Package: SOMEnv 0.1.1

Sabina Licen

SOMEnv: SOM Algorithm for the Analysis of Multivariate Environmental Data

Analysis of multivariate environmental high frequency data by Self-Organizing Map and k-means clustering algorithms. By means of the graphical user interface it provides a comfortable way to elaborate by self-organizing map algorithm rather big datasets (txt files up to 100 MB ) obtained by environmental high-frequency monitoring by sensors/instruments. The functions present in the package are based on 'kohonen' and 'openair' packages implemented by functions embedding Vesanto et al. (2001) <http://www.cis.hut.fi/projects/somtoolbox/package/papers/techrep.pdf> heuristic rules for map initialization parameters, k-means clustering algorithm and map features visualization. Cluster profiles visualization as well as graphs dedicated to the visualization of time-dependent variables Licen et al. (2020) <doi:10.4209/aaqr.2019.08.0414> are provided.

Authors:Sabina Licen [aut, cre], Marco Franzon [aut], Tommaso Rodani [aut], Pierluigi Barbieri [aut]

SOMEnv_0.1.1.tar.gz
SOMEnv_0.1.1.zip(r-4.5)SOMEnv_0.1.1.zip(r-4.4)SOMEnv_0.1.1.zip(r-4.3)
SOMEnv_0.1.1.tgz(r-4.4-any)SOMEnv_0.1.1.tgz(r-4.3-any)
SOMEnv_0.1.1.tar.gz(r-4.5-noble)SOMEnv_0.1.1.tar.gz(r-4.4-noble)
SOMEnv_0.1.1.tgz(r-4.4-emscripten)SOMEnv_0.1.1.tgz(r-4.3-emscripten)
SOMEnv.pdf |SOMEnv.html✨
SOMEnv/json (API)

# Install 'SOMEnv' in R:
install.packages('SOMEnv', repos = c('https://somenv.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/somenv/somenv/issues

On CRAN:

2.70 score 1 stars 158 downloads 25 exports 99 dependencies

Last updated 4 years agofrom:abce4cffa6. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-winNOTENov 12 2024
R-4.5-linuxNOTENov 12 2024
R-4.4-winNOTENov 12 2024
R-4.4-macNOTENov 12 2024
R-4.3-winNOTENov 12 2024
R-4.3-macNOTENov 12 2024

Exports:BmusCentrBmusClusBoxClusBoxUnitsCodeCoordDailyBarFreqFreqDFreqMHexagonsHexagonsClusHexagonsVarHexaHitsHexaHitsQuantHexaQerrsHexaQerrsQuantkmeans_clustersRProgNClusChangeparamQuantsom_dimRsom_initRsom_umatRSomEnvGUISOMtopolUmatGraph

Dependencies:base64encbitbit64bslibcachemclicliprclustercolorspacecolourpickercommonmarkcpp11crayondata.tabledeldirdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtablehexbinhighrhmshtmltoolshtmlwidgetshttpuvinterpisobandjpegjquerylibjsonliteknitrkohonenlabelinglaterlatticelatticeExtralifecyclelubridatemagrittrmapprojmapsMASSMatrixmemoisemgcvmimeminiUImunsellnlmeopenairpillarpkgconfigplyrpngprettyunitsprogresspromisespurrrR6rappdirsRColorBrewerRcppRcppEigenreadrrlangrlistrmarkdownsassscalesshinyshinycssloadersshinycustomloadershinyjssourcetoolsstringistringrtibbletidyrtidyselecttimechangetinytextzdbutf8vctrsviridisLitevroomwithrxfunXMLxtableyaml

Readme and manuals

Help Manual

Help pageTopics
BMUs of the cluster centroidsBmusCentr
Cluster assignment for the experimental dataBmusClus
Boxplot of prototype variables split by cluster and variableBoxClus
Boxplot of prototype variables split by clusterBoxUnits
Custom color sequence for clustersClusCol
Prototype coordinates for graphCodeCoord
Plot of daily percentages for each clusterDailyBar
Evaluate Davis-Bouldin index for the cluster split of data inputdb_indexR
Percentage frequency for each clusterFreq
Daily percentage frequency for each clusterFreqD
Monthly percentage frequency for each clusterFreqM
Function to draw an hexagon around a pointHexa
Function to draw an hexagonal SOM mapHexagons
SOM map with clustersHexagonsClus
HeatmapsHexagonsVar
Hits distribution on the SOM mapHexaHits
Hits distribution on the SOM mapHexaHitsQuant
Realtive quantization error distribution on the SOM mapHexaQerrs
Realtive quantization error distribution on the SOM mapHexaQerrsQuant
K-means algorithm applied for different values of clusterskmeans_clustersRProg
Custom number sequence for clustersNClusChange
Basic statistics of values present in the input vectorparamQuant
Calculate map dimensionssom_dimR
Calculate initialization matrix for SOM trainingsom_initR
K-means algorithm applied for a specific number of clusterssom_kmeansRProg
Evaluate pairwise distance matrix for the given codebooksom_mdistR
Unified distance matrix for the SOM mapsom_umatR
The function starts the SOMEnv GUISomEnvGUI
Topographical error for the SOM mapSOMtopol
U-matrix plotUmatGraph