xdem.coreg.VerticalShift

class xdem.coreg.VerticalShift(vshift_reduc_func=<function median>, subsample=1.0)

Vertical translation alignment.

Estimates the mean vertical offset between two elevation datasets based on a reductor function (median, mean, or any custom reductor function).

The estimated vertical shift is stored in the self.meta key “shift_z” (in unit of the elevation dataset inputs, typically meters).

__init__(vshift_reduc_func=<function median>, subsample=1.0)

Instantiate a vertical shift alignment object.

Parameters:

• vshift_reduc_func (Callable[[ndarray[Any, dtype[floating[Any]]]], floating[Any]]) – Reductor function to estimate the central tendency of the vertical shift. Defaults to the median.

• subsample (float | int) – Subsample the input for speed-up. <1 is parsed as a fraction. >1 is a pixel count.

Methods

__init__([vshift_reduc_func, subsample])	Instantiate a vertical shift alignment object.
apply(elev[, bias_vars, resample, ...])	Apply the estimated transform to a DEM.
centroid()	Get the centroid of the coregistration, if defined.
copy()	Return an identical copy of the class.
error(reference_elev, to_be_aligned_elev[, ...])	Calculate the error of a coregistration approach.
fit(reference_elev, to_be_aligned_elev[, ...])	Estimate the coregistration transform on the given DEMs.
fit_and_apply(reference_elev, to_be_aligned_elev)	Estimate and apply the coregistration to a pair of elevation data.
from_matrix(matrix)	Instantiate a generic Coreg class from a transformation matrix.
from_translation([x_off, y_off, z_off])	Instantiate a generic Coreg class from a X/Y/Z translation.
residuals(reference_elev, to_be_aligned_elev)	Calculate the residual offsets (the difference) between two DEMs after applying the transformation.
to_matrix()	Convert the transform to a 4x4 transformation matrix.

Attributes

is_affine	Check if the transform be explained by a 3D affine transform.
meta	Metadata dictionary of the coregistration.