---
title: "multivariate template coordinates example for eigenanatomy"
author: "Brian B. Avants"
date: "`r Sys.Date()`"
bibliography: REFERENCES.bib
output: rmarkdown::html_vignette
vignette: >
    %\VignetteEngine{knitr::rmarkdown}
    %\VignetteIndexEntry{multivariate template coordinates example for eigenanatomy}
    %\VignetteEncoding{UTF-8}
    \usepackage[utf8]{inputenc}
---

How to make a table and plot coordinates of a multivariate (soft) region of interest as produced
by methods such as eigenanatomy.


First, load in a custom template paired with the output of a multivariate sparse decomposition or (alternatively) could be just a statistical map with zeroes in non-interesting areas.

```{r,eval=FALSE}
library( ANTsR )
tem<-antsImageRead( getANTsRData("ch2") )
temlab2<-antsImageRead( getANTsRData("ch2a")  )
temporalLobeRegions = thresholdImage( temlab2, 80, 90  ) %>%
  smoothImage( 3 )
otherRegions = thresholdImage( temlab2, 20, 25  ) %>%
  smoothImage( 1.5 )
```

This is the custom template and soft ROI pair.

```{r,message=FALSE,warning=FALSE,eval=FALSE}
mytem<-list( tem, temporalLobeRegions, otherRegions )
plot( tem, temporalLobeRegions,
      window.overlay=c(0.1, max( temporalLobeRegions ) ) )
plot( tem, otherRegions, axis=3,
      window.overlay=c(0.1, max( otherRegions ) ) )
plot( tem, otherRegions, axis=1,
      window.overlay=c(0.1, max( otherRegions ) ) )
```

Gather the canonical template ( e.g. MNI space ).

```{r,eval=FALSE}
mymni<-list( antsImageRead(getANTsRData("mni") ),
            antsImageRead(getANTsRData("mnib") ),
            antsImageRead(getANTsRData("mnia") ) )
```


Map to the canonical template.

```{r,eval=FALSE}
mynetworkdescriptor<-getMultivariateTemplateCoordinates(
 mytem, mymni , convertToTal = TRUE , pvals=c(0.01,0.05) )
```

Now look at the results in table form.  This tells us where the (center of) the data is located in anatomical space and associates the known p-values with it.  This is simulated data, so we already
know the answers to this and these correspond to what we find here.

```{r,results='asis',eval=FALSE}
knitr::kable( mynetworkdescriptor$networks )
```

Enjoy.