[ Basic Info | User Guide ]
Basic Information on impol
Purpose: Compute polarized intensity and position angle from Q and U
Categories: image analysis
IMPOL computes the total linearly polarized intensity
(optionally debiasing it) and position angle images from
Stokes Q and U images. Position angle is positive N -> E.
Up to three values; the Q, U and I images, respectively.
The I image is only needed if you want to compute the fractional
polarization image as well or if you want to blank the output
based upon an I S/N ratio. Wild card expansion is supported.
Up to two values; the output polarized intensity image and
optionally, its associated error image (which will be constant).
Default is no output images.
Up to two values; the output fractional polarization image and
optionally, its associated error image. You need to input an I
image to keyword in for this.
Up to two values; the output position angle image and
optionally, its associated error image (which will not be
constant). These will be in degrees (but see OPTIONS=RADIANS),
Default is no output images.
Up to two values; the mean standard deviation of the noise in
the Q & U images (i.e. one number for them both), and the
standard deviation of the I image.
These are required for debiasing (Q,U only), or for generating
output error images, or for blanking the output. Try to make
the Q,U value as accurate as possible for the debiasing.
Perhaps measure it from a V image
No default for sigma_QU, sigma_I defaults to sigma_QU
Up to 2 values. The first is the S/N ratio, P/SIGMA_QU, below
which the output images are blanked (see also options=zero
below). It is generally recommended that an SNCUT of at least 2
is used. The second value, which is only valid when you have
input an I image and sigma, is the S/N ratio, I/SIGMA_I, below
which output images are blanked (defaults to no I based
blanking) The default is 2.0 and 0.0.
The output images are blanked if the error in the position
angle image (degrees or radians depending on OPTIONS) is greater
than this value. This is active even if you don't output
the PA image. Note that there is no equivalent for the output
error of the POLI image because the error is constant and
equal to SIGMA. Keyword SNCUT essentially takes care of this.
The default is no position angle error based blanking.
After computing the position angle image, rotate the position
angles back to zero wavelength by an amount specified by
RM (rad/m**2). Better to use IMRM to generate the rotation
measure and zero wavelength position angle images.
Default is 0.0
Task enrichment options. Minimum match is active.
"bias" If computing polarized intensity, do NOT remove the
Ricean bias in the image. By default, the bias is
removed to first order with P = sqrt(P_obs**2 -
sigma**2). You should have a very good reason for
using this option (e.g. a detection experiment). See
VLA memo no. 161 by Patrick Leahy for more details of
"zero" When the output pixel is clipped because the
debiasing fails (P**2 may become negative), setting
OPTIONS=ZERO will cause the output polarized
intensity image (not the position angle image) pixel
to be set to 0.0 rather than being masked out. This
is very important if you are interested in doing
statistics on a region of low polarized intensity S/N
ratio. If you leave the region masked rather than
zeroed, you will bias the statistics in that region -
zero is a better estimate of the pixel than just
excluding it from the statistics (provided the clip
level is sufficiently small). Residual bias in the
statistical results from the area then depend upon
how well the bias remover works and at what level
clipping was performed. See VLA memo no. 161 by
"radians" Output the position angle image in radians instead
"relax" Only warn about image axis descriptor mismatches
instead of giving a fatal error
PGPLOT device on which to draw a plot showing the effect of bias
in polarized intensity images. It plots true polarized
intensity versus the bias, which is the estimated polarized
intensity minus the true polarized intensity. Three estimators
are shown; observed, first order, and maximum likelhood. It is
assumed that sigma_P = 1 in these plots. Because these plots
are drawn following a Monte Carlo simulation of some 15,000
trials of the noise, you will need to be patient. You can just
make this bias plot without actually working on any data if you
wish. See also VLA memo no. 161 by Patrick Leahy.
Default is no plot.
Revision: 1.20, 2011/11/03 04:42:13 UTC
Generated by firstname.lastname@example.org on 21 Jun 2016