agepy.mag.hysteresis.linear_correction

linear_correction(*hysteresis, saturation_percentage=10)

Subtracts a linear fit to the saturation regions.

Linear fit is performed on the saturation region with respect to the magnetic field. The saturation region is defined by a percentage value relative to the number of data points of a single branch. A function f(x) = fit_slope * x is then subtracted from the magnetization. Hysteresis data can be supplied either as one tuple containing the magntic field and magnetization repectively or as multiple tuples containing the two hysteresis branches.

Parameters:

*hysteresis: ArrayLike

One or two 2-D arrays of shape (2, n) containing the magnetic field and magnetization of length n in the first axis.

saturation_percentage: float, default 10

Percentage value of points in at the end of the hysteresis branches belonging to the saturation region.

Returns:

NDArray

The corrected magnetization values. If hysteresis is supplied as whole sequence , then a 1-D array with the same length as the magnetization is returned. If hysteresis is two branches, a 2-D array is returned containing the two magnetization branches in the first axis.

Return type:

ndarray[Any, dtype[TypeVar(_ScalarType_co, bound= generic, covariant=True)]]

Examples

Viable example inputs.

>>> linear_correction((H, M), saturation_percentage=10)
array([<M-values>])

>>> linear_correction((H1, M1), (H2, M2), saturation_percentage=10)
array([[<M1-values>], [<M2-values>]])

>>> hyst = array([H, M])
>>> linear_correction(hyst, saturation_percentage=10)
array([<M-values>])

>>> hyst = array([[H1, M1], [H2, M2]])
>>> linear_correction(*hyst, saturation_percentage=10)
array([[<M1-values>], [<M2-values>]])