`ibex_bluesky_core.fitting`

Fitting methods used by the LiveFit callback.

Members

`DampedOsc`	Damped Oscillator Fitting.
`ERF`	Error Function Fitting.
`ERFC`	Complementary Error Function Fitting.
`Fit`	Base class for all fits.
`FitMethod`	Tell LiveFit how to fit to a scan.
`Gaussian`	Gaussian Fitting.
`Linear`	Linear Fitting.
`Lorentzian`	Lorentzian Fitting.
`NegativeTrapezoid`	Negative Trapezoid Fitting.
`Polynomial`	Polynomial Fitting.
`SlitScan`	Slit Scan Fitting.
`TopHat`	Top Hat Fitting.
`Trapezoid`	Trapezoid Fitting.

class ibex_bluesky_core.fitting.DampedOsc[source]

Bases: Fit

Damped Oscillator Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Damped Oscillator Guessing.

classmethod model(*args: int) → Model[source]: Damped Oscillator Model.

class ibex_bluesky_core.fitting.ERF[source]

Bases: Fit

Error Function Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Error Function Guessing.

classmethod model(*args: int) → Model[source]: Error Function Model.

class ibex_bluesky_core.fitting.ERFC[source]

Bases: Fit

Complementary Error Function Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Complementary Error Function Guessing.

classmethod model(*args: int) → Model[source]: Complementary Error Function Model.

class ibex_bluesky_core.fitting.Fit[source]

Bases: ABC

Base class for all fits.

classmethod fit(*args: int) → FitMethod[source]: Return a FitMethod given model and guess functions to pass to LiveFit.

abstractmethod classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]

Outline base Guessing. method.

Parameters:: *args (int) – Any extra parameters required for fitting.
Returns:: Guess function (x-values: NDArray, y-values: NDArray -> parameters: Dict[str, lmfit.Parameter])
Return type:: Callable

abstractmethod classmethod model(*args: int) → Model[source]

Outline base model function.

Parameters:: *args (int) – Any extra parameters required for fitting.
Returns:: Model function (x-values: NDArray, parameters: np.float64 -> y-values: NDArray)
Return type:: lmfit.Model

class ibex_bluesky_core.fitting.FitMethod(model: Model | Callable[[ndarray[tuple[int, ...], dtype[float64]]], ndarray[tuple[int, ...], dtype[float64]]], guess: Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]])[source]

Bases: object

Tell LiveFit how to fit to a scan. Has a Model function and a Guess function.

Model - Takes x values and a set of parameters to return y values. Guess - Takes x and y values and returns a rough ‘guess’ of the original parameters.

Assign model and guess functions.

Parameters:

model (lmfit.Model | Callable) – The model function to use.
guess (Callable) – The guess function to use.

class ibex_bluesky_core.fitting.Gaussian[source]

Bases: Fit

Gaussian Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Gaussian Guessing.

classmethod model(*args: int) → Model[source]: Gaussian Model.

class ibex_bluesky_core.fitting.Linear[source]

Bases: Fit

Linear Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Linear Guessing.

classmethod model(*args: int) → Model[source]: Linear Model.

class ibex_bluesky_core.fitting.Lorentzian[source]

Bases: Fit

Lorentzian Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Lorentzian Guessing.

classmethod model(*args: int) → Model[source]: Lorentzian Model.

class ibex_bluesky_core.fitting.NegativeTrapezoid[source]

Bases: Fit

Negative Trapezoid Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Negative Trapezoid Guessing.

classmethod model(*args: int) → Model[source]: Negative Trapezoid Model.

class ibex_bluesky_core.fitting.Polynomial[source]

Bases: Fit

Polynomial Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Polynomial Guessing.

classmethod model(*args: int) → Model[source]: Polynomial Model.

class ibex_bluesky_core.fitting.SlitScan[source]

Bases: Fit

Slit Scan Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Slit Scan Guessing.

classmethod model(*args: int) → Model[source]: Slit Scan Model.

class ibex_bluesky_core.fitting.TopHat[source]

Bases: Fit

Top Hat Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Top Hat Guessing.

classmethod model(*args: int) → Model[source]: Top Hat Model.

class ibex_bluesky_core.fitting.Trapezoid[source]

Bases: Fit

Trapezoid Fitting.

classmethod guess(*args: int) → Callable[[ndarray[tuple[int, ...], dtype[float64]], ndarray[tuple[int, ...], dtype[float64]]], dict[str, Parameter]][source]: Trapezoid Guessing.

classmethod model(*args: int) → Model[source]: Trapezoid Model.

ibex_bluesky_core.fitting

`ibex_bluesky_core.fitting`