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imagepol - Constructor

	Package	general
	Module	images
	Tool	imagepol

Create an Imagepol tool from an AIPS++ image file

Synopsis
imagepol(infile)

Arguments

infile	in	Input image (file name or tool)
		Allowed:	String or Image tool

Returns
Imagepol tool or fail

Description

The constructor takes an image as its input. This can be specified as either the name of a disk file, or you can give a pre-existing Image tool. If you give a disk file name, the disk image file may be in AIPS++, FITS or Miriad format.

The input image must have a Stokes axis. The exact collection of Stokes that the image has, determines what the Imagepol tool can compute. Stokes I, Q, U, and V refer to total intensity, two components of linear polarization, and circular polatization, respectively. Therefore, if you ask for linear polarization and the image only has Stokes I and V, you will get an error.

The input image may contain data at many frequencies. For example, the image may be a 4D image with axes RA, DEC, Stokes and Frequency (order not important) where the Frequency axis is regularly sampled. However, the image may also contain many frequencies at irregular intervals. Such an image may be created with the Image tool constructor called imageconcat. It enables you to concatenate images along an axis, and it allows irregular coordinate values along that axis.

Example

- im := image('$AD/myimage')
- p1 := imagepol(im)
- p2 := imagepol('$AD/myimage')

We create two Imagepol tools, one from an Image tool and one directly from the disk file.

Example

- im := imageconcat(infiles="im.f1 im.f2 im.f3 im.f4 im.f5", axis=4)
- p := imagepol(im)
- p.rotationmeasure(rm='rm', rmerr='rmerr', rmmax=500, maxpaerr=10)

Say we have 5 images, each with axes RA, DEC, Stokes, and Frequency in that order. We make an Image tool which concatenates these images along the frequency axis - you have ordered them in increasing or decreasing frequency order. Note that the Image tool is virtual - it is not written to an output file. This just means that the data are read from the input images as needed. The Imagepol tool is then made from this virtual Image tool. We then compute the Rotation Measure and Rotation Measure error images with the traditional method and write them out to disk.