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mlampros/vmdecomp

By mlampros

•Updated about 1 year ago

R package for 'Variational Mode Decomposition' (1- and 2-dimensional)

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mlampros/vmdecomp repository overview

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⁠VMDecomp


The VMDecomp R package is the RcppArmadillo implementation of the "Variational Mode Decomposition" Matlab code⁠ in R. More details on the functionality of VMDecomp can be found in the package Documentation⁠, Vignette⁠ and blog post⁠.


⁠Examples:

Variational Mode Decomposition (including residuals)



require(VMDecomp)
data(arrhythmia)

alpha = 2000       # moderate bandwidth constraint
tau = 0            # noise-tolerance (no strict fidelity enforcement)
K = 9              # 9 modes
DC = FALSE         # no DC part imposed
init = 1           # initialize omegas uniformly
tol = 1e-6

vec_arrhythmia = arrhythmia[['MLII']]

set.seed(1)
arr_vmd = vmd(data = vec_arrhythmia, 
              alpha = alpha,
              tau = tau, 
              K = K, 
              DC = DC,
              init = init, 
              tol = tol,
              verbose = TRUE)
              
imfs = data.table::data.table(arr_vmd$u)
colnames(imfs) = glue::glue("IMF_{1:ncol(imfs)}")
imfs$residual = rowSums(imfs) - vec_arrhythmia

round(imfs, digits = 5)

#           IMF_1    IMF_2    IMF_3   IMF_4   IMF_5    IMF_6    IMF_7    IMF_8    IMF_9 residual
#     1: -0.06947  0.07831  0.13355 0.14031 0.10371  0.05622 -0.00143 -0.09686 -0.00629 -0.01194
#     2: -0.06971  0.07765  0.13199 0.13698 0.09920  0.05226 -0.00062 -0.07683 -0.01055 -0.00963
#     3: -0.07016  0.07639  0.12896 0.13047 0.09046  0.04475  0.00097 -0.04075 -0.01487 -0.00377
#     4: -0.07068  0.07468  0.12466 0.12114 0.07810  0.03447  0.00329  0.00427 -0.01331  0.00662
#     5: -0.07108  0.07273  0.11937 0.10947 0.06297  0.02246  0.00622  0.04929 -0.00211  0.01932
#    ---                                                                                        
#  9996: -0.07001 -0.13154 -0.24738 0.18826 0.03381 -0.07354  0.00076  0.03773  0.01426  0.01234
#  9997: -0.06980 -0.13333 -0.25498 0.21256 0.03400 -0.11214  0.05833 -0.00481  0.01450  0.00432
#  9998: -0.06951 -0.13452 -0.26056 0.23154 0.03414 -0.14316  0.10925 -0.04580  0.00791 -0.00570
#  9999: -0.06934 -0.13534 -0.26432 0.24447 0.03413 -0.16496  0.14706 -0.07813 -0.00137 -0.00780
# 10000: -0.06932 -0.13581 -0.26626 0.25095 0.03402 -0.17629  0.16708 -0.09601 -0.00797  0.00040


Estimation of the K-modes Parameter (correlation threshold of 0.1 and a minimum K of 2)



require(VMDecomp)
data(arrhythmia)

default_vmd_params = list(alpha = 2000,
                          tau = 0,
                          DC = FALSE,
                          init = 1,
                          tol = 1e-6)

res_k = estimate_k_modes(signal_1d = arrhythmia[['MLII']],
                         cor_thresh = 0.1,
                         default_vmd_params = default_vmd_params,
                         min_K = 2,
                         seed = 1,
                         verbose = TRUE)
                         
# VMD based on a K of '2' will be computed ... 
# VMD based on a K of '3' will be computed ... 
# VMD based on a K of '4' will be computed ... 
# VMD based on a K of '5' will be computed ... 
# VMD based on a K of '6' will be computed ... 
# VMD based on a K of '7' will be computed ... 
# VMD based on a K of '8' will be computed ... 
# VMD based on a K of '9' will be computed ... 
# Optimal K parameter: '8'  Pre-specified correlation coefficient threshold: '0.1'
# Elapsed time: 0 hours and 1 minutes and 19 seconds.

res_k
# [1] 8


⁠Installation:

To install the package from CRAN use,

install.packages("VMDecomp")


or download the latest version from Github using the pak package,


pak::pak('mlampros/VMDecomp')


⁠Docker Image

Docker images of the VMDecomp package are available to download from my dockerhub⁠ account. The images come with Rstudio and the R-development version (latest) installed. The whole process was tested on Ubuntu 18.04. To pull & run the image do the following,



docker pull mlampros/vmdecomp:rstudiodev

docker run -d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 mlampros/vmdecomp:rstudiodev


The user can also bind a home directory / folder to the image to use its files by specifying the -v command,



docker run -d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 -v /home/YOUR_DIR:/home/rstudio/YOUR_DIR mlampros/vmdecomp:rstudiodev



The USER defaults to rstudio but you have to give your PASSWORD of preference (see rocker-project.org⁠ for more information).


Open your web-browser and depending where the docker image was build / run give,


1st. Option on your personal computer,


http://0.0.0.0:8787 


2nd. Option on a cloud instance,


http://Public DNS:8787


to access the Rstudio console in order to give your username and password.


⁠Similar Projects:

⁠Citation:

If you use the VMDecomp R package in your paper or research please cite both VMDecomp and the original articles / software https://CRAN.R-project.org/package=VMDecomp:


@Manual{,
  title = {{VMDecomp}: Variational Mode Decomposition using R},
  author = {Lampros Mouselimis},
  year = {2025},
  note = {R package version 1.0.2},
  url = {https://CRAN.R-project.org/package=VMDecomp},
}

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docker pull mlampros/vmdecomp:buildcache