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1.1.1 Separate a complex image into individual components
Description
This function is an image decomposition tool that performs several tasks, with
the end result being that a strongly blended image is separated into
components - both in the sense that it determines the parameters for each
component (assuming a Gaussian model) and that it physically assigns each
pixel in the image to an individual object. The products of these two
operations are called the component list and the component map, respectively.
The fitting process (which determines the component list) and the
pixel-decomposition process (which determines the component map) are
designed to work cooperatively to increase the efficiency and accuracy of both.
The algorithm behind the decomposition is based on the function clfind, described in Williams et al 1994, which uses a contouring procedure whereby a closed contour designates a separate component. The program first separates the image into clearly distint ’regions’ of blended emission, then contours each region to determine the areas constituting each component and passes this information on to the fitter, which determines the component list.
The contour deblending can optionally be replaced with a simpler local maximum scan, and the fitting can be replaced with a moment-based estimation method to speed up calculations on very large images or if either primary method causes trouble, but in general this will impede the accuracy of the fit.
The function works with both two and three dimensional images.
Arguments
| Inputs |
| ||
| region |
| Region of interest. Default is unset.
| |
| allowed: | any |
|
| Default: | record |
|
| mask |
| Boolean LEL expression or mask region. Default is
unset.
| |
| allowed: | any |
|
| Default: | variant |
|
| simple |
| Skip contour deblending and scan for local maxima
| |
| allowed: | bool |
|
| Default: | false |
|
| threshold |
| Value of minimum positive contour. Default is unset.
| |
| allowed: | double |
|
| Default: | -1 |
|
| ncontour |
| Number of contours to use in deblending (¿= 2)
| |
| allowed: | int |
|
| Default: | 11 |
|
| minrange |
| Minimum number of closed contours in a component (¿
0)
| |
| allowed: | int |
|
| Default: | 1 |
|
| naxis |
| Max number of perpendicular steps between contiguous
pixels. Values of 1, 2 or 3 are allowed.
| |
| allowed: | int |
|
| Default: | 2 |
|
| fit |
| Fit to the components after deblending?
| |
| allowed: | bool |
|
| Default: | true |
|
| maxrms |
| Maximum RMS of fit residuals to not retry fit (¿ 0).
Default is unset.
| |
| allowed: | double |
|
| Default: | -1 |
|
| maxretry |
| Maximum number of times to retry the fit (¿= 0).
Default is unset.
| |
| allowed: | int |
|
| Default: | -1 |
|
| maxiter |
| Maximum number of iterations allowed in a single fit (¿
0)
| |
| allowed: | int |
|
| Default: | 256 |
|
| convcriteria |
| Criterion to establish convergence (¿=0)
| |
| allowed: | double |
|
| Default: | 0.0001 |
|
Example
"""
# print "\t----\t decompose Ex 1 \t----" ia.maketestimage() print ia.decompose(threshold=2.5, maxrms=1.0) #Attempt 1: Converged after 22 iterations #Attempt 1: Converged after 16 iterations #1: Peak: 17.955 Mu: [0.000327928, 8.62573e-05] # Axes: [0.00175981, 0.00142841] Rotation: 1.29539 #2: Peak: 19.8093 Mu: [1.67927e-06, -0.000374393] # Axes: [0.00179054, 0.00132541] Rotation: 1.78404 #3: Peak: 10.1155 Mu: [6.28252, -7.09688e-05] # Axes: [0.00180877, 0.00104523] Rotation: 1.78847 #[[ 1.79549522e+01 3.27928370e-04 8.62573434e-05 1.75980886e-03 # 8.11686337e-01 1.29538655e+00] # [ 1.98093319e+01 1.67927124e-06 -3.74393392e-04 1.79054437e-03 # 7.40229547e-01 1.78403902e+00] # [ 1.01155214e+01 6.28252172e+00 -7.09688029e-05 1.80877140e-03 # 5.77867746e-01 1.78847444e+00]] ia.close() # """ |
Please send any comments or questions about CASA or AIPS++ to aips2-requests@nrao.edu
Copyright © 2007 Associated Universities Inc., Washington, D.C.
This code is available under the terms of the GNU General Public Lincense
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