read_ds9_contours

Context: contrib

Synopsis

Read in the contours from a ds9 *.con file with optional coordinate conversion.

Syntax

(xs, ys) = read_ds9_contours(filename [, coords=None, fromsys=None,
tosys=None])

This routine reads in the contours from a DS9 *.con file and returns the x and y coordinates of each component as a separate numpy array. If the coords, fromsys and tosys arguments are given then they are used to convert the values to a different coordinate system (e.g. if the values were written out in WCS but you wish to use the sky system).

Loading the routine

The routine can be loaded into a ChIPS or Sherpa session by saying:

from crates_contrib.utils import *

Coordinate conversion

To convert the coordinate values form the file then coords should be either the name of an image file or a crate containing an image and the fromsys and tosys arguments determine what systems to use:

The fromsys and tosys arguments

Value	Description
"world" or "eqpos"	The WCS coordinate systems supported by CIAO
"physical" or "sky"	The physical coordinate system
"logical" or "image"	The logical coordinate system

Example 1

(xs, ys) = read_ds9_contours("ds9.con")
add_image("image.fits")
for i in range(0, len(xs))
    add_line(xs[i], ys[i], ["color", "green"])

Here we read in the contours stored in the file ds9.con and then add them onto a ChIPS image as green lines. See the add_ds9_contours() routine from chips_contrib.utils for a way to automate this.

Example 2

chips> (xs, ys) = read_ds9_contours("ds9.con", "img.fits", "world",
"sky")

Here the contour coordinates are read in and then converted from WCS to SKY coordinates using the coordinate axes in the image file img.fits.