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skymap__define.pro
This class creates a smoothed sky map from an irregularly spaced set of measurements. The default smoothing kernel is a gaussian. The class also implements sigma clipping.
The smoothed map is evaluated according to m(x,y) = sum( w_i v_i) / sum(w_i)
where v_i is the ith sampled data point and w_i is a smoothing function. In this class, w_i is a gaussian centered on v_i, with a fwhm specified by the user.
The variance map is given by v(x,y) = sum(w_i^2 dv_i^2) / sum(w_i)^2
where dv_i^2 is the variance on measurement i
METHODS: weight: Implementation of the weighting kernel. getMap: return the smoothed map getIncluded: return a 1/0 bit vectors, listing which data points were included/clipped. writeFits: output the map to a fits file makeMap: calculate the smoothed map makeMapClip: Iteratively calculate map with sigma clipping init: Create the object cleanup: Destroy the object
SUPERCLASSES: none
SUBCLASSES: nicest: Overloads the weight method to implement Marco Lombardi's NICEST algorithm.
Class description for skymap
Subclasses: nicest
Routines
result = skymap::weight(id, x, y)This function evaluates the gaussian smoothing kernel applied on source "id" at location (x,y)
result = skymap::getMap( [variance=variance])This function returns the map structure associated with the object.
result = skymap::getIncluded()This function returns a 1/0 bit vector, listing whether each data point was included/clipped when calculating the smoothed map.
skymap::writeFits, name, varname=varnameOutput the map data to a fits image
skymap::makeMapClip, clip [, lo=lo] [, hi=hi] [, tol=tol] [, max_reject=max_reject] [, maxiter=maxiter] [, miniter=miniter]This procedure iteratively computes the smooth map with sigma clipping.
skymap::makeMapThis main procedure to create the smoothed map
result = skymap::init(map, x, y, val, dval [, fwhm=fwhm] [, truncate=truncate] [, verbose=verbose])Initializes the object
skymap__cleanupskymap__define
Routine details
topskymap::weight
result = skymap::weight(id, x, y)
This function evaluates the gaussian smoothing kernel applied on source "id" at location (x,y)
Return value
w_id(x,y)
Parameters
- id in required
The index of the source to consider. scalar
- x in required
The x location in sky coordinates, scalar or array
- y in required
The y location in sky coordinates, scalar or array
Author information
- History:
December 2010: Written by Chris Beaumont Aug 2011: Added support for euclidian (non-sky) maps. cnb.
topskymap::getMap
result = skymap::getMap( [variance=variance])
This function returns the map structure associated with the object.
Keywords
- variance in optional
Set to hold the variance map
topskymap::getIncluded
result = skymap::getIncluded()
This function returns a 1/0 bit vector, listing whether each data point was included/clipped when calculating the smoothed map.
topskymap::writeFits
skymap::writeFits, name, varname=varname
Output the map data to a fits image
Parameters
- name in required
The file name to write to
Keywords
- varname
topskymap::makeMapClip
skymap::makeMapClip, clip [, lo=lo] [, hi=hi] [, tol=tol] [, max_reject=max_reject] [, maxiter=maxiter] [, miniter=miniter]
This procedure iteratively computes the smooth map with sigma clipping.
DESCRIPTION: makeMap is iteratively called and, at each iteration, each data point v_i is compared to the map value map(x_i, y_i). If the two values disagree by more than CLIP * sigma_map(x_i, y_i), the point is rejected. The map is recalculated with valid points until convergence.
Parameters
- clip in required
The outlier threshhold (see above). 3 is typical
Keywords
- lo in optional
set to flag only the lo-valued outliers.
- hi in optional
set to flag only the hi-valued outliers.
- tol in optional
Specifiy a convergence tolerance. The clipping has converged when fewer than TOL * n_object objects change their inlier/outlier classification. Defaults to .01
- max_reject in optional
Set to the max fraction of objects that can be flagged as outliers before failure. Defaults to .2
- maxiter in optional
The maximum number of clipping iterations before failure. Defaults to 5.
- miniter in optional
The minimum number of clipping iterations. Default is 2.
topskymap::makeMap
skymap::makeMap
This main procedure to create the smoothed map
This function uses weighted mean smoothing with a Gaussian smoothing kernel.
V(x,y) = sum(w_i * val_i) / sum(w_i) where w_i = 1/dval_i^2 * exp[-((x-x_i)^2 + (y-y_i)^2) / 2 sigma^2] w_i truncated to 0 at (x - x_i)^2 + (y - y_i)^2 > truncate^2
The variance map is given by dV(x,y) = sum(w_i * dval_i^2) / sum(w_i)^2 In other words, it is the interpolated value of the variance, divided by the "effective" number of points which contribute to each pixel.
The procedure only calculates weights out to the truncation radius to speed things up. The procedure takes O(stamp_size * n_data) operations, instead of O(map_size * n_data). ;-
topskymap::init
result = skymap::init(map, x, y, val, dval [, fwhm=fwhm] [, truncate=truncate] [, verbose=verbose])
Initializes the object
Parameters
- map in required
A map structure created by map_init.pro
- x in required
The x coordinates of the data
- y in required
The y coordinates of the data
- val in required
Value of the data
- dval in required
1-sigma errors on the data
Keywords
- fwhm in optional
The fwhm of the smoothing kernel, in degrees. Defaults to 1/100 of the map size
- truncate in optional
The radius at which to truncate the smoothing. This can considerably speed up execution time. See makeMap for details.
- verbose in optional
Set to request extra textual output
topskymap__cleanup
skymap__cleanup
topskymap__define
skymap__define
File attributes
| Modifcation date: | Fri Jun 15 10:31:02 2012 |
| Lines: | 429 |