estimate_xtilt_ztilt#

EBSDDetector.estimate_xtilt_ztilt(degrees: bool = False, is_outlier: list | tuple | ndarray | None = None) → float | Tuple[float, float][source]#

Estimate the tilts about the detector \(X_d\) and \(Z_d\) axes.

These tilts bring the sample plane normal into coincidence with the detector plane normal (but in the opposite direction) [Winkelmann et al., 2020].

See the reference frame tutorial for details on the detector sample geometry.

Estimates are found by fitting a hyperplane to pc using singular value decomposition.

Parameters:
degrees

Whether to return the estimated tilts in radians (False, default) or degrees (True).

is_outlier

Boolean array with True for PCs to not include in the fit. If not given, all PCs are used. Must be of navigation_shape.

Returns:
x_tilt

Estimated tilt about detector \(X_d\) in radians (degrees=False) or degrees (degrees=True).

z_tilt

Estimated tilt about detector \(Z_d\) in radians (degrees=False) or degrees (degrees=True).

See also

estimate_xtilt, fit_pc

Notes

This method is adapted from Aimo Winkelmann’s function fit_plane() in the xcdskd Python package. Its use is described in [Winkelmann et al., 2020].

Winkelmann refers to Gander & Hrebicek, “Solving Problems in Scientific Computing”, 3rd Ed., Chapter 6, p. 97 for the implementation of the hyperplane fitting.

Examples using EBSDDetector.estimate_xtilt_ztilt#

Estimate tilts about the detector x and z axis

Estimate tilts about the detector x and z axis