mvpa2.clfs.distance

Distance functions to be used in kernels and elsewhere

Functions

absmin_distance(a, b)	Returns dinstance max(|a-b|)
cartesian_distance(a, b)	Return Cartesian distance between a and b
corouge(streamline1, streamline2)	Mean of the mean min distances.
mahalanobis_distance(x[, y, w])	Calculate Mahalanobis distance of the pairs of points.
manhattan_distance(a, b)	Return Manhattan distance between a and b
mean_min(streamline1, streamline2)	Basic building block to compute several distances between streamlines.
one_minus_correlation(X, Y)	Return one minus the correlation matrix between the rows of two matrices.
pnorm_w(data1[, data2, weight, p, …])	Weighted p-norm between two datasets (pure Python implementation)
pnorm_w_python(data1[, data2, weight, p, …])	Weighted p-norm between two datasets (pure Python implementation)
squared_euclidean_distance(data1[, data2, …])	Compute weighted euclidean distance matrix between two datasets.