teldufalsari/kmath
2
0
Fork 0
forked from kscience/kmath
Code Pull Requests 1 Activity

Minor: micro-optimize getFeature function, reformat

Browse Source
This commit is contained in:
Iaroslav Postovalov 2021-01-19 00:14:12 +07:00
parent 3f00410fc1
commit f1b319f73d
No known key found for this signature in database
GPG Key ID: 46E15E4A31B3BCD7
1 changed files with 9 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/FeaturedMatrix.kt
View File

@ -60,8 +60,9 @@ public inline fun <reified T : Any> Matrix<*>.hasFeature(): Boolean =
/**
* Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the criteria
*/
@Suppress("UNCHECKED_CAST")
public inline fun <reified T : Any> Matrix<*>.getFeature(): T? =
features.filterIsInstance<T>().firstOrNull()
features.find { it is T }?.let { it as T }
/**
* Diagonal matrix of ones. The matrix is virtual no actual matrix is created
@ -78,7 +79,12 @@ public fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R, *>.one(rows: Int, c
public fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R, *>.zero(rows: Int, columns: Int): FeaturedMatrix<T> =
VirtualMatrix(rows, columns) { _, _ -> elementContext.zero }
public class TransposedFeature<T : Any>(public val original: Matrix<T>) : MatrixFeature
/**
* Matrices with this feature were transposed previosly and hold the reference to their original.
*
* @property original the matrix before transposition.
*/
public inline class TransposedFeature<T : Any>(public val original: Matrix<T>) : MatrixFeature
/**
* Create a virtual transposed matrix without copying anything. `A.transpose().transpose() === A`.
@ -105,5 +111,5 @@ public fun Matrix<Double>.transposeConjugate(): Matrix<Double> = transpose()
@JvmName("transposeConjugateComplex")
public fun Matrix<Complex>.transposeConjugate(): Matrix<Complex> {
val t = transpose()
return VirtualMatrix(t.rowNum, t.colNum) { i, j -> t[i,j].conjugate }
return VirtualMatrix(t.rowNum, t.colNum) { i, j -> t[i, j].conjugate }
}