| Title: | Implements Generic Composite Similarity Measure |
| Version: | 0.2.0 |
| Description: | Provides implementation of the generic composite similarity measure (GCSM) described in Liu et al. (2020) <doi:10.1016/j.ecoinf.2020.101169>. The implementation is in C++ and uses 'RcppArmadillo'. Additionally, implementations of the structural similarity (SSIM) and the composite similarity measure based on means, standard deviations, and correlation coefficient (CMSC), are included. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.3 |
| URL: | https://github.com/liuyadong/GCSM |
| BugReports: | https://github.com/liuyadong/GCSM/issues |
| LinkingTo: | Rcpp, RcppArmadillo |
| Imports: | Rcpp |
| Suggests: | testthat |
| NeedsCompilation: | yes |
| Packaged: | 2025-10-14 17:11:07 UTC; yadong |
| Author: | Yadong Liu [aut, cre] |
| Maintainer: | Yadong Liu <liuyadong828@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-10-14 17:20:02 UTC |
Composite similarity between vectors
Description
Compute composite measures, GCSM or CMSC, between two vectors.
Usage
cmsc( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")cmsc_e1( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")cmsc_e2( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")gcsm( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")Arguments
x | A vector. |
y | The other vector. |
rescale | Rescale or not before computation. |
xmin,xmax,ymin,ymax | Normalization parameters. If |
comp | Variable to return. If |
Details
These functions compute composite measures between vectors. Missing valuesare omitted. Normalization parameters are used to rescalex andy, anddetermine the global minimum (min) and maximum (max). Ifrescale isTRUE,x andy are rescaled to(x-xmin)/(xmax-xmin) and(y-ymin)/(ymax-ymin); and setmin=0,max=1. IfFALSE,min=min(xmin,ymin),max=max(xmax,ymax).
Value
A number.
Examples
x = runif(9)gcsm(x, x)cmsc(x, x)# mean shiftgcsm(x, x - 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)cmsc(x, x - 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)gcsm(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)cmsc(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)## dissimilarityy = 1 - x # y is the perfect antianalog of xgcsm(y, x)gcsm(y, x - 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)gcsm(y, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)# random noisenoise = rnorm(9, mean = 0, sd = 0.2)gcsm(x, x + noise, xmin = 0, xmax = 1, ymin = 0, ymax = 1)cmsc(x, x + noise, xmin = 0, xmax = 1, ymin = 0, ymax = 1)## dissimilaritygcsm(y, x + noise, xmin = 0, xmax = 1, ymin = 0, ymax = 1)Composite similarity on spatial windows
Description
Compute composite measures, GCSM, CMSC or SSIM, on spatial windows.
Usage
cmsc_sw( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, ksize = 9, globe = FALSE, comp = "si")cmsc_e1_sw( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, ksize = 9, globe = FALSE, comp = "si")cmsc_e2_sw( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, ksize = 9, globe = FALSE, comp = "si")gcsm_sw( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, ksize = 9, globe = FALSE, comp = "si")ssim_sw( x, y, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, ksize = 11, sigma = 1.5, globe = FALSE, comp = "si")Arguments
x | A matrix. |
y | The other matrix. |
rescale | Rescale or not before computation. |
xmin,xmax,ymin,ymax | Normalization parameters. If |
ksize | Side length of spatial windows. |
globe | Are data at the global scale? If |
comp | Variable to return. If |
sigma | Standard deviation of Gaussian weighting functiondepending on the distance between the cell and kernel center. |
Details
These functions slide the spatial window over space. Missing values areomitted. Normalization parameters are used to rescalex andy, anddetermine the global minimum (min) and maximum (max). Ifrescale isTRUE,x andy are rescaled to(x-xmin)/(xmax-xmin) and(y-ymin)/(ymax-ymin); and setmin=0,max=1. IfFALSE,min=min(xmin,ymin),max=max(xmax,ymax). OpenMP is used for parallelcomputing.
Value
A matrix.
Examples
x = matrix(runif(36), nrow = 6, ncol = 6)gcsm_sw(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1, ksize = 3)cmsc_sw(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1, ksize = 3)ssim_sw(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1, ksize = 3)Composite similarity on temporal windows
Description
Compute composite measures, GCSM or CMSC, on temporal windows.
Usage
cmsc_tw( xxx, yyy, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")cmsc_e1_tw( xxx, yyy, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")cmsc_e2_tw( xxx, yyy, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")gcsm_tw( xxx, yyy, rescale = FALSE, xmin = NA_real_, xmax = NA_real_, ymin = NA_real_, ymax = NA_real_, comp = "si")Arguments
xxx | A 3-d array with the 3rd dimension representing time. |
yyy | The other 3-d array. |
rescale | Rescale or not before computation. |
xmin,xmax,ymin,ymax | Normalization parameters. If |
comp | Variable to return. If |
Details
These functions slide the temporal window over space. Missing values areomitted. Normalization parameters are used to rescalexxx andyyy, anddetermine the global minimum (min) and maximum (max). Ifrescale isTRUE,xxx andyyy are rescaled to(xxx-xmin)/(xmax-xmin) and(yyy-ymin)/(ymax-ymin); and setmin=0,max=1. IfFALSE,min=min(xmin,ymin),max=max(xmax,ymax). OpenMP is used for parallelcomputing.
Value
A matrix.
Examples
x = array(runif(81), dim = c(3, 3, 9))gcsm_tw(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)cmsc_tw(x, x + 0.2, xmin = 0, xmax = 1, ymin = 0, ymax = 1)