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vignettes/tensorprod.Rmd

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@@ -6,7 +6,7 @@ bibliography: stokes.bib
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link-citations: true
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vignette: >
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%\VignetteEngine{knitr::rmarkdown}
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%\VignetteIndexEntry{spraycross}
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%\VignetteIndexEntry{tensorprod}
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%\usepackage[utf8]{inputenc}
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---
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@@ -24,7 +24,7 @@ registerS3method(
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```
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```{r out.width='20%', out.extra='style="float:right; padding:10px"',echo=FALSE}
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knitr::include_graphics(system.file("help/figures/spray.png", package = "spray"))
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knitr::include_graphics(system.file("help/figures/stokes.png", package = "stokes"))
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```
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```{r, label=showAlt,comment=""}
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[where $\phi_i(v_j)=\delta_{ij}$,$v_1,\ldots,v_k$ being a basis for
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$V$] is a basis for $\mathcal{J}^k(V)$, which therefore has dimension
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$n^k$. Function `spraycross2()` evaluates the tensor product and I
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$n^k$. Function `tensorprod()` evaluates the tensor product and I
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give examples here.
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```{r}
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Thus $a=4\phi_1\otimes\phi_1+3\phi_1\otimes\phi_2$ and
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$b=7\phi_3\otimes\phi_5+8\phi_4\otimes\phi_4+9\phi_7\otimes\phi_3$.
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Now the cross product $a\otimes b$ is given by `spraycross()`:
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Now the cross product $a\otimes b$ is given by `tensorprod()`:
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```{r}
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tensorprod(a,b)

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