operator fun <T>Matrix<T>.set(i:Int, j:Int, v:T):Unit operator fun <T>Matrix<T>.set(rows:IntRange, cols:IntRange, value:T):Unit operator fun <T>Matrix<T>.set(rows:Int, cols:IntRange, value:T):Unit operator fun <T>Matrix<T>.set(rows:IntRange, cols:Int, value:T):Unit operator fun <T>NDArray<T>.set(vararg indices:Int, value:NDArray<T>):Unit operator fun <T>NDArray<T>.set(vararg indices:Int, value:T):Unitoperator fun <T>Matrix<T>.set(rows:IntRange, cols:IntRange, value:Matrix<T>):Unit Allow assignment to a slice, e.g. matrix[1..2, 3..4]=something. Note that the range 1..2 is inclusive, so it will retrieve row 1 and 2. Use 1.until(2) for a non-inclusive range.operator fun <T>Matrix<T>.set(rows:Int, cols:IntRange, value:Matrix<T>):Unit Allow assignment to a slice, e.g. matrix[2, 3..4]=something. Note that the range 3..4 is inclusive, so it will retrieve col 3 and 4. Use 1.until(2) for a non-inclusive range.operator fun <T>Matrix<T>.set(rows:IntRange, cols:Int, value:Matrix<T>):Unit Allow assignment to a slice, e.g. matrix[1..2, 3]=something. Note that the range 1..2 is inclusive, so it will retrieve row 1 and 2. Use 1.until(2) for a non-inclusive range.
toMatrixOrNull	fun <T>NDArray<T>.toMatrixOrNull():Matrix<T>?
toTypedArray	fun <T>NDArray<T>.toTypedArray():Array<T> Converts this NDArray into a one-dimensional Array in row-major order.
widthOfDims	fun <T>NDArray<T>.widthOfDims():ArrayList<Int>

Inheritors

Name	Summary
DoubleMatrixBase	abstract class DoubleMatrixBase :MatrixBase<Double> Some functionality to help more easily implement double based koma backends. Feel free to not use if your backend has fast implementations of these functions.