Distance functions to be used in kernels and elsewhere


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
manhatten_distance(\*args, \*\*kwargs) DEPRECATED: Use correctly spelled manhattan_distance instead
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 (scipy.weave 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.


deprecated([extra]) Decorator to mark a function or class as deprecated.