xdem.coreg.DirectionalBias

class xdem.coreg.DirectionalBias(angle=0, fit_or_bin='bin_and_fit', fit_func='nfreq_sumsin', fit_optimizer=<function curve_fit>, bin_sizes=10, bin_statistic=<function nanmedian>, bin_apply_method='linear')

Bias correction for directional biases, for example along- or across-track of satellite angle.

__init__(angle=0, fit_or_bin='bin_and_fit', fit_func='nfreq_sumsin', fit_optimizer=<function curve_fit>, bin_sizes=10, bin_statistic=<function nanmedian>, bin_apply_method='linear')

Instantiate a directional bias correction.

Parameters

• angle (float) – Angle in which to perform the directional correction (degrees).

• fit_or_bin (Union[Literal['bin_and_fit'], Literal['fit'], Literal['bin']]) – Whether to fit or bin. Use “fit” to correct by optimizing a function or “bin” to correct with a statistic of central tendency in defined bins.

• fit_func (Union[Callable[..., ndarray[Any, dtype[floating[Any]]]], Literal['norder_polynomial'], Literal['nfreq_sumsin']]) – Function to fit to the bias with variables later passed in .fit().

• fit_optimizer (Callable[..., tuple[ndarray[Any, dtype[floating[Any]]], Any]]) – Optimizer to minimize the function.

• bin_sizes (int | dict[str, Union[int, Iterable[float]]]) – Size (if integer) or edges (if iterable) for binning variables later passed in .fit().

• bin_statistic (Callable[[ndarray[Any, dtype[floating[Any]]]], floating[Any]]) – Statistic of central tendency (e.g., mean) to apply during the binning.

• bin_apply_method (Union[Literal['linear'], Literal['per_bin']]) – Method to correct with the binned statistics, either “linear” to interpolate linearly between bins, or “per_bin” to apply the statistic for each bin.

Methods

__init__([angle, fit_or_bin, fit_func, ...])	Instantiate a directional bias correction.
apply(dem[, bias_vars, transform, crs, resample])	Apply the estimated transform to a DEM.
apply_pts(coords)	Apply the estimated transform to a set of 3D points.
copy()	Return an identical copy of the class.
error(reference_dem, dem_to_be_aligned[, ...])	Calculate the error of a coregistration approach.
fit(reference_dem, dem_to_be_aligned[, ...])	Estimate the coregistration transform on the given DEMs.
fit_pts(reference_dem, dem_to_be_aligned[, ...])	Estimate the coregistration transform between a DEM and a reference point elevation data.
residuals(reference_dem, dem_to_be_aligned)	Calculate the residual offsets (the difference) between two DEMs after applying the transformation.