---
name: "ann2fig"
section: "1"
platform: "linux"
package: "ann-tools"
version: "1.1.2+doc-9+b1"
release: "Debian 13 (Trixie)"
platforms: ["linux"]
url: "https://new.carta.tech/ann2fig"
---

# ann2fig(1)

Dump ANN tree structure in Fig format

## NAME

ann2fig - Dump ANN tree structure in Fig format

## SYNOPSIS

```
    ann2fig [-upi scale] [-x low_x] [-y low_y]
        [-sz size] [-dx dim_x] [-dy dim_y] [-sl dim value]*
        [-ps pointsize] file
```

## DESCRIPTION

This program inputs an ann dump file of a search structure perhaps along with point coordinates, and outputs a fig (Ver 3.1) file (see fig2dev (1)) displaying the tree.  The fig file may then be displayed using xfig, or converted to any of a number of other formats using fig2dev.

If the dimension is 2 then the entire tree is displayed.  If the dimension is larger than 2 then the user has the option of selecting which two dimensions will be displayed, and the slice value for each of the remaining dimensions.  All leaf cells intersecting the slice are shown along with the points in these cells.

## OPTIONS

- \-upi scale

  fig units per inch (default = 1200)

- \-x low\_x -y low\_y

  x and y offset of upper left corner (inches) (default = 1)

- \-sz size

  maximum side length of figure (in inches) (default = 5)

- \-dx dim\_x

  horizontal dimension (default = 0)

- \-dy dim\_y

  vertical dimension (default = 1)

- \-sv value

  default slice value (default = 0)

- \-sl dim value

  each such pair defines the value along the given dimension at which to slice.  This may be supplied for all dimensions except dim\_x and dim\_y.

- \-ps pointsize

  size of points in fig units (def = 10)

- file

  file (input=file.dmp, output=file.fig)

## AUTHOR

David Mount

## COPYRIGHT

This man page is Copyright (C) 2007 Rafael Laboissiere \<rafael AT debian DOT org\> and released under the GNU GPL, version 3 or later.  It was written for the Debian distribution but may be used by others.

## SEE ALSO

[**fig2dev**(1)](/fig2dev/1.md) [**ann\_sample**(1)](/ann_sample/1.md)