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.help response Aug86 noao.twodspec.longslit
.ih
NAME
response -- Determine response calibrations
.ih
USAGE
response calibration normalization response
.ih
PARAMETERS
.ls calibration
Images to use in determining response calibrations. These are
generally quartz continuum spectra. An image section may be used to select
only a portion of the image.
.le
.ls normalization
Images to use determining the normalization spectrum. In almost all cases
the normalization images are the same as the calibration images or a
subsection of the calibration images.
.le
.ls responses
Response calibration images to be created. Each response image is paired
with a calibration image. If the image exists then it will be modified
otherwise it is created.
.le
.ls interactive = yes
Graph the average calibration spectrum and fit the normalization spectrum
interactively?
.le
.ls threshold = INDEF
Set the response to 1 when the normalization spectrum or input image data
fall below this value. If INDEF then no threshold is applied.
.le
.ls sample = "*"
Sample of points to use in fitting the average calibration spectrum.
The sample is selected with a range string.
.le
.ls naverage = 1
Number of sample points to average or median before fitting the function.
If the number is positive the average of each set of naverage sample
points is formed while if the number is negative then the median of each set
of points (in absolute value) is formed. This subsample of points is
used in fitting the normalization spectrum.
.le
.ls function = "spline3"
Function to fit to the average image spectrum to form the normalization
spectrum. The options are "spline1", "spline3", "legendre", and "chebyshev".
.le
.ls order = 1
Order of the fitting function or the number of spline pieces.
.le
.ls low_reject = 0., high_reject = 0.
Rejection limits below and above the fit in units of the residual sigma.
.le
.ls niterate = 1
Number of rejection iterations.
.le
.ls grow = 0
Reject additional points within this distance of points exceeding the
rejection threshold.
.le
.ih
CURSOR KEYS
The interactive curve fitting package \fBicfit\fR is used to fit a function
to the average calibration spectrum. Help for this package is found
under the name "icfit".
.ih
DESCRIPTION
A response calibration, in the form of an image, is created for each input
image, normally a quartz spectrum. The response calibration is formed by
dividing the calibration image by a normalization spectrum which is the
same at all points along the spatial axis. The normalization spectrum is
obtained by averaging the normalization image across the dispersion to form
a one dimensional spectrum and smoothing the spectrum by fitting a
function. The threshold value does not apply to creating or fitting of
the normalization spectrum but only the final creation of the response
values. When normalizing (that is dividing the data values by the
fit to the normalization spectrum) only pixels in which both the fitted
normalization value and the data value are above the threshold are
computed. If either the normalization value or the data value is below
the threshold the output response value is one.
The image header keyword DISPAXIS must be present with a value of 1 for
dispersion parallel to the lines (varying with the column coordinate) or 2
for dispersion parallel to the columns (varying with line coordinate).
This parameter may be added using \fBhedit\fR. Note that if the image has
been transposed (\fBimtranspose\fR) the dispersion axis should still refer
to the original dispersion axis unless the physical world coordinate system
is first reset (see \fBwcsreset\fR). This is done in order to allow images
which have DISPAXIS defined prior to transposing to still work correctly
without requiring this keyword to be changed.
If the output image does not exist it is first created with unit response
everywhere. Subsequently the response is only modified in those regions
occupied by the input calibration image. Thus, image sections may be used
to select regions in which the response is desired. This ability is
particularly useful when dealing with multiple slits within an image or to
exclude regions outside the slit.
Normally the normalization images are the same as the calibration images.
In other words the calibration image is normalized by the average spectrum
of the calibration image itself. Sometimes, however, the normalization
image may be a smaller image section of the calibration image to avoid
contaminating the normalization spectrum by effects at the edge of the
slit. Again, this may be quite useful in multi-slit images.
The normalization spectrum is smoothed by fitting a function
using the interactive curve fitting package (\fBicfit\fR). The
parameters determining the fitted normalization spectrum are the sample
points, the averaging bin size, the fitting function, the order of the
function, the rejection sigmas, the number of rejection iterations, and
the rejection width. The sample points for the average spectrum are
selected by a range string. Points in the normalization spectrum not in the
sample are not used in determining the fitted function. The selected
sample points may be binned into a set of averages or medians which are
used in the function fit instead of the sample points with the
averaging bin size parameter \fInaverage\fR. This parameter selects
the number of sample points to be averaged if its value is positive or
the number of points to be medianed if its value is negative
(naturally, the absolute value is used for the number of points). A
value of one uses all sample points without binning. The fitted
function may be used to reject points from the fit using the parameters
\fIlow_reject, high_reject, niterate\fR and \fIgrow\fR. If one or both
of the rejection limits are greater than zero then the sigma of the
residuals is computed and points with residuals less than
\fI-low_reject\fR times the sigma and greater than \fIhigh_reject\fR
times the sigma are removed and the function fitted again. In addition
points within a distance given by the parameter \fIgrow\fR of the a
rejected point are also rejected. A value of zero for this parameter
rejects only the points exceeding the rejection threshold. Finally,
the rejection procedure may be iterated the number of times given by
the parameter \fIniterate\fR.
The fitted function may be examined and modified interactively when the
parameter \fIinteractive\fR is set. In this case the normalization spectrum
and the fitted function or the residuals of the fit are graphed.
Deleted points are marked with an x and rejected points by a diamond.
The sample regions are indicated along the bottom of the graph.
The cursor keys and colon commands are used to change the values
of the fitting parameters, delete points, and window and expand the
graph. When the fitted function is satisfactory exit with a carriage
return or 'q' and the calibration image will be created. Changes in
the fitted parameters are remembered from image to image within the
task but not outside the task.
When the task finishes creating a response image the fitting parameters
are updated in the parameter file.
.ih
EXAMPLES
1. To create a response image non-interactively:
cl> response quartz quartz response order=20 interactive=no
2. To determine independent responses for a multislit image determine the
image sections defining each slit. Then the responses are computed as
follows:
.nf
cl> response quartz[10:20,*],quartz[35:45,*] \
>>> quartz[12:18,*],quartz[12:18,*] resp,resp
.fi
Generally the slit image sections are prepared in a file which is then
used to define the lists of input images and response.
.nf
cl> response @slits @slits @responses
.fi
3. If the DISPAXIS keyword is missing and the dispersion is running
vertically (varying with the image lines):
.nf
cl> hedit *.imh dispaxis 2 add+
.fi
.ih
SEE ALSO
icfit, iillumination
.endhelp
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