Package: tensorA 0.36.2.1

K. Gerald van den Boogaart
tensorA: Advanced Tensor Arithmetic with Named Indices
Provides convenience functions for advanced linear algebra with tensors and computation with data sets of tensors on a higher level abstraction. It includes Einstein and Riemann summing conventions, dragging, co- and contravariate indices, parallel computations on sequences of tensors.
Authors:
tensorA_0.36.2.1.tar.gz
tensorA_0.36.2.1.tar.gz(r-4.7-arm64)tensorA_0.36.2.1.tar.gz(r-4.7-x86_64)tensorA_0.36.2.1.tar.gz(r-4.6-arm64)tensorA_0.36.2.1.tar.gz(r-4.6-x86_64)
tensorA_0.36.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
tensorA/json (API)
| # Install 'tensorA' in R: |
| install.packages('tensorA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:5138ccc96d. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 101 | ||
| linux-devel-x86_64 | OK | 103 | ||
| source / vignettes | OK | 156 | ||
| linux-release-arm64 | OK | 105 | ||
| linux-release-x86_64 | OK | 107 | ||
| wasm-release | OK | 89 |
Exports:-.tensor[.tensor[[.tensor[[<-.tensor*.tensor/.tensor%e%%e%.tensor%r%%r%.tensor^.tensor+.tensor|.tensor$.tensoradd.tensoras.contravariateas.contravariate.characteras.covariateas.covariate.characteras.tensoras.tensor.defaultas.tensor.tensorbind.tensorchol.tensorcontranamedelta.tensordiag.tensordiagmul.tensordim<-.tensordimnames.tensordimnames<-.tensordrag.tensoreinstein.tensorftable.tensorinv.tensoris.contravariateis.contravariate.characteris.contravariate.numericis.contravariate.tensoris.covariateis.covariate.characteris.covariate.numericis.covariate.tensoris.tensorlevel.tensormargin.tensormarkmark.charactermark.numericmark.tensormean.tensormul.tensornames.tensornames<-.tensornormnorm.tensorone.tensoropnormopnorm.tensorpos.tensorpower.tensorrenamefirst.tensorreorder.tensorrep.tensorriemann.tensorslice.tensorsolve.tensorsvd.tensorto.matrix.tensorto.tensorto.tensor.defaulttoPos.tensortrace.tensortripledelta.tensorundrop.tensoruntensorvar.tensor
Dependencies: