CrossCorrelation#

class CrossCorrelation(target, template_coordinates, template_weights, template_mask_coordinates=None, target_mask=None, negate_score=True, return_gradient=False, interpolation_order=1, **kwargs)[source]#

Bases: _MatchCoordinatesToDensity

Computes the Cross-Correlation score as:

\[\text{score} = \text{target_weights} \cdot \text{template_weights}\]
Parameters:
targetNDArray

A d-dimensional target to match the template coordinate set to.

template_coordinatesNDArray

Template coordinate array with shape (d,n).

template_weightsNDArray

Template weight array with shape (n,).

template_mask_coordinatesNDArray, optional

Template mask coordinates with shape (d,n).

target_maskNDArray, optional

A d-dimensional mask to be applied to the target.

negate_scorebool, optional

Whether the final score should be multiplied by negative one. Default is True.

return_gradientbool, optional

Invoking __call_ returns a tuple of score and parameter gradient. Default is False.

**kwargsDict, optional

Keyword arguments propagated to downstream functions.

Methods

CrossCorrelation.grad()

Calculate the gradient of the cost function w.r.t.

CrossCorrelation.rotate_array(arr, ...[, ...])

CrossCorrelation.score(x)

Compute the matching score for the given transformation parameters.

CrossCorrelation.score_angles(x)

Computes the score after a given rotation.

CrossCorrelation.score_translation(x)

Computes the score after a given translation.