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add documentation to the main function levenbergMarquardt

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Margarita Lashina 2023-06-07 06:00:58 +03:00
parent e8dafad6c5
commit 0655642933
1 changed files with 15 additions and 0 deletions
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kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/LevenbergMarquardtAlgorithm.kt
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@ -104,6 +104,21 @@ public data class LMInput (
var exampleNumber: Int var exampleNumber: Int
) )
/**
* Levenberg-Marquardt optimization.
*
* An optimization method that iteratively searches for the optimal function parameters
* that best describe the dataset. The 'input' is the function being optimized, a set of real data
* (calculated with independent variables, but with an unknown set of parameters), a set of
* independent variables, and variables for adjusting the algorithm, described in the documentation for the LMInput class.
* The function returns number of completed iterations, the number of evaluations of the input function during execution,
* chi squared value on final parameters, final lambda parameter used to calculate the offset, final parameters
* and type of convergence in the 'output'.
*
* @receiver the `input`.
* @return the 'output'.
*/
public fun DoubleTensorAlgebra.levenbergMarquardt(inputData: LMInput): LMResultInfo { public fun DoubleTensorAlgebra.levenbergMarquardt(inputData: LMInput): LMResultInfo {
val resultInfo = LMResultInfo(0, 0, 0.0, val resultInfo = LMResultInfo(0, 0, 0.0,
0.0, inputData.startParameters, TypeOfConvergence.NoConvergence) 0.0, inputData.startParameters, TypeOfConvergence.NoConvergence)