SimilarityMeasures (version 1.4)

LCSSCalc: Run the LCSS Algorithm on Two Trajectories Without Translations

Description

A function to calculate the longest common subsequence between two trajectories. This function does not calculate translations and only uses the given trajectories and optional translation.

Usage

LCSSCalc(traj1, traj2, pointSpacing=-1, pointDistance=20,  trans=rep(0, (dim(traj1)[2])))

Arguments

traj1

An m x n matrix containing trajectory1. Here m is the number of points and n is the dimension of the points.

traj2

A k x n matrix containing trajectory2. Here k is the number of points and n is the dimension of the points. The two trajectories are not required to have the same number of points.

pointSpacing

An integer value of the maximum index difference between trajectory1 and trajectory2 allowed in the calculation. A negative value sets the point spacing to unlimited.

pointDistance

A floating point number representing the maximum distance in each dimension allowed for points to be considered equivalent.

trans

A vector containing translations in each dimension to be applied to trajectory2 in this calculation.

Value

An integer value is returned. This represents the maximum LCSS value obtained using the variables provided. If a problem occurs, then a string containing information about the problem is returned.

Details

The LCSS algorithm calculates the largest number of equivalent points between the two trajectories when traversed in a monotone way. If a translation is given then this is applied before the calculation is done. This function is used by all of the the LCSS functions. Please see the references for more information.

References

Vlachos, M., Kollios, G. and Gunopulos, D. (2002) Discovering similar multidimensional trajectories. Paper presented at the Data Engineering, 2002. Proceedings. 18th International Conference on.

See Also

LCSS, LCSSRatio, LCSSRatioCalc, LCSSTranslation

Examples

# Creating two trajectories.
path1 <- matrix(c(0, 1, 2, 3, 0, 1, 2, 3), 4)
path2 <- matrix(c(0, 1, 2, 3, 4, 5, 6, 7), 4)

# Running the LCSS algorithm on the trajectories.
LCSSCalc(path1, path2, 2, 2, c(0, 3))