API Models

Models summaries

class satlas2.models.models.ExponentialDecay(a: float, tau: float, name: str = 'ExponentialDecay', prefunc: callable | None = None)

Model for an exponential decay

Parameters:

• a (float) – Amplitude of the exponential

• tau (float) – Half-life of the exponential

• name (str, optional) – Name of the model, by default ‘ExponentialDecay’

• prefunc (callable, optional) – Transform function for the input, by default None

class satlas2.models.models.Polynomial(p: ArrayLike, name: str = 'Polynomial', prefunc: callable | None = None)

Model class for a polynomial response

Parameters:

• p (ArrayLike) – Polynomial coefficients, sorted in increasing order

• name (str) – Name of the model

• prefunc (callable, optional) – Transform function for the input, by default None

class satlas2.models.models.SkewedVoigt(A: float, mu: float, FWHMG: float, FWHML: float, skew: float, name: str = 'SkewedVoigt', prefunc: callable | None = None)

Model for a skewed Voigt peak by the error function. Negative skew value is left-skewed, positive skew value is right-skewed.

Parameters:

• A (float) – Amplitude of the peak

• mu (float) – Position of the peak

• FWHMG (float) – Gaussian FWHM

• FWHML (float) – Lorentzian FWHM

• skew (float) – Skew of the peak

• name (str, optional) – Name of the model, by default ‘SkewedVoigt’

• prefunc (callable, optional) – Transform of the input, by default None

class satlas2.models.models.PiecewiseConstant(values: ArrayLike, bounds: ArrayLike, name: str = 'PiecewiseConstant', prefunc: callable | None = None)

Model class for a PiecewiseConstant response

Parameters:

• values (ArrayLike) – Background values between bounds, starting at -inf

• bounds (ArrayLike) – Bounds for background values

• name (str, optional) – Name of the model

• prefunc (callable, optional) – Transform function for the input, by default None

class satlas2.models.models.Voigt(A: float, mu: float, FWHMG: float, FWHML: float, name: str = 'Voigt', prefunc: callable | None = None)

Model for a Voigt lineshape

Parameters:

• A (float) – Amplitude of the profile

• mu (float) – Position of the peak

• FWHMG (float) – Gaussian FWHM of the peak

• FWHML (float) – Lorentzian FWHM of the peak

• name (str, optional) – Name of the model, by default ‘Voigt’

• prefunc (callable, optional) – Transform function of the input, by default None

Methods

calculateFWHM()

Calculate the total FWHM of the profiles, with uncertainty, taking the correlations into account.

class satlas2.models.hfsModel.HFS(I: float, J: ArrayLike, A: ArrayLike = [0, 0], B: ArrayLike = [0, 0], C: ArrayLike = [0, 0], df: float = 0, fwhmg: float = 50, fwhml: float = 50, name: str = 'HFS', peak: str = 'voigt', peak_kwargs: dict | None = None, N: int | None = None, offset: float = 0, poisson: float = 0, scale: float = 1.0, racah: bool = True, prefunc: callable | None = None)

Initializes a hyperfine spectrum Model with the given hyperfine parameters.

Parameters:

• I (float) – Integer or half-integer value of the nuclear spin

• J (ArrayLike) – A sequence of 2 spins, respectively the J value of the lower state and the J value of the higher state

• A (ArrayLike, optional) – A sequence of 2 A values, respectively for the lower and the higher state, by default [0, 0]

• B (ArrayLike, optional) – A sequence of 2 B values, respectively for the lower and the higher state, by default [0, 0]

• C (ArrayLike, optional) – A sequence of 2 C values, respectively for the lower and the higher state, by default [0, 0]

• df (float, optional) – The centroid of the spectrum, by default 0

• fwhmg (float, optional) – The Gaussian FWHM of the Voigt profile, by default 50

• fwhml (float, optional) – The Lorentzian FWHM of the Voigt profile, by default 50

• name (str, optional) – Name of the model, by default ‘HFS’

• peak (str, optional) – peak function to use, by default ‘voigt’

• peak_kwargs (dict, optional) – additional fitting parameters for skew and custom peaks

• N (int, optional) – Number of sidepeaks to be generated, by default None

• offset (float, optional) – Offset in units of x for the sidepeak, by default 0

• poisson (float, optional) – The poisson factor for the sidepeaks, by default 0

• scale (float, optional) – The amplitude of the entire spectrum, by default 1.0

• racah (bool, optional) – Use individual amplitudes are setting the Racah intensities, by default True

• prefunc (callable, optional) – Transformation to be applied on the input before evaluation, by default None

Methods

calculateFWHM()	Calculate the total FWHM of the profiles, with uncertainty, taking the correlations into account.
pos()	Returns the positions of the peaks in MHz in the hyperfine spectrum

Extensive models

Implementation of the various common Models.

class satlas2.models.models.ExponentialDecay(a: float, tau: float, name: str = 'ExponentialDecay', prefunc: callable | None = None)

Bases: Model

Model for an exponential decay

Parameters:

