wcc {ptw}R Documentation

Weighted auto- and cross-correlation measures

Description

Functions to calculate weighted auto- and cross-correlation measures. The wcc is a suitable measure for the similarity of two patterns when features may be shifted. Identical patterns lead to a wcc value of 1.

Usage

wcc(pattern1, pattern2, trwdth, wghts = NULL, acors1 = NULL, acors2 = NULL)
wac (pattern1, trwdth, wghts = NULL)

Arguments

pattern1, pattern2 input patterns, typically spectra. Vectors
trwdth triangle width, given in the number of data points
wghts optional weights vector, will be calculated from triangle width if necessary. Sometimes it is more efficient to pre-calculate it and give it as an argument
acors1, acors2 autocorrelations of the input patterns. If not provided, they are calculated

Details

wcc and wac are defined such that the triangle width stands for the number of points on one side of and including the current point. Thus, a trwdth of 0 signifies a non-existent triangle and results in an error; a trwdth equal to 1 only includes the current point with weight 1 and no neighbouring points.

Value

One number, the weighted autocorrelation or crosscorrelation

Author(s)

Ron Wehrens

References

de Gelder, R., Wehrens, R. and Hageman, J.A. A generalized expression for the similarity spectra: application to powder diffraction pattern classification. J. Comput. Chem., 22(3), 273-289, 2001.

Examples

data(gaschrom)
wcc(gaschrom[1,], gaschrom[2,], 20)

[Package ptw version 1.0-0 Index]