Package: DSWE 1.8.0

Yu Ding

DSWE: Data Science for Wind Energy

Data science methods used in wind energy applications. Current functionalities include creating a multi-dimensional power curve model, performing power curve function comparison, covariate matching, and energy decomposition. Relevant works for the developed functions are: funGP() - Prakash et al. (2022) <doi:10.1080/00401706.2021.1905073>, AMK() - Lee et al. (2015) <doi:10.1080/01621459.2014.977385>, tempGP() - Prakash et al. (2022) <doi:10.1080/00401706.2022.2069158>, ComparePCurve() - Ding et al. (2021) <doi:10.1016/j.renene.2021.02.136>, deltaEnergy() - Latiffianti et al. (2022) <doi:10.1002/we.2722>, syncSize() - Latiffianti et al. (2022) <doi:10.1002/we.2722>, imptPower() - Latiffianti et al. (2022) <doi:10.1002/we.2722>, All other functions - Ding (2019, ISBN:9780429956508).

Authors:Nitesh Kumar [aut], Abhinav Prakash [aut], Yu Ding [aut, cre], Effi Latiffianti [ctb, cph], Ahmadreza Chokhachian [ctb, cph]

DSWE_1.8.0.tar.gz
DSWE_1.8.0.zip(r-4.7-x86_64)DSWE_1.8.0.zip(r-4.7-arm64)DSWE_1.8.0.zip(r-4.6-x86_64)DSWE_1.8.0.zip(r-4.6-arm64)DSWE_1.8.0.zip(r-4.5-x86_64)
DSWE_1.8.0.tgz(r-4.6-x86_64)DSWE_1.8.0.tgz(r-4.6-arm64)DSWE_1.8.0.tgz(r-4.5-x86_64)DSWE_1.8.0.tgz(r-4.5-arm64)
DSWE_1.8.0.tar.gz(r-4.7-arm64)DSWE_1.8.0.tar.gz(r-4.7-x86_64)DSWE_1.8.0.tar.gz(r-4.6-arm64)DSWE_1.8.0.tar.gz(r-4.6-x86_64)
DSWE_1.8.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
DSWE/json (API)

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

Bug tracker:https://github.com/tamu-aml/dswe-package/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • data1 - Wind Energy data set containing 47,542 data points
  • data2 - Wind Energy data set containing 48,068 data points

On CRAN:

Conda:

openblascpp

4.34 score 11 stars 1 scripts 408 downloads 1 mentions 16 exports 89 dependencies

Last updated from:d370677c11. Checks:13 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING176
linux-devel-x86_64WARNING266
source / vignettesOK301
linux-release-arm64WARNING194
linux-release-x86_64WARNING204
macos-release-arm64WARNING261
macos-release-x86_64WARNING439
macos-oldrel-arm64WARNING211
macos-oldrel-x86_64WARNING548
windows-devel-arm64WARNING403
windows-devel-x86_64WARNING233
windows-release-arm64WARNING407
windows-release-x86_64WARNING210
windows-oldrel-x86_64WARNING173
wasm-releaseOK148

Exports:AMKComparePCurveComputeWeightedDifferenceCovMatchdeltaEnergyfunGPimptPowerKnnPCFitKnnPredictKnnUpdateSplinePCFitSvmPCFitsyncSizetempGPupdateDataXgbPCFit

Dependencies:askpassbase64encBHbslibcachemclassclicpp11crosstalkcurldata.tabledigestdotCall64dplyre1071evaluatefarverfastmapfieldsFNNfontawesomefsgenericsggplot2glueGpGpGPvecchiagssgtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonlitekernlabKernSmoothknitrlabelinglaterlatticelazyevallifecyclemagrittrmapsMASSMatrixmatrixStatsmemoisemimemixtoolsnlmeopensslotelpillarpkgconfigplotlypromisesproxypurrrR6rappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownS7sassscalessegmentedspamsparseinvstringistringrsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxgboostyaml