Out-of-the-Box Fitting Functions¶

fitting_functions_list.linear(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2050>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2110>, float]¶

Simple linear fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] + a[1] * x

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 2 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.constant(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2350>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2410>, float]¶

Constant fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 1 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.parabolic(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2650>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2710>, float]¶

Parabolic fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] + a[1] * x + a[2] * x ^ 2

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 3 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.straight_power(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2950>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2a10>, float]¶

Represent fitting of y ~ x^n.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] * (x + a[1]) ^ a[2] + a[3]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 4 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.inverse_power(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2c50>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2d10>, float]¶

Represent fitting of y ~ x^(-n).

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] / (x + a[1]) ^ a[2] + a[3]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 4 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.polynomial() → eddington.fitting_function_class.FittingFunction¶

Creates a polynomial fitting function with parameters as coefficients.

Parameters:	n (int) – Degree of the polynomial.
Returns:	a polynomial fitting function
Return type:	FittingFunction
Raises:	FittingFunctionLoadError – Raised when trying to load a polynomial with negative degree.

fitting_functions_list.hyperbolic(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c2f50>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8050>, float]¶

Hyperbolic fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] / (x + a[1]) + a[2]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 3 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.exponential(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8290>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8350>, float]¶

Exponential fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] * exp(a[1] * x) + a[2]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 3 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.sin(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8890>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8950>, float]¶

Sine fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] * sin(a[1] * x + a[2]) + a[3]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 4 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.cos(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8590>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8650>, float]¶

Cosines fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] * cos(a[1] * x + a[2]) + a[3]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 4 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.normal(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8b90>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8c50>, float]¶

Normal distribution fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] * exp( - ((x - a[1]) / a[2]) ^ 2) + a[3]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 4 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`

fitting_functions_list.poisson(x: Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8e90>, float]) → Union[<sphinx.ext.autodoc.importer._MockObject object at 0x7fb3a80c8f50>, float]¶

Poisson fitting function.

param a: Parameters to be fitted

type a: np.ndarray

param x: Value to be evaluated by the function

type x: float or np.ndarray

return: evaluation value or values

rtype: float or np.ndarray

Syntax: y = a[0] * (a[1] ^ x) * exp(-a[1]) / gamma(x+1) + a[2]

Parameters:	a (`numpy.ndarray`) – Coefficients array of length 3 x (`numpy.ndarray` or `float`) – Free parameter
Returns:	`numpy.ndarray` or `float`