findpars -- edit the star detection parameters
- threshold = 4.(sigma)
- The object detection threshold above local background in units of datapars.sigma .
- nsigma = 1.5
- The semi-major axis of the Gaussian convolution kernel used to computed the density enhancement and mean density images in Gaussian sigma. This semi- major axis is equal to min (2.0, 0.42466 * nsigma * datapars.fwhmpsf / datapars.scale ) pixels.
- ratio = 1.0
- The ratio of the sigma of the Gaussian convolution kernel along the minor axis direction to the sigma along the major axis direction. Ratio defaults to 1.0 in which case the image is convolved with a circular Gaussian.
- theta = 0.0
- The position angle of the major axis of the Gaussian convolution kernel. Theta is measured in degrees counter-clockwise from the x axis.
- sharplo = .2, sharphi = 1.0
- Sharplo and sharphi are numerical cutoffs on the image sharpness statistic designed to eliminate brightness maxima which are due to bad pixels rather than to astronomical objects.
- roundlo = -1.roundhi = 1.0
- Roundlo and roundhi are numerical cutoffs on the image roundness statistic designed to eliminate brightness maxima which are due to bad rows or columns, rather than to astronomical objects.
- mkdetections = no
- Mark the positions of the detected objects on the displayed image ?
DAOFIND approximates the stellar point spread function with an elliptical Gaussian function, whose sigma along the semi-major axis is 0.42466 * datapars.fwhmpsf / datapars.scale pixels, semi-minor to semi-major axis ratio is ratio , and major axis position angle is theta . Using this model, a convolution kernel, truncated at nsigma sigma, and normalized to sum to zero, is constructed.
The density enhancement image starmap is computed by convolving the input image with the Gaussian kernel. This operation is mathematically equivalent to fitting, in the least-squares sense, the image data at each point with a truncated, lowered elliptical Gaussian function. After convolution each point in starmap contains as estimate of the amplitude of the best fitting Gaussian function at that point. Each point in skymap , if the user chooses to compute it, contains an estimate of the best fitting sky value at that point.
After image convolution DAOFIND steps through starmap searching for density enhancements greater than findpars.threshold * datapars.sigma , and brighter than all other density enhancements within a semi-major axis of 0.42466 findpars.nsigma * datapars.fwhmpsf . As the program selects candidates, it computes two shape characteristics sharpness and roundness. The sharpness statistic measures the ratio of the difference between the height of the central pixel and the mean of the surrounding non-bad pixels, to the height of the best fitting Gaussian function at that point. The roundness statistics measures the ratio of, the difference in the height of the best fitting Gaussian function in x minus the best fitting Gaussian function in y, over the average of the best fitting Gaussian functions in x and y. The limits on these parameters findpars.sharplo , findpars.sharphi , findpars.roundlo , and findpars.roundhi , are set to weed out non-astronomical objects and brightness enhancements that are elongated in x and y respectively.
Lastly the x and y centroids of the detected objects are computed by estimating the x and y positions of the best fitting 1D Gaussian functions in x and y respectively, a rough magnitude is estimated by computing the ratio of the amplitude of the best fitting Gaussian at the object position to findpars.threshold * datapars.sigma , and the object is added to the output coordinate file.
1. List the object detection parameters.
da> lpar findpars
2. Edit the object detection parameters.
3. Edit the FINDPARS parameters from within the DAOFIND task.
da> epar daofind ... edit a few daofind parameters ... move to the findpars parameter and type :e ... edit the findpars parameter and type :wq ... finish editing the daofind parameters and type :wq
4. Save the current FINDPARS parameter set in a text file fndnite1.par. This can also be done from inside a higher level task as in the previous example.
da> findpars ... edit the parameters ... type ":w fndnite1.par" from within epar