ibex_bluesky_core.callbacks.fitting.fitting_utils
Defines the standard fits. The model and guess functions for each fit.
Members
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.DampedOsc[source]
Bases: Fit
Damped Oscillator Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Damped Oscillator Guessing.
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classmethod model(*args: int) → Model[source]
Damped Oscillator Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.ERF[source]
Bases: Fit
Error Function Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Error Function Guessing.
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classmethod model(*args: int) → Model[source]
Error Function Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.ERFC[source]
Bases: Fit
Complementary Error Function Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Complementary Error Function Guessing.
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classmethod model(*args: int) → Model[source]
Complementary Error Function Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.Fit[source]
Bases: ABC
Base class for all fits.
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classmethod fit(*args: int) → FitMethod[source]
Return a FitMethod given model and guess functions to pass to LiveFit.
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abstract classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, 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
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abstract 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
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.Gaussian[source]
Bases: Fit
Gaussian Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Gaussian Guessing.
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classmethod model(*args: int) → Model[source]
Gaussian Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.Linear[source]
Bases: Fit
Linear Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Linear Guessing.
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classmethod model(*args: int) → Model[source]
Linear Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.Lorentzian[source]
Bases: Fit
Lorentzian Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Lorentzian Guessing.
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classmethod model(*args: int) → Model[source]
Lorentzian Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.Polynomial[source]
Bases: Fit
Polynomial Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Polynomial Guessing.
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classmethod model(*args: int) → Model[source]
Polynomial Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.SlitScan[source]
Bases: Fit
Slit Scan Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Slit Scan Guessing.
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classmethod model(*args: int) → Model[source]
Slit Scan Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.TopHat[source]
Bases: Fit
Top Hat Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Top Hat Guessing.
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classmethod model(*args: int) → Model[source]
Top Hat Model.
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class ibex_bluesky_core.callbacks.fitting.fitting_utils.Trapezoid[source]
Bases: Fit
Trapezoid Fitting.
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classmethod guess(*args: int) → Callable[[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]], dict[str, Parameter]][source]
Trapezoid Guessing.
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classmethod model(*args: int) → Model[source]
Trapezoid Model.