NormalizedDotProductMetric

class kikuchipy.indexing.NormalizedDotProductMetric(n_experimental_patterns: int | None = None, n_dictionary_patterns: int | None = None, navigation_mask: ndarray | None = None, signal_mask: ndarray | None = None, dtype: str | dtype | type = 'float32', rechunk: bool = False)

Bases: SimilarityMetric

Similarity metric implementing the normalized dot product [Chen et al., 2015].

The metric is defined as

\[\rho = \frac {\langle \mathbf{X}, \mathbf{Y} \rangle} {||\mathbf{X}|| \cdot ||\mathbf{Y}||},\]

where \({\langle \mathbf{X}, \mathbf{Y} \rangle}\) is the dot (inner) product of the pattern vectors \(\mathbf{X}\) and \(\mathbf{Y}\).

See SimilarityMetric for the description of the initialization parameters and the list of attributes.

Attributes

Methods

NormalizedDotProductMetric.match(...)	Match all experimental patterns to all dictionary patterns and return their similarities.
NormalizedDotProductMetric.prepare_dictionary(...)	Prepare dictionary patterns before matching to experimental patterns in match().
NormalizedDotProductMetric.prepare_experimental(...)	Prepare experimental patterns before matching to dictionary patterns in match().