numopt-js
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    Interface ConstrainedLevenbergMarquardtOptions

    Options for constrained Levenberg-Marquardt algorithm.

    interface ConstrainedLevenbergMarquardtOptions {
        constraintTolerance?: number;
        dcdp?: (parameters: Float64Array, states: Float64Array) => Matrix;
        dcdx?: (parameters: Float64Array, states: Float64Array) => Matrix;
        drdp?: (parameters: Float64Array, states: Float64Array) => Matrix;
        drdx?: (parameters: Float64Array, states: Float64Array) => Matrix;
        lambdaFactor?: number;
        lambdaInitial?: number;
        logLevel?: "DEBUG" | "INFO" | "WARN" | "ERROR";
        maxIterations?: number;
        onIteration?: (
            iteration: number,
            cost: number,
            parameters: Float64Array,
        ) => void;
        stepSizeP?: number;
        stepSizeX?: number;
        tolerance?: number;
        tolGradient?: number;
        tolResidual?: number;
        tolStep?: number;
        verbose?: boolean;
    }

    Hierarchy (View Summary)

    Index
    constraintTolerance? dcdp? dcdx? drdp? drdx? lambdaFactor? lambdaInitial? logLevel? maxIterations? onIteration? stepSizeP? stepSizeX? tolerance? tolGradient? tolResidual? tolStep? verbose?
    constraintTolerance?: number

    Tolerance for checking constraint satisfaction c(p, x) = 0. If ||c(p, x)|| exceeds this value, a warning will be issued. Default: 1e-6

    dcdp?: (parameters: Float64Array, states: Float64Array) => Matrix

    Analytical partial derivative of constraint function with respect to parameters. If provided, this will be used instead of numerical differentiation. Returns a Matrix of size (constraintCount × parameterCount).

    dcdx?: (parameters: Float64Array, states: Float64Array) => Matrix

    Analytical partial derivative of constraint function with respect to states. If provided, this will be used instead of numerical differentiation. Returns a Matrix of size (constraintCount × stateCount). Supports both square (constraintCount == stateCount) and non-square matrices. Non-square systems are solved in a least-squares sense.

    drdp?: (parameters: Float64Array, states: Float64Array) => Matrix

    Analytical partial derivative of residual function with respect to parameters. If provided, this will be used instead of numerical differentiation. Returns a Matrix of size (residualCount × parameterCount).

    drdx?: (parameters: Float64Array, states: Float64Array) => Matrix

    Analytical partial derivative of residual function with respect to states. If provided, this will be used instead of numerical differentiation. Returns a Matrix of size (residualCount × stateCount).

    lambdaFactor?: number

    Factor for updating lambda (success: divide, failure: multiply). Default: 10.0

    lambdaInitial?: number

    Initial value of damping parameter lambda. Default: 1e-3

    logLevel?: "DEBUG" | "INFO" | "WARN" | "ERROR"

    Log level for detailed logging output. Controls which log messages are displayed:

    • DEBUG: Detailed progress information (cost, gradient norm, step size, etc.)
    • INFO: Convergence messages and important state changes
    • WARN: Warnings (singular matrix, max iterations reached, line search failure, etc.)
    • ERROR: Fatal errors (currently not used, reserved for future extensions)

    If verbose is true and logLevel is not specified, logLevel defaults to INFO. If both logLevel and verbose are specified, logLevel takes precedence. Default: undefined (no logging)

    maxIterations?: number

    Maximum number of iterations before stopping. Default: 1000

    onIteration?: (
        iteration: number,
        cost: number,
        parameters: Float64Array,
    ) => void

    Callback function called at each iteration for progress monitoring. Useful for debugging and monitoring convergence.

    stepSizeP?: number

    Step size for numerical differentiation with respect to parameters. Default: 1e-6

    stepSizeX?: number

    Step size for numerical differentiation with respect to states. Default: 1e-6

    tolerance?: number

    Tolerance for convergence check (gradient norm, step size, etc.). Default: 1e-6

    Levenberg-Marquardt and constrained Levenberg-Marquardt prefer tolGradient / tolStep / tolResidual. If those are omitted, this value is used as a common fallback.

    tolGradient?: number

    Tolerance for gradient norm convergence check. Preferred over tolerance. Default: 1e-6 (or tolerance if set).

    tolResidual?: number

    Tolerance for residual norm convergence check. Preferred over tolerance. Default: 1e-6 (or tolerance if set).

    tolStep?: number

    Tolerance for step size convergence check. Preferred over tolerance. Default: 1e-6 (or tolerance if set).

    verbose?: boolean

    Enable verbose logging for debugging. When true, detailed information is logged to console. Default: false

    Use logLevel instead for more fine-grained control. If both logLevel and verbose are specified, logLevel takes precedence.

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