Manhattandist

Purpose

Calculates Manhattan Distance between Samples (rows) of a Dataset Object (DSO) or a matrix.

Synopsis

distances = manhattandist(x)

distances = manhattandist(x,basis)

distances = manhattandist(x,options)

distances = manhattandist(x,basis,options)

Description

Calculates the Manhattan Distance, sum of the absolute value differences, from each row to every other row in the supplied matrix or, optionally, all rows of (x) to all rows in a second matrix (basis).

Inputs

• x = A DSO or a matrix.

Optional Inputs

• basis = A second DSO/matrix to compare the first DSO/matrix against when calculating Manhattan distance.
• options = Discussed below.

Outputs

• distances = A m-by-m matrix containing the comprehensive calculated Manhattan distances between samples.

Options

options = A structure array with the following fields:

• waitbar: [{'auto'}| 'on' | 'off' ], display waitbar. 'Auto' setting will automatically display a waitbar if computation takes longer than 3 seconds.
• diag: {default: 0} Defines the values to be used when comparing a sample to itself. Technically this distance is zero however in some instances, using an alternate value (e.g.: inf) is useful for flagging these self-calculated distances.

See Also

analysis, analysis_GUI, cluster, pca, simca, gcluster