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polykin.math.optimization¤

VectorOptimumResult dataclass ¤

Dataclass with the results of the optimization.

ATTRIBUTE DESCRIPTION
method

Method used to find the optimum.

TYPE: str

success

If True, the optimum was found.

TYPE: bool

message

Description of the exit status.

TYPE: str

nfeval

Number of function evaluations.

TYPE: int

ngeval

Number of user-supplied gradient evaluations.

TYPE: int | None

nheval

Number of user-supplied Hessian evaluations.

TYPE: int | None

niter

Number of iterations.

TYPE: int

x

Optimum value.

TYPE: FloatVector

f

Function value at the optimum.

TYPE: float

g

Gradient at the optimum.

TYPE: FloatVector | None

H

Last evaluated or estimated Hessian matrix.

TYPE: FloatMatrix | None

Hinv

Last evaluated or estimated inverse Hessian (\(H^{-1}\)) matrix.

TYPE: FloatMatrix | None

L

Last evaluated or estimated Cholesky factor \(L\) (where \(H = LL^T\)) of the Hessian matrix.

TYPE: FloatMatrix | None

Source code in src/polykin/math/optimization/results.py 
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@dataclass(frozen=True, slots=True)
class VectorOptimumResult:
    """Dataclass with the results of the optimization.

    Attributes
    ----------
    method: str
        Method used to find the optimum.
    success: bool
        If `True`, the optimum was found.
    message: str
        Description of the exit status.
    nfeval: int
        Number of function evaluations.
    ngeval: int | None
        Number of user-supplied gradient evaluations.
    nheval: int | None
        Number of user-supplied Hessian evaluations.
    niter: int
        Number of iterations.
    x: FloatVector
        Optimum value.
    f: float
        Function value at the optimum.
    g: FloatVector | None
        Gradient at the optimum.
    H: FloatMatrix | None
        Last evaluated or estimated Hessian matrix.
    Hinv: FloatMatrix | None
        Last evaluated or estimated inverse Hessian ($H^{-1}$) matrix.
    L: FloatMatrix | None
        Last evaluated or estimated Cholesky factor $L$ (where $H = LL^T$) of the
        Hessian matrix.
    """

    method: str
    success: bool
    message: str
    nfeval: int
    ngeval: int | None
    nheval: int | None
    niter: int
    x: FloatVector
    f: float
    g: FloatVector | None = None
    H: FloatMatrix | None = None
    Hinv: FloatMatrix | None = None
    L: FloatMatrix | None = None

    def __repr__(self) -> str:
        """Return a string representation of the optimum result."""
        rows = [
            ("method", self.method),
            ("success", colored_bool(self.success)),
            ("message", self.message),
            ("nfeval", self.nfeval),
            ("ngeval", self.ngeval),
            ("nheval", self.nheval),
            ("niter", self.niter),
            ("x", self.x),
            ("f", self.f),
            ("g", self.g),
            ("H", self.H),
            ("Hinv", self.Hinv),
            ("L", self.L),
        ]

        return "\n".join(
            f"{name:>7}: {value}"
            for name, value in rows
            if value is not None and not (hasattr(value, "size") and value.size == 0)
        )

__repr__ ¤

__repr__() -> str

Return a string representation of the optimum result.

Source code in src/polykin/math/optimization/results.py 
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def __repr__(self) -> str:
    """Return a string representation of the optimum result."""
    rows = [
        ("method", self.method),
        ("success", colored_bool(self.success)),
        ("message", self.message),
        ("nfeval", self.nfeval),
        ("ngeval", self.ngeval),
        ("nheval", self.nheval),
        ("niter", self.niter),
        ("x", self.x),
        ("f", self.f),
        ("g", self.g),
        ("H", self.H),
        ("Hinv", self.Hinv),
        ("L", self.L),
    ]

    return "\n".join(
        f"{name:>7}: {value}"
        for name, value in rows
        if value is not None and not (hasattr(value, "size") and value.size == 0)
    )