# SimLoop: Loop Over and Test Trajectories With Different Translations In SimilarityMeasures: Trajectory Similarity Measures

## Description

Function to loop over and test the trajectories using the different translations in each dimension. This is used by the LCSS function to test all of the n dimensional translations. Do not call this function directly.

## Usage

 ```1 2 3``` ```SimLoop(traj1, traj2, pointSpacing, pointDistance, spacing, similarity, translations, dimensions, dimLeft=dimensions, currentTrans=rep(0, dimensions)) ```

## 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. `pointDistance` A floating point number representing the maximum distance in each dimension allowed for points to be considered equivalent. `spacing` The integer spacing between each translation that will be tested. `similarity` A vector containing the current best similarity and translations calculated. `translations` A list of vectors containing the translations in each dimension. `dimensions` An integer representing the number of dimensions being used for the calculation. `dimLeft` An integer number of dimensions which have not been looped over yet. `currentTrans` A vector containing the current translation being tested.

## Details

This function is used to loop over the n dimensions for the `LCSS` function. This function should not be called directly.

## Value

Returns the current best LCSS value and the translations that created this as a vector.

## Author(s)

Kevin Toohey

`LCSS`, `LCSSRatio`, `LCSSRatioCalc`, `LCSSTranslation`, `LCSSCalc`
 ```1 2 3 4 5 6``` ```# 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. LCSS(path1, path2, 2, 2, 0.5) ```