R: Calculate RMS or WCC values on a grid

ptwgrid {ptw} | R Documentation

## Calculate RMS or WCC values on a grid

### Description

Calculates values of the chosen optimization criterion (RMS or WCC) on a grid defined by the coefficients of the warping function.

### Usage

    ptwgrid(ref, samp, selected.traces,
    	coef.mins, coef.maxs, coef.lengths,
    	optim.crit = c("WCC", "RMS"),
    	smooth.param = 1e05,
    	trwdth = 20)

### Arguments

`ref` | reference. Either a vector (containing one reference signal) or a matrix (one reference per row). If more than one reference is specified, the number of reference signals must equal the number of sample signals
`samp` | sample. A vector (containing one sample signal) or a matrix (one sample per row). If more than one sample is specified, the number of sample signals must equal the number of reference signals
`selected.traces` | optional vector containing the row numbers to use from `ref` (if more than one reference signal is specified) and `samp`
`coef.mins` | a vector containing the respective minimal values of coefficients for the grid. The first number is the minimal zeroth-order coefficient (i.e., a constant shift); further numbers indicate the minimal linear, quadratic, ... stretches
`coef.maxs` | a vector containing the maximal values of coefficients for the grid
`coef.lengths` | a vector of the same length as coef.maxs and coef.mins containing the number of steps in which to vary the respective coefficients between their minimum and maximum value
`optim.crit` | either `"WCC"` or `"RMS"`. In both cases, the optimal value of the alignment leads to a value of 0. For "WCC", this means that `1 - WCC` is optimized rather than `WCC` (where the optimal value equals 1)
`smooth.param` | smoothing parameter for smoothing the reference and sample when `optim.crit` equals `"RMS"`. If no smoothing is required, set this to 0

.

`trwdth` | the width of the triangle in the WCC criterion during the optimization, given as a number of data points. Default: 20

### Details

In contrast to ptw, only the three situations leading to one warping function are distinguished here:

1. One sample and one reference;

2. Several samples, warped to an equal number of references (pair-wise);

3. Several samples, warped to a single reference.

Which situation is applicable is determined from the dimensions of `ref` and `samp`.

### Value

An array of dimension `length(coef.mins)` and maximal indices per dimension specified by `coef.lengths`

### Author(s)

Tom Bloemberg, Jan Gerretzen, Ron Wehrens

### See Also

`ptw`

### Examples

      ## Not run:
      data(gaschrom)
      mygrid <- ptwgrid(gaschrom[1,], gaschrom[16,],
                        coef.mins = c(-10, .9), coef.max = c(10, 1.1),
                        coef.lengths = c(21, 21))
      image(seq(-10, 10, length = 21),
            seq(.9, 1.1, length = 21),
            mygrid)

    ## End(Not run)

[Package ptw version 1.9-12 Index]