• a (float) – Amplitude of the exponential

• tau (float) – Half-life of the exponential

• name (str, optional) – Name of the model, by default ‘ExponentialDecay’

• prefunc (callable, optional) – Transform function for the input, by default None

class satlas2.models.models.PiecewiseConstant(values: ArrayLike, bounds: ArrayLike, name: str = 'PiecewiseConstant', prefunc: callable | None = None)

Bases: Model

Model class for a PiecewiseConstant response

Parameters:

• values (ArrayLike) – Background values between bounds, starting at -inf

• bounds (ArrayLike) – Bounds for background values

• name (str, optional) – Name of the model

• prefunc (callable, optional) – Transform function for the input, by default None

class satlas2.models.models.Polynomial(p: ArrayLike, name: str = 'Polynomial', prefunc: callable | None = None)

Bases: Model

Model class for a polynomial response

Parameters:

• p (ArrayLike) – Polynomial coefficients, sorted in increasing order

• name (str) – Name of the model

• prefunc (callable, optional) – Transform function for the input, by default None

class satlas2.models.models.SkewedVoigt(A: float, mu: float, FWHMG: float, FWHML: float, skew: float, name: str = 'SkewedVoigt', prefunc: callable | None = None)

Bases: Voigt

Model for a skewed Voigt peak by the error function. Negative skew value is left-skewed, positive skew value is right-skewed.

Parameters:

• A (float) – Amplitude of the peak

• mu (float) – Position of the peak

• FWHMG (float) – Gaussian FWHM

• FWHML (float) – Lorentzian FWHM

• skew (float) – Skew of the peak

• name (str, optional) – Name of the model, by default ‘SkewedVoigt’

• prefunc (callable, optional) – Transform of the input, by default None

class satlas2.models.models.Voigt(A: float, mu: float, FWHMG: float, FWHML: float, name: str = 'Voigt', prefunc: callable | None = None)

Bases: Model

Model for a Voigt lineshape

Parameters:

• A (float) – Amplitude of the profile

• mu (float) – Position of the peak

• FWHMG (float) – Gaussian FWHM of the peak

• FWHML (float) – Lorentzian FWHM of the peak

• name (str, optional) – Name of the model, by default ‘Voigt’

• prefunc (callable, optional) – Transform function of the input, by default None

calculateFWHM() → Tuple[float, float]

Calculate the total FWHM of the profiles, with uncertainty, taking the correlations into account.

Returns:

Tuple of the form (value, uncertainty)

Return type:

Tuple[float, float]

Implementation of the HFSModel class, currently only supplied with a Voigt profile.

class satlas2.models.hfsModel.HFS(I: float, J: ArrayLike, A: ArrayLike = [0, 0], B: ArrayLike = [0, 0], C: ArrayLike = [0, 0], df: float = 0, fwhmg: float = 50, fwhml: float = 50, name: str = 'HFS', peak: str = 'voigt', peak_kwargs: dict | None = None, N: int | None = None, offset: float = 0, poisson: float = 0, scale: float = 1.0, racah: bool = True, prefunc: callable | None = None)

Bases: Model

Initializes a hyperfine spectrum Model with the given hyperfine parameters.

Parameters:

• I (float) – Integer or half-integer value of the nuclear spin

• J (ArrayLike) – A sequence of 2 spins, respectively the J value of the lower state and the J value of the higher state

• A (ArrayLike, optional) – A sequence of 2 A values, respectively for the lower and the higher state, by default [0, 0]

• B (ArrayLike, optional) – A sequence of 2 B values, respectively for the lower and the higher state, by default [0, 0]

• C (ArrayLike, optional) – A sequence of 2 C values, respectively for the lower and the higher state, by default [0, 0]

• df (float, optional) – The centroid of the spectrum, by default 0

• fwhmg (float, optional) – The Gaussian FWHM of the Voigt profile, by default 50

• fwhml (float, optional) – The Lorentzian FWHM of the Voigt profile, by default 50

• name (str, optional) – Name of the model, by default ‘HFS’

• peak (str, optional) – peak function to use, by default ‘voigt’

• peak_kwargs (dict, optional) – additional fitting parameters for skew and custom peaks

• N (int, optional) – Number of sidepeaks to be generated, by default None

• offset (float, optional) – Offset in units of x for the sidepeak, by default 0

• poisson (float, optional) – The poisson factor for the sidepeaks, by default 0

• scale (float, optional) – The amplitude of the entire spectrum, by default 1.0

• racah (bool, optional) – Use individual amplitudes are setting the Racah intensities, by default True

• prefunc (callable, optional) – Transformation to be applied on the input before evaluation, by default None

calculateFWHM() → Tuple[float, float]

Calculate the total FWHM of the profiles, with uncertainty, taking the correlations into account.

Returns:

Tuple of the form (value, uncertainty)

Return type:

Tuple[float, float]

pos() → ArrayLike

Returns the positions of the peaks in MHz in the hyperfine spectrum

Return type:

ArrayLike